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} | 6 | "2021-09-11T22:38:44Z" | "2021-09-14T15:30:28Z" | "2021-09-12T15:15:11Z" | NONE | null | ###
- [X] I have checked that the issue still exists on the latest versions of the docs on `master` [here](https://pandas.pydata.org/docs/dev/)
### Location of the documentation
https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.fillna.html
### Documentation problem
Typo in one of the examples for `fillna()`. Specifically, the last example with `df2 = pd.DataFrame(np.zeros((4, 4)), columns=list("ABCE"))` where the last column should be `E` but is instead `D` in the printout.
### Suggested fix for documentation
Either fix to `df2 = pd.DataFrame(np.zeros((4, 4)), columns=list("ABCD"))` or fix the printout. | {
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} | 1 | "2021-09-11T22:41:07Z" | "2021-09-12T15:11:15Z" | "2021-09-12T15:06:28Z" | MEMBER | null | - [x] closes #23089
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
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} | 0 | "2021-09-11T23:06:05Z" | "2021-09-12T15:00:17Z" | "2021-09-12T14:59:07Z" | MEMBER | null | ```
from asv_bench.benchmarks.groupby import *
self = Apply()
self.setup(4)
%timeit self.time_copy_function_multi_col(4)
451 ms ± 6.17 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) # <- PR
492 ms ± 8.97 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) # <- master
``` | {
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
Discussed on this week's call. | {
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} | 1 | "2021-09-12T03:36:05Z" | "2021-09-12T19:19:15Z" | "2021-09-12T19:11:14Z" | MEMBER | null | - [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
This now follows the structure of other `SparseArray` reductions like `sum` more closely, though there is some added complexity here to avoid taking the `min/max` of an empty array, which would raise when we want to return the corresponding missing value instead.
Benchmarks:
```
before after ratio
[5deec13d] [f3eea313]
<master> <perf_sparse_min_max>
- 4.05±0.3ms 11.6±0.3μs 0.00 sparse.MinMax.time_min_max('max', 0.0)
- 4.49±0.4ms 11.6±0.2μs 0.00 sparse.MinMax.time_min_max('min', 0.0)
- 4.62±0.7ms 10.6±0.2μs 0.00 sparse.MinMax.time_min_max('max', nan)
- 5.37±0.7ms 10.3±0.3μs 0.00 sparse.MinMax.time_min_max('min', nan)
``` | {
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] | open | false | null | [] | null | 5 | "2021-09-12T05:47:11Z" | "2021-09-30T23:43:24Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
import io
df = pd.read_csv(io.StringIO('A\nB\nC'), sep='\n', header=None, names=range(3))
```
### Issue Description
`pd.read_csv()` incorrectly parses data in case `'\n'` is used as a separator.
```python
df = pd.read_csv(io.StringIO('A\nB\nC'), sep='\n', header=None, names=range(3))
```
produces:
```
0 1 2
0 A NaN NaN
1 B NaN NaN
2 C NaN NaN
```
### Expected Behavior
Expected:
```
0 1 2
0 A B C
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 5f648bf1706dd75a9ca0d29f26eadfbb595fe52b
python : 3.8.10.final.0
python-bits : 64
OS : Darwin
OS-release : 20.6.0
Version : Darwin Kernel Version 20.6.0: Wed Jun 23 00:26:31 PDT 2021; root:xnu-7195.141.2~5/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 1.3.2
numpy : 1.19.2
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : 0.29.24
pytest : 6.2.5
hypothesis : None
sphinx : 4.1.2
blosc : None
feather : None
xlsxwriter : 3.0.1
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : 2.9.1 (dt dec pq3 ext lo64)
jinja2 : 3.0.1
IPython : 7.27.0
pandas_datareader: None
bs4 : 4.10.0
bottleneck : 1.3.2
fsspec : 2021.08.1
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.8
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.2
sqlalchemy : 1.4.23
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.54.0
</details>
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} | 0 | "2021-09-12T11:00:41Z" | "2021-09-12T15:15:12Z" | "2021-09-12T15:15:11Z" | CONTRIBUTOR | null | - [x] closes #43522
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them | {
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} | 15 | "2021-09-12T13:51:26Z" | "2021-11-06T19:28:17Z" | "2021-10-18T11:00:43Z" | MEMBER | null | Tracking issue for the 1.3.4 release.
Currently scheduled for October 17, 2021. (could release earlier if there are issues with the pandas 1.3.3 py3.10 wheels once Python 3.10.0 final is released xref https://github.com/pandas-dev/pandas/issues/41940#issuecomment-917375309)
https://github.com/pandas-dev/pandas/milestone/90
List of open regressions: https://github.com/pandas-dev/pandas/issues?q=is%3Aopen+is%3Aissue+label%3ARegression
performance regressions between 1.2.5 and 1.3.x https://simonjayhawkins.github.io/fantastic-dollop/#regressions?sort=3&dir=desc&branch=1.3.x (significant ones have now been addressed)
cc @pandas-dev/pandas-core @pandas-dev/pandas-triage | {
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- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
run pytest
```
### Issue Description
pytest is failing with `unrecognized arguments: --strict-data-files`
```console
+ /usr/bin/pytest -ra
ERROR: usage: pytest [options] [file_or_dir] [file_or_dir] [...]
pytest: error: unrecognized arguments: --strict-data-files
inifile: /home/tkloczko/rpmbuild/BUILD/pandas-1.3.3/pyproject.toml
rootdir: /home/tkloczko/rpmbuild/BUILD/pandas-1.3.3
```
### Expected Behavior
pytest should run test suite
### Installed Versions
N/A
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Please merge this one, it moves a private method to the base class script. | {
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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} | 7 | "2021-09-12T19:13:16Z" | "2021-09-21T21:37:42Z" | "2021-09-21T21:37:42Z" | CONTRIBUTOR | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
df = pd.DataFrame(data=[ "a"*127 ]*4000)
# Put two-byte utf-8 encoded character at the end of the chunk (the utf-8 encoding of "ą" is b'\xc4\x85')
df.iloc[2047] = "a"*127 + "ą"
df.to_csv("./bugtest.csv", index=False, header=False, encoding="utf-8")
df1 = pd.read_csv("./bugtest.csv", header=None, memory_map=True) # <-- this fails
Traceback (most recent call last):
File "/home/michal/.conda/envs/py39nlp/lib/python3.9/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 69, in __init__
self._reader = parsers.TextReader(self.handles.handle, **kwds)
File "pandas/_libs/parsers.pyx", line 542, in pandas._libs.parsers.TextReader.__cinit__
File "pandas/_libs/parsers.pyx", line 745, in pandas._libs.parsers.TextReader._get_header
File "pandas/_libs/parsers.pyx", line 843, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas/_libs/parsers.pyx", line 1917, in pandas._libs.parsers.raise_parser_error
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xc4 in position 262143: unexpected end of data
python-BaseException
```
### Issue Description
This bug occurs when the end of the internal 256KB buffer falls inside an utf-8 encoded multibyte character. When memory_map=True, the csv parser uses `_MMapWrapper.read()` method defined in [common.py (L872)](https://github.com/pandas-dev/pandas/blob/5f36af325c276454201495eaf66be55bd17964a5/pandas/io/common.py#L872):
```python
def read(self, size: int = -1) -> str | bytes:
# CSV c-engine uses read instead of iterating
content: bytes = self.mmap.read(size)
if self.decode:
# memory mapping is applied before compression. Encoding should
# be applied to the de-compressed data.
return content.decode(self.encoding, errors=self.errors)
return content
```
As this function is called with size=256KB, it is clear that `content` buffer can split a multibyte character. When it happens, the utf-8 codec raises "unexpected end of data" error.
The `_MMapWrapper.read()` method was added in [ REGR: memory_map with non-UTF8 encoding #40994 ](https://github.com/pandas-dev/pandas/pull/40994/commits/148881f63e84353458759bff45849ff36efae814), so the bug is present in Pandas 1.2.5 and newer versions.
### Expected Behavior
Doesn't raise exception, produces the same result as `pd.read_csv("./bugtest.csv", header=None, memory_map=False)`
### Installed Versions
<details>
pandas_datareader: None
bs4 : 4.9.3
bottleneck : None
fsspec : 2021.07.0
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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https://api.github.com/repos/pandas-dev/pandas/issues/43541 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43541/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43541/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43541/events | https://github.com/pandas-dev/pandas/issues/43541 | 994,288,385 | MDU6SXNzdWU5OTQyODgzODU= | 43,541 | BUG: `merge_asof` gives incorrect results when `by` consists of multiple categorical columns with equal, but differently ordered, categories | {
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] | open | false | null | [] | null | 1 | "2021-09-12T21:34:33Z" | "2021-09-30T23:44:00Z" | null | NONE | null | Observing that `merge_asof` gives unexpected output when:
- `by` includes more than one column, one of which is categorical
- categorical columns included in `by` have equal categories but with different order in left/right dataframes
It seems to me the issue is caused by the categorical columns being cast to their codes during the call to `flip` in `_get_join_indexers` when `by` includes more than one column, causing the misalignment. Categorical columns' dtypes are checked for equality, but the check only fails when they have different categories.
A minimal example of the issue can be set up as follows:
```python
df_left = pd.DataFrame({
"c1": ["a", "a", "b", "b"],
"c2": ["x"] * 4,
"t": [1] * 4,
"v": range(4)
}).sort_values("t")
df_right = pd.DataFrame({
"c1": ["b", "b"],
"c2": ["x"] * 2,
"t": [1, 2],
"v": range(2)
}).sort_values("t")
df_left_cat = df_left.copy().astype({"c1": pd.CategoricalDtype(["a", "b"])})
df_right_cat = df_right.copy().astype({"c1": pd.CategoricalDtype(["b", "a"])}) # order of categories is inverted on purpose
```
Performing `merge_asof` on dataframes where the `by` columns are of object dtype works as expected:
```python
pd.merge_asof(df_left, df_right, by=["c1", "c2"], on="t", direction="forward", suffixes=["_left", "_right"])
```
| c1 | c2 | t | v_left | v_right
-- | -- | -- | -- | -- | --
0 | a | x | 1 | 0 | NaN
1 | a | x | 1 | 1 | NaN
2 | b | x | 1 | 2 | 0.0
3 | b | x | 1 | 3 | 0.0
When using dataframes with categorical columns as defined above, however, the result is not the expected one:
```python
pd.merge_asof(df_left_cat, df_right_cat, by=["c1", "c2"], on="t", direction="forward", suffixes=["_left", "_right"])
```
| c1 | c2 | t | v_left | v_right
-- | -- | -- | -- | -- | --
0 | a | x | 1 | 0 | 0.0
1 | a | x | 1 | 1 | 0.0
2 | b | x | 1 | 2 | NaN
3 | b | x | 1 | 3 | NaN
I ran this with the latest version of pandas at the time of writing (1.3.3). Output of `pd.show_versions()`:
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.9.2.final.0
python-bits : 64
OS : Darwin
OS-release : 20.6.0
Version : Darwin Kernel Version 20.6.0: Wed Jun 23 00:26:27 PDT 2021; root:xnu-7195.141.2~5/RELEASE_ARM64_T8101
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 1.3.3
numpy : 1.21.1
pytz : 2021.1
dateutil : 2.8.2
pip : 21.0.1
setuptools : 52.0.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.27.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
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- [X] I have searched the [[pandas] tag](https://stackoverflow.com/questions/tagged/pandas) on StackOverflow for similar questions.
- [X] I have asked my usage related question on [StackOverflow](https://stackoverflow.com).
### Link to question on StackOverflow
AttributeError: Can't get attribute 'new_block' on <module 'pandas.core.internals.blocks' from '/usr/local/lib/python3.6/dist-packages/pandas/core/internals/blocks.py'>
### Question about pandas
Traceback (most recent call last):
[27] File "/ganling_ms/yiaijun/ConWea-master/train.py", line 325, in <module>
[28] main(dataset_path=args.dataset_path)
[29] File "/ganling_ms/yiaijun/ConWea-master/train.py", line 291, in main
[30] df = pickle.load(open(dataset_path+ 'df_contextualized.pkl', "rb"))
[31] AttributeError: Can't get attribute 'new_block' on <module 'pandas.core.internals.blocks' from '/usr/local/lib/python3.6/dist-packages/pandas/core/internals/blocks.py'> | {
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} | 2 | "2021-09-13T04:42:22Z" | "2021-09-14T15:21:12Z" | "2021-09-14T15:21:12Z" | CONTRIBUTOR | null | …lt.show, plt.savefig and Jupyter Notebook.
- [x] closes #43560
- [ ] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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} | 3 | "2021-09-13T04:48:40Z" | "2021-09-14T15:16:45Z" | "2021-09-14T12:58:51Z" | MEMBER | null | While looking into windows timeouts, noticed network tests were still being run with -m "not network". `tm.network` adds the keyword `network`, but does not add a mark, so -m "not network" was still running network tests. While a mark could probably be set somehow in that decorator, I couldn't find a `pytest` documented way to do that.
Instead, this pushes `pytest_runtest_setup` into `pytest_collection_modifyitems` (which I think is more intuitive since we know if a test should be skipped or not at collection time, and shouldn't need these skip checks at setup-time for each test).
The other reason for this change was that `pytest_runtest_setup` is too late in the pipeline to add the network marker. By moving the skip logic to `pytest_collection_modifyitems`, we can consolidate the skip checks with adding the corresponding marker if the "network" keyword is found.
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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] | open | false | null | [] | null | 1 | "2021-09-13T08:02:14Z" | "2021-10-03T19:50:13Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [x] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
df = pd.DataFrame({'idx': [0, 1, 0, 1],
'col': list('aabb'),
'ints': [10, 20, 30, 40],
'ints2': [11, 21, 31, 41],
'floats': [0.1, 0.2, 0.3, 0.4],
'strs': list('ABCD'),
'dts': pd.date_range('2021-01-01 10:00:00', '2021-01-04 10:00:00').to_series()})
df.pivot(index='idx', columns='col', values=['ints', 'floats'])
# ints floats
# col a b a b
# idx
# 0 10.0 30.0 0.1 0.3
# 1 20.0 40.0 0.2 0.4
df.pivot(index='idx', columns='col', values=['ints', 'ints2']).dtypes # -> all int
df.pivot(index='idx', columns='col', values=['ints', 'floats']).dtypes # -> all float
df.pivot(index='idx', columns='col', values=['ints', 'strs']).dtypes # -> all object
df.pivot(index='idx', columns='col', values=['ints', 'dts']).dtypes # -> object and datetime64
```
### Issue Description
When calling `DataFrame.pivot` with a list of column names as the `values` argument, numeric columns are cast to a common ancestor datatype of the selected columns. So depending on the dtypes of the columns selected in the `values` argument:
- If only int columns are selected, the dtype is maintained
- If at least a float column is selected, all int columns are cast to float.
- If at least an object or datetime column is selected, all numeric columns (int and floats) are cast to object
- datetime columns remain as datetime column even if some object column is selected
- Object columns remain as object dtype
### Expected Behavior
As far as I understand, the dtype of pivoted columns could be maintained. If there are missing values on the pivot table, int columns might be casted to floats to allow NaNs, but otherwise no dtype transformations should occur due to pivot.
Perhaps, the behaviour is expected as if one were to do `df.stack().unstack()`. In that case, perhaps it could be included in the notes section of the documentation.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : c7f7443c1bad8262358114d5e88cd9c8a308e8aa
python : 3.9.2.final.0
python-bits : 64
OS : Darwin
OS-release : 20.6.0
Version : Darwin Kernel Version 20.6.0: Wed Jun 23 00:26:31 PDT 2021; root:xnu-7195.141.2~5/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 1.3.1
numpy : 1.21.1
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.3
setuptools : 57.4.0
Cython : None
pytest : 6.2.4
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.9.1 (dt dec pq3 ext lo64)
jinja2 : 3.0.1
IPython : 7.26.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.2
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : None
tables : None
tabulate : 0.8.9
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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} | 0 | "2021-09-13T11:41:56Z" | "2021-09-14T12:43:33Z" | "2021-09-14T12:43:33Z" | CONTRIBUTOR | null | xref #43505
- [X] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [X] whatsnew entry
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} | 4 | "2021-09-13T12:25:55Z" | "2021-09-16T21:02:18Z" | "2021-09-16T21:02:18Z" | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this issue exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this issue exists on the master branch of pandas.
### Reproducible Example
from dateutil import tz
import pandas as pd
from time import time
dates = pd.date_range('2010-01-01', periods=1000, tz=tz.tzutc())
index = pd.MultiIndex.from_product([range(100), dates])
index2 = index.copy()
start_time = time()
index.equals(index2)
used_time = time() - start_time
print("Took", int(used_time*1000), "milliseconds")
### Installed Versions
<details>
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.9.6.final.0
python-bits : 64
OS : Darwin
OS-release : 20.5.0
Version : Darwin Kernel Version 20.5.0: Sat May 8 05:10:33 PDT 2021; root:xnu-7195.121.3~9/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 57.4.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
### Prior Performance
This issue did not exist in pandas 1.2.5. The timing measured by the script with pandas 1.2.5 on my computer is about 30 milliseconds, while the timing in pandas 1.3.1, 1.3.2 and 1.3.3 is about 600 ms. Thus there has been a 20x increase in run time. This severely impacts the performance of our application. A section of our code that used to take about 30 seconds, now takes about 10 minutes (that code uses `pd.concat` a lot, which in turn calls `MultiIndex.equals`). | {
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} | 2 | "2021-09-13T14:32:15Z" | "2021-09-14T14:35:51Z" | "2021-09-14T14:35:51Z" | MEMBER | null | Doing a merge with `how="outer"` on an integer / all-NaN column started failing.
This works in pandas 1.3.2:
```python
df1 = pd.DataFrame({"key": [1, 2], "col1": [1, 2]})
df2 = pd.DataFrame({"key": [np.nan, np.nan], "col2": [3, 4]})
In [3]: df1.merge(df2, on="key", how="outer")
Out[3]:
key col1 col2
0 1.0 1.0 NaN
1 2.0 2.0 NaN
2 NaN NaN 3.0
3 NaN NaN 4.0
```
However, this started failing on master some time ago, and apparently now also in pandas 1.3.3:
```python
In [4]: df1.merge(df2, on="key", how="outer")
---------------------------------------------------------------------------
IntCastingNaNError Traceback (most recent call last)
<ipython-input-4-d831b6be2611> in <module>
----> 1 df1.merge(df2, on="key", how="outer")
~/miniconda3/envs/pandas13/lib/python3.9/site-packages/pandas/core/frame.py in merge(self, right, how, on, left_on, right_on, left_index, right_index, sort, suffixes, copy, indicator, validate)
9189 from pandas.core.reshape.merge import merge
9190
-> 9191 return merge(
9192 self,
9193 right,
~/miniconda3/envs/pandas13/lib/python3.9/site-packages/pandas/core/reshape/merge.py in merge(left, right, how, on, left_on, right_on, left_index, right_index, sort, suffixes, copy, indicator, validate)
118 validate=validate,
119 )
--> 120 return op.get_result()
121
122
~/miniconda3/envs/pandas13/lib/python3.9/site-packages/pandas/core/reshape/merge.py in get_result(self)
734 result = self._indicator_post_merge(result)
735
--> 736 self._maybe_add_join_keys(result, left_indexer, right_indexer)
737
738 self._maybe_restore_index_levels(result)
~/miniconda3/envs/pandas13/lib/python3.9/site-packages/pandas/core/reshape/merge.py in _maybe_add_join_keys(self, result, left_indexer, right_indexer)
915
916 if result._is_label_reference(name):
--> 917 result[name] = Series(
918 key_col, dtype=result_dtype, index=result.index
919 )
~/miniconda3/envs/pandas13/lib/python3.9/site-packages/pandas/core/series.py in __init__(self, data, index, dtype, name, copy, fastpath)
381 if dtype is not None:
382 # astype copies
--> 383 data = data.astype(dtype)
384 else:
385 # GH#24096 we need to ensure the index remains immutable
~/miniconda3/envs/pandas13/lib/python3.9/site-packages/pandas/core/indexes/numeric.py in astype(self, dtype, copy)
221 # TODO(jreback); this can change once we have an EA Index type
222 # GH 13149
--> 223 arr = astype_nansafe(self._values, dtype=dtype)
224 return Int64Index(arr, name=self.name)
225
~/miniconda3/envs/pandas13/lib/python3.9/site-packages/pandas/core/dtypes/cast.py in astype_nansafe(arr, dtype, copy, skipna)
1166
1167 elif np.issubdtype(arr.dtype, np.floating) and np.issubdtype(dtype, np.integer):
-> 1168 return astype_float_to_int_nansafe(arr, dtype, copy)
1169
1170 elif is_object_dtype(arr):
~/miniconda3/envs/pandas13/lib/python3.9/site-packages/pandas/core/dtypes/cast.py in astype_float_to_int_nansafe(values, dtype, copy)
1211 """
1212 if not np.isfinite(values).all():
-> 1213 raise IntCastingNaNError(
1214 "Cannot convert non-finite values (NA or inf) to integer"
1215 )
IntCastingNaNError: Cannot convert non-finite values (NA or inf) to integer
```
This breaks GeoPandas' `overlay` function (cfr https://github.com/geopandas/geopandas/pull/2101)
cc @simonjayhawkins
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} | 1 | "2021-09-13T15:42:52Z" | "2021-09-14T14:09:55Z" | "2021-09-14T14:09:49Z" | CONTRIBUTOR | null | - [x] refactoring for #40245
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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All this PR does is add a method and fix failing tests because of a minor change to jinja2 templates. | {
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} | 1 | "2021-09-13T16:56:52Z" | "2021-09-14T14:46:12Z" | "2021-09-14T14:35:52Z" | CONTRIBUTOR | null | - [x] closes #43550
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
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] | open | false | null | [] | null | 0 | "2021-09-13T17:25:06Z" | "2021-09-30T23:45:06Z" | null | NONE | null | When I print a dataframe, which uses df.to_string(), I would like the ability to display it in CSV format with commas between the columns instead of spaces, like this:
```
Name,Age
Alex,10
Bob,12
Clarke,13
```
This might be done with a new string option 'display.column_delimiter' in pd.set_option().
pd.set_option('display.column_delimiter', ',')
```
import pandas as pd
data = [['Alex',10],['Bob',12],['Clarke',13]]
df = pd.DataFrame(data,columns=['Name','Age'])
### pd.set_option('display.column_delimiter', ',') ### Use comma instead of spaces
print(df.to_string(index=False))
```
Currently, the output uses spaces as below:
```
Name Age
Alex 10
Bob 12
Clarke 13
```
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} | 1 | "2021-09-13T18:25:18Z" | "2021-09-13T21:51:27Z" | "2021-09-13T19:26:58Z" | MEMBER | null | - [x] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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- [X] I have checked that this issue has not already been reported.
- [ ] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Issue Description
I have a PR which is continually failing at the same point: https://github.com/pandas-dev/pandas/pull/43552/checks?check_run_id=3589495025
The warnings seem to be because within `doc/source/user_guide/scale.rst` the line
```
ts.to_parquet("timeseries.parquet")
```
does not execute, and then following objects are not created and generate errors.
Locally, when trying to execute the code I receive the error message in my environment:
```
ImportError: Unable to find a usable engine; tried using: 'pyarrow', 'fastparquet'.
A suitable version of pyarrow or fastparquet is required for parquet support.
Trying to import the above resulted in these errors:
- Missing optional dependency 'pyarrow'. pyarrow is required for parquet support. Use pip or conda to install pyarrow.
- Missing optional dependency 'fastparquet'. fastparquet is required for parquet support. Use pip or conda to install fastparquet.
```
Running `pip list` in my Python3.8 environment on MacOs 10.13.6 I can see that:
```
fastparquet 0.6.3
pyarrow 4.0.1
```
are both installed, so this conflicts with the error warning displayed.
This is puzzling for a couple of reasons:
- firstly because it errors locally and on online CI checks, but I haven't yet spotted any other PRs suffering.
- for me, I also see local errors on master (not just on my PR branch).
- my PR seems completely unrelated the CI failures.
If anyone spots anything untoward, please share the wisdom.
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} | 0 | "2021-09-13T23:25:34Z" | "2021-09-14T03:36:53Z" | "2021-09-14T03:14:40Z" | MEMBER | null | - [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
Removed test is duplicated of
https://github.com/pandas-dev/pandas/blob/e9d0a58c4152a16153dfb330164991d37fdd02dc/pandas/tests/apply/test_frame_apply.py#L1398-L1406
and
https://github.com/pandas-dev/pandas/blob/e9d0a58c4152a16153dfb330164991d37fdd02dc/pandas/tests/apply/test_series_apply.py#L410-L416 | {
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} | 0 | "2021-09-13T23:36:14Z" | "2021-09-14T16:20:39Z" | "2021-09-14T12:43:19Z" | MEMBER | null | ```
import pandas as pd
ser = pd.Series(range(5))
%timeit ser.to_frame()
%prun -s cumtime for n in range(10000): ser.to_frame()
9.71 µs ± 501 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each) # <- PR
33.2 µs ± 651 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each) # <- master
``` | {
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] | open | false | null | [] | null | 0 | "2021-09-14T03:11:02Z" | "2021-09-30T23:45:22Z" | null | MEMBER | null | In #43545, found that "not network" was not actually skipping network tests.
In the process of looking for a build which explicitly runs network tests, looked like all pytest patterns include "not network" or "slow". In that case, no network tests will be selected (unless they also happen to be "slow"). Can anyone please confirm this or point me to the build where network tests are meant to run? | {
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} | 0 | "2021-09-14T04:32:49Z" | "2021-09-14T15:21:11Z" | "2021-09-14T15:21:11Z" | CONTRIBUTOR | null | ###
- [X] I have checked that the issue still exists on the latest versions of the docs on `master` [here](https://pandas.pydata.org/docs/dev/)
### Location of the documentation
https://pandas.pydata.org/docs/dev/user_guide/10min.html#plotting
### Documentation problem
When following the tutorial, plot may not appear, depending on the environment. Some environments require `plot.show`, some will require `plot.savefig`.
PR #43544 adds a very brief explanation.
### Suggested fix for documentation
If running under Jupyter Notebook, the plot will appear on `~ts.plot`. Otherwise use [`matplotlib.pyplot.show`](https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.show.html) to show it or [`matplotlib.pyplot.savefig`](https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.savefig.html) to write it to a file.
plt.show();
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} | 2 | "2021-09-14T04:45:24Z" | "2021-11-12T03:11:32Z" | "2021-11-12T03:11:32Z" | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
df = pd.DataFrame( { 'element': [ 't_mean','t_mean','t_mean','r','r','r' ],
'time': [ 1,2,3,1,2,3],
'54511': [226,215,232,50,10,305],
'54514': [215,220,220,10,9,111],
} )
df2 = df.set_index( ['element','time'] )
df2.columns.set_names( 'station', inplace=True )
df3 = df2.unstack( 'element' )
print( df3 )
df4 = df3.stack( 'station' )
# everything is ok until now.
# will raise IndexError : index 6 is out of bounds for axis 0 with size 6
df32 = df3.astype( pd.Int64Dtype() ) ### here
df42 = df32.stack( 'station' )
```
### Issue Description
bug exists in **pandas/core/reshape/reshape.py** :
def _stack_multi_columns(frame, level_num=-1, dropna=True):
def _convert_level_number(level_num, columns):
"""
Logic for converting the level number to something we can safely pass
to swaplevel.
If `level_num` matches a column name return the name from
position `level_num`, otherwise return `level_num`.
"""
if level_num in columns.names:
return columns.names[level_num]
return level_num
this = frame.copy()
# this makes life much simpler
if level_num != frame.columns.nlevels - 1:
# roll levels to put selected level at end
roll_columns = this.columns
for i in range(level_num, frame.columns.nlevels - 1):
# Need to check if the ints conflict with level names
lev1 = _convert_level_number(i, roll_columns)
lev2 = _convert_level_number(i + 1, roll_columns)
roll_columns = roll_columns.swaplevel(lev1, lev2)
this.columns = roll_columns
if not this.columns._is_lexsorted():
# Workaround the edge case where 0 is one of the column names,
# which interferes with trying to sort based on the first
# level
level_to_sort = _convert_level_number(0, this.columns)
this = this.sort_index(level=level_to_sort, axis=1)
new_columns = _stack_multi_column_index(this.columns)
# time to ravel the values
new_data = {}
level_vals = this.columns.levels[-1]
level_codes = sorted(set(this.columns.codes[-1]))
level_vals_nan = level_vals.insert(len(level_vals), None)
level_vals_used = np.take(level_vals_nan, level_codes)
levsize = len(level_codes)
drop_cols = []
for key in new_columns:
try:
loc = this.columns.get_loc(key)
except KeyError:
drop_cols.append(key)
continue
# can make more efficient?
# we almost always return a slice
# but if unsorted can get a boolean
# indexer
if not isinstance(loc, slice):
slice_len = len(loc)
else:
slice_len = loc.stop - loc.start
if slice_len != levsize:
chunk = this.loc[:, this.columns[loc]]
chunk.columns = level_vals_nan.take(chunk.columns.codes[-1])
value_slice = chunk.reindex(columns=level_vals_used).values
else:
if frame._is_homogeneous_type and is_extension_array_dtype(
frame.dtypes.iloc[0]
):
dtype = this[this.columns[loc]].dtypes.iloc[0]
subset = this[this.columns[loc]]
value_slice = dtype.construct_array_type()._concat_same_type(
[x._values for _, x in subset.items()]
)
N, K = this.shape #----------------> !!!! look at here, is it a bug?
#N, K = subset.shape #
idx = np.arange(N * K).reshape(K, N).T.ravel()
value_slice = value_slice.take(idx)
elif frame._is_mixed_type:
value_slice = this[this.columns[loc]].values
else:
value_slice = this.values[:, loc]
if value_slice.ndim > 1:
# i.e. not extension
value_slice = value_slice.ravel()
new_data[key] = value_slice
if len(drop_cols) > 0:
new_columns = new_columns.difference(drop_cols)
N = len(this)
if isinstance(this.index, MultiIndex):
new_levels = list(this.index.levels)
new_names = list(this.index.names)
new_codes = [lab.repeat(levsize) for lab in this.index.codes]
else:
old_codes, old_levels = factorize_from_iterable(this.index)
new_levels = [old_levels]
new_codes = [old_codes.repeat(levsize)]
new_names = [this.index.name] # something better?
new_levels.append(level_vals)
new_codes.append(np.tile(level_codes, N))
new_names.append(frame.columns.names[level_num])
new_index = MultiIndex(
levels=new_levels, codes=new_codes, names=new_names, verify_integrity=False
)
result = frame._constructor(new_data, index=new_index, columns=new_columns)
# more efficient way to go about this? can do the whole masking biz but
# will only save a small amount of time...
if dropna:
result = result.dropna(axis=0, how="all")
return result
### Expected Behavior
Don't throw exception
### Installed Versions
<details>
pandas 1.3.3
</details>
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} | 1 | "2021-09-14T05:50:33Z" | "2021-09-14T12:56:56Z" | "2021-09-14T12:56:52Z" | CONTRIBUTOR | null | - [x] closes #39548
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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- [ ] I have checked that this issue has not already been reported.
- [ ] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
df = pd.DataFrame(columns=['url'])
df['url'] = ['https://qweqwe.com/2021-09-14/qweqwejpgqweqwe.jpg']
df['id'] = df['url'].str.split('/').str[-2].astype(str) + '_' + df['url'].str.split('/').str[-1].str.split('.jpg').str[0]
print(df['id'].iloc[0])
```
### Issue Description
output: 2021-09-14_qweqw
true output: 2021-09-14_qweqwejpgqweqwe
### Expected Behavior
2021-09-14_qweqwejpgqweqwe
### Installed Versions
python 3.9
pandas version 1.3.2 | {
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} | 4 | "2021-09-14T10:09:23Z" | "2021-11-11T09:00:48Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
df = pd.DataFrame({'gender': ['female', 'male', 'female', 'male', 'female', 'male'],
'education': ['low', 'medium', 'high', 'low', 'high', 'low'],
'country': ['US', 'FR', 'US', 'FR', 'FR', 'US']})
# These all work fine:
# value_counts() on a DataFrame
df[['gender', 'education']].value_counts(normalize=True)
df['gender'].value_counts(normalize=True) # on a Series
df.groupby('country')['gender'].value_counts(normalize=True) # on a SeriesGroupby
# but fails on DataFrameGroupBy
df.groupby('country')[['gender', 'education']].value_counts(normalize=True)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
/var/folders/xz/_nt7tl1s0jx2f5_8rwc8kc0r0000gp/T/ipykernel_96325/3153685003.py in <module>
----> 1 df.groupby('country')[['gender', 'education']].value_counts(normalize=True)
~/opt/anaconda3/envs/pandas_dev/lib/python3.9/site-packages/pandas/core/groupby/groupby.py in __getattr__(self, attr)
909 return self[attr]
910
--> 911 raise AttributeError(
912 f"'{type(self).__name__}' object has no attribute '{attr}'"
913 )
AttributeError: 'DataFrameGroupBy' object has no attribute 'value_counts'
```
### Issue Description
Since `value_counts()` is defined both for a `Series` and a `DataFrame`, I also expect it to work on both a `SeriesGroupBy` and a `DataFrameGroupBy`.
There are some related Issues: https://github.com/pandas-dev/pandas/issues/39938 and https://github.com/pandas-dev/pandas/issues/6540, these have been dismissed so far with the argument that `size()` already does that, but `size()` alone is not enough to get the proportions per group.
### Expected Behavior
I managed to get the desired behaviour by applying `value_counts()` to each group:
```
def compute_proportions(df, var):
return (df[var]
.value_counts(normalize=True)
)
(df.groupby('country')
.apply(compute_proportions, var=['gender', 'education'])
)
country gender education
FR female high 0.333333
male low 0.333333
medium 0.333333
US male low 0.666667
female high 0.333333
dtype: float64
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.9.7.final.0
python-bits : 64
OS : Darwin
OS-release : 19.6.0
Version : Darwin Kernel Version 19.6.0: Tue Jun 22 19:49:55 PDT 2021; root:xnu-6153.141.35~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 7.27.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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- [X] I have checked that this issue has not already been reported.
- [x] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [x] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
s = pd.DataFrame({'s':['aaa', 'bbb', 'ccc']})
print(f'Initial df bytes {s.memory_usage(deep=True, index=False).sum()}')
# Initial df bytes 180
s = s.assign(s=s.s.astype('string[pyarrow]'))
print(f'pyarrow string df bytes {s.memory_usage(deep=True, index=False).sum()}')
# pyarrow string df bytes 25
s.to_feather('s.feather')
s = pd.read_feather('s.feather')
print(f'after feather bytes {s.memory_usage(deep=True, index=False).sum()}')
# after feather bytes 180
```
### Issue Description
Loading a df that contains a column of type string[pyarrow] from a feather file loads the column as type string
### Expected Behavior
Load the column in its original string[pyarrow] type
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 5f648bf1706dd75a9ca0d29f26eadfbb595fe52b
python : 3.9.6.final.0
python-bits : 64
OS : Darwin
OS-release : 20.4.0
Version : Darwin Kernel Version 20.4.0: Thu Apr 22 21:46:47 PDT 2021; root:xnu-7195.101.2~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 1.3.2
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 52.0.0.post20210125
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.27.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 2021.08.1
fastparquet : None
gcsfs : 2021.08.1
matplotlib : 3.4.3
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.4.23
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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} | 5 | "2021-09-14T14:38:43Z" | "2021-10-01T00:16:28Z" | null | NONE | null | #### Is your feature request related to a problem?
I am using pandas lib to read xml for further processes, however a number of columns with leading ZERO are always converted to numbers, so I lost the original data.
#### Describe the solution you'd like
It would be great to add **dtype/converter** arguments for `pandas.read_xml()` to force pandas to interprete certain columns with given dtype/converters.
Just like similar IO read (read_csv, read_html, etc)
[read_xml](https://pandas.pydata.org/docs/reference/api/pandas.read_xml.html)
[read_csv](https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html)
#### API breaking implications
Probably not, this argument could be optional.
#### Describe alternatives you've considered
Write my own code to pull data by each xml nodes, which results in very bad performance. | {
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} | 6 | "2021-09-14T15:42:41Z" | "2021-10-16T18:26:59Z" | null | MEMBER | null | From https://github.com/dask/dask/issues/8137
One of the corner cases in groupby apply (discussed in other issues like https://github.com/pandas-dev/pandas/pull/34998) has changed behaviour:
```python
import pandas as pd
df = pd._testing.makeTimeDataFrame()
df.groupby(df.index.month).apply(lambda x: x.drop_duplicates())
```
In pandas 1.3.2 this gives:
```
A B C D
1 2000-01-03 -1.261522 -0.200411 -0.746305 -0.661842
2000-01-04 1.248556 0.256573 -1.401839 0.508941
2000-01-05 -0.036682 0.109758 -0.759474 -0.601479
2000-01-06 -0.778714 -0.932903 -0.544291 -0.986584
2000-01-07 -0.567276 0.744036 1.981160 0.222988
2000-01-10 -0.448542 0.221418 0.485706 -1.142561
2000-01-11 -0.125143 -1.393151 0.879428 0.011297
2000-01-12 0.550527 -1.373356 1.149654 -0.575065
2000-01-13 0.269579 -0.017307 -1.023269 0.738274
2000-01-14 0.757235 -1.875451 -0.751026 0.812741
2000-01-17 2.456978 0.992319 0.945757 -2.468437
2000-01-18 -2.132953 1.210491 0.150581 -1.861079
2000-01-19 0.500947 -0.861651 0.412729 -1.274573
2000-01-20 0.215823 -0.502341 -0.060564 0.439930
2000-01-21 0.454649 1.188960 1.167487 -0.087031
2000-01-24 -1.194599 0.709980 1.927664 -1.868195
2000-01-25 -1.465017 1.187098 0.262209 0.312123
2000-01-26 -0.010187 -0.624253 -0.186090 -0.126192
2000-01-27 -0.520074 -0.189463 -0.379236 -0.259591
2000-01-28 -1.179406 -0.169766 -1.731189 0.583444
2000-01-31 0.677903 0.845305 -0.282444 0.807889
2 2000-02-01 -1.561435 2.068383 -0.500742 -0.040578
2000-02-02 -1.357882 1.302612 1.105816 -0.688315
2000-02-03 0.604455 0.637055 -0.296199 0.699753
2000-02-04 0.102784 -0.786359 -0.598806 0.604410
2000-02-07 0.977317 0.530884 -0.880909 -0.963008
2000-02-08 1.948681 0.065753 -0.530815 -1.688043
2000-02-09 1.461333 1.105021 1.039801 -0.144059
2000-02-10 2.105116 -1.121452 0.076824 -0.334885
2000-02-11 0.984281 0.858620 1.602277 -0.421881
```
while in pandas 1.3.3 it gives:
```
A B C D
2000-01-03 0.131780 0.079102 -2.631289 0.969882
2000-01-04 0.381887 0.177194 -0.031367 -1.062184
2000-01-05 -1.299994 0.951530 0.806066 1.043698
2000-01-06 -0.669137 1.036442 0.762052 -0.475059
2000-01-07 0.498415 -0.511591 -0.500675 0.098846
2000-01-10 -1.313268 0.511975 -0.935800 -0.371694
2000-01-11 1.812837 -0.017126 -0.748976 1.217975
2000-01-12 0.236695 0.012316 0.319136 0.743945
2000-01-13 -1.128511 0.367611 -0.240936 -0.847221
2000-01-14 -2.170718 1.349021 -1.205040 1.210471
2000-01-17 0.220773 1.238868 -0.208188 -0.240763
2000-01-18 -0.949992 0.273480 0.863710 2.446306
2000-01-19 0.622379 1.386699 -1.181249 0.188620
2000-01-20 -1.340407 -0.523331 -1.794468 0.877138
2000-01-21 0.029993 -0.115333 0.358685 1.652006
2000-01-24 1.209907 -1.354522 0.883701 0.686492
2000-01-25 -0.840201 1.415816 0.396826 1.342700
2000-01-26 1.206150 -0.114443 0.011106 0.995629
2000-01-27 -0.505894 0.500736 0.004411 0.807632
2000-01-28 0.117852 -0.411066 1.315072 0.731249
2000-01-31 -0.329046 -1.921455 2.564603 -0.222591
2000-02-01 0.295899 -0.169977 0.162310 -0.554688
2000-02-02 -1.144224 0.530313 -0.530216 0.287826
2000-02-03 1.491748 -1.051309 1.414135 -0.332648
2000-02-04 -0.452243 -0.087787 -0.308278 0.681506
2000-02-07 -1.041728 -0.202066 0.044722 0.665914
2000-02-08 0.712994 1.547563 2.557823 -0.801031
2000-02-09 0.396298 -1.325411 -0.926420 0.738052
2000-02-10 0.460109 0.734418 0.416767 -1.199427
2000-02-11 -0.104655 -0.440354 -0.787402 0.357853
```
(note the difference in index)
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- [x] closes #25781
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
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- [x] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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} | 1 | "2021-09-14T21:01:21Z" | "2021-09-14T23:18:56Z" | "2021-09-14T23:02:40Z" | MEMBER | null | - [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
Purely a move. I have a PR just about ready to start tackling #41112, but it needs to touch some of the renamer code. It'd be nice to have it all in `core.apply`, and logically makes sense to go there.
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- [X] I have read the [installation guide](https://pandas.pydata.org/pandas-docs/stable/getting_started/install.html#installing-pandas).
### Platform
Linux-5.4.0-84-generic-x86_64-with-debian-buster-sid
### Installation Method
Built from source
### pandas Version
1.3.2
### Python Version
3.8
### Installation Logs
Upon executing `python make.py latex` in `doc/` I get errors: the SVG files can't be processed.
Attaching the entire `pandas.log` for reference.
<details>
```
This is pdfTeX, Version 3.14159265-2.6-1.40.18 (TeX Live 2017/Debian) (preloaded format=pdflatex 2021.9.14) 14 SEP 2021 23:40
entering extended mode
restricted \write18 enabled.
%&-line parsing enabled.
**pandas.tex
(./pandas.tex
LaTeX2e <2017-04-15>
Babel <3.18> and hyphenation patterns for 5 language(s) loaded.
(./sphinxmanual.cls
Document Class: sphinxmanual 2019/12/01 v2.3.0 Document class (Sphinx manual)
(/usr/share/texlive/texmf-dist/tex/latex/base/report.cls
Document Class: report 2014/09/29 v1.4h Standard LaTeX document class
(/usr/share/texlive/texmf-dist/tex/latex/base/size10.clo
File: size10.clo 2014/09/29 v1.4h Standard LaTeX file (size option)
)
\c@part=\count79
\c@chapter=\count80
\c@section=\count81
\c@subsection=\count82
\c@subsubsection=\count83
\c@paragraph=\count84
\c@subparagraph=\count85
\c@figure=\count86
\c@table=\count87
\abovecaptionskip=\skip41
\belowcaptionskip=\skip42
\bibindent=\dimen102
)
LaTeX Info: Redefining \and on input line 35.
)
(/usr/share/texlive/texmf-dist/tex/latex/base/inputenc.sty
Package: inputenc 2015/03/17 v1.2c Input encoding file
\inpenc@prehook=\toks14
\inpenc@posthook=\toks15
(/usr/share/texlive/texmf-dist/tex/latex/base/utf8.def
File: utf8.def 2017/01/28 v1.1t UTF-8 support for inputenc
Now handling font encoding OML ...
... no UTF-8 mapping file for font encoding OML
Now handling font encoding T1 ...
... processing UTF-8 mapping file for font encoding T1
(/usr/share/texlive/texmf-dist/tex/latex/base/t1enc.dfu
File: t1enc.dfu 2017/01/28 v1.1t UTF-8 support for inputenc
defining Unicode char U+00A0 (decimal 160)
defining Unicode char U+00A1 (decimal 161)
defining Unicode char U+00A3 (decimal 163)
defining Unicode char U+00AB (decimal 171)
defining Unicode char U+00AD (decimal 173)
defining Unicode char U+00BB (decimal 187)
defining Unicode char U+00BF (decimal 191)
defining Unicode char U+00C0 (decimal 192)
defining Unicode char U+00C1 (decimal 193)
defining Unicode char U+00C2 (decimal 194)
defining Unicode char U+00C3 (decimal 195)
defining Unicode char U+00C4 (decimal 196)
defining Unicode char U+00C5 (decimal 197)
defining Unicode char U+00C6 (decimal 198)
defining Unicode char U+00C7 (decimal 199)
defining Unicode char U+00C8 (decimal 200)
defining Unicode char U+00C9 (decimal 201)
defining Unicode char U+00CA (decimal 202)
defining Unicode char U+00CB (decimal 203)
defining Unicode char U+00CC (decimal 204)
defining Unicode char U+00CD (decimal 205)
defining Unicode char U+00CE (decimal 206)
defining Unicode char U+00CF (decimal 207)
defining Unicode char U+00D0 (decimal 208)
defining Unicode char U+00D1 (decimal 209)
defining Unicode char U+00D2 (decimal 210)
defining Unicode char U+00D3 (decimal 211)
defining Unicode char U+00D4 (decimal 212)
defining Unicode char U+00D5 (decimal 213)
defining Unicode char U+00D6 (decimal 214)
defining Unicode char U+00D8 (decimal 216)
defining Unicode char U+00D9 (decimal 217)
defining Unicode char U+00DA (decimal 218)
defining Unicode char U+00DB (decimal 219)
defining Unicode char U+00DC (decimal 220)
defining Unicode char U+00DD (decimal 221)
defining Unicode char U+00DE (decimal 222)
defining Unicode char U+00DF (decimal 223)
defining Unicode char U+00E0 (decimal 224)
defining Unicode char U+00E1 (decimal 225)
defining Unicode char U+00E2 (decimal 226)
defining Unicode char U+00E3 (decimal 227)
defining Unicode char U+00E4 (decimal 228)
defining Unicode char U+00E5 (decimal 229)
defining Unicode char U+00E6 (decimal 230)
defining Unicode char U+00E7 (decimal 231)
defining Unicode char U+00E8 (decimal 232)
defining Unicode char U+00E9 (decimal 233)
defining Unicode char U+00EA (decimal 234)
defining Unicode char U+00EB (decimal 235)
defining Unicode char U+00EC (decimal 236)
defining Unicode char U+00ED (decimal 237)
defining Unicode char U+00EE (decimal 238)
defining Unicode char U+00EF (decimal 239)
defining Unicode char U+00F0 (decimal 240)
defining Unicode char U+00F1 (decimal 241)
defining Unicode char U+00F2 (decimal 242)
defining Unicode char U+00F3 (decimal 243)
defining Unicode char U+00F4 (decimal 244)
defining Unicode char U+00F5 (decimal 245)
defining Unicode char U+00F6 (decimal 246)
defining Unicode char U+00F8 (decimal 248)
defining Unicode char U+00F9 (decimal 249)
defining Unicode char U+00FA (decimal 250)
defining Unicode char U+00FB (decimal 251)
defining Unicode char U+00FC (decimal 252)
defining Unicode char U+00FD (decimal 253)
defining Unicode char U+00FE (decimal 254)
defining Unicode char U+00FF (decimal 255)
defining Unicode char U+0100 (decimal 256)
defining Unicode char U+0101 (decimal 257)
defining Unicode char U+0102 (decimal 258)
defining Unicode char U+0103 (decimal 259)
defining Unicode char U+0104 (decimal 260)
defining Unicode char U+0105 (decimal 261)
defining Unicode char U+0106 (decimal 262)
defining Unicode char U+0107 (decimal 263)
defining Unicode char U+0108 (decimal 264)
defining Unicode char U+0109 (decimal 265)
defining Unicode char U+010A (decimal 266)
defining Unicode char U+010B (decimal 267)
defining Unicode char U+010C (decimal 268)
defining Unicode char U+010D (decimal 269)
defining Unicode char U+010E (decimal 270)
defining Unicode char U+010F (decimal 271)
defining Unicode char U+0110 (decimal 272)
defining Unicode char U+0111 (decimal 273)
defining Unicode char U+0112 (decimal 274)
defining Unicode char U+0113 (decimal 275)
defining Unicode char U+0114 (decimal 276)
defining Unicode char U+0115 (decimal 277)
defining Unicode char U+0116 (decimal 278)
defining Unicode char U+0117 (decimal 279)
defining Unicode char U+0118 (decimal 280)
defining Unicode char U+0119 (decimal 281)
defining Unicode char U+011A (decimal 282)
defining Unicode char U+011B (decimal 283)
defining Unicode char U+011C (decimal 284)
defining Unicode char U+011D (decimal 285)
defining Unicode char U+011E (decimal 286)
defining Unicode char U+011F (decimal 287)
defining Unicode char U+0120 (decimal 288)
defining Unicode char U+0121 (decimal 289)
defining Unicode char U+0122 (decimal 290)
defining Unicode char U+0123 (decimal 291)
defining Unicode char U+0124 (decimal 292)
defining Unicode char U+0125 (decimal 293)
defining Unicode char U+0128 (decimal 296)
defining Unicode char U+0129 (decimal 297)
defining Unicode char U+012A (decimal 298)
defining Unicode char U+012B (decimal 299)
defining Unicode char U+012C (decimal 300)
defining Unicode char U+012D (decimal 301)
defining Unicode char U+012E (decimal 302)
defining Unicode char U+012F (decimal 303)
defining Unicode char U+0130 (decimal 304)
defining Unicode char U+0131 (decimal 305)
defining Unicode char U+0132 (decimal 306)
defining Unicode char U+0133 (decimal 307)
defining Unicode char U+0134 (decimal 308)
defining Unicode char U+0135 (decimal 309)
defining Unicode char U+0136 (decimal 310)
defining Unicode char U+0137 (decimal 311)
defining Unicode char U+0139 (decimal 313)
defining Unicode char U+013A (decimal 314)
defining Unicode char U+013B (decimal 315)
defining Unicode char U+013C (decimal 316)
defining Unicode char U+013D (decimal 317)
defining Unicode char U+013E (decimal 318)
defining Unicode char U+0141 (decimal 321)
defining Unicode char U+0142 (decimal 322)
defining Unicode char U+0143 (decimal 323)
defining Unicode char U+0144 (decimal 324)
defining Unicode char U+0145 (decimal 325)
defining Unicode char U+0146 (decimal 326)
defining Unicode char U+0147 (decimal 327)
defining Unicode char U+0148 (decimal 328)
defining Unicode char U+014A (decimal 330)
defining Unicode char U+014B (decimal 331)
defining Unicode char U+014C (decimal 332)
defining Unicode char U+014D (decimal 333)
defining Unicode char U+014E (decimal 334)
defining Unicode char U+014F (decimal 335)
defining Unicode char U+0150 (decimal 336)
defining Unicode char U+0151 (decimal 337)
defining Unicode char U+0152 (decimal 338)
defining Unicode char U+0153 (decimal 339)
defining Unicode char U+0154 (decimal 340)
defining Unicode char U+0155 (decimal 341)
defining Unicode char U+0156 (decimal 342)
defining Unicode char U+0157 (decimal 343)
defining Unicode char U+0158 (decimal 344)
defining Unicode char U+0159 (decimal 345)
defining Unicode char U+015A (decimal 346)
defining Unicode char U+015B (decimal 347)
defining Unicode char U+015C (decimal 348)
defining Unicode char U+015D (decimal 349)
defining Unicode char U+015E (decimal 350)
defining Unicode char U+015F (decimal 351)
defining Unicode char U+0160 (decimal 352)
defining Unicode char U+0161 (decimal 353)
defining Unicode char U+0162 (decimal 354)
defining Unicode char U+0163 (decimal 355)
defining Unicode char U+0164 (decimal 356)
defining Unicode char U+0165 (decimal 357)
defining Unicode char U+0168 (decimal 360)
defining Unicode char U+0169 (decimal 361)
defining Unicode char U+016A (decimal 362)
defining Unicode char U+016B (decimal 363)
defining Unicode char U+016C (decimal 364)
defining Unicode char U+016D (decimal 365)
defining Unicode char U+016E (decimal 366)
defining Unicode char U+016F (decimal 367)
defining Unicode char U+0170 (decimal 368)
defining Unicode char U+0171 (decimal 369)
defining Unicode char U+0172 (decimal 370)
defining Unicode char U+0173 (decimal 371)
defining Unicode char U+0174 (decimal 372)
defining Unicode char U+0175 (decimal 373)
defining Unicode char U+0176 (decimal 374)
defining Unicode char U+0177 (decimal 375)
defining Unicode char U+0178 (decimal 376)
defining Unicode char U+0179 (decimal 377)
defining Unicode char U+017A (decimal 378)
defining Unicode char U+017B (decimal 379)
defining Unicode char U+017C (decimal 380)
defining Unicode char U+017D (decimal 381)
defining Unicode char U+017E (decimal 382)
defining Unicode char U+01CD (decimal 461)
defining Unicode char U+01CE (decimal 462)
defining Unicode char U+01CF (decimal 463)
defining Unicode char U+01D0 (decimal 464)
defining Unicode char U+01D1 (decimal 465)
defining Unicode char U+01D2 (decimal 466)
defining Unicode char U+01D3 (decimal 467)
defining Unicode char U+01D4 (decimal 468)
defining Unicode char U+01E2 (decimal 482)
defining Unicode char U+01E3 (decimal 483)
defining Unicode char U+01E6 (decimal 486)
defining Unicode char U+01E7 (decimal 487)
defining Unicode char U+01E8 (decimal 488)
defining Unicode char U+01E9 (decimal 489)
defining Unicode char U+01EA (decimal 490)
defining Unicode char U+01EB (decimal 491)
defining Unicode char U+01F0 (decimal 496)
defining Unicode char U+01F4 (decimal 500)
defining Unicode char U+01F5 (decimal 501)
defining Unicode char U+0218 (decimal 536)
defining Unicode char U+0219 (decimal 537)
defining Unicode char U+021A (decimal 538)
defining Unicode char U+021B (decimal 539)
defining Unicode char U+0232 (decimal 562)
defining Unicode char U+0233 (decimal 563)
defining Unicode char U+1E02 (decimal 7682)
defining Unicode char U+1E03 (decimal 7683)
defining Unicode char U+200C (decimal 8204)
defining Unicode char U+2010 (decimal 8208)
defining Unicode char U+2011 (decimal 8209)
defining Unicode char U+2012 (decimal 8210)
defining Unicode char U+2013 (decimal 8211)
defining Unicode char U+2014 (decimal 8212)
defining Unicode char U+2015 (decimal 8213)
defining Unicode char U+2018 (decimal 8216)
defining Unicode char U+2019 (decimal 8217)
defining Unicode char U+201A (decimal 8218)
defining Unicode char U+201C (decimal 8220)
defining Unicode char U+201D (decimal 8221)
defining Unicode char U+201E (decimal 8222)
defining Unicode char U+2030 (decimal 8240)
defining Unicode char U+2031 (decimal 8241)
defining Unicode char U+2039 (decimal 8249)
defining Unicode char U+203A (decimal 8250)
defining Unicode char U+2423 (decimal 9251)
defining Unicode char U+1E20 (decimal 7712)
defining Unicode char U+1E21 (decimal 7713)
)
Now handling font encoding OT1 ...
... processing UTF-8 mapping file for font encoding OT1
(/usr/share/texlive/texmf-dist/tex/latex/base/ot1enc.dfu
File: ot1enc.dfu 2017/01/28 v1.1t UTF-8 support for inputenc
defining Unicode char U+00A0 (decimal 160)
defining Unicode char U+00A1 (decimal 161)
defining Unicode char U+00A3 (decimal 163)
defining Unicode char U+00AD (decimal 173)
defining Unicode char U+00B8 (decimal 184)
defining Unicode char U+00BF (decimal 191)
defining Unicode char U+00C5 (decimal 197)
defining Unicode char U+00C6 (decimal 198)
defining Unicode char U+00D8 (decimal 216)
defining Unicode char U+00DF (decimal 223)
defining Unicode char U+00E6 (decimal 230)
defining Unicode char U+00EC (decimal 236)
defining Unicode char U+00ED (decimal 237)
defining Unicode char U+00EE (decimal 238)
defining Unicode char U+00EF (decimal 239)
defining Unicode char U+00F8 (decimal 248)
defining Unicode char U+0131 (decimal 305)
defining Unicode char U+0141 (decimal 321)
defining Unicode char U+0142 (decimal 322)
defining Unicode char U+0152 (decimal 338)
defining Unicode char U+0153 (decimal 339)
defining Unicode char U+0174 (decimal 372)
defining Unicode char U+0175 (decimal 373)
defining Unicode char U+0176 (decimal 374)
defining Unicode char U+0177 (decimal 375)
defining Unicode char U+0218 (decimal 536)
defining Unicode char U+0219 (decimal 537)
defining Unicode char U+021A (decimal 538)
defining Unicode char U+021B (decimal 539)
defining Unicode char U+2013 (decimal 8211)
defining Unicode char U+2014 (decimal 8212)
defining Unicode char U+2018 (decimal 8216)
defining Unicode char U+2019 (decimal 8217)
defining Unicode char U+201C (decimal 8220)
defining Unicode char U+201D (decimal 8221)
)
Now handling font encoding OMS ...
... processing UTF-8 mapping file for font encoding OMS
(/usr/share/texlive/texmf-dist/tex/latex/base/omsenc.dfu
File: omsenc.dfu 2017/01/28 v1.1t UTF-8 support for inputenc
defining Unicode char U+00A7 (decimal 167)
defining Unicode char U+00B6 (decimal 182)
defining Unicode char U+00B7 (decimal 183)
defining Unicode char U+2020 (decimal 8224)
defining Unicode char U+2021 (decimal 8225)
defining Unicode char U+2022 (decimal 8226)
)
Now handling font encoding OMX ...
... no UTF-8 mapping file for font encoding OMX
Now handling font encoding U ...
... no UTF-8 mapping file for font encoding U
defining Unicode char U+00A9 (decimal 169)
defining Unicode char U+00AA (decimal 170)
defining Unicode char U+00AE (decimal 174)
defining Unicode char U+00BA (decimal 186)
defining Unicode char U+02C6 (decimal 710)
defining Unicode char U+02DC (decimal 732)
defining Unicode char U+200C (decimal 8204)
defining Unicode char U+2026 (decimal 8230)
defining Unicode char U+2122 (decimal 8482)
defining Unicode char U+2423 (decimal 9251)
))
defining Unicode char U+00A0 (decimal 160)
defining Unicode char U+2500 (decimal 9472)
defining Unicode char U+2502 (decimal 9474)
defining Unicode char U+2514 (decimal 9492)
defining Unicode char U+251C (decimal 9500)
defining Unicode char U+2572 (decimal 9586)
(/usr/share/texlive/texmf-dist/tex/latex/cmap/cmap.sty
Package: cmap 2008/03/06 v1.0h CMap support: searchable PDF
)
(/usr/share/texlive/texmf-dist/tex/latex/base/fontenc.sty
Package: fontenc 2017/04/05 v2.0i Standard LaTeX package
(/usr/share/texlive/texmf-dist/tex/latex/base/t1enc.def
File: t1enc.def 2017/04/05 v2.0i Standard LaTeX file
LaTeX Font Info: Redeclaring font encoding T1 on input line 48.
)<<t1.cmap>>)
(/usr/share/texlive/texmf-dist/tex/latex/amsmath/amsmath.sty
Package: amsmath 2017/09/02 v2.17a AMS math features
\@mathmargin=\skip43
For additional information on amsmath, use the `?' option.
(/usr/share/texlive/texmf-dist/tex/latex/amsmath/amstext.sty
Package: amstext 2000/06/29 v2.01 AMS text
(/usr/share/texlive/texmf-dist/tex/latex/amsmath/amsgen.sty
File: amsgen.sty 1999/11/30 v2.0 generic functions
\@emptytoks=\toks16
\ex@=\dimen103
))
(/usr/share/texlive/texmf-dist/tex/latex/amsmath/amsbsy.sty
Package: amsbsy 1999/11/29 v1.2d Bold Symbols
\pmbraise@=\dimen104
)
(/usr/share/texlive/texmf-dist/tex/latex/amsmath/amsopn.sty
Package: amsopn 2016/03/08 v2.02 operator names
)
\inf@bad=\count88
LaTeX Info: Redefining \frac on input line 213.
\uproot@=\count89
\leftroot@=\count90
LaTeX Info: Redefining \overline on input line 375.
\classnum@=\count91
\DOTSCASE@=\count92
LaTeX Info: Redefining \ldots on input line 472.
LaTeX Info: Redefining \dots on input line 475.
LaTeX Info: Redefining \cdots on input line 596.
\Mathstrutbox@=\box26
\strutbox@=\box27
\big@size=\dimen105
LaTeX Font Info: Redeclaring font encoding OML on input line 712.
LaTeX Font Info: Redeclaring font encoding OMS on input line 713.
\macc@depth=\count93
\c@MaxMatrixCols=\count94
\dotsspace@=\muskip10
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\dspbrk@lvl=\count96
\tag@help=\toks17
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\column@=\count98
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\andhelp@=\toks18
\eqnshift@=\dimen106
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\tagwidth@=\dimen109
\totwidth@=\dimen110
\lineht@=\dimen111
\@envbody=\toks19
\multlinegap=\skip44
\multlinetaggap=\skip45
\mathdisplay@stack=\toks20
LaTeX Info: Redefining \[ on input line 2817.
LaTeX Info: Redefining \] on input line 2818.
)
(/usr/share/texlive/texmf-dist/tex/latex/amsfonts/amssymb.sty
Package: amssymb 2013/01/14 v3.01 AMS font symbols
(/usr/share/texlive/texmf-dist/tex/latex/amsfonts/amsfonts.sty
Package: amsfonts 2013/01/14 v3.01 Basic AMSFonts support
\symAMSa=\mathgroup4
\symAMSb=\mathgroup5
LaTeX Font Info: Overwriting math alphabet `\mathfrak' in version `bold'
(Font) U/euf/m/n --> U/euf/b/n on input line 106.
))
(/usr/share/texlive/texmf-dist/tex/generic/babel/babel.sty
Package: babel 2018/02/14 3.18 The Babel package
(/usr/share/texlive/texmf-dist/tex/generic/babel/switch.def
File: switch.def 2018/02/14 3.18 Babel switching mechanism
)
(/usr/share/texlive/texmf-dist/tex/generic/babel-english/english.ldf
Language: english 2017/06/06 v3.3r English support from the babel system
(/usr/share/texlive/texmf-dist/tex/generic/babel/babel.def
File: babel.def 2018/02/14 3.18 Babel common definitions
\babel@savecnt=\count100
\U@D=\dimen112
(/usr/share/texlive/texmf-dist/tex/generic/babel/txtbabel.def)
\bbl@dirlevel=\count101
)
\l@canadian = a dialect from \language\l@american
\l@australian = a dialect from \language\l@british
\l@newzealand = a dialect from \language\l@british
))
(/usr/share/texmf/tex/latex/tex-gyre/tgtermes.sty
Package: tgtermes 2009/09/27 v1.2 TeX Gyre Termes as default roman family
(/usr/share/texlive/texmf-dist/tex/latex/oberdiek/kvoptions.sty
Package: kvoptions 2016/05/16 v3.12 Key value format for package options (HO)
(/usr/share/texlive/texmf-dist/tex/latex/graphics/keyval.sty
Package: keyval 2014/10/28 v1.15 key=value parser (DPC)
\KV@toks@=\toks21
)
(/usr/share/texlive/texmf-dist/tex/generic/oberdiek/ltxcmds.sty
Package: ltxcmds 2016/05/16 v1.23 LaTeX kernel commands for general use (HO)
)
(/usr/share/texlive/texmf-dist/tex/generic/oberdiek/kvsetkeys.sty
Package: kvsetkeys 2016/05/16 v1.17 Key value parser (HO)
(/usr/share/texlive/texmf-dist/tex/generic/oberdiek/infwarerr.sty
Package: infwarerr 2016/05/16 v1.4 Providing info/warning/error messages (HO)
)
(/usr/share/texlive/texmf-dist/tex/generic/oberdiek/etexcmds.sty
Package: etexcmds 2016/05/16 v1.6 Avoid name clashes with e-TeX commands (HO)
(/usr/share/texlive/texmf-dist/tex/generic/oberdiek/ifluatex.sty
Package: ifluatex 2016/05/16 v1.4 Provides the ifluatex switch (HO)
Package ifluatex Info: LuaTeX not detected.
)
Package etexcmds Info: Could not find \expanded.
(etexcmds) That can mean that you are not using pdfTeX 1.50 or
(etexcmds) that some package has redefined \expanded.
(etexcmds) In the latter case, load this package earlier.
))))
(/usr/share/texmf/tex/latex/tex-gyre/tgheros.sty
Package: tgheros 2009/09/27 v1.2 TeX Gyre Heros as default sans serif family
)
(/usr/share/texlive/texmf-dist/tex/latex/fncychap/fncychap.sty
Package: fncychap 2007/07/30 v1.34 LaTeX package (Revised chapters)
\RW=\skip46
\mylen=\skip47
\myhi=\skip48
\px=\skip49
\py=\skip50
\pyy=\skip51
\pxx=\skip52
\c@AlphaCnt=\count102
\c@AlphaDecCnt=\count103
) (./sphinx.sty
Package: sphinx 2021/01/27 v4.0.0 LaTeX package (Sphinx markup)
(/usr/share/texlive/texmf-dist/tex/latex/xcolor/xcolor.sty
Package: xcolor 2016/05/11 v2.12 LaTeX color extensions (UK)
(/usr/share/texlive/texmf-dist/tex/latex/graphics-cfg/color.cfg
File: color.cfg 2016/01/02 v1.6 sample color configuration
)
Package xcolor Info: Driver file: pdftex.def on input line 225.
(/usr/share/texlive/texmf-dist/tex/latex/graphics-def/pdftex.def
File: pdftex.def 2018/01/08 v1.0l Graphics/color driver for pdftex
)
Package xcolor Info: Model `cmy' substituted by `cmy0' on input line 1348.
Package xcolor Info: Model `hsb' substituted by `rgb' on input line 1352.
Package xcolor Info: Model `RGB' extended on input line 1364.
Package xcolor Info: Model `HTML' substituted by `rgb' on input line 1366.
Package xcolor Info: Model `Hsb' substituted by `hsb' on input line 1367.
Package xcolor Info: Model `tHsb' substituted by `hsb' on input line 1368.
Package xcolor Info: Model `HSB' substituted by `hsb' on input line 1369.
Package xcolor Info: Model `Gray' substituted by `gray' on input line 1370.
Package xcolor Info: Model `wave' substituted by `hsb' on input line 1371.
)
\sphinxverbatimsep=\dimen113
\sphinxverbatimborder=\dimen114
\sphinxshadowsep=\dimen115
\sphinxshadowsize=\dimen116
\sphinxshadowrule=\dimen117
\spx@notice@border=\dimen118
(./sphinxoptionshyperref.sty
File: sphinxoptionshyperref.sty 2021/01/27 hyperref
) (./sphinxoptionsgeometry.sty
File: sphinxoptionsgeometry.sty 2021/01/27 geometry
)
(/usr/share/texlive/texmf-dist/tex/latex/base/textcomp.sty
Package: textcomp 2017/04/05 v2.0i Standard LaTeX package
Package textcomp Info: Sub-encoding information:
(textcomp) 5 = only ISO-Adobe without \textcurrency
(textcomp) 4 = 5 + \texteuro
(textcomp) 3 = 4 + \textohm
(textcomp) 2 = 3 + \textestimated + \textcurrency
(textcomp) 1 = TS1 - \textcircled - \t
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Type <return> to proceed, S to scroll future error messages,
R to run without stopping, Q to run quietly,
I to insert something, E to edit your file,
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] | open | false | null | [] | null | 2 | "2021-09-14T23:19:54Z" | "2021-10-03T03:37:39Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
import numpy as np
df = pd.DataFrame([
{'category': 'Books', 'date_str': '2021-01-01', 'amount': 10.00},
{'category': 'Books', 'date_str': '2021-01-01', 'amount': 20.00},
{'category': 'Books', 'date_str': '2021-01-03', 'amount': 50.00},
{'category': 'Vacation', 'date_str': '2021-01-01', 'amount': 100.00},
{'category': 'Vacation', 'date_str': '2021-01-01', 'amount': 200.00},
{'category': 'Vacation', 'date_str': '2021-01-02', 'amount': 500.00},
])
df['date'] = pd.to_datetime(df['date_str'])
pivot = df.pivot_table(
index = ["category", "date"],
values = ["amount"],
aggfunc = [np.sum],
margins = True
)
```
### Issue Description
When executing the `pivot_table` function with `margins=True` on a dataset with dates that have been explicitly typed as `datetime`, a `FutureWarning` error is produced regarding inference of `datetime64[ns]`, and the pivot operation appears to try to aggregate the date-valued field, producing `NaT`.
```
<ipython-input-22-f8a00ede7c0c>:1: FutureWarning: Inferring datetime64[ns] from
data containing strings is deprecated and will be removed in a future version. To
retain the old behavior explicitly pass Series(data, dtype={value.dtype})
pivot = df.pivot_table(
```
I'm not sure why this warning is triggered given that the `date` field is explicitly typed (no inference) and fully populated (no missing date values).
Here's what the pivot produces, with the `NaT` on the bottom row under the `date` column:
```
sum
amount
category date
Books 2021-01-01 30.0
2021-01-03 50.0
Vacation 2021-01-01 300.0
2021-01-02 500.0
All NaT 880.0
```
### Expected Behavior
Absent a clear semantic for summing up date-valued fields, I would expect the pivot operation to ignore that field when calculating totals as part of the `margins` behavior, and no `FutureWarning` to be produced.
The expected resulting table would look like (note absent 'NaT` on the bottom `All` line):
```
sum
amount
category date
Books 2021-01-01 30.0
2021-01-03 50.0
Vacation 2021-01-01 300.0
2021-01-02 500.0
All 880.0
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.8.11.final.0
python-bits : 64
OS : Darwin
OS-release : 20.6.0
Version : Darwin Kernel Version 20.6.0: Wed Jun 23 00:26:31 PDT 2021; root:xnu-7195.141.2~5/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.19.2
pytz : 2020.1
dateutil : 2.8.1
pip : 21.1.2
setuptools : 57.0.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 1.3.6
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.18.1
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.2
numexpr : None
odfpy : None
openpyxl : 3.0.5
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 1.3.19
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
numba : None
</details>
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} | 1 | "2021-09-15T02:03:32Z" | "2021-09-15T23:55:09Z" | "2021-09-15T23:24:04Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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} | 0 | "2021-09-15T02:15:14Z" | "2021-09-15T15:01:42Z" | "2021-09-15T14:10:53Z" | MEMBER | null | ```
from asv_bench.benchmarks.groupby import *
self = GroupByMethods()
self.setup("int", "std", "transformation", 10)
%timeit self.time_dtype_as_field('int', 'std', 'transformation', 10)
325 µs ± 9.84 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) # <- PR
361 µs ± 2.05 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) # <- master
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} | 1 | "2021-09-15T03:22:31Z" | "2021-09-15T15:01:00Z" | "2021-09-15T12:48:54Z" | MEMBER | null | Follow-up to #43507 | {
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} | 2 | "2021-09-15T03:48:17Z" | "2021-09-15T15:02:00Z" | "2021-09-15T12:50:33Z" | MEMBER | null | ```
from asv_bench.benchmarks.groupby import *
self = Apply()
self.setup(4)
%timeit self.time_copy_function_multi_col(4)
451 ms ± 2.2 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) # <- PR
559 ms ± 1.35 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) # <- master
``` | {
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} | 0 | "2021-09-15T03:57:44Z" | "2021-09-15T20:55:31Z" | null | CONTRIBUTOR | null | Followups from #43338
- [ ] tests for `groupy.rolling.rank`
- [ ] `dense` ranking method impl
- [ ] add `expanding` rank to asvs
- [ ] unify separate tiebreakers dicts in aggregations.pyx and algos.pyx: https://github.com/pandas-dev/pandas/pull/43338#discussion_r708248202 | {
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] | closed | false | null | [] | null | 3 | "2021-09-15T04:37:19Z" | "2021-09-19T22:55:14Z" | "2021-09-19T22:55:14Z" | CONTRIBUTOR | null | ###
- [X] I have checked that the issue still exists on the latest versions of the docs on `master` [here](https://pandas.pydata.org/docs/dev/)
### Location of the documentation
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Categorical.html#pandas.Categorical
### Documentation problem
Argument `fastpath` is not documented.
### Suggested fix for documentation
All arguments to the function should be documented. `fastpath` is not currently documented even though it is part of the function signature. | {
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] | open | false | null | [] | null | 4 | "2021-09-15T08:26:53Z" | "2021-10-02T00:28:33Z" | null | NONE | null | ###
- [x] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
df = pd.read_csv('https://stepik.org/media/attachments/course/4852/titanic.csv')
dt = df.dtypes.value_counts()
print(dt)
print(dt.index)
print(dt['float64'])
print(dt['object'])
print(dt['int64'])
```
### Issue Description
I'm trying to get the number of columns of a particular data type. This code should work correctly, but most of times in crashed with KeyError on different keys. For example:
```python
int64 5
object 5
float64 2
dtype: int64
Index([int64, object, float64], dtype='object')
2
5
Traceback (most recent call last):
File "/home/kizhifox/coding/stepik/venv/lib/python3.8/site-packages/pandas/core/indexes/base.py", line 3361, in get_loc
return self._engine.get_loc(casted_key)
File "pandas/_libs/index.pyx", line 76, in pandas._libs.index.IndexEngine.get_loc
File "pandas/_libs/index.pyx", line 108, in pandas._libs.index.IndexEngine.get_loc
File "pandas/_libs/hashtable_class_helper.pxi", line 5198, in pandas._libs.hashtable.PyObjectHashTable.get_item
File "pandas/_libs/hashtable_class_helper.pxi", line 5206, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 'int64'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/kizhifox/coding/stepik/test.py", line 8, in <module>
print(dt['int64'])
File "/home/kizhifox/coding/stepik/venv/lib/python3.8/site-packages/pandas/core/series.py", line 942, in __getitem__
return self._get_value(key)
File "/home/kizhifox/coding/stepik/venv/lib/python3.8/site-packages/pandas/core/series.py", line 1051, in _get_value
loc = self.index.get_loc(label)
File "/home/kizhifox/coding/stepik/venv/lib/python3.8/site-packages/pandas/core/indexes/base.py", line 3363, in get_loc
raise KeyError(key) from err
KeyError: 'int64'
Process finished with exit code 1
```
I have also tried downloading the CSV file and using dt.get() to access the values, but that also didn't work.
### Expected Behavior
Expected output (approximately every 10th launch is displayed):
```python
int64 5
object 5
float64 2
dtype: int64
Index([int64, object, float64], dtype='object')
2
5
5
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.11.0-34-generic
Version : #36~20.04.1-Ubuntu SMP Fri Aug 27 08:06:32 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : ru_RU.UTF-8
LOCALE : ru_RU.UTF-8
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 20.0.2
setuptools : 44.0.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.27.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
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} | 2 | "2021-09-15T11:36:51Z" | "2021-09-15T12:33:24Z" | "2021-09-15T12:33:16Z" | NONE | null | I don't know if there is a way to generate a date range with month beginning dates instead of month ending. I know I could use time delta to modify the DatetimeIndex that I obtain below. However, I was wondering if there is some argument that can be passed while creating the date_range instance.
See below:
>>>pd.date_range(start='1/1/2018', end='08/08/2018',
freq='M')
DatetimeIndex(['2018-01-31', '2018-02-28', '2018-03-31', '2018-04-30',
'2018-05-31', '2018-06-30', '2018-07-31'],
dtype='datetime64[ns]', freq='M')
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I'm using a SQL Database, hence _read_sql_ uses [_SQLDatabase.has_table_](https://github.com/pandas-dev/pandas/blob/master/pandas/io/sql.py#L1726) method to determine whether or not a valid table name was provided as part of the sql argument.
The problem here is that the following line in the _has_table_ method requires a table schema name(if default schema table is not used)
`return insp.has_table(name, schema or self.meta.schema)`
but there is no schema name passed when instantiating the _SQLDatabase_ class nor is a schema name given when calling the _has_table_ method from _read_sql_.
In order to solve the bug the following could be done,
1. Add a _schema_ parameter to the read_sql method (similar to that of read_sql_table)
2. And then [this line](https://github.com/pandas-dev/pandas/blob/084c543bf9e70ed4f2ce1d4115b9959f7ae0c396/pandas/io/sql.py#L573) should be updated to this - `_is_table_name = pandas_sql.has_table(sql, schema)` | {
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} | 3 | "2021-09-15T15:50:37Z" | "2021-10-21T00:50:22Z" | "2021-10-21T00:50:22Z" | NONE | null | #### Is your feature request related to a problem?
We can avoid the materialization of `RangeIndex` when `sort_values` is invoked on it. The reason being RangeIndex is always sorted.
#### Describe the solution you'd like
```python
>>> import pandas as pd
>>> pd.__version__
'1.3.3'
>>> idx = pd.RangeIndex(0, 10, 1)
>>> idx
RangeIndex(start=0, stop=10, step=1)
>>> idx.sort_values(ascending=True)
Int64Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64') # Instead we should be returning RangeIndex(start=0, stop=10, step=1)
>>> idx.sort_values(ascending=False)
Int64Index([9, 8, 7, 6, 5, 4, 3, 2, 1, 0], dtype='int64') #Instead we can return RangeIndex(start=10-1, start=0-1, step=-1), see below
>>> pd.RangeIndex(10-1, 0-1, -1)._values
array([9, 8, 7, 6, 5, 4, 3, 2, 1, 0])
```
#### API breaking implications
This would break the expected return types of `Index` of `DataFrame` & `Series` in some operations, but would result in speedup of operation as we would not be materializing the `RangeIndex`.
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] | open | false | null | [] | null | 0 | "2021-09-15T18:15:18Z" | "2021-10-01T22:25:16Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
pd.read_sql('test_data', 'postgres:///db_name')
```
### Issue Description
This specific method wraps around the _read_sql_query_ and _read_sql_table_ methods, where _read_sql_ checks if the sql parameter contains a valid table name, if not it assumes that the sql parameter contains a sql query and routes the request to _read_sql_query_.
I'm using a SQL Database, hence _read_sql_ uses [_SQLDatabase.has_table_](https://github.com/pandas-dev/pandas/blob/master/pandas/io/sql.py#L1726) method to determine whether or not a valid table name was provided as part of the sql argument.
The problem here is that the following line in the _has_table_ method requires a table schema name(if default schema table is not used)
`return insp.has_table(name, schema or self.meta.schema)`
but there is no schema name passed when instantiating the _SQLDatabase_ class nor is a schema name given when calling the _has_table_ method from _read_sql_.
### Expected Behavior
`df = pd.read_sql('test_data', 'postgres:///db_name')` should be able to find the 'test_data' table that has a custom table schema.
in order to solve the bug the following could be done,
1. Add a _schema_ parameter to the read_sql method (similar to that of read_sql_table)
2. And then [this line](https://github.com/pandas-dev/pandas/blob/084c543bf9e70ed4f2ce1d4115b9959f7ae0c396/pandas/io/sql.py#L573) should be updated to this - `_is_table_name = pandas_sql.has_table(sql, schema)`
Happy to create a PR if agreed.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : None
python : 3.8.3.final.0
python-bits : 64
OS : Darwin
OS-release : 20.5.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 1.0.5
numpy : 1.18.5
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 49.2.0.post20200714
Cython : 0.29.21
pytest : 5.4.3
hypothesis : None
sphinx : 3.1.2
blosc : None
feather : None
xlsxwriter : 1.2.9
lxml.etree : 4.5.2
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.16.1
pandas_datareader: None
bs4 : 4.9.1
bottleneck : 1.3.2
fastparquet : None
gcsfs : None
lxml.etree : 4.5.2
matplotlib : 3.2.2
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.4
pandas_gbq : None
pyarrow : None
pytables : None
pytest : 5.4.3
pyxlsb : None
s3fs : None
scipy : 1.5.0
sqlalchemy : 1.3.18
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.2.9
numba : 0.50.1
</details>
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} | 0 | "2021-09-15T18:43:09Z" | "2021-09-21T12:14:17Z" | "2021-09-21T12:14:17Z" | CONTRIBUTOR | null | ```
/home/runner/work/pandas/pandas/asv_bench/benchmarks/algorithms.py:79: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.NumericIndex with the appropriate dtype instead.
"int": pd.Int64Index(np.arange(N)),
/home/runner/work/pandas/pandas/asv_bench/benchmarks/algorithms.py:80: FutureWarning: pandas.UInt64Index is deprecated and will be removed from pandas in a future version. Use pandas.NumericIndex with the appropriate dtype instead.
"uint": pd.UInt64Index(np.arange(N)),
/home/runner/work/pandas/pandas/asv_bench/benchmarks/algorithms.py:81: FutureWarning: pandas.Float64Index is deprecated and will be removed from pandas in a future version. Use pandas.NumericIndex with the appropriate dtype instead.
"float": pd.Float64Index(np.random.randn(N)),
For parameters: True, 'first', 'uint'
```
xref https://github.com/pandas-dev/pandas/pull/43028
cc @topper-123 | {
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] | open | false | null | [] | null | 0 | "2021-09-15T19:20:04Z" | "2021-10-01T22:26:08Z" | null | CONTRIBUTOR | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import numpy as np
import pandas as pd
s = pd.Series(
[1., 2., np.nan],
index=pd.DatetimeIndex(['NaT', '2015-02-08', 'NaT'])
)
s.idxmin(skipna=False)
```
### Issue Description
In the last few days something was merged that changed the dtype of `idxmax` when skipna is False and the index is a datetime. I noticed this while running the upstream dask tests.
### Expected Behavior
I would expect the dtype of `idxmax` and `idxmin` to match the dtype of the index (`NaT`). Instead I get a nan with dtype float.
Compare the output above to
```python
s.idxmin(skipna=True)
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 084c543bf9e70ed4f2ce1d4115b9959f7ae0c396
python : 3.9.7.final.0
python-bits : 64
OS : Linux
OS-release : 5.11.0-7633-generic
Version : #35~1630100930~20.04~ae2753e-Ubuntu SMP Mon Aug 30 18:23:52 UTC
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.4.0.dev0+700.g084c543bf9
numpy : 1.22.0.dev0+1046.gb892ed2c7
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : None
pytest : 6.2.5
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.27.0
pandas_datareader: 0.10.0
bs4 : None
bottleneck : None
fsspec : 2021.08.1+8.g0589358
fastparquet : 0.7.1
gcsfs : None
matplotlib : 3.4.3
numexpr : 2.7.3
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : 2021.08.1+5.gf9d83b7
scipy : 1.7.1
sqlalchemy : 1.3.23
tables : 3.6.1
tabulate : None
xarray : 0.19.0
xlrd : None
xlwt : None
numba : 0.53.1
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} | 7 | "2021-09-15T19:57:19Z" | "2021-09-16T22:59:28Z" | "2021-09-16T22:59:27Z" | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
d = DataFrame([1.0, 2.0])
d.corr(method='spearman')
```
### Issue Description
Calling the `corr` method of a `DataFrame` with `method='spearman'` produces a ValueError due to a buffer dtype mismatch on 32-bit platforms.
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/lib/python3.10/site-packages/pandas/core/frame.py", line 9376, in corr
correl = libalgos.nancorr_spearman(mat, minp=min_periods)
File "pandas/_libs/algos.pyx", line 415, in pandas._libs.algos.nancorr_spearman
File "pandas/_libs/algos.pyx", line 938, in pandas._libs.algos.rank_1d
ValueError: Buffer dtype mismatch, expected 'const intp_t' but got 'long long'
```
If I have some time, I’ll look into this further and try to offer a PR. The problem was discovered due to a failing test in `pingouin` (https://github.com/raphaelvallat/pingouin/issues/197).
I have reproduced this on both 32-bit x86 and 32-bit ARM. While my “installed versions” are those currently in Fedora Rawhide, including Pandas 1.3.0, I did build an RPM for Pandas 1.3.3 and reproduce with that too.
### Expected Behavior
```
0
0 1.0
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : f00ed8f47020034e752baf0250483053340971b0
python : 3.10.0.candidate.2
python-bits : 32
OS : Linux
OS-release : 5.13.14-200.fc34.x86_64
Version : #1 SMP Fri Sep 3 15:33:01 UTC 2021
machine : armv7l
processor : armv7l
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.0
numpy : 1.21.1
pytz : 2021.1
dateutil : 2.8.1
pip : None
setuptools : 57.4.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : 1.3.2
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.5.0b1
numexpr : 2.7.1
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.0
sqlalchemy : None
tables : 3.6.1
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
```
from dateutil import tz
import pandas as pd
from time import time
dates = pd.date_range('2010-01-01', periods=1000, tz=tz.tzutc())
index = pd.MultiIndex.from_product([range(100), dates])
index2 = index.copy()
%timeit index.equals(index2)
330 ms ± 6.44 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) # <- master
1.79 ms ± 7.4 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) # <- PR
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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} | 2 | "2021-09-15T23:01:56Z" | "2021-10-19T15:00:16Z" | "2021-10-19T15:00:16Z" | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
>>> import pandas as pd
>>> df = pd.DataFrame({'a': [1, 2, 3]})
>>> df.index = pd.RangeIndex(4, -1, -2)
>>> df
a
4 1
2 2
0 3
>>> df.sort_index()
a
0 3
2 2
4 1
>>> df.sort_index().index
Int64Index([0, 2, 4], dtype='int64')
>>> df.sort_index(ignore_index=True).index
RangeIndex(start=0, stop=3, step=1) #Index is being ignored.
>>> df.sort_index(ascending=False)
a
4 1
2 2
0 3
>>> df.sort_index(ascending=False, ignore_index=True)
a
4 1
2 2
0 3
>>> df.sort_index(ascending=False, ignore_index=True).index
RangeIndex(start=4, stop=-1, step=-2) # Index is not being ignored.
```
### Issue Description
In `DataFrame.sort_index`, looks like `ignore_index=True` is being adhered to only when there is a sorting taking place. This seems to be unexpected.
### Expected Behavior
The expected behavior for `ignore_index=True` is to always ignore the index irrespective of if there was a sorting performed or not.
### Installed Versions
<details>
>>> pd.show_versions()
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-76-generic
Version : #86-Ubuntu SMP Fri Jan 17 17:24:28 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : 0.29.24
pytest : 6.2.5
hypothesis : 6.21.3
sphinx : 4.2.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.27.0
pandas_datareader: None
bs4 : 4.10.0
bottleneck : None
fsspec : 2021.08.1
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 5.0.0
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : 0.53.1
>>>
</details>
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} | 0 | "2021-09-16T01:01:05Z" | "2021-09-16T17:51:53Z" | "2021-09-16T17:19:26Z" | MEMBER | null | Separate PR will get 1 out of JoinUnit.indexers. | {
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} | 7 | "2021-09-16T01:46:22Z" | "2021-10-31T14:58:46Z" | "2021-10-31T14:58:27Z" | CONTRIBUTOR | null | …me shifts
- [x] closes #41264
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
Tests added for issue: https://github.com/pandas-dev/pandas/issues/41264 | {
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## Steps to reproduce:
```python
>>> import json
>>> import pandas as pd
>>> s = '["http://www.example.com"]'
>>> json.loads(s)
['http://www.example.com'] # Proves the JSON is valid
>>> pd.read_json(s)
....
ValueError: Protocol not known: ["http
```
## Work around 1:
Write the string to a file.
```python
>>> with open('test.json', 'w') as f:
... f.write(s)
>>> pd.read_json('test.json')
0
0 http://www.example.com
```
## Work around 2:
Wrap the string into a file-like object.
```python
>>> import io
>>> pd.read_json(io.StringIO(s))
0
0 http://www.example.com
```
## Versions
pandas 1.3.3 on Windows
```python
>>> pd.show_versions()
```
```
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.9.7.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19043
machine : AMD64
processor : AMD64 Family 25 Model 33 Stepping 0, AuthenticAMD
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_Australia.1252
pandas : 1.3.3
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : 0.29.24
pytest : None
hypothesis : None
sphinx : 4.2.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.27.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 2021.08.1
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : 2.7.3
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : None
tables : 3.6.1
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
```
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} | 0 | "2021-09-16T02:42:11Z" | "2021-09-20T14:58:52Z" | "2021-09-20T14:58:52Z" | MEMBER | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
keys = ["e", "e"]
df = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})
result = pd.concat([df, df], axis=1, keys=keys)
```
### Issue Description
concat raises when all the indexes of `objs` argument are the same and there are duplicates in the `keys` argument.
### Expected Behavior
Not to raise.
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
</details>
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] | open | false | null | [] | null | 2 | "2021-09-16T06:10:01Z" | "2021-10-01T22:28:55Z" | null | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
import numpy as np
df = pd.DataFrame(index=pd.MultiIndex.from_product([list('ab'), list('cd'), list('e')]), columns=['Val'])
df.loc[np.s_[:,'c',:]]
```
### Issue Description
for versions later than 1.3, this selection will keep the second level in the index. But for versions earlier than 1.3, the 2nd level will be dropped:
### Expected Behavior
I've read the release notes of 1.3 but can't find a documentation about this. Is this a changed behavior?
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 7c48ff4409c622c582c56a5702373f726de08e96
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-156-generic
Version : #163-Ubuntu SMP Thu Aug 19 23:31:58 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.2.5
numpy : 1.20.3
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : 0.29.23
pytest : 6.2.4
hypothesis : None
sphinx : 4.1.2
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.2
html5lib : 1.1
pymysql : 0.9.3
psycopg2 : 2.8.6 (dt dec pq3 ext lo64)
jinja2 : 3.0.1
IPython : 7.27.0
pandas_datareader: 0.9.0
bs4 : 4.9.3
bottleneck : None
fsspec : 0.8.5
fastparquet : None
gcsfs : None
matplotlib : 3.3.3
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.5
pandas_gbq : None
pyarrow : 4.0.1
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.4.17
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : None
numba : 0.54.0
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-156-generic
Version : #163-Ubuntu SMP Thu Aug 19 23:31:58 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.3
numpy : 1.20.3
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : 0.29.23
pytest : 6.2.4
hypothesis : None
sphinx : 4.1.2
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.2
html5lib : 1.1
pymysql : 0.9.3
psycopg2 : 2.8.6 (dt dec pq3 ext lo64)
jinja2 : 3.0.1
IPython : 7.27.0
pandas_datareader: 0.9.0
bs4 : 4.9.3
bottleneck : None
fsspec : 0.8.5
fastparquet : None
gcsfs : None
matplotlib : 3.3.3
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.5
pandas_gbq : None
pyarrow : 4.0.1
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.4.17
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : None
numba : 0.54.0
</details>
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} | 1 | "2021-09-16T07:02:03Z" | "2021-09-16T07:36:01Z" | "2021-09-16T07:35:43Z" | NONE | null | ###
- [X] I have searched the [[pandas] tag](https://stackoverflow.com/questions/tagged/pandas) on StackOverflow for similar questions.
- [X] I have asked my usage related question on [StackOverflow](https://stackoverflow.com).
### Link to question on StackOverflow
https://stackoverflow.com/questions/69202964/i-am-unable-to-replace-a-special-character-with-0-and-then-in-return-replace-tha
### Question about pandas
Hi,
I need to replace '?' value with the mean/median value of my 'Price' column. I tried using fillna() but I am getting the above error. I am sharing the code below:
car.info()
[`**<class` 'pandas.core.frame.DataFrame'>
RangeIndex: 205 entries, 0 to 204
Data columns (total 26 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 symboling 205 non-null int64
1 normalized-losses 205 non-null object
2 make 205 non-null object
3 fuel-type 205 non-null object
4 aspiration 205 non-null object
5 num-of-doors 205 non-null object
6 body-style 205 non-null object
7 drive-wheels 205 non-null object
8 engine-location 205 non-null object
9 wheel-base 205 non-null float64
10 length 205 non-null float64
11 width 205 non-null float64
12 height 205 non-null float64
13 curb-weight 205 non-null int64
14 engine-type 205 non-null object
15 num-of-cylinders 205 non-null object
16 engine-size 205 non-null int64
17 fuel-system 205 non-null object
18 bore 205 non-null object
19 stroke 205 non-null object
20 compression-ratio 205 non-null float64
21 horsepower 205 non-null object
22 peak-rpm 205 non-null object
23 city-mpg 205 non-null int64
24 highway-mpg 205 non-null int64
25 price 205 non-null object
dtypes: float64(5), int64(5), object(16)
memory usage: 41.8+ [`[KB]**`]]
car['price'].replace({ "?": np.nan},inplace=True)
car['price'] = car.price.astype(float) # changing object datatype to float
car['price'][:15]
**13495.0
1 16500.0
2 16500.0
3 13950.0
4 17450.0
5 15250.0
6 17710.0
7 18920.0
8 23875.0
9 NaN
10 16430.0
11 16925.0
12 20970.0
13 21105.0
14 24565.0
Name: price, dtype: float64**
med_price = car.groupby(['make','aspiration'])['price'].agg(np.median)
car['price'].fillna(med_price,inplace=True)
car.head(15) # this throws the error mentioned above in the question,.
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} | 1 | "2021-09-16T10:24:14Z" | "2021-09-16T22:46:45Z" | "2021-09-16T22:46:40Z" | CONTRIBUTOR | null | - [ ] closes #xxxx
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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] | open | false | null | [] | null | 6 | "2021-09-16T12:58:29Z" | "2021-11-05T05:54:44Z" | null | CONTRIBUTOR | null | - [ ] closes #xxxx
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
Please take a look and let me know if things look fine, I'll make a whatsnew entry then :)
This PR has been made as per [this](https://github.com/pandas-dev/pandas/pull/43248#discussion_r701003907) suggestion by @attack68. | {
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} | 2 | "2021-09-16T13:16:54Z" | "2021-09-16T16:53:11Z" | "2021-09-16T13:28:00Z" | NONE | null | ###
- [X] I have read the [installation guide](https://pandas.pydata.org/pandas-docs/stable/getting_started/install.html#installing-pandas).
### Platform
Windows-10-10.0.19043-SP0
### Installation Method
pip install
### pandas Version
1.3.3
### Python Version
3.10(RC) - MS Store
### Installation Logs
<details>
> pip install pandas
Collecting pandas
Using cached pandas-1.3.3.tar.gz (4.7 MB)
Installing build dependencies ... error
ERROR: Command errored out with exit status 1:
command: 'C:\Users\Mohammad\AppData\Local\Microsoft\WindowsApps\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\python.exe' 'C:\Users\Mohammad\AppData\Local\Temp\pip-standalone-pip-wfs959uc\__env_pip__.zip\pip' install --ignore-installed --no-user --prefix 'C:\Users\Mohammad\AppData\Local\Temp\pip-build-env-dej0yus_\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=51.0.0' wheel 'Cython>=0.29.21,<3' 'numpy==1.17.3; python_version=='"'"'3.7'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.18.3; python_version=='"'"'3.8'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.3; python_version>='"'"'3.9'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.7'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.9'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"''
cwd: None
Complete output (877 lines):
Ignoring numpy: markers 'python_version == "3.7" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and (platform_machine != "arm64" or platform_system != "Darwin") and platform_machine != "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.7" and platform_machine == "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and platform_machine == "aarch64"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and platform_machine == "arm64" and platform_system == "Darwin"' don't match your environment
Ignoring numpy: markers 'python_version == "3.9" and platform_machine == "arm64" and platform_system == "Darwin"' don't match your environment
Collecting setuptools>=51.0.0
Using cached setuptools-58.0.4-py3-none-any.whl (816 kB)
Collecting wheel
Using cached wheel-0.37.0-py2.py3-none-any.whl (35 kB)
Collecting Cython<3,>=0.29.21
Using cached Cython-0.29.24-py2.py3-none-any.whl (979 kB)
Collecting numpy==1.19.3
Using cached numpy-1.19.3.zip (7.3 MB)
Installing build dependencies: started
Installing build dependencies: finished with status 'done'
Getting requirements to build wheel: started
Getting requirements to build wheel: finished with status 'done'
Preparing wheel metadata: started
Preparing wheel metadata: finished with status 'done'
Building wheels for collected packages: numpy
Building wheel for numpy (PEP 517): started
Building wheel for numpy (PEP 517): finished with status 'error'
ERROR: Command errored out with exit status 1:
command: 'C:\Users\Mohammad\AppData\Local\Microsoft\WindowsApps\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\python.exe' 'C:\Users\Mohammad\AppData\Local\Temp\tmpnqqfvm5__in_process.py' build_wheel 'C:\Users\Mohammad\AppData\Local\Temp\tmpf8w1yqv6'
cwd: C:\Users\Mohammad\AppData\Local\Temp\pip-install-h82rmjm2\numpy_afedde72f5784bcdbc43d901011395cf
Complete output (846 lines):
setup.py:67: RuntimeWarning: NumPy 1.19.3 may not yet support Python 3.10.
warnings.warn(
Running from numpy source directory.
C:\Users\Mohammad\AppData\Local\Temp\pip-install-h82rmjm2\numpy_afedde72f5784bcdbc43d901011395cf\tools\cythonize.py:67: DeprecationWarning: The distutils package is deprecated and slated for removal in Python 3.12. Use setuptools or check PEP 632 for potential alternatives
from distutils.version import LooseVersion
numpy/random\_bounded_integers.pxd.in has not changed
numpy/random\bit_generator.pyx has not changed
numpy/random\mtrand.pyx has not changed
Processing numpy/random\_bounded_integers.pyx
numpy/random\_bounded_integers.pyx.in has not changed
numpy/random\_common.pyx has not changed
numpy/random\_generator.pyx has not changed
numpy/random\_mt19937.pyx has not changed
numpy/random\_pcg64.pyx has not changed
numpy/random\_philox.pyx has not changed
numpy/random\_sfc64.pyx has not changed
Cythonizing sources
blas_opt_info:
blas_mkl_info:
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils
customize MSVCCompiler
libraries mkl_rt not found in ['C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\lib', 'C:\\', 'C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\libs']
NOT AVAILABLE
blis_info:
libraries blis not found in ['C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\lib', 'C:\\', 'C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\libs']
NOT AVAILABLE
openblas_info:
libraries openblas not found in ['C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\lib', 'C:\\', 'C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\libs']
get_default_fcompiler: matching types: '['gnu', 'intelv', 'absoft', 'compaqv', 'intelev', 'gnu95', 'g95', 'intelvem', 'intelem', 'flang']'
customize GnuFCompiler
Could not locate executable g77
Could not locate executable f77
customize IntelVisualFCompiler
Could not locate executable ifort
Could not locate executable ifl
customize AbsoftFCompiler
Could not locate executable f90
customize CompaqVisualFCompiler
Could not locate executable DF
customize IntelItaniumVisualFCompiler
Could not locate executable efl
customize Gnu95FCompiler
Found executable D:\MinGW-w64\bin\gfortran.exe
Using built-in specs.
COLLECT_GCC=D:\MinGW-w64\bin\gfortran.exe
COLLECT_LTO_WRAPPER=D:/MinGW-w64/bin/../libexec/gcc/x86_64-w64-mingw32/8.1.0/lto-wrapper.exe
Target: x86_64-w64-mingw32
Configured with: ../../../src/gcc-8.1.0/configure --host=x86_64-w64-mingw32 --build=x86_64-w64-mingw32 --target=x86_64-w64-mingw32 --prefix=/mingw64 --with-sysroot=/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64 --enable-shared --enable-static --disable-multilib --enable-languages=c,c++,fortran,lto --enable-libstdcxx-time=yes --enable-threads=posix --enable-libgomp --enable-libatomic --enable-lto --enable-graphite --enable-checking=release --enable-fully-dynamic-string --enable-version-specific-runtime-libs --disable-libstdcxx-pch --disable-libstdcxx-debug --enable-bootstrap --disable-rpath --disable-win32-registry --disable-nls --disable-werror --disable-symvers --with-gnu-as --with-gnu-ld --with-arch=nocona --with-tune=core2 --with-libiconv --with-system-zlib --with-gmp=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-mpfr=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-mpc=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-isl=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-pkgversion='x86_64-posix-seh-rev0, Built by MinGW-W64 project' --with-bugurl=https://sourceforge.net/projects/mingw-w64 CFLAGS='-O2 -pipe -fno-ident -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' CXXFLAGS='-O2 -pipe -fno-ident -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' CPPFLAGS=' -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' LDFLAGS='-pipe -fno-ident -L/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/lib -L/c/mingw810/prerequisites/x86_64-zlib-static/lib -L/c/mingw810/prerequisites/x86_64-w64-mingw32-static/lib '
Thread model: posix
gcc version 8.1.0 (x86_64-posix-seh-rev0, Built by MinGW-W64 project)
NOT AVAILABLE
atlas_3_10_blas_threads_info:
Setting PTATLAS=ATLAS
libraries tatlas not found in ['C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\lib', 'C:\\', 'C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\libs']
NOT AVAILABLE
atlas_3_10_blas_info:
libraries satlas not found in ['C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\lib', 'C:\\', 'C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\libs']
NOT AVAILABLE
atlas_blas_threads_info:
Setting PTATLAS=ATLAS
libraries ptf77blas,ptcblas,atlas not found in ['C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\lib', 'C:\\', 'C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\libs']
NOT AVAILABLE
atlas_blas_info:
libraries f77blas,cblas,atlas not found in ['C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\lib', 'C:\\', 'C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\libs']
NOT AVAILABLE
accelerate_info:
NOT AVAILABLE
C:\Users\Mohammad\AppData\Local\Temp\pip-install-h82rmjm2\numpy_afedde72f5784bcdbc43d901011395cf\numpy\distutils\system_info.py:1914: UserWarning:
Optimized (vendor) Blas libraries are not found.
Falls back to netlib Blas library which has worse performance.
A better performance should be easily gained by switching
Blas library.
if self._calc_info(blas):
blas_info:
libraries blas not found in ['C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\lib', 'C:\\', 'C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\libs']
NOT AVAILABLE
C:\Users\Mohammad\AppData\Local\Temp\pip-install-h82rmjm2\numpy_afedde72f5784bcdbc43d901011395cf\numpy\distutils\system_info.py:1914: UserWarning:
Blas (http://www.netlib.org/blas/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [blas]) or by setting
the BLAS environment variable.
if self._calc_info(blas):
blas_src_info:
NOT AVAILABLE
C:\Users\Mohammad\AppData\Local\Temp\pip-install-h82rmjm2\numpy_afedde72f5784bcdbc43d901011395cf\numpy\distutils\system_info.py:1914: UserWarning:
Blas (http://www.netlib.org/blas/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [blas_src]) or by setting
the BLAS_SRC environment variable.
if self._calc_info(blas):
NOT AVAILABLE
non-existing path in 'numpy\\distutils': 'site.cfg'
lapack_opt_info:
lapack_mkl_info:
libraries mkl_rt not found in ['C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\lib', 'C:\\', 'C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\libs']
NOT AVAILABLE
openblas_lapack_info:
libraries openblas not found in ['C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\lib', 'C:\\', 'C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\libs']
get_default_fcompiler: matching types: '['gnu', 'intelv', 'absoft', 'compaqv', 'intelev', 'gnu95', 'g95', 'intelvem', 'intelem', 'flang']'
customize GnuFCompiler
customize IntelVisualFCompiler
customize AbsoftFCompiler
customize CompaqVisualFCompiler
customize IntelItaniumVisualFCompiler
customize Gnu95FCompiler
Using built-in specs.
COLLECT_GCC=D:\MinGW-w64\bin\gfortran.exe
COLLECT_LTO_WRAPPER=D:/MinGW-w64/bin/../libexec/gcc/x86_64-w64-mingw32/8.1.0/lto-wrapper.exe
Target: x86_64-w64-mingw32
Configured with: ../../../src/gcc-8.1.0/configure --host=x86_64-w64-mingw32 --build=x86_64-w64-mingw32 --target=x86_64-w64-mingw32 --prefix=/mingw64 --with-sysroot=/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64 --enable-shared --enable-static --disable-multilib --enable-languages=c,c++,fortran,lto --enable-libstdcxx-time=yes --enable-threads=posix --enable-libgomp --enable-libatomic --enable-lto --enable-graphite --enable-checking=release --enable-fully-dynamic-string --enable-version-specific-runtime-libs --disable-libstdcxx-pch --disable-libstdcxx-debug --enable-bootstrap --disable-rpath --disable-win32-registry --disable-nls --disable-werror --disable-symvers --with-gnu-as --with-gnu-ld --with-arch=nocona --with-tune=core2 --with-libiconv --with-system-zlib --with-gmp=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-mpfr=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-mpc=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-isl=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-pkgversion='x86_64-posix-seh-rev0, Built by MinGW-W64 project' --with-bugurl=https://sourceforge.net/projects/mingw-w64 CFLAGS='-O2 -pipe -fno-ident -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' CXXFLAGS='-O2 -pipe -fno-ident -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' CPPFLAGS=' -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' LDFLAGS='-pipe -fno-ident -L/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/lib -L/c/mingw810/prerequisites/x86_64-zlib-static/lib -L/c/mingw810/prerequisites/x86_64-w64-mingw32-static/lib '
Thread model: posix
gcc version 8.1.0 (x86_64-posix-seh-rev0, Built by MinGW-W64 project)
NOT AVAILABLE
openblas_clapack_info:
libraries openblas,lapack not found in ['C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\lib', 'C:\\', 'C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\libs']
get_default_fcompiler: matching types: '['gnu', 'intelv', 'absoft', 'compaqv', 'intelev', 'gnu95', 'g95', 'intelvem', 'intelem', 'flang']'
customize GnuFCompiler
customize IntelVisualFCompiler
customize AbsoftFCompiler
customize CompaqVisualFCompiler
customize IntelItaniumVisualFCompiler
customize Gnu95FCompiler
Using built-in specs.
COLLECT_GCC=D:\MinGW-w64\bin\gfortran.exe
COLLECT_LTO_WRAPPER=D:/MinGW-w64/bin/../libexec/gcc/x86_64-w64-mingw32/8.1.0/lto-wrapper.exe
Target: x86_64-w64-mingw32
Configured with: ../../../src/gcc-8.1.0/configure --host=x86_64-w64-mingw32 --build=x86_64-w64-mingw32 --target=x86_64-w64-mingw32 --prefix=/mingw64 --with-sysroot=/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64 --enable-shared --enable-static --disable-multilib --enable-languages=c,c++,fortran,lto --enable-libstdcxx-time=yes --enable-threads=posix --enable-libgomp --enable-libatomic --enable-lto --enable-graphite --enable-checking=release --enable-fully-dynamic-string --enable-version-specific-runtime-libs --disable-libstdcxx-pch --disable-libstdcxx-debug --enable-bootstrap --disable-rpath --disable-win32-registry --disable-nls --disable-werror --disable-symvers --with-gnu-as --with-gnu-ld --with-arch=nocona --with-tune=core2 --with-libiconv --with-system-zlib --with-gmp=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-mpfr=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-mpc=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-isl=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-pkgversion='x86_64-posix-seh-rev0, Built by MinGW-W64 project' --with-bugurl=https://sourceforge.net/projects/mingw-w64 CFLAGS='-O2 -pipe -fno-ident -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' CXXFLAGS='-O2 -pipe -fno-ident -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' CPPFLAGS=' -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' LDFLAGS='-pipe -fno-ident -L/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/lib -L/c/mingw810/prerequisites/x86_64-zlib-static/lib -L/c/mingw810/prerequisites/x86_64-w64-mingw32-static/lib '
Thread model: posix
gcc version 8.1.0 (x86_64-posix-seh-rev0, Built by MinGW-W64 project)
NOT AVAILABLE
flame_info:
libraries flame not found in ['C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\lib', 'C:\\', 'C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\libs']
NOT AVAILABLE
atlas_3_10_threads_info:
Setting PTATLAS=ATLAS
libraries lapack_atlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\lib
libraries tatlas,tatlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\lib
libraries lapack_atlas not found in C:\
libraries tatlas,tatlas not found in C:\
libraries lapack_atlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\libs
libraries tatlas,tatlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\libs
<class 'numpy.distutils.system_info.atlas_3_10_threads_info'>
NOT AVAILABLE
atlas_3_10_info:
libraries lapack_atlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\lib
libraries satlas,satlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\lib
libraries lapack_atlas not found in C:\
libraries satlas,satlas not found in C:\
libraries lapack_atlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\libs
libraries satlas,satlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\libs
<class 'numpy.distutils.system_info.atlas_3_10_info'>
NOT AVAILABLE
atlas_threads_info:
Setting PTATLAS=ATLAS
libraries lapack_atlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\lib
libraries ptf77blas,ptcblas,atlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\lib
libraries lapack_atlas not found in C:\
libraries ptf77blas,ptcblas,atlas not found in C:\
libraries lapack_atlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\libs
libraries ptf77blas,ptcblas,atlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\libs
<class 'numpy.distutils.system_info.atlas_threads_info'>
NOT AVAILABLE
atlas_info:
libraries lapack_atlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\lib
libraries f77blas,cblas,atlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\lib
libraries lapack_atlas not found in C:\
libraries f77blas,cblas,atlas not found in C:\
libraries lapack_atlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\libs
libraries f77blas,cblas,atlas not found in C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\libs
<class 'numpy.distutils.system_info.atlas_info'>
NOT AVAILABLE
lapack_info:
libraries lapack not found in ['C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\lib', 'C:\\', 'C:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\\libs']
NOT AVAILABLE
C:\Users\Mohammad\AppData\Local\Temp\pip-install-h82rmjm2\numpy_afedde72f5784bcdbc43d901011395cf\numpy\distutils\system_info.py:1748: UserWarning:
Lapack (http://www.netlib.org/lapack/) libraries not found.
Directories to search for the libraries can be specified in the
numpy/distutils/site.cfg file (section [lapack]) or by setting
the LAPACK environment variable.
return getattr(self, '_calc_info_{}'.format(name))()
lapack_src_info:
NOT AVAILABLE
C:\Users\Mohammad\AppData\Local\Temp\pip-install-h82rmjm2\numpy_afedde72f5784bcdbc43d901011395cf\numpy\distutils\system_info.py:1748: UserWarning:
Lapack (http://www.netlib.org/lapack/) sources not found.
Directories to search for the sources can be specified in the
numpy/distutils/site.cfg file (section [lapack_src]) or by setting
the LAPACK_SRC environment variable.
return getattr(self, '_calc_info_{}'.format(name))()
NOT AVAILABLE
numpy_linalg_lapack_lite:
FOUND:
language = c
define_macros = [('HAVE_BLAS_ILP64', None), ('BLAS_SYMBOL_SUFFIX', '64_')]
C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\lib\distutils\dist.py:274: UserWarning: Unknown distribution option: 'define_macros'
warnings.warn(msg)
running bdist_wheel
running build
running config_cc
unifing config_cc, config, build_clib, build_ext, build commands --compiler options
running config_fc
unifing config_fc, config, build_clib, build_ext, build commands --fcompiler options
running build_src
build_src
building py_modules sources
building library "npymath" sources
Using built-in specs.
COLLECT_GCC=D:\MinGW-w64\bin\gfortran.exe
COLLECT_LTO_WRAPPER=D:/MinGW-w64/bin/../libexec/gcc/x86_64-w64-mingw32/8.1.0/lto-wrapper.exe
Target: x86_64-w64-mingw32
Configured with: ../../../src/gcc-8.1.0/configure --host=x86_64-w64-mingw32 --build=x86_64-w64-mingw32 --target=x86_64-w64-mingw32 --prefix=/mingw64 --with-sysroot=/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64 --enable-shared --enable-static --disable-multilib --enable-languages=c,c++,fortran,lto --enable-libstdcxx-time=yes --enable-threads=posix --enable-libgomp --enable-libatomic --enable-lto --enable-graphite --enable-checking=release --enable-fully-dynamic-string --enable-version-specific-runtime-libs --disable-libstdcxx-pch --disable-libstdcxx-debug --enable-bootstrap --disable-rpath --disable-win32-registry --disable-nls --disable-werror --disable-symvers --with-gnu-as --with-gnu-ld --with-arch=nocona --with-tune=core2 --with-libiconv --with-system-zlib --with-gmp=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-mpfr=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-mpc=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-isl=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-pkgversion='x86_64-posix-seh-rev0, Built by MinGW-W64 project' --with-bugurl=https://sourceforge.net/projects/mingw-w64 CFLAGS='-O2 -pipe -fno-ident -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' CXXFLAGS='-O2 -pipe -fno-ident -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' CPPFLAGS=' -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' LDFLAGS='-pipe -fno-ident -L/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/lib -L/c/mingw810/prerequisites/x86_64-zlib-static/lib -L/c/mingw810/prerequisites/x86_64-w64-mingw32-static/lib '
Thread model: posix
gcc version 8.1.0 (x86_64-posix-seh-rev0, Built by MinGW-W64 project)
Using built-in specs.
COLLECT_GCC=D:\MinGW-w64\bin\gfortran.exe
COLLECT_LTO_WRAPPER=D:/MinGW-w64/bin/../libexec/gcc/x86_64-w64-mingw32/8.1.0/lto-wrapper.exe
Target: x86_64-w64-mingw32
Configured with: ../../../src/gcc-8.1.0/configure --host=x86_64-w64-mingw32 --build=x86_64-w64-mingw32 --target=x86_64-w64-mingw32 --prefix=/mingw64 --with-sysroot=/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64 --enable-shared --enable-static --disable-multilib --enable-languages=c,c++,fortran,lto --enable-libstdcxx-time=yes --enable-threads=posix --enable-libgomp --enable-libatomic --enable-lto --enable-graphite --enable-checking=release --enable-fully-dynamic-string --enable-version-specific-runtime-libs --disable-libstdcxx-pch --disable-libstdcxx-debug --enable-bootstrap --disable-rpath --disable-win32-registry --disable-nls --disable-werror --disable-symvers --with-gnu-as --with-gnu-ld --with-arch=nocona --with-tune=core2 --with-libiconv --with-system-zlib --with-gmp=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-mpfr=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-mpc=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-isl=/c/mingw810/prerequisites/x86_64-w64-mingw32-static --with-pkgversion='x86_64-posix-seh-rev0, Built by MinGW-W64 project' --with-bugurl=https://sourceforge.net/projects/mingw-w64 CFLAGS='-O2 -pipe -fno-ident -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' CXXFLAGS='-O2 -pipe -fno-ident -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' CPPFLAGS=' -I/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/include -I/c/mingw810/prerequisites/x86_64-zlib-static/include -I/c/mingw810/prerequisites/x86_64-w64-mingw32-static/include' LDFLAGS='-pipe -fno-ident -L/c/mingw810/x86_64-810-posix-seh-rt_v6-rev0/mingw64/opt/lib -L/c/mingw810/prerequisites/x86_64-zlib-static/lib -L/c/mingw810/prerequisites/x86_64-w64-mingw32-static/lib '
Thread model: posix
gcc version 8.1.0 (x86_64-posix-seh-rev0, Built by MinGW-W64 project)
adding 'build\src.win-amd64-3.10\numpy\core\src\npymath' to include_dirs.
None - nothing done with h_files = ['build\\src.win-amd64-3.10\\numpy\\core\\src\\npymath\\npy_math_internal.h']
building library "npysort" sources
adding 'build\src.win-amd64-3.10\numpy\core\src\common' to include_dirs.
None - nothing done with h_files = ['build\\src.win-amd64-3.10\\numpy\\core\\src\\common\\npy_sort.h', 'build\\src.win-amd64-3.10\\numpy\\core\\src\\common\\npy_partition.h', 'build\\src.win-amd64-3.10\\numpy\\core\\src\\common\\npy_binsearch.h']
building library "npyrandom" sources
building extension "numpy.core._multiarray_tests" sources
building extension "numpy.core._multiarray_umath" sources
adding 'build\src.win-amd64-3.10\numpy\core\src\umath' to include_dirs.
adding 'build\src.win-amd64-3.10\numpy\core\src\npymath' to include_dirs.
adding 'build\src.win-amd64-3.10\numpy\core\src\common' to include_dirs.
numpy.core - nothing done with h_files = ['build\\src.win-amd64-3.10\\numpy\\core\\src\\umath\\funcs.inc', 'build\\src.win-amd64-3.10\\numpy\\core\\src\\umath\\simd.inc', 'build\\src.win-amd64-3.10\\numpy\\core\\src\\umath\\loops.h', 'build\\src.win-amd64-3.10\\numpy\\core\\src\\umath\\matmul.h', 'build\\src.win-amd64-3.10\\numpy\\core\\src\\umath\\clip.h', 'build\\src.win-amd64-3.10\\numpy\\core\\src\\npymath\\npy_math_internal.h', 'build\\src.win-amd64-3.10\\numpy\\core\\src\\common\\templ_common.h', 'build\\src.win-amd64-3.10\\numpy\\core\\include/numpy\\config.h', 'build\\src.win-amd64-3.10\\numpy\\core\\include/numpy\\_numpyconfig.h', 'build\\src.win-amd64-3.10\\numpy\\core\\include/numpy\\__multiarray_api.h', 'build\\src.win-amd64-3.10\\numpy\\core\\include/numpy\\__ufunc_api.h']
building extension "numpy.core._umath_tests" sources
building extension "numpy.core._rational_tests" sources
building extension "numpy.core._struct_ufunc_tests" sources
building extension "numpy.core._operand_flag_tests" sources
building extension "numpy.fft._pocketfft_internal" sources
building extension "numpy.linalg.lapack_lite" sources
### Warning: Using unoptimized lapack ###
building extension "numpy.linalg._umath_linalg" sources
### Warning: Using unoptimized lapack ###
building extension "numpy.random._mt19937" sources
building extension "numpy.random._philox" sources
building extension "numpy.random._pcg64" sources
building extension "numpy.random._sfc64" sources
building extension "numpy.random._common" sources
building extension "numpy.random.bit_generator" sources
building extension "numpy.random._generator" sources
building extension "numpy.random._bounded_integers" sources
building extension "numpy.random.mtrand" sources
building data_files sources
build_src: building npy-pkg config files
running build_py
creating build\lib.win-amd64-3.10
creating build\lib.win-amd64-3.10\numpy
copying numpy\conftest.py -> build\lib.win-amd64-3.10\numpy
copying numpy\ctypeslib.py -> build\lib.win-amd64-3.10\numpy
copying numpy\dual.py -> build\lib.win-amd64-3.10\numpy
copying numpy\matlib.py -> build\lib.win-amd64-3.10\numpy
copying numpy\setup.py -> build\lib.win-amd64-3.10\numpy
copying numpy\version.py -> build\lib.win-amd64-3.10\numpy
copying numpy\_distributor_init.py -> build\lib.win-amd64-3.10\numpy
copying numpy\_globals.py -> build\lib.win-amd64-3.10\numpy
copying numpy\_pytesttester.py -> build\lib.win-amd64-3.10\numpy
copying numpy\__init__.py -> build\lib.win-amd64-3.10\numpy
copying build\src.win-amd64-3.10\numpy\__config__.py -> build\lib.win-amd64-3.10\numpy
creating build\lib.win-amd64-3.10\numpy\compat
copying numpy\compat\py3k.py -> build\lib.win-amd64-3.10\numpy\compat
copying numpy\compat\setup.py -> build\lib.win-amd64-3.10\numpy\compat
copying numpy\compat\_inspect.py -> build\lib.win-amd64-3.10\numpy\compat
copying numpy\compat\__init__.py -> build\lib.win-amd64-3.10\numpy\compat
creating build\lib.win-amd64-3.10\numpy\compat\tests
copying numpy\compat\tests\test_compat.py -> build\lib.win-amd64-3.10\numpy\compat\tests
copying numpy\compat\tests\__init__.py -> build\lib.win-amd64-3.10\numpy\compat\tests
creating build\lib.win-amd64-3.10\numpy\core
copying numpy\core\arrayprint.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\cversions.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\defchararray.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\einsumfunc.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\fromnumeric.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\function_base.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\getlimits.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\machar.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\memmap.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\multiarray.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\numeric.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\numerictypes.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\overrides.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\records.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\setup.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\setup_common.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\shape_base.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\umath.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\umath_tests.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\_add_newdocs.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\_asarray.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\_dtype.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\_dtype_ctypes.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\_exceptions.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\_internal.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\_methods.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\_string_helpers.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\_type_aliases.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\_ufunc_config.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\__init__.py -> build\lib.win-amd64-3.10\numpy\core
copying numpy\core\code_generators\generate_numpy_api.py -> build\lib.win-amd64-3.10\numpy\core
creating build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_abc.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_api.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_arrayprint.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_conversion_utils.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_cpu_features.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_datetime.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_defchararray.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_deprecations.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_dtype.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_einsum.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_errstate.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_extint128.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_function_base.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_getlimits.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_half.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_indexerrors.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_indexing.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_item_selection.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_longdouble.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_machar.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_memmap.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_mem_overlap.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_multiarray.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_nditer.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_numeric.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_numerictypes.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_overrides.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_print.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_protocols.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_records.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_regression.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_scalarbuffer.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_scalarinherit.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_scalarmath.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_scalarprint.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_scalar_ctors.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_scalar_methods.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_shape_base.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_ufunc.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_umath.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_umath_accuracy.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_umath_complex.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test_unicode.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\test__exceptions.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\_locales.py -> build\lib.win-amd64-3.10\numpy\core\tests
copying numpy\core\tests\__init__.py -> build\lib.win-amd64-3.10\numpy\core\tests
creating build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\ccompiler.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\conv_template.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\core.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\cpuinfo.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\exec_command.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\extension.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\from_template.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\intelccompiler.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\lib2def.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\line_endings.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\log.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\mingw32ccompiler.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\misc_util.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\msvc9compiler.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\msvccompiler.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\npy_pkg_config.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\numpy_distribution.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\pathccompiler.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\setup.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\system_info.py -> build\lib.win-amd64-3.10\numpy\distutils
copying numpy\distutils\unixccompiler.py -> build\lib.win-amd64-3.10\numpy\distutils
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copying numpy\distutils\__init__.py -> build\lib.win-amd64-3.10\numpy\distutils
copying build\src.win-amd64-3.10\numpy\distutils\__config__.py -> build\lib.win-amd64-3.10\numpy\distutils
creating build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\autodist.py -> build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\bdist_rpm.py -> build\lib.win-amd64-3.10\numpy\distutils\command
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copying numpy\distutils\command\build_clib.py -> build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\build_ext.py -> build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\build_py.py -> build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\build_scripts.py -> build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\build_src.py -> build\lib.win-amd64-3.10\numpy\distutils\command
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copying numpy\distutils\command\config_compiler.py -> build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\develop.py -> build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\egg_info.py -> build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\install.py -> build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\install_clib.py -> build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\install_data.py -> build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\install_headers.py -> build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\sdist.py -> build\lib.win-amd64-3.10\numpy\distutils\command
copying numpy\distutils\command\__init__.py -> build\lib.win-amd64-3.10\numpy\distutils\command
creating build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\absoft.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\compaq.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\environment.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\g95.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\gnu.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\hpux.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\ibm.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\intel.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\lahey.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\mips.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\nag.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\none.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\nv.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\pathf95.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\pg.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\sun.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\vast.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
copying numpy\distutils\fcompiler\__init__.py -> build\lib.win-amd64-3.10\numpy\distutils\fcompiler
creating build\lib.win-amd64-3.10\numpy\distutils\tests
copying numpy\distutils\tests\test_exec_command.py -> build\lib.win-amd64-3.10\numpy\distutils\tests
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copying numpy\distutils\tests\test_fcompiler_gnu.py -> build\lib.win-amd64-3.10\numpy\distutils\tests
copying numpy\distutils\tests\test_fcompiler_intel.py -> build\lib.win-amd64-3.10\numpy\distutils\tests
copying numpy\distutils\tests\test_fcompiler_nagfor.py -> build\lib.win-amd64-3.10\numpy\distutils\tests
copying numpy\distutils\tests\test_from_template.py -> build\lib.win-amd64-3.10\numpy\distutils\tests
copying numpy\distutils\tests\test_mingw32ccompiler.py -> build\lib.win-amd64-3.10\numpy\distutils\tests
copying numpy\distutils\tests\test_misc_util.py -> build\lib.win-amd64-3.10\numpy\distutils\tests
copying numpy\distutils\tests\test_npy_pkg_config.py -> build\lib.win-amd64-3.10\numpy\distutils\tests
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creating build\lib.win-amd64-3.10\numpy\doc
copying numpy\doc\basics.py -> build\lib.win-amd64-3.10\numpy\doc
copying numpy\doc\broadcasting.py -> build\lib.win-amd64-3.10\numpy\doc
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copying numpy\doc\constants.py -> build\lib.win-amd64-3.10\numpy\doc
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copying numpy\doc\dispatch.py -> build\lib.win-amd64-3.10\numpy\doc
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copying numpy\doc\misc.py -> build\lib.win-amd64-3.10\numpy\doc
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copying numpy\doc\ufuncs.py -> build\lib.win-amd64-3.10\numpy\doc
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creating build\lib.win-amd64-3.10\numpy\f2py
copying numpy\f2py\auxfuncs.py -> build\lib.win-amd64-3.10\numpy\f2py
copying numpy\f2py\capi_maps.py -> build\lib.win-amd64-3.10\numpy\f2py
copying numpy\f2py\cb_rules.py -> build\lib.win-amd64-3.10\numpy\f2py
copying numpy\f2py\cfuncs.py -> build\lib.win-amd64-3.10\numpy\f2py
copying numpy\f2py\common_rules.py -> build\lib.win-amd64-3.10\numpy\f2py
copying numpy\f2py\crackfortran.py -> build\lib.win-amd64-3.10\numpy\f2py
copying numpy\f2py\diagnose.py -> build\lib.win-amd64-3.10\numpy\f2py
copying numpy\f2py\f2py2e.py -> build\lib.win-amd64-3.10\numpy\f2py
copying numpy\f2py\f2py_testing.py -> build\lib.win-amd64-3.10\numpy\f2py
copying numpy\f2py\f90mod_rules.py -> build\lib.win-amd64-3.10\numpy\f2py
copying numpy\f2py\func2subr.py -> build\lib.win-amd64-3.10\numpy\f2py
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copying numpy\f2py\setup.py -> build\lib.win-amd64-3.10\numpy\f2py
copying numpy\f2py\use_rules.py -> build\lib.win-amd64-3.10\numpy\f2py
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copying numpy\f2py\__main__.py -> build\lib.win-amd64-3.10\numpy\f2py
copying numpy\f2py\__version__.py -> build\lib.win-amd64-3.10\numpy\f2py
creating build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_array_from_pyobj.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_assumed_shape.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_block_docstring.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_callback.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_common.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_compile_function.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_crackfortran.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_kind.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_mixed.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_parameter.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_quoted_character.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
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copying numpy\f2py\tests\test_return_character.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_return_complex.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_return_integer.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_return_logical.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_return_real.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_semicolon_split.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_size.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\test_string.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
copying numpy\f2py\tests\util.py -> build\lib.win-amd64-3.10\numpy\f2py\tests
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creating build\lib.win-amd64-3.10\numpy\fft
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copying numpy\fft\setup.py -> build\lib.win-amd64-3.10\numpy\fft
copying numpy\fft\_pocketfft.py -> build\lib.win-amd64-3.10\numpy\fft
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creating build\lib.win-amd64-3.10\numpy\fft\tests
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copying numpy\fft\tests\test_pocketfft.py -> build\lib.win-amd64-3.10\numpy\fft\tests
copying numpy\fft\tests\__init__.py -> build\lib.win-amd64-3.10\numpy\fft\tests
creating build\lib.win-amd64-3.10\numpy\lib
copying numpy\lib\arraypad.py -> build\lib.win-amd64-3.10\numpy\lib
copying numpy\lib\arraysetops.py -> build\lib.win-amd64-3.10\numpy\lib
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copying numpy\lib\financial.py -> build\lib.win-amd64-3.10\numpy\lib
copying numpy\lib\format.py -> build\lib.win-amd64-3.10\numpy\lib
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copying numpy\lib\nanfunctions.py -> build\lib.win-amd64-3.10\numpy\lib
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copying numpy\lib\polynomial.py -> build\lib.win-amd64-3.10\numpy\lib
copying numpy\lib\recfunctions.py -> build\lib.win-amd64-3.10\numpy\lib
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copying numpy\lib\stride_tricks.py -> build\lib.win-amd64-3.10\numpy\lib
copying numpy\lib\twodim_base.py -> build\lib.win-amd64-3.10\numpy\lib
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copying numpy\lib\ufunclike.py -> build\lib.win-amd64-3.10\numpy\lib
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creating build\lib.win-amd64-3.10\numpy\lib\tests
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copying numpy\lib\tests\test_arrayterator.py -> build\lib.win-amd64-3.10\numpy\lib\tests
copying numpy\lib\tests\test_financial.py -> build\lib.win-amd64-3.10\numpy\lib\tests
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copying numpy\lib\tests\test_function_base.py -> build\lib.win-amd64-3.10\numpy\lib\tests
copying numpy\lib\tests\test_histograms.py -> build\lib.win-amd64-3.10\numpy\lib\tests
copying numpy\lib\tests\test_index_tricks.py -> build\lib.win-amd64-3.10\numpy\lib\tests
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copying numpy\lib\tests\test_packbits.py -> build\lib.win-amd64-3.10\numpy\lib\tests
copying numpy\lib\tests\test_polynomial.py -> build\lib.win-amd64-3.10\numpy\lib\tests
copying numpy\lib\tests\test_recfunctions.py -> build\lib.win-amd64-3.10\numpy\lib\tests
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copying numpy\lib\tests\test_shape_base.py -> build\lib.win-amd64-3.10\numpy\lib\tests
copying numpy\lib\tests\test_stride_tricks.py -> build\lib.win-amd64-3.10\numpy\lib\tests
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copying numpy\lib\tests\test_type_check.py -> build\lib.win-amd64-3.10\numpy\lib\tests
copying numpy\lib\tests\test_ufunclike.py -> build\lib.win-amd64-3.10\numpy\lib\tests
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creating build\lib.win-amd64-3.10\numpy\linalg
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creating build\lib.win-amd64-3.10\numpy\linalg\tests
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copying numpy\linalg\tests\test_regression.py -> build\lib.win-amd64-3.10\numpy\linalg\tests
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creating build\lib.win-amd64-3.10\numpy\ma
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creating build\lib.win-amd64-3.10\numpy\ma\tests
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copying numpy\ma\tests\test_mrecords.py -> build\lib.win-amd64-3.10\numpy\ma\tests
copying numpy\ma\tests\test_old_ma.py -> build\lib.win-amd64-3.10\numpy\ma\tests
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creating build\lib.win-amd64-3.10\numpy\matrixlib
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creating build\lib.win-amd64-3.10\numpy\matrixlib\tests
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creating build\lib.win-amd64-3.10\numpy\polynomial
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copying numpy\polynomial\hermite.py -> build\lib.win-amd64-3.10\numpy\polynomial
copying numpy\polynomial\hermite_e.py -> build\lib.win-amd64-3.10\numpy\polynomial
copying numpy\polynomial\laguerre.py -> build\lib.win-amd64-3.10\numpy\polynomial
copying numpy\polynomial\legendre.py -> build\lib.win-amd64-3.10\numpy\polynomial
copying numpy\polynomial\polynomial.py -> build\lib.win-amd64-3.10\numpy\polynomial
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copying numpy\polynomial\_polybase.py -> build\lib.win-amd64-3.10\numpy\polynomial
copying numpy\polynomial\__init__.py -> build\lib.win-amd64-3.10\numpy\polynomial
creating build\lib.win-amd64-3.10\numpy\polynomial\tests
copying numpy\polynomial\tests\test_chebyshev.py -> build\lib.win-amd64-3.10\numpy\polynomial\tests
copying numpy\polynomial\tests\test_classes.py -> build\lib.win-amd64-3.10\numpy\polynomial\tests
copying numpy\polynomial\tests\test_hermite.py -> build\lib.win-amd64-3.10\numpy\polynomial\tests
copying numpy\polynomial\tests\test_hermite_e.py -> build\lib.win-amd64-3.10\numpy\polynomial\tests
copying numpy\polynomial\tests\test_laguerre.py -> build\lib.win-amd64-3.10\numpy\polynomial\tests
copying numpy\polynomial\tests\test_legendre.py -> build\lib.win-amd64-3.10\numpy\polynomial\tests
copying numpy\polynomial\tests\test_polynomial.py -> build\lib.win-amd64-3.10\numpy\polynomial\tests
copying numpy\polynomial\tests\test_polyutils.py -> build\lib.win-amd64-3.10\numpy\polynomial\tests
copying numpy\polynomial\tests\test_printing.py -> build\lib.win-amd64-3.10\numpy\polynomial\tests
copying numpy\polynomial\tests\__init__.py -> build\lib.win-amd64-3.10\numpy\polynomial\tests
creating build\lib.win-amd64-3.10\numpy\random
copying numpy\random\setup.py -> build\lib.win-amd64-3.10\numpy\random
copying numpy\random\_pickle.py -> build\lib.win-amd64-3.10\numpy\random
copying numpy\random\__init__.py -> build\lib.win-amd64-3.10\numpy\random
creating build\lib.win-amd64-3.10\numpy\random\tests
copying numpy\random\tests\test_direct.py -> build\lib.win-amd64-3.10\numpy\random\tests
copying numpy\random\tests\test_extending.py -> build\lib.win-amd64-3.10\numpy\random\tests
copying numpy\random\tests\test_generator_mt19937.py -> build\lib.win-amd64-3.10\numpy\random\tests
copying numpy\random\tests\test_generator_mt19937_regressions.py -> build\lib.win-amd64-3.10\numpy\random\tests
copying numpy\random\tests\test_random.py -> build\lib.win-amd64-3.10\numpy\random\tests
copying numpy\random\tests\test_randomstate.py -> build\lib.win-amd64-3.10\numpy\random\tests
copying numpy\random\tests\test_randomstate_regression.py -> build\lib.win-amd64-3.10\numpy\random\tests
copying numpy\random\tests\test_regression.py -> build\lib.win-amd64-3.10\numpy\random\tests
copying numpy\random\tests\test_seed_sequence.py -> build\lib.win-amd64-3.10\numpy\random\tests
copying numpy\random\tests\test_smoke.py -> build\lib.win-amd64-3.10\numpy\random\tests
copying numpy\random\tests\__init__.py -> build\lib.win-amd64-3.10\numpy\random\tests
creating build\lib.win-amd64-3.10\numpy\testing
copying numpy\testing\print_coercion_tables.py -> build\lib.win-amd64-3.10\numpy\testing
copying numpy\testing\setup.py -> build\lib.win-amd64-3.10\numpy\testing
copying numpy\testing\utils.py -> build\lib.win-amd64-3.10\numpy\testing
copying numpy\testing\__init__.py -> build\lib.win-amd64-3.10\numpy\testing
creating build\lib.win-amd64-3.10\numpy\testing\_private
copying numpy\testing\_private\decorators.py -> build\lib.win-amd64-3.10\numpy\testing\_private
copying numpy\testing\_private\noseclasses.py -> build\lib.win-amd64-3.10\numpy\testing\_private
copying numpy\testing\_private\nosetester.py -> build\lib.win-amd64-3.10\numpy\testing\_private
copying numpy\testing\_private\parameterized.py -> build\lib.win-amd64-3.10\numpy\testing\_private
copying numpy\testing\_private\utils.py -> build\lib.win-amd64-3.10\numpy\testing\_private
copying numpy\testing\_private\__init__.py -> build\lib.win-amd64-3.10\numpy\testing\_private
creating build\lib.win-amd64-3.10\numpy\testing\tests
copying numpy\testing\tests\test_decorators.py -> build\lib.win-amd64-3.10\numpy\testing\tests
copying numpy\testing\tests\test_doctesting.py -> build\lib.win-amd64-3.10\numpy\testing\tests
copying numpy\testing\tests\test_utils.py -> build\lib.win-amd64-3.10\numpy\testing\tests
copying numpy\testing\tests\__init__.py -> build\lib.win-amd64-3.10\numpy\testing\tests
creating build\lib.win-amd64-3.10\numpy\tests
copying numpy\tests\test_ctypeslib.py -> build\lib.win-amd64-3.10\numpy\tests
copying numpy\tests\test_matlib.py -> build\lib.win-amd64-3.10\numpy\tests
copying numpy\tests\test_numpy_version.py -> build\lib.win-amd64-3.10\numpy\tests
copying numpy\tests\test_public_api.py -> build\lib.win-amd64-3.10\numpy\tests
copying numpy\tests\test_reloading.py -> build\lib.win-amd64-3.10\numpy\tests
copying numpy\tests\test_scripts.py -> build\lib.win-amd64-3.10\numpy\tests
copying numpy\tests\test_warnings.py -> build\lib.win-amd64-3.10\numpy\tests
copying numpy\tests\__init__.py -> build\lib.win-amd64-3.10\numpy\tests
running build_clib
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils
customize MSVCCompiler
customize MSVCCompiler using new_build_clib
building 'npymath' library
compiling C sources
creating build\temp.win-amd64-3.10
creating build\temp.win-amd64-3.10\numpy
creating build\temp.win-amd64-3.10\numpy\core
creating build\temp.win-amd64-3.10\numpy\core\src
creating build\temp.win-amd64-3.10\numpy\core\src\npymath
creating build\temp.win-amd64-3.10\build
creating build\temp.win-amd64-3.10\build\src.win-amd64-3.10
creating build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy
creating build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core
creating build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src
creating build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npymath
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\npymath\npy_math.c /Fobuild\temp.win-amd64-3.10\numpy\core\src\npymath\npy_math.obj /GL-
cl : Command line warning D9025 : overriding '/GL' with '/GL-'
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\npymath\ieee754.c /Fobuild\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npymath\ieee754.obj /GL-
cl : Command line warning D9025 : overriding '/GL' with '/GL-'
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\npymath\npy_math_complex.c /Fobuild\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npymath\npy_math_complex.obj /GL-
cl : Command line warning D9025 : overriding '/GL' with '/GL-'
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\npymath\halffloat.c /Fobuild\temp.win-amd64-3.10\numpy\core\src\npymath\halffloat.obj /GL-
cl : Command line warning D9025 : overriding '/GL' with '/GL-'
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\lib.exe build\temp.win-amd64-3.10\numpy\core\src\npymath\npy_math.obj build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npymath\ieee754.obj build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npymath\npy_math_complex.obj build\temp.win-amd64-3.10\numpy\core\src\npymath\halffloat.obj /OUT:build\temp.win-amd64-3.10\npymath.lib
building 'npysort' library
compiling C sources
creating build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\npysort\quicksort.c /Fobuild\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\quicksort.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\npysort\mergesort.c /Fobuild\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\mergesort.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\npysort\timsort.c /Fobuild\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\timsort.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\npysort\heapsort.c /Fobuild\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\heapsort.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\npysort\radixsort.c /Fobuild\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\radixsort.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\npysort\selection.c /Fobuild\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\selection.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\npysort\binsearch.c /Fobuild\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\binsearch.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\lib.exe build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\quicksort.obj build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\mergesort.obj build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\timsort.obj build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\heapsort.obj build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\radixsort.obj build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\selection.obj build\temp.win-amd64-3.10\build\src.win-amd64-3.10\numpy\core\src\npysort\binsearch.obj /OUT:build\temp.win-amd64-3.10\npysort.lib
building 'npyrandom' library
compiling C sources
creating build\temp.win-amd64-3.10\numpy\random
creating build\temp.win-amd64-3.10\numpy\random\src
creating build\temp.win-amd64-3.10\numpy\random\src\distributions
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\random\src\distributions\logfactorial.c /Fobuild\temp.win-amd64-3.10\numpy\random\src\distributions\logfactorial.obj /GL-
cl : Command line warning D9025 : overriding '/GL' with '/GL-'
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\random\src\distributions\distributions.c /Fobuild\temp.win-amd64-3.10\numpy\random\src\distributions\distributions.obj /GL-
cl : Command line warning D9025 : overriding '/GL' with '/GL-'
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\random\src\distributions\random_mvhg_count.c /Fobuild\temp.win-amd64-3.10\numpy\random\src\distributions\random_mvhg_count.obj /GL-
cl : Command line warning D9025 : overriding '/GL' with '/GL-'
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\random\src\distributions\random_mvhg_marginals.c /Fobuild\temp.win-amd64-3.10\numpy\random\src\distributions\random_mvhg_marginals.obj /GL-
cl : Command line warning D9025 : overriding '/GL' with '/GL-'
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\random\src\distributions\random_hypergeometric.c /Fobuild\temp.win-amd64-3.10\numpy\random\src\distributions\random_hypergeometric.obj /GL-
cl : Command line warning D9025 : overriding '/GL' with '/GL-'
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\lib.exe build\temp.win-amd64-3.10\numpy\random\src\distributions\logfactorial.obj build\temp.win-amd64-3.10\numpy\random\src\distributions\distributions.obj build\temp.win-amd64-3.10\numpy\random\src\distributions\random_mvhg_count.obj build\temp.win-amd64-3.10\numpy\random\src\distributions\random_mvhg_marginals.obj build\temp.win-amd64-3.10\numpy\random\src\distributions\random_hypergeometric.obj /OUT:build\temp.win-amd64-3.10\npyrandom.lib
running build_ext
No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils
customize MSVCCompiler
customize MSVCCompiler using new_build_ext
building 'numpy.core._multiarray_tests' extension
compiling C sources
creating build\temp.win-amd64-3.10\Release\build
creating build\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10
creating build\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy
creating build\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core
creating build\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src
creating build\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src\multiarray
creating build\temp.win-amd64-3.10\Release\numpy
creating build\temp.win-amd64-3.10\Release\numpy\core
creating build\temp.win-amd64-3.10\Release\numpy\core\src
creating build\temp.win-amd64-3.10\Release\numpy\core\src\common
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\multiarray\_multiarray_tests.c /Fobuild\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src\multiarray\_multiarray_tests.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\common\mem_overlap.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\common\mem_overlap.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\link.exe /nologo /INCREMENTAL:NO /LTCG /DLL /MANIFEST:EMBED,ID=2 /MANIFESTUAC:NO /LIBPATH:C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\libs /LIBPATH:C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\PCbuild\amd64 /LIBPATH:build\temp.win-amd64-3.10 /LIBPATH:C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\lib\x64 /LIBPATH:C:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\lib\um\x64 /LIBPATH:D:\Windows Kits\10\lib\10.0.19041.0\ucrt\x64 /LIBPATH:D:\Windows Kits\10\lib\10.0.19041.0\um\x64 npymath.lib /EXPORT:PyInit__multiarray_tests build\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src\multiarray\_multiarray_tests.obj build\temp.win-amd64-3.10\Release\numpy\core\src\common\mem_overlap.obj /OUT:build\lib.win-amd64-3.10\numpy\core\_multiarray_tests.cp310-win_amd64.pyd /IMPLIB:build\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src\multiarray\_multiarray_tests.cp310-win_amd64.lib
building 'numpy.core._multiarray_umath' extension
compiling C sources
creating build\temp.win-amd64-3.10\Release\numpy\core\src\multiarray
creating build\temp.win-amd64-3.10\Release\numpy\core\src\umath
creating build\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src\umath
creating build\temp.win-amd64-3.10\Release\numpy\core\src\npymath
creating build\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src\npymath
creating build\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src\common
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\alloc.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\alloc.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\arrayobject.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\arrayobject.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\multiarray\arraytypes.c /Fobuild\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src\multiarray\arraytypes.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\array_assign_scalar.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\array_assign_scalar.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\array_assign_array.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\array_assign_array.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\arrayfunction_override.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\arrayfunction_override.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\buffer.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\buffer.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\calculation.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\calculation.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\compiled_base.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\compiled_base.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\common.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\common.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\convert.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\convert.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\convert_datatype.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\convert_datatype.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\conversion_utils.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\conversion_utils.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\ctors.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\ctors.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\datetime.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\datetime.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\datetime_strings.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\datetime_strings.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\datetime_busday.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\datetime_busday.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\datetime_busdaycal.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\datetime_busdaycal.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\descriptor.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\descriptor.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\dragon4.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\dragon4.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\dtype_transfer.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\dtype_transfer.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\multiarray\einsum.c /Fobuild\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src\multiarray\einsum.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\flagsobject.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\flagsobject.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\getset.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\getset.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\hashdescr.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\hashdescr.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\item_selection.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\item_selection.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\iterators.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\iterators.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\multiarray\lowlevel_strided_loops.c /Fobuild\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src\multiarray\lowlevel_strided_loops.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\mapping.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\mapping.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\methods.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\methods.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\multiarraymodule.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\multiarraymodule.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\multiarray\nditer_templ.c /Fobuild\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src\multiarray\nditer_templ.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\nditer_api.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\nditer_api.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\nditer_constr.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\nditer_constr.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\nditer_pywrap.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\nditer_pywrap.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\number.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\number.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\refcount.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\refcount.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\sequence.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\sequence.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\shape.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\shape.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcnumpy\core\src\multiarray\scalarapi.c /Fobuild\temp.win-amd64-3.10\Release\numpy\core\src\multiarray\scalarapi.obj
C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\multiarray\scalartypes.c /Fobuild\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src\multiarray\scalartypes.obj
scalartypes.c
numpy\core\include\numpy/npy_3kcompat.h(227): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\common.h(239): warning C4244: 'return': conversion from 'npy_uintp' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(425): warning C4267: '=': conversion from 'size_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(426): warning C4267: '=': conversion from 'size_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(1899): warning C4244: 'function': conversion from 'npy_double' to 'npy_float', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(1902): warning C4244: 'function': conversion from 'npy_double' to 'npy_float', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2577): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2561): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2577): warning C4244: '=': conversion from 'Py_ssize_t' to 'int', possible loss of data
numpy\core\src\multiarray\scalartypes.c.src(2967): error C2440: 'function': cannot convert from 'double' to 'PyObject *'
numpy\core\src\multiarray\scalartypes.c.src(2967): warning C4024: '_Py_HashDouble': different types for formal and actual parameter 1
numpy\core\src\multiarray\scalartypes.c.src(2967): error C2198: '_Py_HashDouble': too few arguments for call
numpy\core\src\multiarray\scalartypes.c.src(2976): error C2440: 'function': cannot convert from 'double' to 'PyObject *'
numpy\core\src\multiarray\scalartypes.c.src(2976): warning C4024: '_Py_HashDouble': different types for formal and actual parameter 1
numpy\core\src\multiarray\scalartypes.c.src(2975): error C2198: '_Py_HashDouble': too few arguments for call
numpy\core\src\multiarray\scalartypes.c.src(2982): error C2440: 'function': cannot convert from 'double' to 'PyObject *'
numpy\core\src\multiarray\scalartypes.c.src(2982): warning C4024: '_Py_HashDouble': different types for formal and actual parameter 1
numpy\core\src\multiarray\scalartypes.c.src(2981): error C2198: '_Py_HashDouble': too few arguments for call
numpy\core\src\multiarray\scalartypes.c.src(2967): error C2440: 'function': cannot convert from 'npy_longdouble' to 'PyObject *'
numpy\core\src\multiarray\scalartypes.c.src(2967): warning C4024: '_Py_HashDouble': different types for formal and actual parameter 1
numpy\core\src\multiarray\scalartypes.c.src(2967): error C2198: '_Py_HashDouble': too few arguments for call
numpy\core\src\multiarray\scalartypes.c.src(2976): error C2440: 'function': cannot convert from 'npy_longdouble' to 'PyObject *'
numpy\core\src\multiarray\scalartypes.c.src(2976): warning C4024: '_Py_HashDouble': different types for formal and actual parameter 1
numpy\core\src\multiarray\scalartypes.c.src(2975): error C2198: '_Py_HashDouble': too few arguments for call
numpy\core\src\multiarray\scalartypes.c.src(2982): error C2440: 'function': cannot convert from 'npy_longdouble' to 'PyObject *'
numpy\core\src\multiarray\scalartypes.c.src(2982): warning C4024: '_Py_HashDouble': different types for formal and actual parameter 1
numpy\core\src\multiarray\scalartypes.c.src(2981): error C2198: '_Py_HashDouble': too few arguments for call
numpy\core\src\multiarray\scalartypes.c.src(2997): error C2440: 'function': cannot convert from 'double' to 'PyObject *'
numpy\core\src\multiarray\scalartypes.c.src(2997): warning C4024: '_Py_HashDouble': different types for formal and actual parameter 1
numpy\core\src\multiarray\scalartypes.c.src(2997): error C2198: '_Py_HashDouble': too few arguments for call
numpy\core\src\multiarray\scalartypes.c.src(3913): warning C4244: 'return': conversion from 'npy_intp' to 'int', possible loss of data
error: Command "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild\src.win-amd64-3.10\numpy\core\src\umath -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Inumpy\core\include -Ibuild\src.win-amd64-3.10\numpy\core\include/numpy -Inumpy\core\src\common -Inumpy\core\src -Inumpy\core -Inumpy\core\src\npymath -Inumpy\core\src\multiarray -Inumpy\core\src\umath -Inumpy\core\src\npysort -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\include -IC:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.10_3.10.194.0_x64__qbz5n2kfra8p0\Include -Ibuild\src.win-amd64-3.10\numpy\core\src\common -Ibuild\src.win-amd64-3.10\numpy\core\src\npymath -IC:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Tools\MSVC\14.29.30133\include -IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.8\include\um -ID:\Windows Kits\10\include\10.0.19041.0\ucrt -ID:\Windows Kits\10\include\10.0.19041.0\shared -ID:\Windows Kits\10\include\10.0.19041.0\um -ID:\Windows Kits\10\include\10.0.19041.0\winrt -ID:\Windows Kits\10\include\10.0.19041.0\cppwinrt /Tcbuild\src.win-amd64-3.10\numpy\core\src\multiarray\scalartypes.c /Fobuild\temp.win-amd64-3.10\Release\build\src.win-amd64-3.10\numpy\core\src\multiarray\scalartypes.obj" failed with exit status 2
----------------------------------------
ERROR: Failed building wheel for numpy
Failed to build numpy
ERROR: Could not build wheels for numpy which use PEP 517 and cannot be installed directly
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/71/65/3ab03ef46613e66880dba5b2c2cb5836938f0219389a11c10cfdc617e836/pandas-1.3.3.tar.gz#sha256=272c8cb14aa9793eada6b1ebe81994616e647b5892a370c7135efb2924b701df (from https://pypi.org/simple/pandas/) (requires-python:>=3.7.1). Command errored out with exit status 1: 'C:\Users\Mohammad\AppData\Local\Microsoft\WindowsApps\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\python.exe' 'C:\Users\Mohammad\AppData\Local\Temp\pip-standalone-pip-wfs959uc\__env_pip__.zip\pip' install --ignore-installed --no-user --prefix 'C:\Users\Mohammad\AppData\Local\Temp\pip-build-env-dej0yus_\overlay' --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=51.0.0' wheel 'Cython>=0.29.21,<3' 'numpy==1.17.3; python_version=='"'"'3.7'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.18.3; python_version=='"'"'3.8'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.3; python_version>='"'"'3.9'"'"' and (platform_machine!='"'"'arm64'"'"' or platform_system!='"'"'Darwin'"'"') and platform_machine!='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.7'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy==1.19.2; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'aarch64'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.8'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' 'numpy>=1.20.0; python_version=='"'"'3.9'"'"' and platform_machine=='"'"'arm64'"'"' and platform_system=='"'"'Darwin'"'"'' Check the logs for full command output.
</details>
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https://api.github.com/repos/pandas-dev/pandas/issues/43604 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43604/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43604/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43604/events | https://github.com/pandas-dev/pandas/pull/43604 | 998,306,621 | PR_kwDOAA0YD84r16T8 | 43,604 | DOC : DataFrame.to_parquet doesn't round-trip pyarrow StringDtype #42664 | {
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] | open | false | null | [] | null | 4 | "2021-09-16T14:50:33Z" | "2021-10-28T17:49:40Z" | null | NONE | null | - [ ] closes #42664
Added a small note, both in _user_guide/text.rst_ and _user_guide/io.rst_ and example.
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} | 5 | "2021-09-16T15:04:40Z" | "2021-09-16T20:54:38Z" | "2021-09-16T20:54:26Z" | NONE | null | Hello maintainer,
Is there's not an error in documentation for "to_markdown" function at:
https://github.com/pandas-dev/pandas/blob/73c68257545b5f8530b7044f56647bd2db92e2ba/pandas/core/frame.py#L2550
The documentation indicate to be able to take a str in argument (Path), but when tested, it crash with:
```
pd.DataFrame(data).to_markdown(args.output_file, index=False)
File "venv/lib/python3.6/site-packages/pandas/core/frame.py", line 2267, in to_markdown
buf.writelines(result)
AttributeError: 'str' object has no attribute 'writelines'
```
In https://pandas.pydata.org/pandas-docs/version/1.0.1/reference/api/pandas.DataFrame.to_markdown.html
the documentation do not have mention of the "str" option.
Version of pandas: 1.1.5
Version of python: 3.6.9
That's all, have a nice day ;)
Regards | {
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} | 0 | "2021-09-16T15:48:13Z" | "2021-09-16T21:09:02Z" | "2021-09-16T21:07:57Z" | MEMBER | null | Will be able to re-use make_na_array for AM and possibly BM._make_na_block | {
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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} | 5 | "2021-09-16T19:47:58Z" | "2021-09-16T23:33:02Z" | "2021-09-16T22:59:28Z" | MEMBER | null | - [x] closes #43588
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
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This works on master, so this PR just adds a regression test (by removing the unnecessary `scipy` skips, this should be ensuring that some `spearman` tests will be run on 32-bit).
In the backport, these tests with the skip removed should fail, but the fix should be tiny (replacing 2 `int64` with `intp`) | {
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} | 1 | "2021-09-16T20:23:05Z" | "2021-09-17T22:40:05Z" | "2021-09-17T21:35:57Z" | MEMBER | null | ```
from asv_bench.benchmarks.groupby import *
self = GroupByMethods()
self.setup('object', 'ffill', 'direct', 1)
%timeit self.time_dtype_as_group('object', 'ffill', 'direct', 1)
67.6 µs ± 708 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each) # <- PR
82 µs ± 2.24 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each) # <- master
``` | {
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} | 6 | "2021-09-16T21:50:14Z" | "2021-09-23T16:11:52Z" | "2021-09-23T14:49:35Z" | MEMBER | null | - [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
This also starts to add a shared aggregation function (mean) that can shared between rolling/groupby/DataFrame when using the numba engine.
```
df = pd.DataFrame(np.ones((10000, 1000)))
roll = df.rolling(10)
roll.mean(engine="numba", engine_kwargs={"nopython": True, "nogil": True, "parallel": True})
%timeit roll.mean(engine="numba", engine_kwargs={"nopython": True, "nogil": True, "parallel": True})
260 ms ± 13.5 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) <- PR
431 ms ± 9.21 ms per loop (mean ± std. dev. of 7 runs, 1 loop each) <- master
```
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} | 7 | "2021-09-16T22:20:45Z" | "2021-09-17T00:04:03Z" | "2021-09-16T22:37:50Z" | MEMBER | null | - [ ] closes #41829
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
Successful run https://app.circleci.com/pipelines/github/lithomas1/pandas/3/workflows/ebe9e4aa-f86b-4bb2-9324-2b7a5eb9c243/jobs/3 (my fork)
I think someone with admin permissions in the github organization needs to turn on CircleCi on the pandas repo again. It probably would be better if this were merged first.
I also figured out how the credits work. Basically there's a setting for it in project settings. I think it should already be on.
(my fork settings) | {
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
This makes the errors checking in `get_handle` simpler and consistent with the XML code. | {
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- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [X] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
<CASE 1>
import pandas as pd
cat = pd.Categorical(['a', 'a', 'c'], categories=['a', 'b', 'c'])
codes, uniques = pd.factorize(cat)
codes
>>> Output-: array([0, 0, 1], dtype=int64)
<CASE 2>
import pandas as pd
cat = pd.Categorical(['a', 'a', 'c'], categories=['a', 'b', 'c'], ordered=True)
codes, uniques = pd.factorize(cat)
codes
>>> Output-: array([0, 0, 1], dtype=int64)
```
### Issue Description
In case 1 when we define a nominal variable we get the factorized values as [0,0,1] which seems fine but in case 2 when the variable is ordinal we get the same output i.e. [0,0,1]
### Expected Behavior
But instead, we should have got the output as [0,0,2]
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 5f648bf1706dd75a9ca0d29f26eadfbb595fe52b
python : 3.8.11.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19042
machine : AMD64
processor : Intel64 Family 6 Model 165 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_India.1252
pandas : 1.3.2
numpy : 1.20.3
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 52.0.0.post20210125
Cython : None
pytest : 6.2.4
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.26.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : 1.3.2
fsspec : 2021.07.0
fastparquet : None
gcsfs : None
matplotlib : 3.4.2
numexpr : 2.7.3
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : 0.54.0
</details>
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- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [x] whatsnew entry
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} | 2 | "2021-09-17T10:44:29Z" | "2021-09-22T12:36:51Z" | "2021-09-22T12:36:51Z" | CONTRIBUTOR | null | I noticed that the HTML generated by the Styler also contains CSS rules for explicitly excluded table elements (rows/cols).
I'm aware that not all unused CSS rules can be detected, but I suspect that any CSS rule with an id-selector where the id is not in the table could be omitted.
#### API breaking implications
I am not aware of what to do and what undesirable side effects this could have.
#### Additional context
Tested with pandas 1.3.3.
Here are two easy examples:
In this example `html` contains only one unused CSS rule:
```python
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randn(10, 4), columns=list('ABCD'))
html = df.style\
.highlight_max(axis=None)\
.hide_columns(df.columns)\
.hide_columns()\
.hide_index(df.index)\
.hide_index()\
.render()
breakpoint()
```
But when using `background_gradient`, we potential have a huge amount (depending of the size of the `df` and the amount of hidden content) of unused CSS rules:
```python
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randn(10, 4), columns=list('ABCD'))
html = df.style\
.background_gradient() \
.hide_columns(df.columns) \
.hide_columns() \
.hide_index(df.index) \
.hide_index() \
.render()
breakpoint()
```
Reducing the amount of data in the generated html could also improve other use cases like mentioned [here](https://pandas.pydata.org/pandas-docs/stable/user_guide/style.html#Optimization)
Is this optimization possible without unwanted side effects and easy to implement? If so, and the benefit is great enough, I could try it out if you give me some code pointers. | {
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} | 1 | "2021-09-17T14:10:41Z" | "2021-10-16T20:16:33Z" | "2021-10-16T20:16:13Z" | CONTRIBUTOR | null | xref #36602
- [x] closes #36602
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
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https://api.github.com/repos/pandas-dev/pandas/issues/43621 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/43621/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/43621/comments | https://api.github.com/repos/pandas-dev/pandas/issues/43621/events | https://github.com/pandas-dev/pandas/issues/43621 | 999,451,709 | I_kwDOAA0YD847kmw9 | 43,621 | BUG: pandas.to_csv() saves column values as integers when column contains numbers as string | {
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] | closed | false | null | [] | null | 6 | "2021-09-17T15:01:04Z" | "2021-09-20T19:44:25Z" | "2021-09-20T19:44:18Z" | NONE | null | ###
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.
- [x] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
pre_save = pd.DataFrame({'b': ['1', '2', '3', '4']})
assert pre_save.b[1] == '2'
pre_save.to_csv('pre_save')
post_save = pd.read_csv('pre_save')
assert post_save.b[1] == '2' ## Results in assertion error
assert post_save.b[1] == 2 ## Run properly
```
### Issue Description
While saving a dataframe that contains numbers as string in its columns as a csv, Pandas converts the data type automatically and saves column values as numbers instead of string.
One could also verify the behavior by looking at the csv file generated by .to_csv function. It contains normal numbers instead of double quoted ones.
### Expected Behavior
import pandas as pd
pre_save = pd.DataFrame({'b': ['1', '2', '3', '4']})
assert pre_save.b[1] == '2'
pre_save.to_csv('pre_save')
post_save = pd.read_csv('pre_save')
assert post_save.b[1] == '2' ## This should not result in assertion error
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : None
python : 3.7.10.final.0
python-bits : 64
OS : Darwin
OS-release : 18.7.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 0.25.1
numpy : 1.17.2
pytz : 2021.1
dateutil : 2.8.1
pip : 21.1.1
setuptools : 57.0.0
Cython : None
pytest : 5.2.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.0
IPython : 7.5.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : 3.4.2
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 0.17.0
pytables : None
s3fs : None
scipy : 1.6.3
sqlalchemy : None
tables : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
</details>
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