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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.html#code-standards) for how to run them
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- [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
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- [ ] I have asked my usage related question on [StackOverflow](https://stackoverflow.com).
---
#### Question about pandas
I want to roll my own dataframe functionality and syntax. Below is an example with a ternary-like operator
**Example A:**
Let's say I want to set ‘row_A’ equal to 5 if ‘row_B’ is 10.
Right now, this has to be written like this:
`df.loc[df.row_1 == ‘10’, 'row_1'] = 5
`
But I want this to work:
`
df.row_A = 5 if row_B = 10
`
My question is, is it feasible possible to add / overload the functionality implied? Has anyone tried this?
Example A above would just be the beginning.
While subjective, I think this deals with a large class of "not quite" esoteric operations, that are in fact arcane and esoteric to execute concisely in Pandas.
Note that I’m in principle happy to share / learn / complement / accept someone else's implementation too.
Please let me know if this is insanity.
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} | 1 | "2021-03-19T22:16:08Z" | "2021-03-25T20:52:44Z" | "2021-03-20T01:24:05Z" | CONTRIBUTOR | null | For example: `Duplicate explicit target name: "user guide"`
I was seeing these warnings in the dask docs build because dask pulls docstrings from pandas. I think using anonomous links like this should fix it based on https://github.com/sphinx-doc/sphinx/issues/3921
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} | 2 | "2021-03-19T22:23:55Z" | "2021-03-23T16:36:18Z" | "2021-03-23T16:35:07Z" | MEMBER | null | The way we pass state back and forth is a bit nutty, punting on that. | {
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} | 6 | "2021-03-20T00:20:37Z" | "2021-03-23T15:19:21Z" | "2021-03-23T15:17:56Z" | MEMBER | null | - [x] closes #39837
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [x] whatsnew entry
Not sure how best to test this - confirmed this now works when run on PyPy, but since we don't test against PyPy the examples in the issue (or any other simple case) which fail on PyPy will still pass on master.
Benchmarks look similar, might be minor performance improvement for the single block case:
```
before after ratio
[b524462e] [b1f4bcc8]
<master> <bug/is_mixed_type>
194±5ms 190±2ms 0.98 io.json.ToJSONISO.time_iso_format('columns')
208±5ms 198±6ms 0.95 io.json.ToJSONISO.time_iso_format('index')
186±4ms 173±3ms 0.93 io.json.ToJSONISO.time_iso_format('records')
193±10ms 187±3ms 0.97 io.json.ToJSONISO.time_iso_format('split')
164±4ms 165±3ms 1.00 io.json.ToJSONISO.time_iso_format('values')
115±4ms 114±3ms 0.99 io.json.ToJSONLines.time_delta_int_tstamp_lines
142±4ms 132±6ms 0.93 io.json.ToJSONLines.time_float_int_lines
140±4ms 142±4ms 1.02 io.json.ToJSONLines.time_float_int_str_lines
152±2ms 153±3ms 1.01 io.json.ToJSONLines.time_float_longint_str_lines
110±3ms 107±3ms 0.97 io.json.ToJSONLines.time_floats_with_dt_index_lines
112±3ms 104±3ms 0.93 io.json.ToJSONLines.time_floats_with_int_idex_lines
54.3M 55M 1.01 io.json.ToJSONMem.peakmem_float
55.4M 55.2M 1.00 io.json.ToJSONMem.peakmem_int
88.6±2ms 78.8±2ms 0.89 io.json.ToJSON.time_to_json('index', 'df')
70.7±2ms 61.7±2ms 0.87 io.json.ToJSON.time_to_json('values', 'df')
94.9±3ms 81.4±1ms 0.86 io.json.ToJSON.time_to_json('index', 'df_date_idx')
76.3±0.9ms 65.1±1ms 0.85 io.json.ToJSON.time_to_json('records', 'df_date_idx')
``` | {
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} | 1 | "2021-03-20T01:49:55Z" | "2021-03-22T14:28:26Z" | "2021-03-22T13:03:21Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
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} | 2 | "2021-03-20T01:59:54Z" | "2021-03-20T16:53:03Z" | "2021-03-20T15:41:37Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] tests added / passed
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
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] | null | 7 | "2021-03-20T12:27:07Z" | "2021-08-19T11:42:38Z" | "2021-08-19T11:42:38Z" | MEMBER | null | Instead of
```python
OutputKey = collections.namedtuple("OutputKey", ["label", "position"])
```
we can do
```python
from typing import NamedTuple
class OutputKey(NamedTuple)
label
position
```
The advantage is that like this we can add type hints to the various elements, such as
```python
from typing import NamedTuple
class OutputKey(NamedTuple)
label: Hashable
position: int
```
-----
See https://docs.python.org/3/library/typing.html#typing.NamedTuple for reference | {
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} | 5 | "2021-03-20T12:29:02Z" | "2021-04-02T16:30:17Z" | "2021-04-02T14:50:54Z" | MEMBER | null | For context, see #40468, where the error which was fixed was arguably a false-positive.
I've loosened the check so that now it only errors / replaces if:
- you imported an object from somewhere in pandas `e.g. from pandas.io.formats import info`
- you also accessed that object as `pd.` or `pandas.` (e.g. `pd.info` or `pandas.info`)
Before, it just checked whether an object appeared both with and without the `pd.` prefix, which was too tight a check - sorry about that :flushed:
I've also added line number and column offset of the inconsistency for ease of checking/fixing | {
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} | 14 | "2021-03-20T12:45:37Z" | "2021-04-13T12:13:36Z" | "2021-04-13T12:13:36Z" | MEMBER | null | This means we can address
> type hints are executed at module import time, which is not computationally free.
(from https://www.python.org/dev/peps/pep-0563/), as well as use the more modern syntax of Python
----
This is easy to automate, just checking there's no downsides to putting this everywhere. Should any files (probably `__init__.py`, any others?) be excluded? cc @simonjayhawkins | {
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} | 5 | "2021-03-20T14:40:45Z" | "2021-03-23T10:10:17Z" | "2021-03-23T01:33:04Z" | CONTRIBUTOR | null | Minor clean-up.
```python
>>> from typing import Hashable
>>> isinstance(None, Hashable)
True
```
In old versions of mypy, mypy had a bug and didn't see this, but is has been fixed now.
There are many instances of `Optional[Hashable]` instead of just `Hashable` in the code base, other than in these dicts. I've assumed those should be left as-is for readability and not because it's strictly needed.
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} | 1 | "2021-03-20T14:57:52Z" | "2021-03-23T17:08:08Z" | "2021-03-23T16:23:02Z" | CONTRIBUTOR | null | Typing of `first_valid_index` & `last_valid_index` + make the `how` param in internal functions a named parameter for better readability. | {
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} | 3 | "2021-03-20T15:07:43Z" | "2021-06-26T07:44:15Z" | "2021-03-23T16:47:15Z" | MEMBER | null | Partially-fixes one of the currently-disabled ArrayManager tests. | {
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Looks like some combination of this, #40474, #40476 are resposible for broken CI. Trying this one first. | {
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} | 1 | "2021-03-20T16:11:26Z" | "2021-03-22T11:58:59Z" | "2021-03-21T21:00:40Z" | CONTRIBUTOR | null | From #39501 splitting out the part to make the EA `registry` private. This will make it so that `pyright --verifytypes` accepts pandas public API.
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] | open | false | null | [] | null | 2 | "2021-03-20T16:14:30Z" | "2021-08-19T02:47:56Z" | null | MEMBER | null | With `df = pd.DataFrame({'a': [1, 2], 'b': [3, 4]})`, my expectation is that:
df.agg([func])
df.agg({'a': func, 'b': func})
Behave the same. However, the former allows partial failure when a TypeError is raised, whereas the latter does not. Similarly with groupby as well.
While I'd like to focus this issue on just agg with list/dict-likes, comparisons for all frame/series, agg/transform, list/dict with functions that raise ValueError/TypeError combinations are below.
<details><summary>Results</summary>
```
Series <class 'ValueError'>
.agg with dict: raised ValueError()
.agg with list: raised ValueError()
.transform with dict: partial failure allowed
.transform with list: partial failure allowed
groupby(...).agg with dict: raised SpecificationError('nested renamer is not supported')
groupby(...).agg with list: raised ValueError()
groupby(...).transform with dict: raised TypeError("unhashable type: 'dict'")
groupby(...).transform with list: raised TypeError("unhashable type: 'list'")
Frame <class 'ValueError'>
.agg with dict: raised ValueError()
.agg with list: raised ValueError()
.transform with dict: partial failure allowed
.transform with list: partial failure allowed
groupby(...).agg with dict: raised ValueError()
groupby(...).agg with list: raised ValueError()
groupby(...).transform with dict: raised TypeError("unhashable type: 'dict'")
groupby(...).transform with list: raised TypeError("unhashable type: 'list'")
Series <class 'TypeError'>
.agg with dict: raised TypeError()
.agg with list: partial failure allowed
.transform with dict: partial failure allowed
.transform with list: partial failure allowed
groupby(...).agg with dict: raised SpecificationError('nested renamer is not supported')
groupby(...).agg with list: raised TypeError()
groupby(...).transform with dict: raised TypeError("unhashable type: 'dict'")
groupby(...).transform with list: raised TypeError("unhashable type: 'list'")
Frame <class 'TypeError'>
.agg with dict: raised TypeError('DataFrame constructor called with incompatible data and dtype: ')
.agg with list: partial failure allowed
.transform with dict: partial failure allowed
.transform with list: partial failure allowed
groupby(...).agg with dict: raised TypeError()
groupby(...).agg with list: partial failure allowed
groupby(...).transform with dict: raised TypeError("unhashable type: 'dict'")
groupby(...).transform with list: raised TypeError("unhashable type: 'list'")
```
</details>
<details><summary>Code</summary>
```
def run_series(err_klass):
def failop(x): raise err_klass
def passop_agg(x): return x.sum()
def passop_transform(x): return x
ser = pd.Series([1, 2])
print('Series', err_klass)
args = it.product((False, True), ('agg', 'transform'), (False, True))
for use_gb, method, is_list in args:
obj = ser.groupby(level=0) if use_gb else ser
op = passop_transform if method == 'transform' else passop_agg
func = [failop, op] if is_list else {'a': failop, 'b': op}
try:
getattr(obj, method)(func)
result = 'partial failure allowed'
except Exception as err:
result = f'raised {repr(err)}'
print(
f' {"groupby(...)" if use_gb else ""}.{method} '
f'{"with list" if is_list else "with dict"}: {result}'
)
print()
def run_frame(err_klass):
def op_agg(x):
if x.sum().sum() < 100:
raise err_klass
return x.sum()
def op_transform(x):
if x.sum().sum() < 100:
raise err_klass
return x
df = pd.DataFrame({'a': [1, 2], 'b': [100, 200]})
print('Frame', err_klass)
args = it.product((False, True), ('agg', 'transform'), (False, True))
for use_gb, method, is_list in args:
obj = df.groupby(level=0) if use_gb else df
op = op_transform if method == 'transform' else op_agg
func = [op] if is_list else {'a': op, 'b': op}
try:
getattr(obj, method)(func)
result = 'partial failure allowed'
except Exception as err:
result = f'raised {repr(err)}'
print(
f' {"groupby(...)" if use_gb else ""}.{method} '
f'{"with list" if is_list else "with dict"}: {result}'
)
print()
run_series(ValueError)
run_frame(ValueError)
run_series(TypeError)
run_frame(TypeError)
```
</details>
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} | 1 | "2021-03-20T16:21:51Z" | "2021-03-22T11:59:32Z" | "2021-03-21T21:01:24Z" | CONTRIBUTOR | null | In `_typing.py` change `DatetimeLikeScalar` from `TypeVar` to `Union`
Allows removal of 4 `#type: ignore` lines
Per split out from #39501 | {
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- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
Ref: #34224. Back when transform and agg shared code, this was introduced to stop transform from having an infinite recursive loop. Now they do not, it is no longer necessary and only serves to obfusticate the error message. | {
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- [ ] tests added / passed
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
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`include_api = False` in the if block doesn't have any effect.
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} | 20 | "2021-03-21T15:15:44Z" | "2021-06-01T13:05:04Z" | "2021-06-01T12:36:36Z" | CONTRIBUTOR | null | - [x] closes #40371
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
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} | 24 | "2021-03-21T16:07:22Z" | "2021-05-03T19:07:13Z" | "2021-05-03T17:31:13Z" | CONTRIBUTOR | null | - [x] xref, but is first step in implementing #36893
- [x] tests added and passed
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- [x] whatsnew entry (in the docstring)
- [ ] whatsnew entry (in the docs)
This is the first step in implementing an `engine` backend to the SQL I/O functions, as discussed in #36893. This PR is simply to refactor the existing SQLAlchemy parts to make them extensible for an external engine.
No new engines were added at this stage. No new tests were added, only verified that existing tests fail ("test behavior, not implementation" suggests that we don't need to test internal refactoring)
Lots of the code was borrowed from the Parquet I/O implementation. | {
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} | 3 | "2021-03-21T17:31:44Z" | "2021-05-13T23:27:48Z" | "2021-05-13T23:27:45Z" | CONTRIBUTOR | null | - [x] closes #40250
- [x] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
#40250 is an issue which seems to have been fixed in master already through #39446. This PR adds a test for this issue.
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] | closed | false | null | [] | null | 2 | "2021-03-21T20:19:08Z" | "2021-05-16T08:33:45Z" | "2021-05-16T08:33:45Z" | NONE | null | #### Location of the documentation
https://pandas.pydata.org/pandas-docs/stable/development/contributing.html#creating-a-python-environment-pip
#### Documentation problem
Requirements file fails to install if prerequisites for the pytables package are not met. As far as I can tell these instructions will fail if you don't have [HDF5](https://www.hdfgroup.org/solutions/hdf5/) installed already.
This following line returns an error:
```
python -m pip install -r requirements-dev.txt
```
Click below for Windows Powershell Error trace:
<details>
<!-- do not delete the following blank line -->
```sh
Collecting tables>=3.5.1
Using cached tables-3.6.1.tar.gz (4.6 MB)
ERROR: Command errored out with exit status 1:
command: 'C:\Users\ferga\virtualenvs\pandas-dev\Scripts\python.exe' -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\ferga\\AppData\\Local\\Temp\\pip-install-z88l7dtf\\tables_ad6031c18d884368946e8601e5e6b83a\\setup.py'"'"'; __file__='"'"'C:\\Users\\ferga\\AppData\\Local\\Temp\\pip-install-z88l7dtf\\tables_ad6031c18d884368946e8601e5e6b83a\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' egg_info --egg-base 'C:\Users\ferga\AppData\Local\Temp\pip-pip-egg-info-_f3hgzqo'
cwd: C:\Users\ferga\AppData\Local\Temp\pip-install-z88l7dtf\tables_ad6031c18d884368946e8601e5e6b83a\
Complete output (9 lines):
H5closet5cs0mu2.c
C:\Users\ferga\AppData\Local\Temp\H5closet5cs0mu2.c(2): warning C4013: 'H5close' undefined; assuming extern returning int
LINK : fatal error LNK1181: cannot open input file 'hdf5.lib'
* Using Python 3.9.2 (tags/v3.9.2:1a79785, Feb 19 2021, 13:44:55) [MSC v.1928 64 bit (AMD64)]
* USE_PKGCONFIG: False
.. ERROR:: Could not find a local HDF5 installation.
You may need to explicitly state where your local HDF5 headers and
library can be found by setting the ``HDF5_DIR`` environment
variable or by using the ``--hdf5`` command-line option.
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/2b/32/847ee3f521aae6a0be380d923a736162d698586f444df1ac24b98c65025c/tables-3.6.1.tar.gz#sha256=49a972b8a7c27a8a173aeb05f67acb45fe608b64cd8e9fa667c0962a60b71b49 (from https://pypi.org/simple/tables/) (requires-python:>=3.5). Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.
Downloading tables-3.5.2.tar.gz (7.8 MB)
|████████████████████████████████| 7.8 MB 2.2 MB/s
ERROR: Command errored out with exit status 1:
command: 'C:\Users\ferga\virtualenvs\pandas-dev\Scripts\python.exe' -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\ferga\\AppData\\Local\\Temp\\pip-install-z88l7dtf\\tables_ecb0a9038fe14c25bf054f52525e8223\\setup.py'"'"'; __file__='"'"'C:\\Users\\ferga\\AppData\\Local\\Temp\\pip-install-z88l7dtf\\tables_ecb0a9038fe14c25bf054f52525e8223\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' egg_info --egg-base 'C:\Users\ferga\AppData\Local\Temp\pip-pip-egg-info-695w_dt8'
cwd: C:\Users\ferga\AppData\Local\Temp\pip-install-z88l7dtf\tables_ecb0a9038fe14c25bf054f52525e8223\
Complete output (9 lines):
H5close0vbr0smy.c
C:\Users\ferga\AppData\Local\Temp\H5close0vbr0smy.c(2): warning C4013: 'H5close' undefined; assuming extern returning int
LINK : fatal error LNK1181: cannot open input file 'hdf5.lib'
* Using Python 3.9.2 (tags/v3.9.2:1a79785, Feb 19 2021, 13:44:55) [MSC v.1928 64 bit (AMD64)]
* USE_PKGCONFIG: False
.. ERROR:: Could not find a local HDF5 installation.
You may need to explicitly state where your local HDF5 headers and
library can be found by setting the ``HDF5_DIR`` environment
variable or by using the ``--hdf5`` command-line option.
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/73/51/6dabb2b94826e5db3aa2542b80f1382780b96a0cd13e0cfb637b36ede5c5/tables-3.5.2.tar.gz#sha256=b220e32262bab320aa41d33125a7851ff898be97c0de30b456247508e2cc33c2 (from https://pypi.org/simple/tables/). Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.
Downloading tables-3.5.1.tar.gz (8.3 MB)
|████████████████████████████████| 8.3 MB 3.3 MB/s
ERROR: Command errored out with exit status 1:
command: 'C:\Users\ferga\virtualenvs\pandas-dev\Scripts\python.exe' -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'C:\\Users\\ferga\\AppData\\Local\\Temp\\pip-install-z88l7dtf\\tables_cd421b0f0e7a4033b8cbd6af4ac8c022\\setup.py'"'"'; __file__='"'"'C:\\Users\\ferga\\AppData\\Local\\Temp\\pip-install-z88l7dtf\\tables_cd421b0f0e7a4033b8cbd6af4ac8c022\\setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' egg_info --egg-base 'C:\Users\ferga\AppData\Local\Temp\pip-pip-egg-info-r8d5q3it'
cwd: C:\Users\ferga\AppData\Local\Temp\pip-install-z88l7dtf\tables_cd421b0f0e7a4033b8cbd6af4ac8c022\
Complete output (9 lines):
H5close0scl0_1r.c
C:\Users\ferga\AppData\Local\Temp\H5close0scl0_1r.c(2): warning C4013: 'H5close' undefined; assuming extern returning int
LINK : fatal error LNK1181: cannot open input file 'hdf5.lib'
* Using Python 3.9.2 (tags/v3.9.2:1a79785, Feb 19 2021, 13:44:55) [MSC v.1928 64 bit (AMD64)]
* USE_PKGCONFIG: False
.. ERROR:: Could not find a local HDF5 installation.
You may need to explicitly state where your local HDF5 headers and
library can be found by setting the ``HDF5_DIR`` environment
variable or by using the ``--hdf5`` command-line option.
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/c6/e6/38cdcdc501ff889ea1e60bd5ef61d0573f73606f4dd0169786fd991c6b70/tables-3.5.1.tar.gz#sha256=88e2f3be1f143febc8bf8a7fe49ad51fc12518d6a1ac4eb641778d93e5dc2039 (from https://pypi.org/simple/tables/). Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.
ERROR: Could not find a version that satisfies the requirement tables>=3.5.1
ERROR: No matching distribution found for tables>=3.5.1
```
</details>
#### Suggested fix for documentation
One or more of the following:
* Explain the issue and link to [pytables documentation](http://www.pytables.org/usersguide/installation.html#prerequisites) where prerequisites are explained.
* Update instructions with steps to install pytables prerequisites
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} | 3 | "2021-03-21T20:48:52Z" | "2021-03-23T16:18:52Z" | "2021-03-23T16:10:30Z" | MEMBER | null | Ensuring a contiguous input seems to give about a 5-10% performance improvement on the existing benchmark `gil.ParallelKth` | {
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} | 4 | "2021-03-21T21:18:58Z" | "2021-06-12T11:41:01Z" | "2021-06-12T10:21:22Z" | CONTRIBUTOR | null | This is not exactly right, but we have an inconsitency in the argument specifications of using 'array_like' vs 'array-like', in argument types we should settle on one (prob 'array-like')
```
(pandas-dev) ~/pandas$ grep -r array-like --include '*.py' pandas|wc
317 2259 24072
(pandas-dev) ~/pandas$ grep -r array_like --include '*.py' pandas|wc
104 498 7414
```
Similar to this
```
pandas/plotting/_core.py: yerr : DataFrame, Series, array-like, dict and str
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} | 2 | "2021-03-22T03:03:20Z" | "2021-03-22T14:25:23Z" | "2021-03-22T13:11:24Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/40562 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40562/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40562/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40562/events | https://github.com/pandas-dev/pandas/pull/40562 | 837,298,234 | MDExOlB1bGxSZXF1ZXN0NTk3NjUyMjgx | 40,562 | ENH: applymap get kwargs #39987 | {
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} | 1 | "2021-03-22T04:17:36Z" | "2021-03-23T16:11:20Z" | "2021-03-23T16:11:17Z" | CONTRIBUTOR | null | - [X] closes #39987
- [X] tests added / passed
- [X] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
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https://api.github.com/repos/pandas-dev/pandas/issues/40563 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40563/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40563/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40563/events | https://github.com/pandas-dev/pandas/pull/40563 | 837,327,888 | MDExOlB1bGxSZXF1ZXN0NTk3Njc3ODI3 | 40,563 | BUG: Fix query doesn't support equals or not equals with Python parse… | {
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] | closed | false | null | [] | null | 8 | "2021-03-22T05:23:10Z" | "2021-11-09T00:20:37Z" | "2021-11-09T00:20:37Z" | CONTRIBUTOR | null | …r (#40436)
- [X] closes #40436
- [X] tests added / passed
- [X] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [X] whatsnew entry
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} | 0 | "2021-03-22T07:29:07Z" | "2021-03-22T10:49:55Z" | "2021-03-22T10:49:50Z" | CONTRIBUTOR | null | <!-- START pr-commits -->
<!-- END pr-commits -->
## Base PullRequest
default branch (https://github.com/pandas-dev/pandas/tree/master)
## Command results
<details>
<summary>Details: </summary>
<details>
<summary><em>add path</em></summary>
```Shell
/home/runner/work/_actions/technote-space/create-pr-action/v2/node_modules/npm-check-updates/bin
```
</details>
<details>
<summary><em>pip install pre-commit</em></summary>
```Shell
Collecting pre-commit
Downloading pre_commit-2.11.1-py2.py3-none-any.whl (187 kB)
Collecting identify>=1.0.0
Downloading identify-2.2.0-py2.py3-none-any.whl (98 kB)
Collecting toml
Using cached toml-0.10.2-py2.py3-none-any.whl (16 kB)
Collecting cfgv>=2.0.0
Using cached cfgv-3.2.0-py2.py3-none-any.whl (7.3 kB)
Collecting nodeenv>=0.11.1
Using cached nodeenv-1.5.0-py2.py3-none-any.whl (21 kB)
Collecting virtualenv>=20.0.8
Downloading virtualenv-20.4.3-py2.py3-none-any.whl (7.2 MB)
Collecting pyyaml>=5.1
Downloading PyYAML-5.4.1-cp39-cp39-manylinux1_x86_64.whl (630 kB)
Collecting filelock<4,>=3.0.0
Using cached filelock-3.0.12-py3-none-any.whl (7.6 kB)
Collecting distlib<1,>=0.3.1
Using cached distlib-0.3.1-py2.py3-none-any.whl (335 kB)
Collecting six<2,>=1.9.0
Using cached six-1.15.0-py2.py3-none-any.whl (10 kB)
Collecting appdirs<2,>=1.4.3
Using cached appdirs-1.4.4-py2.py3-none-any.whl (9.6 kB)
Installing collected packages: six, filelock, distlib, appdirs, virtualenv, toml, pyyaml, nodeenv, identify, cfgv, pre-commit
Successfully installed appdirs-1.4.4 cfgv-3.2.0 distlib-0.3.1 filelock-3.0.12 identify-2.2.0 nodeenv-1.5.0 pre-commit-2.11.1 pyyaml-5.4.1 six-1.15.0 toml-0.10.2 virtualenv-20.4.3
```
</details>
<details>
<summary><em>pre-commit autoupdate || (exit 0);</em></summary>
```Shell
Updating https://github.com/MarcoGorelli/absolufy-imports ... [INFO] Initializing environment for https://github.com/MarcoGorelli/absolufy-imports.
already up to date.
Updating https://github.com/python/black ... already up to date.
Updating https://github.com/codespell-project/codespell ... [INFO] Initializing environment for https://github.com/codespell-project/codespell.
already up to date.
Updating https://github.com/pre-commit/pre-commit-hooks ... [INFO] Initializing environment for https://github.com/pre-commit/pre-commit-hooks.
already up to date.
Updating https://github.com/cpplint/cpplint ... [INFO] Initializing environment for https://github.com/cpplint/cpplint.
=====> /home/runner/.cache/pre-commit/repo14gb2ni_/.pre-commit-hooks.yaml does not exist
Updating https://gitlab.com/pycqa/flake8 ... [INFO] Initializing environment for https://gitlab.com/pycqa/flake8.
already up to date.
Updating https://github.com/PyCQA/isort ... [INFO] Initializing environment for https://github.com/PyCQA/isort.
updating 5.7.0 -> 5.8.0.
Updating https://github.com/asottile/pyupgrade ... [INFO] Initializing environment for https://github.com/asottile/pyupgrade.
updating v2.10.0 -> v2.11.0.
Updating https://github.com/pre-commit/pygrep-hooks ... [INFO] Initializing environment for https://github.com/pre-commit/pygrep-hooks.
already up to date.
Updating https://github.com/asottile/yesqa ... already up to date.
```
</details>
<details>
<summary><em>pre-commit run -a || (exit 0);</em></summary>
```Shell
[INFO] Initializing environment for https://github.com/cpplint/cpplint.
[INFO] Initializing environment for https://gitlab.com/pycqa/flake8:flake8-comprehensions>=3.1.0.
[INFO] Installing environment for https://github.com/MarcoGorelli/absolufy-imports.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/python/black.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/codespell-project/codespell.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/pre-commit/pre-commit-hooks.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/cpplint/cpplint.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://gitlab.com/pycqa/flake8.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://gitlab.com/pycqa/flake8.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/PyCQA/isort.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/asottile/pyupgrade.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for https://github.com/asottile/yesqa.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for local.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for local.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
[INFO] Installing environment for local.
[INFO] Once installed this environment will be reused.
[INFO] This may take a few minutes...
absolufy-imports....................................................................................Passed
black...............................................................................................Passed
codespell...........................................................................................Passed
Fix End of Files....................................................................................Passed
Trim Trailing Whitespace............................................................................Passed
cpplint.............................................................................................Passed
flake8..............................................................................................Passed
flake8 (cython).....................................................................................Passed
flake8 (cython template)............................................................................Passed
isort...............................................................................................Passed
pyupgrade...........................................................................................Failed
- hook id: pyupgrade
- exit code: 1
- files were modified by this hook
Rewriting pandas/io/pytables.py
Rewriting pandas/core/internals/blocks.py
Rewriting pandas/tests/io/test_sql.py
Rewriting pandas/tests/io/parser/test_encoding.py
Rewriting pandas/tests/io/parser/common/test_file_buffer_url.py
rst ``code`` is two backticks.......................................................................Passed
rst directives end with two colons..................................................................Passed
rst ``inline code`` next to normal text.............................................................Passed
Strip unnecessary `# noqa`s.........................................................................Passed
flake8-rst..........................................................................................Passed
Check for use of Union[Series, DataFrame] instead of FrameOrSeriesUnion alias.......................Passed
Check for inconsistent use of pandas namespace in tests.............................................Passed
Check for incorrect code block or IPython directives................................................Passed
Check code for instances of os.remove...............................................................Passed
Check for non-standard imports......................................................................Passed
Check for non-standard imports in test suite........................................................Passed
Check for use of np.bool/np.object instead of np.bool_/np.object_...................................Passed
Generate pip dependency from conda..................................................................Passed
Validate correct capitalization among titles in documentation.......................................Passed
Check for use of foo.__class__ instead of type(foo).................................................Passed
Check for use of bare pytest raises.................................................................Passed
Check for use of private functions across modules...................................................Passed
Check for import of private attributes across modules...............................................Passed
Check for use of pytest.xfail.......................................................................Passed
Check for use of not concatenated strings...........................................................Passed
Check for strings with wrong placed spaces..........................................................Passed
Check for outdated annotation syntax and missing error codes........................................Passed
```
</details>
</details>
## Changed files
<details>
<summary>Changed 6 files: </summary>
- .pre-commit-config.yaml
- pandas/core/internals/blocks.py
- pandas/io/pytables.py
- pandas/tests/io/parser/common/test_file_buffer_url.py
- pandas/tests/io/parser/test_encoding.py
- pandas/tests/io/test_sql.py
</details>
<hr>
[:octocat: Repo](https://github.com/technote-space/create-pr-action) | [:memo: Issues](https://github.com/technote-space/create-pr-action/issues) | [:department_store: Marketplace](https://github.com/marketplace/actions/create-pr-action) | {
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} | 4 | "2021-03-22T08:13:52Z" | "2021-05-08T18:47:56Z" | null | NONE | null | - [X ] I have checked that this issue has not already been reported. **(sorry if I missed it)**
- [X ] I have confirmed this bug exists on the latest version of pandas. **(present on 1.2.3)**
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
# Set up
import pandas as pd
str_serie = pd.Series(["hello", None, "hi"]) # Note the None
true_serie = pd.Series([True] * 3)
print("1st case")
print(str_serie.str.contains('h') | true_serie) # prints True, False, True
print("2nd case")
print(true_serie | str_serie.str.contains('h')) # prints True, True, True
```
#### Problem description
- the commutative property of the `or` or `|` isn't respected.
- in the 1st case, pandas seems to stop evaluating the boolean expression at the string comparison if it encounters a null type.
#### Expected Output
In both cases, the output should be `True, True, True`.
If pandas were to still ignore boolean expressions after a str operation on a null type, then it should at least print some warnings about it.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.9.2.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.18362
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 12, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : French_Switzerland.1252
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 49.2.1
Cython : None
pytest : 6.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : 7.21.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 0.8.7
fastparquet : None
gcsfs : None
matplotlib : 3.3.4
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.1
sqlalchemy : 1.4.0
tables : None
tabulate : 0.8.9
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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} | 0 | "2021-03-22T09:34:51Z" | "2021-08-19T02:48:48Z" | 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 of pandas.
- [X] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
import pandas as pd
s = pd.Series(["2020-10-10", None], dtype="string")
s.astype("datetime64[ns]") # fails
s = pd.Series(["1 Day", None], dtype="string")
s.astype("timedelta64[ns]") # fails
s = pd.Series(["1/1/2021", None], dtype="string")
s.astype("period[M]") # fails
s = pd.Series([True, None], dtype="string")
s.astype("boolean") # fails
```
Similar issue for `timedelta64` raised by jbrockmendel in #38509.
#### Problem description
The behaviour looks like a bug and I'd like to help out, however the `astype` dispatching (https://github.com/pandas-dev/pandas/issues/22384) and the `_from_sequence` specifics (https://github.com/pandas-dev/pandas/issues/33254) seem to be debated issues.
If you'd like I can write a PR that fixes this by:
1. implementing `_from_sequence_of_strings` in the ExtensionArrays where it hasn't been implemented: Categorical, DatetimeArray, TimedeltaArray.
2. in `StringArray.astype()` convert to ExtensionArrayDTypes using `_from_sequence_of_strings` instead of `_from_sequence`.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.8.6.final.0
python-bits : 64
OS : Linux
OS-release : 5.8.0-45-generic
Version : #51-Ubuntu SMP Fri Feb 19 13:24:51 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.2.3
numpy : 1.19.2
pytz : 2020.5
dateutil : 2.8.1
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 : 2.8.5 (dt dec pq3 ext lo64)
jinja2 : None
IPython : 7.19.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 0.8.7
fastparquet : None
gcsfs : None
matplotlib : 3.3.4
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 3.0.0
pyxlsb : None
s3fs : None
scipy : 1.6.0
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
None
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} | 1 | "2021-03-22T13:33:39Z" | "2021-03-22T23:46:57Z" | "2021-03-22T17:06:08Z" | MEMBER | null | Follow-up on https://github.com/pandas-dev/pandas/pull/40527
There is no need for end-users to see this warning if an underlying library they use generates this, so using a DeprecationWarning instead of FutureWarning (as we did before with potentially noisy or internal warnings). At a later point we can change to FutureWarning. | {
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**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
# Your code here
Python 3.9.1 | packaged by conda-forge | (default, Dec 9 2020, 01:07:47)
[Clang 11.0.0 ] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import pandas as pd
>>> pd.__version__
'1.2.0'
>>> df=pd.read_excel('full_data.xlsx')
```
#### Problem description
I am not quite sure how to describe the bug, the code just got stuck when I run `pd.read_excel('full_data.xlsx')`. I found this line cost a significant amount of memories (almost `14G` but the `.xlsx` file is just `9MB`).
I speculate it is result from `read_excel` now leverage `openpyxl` as default engine in `python3.9`. Loading this file in `python3.8` works fine.
```
>>> from openpyxl import load_workbook
>>> wb=load_workbook('full_data.xlsx')
>>> df=pd.DataFrame(wb['Sheet1'].values)
```
The above codes also leads to the same issue.
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] | open | false | null | [] | null | 4 | "2021-03-22T17:39:36Z" | "2021-03-25T08:28:01Z" | null | NONE | null | I'd love it if Pandas could support Databricks' Delta Lake file format (https://github.com/delta-io/delta). It's a type of versioned parquet file format that supports updates/inserts/deletions.
In the past delta lake run only on spark but now there are connectors where spark is not required:
https://pypi.org/project/deltalake/
https://github.com/delta-io/connectors
https://github.com/delta-io/delta-rs/tree/main/python
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} | 0 | "2021-03-22T19:41:06Z" | "2021-06-08T12:55:41Z" | "2021-06-08T12:55:41Z" | MEMBER | null | In practice in all the cases I'm aware of, _can_hold_na is always fixed at the EA subclass level, so we can immediately infer _can_hold_na from the dtype. But in principle ATM an EA subclass could do
```
class WeirdEA(ExtensionArray):
@property
def _can_hold_na(self) -> bool:
return some_func(self[0])
```
We should make _can_hold_na an attribute of `ExtensionDtype` to pre-empt this. | {
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} | 3 | "2021-03-22T22:23:19Z" | "2021-04-01T16:16:09Z" | "2021-04-01T15:54:05Z" | MEMBER | null | - [x] closes #40518
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [x] whatsnew entry
Built on #40546, is a relatively minor change after that. | {
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- [ ] tests added / passed
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} | 2 | "2021-03-22T23:51:40Z" | "2021-03-23T01:27:46Z" | "2021-03-23T01:24:12Z" | MEMBER | null | Should be covered by the test which follows it since `pd.NA` is in `nulls_fixture` | {
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https://api.github.com/repos/pandas-dev/pandas/issues/40578 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40578/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40578/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40578/events | https://github.com/pandas-dev/pandas/pull/40578 | 838,316,663 | MDExOlB1bGxSZXF1ZXN0NTk4NTE3MDYy | 40,578 | CLN: remove unused kwarg from IntervalIndex._searchsorted_monotonic | {
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} | 0 | "2021-03-23T03:36:09Z" | "2021-03-23T15:20:34Z" | "2021-03-23T15:16:20Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
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- [x] I have confirmed this bug exists on the latest version of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
#### Code Sample, a copy-pastable example
```python
import pandas as pd
data = pd.DataFrame(
[
[1, "2020-01-01", "a", 1],
[2, "2020-01-01", "a", 13],
[2, "2020-01-02", "a", 4],
[1, "2020-01-01", "b", 5],
[1, "2020-01-02", "b", 6],
[1, "2020-01-03", "c", 9],
[2, "2020-01-03", "c", 11],
[2, "2020-01-03", "c", 12],
],
columns=["gr1", "date", "gr2", "value"],
)
data["date"] = pd.to_datetime(data["date"])
data.set_index(["date", "gr1", "gr2"], inplace=True)
data.sort_index(level="date", inplace=True)
print(data)
data.groupby(level="gr1").rolling(window="2D", level="date")["value"].max()
```
Output:
```
value
date gr1 gr2
2020-01-01 1 a 1
b 5
2 a 13
2020-01-02 1 b 6
2 a 4
2020-01-03 1 c 9
2 c 11
c 12
data.groupby(level="gr1").rolling(window="2D", level="date")["value"].max()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.9/site-packages/pandas/core/groupby/groupby.py", line 1866, in rolling
return RollingGroupby(self, *args, **kwargs)
File "/usr/local/lib/python3.9/site-packages/pandas/core/window/rolling.py", line 752, in __init__
super().__init__(obj, *args, **kwargs)
File "/usr/local/lib/python3.9/site-packages/pandas/core/window/rolling.py", line 113, in __init__
self.validate()
File "/usr/local/lib/python3.9/site-packages/pandas/core/window/rolling.py", line 1921, in validate
raise ValueError("window must be an integer")
ValueError: window must be an integer
```
#### Problem description
Non-integer rolling window seems to not be compatible with multi-index although the `level` is passed in the `rolling`. I am actually not sure if this is a Bug or design choice/design flaw. Note that the `gr2` column needs to stay in the index otherwise it will be "lost".
#### Expected Output
```
value
date gr1 gr2
2020-01-01 1 a 5
b 5
2 a 13
2020-01-02 1 b 6
2 a 13
2020-01-03 1 c 9
2 c 12
c 12
```
#### Output of ``pd.show_versions()``
<details>
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.9.2.final.0
python-bits : 64
OS : Darwin
OS-release : 20.3.0
Version : Darwin Kernel Version 20.3.0: Thu Jan 21 00:06:51 PST 2021; root:xnu-7195.81.3~1/RELEASE_ARM64_T8101
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 54.1.2
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>
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} | 4 | "2021-03-23T12:56:54Z" | "2021-03-24T07:31:08Z" | "2021-03-24T07:28:47Z" | MEMBER | null | This is a follow-up on https://github.com/pandas-dev/pandas/pull/40033, which changes the `_code` attribute of a Categorical into a property without a setter.
This broke dask / fastparquet, so this PR is making it settable again. We could deprecate the setter, though, at the same time. | {
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} | 5 | "2021-03-23T13:42:15Z" | "2021-04-30T20:49:50Z" | "2021-04-30T20:49:50Z" | 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 of pandas.
- [x] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
series = pd.Series([pd.NA, 1.0, 2.5], dtype=pd.Float64Dtype())
series.clip(upper=2.0)
```
#### Problem description
Pandas 1.2 cannot handle pd.NA values when the series has a Float64Dtype. When running the code snipped above, the following error occurs:
Traceback (most recent call last):
File "<input>", line 1, in <module>
File "C:\Users\XXX\AppData\Local\pypoetry\Cache\virtualenvs\XXX-w19Rd76b-py3.9\lib\site-packages\pandas\core\generic.py", line 7711, in clip
return self._clip_with_scalar(lower, upper, inplace=inplace)
File "C:\Users\XXX\AppData\Local\pypoetry\Cache\virtualenvs\XXX-w19Rd76b-py3.9\lib\site-packages\pandas\core\generic.py", line 7562, in _clip_with_scalar
subset = self.to_numpy() <= upper
File "pandas\_libs\missing.pyx", line 360, in pandas._libs.missing.NAType.__bool__
TypeError: boolean value of NA is ambiguous
#### Expected Output
pd.Series([pd.NA, 1.0, 2.0], dtype=pd.Float64Dtype)
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.9.1.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 85 Stepping 4, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0
Cython : None
pytest : 6.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.1
sqlalchemy : 1.4.2
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
numba : None
</details>
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https://api.github.com/repos/pandas-dev/pandas/issues/40582 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40582/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40582/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40582/events | https://github.com/pandas-dev/pandas/pull/40582 | 838,757,216 | MDExOlB1bGxSZXF1ZXN0NTk4ODgyMzQw | 40,582 | COMPAT: add back dummy CategoricalBlock class | {
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} | 7 | "2021-03-23T13:59:18Z" | "2021-03-23T16:29:28Z" | "2021-03-23T16:08:02Z" | MEMBER | null | See https://github.com/pandas-dev/pandas/issues/40226#issuecomment-804903010
@jbrockmendel this is unfortunate, but short term I think we need to keep the CategoricalBlock class. I am not directly sure what would be the best way to actually deprecate this. | {
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Giving the sample file:
```text
#empty
a,b,c
1,2,3
2,2,3
3,3,3
```
I want to skip text line starting with character '3':
```python
pd.read_csv(filepath, sep=',', comment='3', header=1)
```
#### Problem description
In the resulting dataframe the line starting with char '3' is skipped, but also other occurrences of '3' are replaced by nan's.
```text
a b c
0 1 2 nan
1 2 2 nan
```
#### Expected Output
I expect only record starting with the comment char is missing.
```text
a b c
0 1 2 3
1 2 2 3
```
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.8.3.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-136-generic
Version : #140-Ubuntu SMP Thu Jan 28 05:20:47 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.2.3
numpy : 1.19.0
pytz : 2020.5
dateutil : 2.8.1
pip : 21.0.1
setuptools : 53.0.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.8.6 (dt dec pq3 ext lo64)
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.4
numexpr : None
odfpy : None
openpyxl : 3.0.6
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.0
sqlalchemy : 1.3.23
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : None
numba : 0.50.0
</details>
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<details>
```
before after ratio
[05a0e98a] [16d06e22]
<master> <ref/deduplicate_grp_min_max>
33.0±3ms 33.3±1ms 1.01 gil.ParallelGroupbyMethods.time_loop(2, 'max')
32.2±0.4ms 34.5±3ms 1.07 gil.ParallelGroupbyMethods.time_loop(2, 'min')
64.1±1ms 65.6±0.5ms 1.02 gil.ParallelGroupbyMethods.time_loop(4, 'max')
65.3±3ms 65.5±1ms 1.00 gil.ParallelGroupbyMethods.time_loop(4, 'min')
20.2±2ms 20.2±0.8ms 1.00 gil.ParallelGroupbyMethods.time_parallel(2, 'max')
21.3±1ms 20.1±0.8ms 0.95 gil.ParallelGroupbyMethods.time_parallel(2, 'min')
25.1±0.7ms 25.3±0.5ms 1.01 gil.ParallelGroupbyMethods.time_parallel(4, 'max')
25.0±0.4ms 26.5±2ms 1.06 gil.ParallelGroupbyMethods.time_parallel(4, 'min')
125±50ms 104±1ms ~0.83 groupby.GroupByCythonAgg.time_frame_agg('float64', 'max')
105±2ms 107±2ms 1.02 groupby.GroupByCythonAgg.time_frame_agg('float64', 'min')
```
</details>
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} | 1 | "2021-03-23T14:51:17Z" | "2021-04-13T17:12:16Z" | "2021-04-13T17:12:16Z" | 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 of pandas.
- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
import pandas as pd
def test_groupby_any():
df = pd.DataFrame(
{
"ids": ["id1", "id1", "id2", "id2"],
"A": [True, False, pd.NA, True]
}
).astype({"ids": pd.StringDtype(),
"A": pd.BooleanDtype()})
result = df.groupby("ids").any(skipna=True)
expected = pd.DataFrame(
{
"A": [True, True]
}, index=pd.Series(["id1", "id2"], name="ids")
)
pd.testing.assert_frame_equal(expected, result)
```
#### Problem description
When running df.groupby(field_to_group_on).any(skipna=True) it should be expected that pd.NA values are neglected for the .any() method. However the output is this:
self = <BooleanArray>
[True, False, <NA>, True]
Length: 4, dtype: boolean
dtype = dtype('bool'), copy = True
def astype(self, dtype, copy: bool = True) -> ArrayLike:
"""
Cast to a NumPy array or ExtensionArray with 'dtype'.
Parameters
----------
dtype : str or dtype
Typecode or data-type to which the array is cast.
copy : bool, default True
Whether to copy the data, even if not necessary. If False,
a copy is made only if the old dtype does not match the
new dtype.
Returns
-------
ndarray or ExtensionArray
NumPy ndarray, BooleanArray or IntegerArray with 'dtype' for its dtype.
Raises
------
TypeError
if incompatible type with an BooleanDtype, equivalent of same_kind
casting
"""
from pandas.core.arrays.string_ import StringDtype
dtype = pandas_dtype(dtype)
if isinstance(dtype, BooleanDtype):
values, mask = coerce_to_array(self, copy=copy)
if not copy:
return self
else:
return BooleanArray(values, mask, copy=False)
elif isinstance(dtype, StringDtype):
return dtype.construct_array_type()._from_sequence(self, copy=False)
if is_bool_dtype(dtype):
# astype_nansafe converts np.nan to True
if self._hasna:
> raise ValueError("cannot convert float NaN to bool")
E ValueError: cannot convert float NaN to bool
#### Expected Output
```
expected = pd.DataFrame(
{
"A": [True, True]
}, index=pd.Series(["id1", "id2"], name="ids")
)
```
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.9.1.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 85 Stepping 4, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0
Cython : None
pytest : 6.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.3
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.1
sqlalchemy : 1.4.2
tables : None
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : None
numba : None
</details>
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} | 4 | "2021-03-23T14:53:20Z" | "2021-03-23T21:13:58Z" | "2021-03-23T20:28:33Z" | MEMBER | null | Shaves about 10% off the benchmark discussed in https://github.com/pandas-dev/pandas/pull/40171#issuecomment-790219422 | {
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] | open | false | null | [] | null | 3 | "2021-03-23T14:54:02Z" | "2021-08-23T04:05:48Z" | null | NONE | null | I sometimes receive a `Error tokenizing data. C error: ...` for tables that can normally be read with `read_csv()` without any problems.
Find attached the .csv file [sample.tar.gz](https://github.com/pandas-dev/pandas/files/6190356/sample.tar.gz) for which I can reproduce the problem.
```python
import pandas as pd
path = "sample.csv"
pd.read_csv(path, sep=";", header=[0,1])
```
This raises the following exception:
```lang-text
ParserError: Error tokenizing data. C error: Expected 15 fields in line 983050, saw 23
```
The tables I try to read have 23 columns, as declared correctly in the file header. However, the files contain corrupted lines (very few, <0.01% of all lines), where the data of 8 columns are omitted. For those lines, 8 delimiters are missing.
I'm working with about 100 different files containing 1M to 20M lines. All files suffer from the same kind of ill-formatted lines. `read_csv()` graciously handles those lines most of the time. Only for the file provided above, it raises an exception.
I can avoid the exception as follows:
- Delete a couple of unrelated (healthy) lines at the beginning of the document
- By setting `engine="python"` (slow)
- By setting `low_memory=False`
- By setting `error_bad_lines=False` (drops a couple of lines)
In summary, I think `read_csv()` behaves inconsistently if running with `low-memory=True` and C-engine.
I first thought that the problem is related to issue #11166, but I'm not sure 100%.
[sample.tar.gz](https://github.com/pandas-dev/pandas/files/6190356/sample.tar.gz)
I'm running python3.8 and pandas 1.2.3. See details below.
#### Expected Output
No exception for file `sample.csv`, regardless of the settings for `engine` and `low_memory`.
#### System
<details>
```lang-text
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.8.0.final.0
python-bits : 64
OS : Darwin
OS-release : 18.7.0
Version : Darwin Kernel Version 18.7.0: Fri Oct 30 12:37:06 PDT 2020; root:xnu-4903.278.44.0.2~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : None.UTF-8
pandas : 1.2.3
numpy : 1.20.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.3.3
setuptools : 54.1.2
Cython : None
pytest : 6.2.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 7.13.0
pandas_datareader: None
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 : 1.0.0
pyxlsb : None
s3fs : None
scipy : 1.3.2
sqlalchemy : None
tables : 3.6.1
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
```
</details>
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] | open | false | null | [] | null | 5 | "2021-03-23T14:54:53Z" | "2021-03-24T17:01:09Z" | null | NONE | null | import pandas as pd
df = pd.DataFrame(data={'col1': [1, 2], 'col2': [3, 4]})
df.to_parquet('df.parquet',compression=None, index=False)
pd.read_parquet('df.parquet')
I am running this code and it shows index. I set index as False. | {
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] | open | false | null | [] | null | 1 | "2021-03-23T15:18:02Z" | "2021-08-19T02:52:23Z" | 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 of pandas.
---
#### Code Sample, a copy-pastable example
**test.txt file** :
5 6
7 8
9 10
```python
# Your code here
import pandas as pd
print(pd.__version__)
print("Case 1: no converters or dtype. ")
a = pd.read_csv("test.txt", sep="\t", index_col=["Index"], names=["Index", "Length"])
print(a["Length"])
print(a.index)
print("Case 2: converters option")
a = pd.read_csv("test.t", sep="\t", index_col=["Index"], names=["Index", "Length"], converters={"Index": str, "Length": str})
print(a["Length"])
print(a.index)
print("Case 3: dtype option")
a = pd.read_csv("test.t", sep="\t", index_col=["Index"], names=["Index", "Length"], dtype={"Index": str, "Length": str})
print(a["Length"])
print(a.index)
```
#### Problem description
Output of code above:
Case 1: no converters or dtype.
Index
5 6
7 8
9 10
Name: Length, dtype: int64
Int64Index([5, 7, 9], dtype='int64', name='Index')
Case 2: converters option
Index
5 6
7 8
9 10
Name: Length, dtype: object
**Int64Index([5, 7, 9], dtype='int64', name='Index')**
Case 3: dtype option
Index
5 6
7 8
9 10
Name: Length, dtype: object
**Int64Index([5, 7, 9], dtype='int64', name='Index')**
Converters and dtype are not applied to index column when reading file via pd.read_csv .
In all three cases type of index elements remains **int** .
Other columns are converted as expected.
#### Expected Output
In "Case 2" and "Case 3" type of index elements expected to be **str**.
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.8.5.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-54-generic
Version : #58-Ubuntu SMP Mon Jun 24 10:55:24 UTC 2019
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.2.3
numpy : 1.19.2
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.4
setuptools : 50.3.1.post20201107
Cython : 0.29.21
pytest : 6.1.1
hypothesis : None
sphinx : 3.2.1
blosc : None
feather : None
xlsxwriter : 1.3.7
lxml.etree : 4.6.1
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.19.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : 1.3.2
fsspec : 0.8.3
fastparquet : None
gcsfs : None
matplotlib : 3.3.2
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.5
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.5.2
sqlalchemy : 1.3.20
tables : 3.6.1
tabulate : None
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.51.2
</details>
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- [x] I have asked my usage related question on [StackOverflow](https://stackoverflow.com).
---
#### Question about pandas
```
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randint(0,10,size=(10, 4)), columns=list('ABCD'))
df.A = df.agg('City_{0[A]}'.format, axis=1)
df.index = (df.index)*int(np.random.randint(6,23)**0.5)+int(np.random.randint(2,23))
```
**This is my df:**
A | B | C | D
-- | -- | -- | --
City_2 | 3 | 7 | 3
City_0 | 4 | 8 | 9
City_1 | 1 | 2 | 1
City_5 | 5 | 0 | 9
City_5 | 1 | 6 | 0
City_0 | 3 | 8 | 6
City_7 | 2 | 6 | 6
City_1 | 6 | 0 | 2
City_8 | 6 | 2 | 4
City_2 | 2 | 5 | 6
If I do
`df.groupby([df.index//5,df.A], as_index=True).mean()`
or
`df.groupby([df.index//5,df.A]).mean()`
**Result:**
| | | B | C | D |
|--:|-------:|--:|--:|--:|
| | A | | | |
| 1 | City_2 | 3 | 7 | 3 |
| 2 | City_0 | 4 | 8 | 9 |
| 3 | City_1 | 1 | 2 | 1 |
| | City_5 | 5 | 0 | 9 |
| 4 | City_0 | 3 | 8 | 6 |
| | City_5 | 1 | 6 | 0 |
| 5 | City_7 | 2 | 6 | 6 |
| 6 | City_1 | 6 | 0 | 2 |
| | City_8 | 6 | 2 | 4 |
| 7 | City_2 | 2 | 5 | 6 |
So If do `.reset_index()`
I will get this (that index with no column name will get name as `level_0` ):
level_0 | A | B | C | D
-- | -- | -- | -- | --
1 | City_2 | 3 | 7 | 3
2 | City_0 | 4 | 8 | 9
3 | City_1 | 1 | 2 | 1
3 | City_5 | 5 | 0 | 9
4 | City_0 | 3 | 8 | 6
4 | City_5 | 1 | 6 | 0
5 | City_7 | 2 | 6 | 6
6 | City_1 | 6 | 0 | 2
6 | City_8 | 6 | 2 | 4
7 | City_2 | 2 | 5 | 6
The same is not with the `as_index=False`
`df.groupby([df.index//5,df.A], as_index=False).mean()` will give me
A | B | C | D
-- | -- | -- | --
City_2 | 3 | 7 | 3
City_0 | 4 | 8 | 9
City_1 | 1 | 2 | 1
City_5 | 5 | 0 | 9
City_0 | 3 | 8 | 6
City_5 | 1 | 6 | 0
City_7 | 2 | 6 | 6
City_1 | 6 | 0 | 2
City_8 | 6 | 2 | 4
City_2 | 2 | 5 | 6
I will lose the `groupby index info`.
**My question:**
shouldn't be `as_index=False` give `df.index//5` column also. Or `as_index` is designed to work like this only.
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} | 3 | "2021-03-23T16:14:13Z" | "2021-03-25T13:40:11Z" | "2021-03-23T20:30:31Z" | MEMBER | null | - [x] closes #39595
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [x] whatsnew entry
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} | 4 | "2021-03-23T20:01:24Z" | "2021-04-02T17:15:27Z" | "2021-04-02T17:15:22Z" | CONTRIBUTOR | null | Adds a test for loc on sparse dataframes.
- [x] closes #34687
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
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} | 3 | "2021-03-23T20:09:19Z" | "2021-03-29T15:02:01Z" | "2021-03-29T14:55:35Z" | MEMBER | null | - [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
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} | 2 | "2021-03-23T20:20:40Z" | "2021-03-24T23:13:35Z" | "2021-03-24T23:13:35Z" | MEMBER | null | Following https://pandas.pydata.org/pandas-docs/stable/development/contributing.html#creating-a-python-environment-pip to create dev environemnt
However, some failure pops up
```
ERROR: Command errored out with exit status 1:
command: /Users/kaiqidong/pyvenv/pandas-dev/bin/python -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/private/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/pip-install-a1dqlo0f/fastparquet_1298cd7d34ec45bc9cadbaacbc22c22c/setup.py'"'"'; __file__='"'"'/private/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/pip-install-a1dqlo0f/fastparquet_1298cd7d34ec45bc9cadbaacbc22c22c/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' egg_info --egg-base /private/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/pip-pip-egg-info-rsz4xmwi
cwd: /private/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/pip-install-a1dqlo0f/fastparquet_1298cd7d34ec45bc9cadbaacbc22c22c/
Complete output (95 lines):
Processing numpy/random/_bounded_integers.pxd.in
Processing numpy/random/_philox.pyx
Traceback (most recent call last):
File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/tools/cythonize.py", line 59, in process_pyx
from Cython.Compiler.Version import version as cython_version
ModuleNotFoundError: No module named 'Cython'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/tools/cythonize.py", line 235, in <module>
main()
File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/tools/cythonize.py", line 231, in main
find_process_files(root_dir)
File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/tools/cythonize.py", line 222, in find_process_files
process(root_dir, fromfile, tofile, function, hash_db)
File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/tools/cythonize.py", line 188, in process
processor_function(fromfile, tofile)
File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/tools/cythonize.py", line 64, in process_pyx
raise OSError('Cython needs to be installed in Python as a module')
OSError: Cython needs to be installed in Python as a module
Running from numpy source directory.
/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py:485: UserWarning: Unrecognized setuptools command, proceeding with generating Cython sources and expanding templates
run_build = parse_setuppy_commands()
Traceback (most recent call last):
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 154, in save_modules
yield saved
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 195, in setup_context
yield
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 250, in run_setup
_execfile(setup_script, ns)
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 45, in _execfile
exec(code, globals, locals)
File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py", line 513, in <module>
File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py", line 493, in setup_package
File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py", line 290, in generate_cython
RuntimeError: Running cythonize failed!
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/private/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/pip-install-a1dqlo0f/fastparquet_1298cd7d34ec45bc9cadbaacbc22c22c/setup.py", line 52, in <module>
setup(
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/__init__.py", line 144, in setup
_install_setup_requires(attrs)
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/__init__.py", line 139, in _install_setup_requires
dist.fetch_build_eggs(dist.setup_requires)
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/dist.py", line 716, in fetch_build_eggs
resolved_dists = pkg_resources.working_set.resolve(
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/pkg_resources/__init__.py", line 780, in resolve
dist = best[req.key] = env.best_match(
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/pkg_resources/__init__.py", line 1065, in best_match
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File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/pkg_resources/__init__.py", line 1077, in obtain
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File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/dist.py", line 786, in fetch_build_egg
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File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/command/easy_install.py", line 705, in install_item
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File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/command/easy_install.py", line 890, in install_eggs
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File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/command/easy_install.py", line 1158, in build_and_install
self.run_setup(setup_script, setup_base, args)
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/command/easy_install.py", line 1144, in run_setup
run_setup(setup_script, args)
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 253, in run_setup
raise
File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.8/lib/python3.8/contextlib.py", line 131, in __exit__
self.gen.throw(type, value, traceback)
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 195, in setup_context
yield
File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.8/lib/python3.8/contextlib.py", line 131, in __exit__
self.gen.throw(type, value, traceback)
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 166, in save_modules
saved_exc.resume()
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 141, in resume
six.reraise(type, exc, self._tb)
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/_vendor/six.py", line 685, in reraise
raise value.with_traceback(tb)
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 154, in save_modules
yield saved
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 195, in setup_context
yield
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 250, in run_setup
_execfile(setup_script, ns)
File "/Users/kaiqidong/pyvenv/pandas-dev/lib/python3.8/site-packages/setuptools/sandbox.py", line 45, in _execfile
exec(code, globals, locals)
File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py", line 513, in <module>
File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py", line 493, in setup_package
File "/var/folders/sq/gc62mtns2n1gg_pgs6q2g0zw0000gn/T/easy_install-v2l4o5n8/numpy-1.20.1/setup.py", line 290, in generate_cython
RuntimeError: Running cythonize failed!
Cythonizing sources
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/58/49/dccb790fa17ab3fbf84a6b848050083c7a1899e9586000e34e3e4fbf5538/fastparquet-0.3.2.tar.gz#sha256=d81dcec444f4c4829234b9baac57c7125b8fbe9119c2eca2dee922650db49205 (from https://pypi.org/simple/fastparquet/) (requires-python:>=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*,). Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.
ERROR: Could not find a version that satisfies the requirement fastparquet>=0.3.2
ERROR: No matching distribution found for fastparquet>=0.3.2
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} | 1 | "2021-03-23T20:51:09Z" | "2021-04-21T06:09:13Z" | "2021-04-20T23:01:03Z" | CONTRIBUTOR | null | A PR for Europeans:

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- [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
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} | 1 | "2021-03-23T21:26:51Z" | "2021-03-24T23:13:39Z" | "2021-03-24T23:13:35Z" | MEMBER | null | - [x] closes #40595
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
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xref #39776
xref https://github.com/dask/fastparquet/issues/576#issuecomment-805220721 | {
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- [Zoom link](https://nyu.zoom.us/j/98201283174?pwd=d0VoUy9GTDRlVVZ0cCtTK0s4NnlBZz09)
- [Agenda/notes](https://docs.google.com/document/d/1JoiqTdK6gi5W1QiTWrqtTV-rNmIqU3xROgHY5iT4J5g/edit#heading=h.98uhh75g3r7w)
---
A time to talk about pandas documentation. [Agenda/notes doc](https://docs.google.com/document/d/1JoiqTdK6gi5W1QiTWrqtTV-rNmIqU3xROgHY5iT4J5g/edit#heading=h.1obsyhexqytc) — feel free to add things in advance. All are welcome. Thanks!
@pandas-dev/pandas-core @pandas-dev/pandas-triage @pandas-dev/pydata-sphinx-theme @pandas-dev/pandas-docs | {
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} | 3 | "2021-03-24T02:29:31Z" | "2021-03-26T11:24:25Z" | "2021-03-25T01:51:54Z" | MEMBER | null | - [x] closes #39338
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [x] whatsnew entry
Issue comes from the first pair in the `regex` arg hitting the simple replace path, which causes the `ObjectBlock` to be split. From here, the mask indexing will be wrong, but that will not cause an error unless a later pair hits `_replace_regex`, which actually uses the mask. | {
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] | open | false | null | [] | null | 1 | "2021-03-24T04:37:24Z" | "2021-08-19T02:53:04Z" | null | NONE | null | So I found this issue was fixed in 2017 and 2019 respectively, however I think it's back. I spent half the day trying to figure out what I was doing wrong until I stumbled upon this thread/report: https://github.com/pandas-dev/pandas/issues/16822
And it seems like the bug may have crawled its way back in? Sorry if I should not have opened a new bug report however you mentioned opening a new bug report for the 2019 reports of this bug so I figured I would report that it might be back as well.
- [x ] I have checked that this issue has not already been reported.
- [x ] I have confirmed this bug exists on the latest version of pandas.
- [x ] (optional) I have confirmed this bug exists on the master branch of pandas.
---
**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
#### Code Sample, a copy-pastable example
```python
fullColors = list(itertools.repeat('#3FD21C',10)) + list(itertools.repeat('#ED5851',25))
df.plot(kind='bar', logy='sym', color=fullColors)
plt.show()
```
#### Problem description
So I have a dataframe with 1 data column and an index column, the dataframe has 50 values/rows in it and when i pass in a list of 50 colors I would expect those colors get matched up with each bar (or in my case half the bars are one color and half another) however only the first color passed in gets used to color all of the bars.
#### Expected Output
A bar graph with multiple colored bars rather than just 1 color
#### Output of ``pd.show_versions()``
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.8.8.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 11, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.2.3
numpy : 1.18.5
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 52.0.0.post20210125
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 1.3.7
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.21.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.4
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.1
sqlalchemy : 1.3.18
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
None
</details>
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} | 0 | "2021-03-24T07:30:45Z" | "2021-05-12T13:52:59Z" | "2021-05-12T13:52:59Z" | MEMBER | null | Needed follow-up on https://github.com/pandas-dev/pandas/pull/40580 (and https://github.com/pandas-dev/pandas/pull/40033), we should deprecate the setter of the `Categorical._codes` property.
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ImportError: cannot import name 'FrameOrSeriesUnion' from 'pandas._typing' (C:\Users\ASUS\Anaconda3\lib\site-packages\pandas\_typing.py)
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] | open | false | null | [] | null | 1 | "2021-03-24T08:38:30Z" | "2021-08-25T21:11:03Z" | null | CONTRIBUTOR | null | - [x] I have checked that this issue has not already been reported.
The issue may be related to issue #34133
- [x] I have confirmed this bug exists on the latest version of pandas.
---
#### Code Sample, a copy-pastable example
```python
import pandas
idx_single = pandas.RangeIndex(10)
idx_double = pandas.Index(idx_single.tolist() + idx_single.tolist())
# idx_double
df1 = pandas.DataFrame(index=idx_double)
df2 = pandas.DataFrame(index=idx_single, data=1, columns=["one", "two"])
print(df1.index)
print(df1.join(df2, how="left", sort=False).index)
print(df1.merge(df2, how="left", right_index=True, left_index=True, sort=False).index)
```
#### Problem description
The index of the joined (or merged) dataframe is not the same as the left hand dataframe even though sort=False.
```
Int64Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64')
Int64Index([0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9], dtype='int64')
Int64Index([0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9], dtype='int64')
```
#### Expected Output
I would expect the index of the joined/merged dataframe to be the same as the left hand dataframe.
```
Int64Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64')
Int64Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64')
Int64Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64')
```
#### Output of ``pd.show_versions()``
<details>
INSTALLED VERSIONS
------------------
commit : f2c8480af2f25efdbd803218b9d87980f416563e
python : 3.9.0.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.18362
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : French_Belgium.1252
pandas : 1.2.3
numpy : 1.20.1
pytz : 2021.1
dateutil : 2.8.1
pip : 21.0.1
setuptools : 49.2.0
</details>
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} | 4 | "2021-03-24T08:42:22Z" | "2021-03-24T14:10:22Z" | "2021-03-24T14:08:52Z" | MEMBER | null | Closes #40500, see that issue for the analysis of speedup vs size.
Another take of https://github.com/pandas-dev/pandas/pull/40502, but hopefully now without crashing the tests because of increased memory use. | {
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Mac M1
Python 3.8.2 created using Xcode Command Line Tools for M1 Macs
On trying to install pandas, it failed and it returns very long erorr message starts as below
(py382tf) mgd@MGD ~ % pip install pandas
Collecting pandas
Using cached https://files.pythonhosted.org/packages/8a/6f/7fcef020b5b305862cacf376183eaa0f907f2fa42f0b687b2a9a2c6cda4d/pandas-1.2.3.tar.gz
Installing build dependencies ... error
ERROR: Command errored out with exit status 1:
command: /Users/mgd/py382tf/bin/python3 /Users/mgd/py382tf/lib/python3.8/site-packages/pip install --ignore-installed --no-user --prefix /private/var/folders/px/zqhcsbbx4yxfmhc7927tnfj00000gn/T/pip-build-env-orb4vxpv/overlay --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- setuptools wheel 'Cython>=0.29.21,<3' 'numpy==1.16.5; python_version=='"'"'3.7'"'"' and platform_system!='"'"'AIX'"'"'' 'numpy==1.17.3; python_version=='"'"'3.8'"'"' and platform_system!='"'"'AIX'"'"'' 'numpy==1.16.5; python_version=='"'"'3.7'"'"' and platform_system=='"'"'AIX'"'"'' 'numpy==1.17.3; python_version=='"'"'3.8'"'"' and platform_system=='"'"'AIX'"'"'' 'numpy; python_version>='"'"'3.9'"'"''
cwd: None
Complete output (4451 lines):
Ignoring numpy: markers 'python_version == "3.7" and platform_system != "AIX"' don't match your environment
Ignoring numpy: markers 'python_version == "3.7" and platform_system == "AIX"' don't match your environment
Ignoring numpy: markers 'python_version == "3.8" and platform_system == "AIX"' don't match your environment
Ignoring numpy: markers 'python_version >= "3.9"' don't match your environment
Collecting setuptools
Using cached https://files.pythonhosted.org/packages/9e/d4/b99a960314121a003e9f39c61dfde01a1010bb47661e193a7722f7f32d52/setuptools-54.2.0-py3-none-any.whl
Collecting wheel
Using cached https://files.pythonhosted.org/packages/65/63/39d04c74222770ed1589c0eaba06c05891801219272420b40311cd60c880/wheel-0.36.2-py2.py3-none-any.whl
Collecting Cython<3,>=0.29.21
Using cached https://files.pythonhosted.org/packages/9e/98/bff39b3acaebbc6102be71797f655bbe60738f7339db4ad7bd0772c08daf/Cython-0.29.22-py2.py3-none-any.whl
Collecting numpy==1.17.3
Using cached https://files.pythonhosted.org/packages/b6/d6/be8f975f5322336f62371c9abeb936d592c98c047ad63035f1b38ae08efe/numpy-1.17.3.zip
Installing collected packages: setuptools, wheel, Cython, numpy
Running setup.py install for numpy: started
Running setup.py install for numpy: finished with status 'error'
ERROR: Command errored out with exit status 1:
command: /Users/mgd/py382tf/bin/python3 -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/private/var/folders/px/zqhcsbbx4yxfmhc7927tnfj00000gn/T/pip-install-x_x_2bsb/numpy/setup.py'"'"'; __file__='"'"'/private/var/folders/px/zqhcsbbx4yxfmhc7927tnfj00000gn/T/pip-install-x_x_2bsb/numpy/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /private/var/folders/px/zqhcsbbx4yxfmhc7927tnfj00000gn/T/pip-record-73r6zlw4/install-record.txt --single-version-externally-managed --prefix /private/var/folders/px/zqhcsbbx4yxfmhc7927tnfj00000gn/T/pip-build-env-orb4vxpv/overlay --compile --install-headers /Users/mgd/py382tf/include/site/python3.8/numpy
cwd: /private/var/folders/px/zqhcsbbx4yxfmhc7927tnfj00000gn/T/pip-install-x_x_2bsb/numpy/
Complete output (4428 lines):
Running from numpy source directory.
Note: if you need reliable uninstall behavior, then install
with pip instead of using `setup.py install`:
- `pip install .` (from a git repo or downloaded source
release)
- `pip install numpy` (last NumPy release on PyPi)
blas_opt_info:
blas_mkl_info:
customize UnixCCompiler
libraries mkl_rt not found in ['/Users/mgd/py382tf/lib', '/usr/lib']
NOT AVAILABLE
blis_info:
customize UnixCCompiler
libraries blis not found in ['/Users/mgd/py382tf/lib', '/usr/lib']
NOT AVAILABLE
openblas_info:
customize UnixCCompiler
customize UnixCCompiler
libraries openblas not found in ['/Users/mgd/py382tf/lib', '/usr/lib']
NOT AVAILABLE
atlas_3_10_blas_threads_info:
Setting PTATLAS=ATLAS
customize UnixCCompiler
libraries tatlas not found in ['/Users/mgd/py382tf/lib', '/usr/lib']
NOT AVAILABLE
atlas_3_10_blas_info:
customize UnixCCompiler
libraries satlas not found in ['/Users/mgd/py382tf/lib', '/usr/lib']
NOT AVAILABLE
atlas_blas_threads_info:
Setting PTATLAS=ATLAS
customize UnixCCompiler
libraries ptf77blas,ptcblas,atlas not found in ['/Users/mgd/py382tf/lib', '/usr/lib']
NOT AVAILABLE
atlas_blas_info:
customize UnixCCompiler
libraries f77blas,cblas,atlas not found in ['/Users/mgd/py382tf/lib', '/usr/lib']
NOT AVAILABLE
accelerate_info:
customize UnixCCompiler
libraries accelerate not found in ['/Users/mgd/py382tf/lib', '/usr/lib']
Library accelerate was not found. Ignoring
customize UnixCCompiler
libraries veclib not found in ['/Users/mgd/py382tf/lib', '/usr/lib']
Library veclib was not found. Ignoring
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https://api.github.com/repos/pandas-dev/pandas/issues/40612 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/40612/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/40612/comments | https://api.github.com/repos/pandas-dev/pandas/issues/40612/events | https://github.com/pandas-dev/pandas/pull/40612 | 839,859,959 | MDExOlB1bGxSZXF1ZXN0NTk5ODA1Nzg2 | 40,612 | TYP: get_indexer | {
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} | 12 | "2021-03-24T15:42:31Z" | "2021-04-19T19:00:57Z" | "2021-04-19T18:54:32Z" | MEMBER | null | @simonjayhawkins im at a loss on why im getting a mypy complaint:
```
error: Overloaded function signatures 1 and 2 overlap with incompatible return types [misc]
```
AFAICT they should be compatible. Am I missing something obvious? | {
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] | open | false | null | [] | null | 0 | "2021-03-24T16:13:21Z" | "2021-08-19T02:56:32Z" | null | NONE | null | It would be good to have the capability to upsample using `.resample()` and forward fill using `.ffill()` on either axis.
It seems to be blocked by the Assertion Error here, but I can' see a clear reason.
https://github.com/pandas-dev/pandas/blob/a20c169f8aee9c272953be43d89dfa82be5e186b/pandas/core/resample.py#L1153
```python
# Code to reproduce.
import pandas as pd
dt_idx = pd.period_range(start='2021-01-01', freq='M', periods=3).to_timestamp()
# Transpose to have time series on columns
df = pd.DataFrame(range(3), index=dt_idx).T
resampled = df.resample('W-Mon', axis=1).ffill()
```
There is a workaround below so this is issue is low priority.
```python
# Current workaround.
import pandas as pd
dt_idx = pd.period_range(start='2021-01-01', freq='M', periods=3).to_timestamp()
# Transpose to have time series on columns
df = pd.DataFrame(range(3), index=dt_idx).T
resampled = df.resample('W-Mon', axis=1).first().ffill(axis=1)
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry
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