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} | 0 | "2021-10-29T02:21:02Z" | "2021-10-29T17:04:33Z" | "2021-10-29T16:05:30Z" | MEMBER | null | - [x] closes #27167
- [ ] 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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} | 7 | "2021-10-29T11:01:32Z" | "2021-11-01T00:28:35Z" | "2021-10-29T16:24:01Z" | CONTRIBUTOR | null | - When running an arm32 ("linux32'd") chroot on an arm64 machine,
Python's platform.machine() will return "armv8l".
- In other cases, on "real" arm32, it'll return whatever uname says
(just like in the first case) which might be e.g. armv7a.
Keeping the other options ("aarch64", "arm64") given that Windows
or other kernels might choose to return different values and these
were added for a reason, but at least this fixes detection on Linux.
This allows tests like test_subtype_integer_errors to be skipped
as intended on arm.
Bug: https://bugs.gentoo.org/818964
Signed-off-by: Sam James <[email protected]>
- [X] tests added / passed
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- [x] Added two examples to the documentation of DataFrame.std function so that users can understand how to use it with different delta degrees of freedom.
- [ ] Add examples to the documentation of DataFrame.var function
---
- [x] tests added / passed
- [x] All pre-commit linting tests pass
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} | 3 | "2021-10-29T16:00:29Z" | "2021-10-30T06:49:25Z" | "2021-10-29T16:07:03Z" | 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
My code runs successfully, but nothing inserted to the table, only old records returned
### Question about pandas
import pandas as pd
from sqlalchemy import create_engine
from snowflake.sqlalchemy import URL
from config import config
engine = create_engine(URL(account=config.account,
user=config.username,
password=config.password,
warehouse=config.warehouse,
database=config.database,
schema=config.schema,))
conn = engine.connect()
df = pd.DataFrame([('AAA', '1234'), ('BBB', '5678')], columns=['name', 'pswd'])
df.to_sql('demo_db.public.test_f1', con=engine, index=False, if_exists='append', index_label=None)
df = pd.read_sql_query('select * from demo_db.public.test_f1', conn)
print(df.head(5))
conn.close()
engine.dispose() | {
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} | 2 | "2021-10-29T17:24:27Z" | "2021-11-10T19:25:10Z" | "2021-11-10T19:25:10Z" | 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
> raise_assert_detail(obj, msg, lobj, robj, index_values=index_values)
E AssertionError: DataFrame.iloc[:, 1] (column name="X2") are different
E
E DataFrame.iloc[:, 1] (column name="X2") values are different (100.0 %)
E [index]: [1999-01-27T19:00:00.000000000, 1999-01-27T20:00:00.000000000, 1999-01-27T21:00:00.000000000, 1999-01-27T21:00:00.000000000, 1999-01-27T22:00:00.000000000]
E [left]: [18:56:00, 19:56:00, 20:56:00, 21:18:00, 21:56:00]
E [right]: [ 18:56:00, 19:56:00, 20:56:00, 21:18:00, 21:56:00]
```
### Issue Description
cc @jorisvandenbossche
### Expected Behavior
NA
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
</details>
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- [ ] whatsnew entry
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draft since will rebase once #43828 is merged.
cc @twoertwein @mroeschke | {
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] | open | false | null | [] | null | 0 | "2021-10-30T15:35:42Z" | "2021-10-30T23:59:42Z" | null | MEMBER | 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.
- [X] I have confirmed this issue exists on the master branch of pandas.
### Reproducible Example
In reshape.merge we do some some casting motivated by what dtypes HashTable supports, see the comment '# upcast 'by' parameter because HashTable is limited'. That comment is no longer accurate, and we can avoid some of this casting. Something like core.algorithms._ensure_data may be reusable.
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
</details>
### Prior Performance
_No response_ | {
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] | open | false | null | [] | null | 0 | "2021-10-30T19:37:00Z" | "2021-10-31T00:00:40Z" | null | 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
ser = pd.Series([True, None, False, True, None], dtype=object)
>>> ser.fillna(True, downcast=None)
0 True
1 True
2 False
3 True
4 True
dtype: bool
>>> ser.fillna(True, downcast="infer")
0 True
1 True
2 False
3 True
4 True
dtype: object
```
### Issue Description
Note that downcast=None is the default, so this also happens with just `ser.fillna(True)`.
Disabling the special-casing for object dtype in Block._maybe_downcast breaks 9 tests. I need to check, think there may be some EA cases that aren't tested but where behavior would change if removed that special-casing.
### Expected Behavior
I'd expect it to go the other way, with object dtype retained with downcast=None and bool inferred with downcast="infer"
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
</details>
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} | 0 | "2021-10-30T23:58:48Z" | "2021-10-31T13:17:53Z" | "2021-10-31T11:48:27Z" | MEMBER | null | Reverts pandas-dev/pandas#44208
THIS IS ONLY ON 1.3.x.
Let's try reverting this. In theory, the test changes that caused the timeouts shouldn't be backported, so this shouldn't be needed. | {
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} | 2 | "2021-10-31T03:29:23Z" | "2021-11-01T21:45:20Z" | "2021-11-01T13:14:52Z" | MEMBER | null | - [x] closes #16380
- [x] closes #14135
- [x] closes #16577
- [x] closes #16925
- [x] closes #17093
- [x] closes #17382
- [x] closes #18050
- [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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] | open | false | null | [] | null | 2 | "2021-10-31T03:36:26Z" | "2021-11-14T04:14:35Z" | null | NONE | null | #### Is your feature request related to a problem?
"I wish I could use pandas to" store a `DataFrame` with `to_hdf` and optionally include the datetime of dataset creation/modification.
#### Describe the solution you'd like
`DataFrame.to_hdf` should have an option that will store the datetime of dataset creation/modification.
[docstring addition]
```
with_datetime : bool, default False
Stores `datetime` when dataset is written
```
#### API breaking implications
Shouldn't break anything.
#### Describe alternatives you've considered
A separate "metafile" that the user would need to write with dataset creation/modification datetimes.
#### Additional context
With the possibility of rewriting datasets, having the creation and modification times of the dataset in the HDF5 file would help to inform HDF5 file readers/users of updated datasets.
```python
my_df.to_pdf(..., with_datetime=True, ...)
...
my_df_read = pd.read_hdf(store_file, key=key_value, mode="r")
print(my_df_read.ctime) # None or datetime
print(my_df_read.mtime) # None or datetime
...
my_df_read.info() # Would also show datetimes if present
```
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} | 0 | "2021-10-31T07:13:43Z" | "2021-11-01T13:50:39Z" | "2021-11-01T13:50:39Z" | 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
see image
```
### Issue Description
The body seems to render but the index headers do not appear.
### Expected Behavior
Index headers visible.
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
</details>
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} | 1 | "2021-10-31T07:54:14Z" | "2021-11-01T13:50:44Z" | "2021-11-01T13:50:40Z" | CONTRIBUTOR | null | There was a previous fix for #43703 but that dealt only with the SingleIndex case
- [x] closes #44247
- [x] tests added / passed
- [x] whatsnew entry
Visuals of the fix compared to the issue:
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} | 3 | "2021-10-31T07:57:37Z" | "2021-11-13T17:03:35Z" | "2021-11-13T17:03:31Z" | CONTRIBUTOR | null | - [x] closes #43668
- [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
I've added a fixture for the specific construction of a subclassed dataframe from the issue - which mirrors the setup in geopandas, I expect this probably needs to be relocated (I could have constructed this inline with the test and maybe that's the right solution, but I can see analogous changes for `astype` perhaps being useful in the geopandas context as well).
I've also added the call to `__finalize__` although it's not strictly needed, since that's also needed by #28283 (Note that the 1 dimensional case already has `__finalize__` called indirectly via `astype`.
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- [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/user_guide/options.html
### Documentation problem
The narrative mentions `e.g. display.max_colwidth, display.max_rows, display.max_columns`, but the example references `pd.get_option("column")`
### Suggested fix for documentation
Perhaps, `pd.get_option("max")` would be more intuitive. | {
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} | 6 | "2021-10-31T13:33:16Z" | "2021-11-14T19:45:26Z" | null | CONTRIBUTOR | null | The two big parts missing from #43744 are interval.pyi and offsets.pyi as they result in many mypy errors.
I had already made changes to somewhat accommodate for interval.pyi and offsets.pyi (if these files are included, we have now "only" ~100 mypy errors). I kept these changes in this PR. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/44252 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44252/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44252/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44252/events | https://github.com/pandas-dev/pandas/issues/44252 | 1,040,499,991 | I_kwDOAA0YD84-BMUX | 44,252 | BUG: multi level index may throws KeyError with a number instead of specified keys | {
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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
>>> import pandas as pd
>>> df = pd.DataFrame({('A', 'a') : [1], ('A', 'b') : [2], ('B', 'c') : [3], ('B', 'd') : [4]})
>>> df
A B
a b c d
0 1 2 3 4
>>> df[('A', 'c')]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.8/site-packages/pandas/core/frame.py", line 3457, in __getitem__
return self._getitem_multilevel(key)
File "/usr/local/lib/python3.8/site-packages/pandas/core/frame.py", line 3508, in _getitem_multilevel
loc = self.columns.get_loc(key)
File "/usr/local/lib/python3.8/site-packages/pandas/core/indexes/multi.py", line 2932, in get_loc
return self._engine.get_loc(key)
File "pandas/_libs/index.pyx", line 725, in pandas._libs.index.BaseMultiIndexCodesEngine.get_loc
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 1832, in pandas._libs.hashtable.UInt64HashTable.get_item
File "pandas/_libs/hashtable_class_helper.pxi", line 1841, in pandas._libs.hashtable.UInt64HashTable.get_item
KeyError: 11
```
### Issue Description
The example throws KeyError with mysterious number `11` instead of specified keys `('A', 'c')`.
It seems that multi-level index throws:
* `KeyError <keys>` if some of keys are invalid in their level (OK)
* `KeyError <number>` if keys are valid for their level, but the combination is wrong (??)
I think this behavior is because of the lack of `catch` for `self._base.get_loc`:
https://github.com/pandas-dev/pandas/blob/945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5/pandas/_libs/index.pyx#L711-L725
### Expected Behavior
It should throw `KeyError: ('A', 'c')` even if all keys are valid for their levels.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.8.12.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.47-linuxkit
Version : #1 SMP Sat Jul 3 21:51:47 UTC 2021
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.4
numpy : 1.21.3
pytz : 2021.3
dateutil : 2.8.2
pip : 21.2.4
setuptools : 57.5.0
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>
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} | 1 | "2021-10-31T16:28:37Z" | "2021-11-01T23:45:59Z" | 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.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
with pypy3.7-v7.3.7-win64.zip and wheels provided per cgohlke:
- the following example works with seaborn-0.11.2 (and 0.11.1) and Pandas-1.2.5,
- but fails with Pandas-1.3.1, 1.3.2 and latest 1.3.4
````python
import seaborn as sns
sns.set()
df = sns.load_dataset("iris")
sns.pairplot(df, hue="species", height=1.5)
````
### Issue Description
jupyterlab kernel crashes and restarts,
- a pandas_libs.parser.TextReader is blamed, but PyPy says "invalid usage of a dying CPython object"
- looking at seaborn code, seaborn is just calling pandas , so doesn't seem guilty of anything apparently
https://github.com/mwaskom/seaborn/issues/2688
https://github.com/mwaskom/seaborn/blob/master/seaborn/utils.py#L586
### Expected Behavior
a typical seaborn graph, (when pandas-1.2.5)
also this pure pandas one works
````
import pandas as pd
df = pd.read_csv('~/seaborn-data/iris.csv',index_col=False)
import pandas as pd
import altair as alt
alt.Chart(df).mark_bar().encode(
x=alt.X('sepal_length', bin=alt.Bin(maxbins=50)),
y='count(*):Q',
color='species:N',
#column='species',
).interactive()
````
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.7.12.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19043
machine : AMD64
processor : Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None
pandas : 1.3.4
numpy : 1.21.3
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3.1
setuptools : 58.3.0
Cython : 0.29.24
pytest : 6.2.5
hypothesis : 6.24.0
sphinx : 4.2.0
blosc : 1.10.6
feather : None
xlsxwriter : 3.0.1
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : 7.29.0
pandas_datareader: 0.10.0
bs4 : 4.10.0
bottleneck : 1.3.2
fsspec : 2021.10.1
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : None
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.4.26
tables : None
tabulate : 0.8.9
xarray : 0.19.0
xlrd : None
xlwt : None
numba : None
</details>
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} | 4 | "2021-10-31T16:35:33Z" | "2021-11-02T08:56:53Z" | "2021-11-02T08:56:44Z" | CONTRIBUTOR | null | small followup to #44233 | {
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} | 0 | "2021-10-31T17:49:05Z" | "2021-11-05T01:03:35Z" | null | NONE | null | This adds a test for ensuring that None-to-NaN type-casting is consistent with `where` when `inplace=True` and otherwise.
- [x] closes #22051
- [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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] | open | false | null | [] | null | 3 | "2021-10-31T18:48:06Z" | "2021-11-01T20:01:13Z" | null | NONE | null | ## The Pain
Pandas is a powerful tool. If you are making a longer pipeline of chained operations there can be many arguments to provide. Often you want to try out different options. But that can take time to change the options and rerun the script.
#### Describe the solution you'd like
I would like to make the arguments interactive. With widgets. And eventually turn the pipeline into a small, interactive data app.
### The solution is already here
[hvplot](https://hvplot.holoviz.org/) now provides the `.interactive` method to make dataframe pipelines interactive. [Panel](https://panel.holoviz.org/) makes it easy to turn the pipeline into a small, interactive data app.
Basically what you can now make for example the `seattle_bikes` dataframe pipeline below interactive with widgets
```python
# Widgets
resample = pn.widgets.Select(value="D", options=["D", "W", "M"], name="Sampling Frequency")
window = pn.widgets.IntSlider(value=50, start=10, end=100, name="Rolling Window Length")
center = pn.widgets.Checkbox(value=True, name="Center")
win_type = pn.widgets.Select(value="gaussian", options=[None, "gaussian"], name="Window Type")
std = pn.widgets.IntSlider(value=10, start=5, end=20, name="std")
line_width = pn.widgets.IntSlider(value=6, start=1, end=20, name="Line Width")
# A Pandas Dataframe made .interactive with hvPlot
pipeline = (
seattle_bikes.interactive()
.resample(resample)
.sum()
.rolling(window, center=center, win_type=win_type)
.sum(std=10)
.dropna()
)
# Interactive Plot
plot = pn.panel(
pipeline.hvplot( # pandas .plot drop in replacement to render to Matplotlib, Bokeh or Plotly
responsive=True,
height=600,
color=PALETTE,
line_width=line_width,
yformatter="%.0f",
).holoviews(),
sizing_mode="stretch_both",
name="Plot",
)
# Interactive Table
table = pipeline.pipe(
pn.widgets.Tabulator,
pagination="remote",
page_size=20,
theme="fast",
sizing_mode="stretch_both",
).panel(name="Table")
```
https://user-images.githubusercontent.com/42288570/139597169-a60db679-ecbe-438b-b5f1-987f1ce0ef03.mp4
You can find the full code in this gist https://gist.github.com/MarcSkovMadsen/ffb273636dced88705c8c88d5ee28f23
You can use it in a notebook, colab, vs code, pycharm or where ever you explore and code.
### Additional Resources
[](https://discourse.holoviz.org/t/pydata-2021-build-polished-data-driven-applications-directly-from-your-pandas-or-xarray-pipelines/3017)
- [hvplot .interactive reference guide](https://hvplot.holoviz.org/)
### You may close this issue
I think this api is truly revolutionary and would like the world to know. Thus I shared the example here as I don't know where else this information can be shared in the Pandas community. You may close this issue. | {
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] | open | false | null | [] | null | 1 | "2021-10-31T18:49:58Z" | "2021-11-07T12:11:56Z" | null | 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
ser = pd.Series([True, False], dtype=object)
>>> ~ser
0 -2
1 -1
dtype: object
```
### Issue Description
This causes trouble e.g. when such a series/frame is passed as `cond` to NDFrame.mask, which in turn passes `~cond` to `self.where`, which in turn does type inference and then raises with complaint about needing bool dtype instead of int64.
### Expected Behavior
I expected it to match the pointwise `~`
```
ser = pd.Series([True, False], dtype=object)
>>> ~ser
0 False
1 True
dtype: object
```
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
</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 | "2021-11-01T02:19:58Z" | "2021-11-01T13:21:00Z" | null | 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
import numpy as np
import pandas as pd
idx = pd.Index([np.inf, np.nan], dtype=np.float64)
assert (pd.isna(idx) == idx.isna()).all()
pd.set_option("use_inf_as_na", True)
assert (pd.isna(idx) == idx.isna()).all() # <- nope!
```
### Issue Description
pd.isna(obj) and obj.isna() are _generally_ interchangeable, but pd.Index caches .isna in a _isnan cache_readonly. If we want to maintain that interchangeability, we'd need to invalidate that cache.
My inclination is that it isn't worth futzing around with, but someone who uses use_inf_as_na=True might care more.
### Expected Behavior
```
assert (pd.isna(idx) == idx.isna()).all()
```
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
</details>
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} | 0 | "2021-11-01T02:22:03Z" | "2021-11-02T01:43:20Z" | "2021-11-01T23:33:42Z" | MEMBER | 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
We could use the cached index.isna more if #44262 is addressed. | {
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} | 1 | "2021-11-01T04:24:52Z" | "2021-11-01T13:48:56Z" | "2021-11-01T13:48:52Z" | CONTRIBUTOR | null | Seems to be incorrect:
> - DataFrame only `(use Series.to_frame().style)`
Fixed:
> - DataFrame only (use `Series.to_frame().style`) | {
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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
ser = pd.Series(range(5))
mask = np.array([True, False, True, False, True])
# The following are all equivalent ATM, but only the first makes sense to me
ser[mask] = 10
ser[mask] = np.array([10])
ser[mask] = [10]
ser[mask] = (10,)
# If we try these with loc or iloc these raise
>>> ser.loc[mask] = (10,)
[...]
ValueError: cannot set using a list-like indexer with a different length than the value
>>> ser.iloc[mask] = [10]
[...]
ValueError: cannot set using a list-like indexer with a different length than the value
```
### Issue Description
This behavior occurs because `Series.__setitem__` goes through `Series._where` in cases where the key is a boolean mask. It then ends up going through `Manager.putmask`, which uses `np.putmask` semantics (mostly) that repeat/broadcast a listlike value.
AFAICT this repeat/broadcasting makes sense for `Series.where` and `Series.mask`, but not for `Series.__setitem__`. I think this behavior is largely accidental. If we disable this behavior in `Series.__setitem__`, 86 tests break. Of these, 84 are `tests.series.indexing.test_where.test_downcast`, and the PR (#4195) that introduced that test was about `where`, not `__setitem__`. The other two tests I tentatively think are breaking because of the particular way I've disabled the broadcasting.
### Expected Behavior
`ser[mask] = (10,)` should raise.
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
</details>
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"node_id": "MDQ6VXNlcjk1Mzk5Mg==",
"organizations_url": "https://api.github.com/users/jreback/orgs",
"received_events_url": "https://api.github.com/users/jreback/received_events",
"repos_url": "https://api.github.com/users/jreback/repos",
"site_admin": false,
"starred_url": "https://api.github.com/users/jreback/starred{/owner}{/repo}",
"subscriptions_url": "https://api.github.com/users/jreback/subscriptions",
"type": "User",
"url": "https://api.github.com/users/jreback"
},
"description": "",
"due_on": "2021-12-31T08:00:00Z",
"html_url": "https://github.com/pandas-dev/pandas/milestone/86",
"id": 6840253,
"labels_url": "https://api.github.com/repos/pandas-dev/pandas/milestones/86/labels",
"node_id": "MDk6TWlsZXN0b25lNjg0MDI1Mw==",
"number": 86,
"open_issues": 77,
"state": "open",
"title": "1.4",
"updated_at": "2021-11-21T02:34:31Z",
"url": "https://api.github.com/repos/pandas-dev/pandas/milestones/86"
} | 0 | "2021-11-01T07:07:30Z" | "2021-11-01T08:56:58Z" | "2021-11-01T08:56:55Z" | 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-2.15.0-py2.py3-none-any.whl (191 kB)
Collecting toml
Downloading toml-0.10.2-py2.py3-none-any.whl (16 kB)
Collecting nodeenv>=0.11.1
Downloading nodeenv-1.6.0-py2.py3-none-any.whl (21 kB)
Collecting virtualenv>=20.0.8
Downloading virtualenv-20.9.0-py2.py3-none-any.whl (5.6 MB)
Collecting pyyaml>=5.1
Downloading PyYAML-6.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (682 kB)
Collecting cfgv>=2.0.0
Downloading cfgv-3.3.1-py2.py3-none-any.whl (7.3 kB)
Collecting identify>=1.0.0
Downloading identify-2.3.3-py2.py3-none-any.whl (98 kB)
Collecting platformdirs<3,>=2
Downloading platformdirs-2.4.0-py3-none-any.whl (14 kB)
Collecting filelock<4,>=3.2
Downloading filelock-3.3.2-py3-none-any.whl (9.7 kB)
Collecting six<2,>=1.9.0
Downloading six-1.16.0-py2.py3-none-any.whl (11 kB)
Collecting distlib<1,>=0.3.1
Downloading distlib-0.3.3-py2.py3-none-any.whl (496 kB)
Collecting backports.entry-points-selectable>=1.0.4
Downloading backports.entry_points_selectable-1.1.0-py2.py3-none-any.whl (6.2 kB)
Installing collected packages: six, platformdirs, filelock, distlib, backports.entry-points-selectable, virtualenv, toml, pyyaml, nodeenv, identify, cfgv, pre-commit
Successfully installed backports.entry-points-selectable-1.1.0 cfgv-3.3.1 distlib-0.3.3 filelock-3.3.2 identify-2.3.3 nodeenv-1.6.0 platformdirs-2.4.0 pre-commit-2.15.0 pyyaml-6.0 six-1.16.0 toml-0.10.2 virtualenv-20.9.0
```
### stderr:
```Shell
WARNING: You are using pip version 21.3; however, version 21.3.1 is available.
You should consider upgrading via the '/opt/hostedtoolcache/Python/3.10.0/x64/bin/python -m pip install --upgrade pip' command.
```
</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 ... [INFO] Initializing environment for https://github.com/python/black.
updating 21.9b0 -> 21.10b0.
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.
already up to date.
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.
already up to date.
Updating https://github.com/asottile/pyupgrade ... [INFO] Initializing environment for https://github.com/asottile/pyupgrade.
already up to date.
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 ... [INFO] Initializing environment for https://github.com/asottile/yesqa.
updating v1.2.3 -> v1.3.0.
```
</details>
<details>
<summary><em>pre-commit run -a || (exit 0);</em></summary>
```Shell
[INFO] Initializing environment for https://gitlab.com/pycqa/flake8:flake8-bugbear==21.3.2,flake8-comprehensions==3.1.0,flake8==3.9.2,pandas-dev-flaker==0.2.0.
[INFO] Initializing environment for https://github.com/asottile/yesqa:flake8-bugbear==21.3.2,flake8-comprehensions==3.1.0,flake8==3.9.2,pandas-dev-flaker==0.2.0.
[INFO] Initializing environment for local:[email protected].
[INFO] Initializing environment for local:flake8-rst==0.7.0,flake8==3.7.9.
[INFO] Initializing environment for local:pyyaml,toml.
[INFO] Initializing environment for local:pyyaml.
[INFO] Initializing environment for local.
[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...
[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
Debug Statements (Python).......................................................................................Passed
Fix End of Files................................................................................................Passed
Trim Trailing Whitespace........................................................................................Passed
cpplint.........................................................................................................Passed
flake8..........................................................................................................Passed
flake8 (cython).................................................................................................Failed
- hook id: flake8
- exit code: 1
multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 478, in run_ast_checks
ast = self.processor.build_ast()
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/processor.py", line 225, in build_ast
return ast.parse("".join(self.lines))
File "/opt/hostedtoolcache/Python/3.10.0/x64/lib/python3.10/ast.py", line 50, in parse
return compile(source, filename, mode, flags,
File "<unknown>", line 9
cimport numpy as cnp
^^^^^^^^^^^^^
SyntaxError: invalid syntax. Perhaps you forgot a comma?
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/opt/hostedtoolcache/Python/3.10.0/x64/lib/python3.10/multiprocessing/pool.py", line 125, in worker
result = (True, func(*args, **kwds))
File "/opt/hostedtoolcache/Python/3.10.0/x64/lib/python3.10/multiprocessing/pool.py", line 48, in mapstar
return list(map(*args))
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 676, in _run_checks
return checker.run_checks()
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 589, in run_checks
self.run_ast_checks()
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 480, in run_ast_checks
row, column = self._extract_syntax_information(e)
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 465, in _extract_syntax_information
lines = physical_line.rstrip("\n").split("\n")
AttributeError: 'int' object has no attribute 'rstrip'
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/bin/flake8", line 8, in <module>
sys.exit(main())
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/main/cli.py", line 22, in main
app.run(argv)
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/main/application.py", line 363, in run
self._run(argv)
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/main/application.py", line 351, in _run
self.run_checks()
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/main/application.py", line 264, in run_checks
self.file_checker_manager.run()
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 321, in run
self.run_parallel()
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 287, in run_parallel
for ret in pool_map:
File "/opt/hostedtoolcache/Python/3.10.0/x64/lib/python3.10/multiprocessing/pool.py", line 448, in <genexpr>
return (item for chunk in result for item in chunk)
File "/opt/hostedtoolcache/Python/3.10.0/x64/lib/python3.10/multiprocessing/pool.py", line 870, in next
raise value
AttributeError: 'int' object has no attribute 'rstrip'
flake8 (cython template)........................................................................................Failed
- hook id: flake8
- exit code: 1
multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 478, in run_ast_checks
ast = self.processor.build_ast()
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/processor.py", line 225, in build_ast
return ast.parse("".join(self.lines))
File "/opt/hostedtoolcache/Python/3.10.0/x64/lib/python3.10/ast.py", line 50, in parse
return compile(source, filename, mode, flags,
File "<unknown>", line 12
def ensure_platform_int(object arr):
^^^
SyntaxError: invalid syntax
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/opt/hostedtoolcache/Python/3.10.0/x64/lib/python3.10/multiprocessing/pool.py", line 125, in worker
result = (True, func(*args, **kwds))
File "/opt/hostedtoolcache/Python/3.10.0/x64/lib/python3.10/multiprocessing/pool.py", line 48, in mapstar
return list(map(*args))
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 676, in _run_checks
return checker.run_checks()
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 589, in run_checks
self.run_ast_checks()
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 480, in run_ast_checks
row, column = self._extract_syntax_information(e)
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 465, in _extract_syntax_information
lines = physical_line.rstrip("\n").split("\n")
AttributeError: 'int' object has no attribute 'rstrip'
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/bin/flake8", line 8, in <module>
sys.exit(main())
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/main/cli.py", line 22, in main
app.run(argv)
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/main/application.py", line 363, in run
self._run(argv)
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/main/application.py", line 351, in _run
self.run_checks()
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/main/application.py", line 264, in run_checks
self.file_checker_manager.run()
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 321, in run
self.run_parallel()
File "/home/runner/.cache/pre-commit/repovgz80w1u/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 287, in run_parallel
for ret in pool_map:
File "/opt/hostedtoolcache/Python/3.10.0/x64/lib/python3.10/multiprocessing/pool.py", line 448, in <genexpr>
return (item for chunk in result for item in chunk)
File "/opt/hostedtoolcache/Python/3.10.0/x64/lib/python3.10/multiprocessing/pool.py", line 870, in next
raise value
AttributeError: 'int' object has no attribute 'rstrip'
isort...........................................................................................................Passed
pyupgrade.......................................................................................................Passed
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......................................................................................................Failed
- hook id: flake8-rst
- exit code: 1
Traceback (most recent call last):
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 486, in run_ast_checks
ast = self.processor.build_ast()
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/processor.py", line 212, in build_ast
return compile("".join(self.lines), "", "exec", PyCF_ONLY_AST)
File "", line 86
gb.<TAB> # noqa: E225, E999
^
SyntaxError: invalid syntax
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/bin/flake8-rst", line 8, in <module>
sys.exit(main())
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8_rst/cli.py", line 16, in main
app.run(argv)
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/main/application.py", line 393, in run
self._run(argv)
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/main/application.py", line 381, in _run
self.run_checks()
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/main/application.py", line 300, in run_checks
self.file_checker_manager.run()
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 331, in run
self.run_serial()
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 315, in run_serial
checker.run_checks()
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 598, in run_checks
self.run_ast_checks()
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 488, in run_ast_checks
row, column = self._extract_syntax_information(e)
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 473, in _extract_syntax_information
lines = physical_line.rstrip("\n").split("\n")
AttributeError: 'int' object has no attribute 'rstrip'
Traceback (most recent call last):
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 486, in run_ast_checks
ast = self.processor.build_ast()
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/processor.py", line 212, in build_ast
return compile("".join(self.lines), "", "exec", PyCF_ONLY_AST)
File "", line 35
df.plot.<TAB> # noqa: E225, E999
^
SyntaxError: invalid syntax
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/bin/flake8-rst", line 8, in <module>
sys.exit(main())
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8_rst/cli.py", line 16, in main
app.run(argv)
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/main/application.py", line 393, in run
self._run(argv)
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/main/application.py", line 381, in _run
self.run_checks()
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/main/application.py", line 300, in run_checks
self.file_checker_manager.run()
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 331, in run
self.run_serial()
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 315, in run_serial
checker.run_checks()
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 598, in run_checks
self.run_ast_checks()
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 488, in run_ast_checks
row, column = self._extract_syntax_information(e)
File "/home/runner/.cache/pre-commit/repomx8iiwnk/py_env-python3.10/lib/python3.10/site-packages/flake8/checker.py", line 473, in _extract_syntax_information
lines = physical_line.rstrip("\n").split("\n")
AttributeError: 'int' object has no attribute 'rstrip'
Unwanted patterns...............................................................................................Passed
Check Cython casting is `<type>obj`, not `<type> obj`...........................................................Passed
Check for backticks incorrectly rendering because of missing spaces.............................................Passed
Check for unnecessary random seeds in asv benchmarks............................................................Passed
Check for usage of numpy testing or array_equal.................................................................Passed
Check for invalid EA testing....................................................................................Passed
Generate pip dependency from conda..............................................................................Passed
Check flake8 version is synced across flake8, yesqa, and environment.yml........................................Passed
Validate correct capitalization among titles in documentation...................................................Passed
Import pandas.array as pd_array in core.........................................................................Passed
Use bool_t instead of bool in pandas/core/generic.py............................................................Passed
Ensure pandas errors are documented in doc/source/reference/general_utility_functions.rst.......................Passed
```
</details>
</details>
## Changed files
<details>
<summary>Changed file: </summary>
- .pre-commit-config.yaml
</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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"-1": 0,
"confused": 0,
"eyes": 0,
"heart": 0,
"hooray": 0,
"laugh": 0,
"rocket": 0,
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"url": "https://api.github.com/repos/pandas-dev/pandas/issues/44266/reactions"
} | https://api.github.com/repos/pandas-dev/pandas/issues/44266/timeline | null | 0 | {
"diff_url": "https://github.com/pandas-dev/pandas/pull/44266.diff",
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] | open | false | null | [] | null | 3 | "2021-11-01T07:34:22Z" | "2021-11-21T11:32:28Z" | null | CONTRIBUTOR | null | - [x] closes #43564
- [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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} | 1 | "2021-11-01T08:55:35Z" | "2021-11-02T00:50:05Z" | "2021-11-02T00:50:05Z" | NONE | null | #### Is your feature request related to a problem?
Hi
There seems to be no code in the source code that uses "moto". But in “requirements-dev.txt”, "moto" is still listed as a dependency.
The following commit removed "import moto" in "pandas/tests/io/conftest.py ".
[TST: make it possible to run tests without moto installed ](https://github.com/pandas-dev/pandas/commit/c753e1e08b01a438aaa252327de046109bf4bcfd)
So should it be removed from "requirements-dev.txt"?
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] | open | false | null | [] | null | 0 | "2021-11-01T14:05:21Z" | "2021-11-05T23:52:48Z" | 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.
- [x] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
df = pd.DataFrame({'a': [2,1,2,1], 'b': [7,2,3,9], 'c': [2.0, 3.0, 1.1, 7.8]})
df = df.set_index('a')
result = df.groupby(level=0).shift()
result_axis_1 = df.groupby(level=0).shift(axis=1)
print(df)
print(result)
print(result_axis_1)
```
### Issue Description
Ouput:
```bash
b c
a
2 7 2.0
1 2 3.0
2 3 1.1
1 9 7.8
b c
a
2 NaN NaN
1 NaN NaN
2 7.0 2.0
1 2.0 3.0
b c
a
2 NaN 7
2 NaN 3
1 NaN 2
1 NaN 9
```
We can see that `groupby.shift(axis=1)` breaks the original order of values in index.
The same behavior we can see for `groupby.apply(lambda df: df.shift())` function:
```python
import pandas as pd
df = pd.DataFrame({'a': [2,1,2,1], 'b': [7,2,3,9], 'c': [2.0, 3.0, 1.1, 7.8]})
df = df.set_index('a')
result = df.groupby(level=0).shift()
result_apply = df.groupby(level=0).apply(lambda df: df.shift())
print(df)
print(result)
print(result_apply)
```
Output:
```bash
b c
a
2 7 2.0
1 2 3.0
2 3 1.1
1 9 7.8
b c
a
2 NaN NaN
1 NaN NaN
2 7.0 2.0
1 2.0 3.0
b c
a
2 NaN NaN
2 7.0 2.0
1 NaN NaN
1 2.0 3.0
```
We get different order of index for `shift`/`apply(shift)`
### Expected Behavior
```bash
b c
a
2 7 2.0
1 2 3.0
2 3 1.1
1 9 7.8
b c
a
2 NaN NaN
1 NaN NaN
2 7.0 2.0
1 2.0 3.0
b c
a
2 NaN 7
1 NaN 2
2 NaN 3
1 NaN 9
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.8.12.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-65-generic
Version : #73-Ubuntu SMP Mon Jan 18 17:25:17 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US
LOCALE : en_US.ISO8859-1
pandas : 1.3.4
numpy : 1.21.3
pytz : 2021.3
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 : 0.4.1
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : 7.28.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : 2021.10.1
fastparquet : None
gcsfs : None
matplotlib : 3.2.2
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.9
pandas_gbq : 0.15.0
pyarrow : 6.0.0
pyxlsb : None
s3fs : 2021.10.1
scipy : 1.7.1
sqlalchemy : 1.4.26
tables : 3.6.1
tabulate : None
xarray : 0.19.0
xlrd : 2.0.1
xlwt : None
numba : None
</details>
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} | 1 | "2021-11-01T16:01:05Z" | "2021-11-05T18:55:38Z" | "2021-11-05T18:50:53Z" | MEMBER | 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
- [x] whatsnew entry
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} | 1 | "2021-11-01T17:09:57Z" | "2021-11-05T16:02:46Z" | "2021-11-05T13:08:39Z" | CONTRIBUTOR | null | closes #43704
Description of render trimming and maximums bug:
```
pd.options.styler.render.max_columns = 5
pd.options.styler.render.max_rows = 5
df = DataFrame(np.random.rand(10,10))
df.columns = pd.MultiIndex.from_product([[0,1,2,3,4], [0,1]])
df.index = pd.MultiIndex.from_product([[0,1,2,3,4], [0,1]])
df.index.names, df.columns.names = ["a", "b"], ["c", "d"]
df.style.hide([(0,0), (0,1), (1,0)], axis=1).hide([(0,0), (0,1), (1,0)], axis=0)
```
## Pre #44248
## After #44248 (merged)
## After this PR
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cc @twoertwein | {
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} | 8 | "2021-11-01T19:12:28Z" | "2021-11-06T20:51:44Z" | "2021-11-06T20:51:37Z" | CONTRIBUTOR | null | - [x] closes #44162 by adding two examples to docstring of DataFrame.var
- [x] tests added / passed
- [x] All linting tests passed (pre-commit)
Screenshot of locally built documentation:
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} | 6 | "2021-11-01T19:36:00Z" | "2021-11-05T18:22:24Z" | "2021-11-05T16:18:15Z" | MEMBER | null | - [x] closes #44265
- [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 should in turn allow us to avoid some special-casing that we do in internals/putmask_smart.
Sits on top of #44261 | {
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} | 0 | "2021-11-01T19:42:01Z" | "2021-11-01T21:40:38Z" | null | 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
https://dev.azure.com/pandas-dev/pandas/_build/results?buildId=68369&view=logs&j=915dbb23-6529-54ae-059d-ec0b59ba10e8&t=86b091c2-17fe-52fe-2454-5f56a371e155&l=2889
```
### Issue Description
Looks like it tries to construct the dtype and raises an ImportError
### Expected Behavior
False
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
</details>
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- [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.core.window.rolling.Rolling.apply.html
### Documentation problem
The parameters description for `raw` states the default is `None`, while the default is actually `False`.
### Suggested fix for documentation
Update the default to `False`. | {
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- [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.
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} | 5 | "2021-11-01T23:15:23Z" | "2021-11-06T22:01:14Z" | "2021-11-06T21:30:23Z" | MEMBER | null | Maths says this should work now.
- [ ] closes #44173
- [ ] 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
Don't backport. | {
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} | 0 | "2021-11-02T04:15:52Z" | "2021-11-05T02:47:16Z" | "2021-11-05T00:59:40Z" | MEMBER | null | - [x] closes #44277
- [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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} | [] | open | false | null | [] | null | 0 | "2021-11-02T05:21:01Z" | "2021-11-02T18:27:18Z" | null | NONE | null | - [x] closes #33931, #40817
- [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
Edit:
https://github.com/pandas-dev/pandas/issues/42305#issuecomment-895218386
This comment identifies the problem as being upstream in datetime's construction of timestamps which fails during some DST changes.
The datetime hash function then being used tries to unset the fold representing the DST change, (https://github.com/python/cpython/blob/main/Lib/datetime.py#L2117). But it does this using the datetime replace function - this change fixes that problem by removing the fold prior to calling the datetime hash function using timestamp's replace function instead. | {
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} | 1 | "2021-11-02T05:41:05Z" | "2021-11-05T02:51:10Z" | "2021-11-05T01:00:19Z" | MEMBER | null | - [x] xref #https://github.com/pandas-dev/pandas/pull/44176#issuecomment-953441787
- [ ] 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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} | 2 | "2021-11-02T06:18:19Z" | "2021-11-02T23:24:54Z" | 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 pandas as pd
with pd.ExcelWriter('TEST.xlsx', datetime_format='YYYY-MM-DD') as writer:
test_df = pd.DataFrame([9000]*10, index=[pd.Timestamp('2021-11-02')]*10)
test_df.to_excel(writer)
```
### Issue Description
In pandas version 0.24.2, the above example would output nicely formatted dates. In pandas version 1.3.4, it outputs YYYY-MM-DD HH:MM:SS format, ignoring the datetime_format field.
This is probably as simple as openpyxl becoming the new default engine but not being configured for date formatting.
### Expected Behavior
In written Excel sheet, YYYY-MM-DD format dates instead of YYYY-MM-DD HH:MM:SS format dates.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 73c68257545b5f8530b7044f56647bd2db92e2ba
python : 3.9.7.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19042
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 13, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.3.3
numpy : 1.20.3
pytz : 2021.1
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : None
pytest : 6.2.4
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 : 1.3.2
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.9
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 : None
</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
- [ ] whatsnew entry
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} | 8 | "2021-11-02T09:43:31Z" | "2021-11-08T13:10:26Z" | "2021-11-08T13:10:26Z" | 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
# Example 1: Timestamp('2021-10-31 02:30:00+0200', tz='Europe/Amsterdam')
timestamp = (pd.to_datetime('2021-10-31 00:30:00')
.tz_localize('UTC')
.tz_convert('Europe/Amsterdam'))
ts_hour = timestamp.floor('60T')
# Returns: AmbiguousTimeError
# Expected: Timestamp('2021-10-31 02:00:00+0200', tz='Europe/Amsterdam')
# Example 2: Timestamp('2021-10-31 02:30:00+0100', tz='Europe/Amsterdam')
timestamp = (pd.to_datetime('2021-10-31 01:30:00')
.tz_localize('UTC')
.tz_convert('Europe/Amsterdam'))
ts_hour = timestamp.floor('60T')
# Returns: AmbiguousTimeError
# Expected: Timestamp('2021-10-31 02:00:00+0100', tz='Europe/Amsterdam')
```
### Issue Description
The timestamp is in local time, so pandas should how enough information to know how to round it down to the whole hour. However, it does not recognize this and asks for an ambiguous argument.
Adding ambiguous=True does not provide the desired result.
### Expected Behavior
See reproducible example
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.9.2.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 12, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : Dutch_Netherlands.1252
pandas : 1.3.4
numpy : 1.21.3
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3.1
setuptools : 58.4.0
Cython : None
pytest : 6.2.4
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.8.6 (dt dec pq3 ext lo64)
jinja2 : 2.11.3
IPython : 7.29.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.2
numexpr : None
odfpy : None
openpyxl : 3.0.7
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.4.13
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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] | open | false | null | [] | null | 2 | "2021-11-02T13:56:59Z" | "2021-11-19T09:23:51Z" | 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
import numpy as np
df = pd.DataFrame({"A": [1, 2, np.nan], "B": [4, np.nan, 8]}, dtype="Int64")
df.fillna('nan')
```
### Issue Description
The code above causes the following error:
```
TypeError Traceback (most recent call last)
<ipython-input-2-fcfc27adad85> in <module>
2 import numpy as np
3 df = pd.DataFrame({"A": [1, 2, np.nan], "B": [4, np.nan, 8]}, dtype="Int64")
----> 4 df.fillna('nan')
~/venv/lib/python3.8/site-packages/pandas/util/_decorators.py in wrapper(*args, **kwargs)
309 stacklevel=stacklevel,
310 )
--> 311 return func(*args, **kwargs)
312
313 return wrapper
~/venv/lib/python3.8/site-packages/pandas/core/frame.py in fillna(self, value, method, axis, inplace, limit, downcast)
5174 downcast=None,
5175 ) -> DataFrame | None:
-> 5176 return super().fillna(
5177 value=value,
5178 method=method,
~/venv/lib/python3.8/site-packages/pandas/core/generic.py in fillna(self, value, method, axis, inplace, limit, downcast)
6380
6381 elif not is_list_like(value):
-> 6382 new_data = self._mgr.fillna(
6383 value=value, limit=limit, inplace=inplace, downcast=downcast
6384 )
~/venv/lib/python3.8/site-packages/pandas/core/internals/managers.py in fillna(self, value, limit, inplace, downcast)
408
409 def fillna(self: T, value, limit, inplace: bool, downcast) -> T:
--> 410 return self.apply(
411 "fillna", value=value, limit=limit, inplace=inplace, downcast=downcast
412 )
~/venv/lib/python3.8/site-packages/pandas/core/internals/managers.py in apply(self, f, align_keys, ignore_failures, **kwargs)
325 applied = b.apply(f, **kwargs)
326 else:
--> 327 applied = getattr(b, f)(**kwargs)
328 except (TypeError, NotImplementedError):
329 if not ignore_failures:
~/venv/lib/python3.8/site-packages/pandas/core/internals/blocks.py in fillna(self, value, limit, inplace, downcast)
1570 self, value, limit=None, inplace: bool = False, downcast=None
1571 ) -> list[Block]:
-> 1572 values = self.values.fillna(value=value, limit=limit)
1573 return [self.make_block_same_class(values=values)]
1574
~/venv/lib/python3.8/site-packages/pandas/core/arrays/masked.py in fillna(self, value, method, limit)
174 # fill with value
175 new_values = self.copy()
--> 176 new_values[mask] = value
177 else:
178 new_values = self.copy()
~/venv/lib/python3.8/site-packages/pandas/core/arrays/masked.py in __setitem__(self, key, value)
186 if _is_scalar:
187 value = [value]
--> 188 value, mask = self._coerce_to_array(value)
189
190 if _is_scalar:
~/venv/lib/python3.8/site-packages/pandas/core/arrays/integer.py in _coerce_to_array(self, value)
332
333 def _coerce_to_array(self, value) -> tuple[np.ndarray, np.ndarray]:
--> 334 return coerce_to_array(value, dtype=self.dtype)
335
336 def astype(self, dtype, copy: bool = True) -> ArrayLike:
~/venv/lib/python3.8/site-packages/pandas/core/arrays/integer.py in coerce_to_array(values, dtype, mask, copy)
202
203 elif not (is_integer_dtype(values) or is_float_dtype(values)):
--> 204 raise TypeError(f"{values.dtype} cannot be converted to an IntegerDtype")
205
206 if mask is None:
TypeError: <U3 cannot be converted to an IntegerDtype
```
### Expected Behavior
df.fillna('nan') should return a new dataframe with `np.nan` values filled with `'nan'` strings.
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.8.12.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.47-linuxkit
Version : #1 SMP Sat Jul 3 21:51:47 UTC 2021
machine : x86_64
processor :
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.4
numpy : 1.19.5
pytz : 2021.3
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.2.0
Cython : None
pytest : 6.2.5
hypothesis : None
sphinx : 4.2.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : None
pymysql : 1.0.2
psycopg2 : 2.9.1 (dt dec pq3 ext lo64)
jinja2 : 3.0.2
IPython : 7.28.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
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 : 1.4.25
tables : None
tabulate : 0.8.9
xarray : None
xlrd : None
xlwt : None
numba : None
</details>
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] | closed | false | null | [] | null | 2 | "2021-11-02T17:08:48Z" | "2021-11-02T22:39:14Z" | "2021-11-02T22:38:51Z" | CONTRIBUTOR | null | ###
- [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.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
a = pd.DataFrame(data=[[21] * 3, [22] * 3], columns=pd.MultiIndex.from_tuples([(1, 10), (2, 10), (3, 11)], names=['foo', 'bar']))
b = pd.DataFrame(data=[[31] * 2, [32] * 2], columns=pd.Int64Index([10, 11], name='bar'))
print(a)
print(b)
print(b + a) # This works, but returns an incorrect result: all NaNs
print(a + b) # This raises a RecursionError
```
### Issue Description
```
755 self, other, op, axis, default_axis, fill_value, level
756 ):
--> 757 return _frame_arith_method_with_reindex(self, other, op)
758
759 other = _align_method_FRAME(self, other, axis)
RecursionError: maximum recursion depth exceeded while calling a Python object
```
### Expected Behavior
```
In [6]: b + a
Out[6]:
foo 1 2 3
bar 10 10 11
0 52 52 52
1 54 54 54
In [7]: a + b
Out[7]:
foo 1 2 3
bar 10 10 11
0 52 52 52
1 54 54 54
```
### Installed Versions
<details>
pandas : 1.0.5
</details>
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] | closed | false | null | [] | null | 1 | "2021-11-02T19:31:15Z" | "2021-11-02T19:36:16Z" | "2021-11-02T19:35:32Z" | 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
s = pd.Series([1,2,3,pd.NA,5], dtype='Int64')
# Raises DataError: No numeric types to aggregate
s.rolling(3).max()
# count works
s.rolling(3).count()
```
### Issue Description
When trying to run a rolling window calculation on an Int64Dtype series that contains NaNs, it seems that many of the available calculations raise the following error:
<details>
```python
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
~/.pyenv/versions/3.8.2/envs/test-env/lib/python3.8/site-packages/pandas/core/window/rolling.py in _prep_values(self, values)
322 try:
--> 323 values = ensure_float64(values)
324 except (ValueError, TypeError) as err:
pandas/_libs/algos_common_helper.pxi in pandas._libs.algos.ensure_float64()
~/.pyenv/versions/3.8.2/envs/test-env/lib/python3.8/site-packages/pandas/core/arrays/masked.py in __array__(self, dtype)
334 """
--> 335 return self.to_numpy(dtype=dtype)
336
~/.pyenv/versions/3.8.2/envs/test-env/lib/python3.8/site-packages/pandas/core/arrays/masked.py in to_numpy(self, dtype, copy, na_value)
291 ):
--> 292 raise ValueError(
293 f"cannot convert to '{dtype}'-dtype NumPy array "
ValueError: cannot convert to 'float64'-dtype NumPy array with missing values. Specify an appropriate 'na_value' for this dtype.
The above exception was the direct cause of the following exception:
TypeError Traceback (most recent call last)
~/.pyenv/versions/3.8.2/envs/test-env/lib/python3.8/site-packages/pandas/core/window/rolling.py in _apply_series(self, homogeneous_func, name)
403 try:
--> 404 values = self._prep_values(obj._values)
405 except (TypeError, NotImplementedError) as err:
~/.pyenv/versions/3.8.2/envs/test-env/lib/python3.8/site-packages/pandas/core/window/rolling.py in _prep_values(self, values)
324 except (ValueError, TypeError) as err:
--> 325 raise TypeError(f"cannot handle this type -> {values.dtype}") from err
326
TypeError: cannot handle this type -> Int64
The above exception was the direct cause of the following exception:
DataError Traceback (most recent call last)
<ipython-input-11-7b94d5aa8fee> in <module>
1 import pandas as pd
2 s = pd.Series([1,2,3,None,5], dtype='Int64')
----> 3 s.rolling(3).max()
~/.pyenv/versions/3.8.2/envs/test-env/lib/python3.8/site-packages/pandas/core/window/rolling.py in max(self, engine, engine_kwargs, *args, **kwargs)
1764 ):
1765 nv.validate_rolling_func("max", args, kwargs)
-> 1766 return super().max(*args, engine=engine, engine_kwargs=engine_kwargs, **kwargs)
1767
1768 @doc(
~/.pyenv/versions/3.8.2/envs/test-env/lib/python3.8/site-packages/pandas/core/window/rolling.py in max(self, engine, engine_kwargs, *args, **kwargs)
1261 )
1262 window_func = window_aggregations.roll_max
-> 1263 return self._apply(window_func, name="max", **kwargs)
1264
1265 def min(
~/.pyenv/versions/3.8.2/envs/test-env/lib/python3.8/site-packages/pandas/core/window/rolling.py in _apply(self, func, name, numba_cache_key, **kwargs)
543
544 if self.method == "single":
--> 545 return self._apply_blockwise(homogeneous_func, name)
546 else:
547 return self._apply_tablewise(homogeneous_func, name)
~/.pyenv/versions/3.8.2/envs/test-env/lib/python3.8/site-packages/pandas/core/window/rolling.py in _apply_blockwise(self, homogeneous_func, name)
417 """
418 if self._selected_obj.ndim == 1:
--> 419 return self._apply_series(homogeneous_func, name)
420
421 obj = self._create_data(self._selected_obj)
~/.pyenv/versions/3.8.2/envs/test-env/lib/python3.8/site-packages/pandas/core/window/rolling.py in _apply_series(self, homogeneous_func, name)
404 values = self._prep_values(obj._values)
405 except (TypeError, NotImplementedError) as err:
--> 406 raise DataError("No numeric types to aggregate") from err
407
408 result = homogeneous_func(values)
DataError: No numeric types to aggregate
```
</details>
I've only shown this behavior for `pandas.core.window.rolling.Rolling.max`, but it also exists for many other of the `pandas.core.window.rolling.Rolling` methods. One calculation in the `pandas.core.window.rolling.Rolling` series of methods that does _not_ raise this error is `count`, which seems to have a different handling of null values altogether from the other methods, so that may be related.
My current work-around is to convert `Int64` columns to `float64` before calling `series.rolling`.
### Expected Behavior
I would expect the behavior to match that of a rolling window calculation on a series with `'float64'` dtype series containing nans.
```python
# Using 'float64' works
s = pd.Series([1,2,3,None,5], dtype='float64')
s.rolling(3).max()
```
In this case, the result is as follows:
```python
0 NaN
1 NaN
2 3.0
3 NaN
4 NaN
dtype: float64
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.8.2.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 : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.4
numpy : 1.21.2
pytz : 2021.1
dateutil : 2.8.1
pip : 21.1.2
setuptools : 41.2.0
Cython : 0.29.17
pytest : 6.0.1
hypothesis : None
sphinx : 3.2.1
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.9.1 (dt dec pq3 ext lo64)
jinja2 : 2.11.3
IPython : 7.18.1
pandas_datareader: None
bs4 : 4.9.3
bottleneck : None
fsspec : 2021.06.0
fastparquet : 0.5.0
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 : 0.53.0
</details>
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} | 1 | "2021-11-02T21:40:33Z" | "2021-11-06T21:25:56Z" | null | 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
e.g.
- https://pandas.pydata.org/docs/dev/user_guide/integer_na.html
- https://pandas.pydata.org/docs/dev/user_guide/boolean.html
### Documentation problem
The user guides for the native/nullable dtypes have prominent admonitions:
> IntegerArray is currently experimental. Its API or implementation may change without warning.
> BooleanArray is currently experimental. Its API or implementation may change without warning.
These are a little ambiguous from the perspective of a downstream library. Specifically, it's not clear whether the _existence_ of these dtypes is "experimental API", or if we can assume that they *will* exist in pandas (unless formally deprecated) but that nuances of their behavior may change.
For example, I am writing a function that needs to coerce a Series to boolean values in a missing-data friendly way. I'm reasonably happy delegating exactly what that means to pandas. Can I do `s.astype("boolean")` without assuming that it will break without warning?
### Suggested fix for documentation
This is maybe more of a usage question, but I do think there's an actionable doc improvement. I understand wanting to iterate on the new ideas and that the admonition is written as broadly as possible to facilitate that. But these dtypes have been around for a while now, users are starting to expect that downstream libraries will support them, and it would be helpful to have a little bit more guidance about how to do that. | {
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} | 1 | "2021-11-02T22:05:54Z" | "2021-11-05T01:01:10Z" | "2021-11-05T00:31:48Z" | MEMBER | 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
- [x] whatsnew entry
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} | 1 | "2021-11-02T22:15:24Z" | "2021-11-14T20:24:19Z" | "2021-11-14T20:24:19Z" | NONE | null | #### Is your feature request related to a problem?
When I try to dump a DataFrame which has spaces in columns into an SQLite database, I get the _SAFE_NAMES_WARNING. However, spaces in column names are no longer changed to underscores since version 0.14. This warning should be removed. IMHO it is no longer relevant.
#### Describe the solution you'd like
Remove the following lines from io/sql.py in function `SQLiteTable._create_table_setup`:
```
pat = re.compile(r"\s+")
column_names = [col_name for col_name, _, _ in column_names_and_types]
if any(map(pat.search, column_names)):
warnings.warn(_SAFE_NAMES_WARNING, stacklevel=6)
```
#### API breaking implications
None
#### Describe alternatives you've considered
None
#### Additional context | {
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} | 1 | "2021-11-02T23:29:00Z" | "2021-11-04T01:11:32Z" | "2021-11-04T00:38:40Z" | MEMBER | null | - [x] xref #40111
- [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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When reading a csv file (or other form of table) into a DataFrame, it would be convenient to be able to directly specify columns to exclude rather than columns to include. This happens a lot when working with data that have a variable number of columns, but a fixed set of columns that should be ignored.
#### Describe the solution you'd like
`pandas.read_csv` and other read functions in the `readers.py` module should get a new parameter `skipcols` that would essentially be the inverse of the `usecols` parameter.
```
skipcols : list-like, optional
Return a subset of the columns excluding the specified columns. If list-like,
all elements must either be positional (i.e. integer indices into the document
columns) or strings that correspond to column names provided either by the
user in `names` or inferred from the document header row(s). For example, a
valid list-like `skipcols` parameter would be ``[0, 1, 2]`` or ``['foo', 'bar', 'baz']``.
Element order is ignored, so ``skipcols=[0, 1]`` is the same as ``[1, 0]``.
```
A callable doesn't make as much sense here since it would be the same as supplying a callable to `usecols` with a `not`.
#### API breaking implications
I don't think this would conflict with the existing API, though it would need to be mutually exclusive with `usecols`
#### Describe alternatives you've considered
This could be accomplished using `usecols=lambda x: x not in columns_to_skip` but I think the syntax would be more clear and straightforward as `skipcols=columns_to_skip`.
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} | 1 | "2021-11-03T04:25:43Z" | "2021-11-03T12:54:27Z" | "2021-11-03T12:54:27Z" | NONE | null | #### Is your feature request related to a problem?
I'm working with code written by other people, where a `df.rename(columns={...})` was causing a Exception later in the program that was really hard to debug.
#### Describe the solution you'd like
My suggestion is that whenever you rename a column in a DataFrame where the new name is already in the column set, a warning be issued. That way it could be easy to avoid (or detect) that kind of problem. Maybe an optional argument with a default value could be added to `rename()`, such as `warn_duplicates=True`.
#### API breaking implications
If implemented the suggested way, nothing must be changed in existing code that uses pandas.
#### Describe alternatives you've considered
As I understand (I haven't checked the source code), the rename might be done by copying the index and for each element in it, apply the mapping.
If it in fact works that way, a solution would be to, for each item that will be mapped, check if the new value is already present in the output index.
Nevertheless, I believe a more efficient and compact way would be: at the end of the `rename()` function, check for duplicates.
For example, let `idx` be an Index object, the following piece of code can list the duplicates:
```python
dup = idx[idx.duplicated()]
```
if `dup` is not empty, it means the rename created duplicated items.
#### Additional context
Why this feature suggestion? Mainly because of the issue I was experimenting. If it is implemented, it will be more easily solved for people using the library in the future.
Here are two examples of when renaming is the origin of a problem:
```python
df = pd.DataFrame(dict(
col0 = [1, 2, 3 ,4],
col1 = [2, 3, 4, 5],
col2 = [3, 4, 5, 6],
col3 = [4, 5, 6, 7]))
# df with a duplicated index
df0 = df.rename(index={3: 1})
# df with a duplicated column
df1 = df.rename(columns={'col2': 'col0'})
# these are ok
print(pd.concat([df, df0], axis=0))
print(pd.concat([df, df1], axis=1))
# these are NOT ok
print(pd.concat([df, df0], axis=1))
print(pd.concat([df, df1], axis=0))
```
Although it may seem an improbable scenario, it might happen for other people, the same way it happened to me. This [post](https://stackoverflow.com/questions/61514861/pandas-pd-concat-results-in-duplicated-columns#comment108816263_61514937) happened me inspecting the source of the problem. Specially, [these comments](https://stackoverflow.com/questions/61514861/pandas-pd-concat-results-in-duplicated-columns#comment108816263_61514937), because they warned me that there must have been something wrong in the code, not in the dataset itself. In fact, there was.
I'd be glad to help implementing it, once this suggestion is approved!
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} | 1 | "2021-11-03T11:58:32Z" | "2021-11-03T12:54:00Z" | "2021-11-03T12:53:51Z" | 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/q/69776073/3433625
### Question about pandas
I was hoping it might be possible to have the Pandas module output all of its supported dtypes, but I haven't found any documentation mentioning how to do this, although I have seen the [utilities documentation](https://pandas.pydata.org/docs/reference/general_utility_functions.html) and the [documentation explaining Pandas dtypes](https://pandas.pydata.org/pandas-docs/stable/user_guide/basics.html#dtypes).
I need to create some artificial datasets in Pandas dataframes which make use of all possible dtypes in order to test another software application which processes dataframes based on the dtypes existing in those dataframes. At present, it looks like I have to look at the documentation and hardcode those dtypes. The primary test case I'm trying to build is a single dataframe featuring all possible dtypes in it. If anyone can shed some light on how to get all possible dtypes from Pandas and generate data for those dtypes, it would be much appreciated. | {
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} | 5 | "2021-11-03T13:56:42Z" | "2021-11-07T09:50:03Z" | "2021-11-06T19:41:49Z" | CONTRIBUTOR | null | Refers https://github.com/pandas-dev/pandas/issues/15825 . Doesn't fix the issue (might be unfixable), but gives a more helpful warning.
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] | open | false | null | [] | null | 8 | "2021-11-03T15:08:09Z" | "2021-11-18T22:38:28Z" | null | NONE | null | Rough attempt at implementing cuDF's `DataFrame.quantiles`; shares a lot of common logic with `sort_values`, as the indexer that sorts the dataframe by all columns is ultimately what is used to grab the desired quantiles.
cc @quasiben @rjzamora
- [ ] closes #43881
- [ ] 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 | 0 | "2021-11-03T16:12:03Z" | "2021-11-06T00:08:45Z" | 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
Self build pandas doc.
```
### Issue Description
When I build pandas doc myself with [guide](https://pandas.pydata.org/docs/development/contributing_documentation.html#how-to-build-the-pandas-documentation) ,I run `python make.py html`,several error occured on doc/source/user_guide/10min.rst
1. This file use matplotlib to render images.And following error occured:
```
WARNING:
>>>-------------------------------------------------------------------------
Warning in /root/pandas/doc/source/user_guide/10min.rst at block ending on line 757
Specify :okwarning: as an option in the ipython:: block to suppress this message
----------------------------------------------------------------------------
<ipython-input-136-993bc8a3a2a6>:1: UserWarning: Matplotlib is currently using agg, which is a non-GUI backend, so cannot show the figure.
plt.show();
<<<-------------------------------------------------------------------------
```
2. When I commented the `plt.show()` line,following error occured:
```
Exception occurred:
File "/root/pandas-doc/lib/python3.9/site-packages/docutils/writers/html5_polyglot/__init__.py", line 445, in section_title_tags
if (ids and self.settings.section_self_link
AttributeError: 'Values' object has no attribute 'section_self_link'
```
Following is the full traceback:
```
# Sphinx version: 4.2.0
# Python version: 3.9.5 (CPython)
# Docutils version: 0.18 release
# Jinja2 version: 3.0.2
# Last messages:
#
# waiting for workers...
# looking for now-outdated files...
# none found
# pickling environment...
# done
# checking consistency...
# done
# preparing documents...
# done
# Loaded extensions:
# sphinx.ext.mathjax (4.2.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinx/ext/mathjax.py
# sphinxcontrib.applehelp (1.0.2) from /root/pandas-doc/lib/python3.9/site-packages/sphinxcontrib/applehelp/__init__.py
# sphinxcontrib.devhelp (1.0.2) from /root/pandas-doc/lib/python3.9/site-packages/sphinxcontrib/devhelp/__init__.py
# sphinxcontrib.htmlhelp (2.0.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinxcontrib/htmlhelp/__init__.py
# sphinxcontrib.serializinghtml (1.1.5) from /root/pandas-doc/lib/python3.9/site-packages/sphinxcontrib/serializinghtml/__init__.py
# sphinxcontrib.qthelp (1.0.3) from /root/pandas-doc/lib/python3.9/site-packages/sphinxcontrib/qthelp/__init__.py
# alabaster (0.7.12) from /root/pandas-doc/lib/python3.9/site-packages/alabaster/__init__.py
# sphinx.ext.autodoc.preserve_defaults (1.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinx/ext/autodoc/preserve_defaults.py
# sphinx.ext.autodoc.type_comment (4.2.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinx/ext/autodoc/type_comment.py
# sphinx.ext.autodoc (4.2.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinx/ext/autodoc/__init__.py
# sphinx.ext.autosummary (4.2.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinx/ext/autosummary/__init__.py
# sphinx.ext.doctest (4.2.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinx/ext/doctest.py
# sphinx.ext.extlinks (4.2.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinx/ext/extlinks.py
# sphinx.ext.todo (4.2.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinx/ext/todo.py
# numpydoc (1.1.0) from /root/pandas-doc/lib/python3.9/site-packages/numpydoc/__init__.py
# IPython.sphinxext.ipython_directive (unknown version) from /root/pandas-doc/lib/python3.9/site-packages/IPython/sphinxext/ipython_directive.py
# IPython.sphinxext.ipython_console_highlighting (unknown version) from /root/pandas-doc/lib/python3.9/site-packages/IPython/sphinxext/ipython_console_highlighting.py
# matplotlib.sphinxext.plot_directive (3.4.3) from /root/pandas-doc/lib/python3.9/site-packages/matplotlib/sphinxext/plot_directive.py
# sphinx.ext.intersphinx (4.2.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinx/ext/intersphinx.py
# sphinx.ext.coverage (4.2.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinx/ext/coverage.py
# sphinx.ext.ifconfig (4.2.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinx/ext/ifconfig.py
# sphinx.ext.linkcode (4.2.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinx/ext/linkcode.py
# nbsphinx (0.8.7) from /root/pandas-doc/lib/python3.9/site-packages/nbsphinx.py
# sphinx_panels (0.6.0) from /root/pandas-doc/lib/python3.9/site-packages/sphinx_panels/__init__.py
# contributors (0.1) from /root/pandas/doc/sphinxext/contributors.py
# pydata_sphinx_theme (unknown version) from /root/pandas-doc/lib/python3.9/site-packages/pydata_sphinx_theme/__init__.py
Traceback (most recent call last):
File "/root/pandas-doc/lib/python3.9/site-packages/sphinx/cmd/build.py", line 280, in build_main
app.build(args.force_all, filenames)
File "/root/pandas-doc/lib/python3.9/site-packages/sphinx/application.py", line 343, in build
self.builder.build_update()
File "/root/pandas-doc/lib/python3.9/site-packages/sphinx/builders/__init__.py", line 293, in build_update
self.build(to_build,
File "/root/pandas-doc/lib/python3.9/site-packages/sphinx/builders/__init__.py", line 357, in build
self.write(docnames, list(updated_docnames), method)
File "/root/pandas-doc/lib/python3.9/site-packages/sphinx/builders/__init__.py", line 528, in write
self._write_parallel(sorted(docnames),
File "/root/pandas-doc/lib/python3.9/site-packages/sphinx/builders/__init__.py", line 555, in _write_parallel
self.write_doc(firstname, doctree)
File "/root/pandas-doc/lib/python3.9/site-packages/sphinx/builders/html/__init__.py", line 626, in write_doc
self.docwriter.write(doctree, destination)
File "/root/pandas-doc/lib/python3.9/site-packages/docutils/writers/__init__.py", line 78, in write
self.translate()
File "/root/pandas-doc/lib/python3.9/site-packages/sphinx/writers/html.py", line 70, in translate
self.document.walkabout(visitor)
File "/root/pandas-doc/lib/python3.9/site-packages/docutils/nodes.py", line 199, in walkabout
if child.walkabout(visitor):
File "/root/pandas-doc/lib/python3.9/site-packages/docutils/nodes.py", line 199, in walkabout
if child.walkabout(visitor):
File "/root/pandas-doc/lib/python3.9/site-packages/docutils/nodes.py", line 191, in walkabout
visitor.dispatch_visit(self)
File "/root/pandas-doc/lib/python3.9/site-packages/sphinx/util/docutils.py", line 477, in dispatch_visit
method(node)
File "/root/pandas-doc/lib/python3.9/site-packages/sphinx/writers/html5.py", line 375, in visit_title
super().visit_title(node)
File "/root/pandas-doc/lib/python3.9/site-packages/docutils/writers/_html_base.py", line 1661, in visit_title
start_tag, close_tag = self.section_title_tags(node)
File "/root/pandas-doc/lib/python3.9/site-packages/docutils/writers/html5_polyglot/__init__.py", line 445, in section_title_tags
if (ids and self.settings.section_self_link
AttributeError: 'Values' object has no attribute 'section_self_link'
```
### Expected Behavior
Build doc successfully.
### Installed Versions
<details>
```
>>> import pandas as pd
>>> pd.show_versions()
/root/pandas-doc/lib/python3.9/site-packages/fastparquet/dataframe.py:5: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.NumericIndex with the appropriate dtype instead.
from pandas import (
INSTALLED VERSIONS
------------------
commit : 2e29e1172bb5d17c5d6f4d8bec1d3e6452091822
python : 3.9.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-77-generic
Version : #86-Ubuntu SMP Thu Jun 17 02:35:03 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.utf8
LOCALE : en_US.UTF-8
pandas : 1.4.0.dev0+1033.g2e29e1172b.dirty
numpy : 1.20.3
pytz : 2021.3
dateutil : 2.8.2
pip : 20.0.2
setuptools : 58.4.0
Cython : 0.29.24
pytest : 6.2.5
hypothesis : 6.24.1
sphinx : 4.2.0
blosc : 1.10.6
feather : None
xlsxwriter : 3.0.2
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : 7.29.0
pandas_datareader: None
bs4 : 4.10.0
bottleneck : 1.3.2
fsspec : 2021.10.1
fastparquet : 0.7.1
gcsfs : 2021.10.1
matplotlib : 3.4.3
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 6.0.0
pyxlsb : None
s3fs : 2021.10.1
scipy : 1.7.1
sqlalchemy : 1.4.26
tables : 3.6.1
tabulate : 0.8.9
xarray : 0.18.2
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.54.1
```
</details>
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_ValueError: must supply a tuple to get_group with multiple grouping keys_
but it is not very clear why it must be a tuple as opposed to any iterable. I prefer to use lists, that way I can use square brackets in the function call and to me it looks better than adding more parenthesis. Thanks! | {
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- [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.to_html.html
### Documentation problem
The documentation contains an optional parameter `min_rows`, but the source code shows that no option is supported. See source code [here](https://github.com/pandas-dev/pandas/blob/v1.3.4/pandas/core/frame.py#L2711).
Verify this optional param is not supported with the following code:
```
import pandas as pd
df = pd.DataFrame({'data': [1, 2, 3]})
df.to_html(max_rows=2, min_rows=1)
```
Which outputs the error
```
1 import pandas as pd
2 df = pd.DataFrame({'data': [1, 2, 3]})
----> 3 df.to_html(max_rows=2, min_rows=1)
TypeError: to_html() got an unexpected keyword argument 'min_rows'
```
### Suggested fix for documentation
Remove the `min_rows` optional param from this documentation. | {
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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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- [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.
- [X] I have confirmed this issue exists on the master branch of pandas.
### Reproducible Example
```
@dataclass()
class Example:
first: int
second: int
class_list = [Example(random.randint(0,1000), random.randint(0,1000)) for x in range(1000)]
```
`pd.DataFrame(class_list)`
6.1 ms ± 902 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
This is probably because the constructor uses asdict which is quite slow, think we can make the constructor work without asdict, something along these lines:
`pd.DataFrame([(x.first, x.second) for x in class_list], columns = ['first', 'second'])`
653 µs ± 58.3 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.8.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.11.0-38-generic
Version : #42~20.04.1-Ubuntu SMP Tue Sep 28 20:41:07 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_IL
LOCALE : en_IL.UTF-8
pandas : 1.3.4
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 : 2.9.1 (dt dec pq3 ext lo64)
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 : 0.14.1
pyarrow : 5.0.0
pyxlsb : None
s3fs : None
scipy : 1.5.2
sqlalchemy : 1.3.20
tables : 3.6.1
tabulate : 0.8.9
xarray : None
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.51.2
</details>
### Prior Performance
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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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} | 1 | "2021-11-04T05:32:51Z" | "2021-11-05T15:54:04Z" | "2021-11-05T09:09:57Z" | 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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] | closed | false | null | [] | null | 0 | "2021-11-04T10:41:04Z" | "2021-11-04T10:41:31Z" | "2021-11-04T10:41:31Z" | 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
def aggfunc(df):
return pd.Series([df['b'].mean()], index=['b_mean'])
df=pd.DataFrame({
'a': ['aa', 'a2', 'a3'],
'b': [1, 2, 3],
}, index=pd.Index([1., 2., 3.]))
df.groupby('a').apply(aggfunc)
```
### Issue Description
I get a KeyError with the provided code. The call stack is:
<details>
```python
Traceback (most recent call last):
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\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 1533, in pandas._libs.hashtable.Float64HashTable.get_item
File "pandas\_libs\hashtable_class_helper.pxi", line 1542, in pandas._libs.hashtable.Float64HashTable.get_item
KeyError: 0.0
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "<input>", line 8, in <module>
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\groupby\groupby.py", line 1275, in apply
result = self._python_apply_general(f, self._selected_obj)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\groupby\groupby.py", line 1309, in _python_apply_general
keys, values, mutated = self.grouper.apply(f, data, self.axis)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\groupby\ops.py", line 804, in apply
result_values, mutated = splitter.fast_apply(f, sdata, group_keys)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\groupby\ops.py", line 1349, in fast_apply
return libreduction.apply_frame_axis0(sdata, f, names, starts, ends)
File "pandas\_libs\reduction.pyx", line 369, in pandas._libs.reduction.apply_frame_axis0
File "pandas\_libs\reduction.pyx", line 428, in pandas._libs.reduction.BlockSlider.__init__
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\frame.py", line 3430, in __getitem__
indexer = convert_to_index_sliceable(self, key)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexing.py", line 2329, in convert_to_index_sliceable
return idx._convert_slice_indexer(key, kind="getitem")
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexes\numeric.py", line 242, in _convert_slice_indexer
return self.slice_indexer(key.start, key.stop, key.step, kind=kind)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexes\base.py", line 5685, in slice_indexer
start_slice, end_slice = self.slice_locs(start, end, step=step)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexes\base.py", line 5893, in slice_locs
end_slice = self.get_slice_bound(end, "right")
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexes\base.py", line 5807, in get_slice_bound
raise err
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexes\base.py", line 5801, in get_slice_bound
slc = self.get_loc(label)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexes\base.py", line 3363, in get_loc
raise KeyError(key) from err
KeyError: 0
```
</details>
Note that the KeyError doesn't appear when I send in these other very similar dataframes:
```python
# okay when the 1st element of 'a' is written differently
df=pd.DataFrame({
'a': ['a1', 'a2', 'a3'],
'b': [1, 2, 3],
}, index=pd.Index([1., 2., 3.]))
```
```python
# okay when index is not float
df=pd.DataFrame({
'a': ['aa', 'a2', 'a3'],
'b': [1, 2, 3],
}, index=pd.Index([1, 2, 3]))
```
```python
# okay when there are only two rows
df=pd.DataFrame({
'a': ['aa', 'a2'],
'b': [1, 2],
}, index=pd.Index([1., 2.]))
```
### Expected Behavior
There should not be any KeyError, and the output should look something like the following:
```python
b_mean
a
a2 2.0
a3 3.0
aa 1.0
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.7.9.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 12, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None
pandas : 1.3.4
numpy : 1.21.3
pytz : 2021.3
dateutil : 2.8.2
pip : 21.1.2
setuptools : 57.0.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 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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] | open | false | null | [] | null | 4 | "2021-11-04T10:48:14Z" | "2021-11-05T09:28:34Z" | 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.
- [ ] I have confirmed this bug exists on the master branch of pandas.
### Reproducible Example
```python
import pandas as pd
def aggfunc(df):
return pd.Series([df['b'].mean()], index=['b_mean'])
df=pd.DataFrame({
'a': ['aa', 'a2', 'a3'],
'b': [1, 2, 3],
}, index=pd.Index([1., 2., 3.]))
df.groupby('a').apply(aggfunc)
```
### Issue Description
``I get a KeyError with the provided code. The call stack is:
<details>
``` python
Traceback (most recent call last):
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\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 1533, in pandas._libs.hashtable.Float64HashTable.get_item
File "pandas\_libs\hashtable_class_helper.pxi", line 1542, in pandas._libs.hashtable.Float64HashTable.get_item
KeyError: 0.0
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "<input>", line 8, in <module>
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\groupby\groupby.py", line 1275, in apply
result = self._python_apply_general(f, self._selected_obj)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\groupby\groupby.py", line 1309, in _python_apply_general
keys, values, mutated = self.grouper.apply(f, data, self.axis)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\groupby\ops.py", line 804, in apply
result_values, mutated = splitter.fast_apply(f, sdata, group_keys)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\groupby\ops.py", line 1349, in fast_apply
return libreduction.apply_frame_axis0(sdata, f, names, starts, ends)
File "pandas\_libs\reduction.pyx", line 369, in pandas._libs.reduction.apply_frame_axis0
File "pandas\_libs\reduction.pyx", line 428, in pandas._libs.reduction.BlockSlider.__init__
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\frame.py", line 3430, in __getitem__
indexer = convert_to_index_sliceable(self, key)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexing.py", line 2329, in convert_to_index_sliceable
return idx._convert_slice_indexer(key, kind="getitem")
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexes\numeric.py", line 242, in _convert_slice_indexer
return self.slice_indexer(key.start, key.stop, key.step, kind=kind)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexes\base.py", line 5685, in slice_indexer
start_slice, end_slice = self.slice_locs(start, end, step=step)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexes\base.py", line 5893, in slice_locs
end_slice = self.get_slice_bound(end, "right")
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexes\base.py", line 5807, in get_slice_bound
raise err
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexes\base.py", line 5801, in get_slice_bound
slc = self.get_loc(label)
File "C:\Users\nbttn1\python_venv\pandas_bug\lib\site-packages\pandas\core\indexes\base.py", line 3363, in get_loc
raise KeyError(key) from err
KeyError: 0
```
</details>
Note that the KeyError doesn't appear when I send in these other very similar dataframes:
``` python
# okay when the 1st element of 'a' is written differently
df=pd.DataFrame({
'a': ['a1', 'a2', 'a3'],
'b': [1, 2, 3],
}, index=pd.Index([1., 2., 3.]))
```
``` python
# okay when index is not float
df=pd.DataFrame({
'a': ['aa', 'a2', 'a3'],
'b': [1, 2, 3],
}, index=pd.Index([1, 2, 3]))
```
``` python
# okay when there are only two rows
df=pd.DataFrame({
'a': ['aa', 'a2'],
'b': [1, 2],
}, index=pd.Index([1., 2.]))
```
### Expected Behavior
There should not be any KeyError, and the output should look something like the following:
``` python
b_mean
a
a2 2.0
a3 3.0
aa 1.0
```
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.7.9.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19041
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 12, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None
pandas : 1.3.4
numpy : 1.21.3
pytz : 2021.3
dateutil : 2.8.2
pip : 21.1.2
setuptools : 57.0.0
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 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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```
>>>-------------------------------------------------------------------------
Exception in /home/runner/work/pandas/pandas/doc/source/user_guide/io.rst at block ending on line 3032
Specify :okexcept: as an option in the ipython:: block to suppress this message
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-331-4c4d77530df1> in <module>
----> 1 df = pd.read_xml(
2 "s3://irs-form-990/201923199349319487_public.xml",
3 xpath=".//irs:Form990PartVIISectionAGrp",
4 namespaces={"irs": "http://www.irs.gov/efile"}
5 )
~/work/pandas/pandas/pandas/io/xml.py in read_xml(path_or_buffer, xpath, namespaces, elems_only, attrs_only, names, encoding, parser, stylesheet, compression, storage_options)
921 """
922
--> 923 return _parse(
924 path_or_buffer=path_or_buffer,
925 xpath=xpath,
~/work/pandas/pandas/pandas/io/xml.py in _parse(path_or_buffer, xpath, namespaces, elems_only, attrs_only, names, encoding, parser, stylesheet, compression, storage_options, **kwargs)
722 raise ValueError("Values for parser can only be lxml or etree.")
723
--> 724 data_dicts = p.parse_data()
725
726 return _data_to_frame(data=data_dicts, **kwargs)
~/work/pandas/pandas/pandas/io/xml.py in parse_data(self)
387 from lxml.etree import XML
388
--> 389 self.xml_doc = XML(self._parse_doc(self.path_or_buffer))
390
391 if self.stylesheet is not None:
~/work/pandas/pandas/pandas/io/xml.py in _parse_doc(self, raw_doc)
536 )
537
--> 538 handle_data = get_data_from_filepath(
539 filepath_or_buffer=raw_doc,
540 encoding=self.encoding,
~/work/pandas/pandas/pandas/io/xml.py in get_data_from_filepath(filepath_or_buffer, encoding, compression, storage_options)
599 or file_exists(filepath_or_buffer)
600 ):
--> 601 with get_handle(
602 filepath_or_buffer,
603 "r",
~/work/pandas/pandas/pandas/io/common.py in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)
606
607 # open URLs
--> 608 ioargs = _get_filepath_or_buffer(
609 path_or_buf,
610 encoding=encoding,
~/work/pandas/pandas/pandas/io/common.py in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options)
354
355 try:
--> 356 file_obj = fsspec.open(
357 filepath_or_buffer, mode=fsspec_mode, **(storage_options or {})
358 ).open()
~/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/fsspec/core.py in open(self)
133 been deleted; but a with-context is better style.
134 """
--> 135 out = self.__enter__()
136 closer = out.close
137 fobjects = self.fobjects.copy()[:-1]
~/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/fsspec/core.py in __enter__(self)
100 mode = self.mode.replace("t", "").replace("b", "") + "b"
101
--> 102 f = self.fs.open(self.path, mode=mode)
103
104 self.fobjects = [f]
~/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/fsspec/spec.py in open(self, path, mode, block_size, cache_options, **kwargs)
974 else:
975 ac = kwargs.pop("autocommit", not self._intrans)
--> 976 f = self._open(
977 path,
978 mode=mode,
~/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/s3fs/core.py in _open(self, path, mode, block_size, acl, version_id, fill_cache, cache_type, autocommit, requester_pays, **kwargs)
532 cache_type = self.default_cache_type
533
--> 534 return S3File(
535 self,
536 path,
~/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/s3fs/core.py in __init__(self, s3, path, mode, block_size, acl, version_id, fill_cache, s3_additional_kwargs, autocommit, cache_type, requester_pays)
1821 self.details = s3.info(path)
1822 self.version_id = self.details.get("VersionId")
-> 1823 super().__init__(
1824 s3, path, mode, block_size, autocommit=autocommit, cache_type=cache_type
1825 )
~/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/fsspec/spec.py in __init__(self, fs, path, mode, block_size, autocommit, cache_type, cache_options, **kwargs)
1302 if mode == "rb":
1303 if not hasattr(self, "details"):
-> 1304 self.details = fs.info(path)
1305 self.size = self.details["size"]
1306 self.cache = caches[cache_type](
~/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/fsspec/asyn.py in wrapper(*args, **kwargs)
86 def wrapper(*args, **kwargs):
87 self = obj or args[0]
---> 88 return sync(self.loop, func, *args, **kwargs)
89
90 return wrapper
~/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/fsspec/asyn.py in sync(loop, func, timeout, *args, **kwargs)
67 raise FSTimeoutError
68 if isinstance(result[0], BaseException):
---> 69 raise result[0]
70 return result[0]
71
~/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/fsspec/asyn.py in _runner(event, coro, result, timeout)
23 coro = asyncio.wait_for(coro, timeout=timeout)
24 try:
---> 25 result[0] = await coro
26 except Exception as ex:
27 result[0] = ex
~/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/s3fs/core.py in _info(self, path, bucket, key, refresh, version_id)
1062 else:
1063 try:
-> 1064 out = await self._simple_info(path)
1065 except PermissionError:
1066 # If the permissions aren't enough for scanning a prefix
~/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/s3fs/core.py in _simple_info(self, path)
975 prefix = key.strip("/")
976
--> 977 out = await self._call_s3(
978 "list_objects_v2",
979 self.kwargs,
~/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/s3fs/core.py in _call_s3(self, method, *akwarglist, **kwargs)
235
236 async def _call_s3(self, method, *akwarglist, **kwargs):
--> 237 await self.set_session()
238 s3 = await self.get_s3(kwargs.get("Bucket"))
239 method = getattr(s3, method)
~/miniconda3/envs/pandas-dev/lib/python3.8/site-packages/s3fs/core.py in set_session(self, refresh, kwargs)
376
377 conf = AioConfig(**config_kwargs)
--> 378 self.session = aiobotocore.AioSession(**self.kwargs)
379
380 for parameters in (config_kwargs, self.kwargs, init_kwargs, client_kwargs):
AttributeError: module 'aiobotocore' has no attribute 'AioSession'
```
cc @pandas-dev/pandas-core | {
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https://api.github.com/repos/pandas-dev/pandas/issues/44312 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44312/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44312/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44312/events | https://github.com/pandas-dev/pandas/issues/44312 | 1,045,130,201 | I_kwDOAA0YD84-S2vZ | 44,312 | BUG: json_normalize crashes when len(record_path)==1 and non-leaf node of nested meta path is None | {
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} | 0 | "2021-11-04T19:36:29Z" | "2021-11-14T02:34:45Z" | "2021-11-14T02:34:45Z" | 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 pandas as pd
j = {'a': 'foo', 'b': [1, 2], 'c': None}
pd.json_normalize(j, record_path='b', meta=['a', ['c', 'e']], errors="ignore")
>>>
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/main/.local/lib/python3.9/site-packages/pandas/io/json/_normalize.py", line 504, in _json_normalize
_recursive_extract(data, record_path, {}, level=0)
File "/home/main/.local/lib/python3.9/site-packages/pandas/io/json/_normalize.py", line 492, in _recursive_extract
meta_val = _pull_field(obj, val[level:])
File "/home/main/.local/lib/python3.9/site-packages/pandas/io/json/_normalize.py", line 388, in _pull_field
result = result[field]
```
### Issue Description
When calling json_normalize with:
- a record path length of one (above succeed with longer record path)
- a nested metadata field where a non-leaf node is None
- errors="ignore"
The parsing crashes with a TypeError.
The error happens on line 388 of _normalize.py.
### Expected Behavior
The missing nested metadata columns are filled with NaNs.
### Installed Versions
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.9.7.final.0
python-bits : 64
OS : Linux
OS-release : 5.14.14-arch1-1
Version : #1 SMP PREEMPT Wed, 20 Oct 2021 21:35:18 +0000
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.4
numpy : 1.20.3
pytz : 2021.3
dateutil : 2.8.2
pip : 21.2.4
setuptools : 41.6.0
Cython : 0.29.24
pytest : 6.2.5
hypothesis : None
sphinx : 4.2.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : 7.19.0
pandas_datareader: None
bs4 : 4.9.3
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.7.1
sqlalchemy : 1.4.23
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
xlwt : None
numba : 0.54.1
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https://api.github.com/repos/pandas-dev/pandas/issues/44313 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44313/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44313/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44313/events | https://github.com/pandas-dev/pandas/issues/44313 | 1,045,191,950 | I_kwDOAA0YD84-TF0O | 44,313 | BUG: Converted number to float incorrectly | {
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] | closed | false | null | [] | null | 3 | "2021-11-04T20:51:32Z" | "2021-11-04T22:25:33Z" | "2021-11-04T21:59:19Z" | 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
data1 = [{
'a': 0.1,
'b': 0.2,
'c': 3
}]
df1 = pd.DataFrame(data1)
data2 = [{
'a': 0.1,
'b': 'a',
'c': 3,
}]
df2 = pd.DataFrame(data2)
```
### Issue Description
When all columns are either float or number, all columns will convert to float (including number).
```
data1 = [{
'a': 0.1,
'b': 0.2,
'c': 3
}]
df1 = pd.DataFrame(data1)
print(df.values)
the output (having "." after "3") is [0.1, 0.2, 3.]
```
When there is at least one non-float or non-number column, the value shows correctly
```
data2 = [{
'a': 0.1,
'b': 'a',
'c': 3
}]
df2 = pd.DataFrame(data2)
print(df.values)
the output is [0.1, 0.2, 3]
```
### Expected Behavior
both are expected to get [0.1, 0.2, 3]
### Installed Versions
<details>
Replace this line with the output of pd.show_versions()
1.2.5
</details>
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} | 1 | "2021-11-04T21:29:29Z" | "2021-11-06T19:45:02Z" | "2021-11-06T19:43:42Z" | 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
I've ONLY checked that the edit here fixes the commented-out test, not sure if thats sufficient to close #7796 | {
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- [x] tests added / passed
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Overlap with (but not rebased on top of) #44275 | {
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- [ ] tests added / passed
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} | 3 | "2021-11-05T08:00:38Z" | "2021-11-05T13:04:15Z" | "2021-11-05T13:04:15Z" | 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/reference/api/pandas.core.groupby.GroupBy.apply.html?highlight=groupby%20apply#pandas.core.groupby.GroupBy.apply
### Documentation problem
Documentation mentions that `func` is called twice on the first item. This [was fixed in 0.25](https://pandas.pydata.org/pandas-docs/stable/whatsnew/v0.25.0.html#groupby-apply-on-dataframe-evaluates-first-group-only-once). I was a bit unsure after reading the documentation, so I tried the example from the 0.25 release notes with all versions available on conda (for Python 3.7) and it seems the function is not called twice on any item.
For reference here is a table of the results. In the table the "count" indicates how often the function was called (same example as in the 0.25 release notes). 3 means the some item is evaluated twice, 2 means that weird behavior is gone...
<details>
| build | count |
|:-------------------------|--------:|
| 0.23.4=py37h637b7d7_1000 | 3 |
| 0.23.4=py37hf8a1672_0 | 3 |
| 0.24.0=py37hf484d3e_0 | 3 |
| 0.24.1=py37hf484d3e_0 | 3 |
| 0.24.2=py37hb3f55d8_0 | 3 |
| 0.24.2=py37hb3f55d8_1 | 3 |
| 0.24.2=py37hf484d3e_0 | 3 |
| 0.25.0=py37hb3f55d8_0 | 2 |
| 0.25.1=py37hb3f55d8_0 | 2 |
| 0.25.2=py37hb3f55d8_0 | 2 |
| 0.25.3=py37hb3f55d8_0 | 2 |
| 1.0.0=py37hb3f55d8_0 | 2 |
| 1.0.1=py37hb3f55d8_0 | 2 |
| 1.0.2=py37h0da4684_0 | 2 |
| 1.0.3=py37h0da4684_0 | 2 |
| 1.0.3=py37h0da4684_1 | 2 |
| 1.0.4=py37h0da4684_0 | 2 |
| 1.0.5=py37h0da4684_0 | 2 |
| 1.1.0=py37h3340039_0 | 2 |
| 1.1.1=py37h3340039_0 | 2 |
| 1.1.2=py37h3340039_0 | 2 |
| 1.1.3=py37h3340039_0 | 2 |
| 1.1.3=py37h9fdb41a_1 | 2 |
| 1.1.3=py37h9fdb41a_2 | 2 |
| 1.1.3=py37hb33c840_2 | 2 |
| 1.1.4=py37h10a2094_0 | 2 |
| 1.1.5=py37hdc94413_0 | 2 |
| 1.2.0=py37h40f5888_1 | 2 |
| 1.2.0=py37hdc94413_0 | 2 |
| 1.2.0=py37hdc94413_1 | 2 |
| 1.2.1=py37h40f5888_0 | 2 |
| 1.2.1=py37hdc94413_0 | 2 |
| 1.2.2=py37h40f5888_0 | 2 |
| 1.2.2=py37hdc94413_0 | 2 |
| 1.2.3=py37h40f5888_0 | 2 |
| 1.2.3=py37hdc94413_0 | 2 |
| 1.2.4=py37h219a48f_0 | 2 |
| 1.2.4=py37h40f5888_0 | 2 |
| 1.2.5=py37h219a48f_0 | 2 |
| 1.2.5=py37h40f5888_0 | 2 |
| 1.3.0=py37h219a48f_0 | 2 |
| 1.3.1=py37h219a48f_0 | 2 |
| 1.3.1=py37h40f5888_0 | 2 |
| 1.3.2=py37h40f5888_0 | 2 |
| 1.3.2=py37he8f5f7f_0 | 2 |
| 1.3.3=py37h40f5888_0 | 2 |
| 1.3.3=py37he8f5f7f_0 | 2 |
| 1.3.4=py37h40f5888_0 | 2 |
| 1.3.4=py37he8f5f7f_0 | 2 |
</details>
### Suggested fix for documentation
I'd propose to delete the following text:
> In the current implementation apply calls func twice on the first group to decide whether it can take a fast or slow code path. This can lead to unexpected behavior if func has side-effects, as they will take effect twice for the first group.
CC: @stuarteberg | {
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- [x] xref #44315
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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
pandas as pd
# load data
p2file = 'test_data.xlsx'
df = pd.ExcelFile(p2file).parse()
print(df.head())
print(df.dtypes)
```
Date/Time ch1 ch2
0 13:00:00 16-jul.-2020 -2202.969155 -999.25
1 13:00:01 16-jul.-2020 -2202.969155 -999.25
2 13:00:02 16-jul.-2020 -2202.969155 -999.25
3 13:00:03 16-jul.-2020 -2202.969155 -999.25
4 13:00:04 16-jul.-2020 -2202.969155 -999.25
Date/Time object
ch1 float64
ch2 float64
dtype: object
```#convert a column in datetime format
dt = pd.to_datetime(df.iloc[:,0])
print(dt.head())
print(dt.dtypes)
```
0 2021-07-16 13:00:00-20:20
1 2021-07-16 13:00:01-20:20
2 2021-07-16 13:00:02-20:20
3 2021-07-16 13:00:03-20:20
4 2021-07-16 13:00:04-20:20
Name: Date/Time, dtype: datetime64[ns, pytz.FixedOffset(-1220)]
datetime64[ns, pytz.FixedOffset(-1220)]
```
### Issue Description
In some of our xlsx files we keep date/time information in 'h: m: s day-month-year' format (date after time),
where day-month-year were separated by a ‘-’ symbol.
Pandas decided to subtract ‘year’ from ‘h: m: s’ and to present it as a time offset.
To avoid this collision , we need to replace the symbol ’-‘ by ‘/’.
Now, it works as desired.
if we keep date/time information in 'day-month-year h: m: s' format (time after date), we do not have this issue.
### Expected Behavior
```#process datetime format
df.iloc[:,0] = df.iloc[:,0].str.replace('-','/')
print(df.head())
print(df.dtypes)
```
Date/Time ch1 ch2
0 13:00:00 16/jul./2020 -2202.969155 -999.25
1 13:00:01 16/jul./2020 -2202.969155 -999.25
2 13:00:02 16/jul./2020 -2202.969155 -999.25
3 13:00:03 16/jul./2020 -2202.969155 -999.25
4 13:00:04 16/jul./2020 -2202.969155 -999.25
Date/Time object
ch1 float64
ch2 float64
dtype: object
```#convert a column in datetime format
dt = pd.to_datetime(df.iloc[:,0])
print(dt.head())
print(dt.dtypes)
```
0 2020-07-16 13:00:00
1 2020-07-16 13:00:01
2 2020-07-16 13:00:02
3 2020-07-16 13:00:03
4 2020-07-16 13:00:04
Name: Date/Time, dtype: datetime64[ns]
datetime64[ns]
### Installed Versions
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.8.12.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19042
machine :
processor :
byteorder : little
LC_ALL : None
LANG : None
LOCALE : fr_FR.cp1252
pandas : 1.3.4
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 : 3.0.1
IPython : 7.29.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.3
numexpr : None
odfpy : None
openpyxl : 3.0.9
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
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} | 2 | "2021-11-05T11:04:47Z" | "2021-11-05T13:20:28Z" | "2021-11-05T13:04:15Z" | CONTRIBUTOR | null | The described behavior has been fixed in 0.25
- [x] closes #44318
- [ ] 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, _comment:_ wouldn't say this is applicable here
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} | 1 | "2021-11-05T11:08:50Z" | "2021-11-15T18:22:55Z" | "2021-11-15T18:22:55Z" | 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
print(pd.Series([1], index=pd.Index([False])).loc[False]) # Works i.e. returns 1
print(pd.DataFrame([[1]], index=pd.Index([False])).loc[False]) # Works i.e. returns [1]
print(pd.DataFrame([[1]], columns=pd.Index([False])).loc[:, False]) # Fails
```
### Issue Description
You can select a single *row* from a `DataFrame` by supplying a boolean key to `loc`, but not a single column. This seems inconsistent.
### Expected Behavior
Return the relevant column
### Installed Versions
<details>
INSTALLED VERSIONS
------------------
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.8.12.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.18363
machine : AMD64
processor : Intel64 Family 6 Model 85 Stepping 7, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United Kingdom.1252
pandas : 1.3.4
numpy : 1.21.3
pytz : 2021.3
dateutil : 2.8.2
pip : 21.1.1
setuptools : 58.0.4
Cython : 0.29.24
pytest : 6.2.4
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : 7.29.0
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 : 3.0.9
pandas_gbq : None
pyarrow : 3.0.0
pyxlsb : None
s3fs : None
scipy : 1.6.2
sqlalchemy : None
tables : 3.6.1
tabulate : None
xarray : 0.19.0
xlrd : 2.0.1
xlwt : None
numba : 0.53.1
</details>
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