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https://api.github.com/repos/pandas-dev/pandas/issues/44423 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44423/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44423/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44423/events | https://github.com/pandas-dev/pandas/pull/44423 | 1,052,556,649 | PR_kwDOAA0YD84ue3b1 | 44,423 | BUG: AttributeError: 'BooleanArray' object has no attribute 'sum' while infer types | {
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No
#### Describe the solution you'd like
`pd.DataFrame.shift`/`pd.Series.shift` could alternatively accept a list of ints or a collection of numbers, and the result would be a dataframe with one column per shift. This would make it very convenient to e.g. crea... | {
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This should resolve issue #44379
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class InPlace(enum.Enum):
only = 0 # never copy; raise instead of casting
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cc @jorisvandenbossche these were introduced in #14536 | {
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I have a DataFrame with several statistics from baseball teams across different years. I want to rank each team in each statistic, grouped by season. Every column is numeric, except for the teamID column which is an obje... | {
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- [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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- [ ] tests added / passed
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This breaks our nightlies, but doesn't on regular CI. It should show up pretty soon in regular CI, once the conda-forge folks add it.
This means unfortuanately that I have no way to test this.
Can someone with with the perms on the MacPython repo ... | {
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- [x] closes #39465
- also relevant for #26023
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From #28602
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Followup to #44398. Should get docs build to green. cc @jbrockmendel
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Replaced Timestamp.now () with pd.Timestamp (2021, 1, 1, 12) | {
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have seen this on multiple PRs. Maybe something recently added causes this to timeout. | {
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closes #44343 | {
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we should do the same | {
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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.
- [ ] I have confirmed this bug exists on the master branch of pandas.
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```
In [42]: arr = pd.timedelta_range(0, periods=3)
In [43]: pd.Series(arr) / 2.0
Out[43]:
0 0 days 00:00:00
1 0 da... | {
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This may be a quite big thing. But I's like pandas to be able to execute a MDX query to an OLAP server and read the results into a DataFrame.
#### Describe the solution you'd like
I imagine there could be a function similar to pd.read_sql
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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.
- [ ] I have confirmed this bug exists on the master branch of pandas.
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I still need to add a test that would actually catch this | {
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- [ ] closes #xxxx
- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
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- [ ] I have confirmed this bug exists on the master branch of pandas.
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- [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
Some of the current `param` definitions are causing the same benchmark to run more than once witho... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/44476 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44476/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44476/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44476/events | https://github.com/pandas-dev/pandas/pull/44476 | 1,054,075,810 | PR_kwDOAA0YD84ujbPm | 44,476 | TST: flaky gcs compression test | {
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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
Bit of a shot in the dark. | {
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xref #44450 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/44478 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44478/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44478/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44478/events | https://github.com/pandas-dev/pandas/pull/44478 | 1,054,336,316 | PR_kwDOAA0YD84ukHRD | 44,478 | avoid a warning by PyTypeChecker | {
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use typing.Union to combine type "FilePathOrBuffer[AnyStr]" and "None", instead of " | " can avoid it.
- [ ] ... | {
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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
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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
Following PR #44331, I added a release note for the 1.4.0 release according to @simo... | {
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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
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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
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numpy.searchsorted() does not handle NaNs in 'object' arrays as
expected (numpy/numpy#15499). Therefore we cannot search NaNs using binary
search. So we use binary search only for targets without NaNs.
- [x] closes #44482
- [x] tests added / passed
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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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https://api.github.com/repos/pandas-dev/pandas/issues/44486 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/44486/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/44486/comments | https://api.github.com/repos/pandas-dev/pandas/issues/44486/events | https://github.com/pandas-dev/pandas/issues/44486 | 1,055,137,502 | I_kwDOAA0YD84-5B7e | 44,486 | ENH: DataFrame.sample should accept numpy.random.Generator | {
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## Rationale
As far as I can tell, the convention for numpy 1.21 random sa... | {
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This is extremely minor and i just quickly did it in codespaces but I ran into this a few times and I thought it might be helpful for others. | {
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- [x] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
cc @stefansorgqc | {
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From what I've seen in python classes: Handling a huge data frame, especially beginners using `apply` on huge data frames don't know that it loads the whole frame while looping.
[Example](https://stackoverflow.com/a/62968313):
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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
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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
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- [ ] tests added / passed
- [ ] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit) for how to run them
- [ ] whatsnew entry
This is yak-shaving the trails back to a bug in Series.where with nullable dtypes.
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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.
- [ ] I have confirmed this issue exists on the master branch of pandas.
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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
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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.
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Changed variable new_pd_index to final_pd_index in line 2099
Handled mypy type ignore[assignment] error in pandas/io/pytables.py in line 2099
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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
Replacing Timestamp.now() in tests.
Left Timestamp.now () in the following tests:
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```
username = session['username']
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Changed variable name from vals to array_vals in pandas/core/index/multi.py: 705 and 706
To remove type: ignore[assignment] mypy error
Changed variable name from m to mapped_result in pandas/core/index/multi.py: 3121
Removed type: ignore[assignment] mypy error in line 3126 and 3131 | {
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Changed variable name `repeats` to `ensured_repeats` pandas/core/indexes/multi.py: 2161 and 2167
Removed type[ignore] assignment and mypy error comment.
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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.
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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.
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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
Gives us the flexibility to consolidate the logic in `__add__` | {
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