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https://api.github.com/repos/pandas-dev/pandas/issues/27413 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27413/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27413/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27413/events | https://github.com/pandas-dev/pandas/pull/27413 | 468,437,436 | MDExOlB1bGxSZXF1ZXN0Mjk3ODY2MzQ4 | 27,413 | CLN/REF: Unify Arithmetic Methods | {
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First is to end up with a single implementation for our arithmetic ops. By implementing the missing methods directly on DTA/PA, we make it so we don't need to special-case inside the `Index.__foo__` methods, so can dispatch to Series more directly.
Second is to get the wrapper defined in_arith_meth... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27414 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27414/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27414/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27414/events | https://github.com/pandas-dev/pandas/issues/27414 | 468,524,860 | MDU6SXNzdWU0Njg1MjQ4NjA= | 27,414 | read_csv memory leak | {
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] | closed | false | null | [] | null | 3 | 2019-07-16T08:44:51Z | 2020-01-21T04:15:08Z | 2020-01-21T04:15:08Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
import sys
import pandas as pd
_dir = r'D:\Python\data'
file_name = pd.read_csv(_dir + r'\dblist.csv', index_col=0)
file_name.loc[:, 'code'] = [x.upper() for x in file_name['code']]
file_name.loc[:, 'name'] = [x.upper() for x in file_name['name']]... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27415 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27415/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27415/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27415/events | https://github.com/pandas-dev/pandas/issues/27415 | 468,568,163 | MDU6SXNzdWU0Njg1NjgxNjM= | 27,415 | Using a `CategoricalIndex` with interval categories as column index breaks operations on a `DataFrame` | {
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```python
>>> a = pd.DataFrame([[1, 2]], columns=pd.CategoricalIndex(pd.interval_range(start=0.0, end=2.0)))
>>> a.T * 100
0
(0.0, 1.0] 100
(1.0, 2.0] 200
>>> a * 100
-------------------------------------------------------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27416 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27416/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27416/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27416/events | https://github.com/pandas-dev/pandas/pull/27416 | 468,624,164 | MDExOlB1bGxSZXF1ZXN0Mjk4MDE2MjY0 | 27,416 | CI: limit pytest version on 3.6 | {
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] | closed | false | null | [] | null | 37 | 2019-07-16T14:54:35Z | 2019-07-27T14:24:27Z | 2019-07-27T14:24:26Z | CONTRIBUTOR | null | While exploring the `maybe_convert_objects` I've got quite a few proposals/questions but in the end I've come to a conclusion that the logic of function itself is far from optimal.
#### Motivation
1. Main argument here is we are not checking for inconsistency of parts of already seen data. E.g. if we have seen `dat... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27418 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27418/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27418/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27418/events | https://github.com/pandas-dev/pandas/pull/27418 | 468,730,217 | MDExOlB1bGxSZXF1ZXN0Mjk4MTAyOTA2 | 27,418 | add some type annotations io/formats/format.py | {
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~~this PR also contains a refactor to simplify the addition of type annotations; `truncate_h` and `tr_col_num` are dependant variables. `truncate_h` can be `True` or `False`. if `True`, `tr_col_num` is an `int` else i... | {
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For Datetime blocks this leads to blowing up with ... | {
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```python
import pandas as pd
a = {'A': [1, 2, 3, 4], 'B': [5, 6, 7, 8], 'C': [9, 10, 11, 12]}
df = pd.DataFrame.from_records(a, index=['A', 'B'])
df.loc[(1,6)]
```
#### Problem description
When a non existent key `.loc` raises `TypeError`. Is this... | {
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Failing on the prerelease at https://pypi.org/project/pytest-azurepipelines/1.0.0a1/ | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27422 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27422/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27422/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27422/events | https://github.com/pandas-dev/pandas/issues/27422 | 468,829,384 | MDU6SXNzdWU0Njg4MjkzODQ= | 27,422 | BUG: to_datetime with multiple timezones does not coerce if invalid string in input | {
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```python
import pandas as pd
se = pd.Series(["2019-01-01 03:00:00-0500", "abc", "2019-01-01 03:00:00-0100"])
assert type(pd.to_datetime(se, errors="coerce").iloc[0]) == str
```
Note that the type of the first element (`"2019-01-01 03:00:00-0500"`) is `str` *after* the "conversion".
```p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27423 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27423/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27423/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27423/events | https://github.com/pandas-dev/pandas/pull/27423 | 468,849,109 | MDExOlB1bGxSZXF1ZXN0Mjk4MTk5MjI2 | 27,423 | CLN: fix build warning in c_timestamp.pyx | {
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pandas/_libs/tslibs/c_timestamp.c: In function ‘__pyx_f_6pandas_5_libs_6tslibs_11c_timestamp_10_Timestamp__get_start_end_field’:
pandas/_libs/tslibs/c_timestamp.c:7257:25: warning: ‘__pyx_t_10’ may be used uninitialized in this function [-Wmaybe-uninitialized]
7257 | __pyx_t_5numpy_int8_t __pyx_t_10[1];
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27424 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27424/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27424/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27424/events | https://github.com/pandas-dev/pandas/pull/27424 | 468,850,297 | MDExOlB1bGxSZXF1ZXN0Mjk4MjAwMTg5 | 27,424 | Removed ABCs from pandas._typing | {
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- [ ] tests added / passed
- [ ] passes `black pandas`
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
This reveals a few new typing issues so won't pass CI but submitting as draft
Here's one way I think that works to avoid import cycles. Basically... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27425 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27425/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27425/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27425/events | https://github.com/pandas-dev/pandas/pull/27425 | 468,855,307 | MDExOlB1bGxSZXF1ZXN0Mjk4MjA0MjU0 | 27,425 | BUG: fix+test fillna with non-nano datetime64; closes #27419 | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/27426 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27426/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27426/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27426/events | https://github.com/pandas-dev/pandas/pull/27426 | 468,883,453 | MDExOlB1bGxSZXF1ZXN0Mjk4MjI3MjI4 | 27,426 | Reallow usecols to reference OOB indices - reverts 25623 | {
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reverts #25623
@heckeop
@gfyoung I know you asked for a FutureWarning to be raised but I didn't want to mess around with the validation_function in place here so just did a simple revert for sake of time / effort
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https://api.github.com/repos/pandas-dev/pandas/issues/27427 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27427/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27427/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27427/events | https://github.com/pandas-dev/pandas/pull/27427 | 468,911,318 | MDExOlB1bGxSZXF1ZXN0Mjk4MjQ5OTYy | 27,427 | Merged mypy.ini into setup.cfg | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27428 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27428/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27428/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27428/events | https://github.com/pandas-dev/pandas/pull/27428 | 468,928,172 | MDExOlB1bGxSZXF1ZXN0Mjk4MjYxOTI5 | 27,428 | CLN/REF: stop allowing iNaT in DatetimeBlock | {
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xref #16674. The broader goal is de-special-casing code in internals.
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https://api.github.com/repos/pandas-dev/pandas/issues/27429 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27429/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27429/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27429/events | https://github.com/pandas-dev/pandas/issues/27429 | 469,033,129 | MDU6SXNzdWU0NjkwMzMxMjk= | 27,429 | cannot join on column with datetime when using the 'on' parameter | {
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] | closed | false | null | [] | null | 3 | 2019-07-17T07:31:20Z | 2019-07-17T18:14:09Z | 2019-07-17T17:55:57Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
import pandas as pd
left = pd.DataFrame({'date':['2019-01-01'], 'a': [1]})
left['date'] = pd.to_datetime(left['date'], utc=True)
right = pd.DataFrame({'date':['2019-01-01'], 'b': [1]})
right['date'] = pd.to_datetime(right['date'], utc=True)
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https://api.github.com/repos/pandas-dev/pandas/issues/27430 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27430/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27430/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27430/events | https://github.com/pandas-dev/pandas/issues/27430 | 469,121,889 | MDU6SXNzdWU0NjkxMjE4ODk= | 27,430 | validate ='m:m' in dataframe.merge should have a meaningful purpose | {
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Currently, in https://github.com/pandas-dev/pandas/blob/master/pandas/core/reshape/merge.py
```python
elif validate in ["many_to_many", "m:m"]:
pass
```
#### Problem description
I was expecting m:m to give me a warning/error if either the left... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27431 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27431/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27431/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27431/events | https://github.com/pandas-dev/pandas/issues/27431 | 469,247,535 | MDU6SXNzdWU0NjkyNDc1MzU= | 27,431 | Feature request: add option to disable columns.levels autosorting | {
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... | closed | false | null | [] | null | 1 | 2019-07-17T14:25:16Z | 2021-07-10T18:23:32Z | 2021-07-10T18:23:32Z | NONE | null | I am trying to develop general code to access specific columns in the order they are displayed by index. However, columns.levels resorts alphabetically automatically, and doesn't seem to have an option to have it... not do that. It would be useful if there was an option to have it remember the original order, to allo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27432 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27432/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27432/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27432/events | https://github.com/pandas-dev/pandas/pull/27432 | 469,274,225 | MDExOlB1bGxSZXF1ZXN0Mjk4NTM5NTAx | 27,432 | PLT: Delegating to plotting backend only plots of Series and DataFrame methods | {
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- [ ] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/27433 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27433/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27433/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27433/events | https://github.com/pandas-dev/pandas/issues/27433 | 469,314,773 | MDU6SXNzdWU0NjkzMTQ3NzM= | 27,433 | df.describe.min(), max(), count() etc. produce results inconsistent with describe | {
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```python
import pandas as pd
df = pd.DataFrame({'data': []})
print (df.describe())
print ('Dataframe mean: {}'.format(df['data'].describe().mean()))
print ('Dataframe min: {}'.format(df['data'].describe().min()))
print ('Dataframe count: {}'.format(d... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27434 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27434/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27434/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27434/events | https://github.com/pandas-dev/pandas/issues/27434 | 469,336,683 | MDU6SXNzdWU0NjkzMzY2ODM= | 27,434 | Connecting to Kaggle for data. | {
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] | closed | false | null | [] | null | 2 | 2019-07-17T16:57:54Z | 2019-08-01T03:34:26Z | 2019-07-17T17:00:24Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
project_data = pd.read_csv('https://www.kaggle.com/hanselhansel/donorschoose#train_data.csv')
resource_data = pd.read_csv('https://www.kaggle.com/hanselhansel/donorschoose#Resources.csv')
```
#### Problem description
Anyone one knows if I am p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27435 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27435/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27435/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27435/events | https://github.com/pandas-dev/pandas/issues/27435 | 469,368,371 | MDU6SXNzdWU0NjkzNjgzNzE= | 27,435 | Cannot install pandas 0.24.2 from source with Python 2.7 into an environment without NumPy | {
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```bash
RuntimeError: Python version >= 3.5 required.
```
#### Problem description
Under this docs: https://pandas.pydata.org/pandas-docs/stable/whatsnew/v0.24.0.html
0.24.x is supposed to be backward compatible to Python 2.
```
The 0.24.x series of ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27436 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27436/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27436/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27436/events | https://github.com/pandas-dev/pandas/pull/27436 | 469,371,508 | MDExOlB1bGxSZXF1ZXN0Mjk4NjEzMzQ1 | 27,436 | BUG: fix+test quantile with empty DataFrame, closes #23925 | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/27437 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27437/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27437/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27437/events | https://github.com/pandas-dev/pandas/issues/27437 | 469,374,615 | MDU6SXNzdWU0NjkzNzQ2MTU= | 27,437 | Indexing on series where index is output from pd.cut | {
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"color": "0e... | open | false | null | [] | null | 2 | 2019-07-17T18:24:13Z | 2021-09-20T18:27:19Z | null | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
import pandas as pd
data = pd.DataFrame(dict(values=range(20), quintiles=pd.cut(range(20), 5)))
grouped = data.groupby("quintiles")["values"]
samples = grouped.agg(lambda x: list(x.sample(3)))
samples
# quintiles
# (-0.019, 3.8] [3, 2, ... | {
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- [X] tests added / passed
- [X] passes `black pandas`
- [X] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
In order to stick to `maybe_convert_objects` realizatio... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27439 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27439/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27439/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27439/events | https://github.com/pandas-dev/pandas/issues/27439 | 469,423,730 | MDU6SXNzdWU0Njk0MjM3MzA= | 27,439 | [Feature request] Add a "filter" method to Index and Series | {
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```python
# Function
def _filter(self, func):
return self[list(map(func, self))]
# Set the attribute
setattr(pd.Index, "filter", _filter)
index = pd.Index(["iris_1", "notiris_1", "iris_2", "other_thing"])
# New way
func = lambda x:x.startswith("... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27441 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27441/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27441/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27441/events | https://github.com/pandas-dev/pandas/issues/27441 | 469,484,956 | MDU6SXNzdWU0Njk0ODQ5NTY= | 27,441 | Add 'key' keyword argument to max/min methods, akin to python's builtin max/min | {
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Specifying a `key=` function F to use indicates you want to return the `val` with the largest `F(val)`, as opposed to returning the largest val or returning the largest F(val).
The following code should work:
```
>>> pd.DataFrame([1, 3, 5, 7]).max(key=l... | {
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... | open | false | null | [] | null | 5 | 2019-07-17T23:13:12Z | 2021-07-10T18:30:33Z | null | NONE | null | Current behavior:
```
>>> df = pd.DataFrame({'a': [1, 1, 3], 'b': [9, 8, 7]})
>>> df.groupby('a')
<pandas.core.groupby.generic.DataFrameGroupBy object at 0x7fd3d5a7b470>
```
Desired behavior ... | {
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- [x] tests added / passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/27444 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27444/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27444/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27444/events | https://github.com/pandas-dev/pandas/pull/27444 | 469,544,767 | MDExOlB1bGxSZXF1ZXN0Mjk4NzM2MjYy | 27,444 | CLN: simplify maybe_convert_objects, soft_convert_objects | {
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Both of the functions have branches that are unreachable, so rip those out, along with adding types and validation. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27445 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27445/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27445/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27445/events | https://github.com/pandas-dev/pandas/pull/27445 | 469,545,970 | MDExOlB1bGxSZXF1ZXN0Mjk4NzM3MTcz | 27,445 | BUG: avoid incorrectly inheriting result | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27446 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27446/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27446/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27446/events | https://github.com/pandas-dev/pandas/issues/27446 | 469,566,261 | MDU6SXNzdWU0Njk1NjYyNjE= | 27,446 | Is the internal twosigma refactor of window.pyx planned for merging in pandas? | {
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I [floated](](https://github.com/pandas-dev/pandas/pull/27403#discussion_r304165649)) the idea of a window.pyx refactor, and... | {
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"followers_url": "https://api.github.com/users/j... | 1 | 2019-07-18T06:39:11Z | 2019-07-18T10:53:56Z | 2019-07-18T10:53:29Z | CONTRIBUTOR | null | Fixes a performance regression introduced in #26403 very shortly before `0.25.0rc0` was cut, which can be seen [here](https://qwhelan.github.io/pandas/#indexing.CategoricalIndexIndexing.time_getitem_slice?machine=T470&num_cpu=4&os=Linux%205.0.0-20-generic&ram=20305904)
![Screenshot from 2019-07-17 23-29-08](https://us... | {
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I am using pandas 0.24.2
This shows that drop_duplicates() in the loc statement does not work although it does work with the boolean approach.
```python
import p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27450 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27450/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27450/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27450/events | https://github.com/pandas-dev/pandas/issues/27450 | 469,686,451 | MDU6SXNzdWU0Njk2ODY0NTE= | 27,450 | Why read_sas is converting strings to float? | {
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"color": "5319e7",
"default": false,
"description": "SAS: read_sas",
"id": 258745163,
"name": "IO SAS",
"node_id": "MDU6TGFiZWwyNTg3NDUxNjM=",
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"description"... | closed | false | null | [] | null | 12 | 2019-07-18T10:15:02Z | 2019-07-23T18:16:20Z | 2019-07-23T16:48:34Z | NONE | null | #### Code Sample
```python
import pandas as pd
df = pd.read_sas('test.sas7bdat', format='sas7bdat', encoding='utf-8')
```
#### Problem description
I am trying to read a `.sas7bdat` file using `read_sas` and I am having a hard time because the module is converting strings values that look like a number into `f... | {
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"id": 7171206... | closed | false | null | [] | {
"closed_at": "2020-01-30T12:18:05Z",
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2019-07-18T10:55:17Z | 2019-11-08T01:03:24Z | 2019-11-08T01:03:24Z | NONE | null | Minor/trivial bug:
https://github.com/pandas-dev/pandas/blob/master/pandas/core/generic.py#L4960
Shouldn't `sample()` check that `frac` is between 0 and 1 somewhere?
Doc improvement suggestion:
Could anyone confirm that `replace=True|False` means allowing|disallowing sampling the same row more than once?
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27452 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27452/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27452/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27452/events | https://github.com/pandas-dev/pandas/issues/27452 | 469,707,237 | MDU6SXNzdWU0Njk3MDcyMzc= | 27,452 | .merge() does not preserve the row-order at the output dataframe | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2019-07-18T11:05:24Z | 2019-07-18T11:15:32Z | 2019-07-18T11:15:08Z | NONE | null | Have a look here:
https://stackoverflow.com/q/57092373/9024698 | {
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Merge with right join not preserve order of columns:
columns = ['A', 'B', 'C']
data_1 = [[2, 5, 3, 5], [8, 2, 4, 1], [6, 5, 9, 1]]
data_1 = np.array(data_1).T
df_1 = pd.DataFrame(data=data_1, columns=columns)
print (df_1)... | {
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] | closed | false | null | [] | null | 1 | 2019-07-18T12:21:11Z | 2019-07-18T16:55:53Z | 2019-07-18T16:55:48Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
import pandas as pd
str1='05-01-2019 00:37'
date1=pd.to_datetime(str1).date()
print(date1)
# output 2019-05-01
str2='15-01-2019 00:37'
date2=pd.to_datetime(str2).date()
print(date2)
# output 2019-01-15
```
#### Problem descript... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27456 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27456/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27456/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27456/events | https://github.com/pandas-dev/pandas/issues/27456 | 469,870,854 | MDU6SXNzdWU0Njk4NzA4NTQ= | 27,456 | issues with overlapping multi index intervals | {
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"description": "Related to indexing on s... | open | false | null | [] | null | 13 | 2019-07-18T16:33:22Z | 2020-04-27T00:16:45Z | null | NONE | null | Scenario 1: single-level indexing, which works fine:
import pandas as pd # pandas version 0.25.0, python version: 3.6.6
idx = pd.IntervalIndex.from_arrays([1,3,1,2],
[3,4,2,4])
df = pd.DataFrame({'Value':[1,2,3,4]},index=idx)
which returns:
df =
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27457 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27457/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27457/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27457/events | https://github.com/pandas-dev/pandas/issues/27457 | 469,906,466 | MDU6SXNzdWU0Njk5MDY0NjY= | 27,457 | missing.cpython-35m-x86_64 | {
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```
7fecaeb6d000-7fecaeb7f000 r-xp 00000000 08:04 3021138 /home/lib/python3.5/site-packages/pandas/_... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27458 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27458/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27458/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27458/events | https://github.com/pandas-dev/pandas/issues/27458 | 469,935,227 | MDU6SXNzdWU0Njk5MzUyMjc= | 27,458 | Feature Request: Binomial Standard Deviation? | {
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We often work with large quantities of simulated data, and it would be convenient if we could get binomial standard deviation with a `.binom_std()` method (or with an optional argument to `.std()`. | {
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- [ X] tests added / passed
- [ ] passes `black pandas`
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/27460 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27460/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27460/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27460/events | https://github.com/pandas-dev/pandas/issues/27460 | 470,041,588 | MDU6SXNzdWU0NzAwNDE1ODg= | 27,460 | REF: share code between pd.array and Series constructor | {
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"de... | open | false | null | [] | null | 0 | 2019-07-18T23:25:25Z | 2019-07-23T19:38:12Z | null | MEMBER | null | I've noticed a couple of places in the code where we do runtime imports of Series just to do `values = Series(values)._values`. It would be nice to avoid that.
This probably also means moving parts of internals.construction to somewhere like `arrays.array_`. In particular I think this would require moving sanitize... | {
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Everything else should be self-explanatory. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27462 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27462/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27462/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27462/events | https://github.com/pandas-dev/pandas/issues/27462 | 470,089,334 | MDU6SXNzdWU0NzAwODkzMzQ= | 27,462 | ENH: allow EA to register types for is_scalar | {
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> i think we need. way for EA to hook into this for an EA scalar
> eg an IPaddress from cyberpandas could register a scalar i think
Before we move on this, I think we need to clarify in which situations we care about `lib.is_scalar(x)` vs the ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27464 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27464/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27464/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27464/events | https://github.com/pandas-dev/pandas/issues/27464 | 470,118,010 | MDU6SXNzdWU0NzAxMTgwMTA= | 27,464 | Bug in DataFrame.rfloordiv when alignment for different columns and index. | {
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"followers_url": "https://api.github.... | 1 | 2019-07-19T03:19:10Z | 2019-08-20T17:45:06Z | 2019-08-20T17:45:06Z | CONTRIBUTOR | null | I think that `.loc[0, 'A']` should be inf.
```python
In [36]: a = pd.DataFrame({"A": [0, 1, 2], 'B': [1.1, None, 1.1]})
In [37]: b = pd.DataFrame({"A": [1.1, 1.2, 1.3]}, index=[0, 2, 3])
In [38]: a.rfloordiv(b, fill_value=1)
Out[38]:
A B
0 NaN 0.0
1 1.0 NaN
2 0.0 0.0
3 1.0 NaN
```
to... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27465 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27465/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27465/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27465/events | https://github.com/pandas-dev/pandas/pull/27465 | 470,128,671 | MDExOlB1bGxSZXF1ZXN0Mjk5MTc3MTY0 | 27,465 | CLN: remove unused parts of skiplist (most of it) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27466 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27466/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27466/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27466/events | https://github.com/pandas-dev/pandas/pull/27466 | 470,131,999 | MDExOlB1bGxSZXF1ZXN0Mjk5MTc5ODU5 | 27,466 | CLN: remove unused row_bool_subset | {
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Tracing back the blame, row_bool_subset was introduced [here](https://github.com/pandas-dev/pandas/commit/b15ae85e1f647821755d35bedd6143ad1e9c3678) in 2012 to close #152 and it started being called only for result.ndim ... | {
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Related #27389 (several issues there)
closes #27486 | {
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... | open | false | null | [] | null | 0 | 2019-07-19T05:53:17Z | 2019-07-22T21:13:33Z | null | NONE | null | Adding tests for #27467 surfaced some bugs:
```python
from pandas import *
df = DataFrame(dict(a=[0, 0, 0, 1, 1, 1], b=range(6)))
g = df.groupby(np.repeat([0,1], 3))
# ok
print(g.ngroup())
#fails
g.transform('ngroup')
AttributeError: ("'Series' object has no attribute 'ngroup'", 'occurred at index a')
`... | {
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... | open | false | null | [] | null | 0 | 2019-07-19T05:54:53Z | 2019-07-23T15:02:19Z | null | NONE | null | Adding tests for #27467 surfaced some bugs:
```python
from pandas import *
df = DataFrame(dict(a=[0, 0, 0, 1, 1, 1], b=range(6)))
g = df.groupby(np.repeat([0,1], 3))
# ok
print(g.size())
#fails
g.transform('size')
TypeError: Transform function invalid for data types
``` | {
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"followers_url": "https://api.github.... | 2 | 2019-07-19T05:58:13Z | 2019-08-12T17:56:47Z | 2019-08-12T17:56:47Z | NONE | null | Adding tests for #27467 surfaced some bugs:
```python
from pandas import *
df = DataFrame(dict(a=[0, 0, 0, 1, 1, 1], b=range(6)))
g = df.groupby(np.repeat([0,1], 3))
# ok
g.quantile(50)
<segfault>
```
quantile accepts floats in `[0,1]` or arrays of floats. It appears not to validate the range though. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27471 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27471/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27471/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27471/events | https://github.com/pandas-dev/pandas/issues/27471 | 470,154,272 | MDU6SXNzdWU0NzAxNTQyNzI= | 27,471 | missing pandas.core.config in v0.25 | {
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I need a print table with several columns by default for automatic test purposes while the default number of columns changed from version v0.23. I was using a simple check
```python
if 'display.max_columns' in pandas.core.config._registered_options:
pandas.set_option('display.max_colum... | {
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... | 6 | 2019-07-19T06:10:48Z | 2021-07-22T18:05:00Z | 2021-07-22T18:05:00Z | NONE | null | Adding tests for #27467 surfaced some bugs:
```python
from pandas import *
df = DataFrame(dict(a=[0, 0, 0, 1, 1, 1], b=range(6)))
g = df.groupby(np.repeat([0,1], 3))
# ok
g.cumcount()
# fails
g.transform('cumcount')
AttributeError: ("'Series' object has no attribute 'cumcount'", 'occurred at index a')
```
... | {
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- [ ] waiting for #27584 to be resolved (move `check_percentiles` out of `NDFrame`)
- [ ] waiting for #27526 to be resolved (#20405 cythonized `Groupby.quantile` with functionality regression)
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/27475 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27475/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27475/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27475/events | https://github.com/pandas-dev/pandas/pull/27475 | 470,224,662 | MDExOlB1bGxSZXF1ZXN0Mjk5MjUyNTE5 | 27,475 | Make a fastpath conditional on `data is None` | {
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case `data is None`. Better include an if-statement to make sure this
condition actually holds.
When this if-statement is not present, failure occurs at a later point
in the code when an empty index is used, because that later code expects da... | {
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... | 4 | 2019-07-19T13:30:37Z | 2019-08-12T21:16:39Z | 2019-07-26T20:58:46Z | CONTRIBUTOR | null | #### Problem description
New added feature read_spss() #26537 doesn´t still have any kind of documentation about it http://pandas-docs.github.io/pandas-docs-travis/user_guide/io.html | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27477 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27477/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27477/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27477/events | https://github.com/pandas-dev/pandas/issues/27477 | 470,372,484 | MDU6SXNzdWU0NzAzNzI0ODQ= | 27,477 | Run a User Survey | {
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We can ask things like
* What version of pandas are you using?
* Is pandas stable enough?
* What APIs are you using (e.g. which `read_` methods)?
* What features would you like (additional readers, etc.)?
I plan to put ... | {
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"followers_url": "https://api.github.... | 33 | 2019-07-19T15:10:58Z | 2019-08-01T20:50:46Z | 2019-08-01T18:04:12Z | CONTRIBUTOR | null | This PR adds a roadmap document. This is useful when pursing funding; we can point to a list of known items that we'd like to do if we had the person time (and funding) to tackle them.
Let's have two discussions
1. Do we want this? Roadmaps tend to go stale. How can we keep this up to date?
2. If so, what items ... | {
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"followers_url": "https://api.github.... | 9 | 2019-07-19T16:01:42Z | 2019-08-20T14:26:50Z | 2019-08-20T14:26:49Z | CONTRIBUTOR | null | Consider
```python
import matplotlib.units as munits
import pandas as pd
pd.plotting.deregister_matplotlib_converters()
print(pd.__version__)
for key in munits.registry:
print(key, '\t', munits.registry[key])
```
`deregister_matplotlib_converters()` should only remove `pandas` converters, and not any... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27480 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27480/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27480/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27480/events | https://github.com/pandas-dev/pandas/pull/27480 | 470,411,751 | MDExOlB1bGxSZXF1ZXN0Mjk5Mzk3MjIy | 27,480 | Use Matplotlib built-in converters for python date(time)s | {
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I'm struggling to write a test for this; I think it requires a clean state with no pandas imports, so one can check what was in the units registry before pandas... | {
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import pandas as pd
x = pd.Series([1,2,3,4])
xt = type(x)
pd.isnull(xt)
## Traceback (most recent call last):
## File "<input>", line 1, in <module>
## File "/home/bbassett/venv37/lib/python3.7/site-packages/pandas/core/dtypes/missing.py", line 122, in isna
## return _isna(obj)
## File "/... | {
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... | 4 | 2019-07-19T19:53:15Z | 2019-12-31T12:34:12Z | null | CONTRIBUTOR | null | I'd like to have a document that describes how we think people should write pandas code.
This introduces a bit of friction when documenting something, since you'll need to decide "does it go in best practices or the user guide?" But I think the idea of a "best practices" document with opinionated, short examples and... | {
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"followers_url": "https://api.github.... | 1 | 2019-07-19T20:55:42Z | 2019-07-25T15:58:18Z | 2019-07-25T15:58:18Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
from pandas import Series
print(Series([-1j]))
```
#### Problem description
This raises the following error:
```
Traceback (most recent call last):
File "foo.py", line 3, in <module>
print(Series([-1j]))
File "/home/david/.pyen... | {
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... | 3 | 2019-07-19T22:40:38Z | 2019-09-05T17:10:54Z | 2019-09-05T17:10:54Z | MEMBER | null | Right now we don't benchmark performance of read_excel across the various engines (xlrd, openpyxl and odfpy) so would gladly accept contributions to improve benchmark coverage on those | {
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Examples:
- `g.transform('invalid_name')`
- `g.transform('agg')`, attribute exists but isn't appropriate agg/transformation.
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My hobby horse right now is the dependency structure. `core.dtypes`... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27488 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27488/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27488/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27488/events | https://github.com/pandas-dev/pandas/pull/27488 | 470,630,211 | MDExOlB1bGxSZXF1ZXN0Mjk5NTMzNzI3 | 27,488 | API: Add entrypoint for plotting | {
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xref #26747
cc @datapythonista @jakevdp @philippjfr | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27489 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27489/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27489/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27489/events | https://github.com/pandas-dev/pandas/pull/27489 | 470,656,446 | MDExOlB1bGxSZXF1ZXN0Mjk5NTUxNTY0 | 27,489 | PERF: speed up IntervalIndex._intersection_non_unique by ~50x | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27490 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27490/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27490/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27490/events | https://github.com/pandas-dev/pandas/issues/27490 | 470,683,892 | MDU6SXNzdWU0NzA2ODM4OTI= | 27,490 | Timestamp unit is not respected | {
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... | open | false | null | [] | null | 2 | 2019-07-20T15:05:50Z | 2021-03-09T20:46:01Z | null | CONTRIBUTOR | null | Timestamps always get returned in nanoseconds regardless of the unit I specify:
```python
import numpy as np, pandas as pd
np.datetime64("2018-01-01").astype("datetime64[s]").astype(int)
>>> 1514764800
pd.Series(np.datetime64("2018-01-01")).astype("datetime64[s]")
```
```
0 2018-01-01
dtype: datetime64[ns]
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We are focusing all deprecation removals and we should try to release by September 2019. | {
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#27456 has been updated. closing as duplicate. | {
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- [X] closes #27329
- [ ] tests added / passed
- [X] whatsnew entry
- [ ] double check performance impact and update docs accordingly if needed. | {
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This PR significantly speeds up this ch... | {
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Similar issue as #24198 in pandas 0.25.0
```python
import pandas as pd
df = pd.DataFrame({'time': [pd.Timestamp('2010-07-15 03:14:45'),
pd.Timestamp('2010-11-19 18:47:06')],
'timezone': ['Etc/GMT+4', 'US/Ea... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27497 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27497/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27497/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27497/events | https://github.com/pandas-dev/pandas/issues/27497 | 470,730,443 | MDU6SXNzdWU0NzA3MzA0NDM= | 27,497 | Nanosecond resolution in time indexing | {
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For equivalent Timestamp indices, `0.25.0` returns an empty Series, while `0.24.2` returns one value.
```python
print(start)
Timestamp('2019-06-24 16:56:11.200999936')
print(stop)
Timestamp('20... | {
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"followers_url": "https://api.github.com/users/jre... | 0 | 2019-07-21T02:09:24Z | 2020-10-27T12:51:13Z | 2020-10-27T12:51:13Z | CONTRIBUTOR | null | Follow up for #27495, where we handle the common case of `MultiIndex` being created from helper functions that ensure the levels are sorted. In order to handle the case of `MultiIndex(codes=..., labels=...)` and labels being individually unsorted, we likely need to re-encode that level. If that is performant, it would ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27499 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27499/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27499/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27499/events | https://github.com/pandas-dev/pandas/pull/27499 | 470,740,065 | MDExOlB1bGxSZXF1ZXN0Mjk5NjA4MzI4 | 27,499 | REF: de-privatize dtypes.concat functions | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27500 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27500/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27500/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27500/events | https://github.com/pandas-dev/pandas/issues/27500 | 470,759,731 | MDU6SXNzdWU0NzA3NTk3MzE= | 27,500 | crosstabs doesn't work with margin and normalize together | {
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"followers_url": "https://api.github.... | 2 | 2019-07-21T09:05:28Z | 2019-08-06T15:45:31Z | 2019-08-06T15:45:31Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```python
import pandas as pd
df = pd.DataFrame({"A": ["foo", "foo", "foo", "foo", "foo",
"bar", "bar", "bar", "bar"],
"B": ["one", "one", "one", "two", "two",
"one", "one", "two", "two"],
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27501 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27501/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27501/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27501/events | https://github.com/pandas-dev/pandas/issues/27501 | 470,763,287 | MDU6SXNzdWU0NzA3NjMyODc= | 27,501 | pd.to_csv gives '__init__() got an unexpected keyword argument 'tupleize_cols'` | {
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] | closed | false | null | [] | null | 4 | 2019-07-21T09:50:24Z | 2019-08-21T15:53:02Z | 2019-07-21T16:15:02Z | NONE | null | Hi, I have an issue which might be related to this:
I'm running the following basic code:
<code>`dfMain.to_csv('./January_filtered_International_WE.csv')` </code>
which used to run normally until yesterday. Yesterday morning I upgraded to `pandas 0.25.0` while running code and now I cannot write a 500k rows (... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27502 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27502/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27502/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27502/events | https://github.com/pandas-dev/pandas/issues/27502 | 470,781,354 | MDU6SXNzdWU0NzA3ODEzNTQ= | 27,502 | MultiIndex with Period level is really slow | {
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In this benchmark, I construct a the multiindexes and single index referred to above by making a date/period range, and adding it to a sin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27504 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27504/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27504/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27504/events | https://github.com/pandas-dev/pandas/pull/27504 | 470,795,862 | MDExOlB1bGxSZXF1ZXN0Mjk5NjQ1OTk4 | 27,504 | ENH: Add Series.set_index | {
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] | closed | false | null | [] | null | 4 | 2019-07-21T15:47:56Z | 2019-08-02T14:44:05Z | 2019-07-31T14:16:13Z | NONE | null | - [X] closes #27058, #21684
- [X] whatsnew entry
- [x] append and list of levels (like `DataFrame.set_index` has)
- [ ] tests added / passed
Help users method-chain all the things. This is modeled closely on the original support for Arrays added in 2011 by Wes Mckinney in
553bacc7abe341991e4d043a5c17521902c... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27505 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27505/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27505/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27505/events | https://github.com/pandas-dev/pandas/pull/27505 | 470,796,856 | MDExOlB1bGxSZXF1ZXN0Mjk5NjQ2NjUw | 27,505 | Update issue template | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27506 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27506/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27506/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27506/events | https://github.com/pandas-dev/pandas/issues/27506 | 470,800,423 | MDU6SXNzdWU0NzA4MDA0MjM= | 27,506 | ensure_int_or_float Surprising Behavior with Int64 / ExtensionArrays | {
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```python
>>> import pandas as pd
>>> from pandas.core.dtypes.common import ensure_int_or_float
>>> ensure_int_or_float(pd.Series(range(3), dtype='Int64'))
0 0
1 1
2 2
dtype: int64
# Directly against PandasArray now
>>> ensure_int_or_float(pd.Series(range(3), dtype='... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27507 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27507/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27507/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27507/events | https://github.com/pandas-dev/pandas/pull/27507 | 470,809,388 | MDExOlB1bGxSZXF1ZXN0Mjk5NjU1MTU3 | 27,507 | remove last references to v0.18 in docs and code | {
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Somehow all the changes didn't get added to #27463, so here's a follow-up.
I've also removed a reference to 0.17 in style.ipynb which also makes the styler api non-provisional. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27508 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27508/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27508/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27508/events | https://github.com/pandas-dev/pandas/pull/27508 | 470,811,698 | MDExOlB1bGxSZXF1ZXN0Mjk5NjU2NDYz | 27,508 | remove references to v0.19 in docs and code | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27509 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27509/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27509/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27509/events | https://github.com/pandas-dev/pandas/issues/27509 | 470,812,918 | MDU6SXNzdWU0NzA4MTI5MTg= | 27,509 | Add 'nice' date-time x-axis labels for non-regular time series plots | {
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... | open | false | null | [] | null | 1 | 2019-07-21T18:55:32Z | 2021-07-10T18:39:22Z | null | CONTRIBUTOR | null | #### Code Sample, a copy-pastable example if possible
```python
import pandas as pd
import numpy as np
df1 = pd.DataFrame({'a':np.arange(5)},
index=pd.DatetimeIndex(['2019-07-01 12:00:00',
'2019-07-01 17:00:00',
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https://api.github.com/repos/pandas-dev/pandas/issues/27510 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27510/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27510/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27510/events | https://github.com/pandas-dev/pandas/pull/27510 | 470,824,285 | MDExOlB1bGxSZXF1ZXN0Mjk5NjY0ODgx | 27,510 | BUG: Retain tz transformation in groupby.transform | {
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- [x] tests added / passed
- [x] passes `black pandas`
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https://api.github.com/repos/pandas-dev/pandas/issues/27511 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27511/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27511/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27511/events | https://github.com/pandas-dev/pandas/pull/27511 | 470,848,009 | MDExOlB1bGxSZXF1ZXN0Mjk5NjgyMDAw | 27,511 | BUG: display.precision of negative complex numbers | {
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https://api.github.com/repos/pandas-dev/pandas/issues/27512 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/27512/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/27512/comments | https://api.github.com/repos/pandas-dev/pandas/issues/27512/events | https://github.com/pandas-dev/pandas/pull/27512 | 470,848,532 | MDExOlB1bGxSZXF1ZXN0Mjk5NjgyMzkx | 27,512 | more type hints for io/formats/format.py | {
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