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https://api.github.com/repos/pandas-dev/pandas/issues/13908 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13908/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13908/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13908/events | https://github.com/pandas-dev/pandas/issues/13908 | 169,433,348 | MDU6SXNzdWUxNjk0MzMzNDg= | 13,908 | BUG: DatetimeIndex indexing fails at nanosecond precision if timezone is used | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2016-08-04T17:46:26Z | 2017-06-29T14:50:22Z | 2016-08-04T20:30:19Z | CONTRIBUTOR | null | `DatetimeIndex` fails to find its own values if a timezone is used:
```
index = pd.DatetimeIndex(['2016-06-28 08:30:00.123456789'], dtype='datetime64[ns, America/Chicago]')
df = pd.DataFrame({'a':[10]}, index=index)
df.loc[df.index[0]]
```
It fails with:
```
*** KeyError: 'the label [2016-06-28 08:30:00.123456789-05... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13909 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13909/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13909/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13909/events | https://github.com/pandas-dev/pandas/pull/13909 | 169,456,362 | MDExOlB1bGxSZXF1ZXN0ODAxMzcwODk= | 13,909 | BUG: pd.to_datetime doesn't raises AttributeError with specific input… | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-08-04T19:38:56Z | 2016-08-05T19:52:09Z | 2016-08-05T19:52:05Z | CONTRIBUTOR | null | - [x] closes #12424
- [x] tests added / passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
…s when errors='ignore'(#12424)
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https://api.github.com/repos/pandas-dev/pandas/issues/13910 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13910/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13910/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13910/events | https://github.com/pandas-dev/pandas/issues/13910 | 169,488,064 | MDU6SXNzdWUxNjk0ODgwNjQ= | 13,910 | Type inferencing makes assignment of datetime to an object Series non-idempotent | {
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... | 7 | 2016-08-04T22:27:45Z | 2019-11-02T18:22:16Z | 2019-11-02T18:09:16Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```
>>> import pandas as pd
>>> s = pd.Series()
>>> ts = pd.Timestamp('2016-01-01')
>>> s['a'] = None
>>> s['b'] = ts
>>> s
a None
b 1451606400000000000
dtype: object
```
OK, no worries, we got coerced to integer. Now let's just ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13911 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13911/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13911/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13911/events | https://github.com/pandas-dev/pandas/pull/13911 | 169,494,195 | MDExOlB1bGxSZXF1ZXN0ODAxNjQ0OTM= | 13,911 | BUG: na_rep given precedence in to_html | {
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"followers_url": "https://api.github.com/users/jorisva... | 10 | 2016-08-04T23:06:54Z | 2017-02-27T21:05:28Z | 2017-02-27T16:00:58Z | CONTRIBUTOR | null | - [x] closes #13828
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
~~I know new tests are appreciated from the get-go, but it's the end of the day for me. I'll add new tests and the appropriate whatsnew entry tomorrow.~~
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https://api.github.com/repos/pandas-dev/pandas/issues/13912 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13912/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13912/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13912/events | https://github.com/pandas-dev/pandas/issues/13912 | 169,500,572 | MDU6SXNzdWUxNjk1MDA1NzI= | 13,912 | BUG: Columns used in sum on 1 row dataframe depend on values instead of dtype | {
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"followers_url": "https://api.github.com/users/j... | 3 | 2016-08-04T23:55:20Z | 2021-05-17T15:17:30Z | 2021-05-17T15:17:30Z | CONTRIBUTOR | null | It seems that somehow the columns used in `sum` when applied to a 1 row dataframe depend on the values in the row instead of just the dtypes. Observe:
``` python
import pandas as pd
import numpy as np
# Frame with some non-numeric dtypes
df = pd.DataFrame({'a': [1], 'b': [1.1], 'c': ['foo'], 'd': [pd.Timestamp('2000-... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13913 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13913/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13913/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13913/events | https://github.com/pandas-dev/pandas/issues/13913 | 169,502,070 | MDU6SXNzdWUxNjk1MDIwNzA= | 13,913 | Groupby apply using a custom function displays incorrect arguments (DF) | {
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"followers_url": "https://api.github.com/users/jorisva... | 8 | 2016-08-05T00:07:55Z | 2016-08-05T17:57:07Z | 2016-08-05T00:12:24Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```
def func3(df):
print(df)
df['Mean'] = np.mean(df['Data'].values)
out = df[['Mean', 'Group']].iloc[0, :].copy(deep=True)
return out
var1 = [1, 2, 3]
grp_var = ['Group1', 'Group2', 'Group2']
df_test = pd.DataFrame.from_dict({'Data': var1, 'Group'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13914 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13914/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13914/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13914/events | https://github.com/pandas-dev/pandas/issues/13914 | 169,525,335 | MDU6SXNzdWUxNjk1MjUzMzU= | 13,914 | BUG: resampling a MultiIndex and specified keys are tuples in .agg | {
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... | 5 | 2016-08-05T04:16:31Z | 2021-05-01T23:04:46Z | null | NONE | null | #### Code Sample, a copy-pastable example if possible
You can reproduce the error by pasting this chunk of code, but this error is ONLY with pandas 0.18.0 or higher. This chunk of code worked fine under 0.17.1 and earlier, and is related to the change in how resampling is done.
The error I get is "TypeError: othe... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13915 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13915/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13915/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13915/events | https://github.com/pandas-dev/pandas/pull/13915 | 169,551,225 | MDExOlB1bGxSZXF1ZXN0ODAyMDQyMTc= | 13,915 | DOC: Add missing word in docstring | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13916 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13916/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13916/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13916/events | https://github.com/pandas-dev/pandas/issues/13916 | 169,554,181 | MDU6SXNzdWUxNjk1NTQxODE= | 13,916 | sum in pandas can concatenate strings | {
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"followers_url": "https://api.github.com/users/jreback/followers",... | 1 | 2016-08-05T08:21:10Z | 2021-11-13T17:32:15Z | null | MEMBER | null | Possibly related: #13912
This looks wrong to me -- probably a bug?
```
In [36]: pd.Series(['a', 'b', 'c']).sum()
Out[36]: 'abc'
In [37]: pd.__version__
Out[37]: '0.18.1'
```
This happens on DataFrames, as well:
```
In [8]: pd.Series(['a', 'b', 'c']).to_frame().sum()
Out[8]:
0 abc
dtype: object
```
Note, of cou... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13917 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13917/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13917/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13917/events | https://github.com/pandas-dev/pandas/pull/13917 | 169,596,477 | MDExOlB1bGxSZXF1ZXN0ODAyMzUzNzE= | 13,917 | BUG: multi-type SparseDataFrame fixes and improvements | {
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"followers_url": "https://api.github.com/users/jr... | 13 | 2016-08-05T12:28:58Z | 2016-08-10T10:42:54Z | 2016-08-10T10:38:24Z | CONTRIBUTOR | null | - [X] 1 tests added / passed
- [X] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Types were incorrectly determined when slicing SparseDataFrames with
multiple dtypes (such as float and object) into SparseSeries.
``` python
import pandas as pd
sdf = pd.SparseDataFrame([[1, 2, 'a'], [4, 5, 'b']... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13918 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13918/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13918/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13918/events | https://github.com/pandas-dev/pandas/issues/13918 | 169,603,209 | MDU6SXNzdWUxNjk2MDMyMDk= | 13,918 | Pandas.items in Python2 vs Python3 | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2016-08-05T13:07:22Z | 2017-08-19T21:59:20Z | 2017-08-19T21:59:20Z | CONTRIBUTOR | null | Inconsistency between python2 and 3 - python2 has no `items` method (but does have `iteritems`). Shouldn't `items` and `iteritems` be the same?
#### Code Sample, a copy-pastable example if possible
```
import pandas as pd
import string
ser = pd.Series(np.arange(10), index=list(string.ascii_letters[:10]))
print(ser.it... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13919 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13919/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13919/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13919/events | https://github.com/pandas-dev/pandas/issues/13919 | 169,603,829 | MDU6SXNzdWUxNjk2MDM4Mjk= | 13,919 | ERR: Categoricals should not allow non-strings when an object dtype is passed | {
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... | 11 | 2016-08-05T13:11:06Z | 2020-05-16T20:31:21Z | null | CONTRIBUTOR | null | HDF Store (with `table`) doesn't support categories with mixed type inside a category
Even though it is possible to store category type using `to_hdf` with `table`, you can't do that when you have mixed types inside the category. It would be nice to mention this at least on docs.
#### Code Sample, a copy-pastable exa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13920 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13920/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13920/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13920/events | https://github.com/pandas-dev/pandas/pull/13920 | 169,639,053 | MDExOlB1bGxSZXF1ZXN0ODAyNjYxNjA= | 13,920 | removed compat check for Series.items method | {
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I couldn't find a relevant test, so this is to check if this breaks any tests in CI.
- [x] closes #13918
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/13921 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13921/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13921/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13921/events | https://github.com/pandas-dev/pandas/issues/13921 | 169,682,549 | MDU6SXNzdWUxNjk2ODI1NDk= | 13,921 | Split-out Cython modules from algos.pyx | {
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With the impending addition of `joins_func_helper.pxi.in`, does it make sense to split Cython modules so that `algos.pyx` isn't so massive?
CC @sinhrks
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https://api.github.com/repos/pandas-dev/pandas/issues/13922 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13922/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13922/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13922/events | https://github.com/pandas-dev/pandas/issues/13922 | 169,755,042 | MDU6SXNzdWUxNjk3NTUwNDI= | 13,922 | memory leak in reindex | {
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] | closed | false | null | [] | null | 3 | 2016-08-06T16:44:28Z | 2016-08-06T18:06:27Z | 2016-08-06T18:06:12Z | CONTRIBUTOR | null | When I reindex, I see memory usage permanently go up.
Path I traced was from pd.DataFrame.assign -> pd.Series.reindex -> pd.Index.reindex
Not sure what the ultimate source of the issue is
``` python
import psutil
import pandas as pd
K = 10
N = 1000 * 1000
for i in range(K):
# any of these will cause the issue... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13923 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13923/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13923/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13923/events | https://github.com/pandas-dev/pandas/issues/13923 | 169,757,142 | MDU6SXNzdWUxNjk3NTcxNDI= | 13,923 | Stata read categoricals gives ValueError: Categorical categories must be unique | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13924 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13924/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13924/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13924/events | https://github.com/pandas-dev/pandas/pull/13924 | 169,762,854 | MDExOlB1bGxSZXF1ZXN0ODAzNDg3MTQ= | 13,924 | CLN/PERF: remove ndarray.take and platform int conversions | {
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- a couple python `any` calls
- unnecessary (?) platform int checks / conversions. I'm testing on Windows - I'm assuming on
Linux 64 this doesn't really make a difference.
``` python
In [1]: right = pd.DataFrame({'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13925 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13925/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13925/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13925/events | https://github.com/pandas-dev/pandas/pull/13925 | 169,763,515 | MDExOlB1bGxSZXF1ZXN0ODAzNDkwNDE= | 13,925 | BLD: split join.pyx from algos.pyx | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-08-06T19:48:36Z | 2016-08-06T21:44:17Z | 2016-08-06T21:44:17Z | CONTRIBUTOR | null | closes #13921
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https://api.github.com/repos/pandas-dev/pandas/issues/13926 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13926/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13926/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13926/events | https://github.com/pandas-dev/pandas/pull/13926 | 169,765,537 | MDExOlB1bGxSZXF1ZXN0ODAzNTAyMDI= | 13,926 | BUG: DatetimeTz shift raises AmbiguousTimeError near DST | {
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- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
As the same as #13650, caused by `.tz_localize(None)` which can be removed.
```
import pandas as pd
s = pd.Series(pd.date_range('2016-11-06', freq='H', periods=10, tz='US/Eastern'))
s.shift(1)
# pytz.exceptions.Amb... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13927 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13927/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13927/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13927/events | https://github.com/pandas-dev/pandas/pull/13927 | 169,774,255 | MDExOlB1bGxSZXF1ZXN0ODAzNTUyMzU= | 13,927 | COMPAT/TST: windows sparse int comparisons | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13928 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13928/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13928/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13928/events | https://github.com/pandas-dev/pandas/issues/13928 | 169,799,687 | MDU6SXNzdWUxNjk3OTk2ODc= | 13,928 | CI: re-enable 3.4 build / updated conda-build on appeveyor | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2016-08-07T14:48:37Z | 2017-01-20T13:56:41Z | 2017-01-19T18:00:21Z | CONTRIBUTOR | null | [fix conda-build version](https://github.com/pydata/pandas/commit/cfbb24f2c0e33ee221c54fd4944458cb0c6f4e84)
Builds are consecutive, 1 at a time.
[disable 3.4 build](https://github.com/pydata/pandas/commit/7e15923d908a42008fb7fecde58be626277fd82e)
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https://api.github.com/repos/pandas-dev/pandas/issues/13929 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13929/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13929/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13929/events | https://github.com/pandas-dev/pandas/issues/13929 | 169,820,074 | MDU6SXNzdWUxNjk4MjAwNzQ= | 13,929 | Possible bug when parsing from string to datetime when slicing | {
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... | 6 | 2016-08-07T22:40:11Z | 2020-03-31T05:54:57Z | null | NONE | null | From [this question in SO](http://stackoverflow.com/questions/38774044/unexpected-behavior-in-pandas-timestamp-slicing?noredirect=1#comment64980593_38774044)
Please consider the following example
```
data = pd.DataFrame(np.random.random((72000,3)), columns=list('uvw'),
index=pd.date_range('2013-11-08 10:0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13930 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13930/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13930/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13930/events | https://github.com/pandas-dev/pandas/pull/13930 | 169,824,003 | MDExOlB1bGxSZXF1ZXN0ODAzODIyODM= | 13,930 | BUG: freqstr may be parsed incorrectly | {
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- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Invalid freq like below doesn'traise `ValueError` properly. The PR makes all the below raise.
```
pd.tseries.frequencies.to_offset('U1')
# <Micro>
pd.tseries.frequencies.to_offset('3U1')
# <3 * Micros>
pd.tseries.f... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13931 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13931/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13931/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13931/events | https://github.com/pandas-dev/pandas/issues/13931 | 169,926,343 | MDU6SXNzdWUxNjk5MjYzNDM= | 13,931 | ERR: improved pd.Period date parsing and formatting | {
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... | 9 | 2016-08-08T13:43:02Z | 2020-05-11T02:12:08Z | null | NONE | null | It seems that pandas.Period has a few bugs w.r.t. date parsing and formatting, or at least poorly documented behavior.
- The documentation makes no mention of the possible range of dates/years.
- Formatting of years in strftime using the %Y format seems inconsistent.
- Parsing of what is commonly assumed to be ISO-8601... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13932 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13932/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13932/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13932/events | https://github.com/pandas-dev/pandas/issues/13932 | 169,926,357 | MDU6SXNzdWUxNjk5MjYzNTc= | 13,932 | CLN: resource warnings | {
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so we have warnings enabled on the 3.5/dev build. Lots of resource warnings....
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https://api.github.com/repos/pandas-dev/pandas/issues/13933 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13933/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13933/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13933/events | https://github.com/pandas-dev/pandas/issues/13933 | 169,931,677 | MDU6SXNzdWUxNjk5MzE2Nzc= | 13,933 | BUG: loffset isn't applied when using resample() with a TimedeltaIndex | {
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```
In [3]: from pandas import *
In [4]: rng = timedelta_range(start='0s', periods=10, freq='s')
In [5]: df = DataFrame({'A' : range(10)}, index=rng)
In [6]: df.resample('2S', loffset='2h').count()
Out[6]:
A
00:00:00 2
00:00:02 2
00:00:04 2
00:00:06 ... | {
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``` python
import pandas
df = pandas.DataFrame()
df['a'] = [1,2,3]
a = df.a
df.drop(['a'], axis=1, inplace=True)
print df.columns
a -= a.mean()
print df.columns
```
#### Current Output
``` python
Index([], dtype='object')
Index([u'a'], dtype='object')
```
####... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13935 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13935/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13935/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13935/events | https://github.com/pandas-dev/pandas/pull/13935 | 169,951,278 | MDExOlB1bGxSZXF1ZXN0ODA0NzA4NjM= | 13,935 | BUG: Right result for DatetimeIndex + TimeDelta when timezone is set(… | {
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... | closed | false | null | [] | null | 8 | 2016-08-08T15:27:52Z | 2016-12-30T23:13:50Z | 2016-12-30T21:46:00Z | CONTRIBUTOR | null | - [x] closes #13905
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
…#13905)
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https://api.github.com/repos/pandas-dev/pandas/issues/13937 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13937/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13937/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13937/events | https://github.com/pandas-dev/pandas/issues/13937 | 169,955,586 | MDU6SXNzdWUxNjk5NTU1ODY= | 13,937 | BUG: DataFrame.to_records() bug in converting datetime64 index with timezone | {
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in to_records(), use pandas.core.common.is_datetime64_any_dtype instead of pandas.core.common.is_datetime64_dtype to check to see if the index is in fact of the datetime64 type.
#### Code Sample, a copy-pastable example if possible
```
import datetime
import pandas as pd
import pytz
data = [datetime.datetim... | {
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- [ ] tests added / passed (doc only), but builds on my machine
- passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry (doc only)
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Can it be added?
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https://api.github.com/repos/pandas-dev/pandas/issues/13940 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13940/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13940/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13940/events | https://github.com/pandas-dev/pandas/pull/13940 | 170,032,620 | MDExOlB1bGxSZXF1ZXN0ODA1MjcyMDg= | 13,940 | BUG: properly close files opened by parsers | {
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- [x] tests passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Addresses all ~~most~~ of the `ResourceWarning`s from #13932. There were three tests that opened files but did not close them. The rest were due to parsers (`CParserWrapper` and `PythonParser`) opening ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13941 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13941/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13941/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13941/events | https://github.com/pandas-dev/pandas/pull/13941 | 170,038,463 | MDExOlB1bGxSZXF1ZXN0ODA1MzEzMjg= | 13,941 | ENH: PeriodIndex now has period dtype | {
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- [x] tests added / passed
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splitted `dtype` related part from #13755, to clarify the differences related to `PeriodIndex`
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
Because sparse `IntIndex` and `BlockIndex` store value locations as `int32`, its size / block numbers can't exceed `int32` also.
warnings has been disappeared in appveyor.
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https://api.github.com/repos/pandas-dev/pandas/issues/13943 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13943/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13943/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13943/events | https://github.com/pandas-dev/pandas/pull/13943 | 170,063,873 | MDExOlB1bGxSZXF1ZXN0ODA1NDkzODE= | 13,943 | TST: Removed regex warning for read_csv | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13944 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13944/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13944/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13944/events | https://github.com/pandas-dev/pandas/pull/13944 | 170,071,871 | MDExOlB1bGxSZXF1ZXN0ODA1NTQ5Mjc= | 13,944 | DOC: Design drafts to assist with next-gen pandas internals discussion | {
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... | 23 | 2016-08-09T03:07:06Z | 2016-08-24T03:45:31Z | 2016-08-24T03:45:31Z | MEMBER | null | Sprinted on my accumulated design ideas. There's more to do, but I'm going to take a break for a bit.
I published this as a sphinx site temporarily to https://wesm.github.io/pandas2-design/ so it's easier to read. This needs to be a team effort, so depending on where the discussions go perhaps we can build a set of d... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13945 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13945/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13945/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13945/events | https://github.com/pandas-dev/pandas/issues/13945 | 170,086,247 | MDU6SXNzdWUxNzAwODYyNDc= | 13,945 | Msgpack roundtrips python 3 strings to bytes | {
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#### Code Sample, a copy-pastable example if possible
``` Python
import pandas as pd
pd.msgpack.unpackb(pd.msgpack.packb("a"))
```
#### Expected Output
```
"a"
```
instead, we get
```
b"a"
```
#### out... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13946 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13946/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13946/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13946/events | https://github.com/pandas-dev/pandas/issues/13946 | 170,135,250 | MDU6SXNzdWUxNzAxMzUyNTA= | 13,946 | pd.read_clipboard in Jupyter makes python 3.5 crash on windows | {
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] | closed | false | null | [] | null | 10 | 2016-08-09T10:40:27Z | 2016-11-15T01:21:57Z | 2016-08-09T11:10:32Z | CONTRIBUTOR | null | Disclaimer: I'm not quite sure if the problem is really on pandas' side or on jupyter's.
I have seen #4561 but this isn't the same problem.
#### Code Sample, a copy-pastable example if possible
Given the following code:
```
import pandas as pd
pd.read_clipboard()
```
If I use it in a python file, it works fine.
If... | {
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1. `pandas/types/common.py:_lcd_dtypes`, which works on `numpy` dtypes only, but differently than `np.find_common_type`.
2. `pandas... | {
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... | 7 | 2016-08-09T13:52:38Z | 2021-07-08T19:22:40Z | null | NONE | null | Unfortunately, I need to work with files containing both `#comments` and `!warnings` aside of useful numbers. Thus, it would be very convenient to load them (in pandas 0.17.1) using
`df = pd.read_csv(inputfile, comment='#!')`
however, this command now allows one comment-identifying character at most, so I need to par... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13949 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13949/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13949/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13949/events | https://github.com/pandas-dev/pandas/pull/13949 | 170,172,555 | MDExOlB1bGxSZXF1ZXN0ODA2MjQ2OTA= | 13,949 | ENH: Improve error message for repeated Stata categories | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-08-09T13:55:44Z | 2016-08-10T22:37:58Z | 2016-08-10T22:37:45Z | CONTRIBUTOR | null | - [x] closes #13923
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Improve the error message to be more explicit when attempting to read Stata
files containing repeated categories.
closes #13923
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... | 2 | 2016-08-09T14:05:39Z | 2021-08-23T04:03:20Z | null | CONTRIBUTOR | null | Hi,
I'm not sure this is a bug but the behaviour is far from intuitive. I'm trying to assign the values of a slice of a `DataFrame` into another slice (of same size) of the same `DataFrame`.
```
In [1]: import pandas as pd
In [2]: import numpy as np
In [3]: a = pd.DataFrame({"a": [1, 2, 3, 4, 5], "b": [6, 7, 8, 9, 10... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13951 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13951/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13951/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13951/events | https://github.com/pandas-dev/pandas/pull/13951 | 170,218,948 | MDExOlB1bGxSZXF1ZXN0ODA2NTc0MTI= | 13,951 | DOC: NDFrame.to_hdf(data_columns) documented (#13061). | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-08-09T17:03:01Z | 2016-08-19T10:50:01Z | 2016-08-19T10:49:54Z | CONTRIBUTOR | null | - [x] closes #13061
- [ ] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
I'm aware there's another PR for the same issue, but it hasn't had activity in a while so this is my attempt. I took the opportunity to remove the unusable "mode=r" option from the same docstrin... | {
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`pd.DataFrame([[np.NaN, np.NaN], [np.NaN, np.NaN]]).sum(skipna=True)`
is:
```
0 0.0
1 0.0
dtype: float64
```
What in my opinion contradicts what is written in documentation (and what by the way is more intuitve outcome):
> Exclude NA/null values. If an entire row/column is NA, the result will ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13955 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13955/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13955/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13955/events | https://github.com/pandas-dev/pandas/pull/13955 | 170,394,225 | MDExOlB1bGxSZXF1ZXN0ODA3Nzc0OTg= | 13,955 | CLN: Period cleanup related to array like meth | {
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- [x] passes `git diff upstream/master | flake8 --diff`
removed unused / duplicated internal method returning array-likes. Also added some tests to guarantee existing API before fixing its dtype (see #13941).
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#### Code Sample, a copy-pastable example if possible
``` python
df = pd.DataFrame({'a': [1, 2, 3], 'b': ['notset... | {
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```
Xeps = np.dot(m.T, m)
for lag in range(1, max_lags + 1):
auto_cov = np.dot(m[... | {
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... | 7 | 2016-08-10T20:54:04Z | 2021-05-01T23:13:47Z | null | CONTRIBUTOR | null | I would like a time-based aggregating function that also acts as a join:
http://code.kx.com/wiki/Reference/wj
In pandas, this might look something like:
```
ms = pd.Timedelta(1, 'ms')
merge_window(df1, df2, on='time', by='ticker', time_range=(-100*ms, 100*ms), how=(np.sum, 'volume'))
```
This would compute the tota... | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2016-08-10T23:58:16Z | 2016-08-11T10:13:53Z | 2016-08-11T10:13:49Z | CONTRIBUTOR | null | This change makes it so that if a `.pxi.in` file is modified, the appropriate module will be rebuilt.
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https://api.github.com/repos/pandas-dev/pandas/issues/13961 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13961/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13961/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13961/events | https://github.com/pandas-dev/pandas/pull/13961 | 170,551,258 | MDExOlB1bGxSZXF1ZXN0ODA4OTE1NjE= | 13,961 | API: Expanded resample | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
My only question here is if `on=` is the keyword name for picking a column - in a `TimeGrouper` that's called `key`. But `on` is what was used in the rolling selection (and elsewhere) so seems c... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13962 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13962/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13962/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13962/events | https://github.com/pandas-dev/pandas/issues/13962 | 170,616,560 | MDU6SXNzdWUxNzA2MTY1NjA= | 13,962 | TST: fail test suite on ResourceWarnings | {
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should just require a setting in
`pandas.util.testing.TestCase.setUpClass` to set when the suite is running.
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https://api.github.com/repos/pandas-dev/pandas/issues/13963 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13963/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13963/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13963/events | https://github.com/pandas-dev/pandas/issues/13963 | 170,646,492 | MDU6SXNzdWUxNzA2NDY0OTI= | 13,963 | Feature request: pandas.DataFrame.setdefault() | {
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] | open | false | null | [] | null | 5 | 2016-08-11T13:32:10Z | 2021-05-01T23:14:10Z | null | NONE | null | We often find ourselves checking for column existence before assigning a value to it, e.g.:
``` python
df = pd.DataFrame()
col = 'ColumnA'
val = 'Value1'
if col not in df.columns:
df[col] = val
```
And we were thinking it would be nice if there was a way to tell pandas: add this column with that value(s) but only... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13964 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13964/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13964/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13964/events | https://github.com/pandas-dev/pandas/issues/13964 | 170,663,726 | MDU6SXNzdWUxNzA2NjM3MjY= | 13,964 | Pandas 0.18.1 groupby and resample with multilevel aggregation error | {
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... | 4 | 2016-08-11T14:45:51Z | 2020-01-20T07:34:12Z | 2020-01-20T07:34:11Z | NONE | null | Initially posted here: http://stackoverflow.com/questions/38861244/pandas-0-18-1-groupby-and-resample-with-multilevel-aggregation-error
From the documentation at the below links, both df3_resample and df4_resample should return the same dataframe, however df4_resample throws an exception.
http://pandas.pydata.org/pa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13965 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13965/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13965/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13965/events | https://github.com/pandas-dev/pandas/issues/13965 | 170,679,944 | MDU6SXNzdWUxNzA2Nzk5NDQ= | 13,965 | Exact matches in time-based .rolling() | {
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"followers_url": "https://api.github.com/users/jr... | 9 | 2016-08-11T15:50:49Z | 2017-04-13T11:39:15Z | 2017-04-13T11:39:14Z | CONTRIBUTOR | null | I would like to `allow_exact_matches` in time-based `.rolling()`. Using an example similar to the one found in the documentation:
```
df = pd.DataFrame({'B': [1, 1, 2, np.nan, 4]},
index = [pd.Timestamp('20130101 09:00:00'),
pd.Timestamp('20130101 09:00:02'),
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13966 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13966/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13966/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13966/events | https://github.com/pandas-dev/pandas/issues/13966 | 170,700,095 | MDU6SXNzdWUxNzA3MDAwOTU= | 13,966 | Time-based .rolling() fails with .groupby() | {
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"followers_url": "https://api.github.com/users/jr... | 19 | 2016-08-11T17:26:11Z | 2021-02-08T20:53:19Z | 2017-04-22T01:28:28Z | CONTRIBUTOR | null | Starting with [this example](http://pandas.pydata.org/pandas-docs/version/0.18.1/whatsnew.html#groupby-syntax-with-window-and-resample-operations):
```
df = pd.DataFrame({'A': [1] * 20 + [2] * 12 + [3] * 8,
'B': np.arange(40)})
```
I can easily compute the rolling mean by identifier:
```
In [20]: ... | {
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#### read_csv() documentation shows the following for na_values
na_values : str or list-like or dict, default None
Ad... | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
TODO: update docs.
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https://api.github.com/repos/pandas-dev/pandas/issues/13969 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13969/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13969/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13969/events | https://github.com/pandas-dev/pandas/issues/13969 | 170,730,455 | MDU6SXNzdWUxNzA3MzA0NTU= | 13,969 | Handling a CustomBusinessDay in time-based .rolling() | {
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... | 6 | 2016-08-11T19:49:40Z | 2020-10-05T00:19:16Z | 2020-10-05T00:19:15Z | CONTRIBUTOR | null | Starting with 10 business days following Christmas Eve:
```
from pandas.tseries.offsets import CustomBusinessDay
from pandas.tseries.holiday import USFederalHolidayCalendar
days = CustomBusinessDay(calendar=USFederalHolidayCalendar())
df = pd.DataFrame({'value': np.arange(n)},
index=pd.date_range('... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13970 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13970/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13970/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13970/events | https://github.com/pandas-dev/pandas/pull/13970 | 170,751,263 | MDExOlB1bGxSZXF1ZXN0ODEwMzM5MTE= | 13,970 | BUG/DEPR: combine dtype fixes | {
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- [x] closes #13947 (`_find_common_type` to support extension types)
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
- `_find_common_type` also needs to handle numpy datetimelike to be compat with panda... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13971 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13971/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13971/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13971/events | https://github.com/pandas-dev/pandas/issues/13971 | 170,757,802 | MDU6SXNzdWUxNzA3NTc4MDI= | 13,971 | BUG: unstack(fill_value) does nothing when unstacking multiple columns | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-08-11T22:00:56Z | 2017-10-16T14:25:24Z | 2017-10-16T14:25:24Z | CONTRIBUTOR | null | In #9746 we got a `fill_value` argument for `pd.unstack()`. But it does nothing if we unstack multiple levels at once:
```
df = pd.DataFrame({'x':['a', 'a', 'b'], 'y':['j', 'k', 'j'], 'z':[0, 1, 2], 'w':[0, 1, 2]})
df.set_index(['x', 'y', 'z']).unstack(['x', 'y'], fill_value=0)
```
That gives:
```
w
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https://api.github.com/repos/pandas-dev/pandas/issues/13972 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13972/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13972/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13972/events | https://github.com/pandas-dev/pandas/pull/13972 | 170,778,117 | MDExOlB1bGxSZXF1ZXN0ODEwNTM2Mjg= | 13,972 | PERF/COMPAT: define platform int to np.intp | {
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`numpy` wants an `np.intp` (i8 on Windows) as a indexer for `take`, but pandas defines a "platform int" as a `np.int_` (i4 on Windows). This hits performance twice, because we often start with i8, cast to i4, then numpy will cast back to i8 in its `take`.
This is an ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13973 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13973/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13973/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13973/events | https://github.com/pandas-dev/pandas/issues/13973 | 170,798,180 | MDU6SXNzdWUxNzA3OTgxODA= | 13,973 | df.sort_values by 2 columns does not work in py3.5.1 but work in py2? | {
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The code above works in py2 but not works in py3.
#### Expected Output
should get sorted dataframe.
#### output of `pd.show_versions()`
0.18.0
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2016-08-12T09:45:24Z | 2016-08-12T13:54:44Z | 2016-08-12T12:01:10Z | NONE | null | I'm honestly not sure if that is to be expected or if it's a general issue. It is a problem when doing row comparisons that can't be done with existing row-wise methods like diff.
#### Consider this example showing three functions doing row-wise differences on a randomly generated dataframe:
```
import pandas as pd
im... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13975 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13975/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13975/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13975/events | https://github.com/pandas-dev/pandas/pull/13975 | 170,841,172 | MDExOlB1bGxSZXF1ZXN0ODEwOTY5MjM= | 13,975 | CLN: PeriodIndex to use nan related cache | {
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- [x] passes `git diff upstream/master | flake8 --diff`
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#### Code Sample, a copy-pastable example if possible
```
from numpy import nan
import pandas as pd
from pandas import Timesta... | {
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``` py
import pandas as pd
import numpy as np
class SubclassedSeries(pd.Series):
pass
class SubclassedDataFrame(pd.DataFrame):
_constructor_sliced = SubclassedSeries
df = SubclassedDataFrame(np.random.random((3, 2))
i, row = next(df.iterrows())
asser... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13979 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13979/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13979/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13979/events | https://github.com/pandas-dev/pandas/pull/13979 | 170,986,767 | MDExOlB1bGxSZXF1ZXN0ODEyMDM0NjA= | 13,979 | API: change unique to return Index | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13980 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13980/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13980/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13980/events | https://github.com/pandas-dev/pandas/pull/13980 | 170,987,189 | MDExOlB1bGxSZXF1ZXN0ODEyMDM3MjA= | 13,980 | BUG: ufunc with PeriodIndex may raise IncompatibleFrequency | {
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`PeriodIndex` supportds addition / subtraction with integer.
```
# OK
pi = pd.PeriodIndex(['2011-01'], freq='M')
pi + 1
# PeriodIndex(['2011-02'], dtype='int64', freq='M')
pi - 1
# PeriodIndex(['2010-12'], dtype='i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13981 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13981/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13981/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13981/events | https://github.com/pandas-dev/pandas/pull/13981 | 170,988,246 | MDExOlB1bGxSZXF1ZXN0ODEyMDQzNzA= | 13,981 | BUG: Index may ignore specified datetime/timedelta dtypes | {
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`Index` ignores specified `dtype` if it is `datetime64` (normal and tz) or `timedelta64`. This PR makes it consistent with `DatetimeIndex` and `TimedeltaIndex`.
```
pd.Index([1, 2, 3], dtype='datetime64[ns, US/East... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13982 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13982/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13982/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13982/events | https://github.com/pandas-dev/pandas/pull/13982 | 170,993,099 | MDExOlB1bGxSZXF1ZXN0ODEyMDczMTA= | 13,982 | TST: Cleanup test_indexing | {
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cleaned up `test_indexing` which is bit large, splitting `@slow` tests to a separate file.
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https://api.github.com/repos/pandas-dev/pandas/issues/13983 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13983/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13983/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13983/events | https://github.com/pandas-dev/pandas/pull/13983 | 171,001,020 | MDExOlB1bGxSZXF1ZXN0ODEyMTE1Nzc= | 13,983 | CLN: Datetimelike._can_hold_na | {
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datetimelike `Index._can_hold_na` is all `False` even though these can store `NaT`.
```
idx = pd.DatetimeIndex(['2011-01-01', 'NaT'])
idx.hasnans
# True
idx._can_hold_na
# False
idx._nan_idxs
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... | 0 | 2016-08-13T09:23:29Z | 2021-05-01T23:14:34Z | null | MEMBER | null | `Series/Index.nunique` has `dropna` kw to exclude `NaN`. Add the same kw to `.unique` also.
As #13979 changes `.unique` to always return `Index`, we can replace `Index._get_unique_index(dropna)` if this option is added.
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indexing with `SparseArray` with `bool` dtype may return incorrect result because of some internal conversions.
```
arr = pd.SparseArray([1, 2, 3])
indexer = pd.SparseArray([True, False, True], fill_value=False, dt... | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/13987 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13987/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13987/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13987/events | https://github.com/pandas-dev/pandas/pull/13987 | 171,004,909 | MDExOlB1bGxSZXF1ZXN0ODEyMTM3MTI= | 13,987 | CLN: move PeriodIndex.__getitem__ to DatetimeIndexOpsMixin | {
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- [x] tests added / passed
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merge `PeriodIndex.__getitem__` to `DatetimeIndexOpsMixin`
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This change itself needs more tests / perf testing, split from the original PR.
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https://api.github.com/repos/pandas-dev/pandas/issues/13989 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13989/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13989/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13989/events | https://github.com/pandas-dev/pandas/pull/13989 | 171,008,985 | MDExOlB1bGxSZXF1ZXN0ODEyMTU4MzM= | 13,989 | DOC: suppress warnings for Panel4D deprecation | {
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The example in the HDF5 docs with a legacy file will have to be updated to not include Panel4D, or the reading of such files will have to be adapted in the future to handle those when Panel4D is actuall... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13990 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13990/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13990/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13990/events | https://github.com/pandas-dev/pandas/pull/13990 | 171,009,001 | MDExOlB1bGxSZXF1ZXN0ODEyMTU4NDI= | 13,990 | Use DeprecationWarning for core.common deprecations (GH13634) | {
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As those functions are mostly used in library code, and less directly by users in their own code, I think a DeprecationWarning is more appropriate in this case.
For example... | {
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cc @jreback @shoyer @sinhrks @TomAugspurger @wesm
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... | 2 | 2016-08-13T17:50:13Z | 2021-05-01T23:15:15Z | null | CONTRIBUTOR | null | ```
import pandas as pd
s = pd.Series(list('ABCDEF'))
grouper = pd.Series([0]*3+[1]*3)
```
The obvious attempt to obtain
```
0 A
1 AB
2 ABC
3 D
4 DE
5 DEF
dtype: object
```
using
```
s.groupby(grouper).cumsum()
```
raises a `DataError: No numeric types to aggregate`. A workaround is availa... | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2016-08-13T18:36:50Z | 2016-08-14T00:15:47Z | 2016-08-14T00:15:47Z | CONTRIBUTOR | null | #### Code sample
``` python
import pandas as pd
df = pd.DataFrame({'A': range(6), 'B': range(6)})
df.groupby('A').cumsum(axis=1)
```
#### Output
```
A B
0 0 0
1 1 1
2 2 4
3 3 9
4 4 16
5 5 25
```
#### Expected Output
```
A B
0 0 0
1 1 2
2 2 4
3 3 6
4 4 8
5 5 10
```
#### The... | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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- made `tz` related tests more comprehensive
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Because `PeriodIndex` now shares the same `NaT` repr (#13609), can use the same definition on `DatetimeIndexOpsMixin`
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_join_multiline internally which only sets the idx variable when
index is True, otherwise idx is never set resulting in the error:
UnboundLocalError: local variable 'idx' referenced before assignment
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Because #13985 has been fixed, `SparseSeries` comparison op now can return `SparseSeries` (it returns normal `Series` on current master).
also fixed a bug when `SparseArray` created from `SparseSeries` may not inh... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14000 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14000/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14000/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14000/events | https://github.com/pandas-dev/pandas/pull/14000 | 171,059,159 | MDExOlB1bGxSZXF1ZXN0ODEyNDM3NDI= | 14,000 | ENH: bool sparse now supports logical op | {
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implemented bool (logical and / or) op for bool `SparseArray`. Currently it raises if `sp_index` are different.
```
s1 = pd.SparseArray([True, True, True, True, True], dtype=np.bool, fill_value=False)
s2 = pd.Spars... | {
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Assuming we have int `DataFrame` and assign float values.
- assigning 2-d float array keeps `int` columns if possible.
```
df = pd.DataFrame(np.zeros((3, 2), dtype=np.int64))
df.iloc[0:2, 0:2] = np.array([[1, 2.1], [2, 2.2]], dtype=np.float64)
df
# 0 1
#0 1... | {
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- [ X] tests added / passed
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<img width="1016" alt="asv_tests" src="https://cloud.githubusercontent.com/assets/609873/17653246/3a3f842a-6260-11e6-8ed2-1d21cc2fccc8.png">
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https://api.github.com/repos/pandas-dev/pandas/issues/14003 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14003/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14003/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14003/events | https://github.com/pandas-dev/pandas/issues/14003 | 171,115,237 | MDU6SXNzdWUxNzExMTUyMzc= | 14,003 | DOC: doc/make.py uses IPython promptManager, which is removed from IPython 5.x | {
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] | closed | false | null | [] | null | 1 | 2016-08-15T06:25:54Z | 2016-08-18T20:50:14Z | 2016-08-18T20:50:14Z | CONTRIBUTOR | null | When I build document as described in contributing guideline below,
http://pandas-docs.github.io/pandas-docs-travis/contributing.html#building-the-documentation
it makes an error like this.
```
AttributeError: "'InteractiveShell' object has no attribute 'prompt_manager'"
```
This file uses removed class, from IPytho... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14004 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14004/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14004/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14004/events | https://github.com/pandas-dev/pandas/pull/14004 | 171,125,361 | MDExOlB1bGxSZXF1ZXN0ODEyODEyOTQ= | 14,004 | DOC: fixed using IP.prompt_manager which is removed from IPython 5.x | {
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- [ ] tests added / passed (there's no test on building docs)
- [x] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry (it's not user facing bug fix)
this PR was made during PyCon APAC, pandas sprint
thanks
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https://api.github.com/repos/pandas-dev/pandas/issues/14005 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14005/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14005/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14005/events | https://github.com/pandas-dev/pandas/pull/14005 | 171,196,525 | MDExOlB1bGxSZXF1ZXN0ODEzMjk5MTE= | 14,005 | BUG: No affect both index and column(GH 13522) | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/14006 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14006/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14006/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14006/events | https://github.com/pandas-dev/pandas/pull/14006 | 171,304,194 | MDExOlB1bGxSZXF1ZXN0ODE0MDQwMjE= | 14,006 | BUG: Avoid sentinel-infinity comparison problems (#13445) | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-08-16T01:59:10Z | 2016-08-16T10:32:47Z | 2016-08-16T10:15:30Z | CONTRIBUTOR | null | The problem causing #13445 ultimately traces to the fact that our Infinity/NegInfinity objects were greater than/less than themselves, which violates an assumption numpy makes when sorting. This was separately reported as https://github.com/numpy/numpy/issues/7934, but we can fix and test downstream as well.
- [X] clo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14007 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14007/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14007/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14007/events | https://github.com/pandas-dev/pandas/pull/14007 | 171,307,838 | MDExOlB1bGxSZXF1ZXN0ODE0MDU2NjE= | 14,007 | DEPR: Deprecate SparseList | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-08-16T02:24:36Z | 2016-08-16T09:57:42Z | 2016-08-16T09:57:38Z | MEMBER | null | Title is self-explanatory. Closes #13784.
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