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https://api.github.com/repos/pandas-dev/pandas/issues/5701 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5701/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5701/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5701/events | https://github.com/pandas-dev/pandas/pull/5701 | 24,318,425 | MDExOlB1bGxSZXF1ZXN0MTA4Mzk2Mzc= | 5,701 | Smarter formatting of timedelta and datetime columns | {
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"followers_url": "https://api.github.com/users/... | 46 | 2013-12-15T20:15:09Z | 2014-06-24T01:58:21Z | 2014-01-15T02:57:34Z | CONTRIBUTOR | null | Closes #3401
Closes #5708
Closes #5912
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https://api.github.com/repos/pandas-dev/pandas/issues/5702 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5702/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5702/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5702/events | https://github.com/pandas-dev/pandas/issues/5702 | 24,320,703 | MDU6SXNzdWUyNDMyMDcwMw== | 5,702 | BUG: astype assignment with loc not working | {
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"id": 2822098,
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{
"color": "e1... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2013-12-15T22:05:26Z | 2013-12-15T23:57:16Z | 2013-12-15T23:56:16Z | CONTRIBUTOR | null | ``` python
In [10]: df = pd.DataFrame({'A': [1., 2., 3., 4.]})
In [11]: df.dtypes
Out[11]:
A float64
dtype: object
In [12]: df.loc[:, 'A'] = df['A'].astype(np.int64)
In [13]: df.dtypes
Out[13]:
A float64
dtype: object
```
#4624 (which closed #4312) fixed it for `.iloc`
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"description": "np.nan, pd.NaT, pd.NA, d... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/wesm... | 8 | 2013-12-15T23:16:17Z | 2013-12-16T16:23:30Z | 2013-12-16T16:23:30Z | CONTRIBUTOR | null | Test code:
```
import pandas as pd
print pd.__version__
s1 = pd.Series([np.nan])
s2 = pd.Series([1])
s1.fillna(s2)
```
Results:
```
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-10-28706fea97bb... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5704 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5704/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5704/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5704/events | https://github.com/pandas-dev/pandas/pull/5704 | 24,322,107 | MDExOlB1bGxSZXF1ZXN0MTA4NDA4NjI= | 5,704 | BUG: loc assignment with astype buggy, (GH5702) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5705 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5705/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5705/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5705/events | https://github.com/pandas-dev/pandas/pull/5705 | 24,322,760 | MDExOlB1bGxSZXF1ZXN0MTA4NDExMDI= | 5,705 | BUG: Bug in fillna with Series and a passed series/dict (GH5703) | {
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"followers_url": "https://api.github.com/users/wesm... | 4 | 2013-12-15T23:52:58Z | 2014-06-21T11:40:12Z | 2013-12-16T16:23:30Z | CONTRIBUTOR | null | closes #5703
```
In [1]: s1 = Series([np.nan])
In [2]: s2 = Series([1])
In [3]: s1.fillna(s2)
Out[3]:
0 1
dtype: float64
In [4]: s1.fillna({ 1 : 1})
Out[4]:
0 1
dtype: float64
In [5]: s1.fillna({ 1 : 2, 2 : 3})
ValueError: cannot fillna on a 1-dim object with more than one value
```
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https://api.github.com/repos/pandas-dev/pandas/issues/5706 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5706/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5706/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5706/events | https://github.com/pandas-dev/pandas/issues/5706 | 24,325,698 | MDU6SXNzdWUyNDMyNTY5OA== | 5,706 | Sentinal -> Sentinel | {
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"gists_url": "https://api... | [] | closed | false | null | [] | null | 0 | 2013-12-16T02:12:18Z | 2013-12-16T13:43:16Z | 2013-12-16T13:43:16Z | CONTRIBUTOR | null | I was working on some typo fixes, and noticed that "Sentinel" is misspelled "Sentinal" in a few user-visible places (function names, arguments). Seems unlikely that anyone's relying on this, though, and it would produce a noisy and easily fixed error if so after the change.
```
./pandas/core/common.py:def sentinal_fa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5707 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5707/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5707/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5707/events | https://github.com/pandas-dev/pandas/pull/5707 | 24,328,384 | MDExOlB1bGxSZXF1ZXN0MTA4NDMwMzA= | 5,707 | Correct "sentinel" spelling. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5708 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5708/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5708/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5708/events | https://github.com/pandas-dev/pandas/issues/5708 | 24,328,932 | MDU6SXNzdWUyNDMyODkzMg== | 5,708 | str for NaT is garbage | {
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In [12]: str(pd.NaT)
Out[12]: '0001-255-255 00:00:00'
```
where as:
```
In [13]: repr(pd.NaT)
Out[13]: 'NaT'
```
I will fix this as part of #5701
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https://api.github.com/repos/pandas-dev/pandas/issues/5709 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5709/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5709/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5709/events | https://github.com/pandas-dev/pandas/pull/5709 | 24,339,778 | MDExOlB1bGxSZXF1ZXN0MTA4NDkwMDM= | 5,709 | StataWriter: Replace non-isalnum characters in variable names by _ instead of integral represantation of replaced character. Eliminate duplicates created by replacement. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5710 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5710/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5710/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5710/events | https://github.com/pandas-dev/pandas/issues/5710 | 24,359,520 | MDU6SXNzdWUyNDM1OTUyMA== | 5,710 | hashtable.so: undefined symbol: _intel_fast_memset | {
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[medlste@login1 config]$ python
Enthought Python Distribution -- www.enthought.com
Version: ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5711 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5711/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5711/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5711/events | https://github.com/pandas-dev/pandas/issues/5711 | 24,362,701 | MDU6SXNzdWUyNDM2MjcwMQ== | 5,711 | Failing tests on win/jenkins | {
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pandas.tests.test_indexing.TestIndexing.test_astype_assignment 16 ms 3
``` python
Error Message
attr is not equal [dtype]: dtype('int32') != dtype('int64')
Stacktrace
Traceback (most recent call last):
File "c:\Python26-AMD64\Lib\unittest.py", line 279, in run
testMethod()
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https://api.github.com/repos/pandas-dev/pandas/issues/5712 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5712/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5712/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5712/events | https://github.com/pandas-dev/pandas/issues/5712 | 24,368,565 | MDU6SXNzdWUyNDM2ODU2NQ== | 5,712 | groupby.transform failing in 0.13 | {
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"followers_url": "https://api.github.com/users/wesm... | 5 | 2013-12-16T18:26:45Z | 2013-12-16T20:21:33Z | 2013-12-16T19:53:58Z | CONTRIBUTOR | null | I have used groupby.transform to compute a number of statistics on data that is grouped by date. It seems to fail on indexing
All of my tests are failing for 0.13 but work in 0.12.
Here is one example:
the following three lines work fine in 0.12 and fails in 0.13.
print cik_df.head()
cik_df["portfolio_ran... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5713 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5713/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5713/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5713/events | https://github.com/pandas-dev/pandas/pull/5713 | 24,369,950 | MDExOlB1bGxSZXF1ZXN0MTA4NjYxNzU= | 5,713 | BUG: Bug in groupby transform with a datetime-like grouper (GH5712) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5714 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5714/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5714/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5714/events | https://github.com/pandas-dev/pandas/pull/5714 | 24,372,056 | MDExOlB1bGxSZXF1ZXN0MTA4NjczOTA= | 5,714 | Add test for DataFrame.corrwith and np.corrcoef compatibility | {
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http://stackoverflow.com/questions/20617854/is-there-a-bug-in-pandas-dataframe-corrwith-function
as a test.
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https://api.github.com/repos/pandas-dev/pandas/issues/5715 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5715/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5715/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5715/events | https://github.com/pandas-dev/pandas/issues/5715 | 24,377,364 | MDU6SXNzdWUyNDM3NzM2NA== | 5,715 | Travis exception on LOCALE_OVERRIDE builds | {
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```
$ ci/script.sh
inside ci/script.sh
Setting LC_ALL to zh_CN.GB18030
cannot import name hashtable
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "pandas/__init__.py", line 9, in <module>
from . import hashtable, tslib, lib
ImportError: ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5716 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5716/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5716/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5716/events | https://github.com/pandas-dev/pandas/pull/5716 | 24,391,100 | MDExOlB1bGxSZXF1ZXN0MTA4Nzc4MzQ= | 5,716 | TST/DOC: close win32 tests issues (GH5711) | {
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closes #5711
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https://api.github.com/repos/pandas-dev/pandas/issues/5717 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5717/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5717/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5717/events | https://github.com/pandas-dev/pandas/issues/5717 | 24,391,999 | MDU6SXNzdWUyNDM5MTk5OQ== | 5,717 | Problem selecting major_axis of a panel in HDFstore from a list if data_columns are used. | {
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I have a hdfstore of the following format: https://gist.github.com/MichaelWS/7997225
My major axis is "id" and minor axis is "date". I am trying to give a large python list into Term and select if an id is in it. This work... | {
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"followers_url": "https://api.github.com/users/wesm... | 4 | 2013-12-17T06:42:27Z | 2013-12-19T17:32:02Z | 2013-12-17T21:32:24Z | CONTRIBUTOR | null | Noticed the following difference in behavior between 0.12 and 0.13rc1 when adding a column to an empty dataframe. Obviously, a weird case, and can be worked around easily.
```
df = pd.DataFrame({"A": [1, 2, 3], "B": [1.2, 4.2, 5.2]})
y = df[df.A > 5]
y['New'] = np.nan
print y
print y.values
```
```
(pandas-0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5721 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5721/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5721/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5721/events | https://github.com/pandas-dev/pandas/pull/5721 | 24,429,826 | MDExOlB1bGxSZXF1ZXN0MTA4OTk1NjI= | 5,721 | DOC: trim CONTRIBUTING.MD | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5722 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5722/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5722/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5722/events | https://github.com/pandas-dev/pandas/pull/5722 | 24,432,180 | MDExOlB1bGxSZXF1ZXN0MTA5MDA5NjY= | 5,722 | DOC: DatetimeIndex accepts name param | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2013-12-17T16:26:49Z | 2014-07-16T08:43:35Z | 2013-12-17T17:36:22Z | CONTRIBUTOR | null | Just a docstring change to reflect `DatetimeIndex` taking a name parameter. I added a test since it wasn't explicitly tested anywhere.
``` python
In [1]: from pandas import DatetimeIndex
In [2]: idx = DatetimeIndex(start='2000-01-01', periods=1, freq='A', name='TEST')
In [3]: idx.name
Out[3]: 'TEST'
```
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https://api.github.com/repos/pandas-dev/pandas/issues/5723 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5723/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5723/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5723/events | https://github.com/pandas-dev/pandas/pull/5723 | 24,448,925 | MDExOlB1bGxSZXF1ZXN0MTA5MTA4Mjg= | 5,723 | BUG: don't use partial setting with scalars (GH5720) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5724 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5724/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5724/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5724/events | https://github.com/pandas-dev/pandas/issues/5724 | 24,455,536 | MDU6SXNzdWUyNDQ1NTUzNg== | 5,724 | groupby.mean, etc, doesn't recognize timedelta64 | {
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... | closed | false | null | [] | {
"closed_at": "2017-05-06T10:20:19Z",
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"created_at": "2016-02-08T15:30:21Z",
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related as well: http://stackoverflow.com/questions/20789976/python-pandas-dataframe-1st-line-issue-with-datetime-timedelta/20802902#20802902
I have a DataFrame with a column of timedeltas (actually upon inspection the dtype... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5725 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5725/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5725/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5725/events | https://github.com/pandas-dev/pandas/issues/5725 | 24,466,997 | MDU6SXNzdWUyNDQ2Njk5Nw== | 5,725 | inconsistent indexing behaviour with multi index | {
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"followers_url": "https://api.github.com/users/wesm... | 7 | 2013-12-18T03:10:21Z | 2013-12-19T12:33:09Z | 2013-12-18T20:30:27Z | CONTRIBUTOR | null | i have a dataframe with multi-index as
```
>>> df
val diffs
tag day
A 26 0.208105 NaN
37 2.709899 NaN
57 0.933981 NaN
B 75 0.624029 NaN
C 0 -1.645489 NaN
27 -1.749618 NaN
27 -0.725497 NaN
37 -0.381485 NaN
67 0.110426 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5726 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5726/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5726/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5726/events | https://github.com/pandas-dev/pandas/pull/5726 | 24,476,667 | MDExOlB1bGxSZXF1ZXN0MTA5MjcwNjU= | 5,726 | DOC: small doc build warning: Note -> Notes | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5727 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5727/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5727/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5727/events | https://github.com/pandas-dev/pandas/issues/5727 | 24,478,638 | MDU6SXNzdWUyNDQ3ODYzOA== | 5,727 | IndexError: index out of bounds for large Series with MultiIndex | {
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``` python
import pandas as pd
import numpy as np
n = 3500000
arrays = [range(n), np.empty(n)]
index = pd.MultiIndex.from_tuples(zip(*arrays))
s = pd.Se... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5728 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5728/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5728/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5728/events | https://github.com/pandas-dev/pandas/issues/5728 | 24,478,962 | MDU6SXNzdWUyNDQ3ODk2Mg== | 5,728 | DataFrame update issue | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5729 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5729/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5729/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5729/events | https://github.com/pandas-dev/pandas/issues/5729 | 24,492,096 | MDU6SXNzdWUyNDQ5MjA5Ng== | 5,729 | New orientation for to_json method | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2013-12-18T14:17:22Z | 2017-09-18T13:10:32Z | 2017-09-18T11:00:01Z | NONE | null | ```
start = datetime.datetime(2013, 1, 1)
end = datetime.datetime(2013, 01, 27)
f=web.get_data_yahoo('AAPL',start, end)
f['Adj Close'].to_json(date_format='iso',orient='split')
```
The above code gives the following result:
```
'{"name":"Adj Close","index":["2013-01-02T00:00:00","2013-01-03T00:00:0
0","2013-01-04T00:... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5730 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5730/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5730/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5730/events | https://github.com/pandas-dev/pandas/pull/5730 | 24,494,182 | MDExOlB1bGxSZXF1ZXN0MTA5MzcxMjk= | 5,730 | CLN/BUG: indexing fixes (GH5725, GH5727) | {
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closes #5725
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https://api.github.com/repos/pandas-dev/pandas/issues/5731 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5731/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5731/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5731/events | https://github.com/pandas-dev/pandas/pull/5731 | 24,494,543 | MDExOlB1bGxSZXF1ZXN0MTA5MzczMzU= | 5,731 | DOC: add demo of factorize | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5732 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5732/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5732/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5732/events | https://github.com/pandas-dev/pandas/issues/5732 | 24,496,571 | MDU6SXNzdWUyNDQ5NjU3MQ== | 5,732 | read_csv/read_table have a prefix argument which is not respected | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5733 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5733/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5733/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5733/events | https://github.com/pandas-dev/pandas/pull/5733 | 24,496,650 | MDExOlB1bGxSZXF1ZXN0MTA5Mzg1ODg= | 5,733 | Fix prefix argument for read_csv/read_table | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5734 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5734/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5734/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5734/events | https://github.com/pandas-dev/pandas/issues/5734 | 24,505,047 | MDU6SXNzdWUyNDUwNTA0Nw== | 5,734 | Series to_string does not show index name | {
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```
repr(pd.Series([1], index=pd.Index(["a"], name="idx")))
```
```
idx
a 1
dtype: int64
```
but `to_string` does not:
```
pd.Series([1], index=pd.Index(["a"], name="idx")).to_string(name=True)
```
```
a 1
```
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https://api.github.com/repos/pandas-dev/pandas/issues/5735 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5735/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5735/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5735/events | https://github.com/pandas-dev/pandas/issues/5735 | 24,512,896 | MDU6SXNzdWUyNDUxMjg5Ng== | 5,735 | TST: excel not completely cleaning up test files | {
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files apple.xlsx, apple.xls are created in the run directory and not deleted
need to change to use `ensure_clean` context manager
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raise KeyError appropriately under py3 on mi series
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"labels_url": "htt... | 22 | 2013-12-19T05:42:17Z | 2014-06-12T17:49:32Z | 2014-02-17T13:59:56Z | CONTRIBUTOR | null | `DataFrame.dtypes` and `DataFrame.ftypes` values were inconsistent for empty dataframes:
``` python
In [2]: pd.DataFrame().dtypes
Out[2]:
Empty DataFrame
Columns: []
Index: []
[0 rows x 0 columns]
In [3]: pd.DataFrame().ftypes
Out[3]:
Empty DataFrame
Columns: []
Index: []
[0 rows x 0 columns]
In [4]: pd.DataFra... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5741 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5741/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5741/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5741/events | https://github.com/pandas-dev/pandas/pull/5741 | 24,538,327 | MDExOlB1bGxSZXF1ZXN0MTA5NjM0ODI= | 5,741 | BUG: Fixed issue #5732. prefix option works in csv | {
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Good catch, @nmichaud.
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https://api.github.com/repos/pandas-dev/pandas/issues/5742 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5742/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5742/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5742/events | https://github.com/pandas-dev/pandas/pull/5742 | 24,539,497 | MDExOlB1bGxSZXF1ZXN0MTA5NjQxNTM= | 5,742 | BUG: don't lose dtypes when concatenating empty array-likes | {
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"followers_url": "https://api.github.com/users/... | 15 | 2013-12-19T06:41:20Z | 2014-06-15T06:34:27Z | 2014-01-18T14:20:24Z | CONTRIBUTOR | null | I develop an application that does quite a bit of data manipulation. Being aware of `pandas` being functional-but-not-really-heavily-optimized I use it to maintain label consistency and for grouping/merging data, heavy-duty maths is usually done with `numpy` ufuncs. The application contains entities that have no data a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5743 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5743/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5743/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5743/events | https://github.com/pandas-dev/pandas/issues/5743 | 24,552,221 | MDU6SXNzdWUyNDU1MjIyMQ== | 5,743 | API: json should be returning string (if possible) in py2 rather than unicode | {
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... | 3 | 2013-12-19T12:01:41Z | 2017-11-24T16:52:16Z | 2017-11-24T16:52:16Z | CONTRIBUTOR | null | http://stackoverflow.com/questions/20670370/pandas-and-unicode/20670901?noredirect=1#comment30966775_20670901
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2013-12-19T14:22:56Z | 2013-12-19T17:32:02Z | 2013-12-19T15:20:21Z | NONE | null | I am using Pandas 0.13.0rc1-23-g286811a, Python 2.7 and Windows XP.
The space in column names is apparently causing a problem. On IPython,
```
df = pd.DataFrame(columns=['a', 'b', 'c c'])
df['d'] = 3
df['c c']
```
Error
```
C:\python_envs\prod2\lib\site-packages\pandas\core\frame.pyc in __getitem__(self, key)
16... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5745 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5745/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5745/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5745/events | https://github.com/pandas-dev/pandas/pull/5745 | 24,560,080 | MDExOlB1bGxSZXF1ZXN0MTA5NzU4OTY= | 5,745 | BUG: don't allow an empty dataframe to have scalar assignment succeed (GH5744) | {
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related #5720
I think this is the correct behavior
```
In [1]: df = pd.DataFrame(columns=['a', 'b', 'c c'])
In [2]: df['d'] = 3
ValueError: Cannot set a frame with no defined index and a value that cannot be converted to a Series
In [3]: df['c c']
Out[3]: Series([], name: c c, dtype: object)
```
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"des... | closed | false | null | [] | null | 1 | 2013-12-19T17:18:13Z | 2014-01-10T12:15:43Z | 2014-01-10T12:15:43Z | NONE | null | So python 3.4 beta1 is out, and eventually travis will roll out 3.4 support.
Out test matrix is already bulky and partial at the same time.
I see travis [introduced](http://about.travis-ci.org/docs/user/caching/) a caching mechanism into their infrastructure. Previous attempts to do the same thing
using a network cac... | {
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allow assignment of a column in a frame with a scalar with no index (so adds to the columns),
instead of raising; this preservers 0.12 behavior
```
related #5720, #5744
going back to 0.12 behavior
effectively can add a column by assigning a scalar to a frame that doesn't have an index
need a more compelling rea... | {
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P.S.
`Good as first PR` doesn't mean "someone else has to do it", it just means wouldn't
it be nice if they did...
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"followers_url": "https://api.github.com/users/... | 2 | 2013-12-19T20:30:14Z | 2014-01-16T14:27:39Z | 2014-01-16T14:27:39Z | CONTRIBUTOR | null | For a sample of data like this:
```
d = pd.Series([1] * 25)
```
Both of these throw an exception (during an attempt to divide by zero):
```
pd.rolling_skew(d, window=25)
pd.rolling_kurt(d, window=25)
```
The issue is in algos.pyx. There are no checks for what amounts to zero variance in the data. If one value occur... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5750 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5750/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5750/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5750/events | https://github.com/pandas-dev/pandas/pull/5750 | 24,587,311 | MDExOlB1bGxSZXF1ZXN0MTA5OTAxNTE= | 5,750 | DOC: added missing argument in Series.apply | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5751 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5751/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5751/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5751/events | https://github.com/pandas-dev/pandas/issues/5751 | 24,587,639 | MDU6SXNzdWUyNDU4NzYzOQ== | 5,751 | Parallelization for embarrassingly parallel tasks | {
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"followers_url": "https://api.github.com/users/jr... | 64 | 2013-12-19T21:03:19Z | 2016-08-29T07:44:34Z | 2016-04-25T15:31:12Z | CONTRIBUTOR | null | I would like to promote the idea of applying multiprocessing.Pool() execution of embarrassingly parallel tasks, e.g. the application of a function to a large number of columns.
Obviously, there's some overhead to set it up, so there will be a lower limit of number of columns from which on this only can be faster than t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5752 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5752/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5752/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5752/events | https://github.com/pandas-dev/pandas/pull/5752 | 24,593,531 | MDExOlB1bGxSZXF1ZXN0MTA5OTQwMDA= | 5,752 | ENH: expose option_context as a top-level API GH5618 | {
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Moving `option_context` to toplevel rather then making `set_option` a context manager means
a one line change instead of metaclasses and config_prefix subtlety and the rest of the ich.
When a given approach to something explodes in complexity I'll [bravely, bravely run away](http://www.youtube.com/watch?v=BZwuTo7... | {
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No idea what the default value should be. numpy equivalent default is 1000, but even 100 is too big IMO.
The default is primarily there to mitigate output bombs when displaying some pandas objects.
Still need to update the release notes on all these micro-PRs.
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https://api.github.com/repos/pandas-dev/pandas/issues/5754 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5754/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5754/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5754/events | https://github.com/pandas-dev/pandas/issues/5754 | 24,605,139 | MDU6SXNzdWUyNDYwNTEzOQ== | 5,754 | pandas concat working in 0.12 but not 0.13 | {
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I am concatenating using the following
```
pd.concat(all_gics, ignore_index=True)
```
My traceback:
/usr/anaconda/lib/python2.7/site-packages/pandas/tools/merge.pyc in concat(objs, axis, join, join_axes, ignore_i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5755 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5755/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5755/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5755/events | https://github.com/pandas-dev/pandas/issues/5755 | 24,607,424 | MDU6SXNzdWUyNDYwNzQyNA== | 5,755 | Consistency with groupby as_index | {
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... | 19 | 2013-12-20T06:42:07Z | 2021-04-11T04:00:59Z | 2021-04-11T04:00:59Z | CONTRIBUTOR | null | Checklist:
- [x] head and tail act like filter
- [x] nth act like filter
- [x] nth on Series should dropna? (discuss?)
- [ ] something subtle with some functions in agg/apply (again)
- [ ] go through other methods to see if as_index acts correctly
- [ ] cythonized vs with apply #7002
- [ ] get_group with `as_index=Fals... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5756 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5756/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5756/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5756/events | https://github.com/pandas-dev/pandas/issues/5756 | 24,619,536 | MDU6SXNzdWUyNDYxOTUzNg== | 5,756 | BUG: creating dataframe from empty series raises exception | {
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``` python
In [1]: pd.__version__
Out[1]: '0.13.0rc1-95-gfec2ff6'
In [2]: pd.DataFrame(pd.Series())
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-2... | {
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closes #5754, BUG: Row-wise concat of differeing dtypes failing in certain cases
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https://api.github.com/repos/pandas-dev/pandas/issues/5758 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5758/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5758/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5758/events | https://github.com/pandas-dev/pandas/issues/5758 | 24,623,314 | MDU6SXNzdWUyNDYyMzMxNA== | 5,758 | BUGI: groupby issue with user function with mutation, and duplicate indices | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2013-12-20T14:03:53Z | 2018-01-31T15:19:14Z | 2018-01-31T15:19:14Z | CONTRIBUTOR | null | Only happens when the user function mutates the input
Originally from: http://stackoverflow.com/questions/20691168/pandas-apply-to-data-frame-groupby/20705226#20705226
Could be auto-fixed or maybe just a better error report to the user (about the dups)
```
In [40]: df = DataFrame(dict(A = ['foo','foo','bar','bar'], ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5759 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5759/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5759/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5759/events | https://github.com/pandas-dev/pandas/pull/5759 | 24,625,587 | MDExOlB1bGxSZXF1ZXN0MTEwMTI4ODQ= | 5,759 | API: Series.ravel compat with ndarray | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5760 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5760/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5760/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5760/events | https://github.com/pandas-dev/pandas/pull/5760 | 24,643,327 | MDExOlB1bGxSZXF1ZXN0MTEwMjI1Njk= | 5,760 | Update rolling skew & kurtosis to handle cases where they aren't defined | {
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"followers_url": "https://api.github.com/users/... | 7 | 2013-12-20T19:35:08Z | 2014-06-20T06:05:10Z | 2014-01-16T14:27:39Z | CONTRIBUTOR | null | closes #5749
The rolling skewness and kurtosis in algos.pyx were modified to match
the testing logic in pandas/core/nanops.py. They now both return NaN
where they are not defined, which occurs where there are either too
few observations or where the variance is zero.
A set of tests was added to verify that Nan is ret... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5761 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5761/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5761/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5761/events | https://github.com/pandas-dev/pandas/pull/5761 | 24,662,958 | MDExOlB1bGxSZXF1ZXN0MTEwMzM4NzA= | 5,761 | DOC: Flesh out the R comparison section of docs (GH3980) | {
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"followers_url": "https://api.github.com/users/... | 12 | 2013-12-21T10:04:08Z | 2014-06-19T00:03:47Z | 2013-12-28T15:55:45Z | CONTRIBUTOR | null | Some additions to #3980.
I've done some more comparisons to the plyr functions located [here](http://nbviewer.ipython.org/gist/chappers/8066230/). More specifically [aaply](http://nbviewer.ipython.org/gist/chappers/8066230/aaply.ipynb), [alply](http://nbviewer.ipython.org/gist/chappers/8066230/alply.ipynb) don't real... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5762 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5762/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5762/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5762/events | https://github.com/pandas-dev/pandas/issues/5762 | 24,664,987 | MDU6SXNzdWUyNDY2NDk4Nw== | 5,762 | groupby and aggregate passing different types to aggregating function | {
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```
>>> pd.__version__
'0.13.0rc1-118-gb0c2aa4'
>>> df
tag val
0 A -0.621620
1 A 0.386178
2 B 0.449459
3 B 0.421856
4 B -0.083518
[5 rows x 2 colu... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5763 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5763/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5763/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5763/events | https://github.com/pandas-dev/pandas/pull/5763 | 24,674,046 | MDExOlB1bGxSZXF1ZXN0MTEwMzgxMzU= | 5,763 | WIP: df rendering using templates + conditional formatting for HTML | {
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"html_url": "https://github.com/pandas-dev/pandas/milestone/24",
"id": 526062,
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Provides conditional formatting and CSS styling of HTML tables for dataframes using code.
The plan is to clean up and package the functionality behind a nice API in some pandas namespace,
perhaps with a dotted API, and ship in 0.14.
Unlike my first attempt from 6 months ago which turned into a rabbit ho... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5764 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5764/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5764/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5764/events | https://github.com/pandas-dev/pandas/issues/5764 | 24,706,910 | MDU6SXNzdWUyNDcwNjkxMA== | 5,764 | BUG: Applying function on column of Groupby object with as_index=False does not select column | {
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"description": "Apply, Aggregat... | closed | false | null | [] | {
"closed_at": "2020-01-30T12:18:05Z",
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"followers_url": "https://api.github.com/users/wesm... | 5 | 2013-12-23T13:53:32Z | 2019-12-31T15:04:44Z | 2019-12-31T15:04:44Z | MEMBER | null | ```
>>> df = pd.DataFrame([[1, 2], [1, 4], [5, 6]], columns=['A', 'B'])
>>> df
A B
0 1 2
1 1 4
2 5 6
[3 rows x 2 columns]
```
Selecting a column of the GroupBy object, still returns all columns:
```
>>> g = df.groupby('A', as_index=False)['B']
>>> g.get_group(1)
A B
0 1 2
1 1 4
[2 rows x 2 columns]
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https://api.github.com/repos/pandas-dev/pandas/issues/5765 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5765/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5765/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5765/events | https://github.com/pandas-dev/pandas/issues/5765 | 24,719,039 | MDU6SXNzdWUyNDcxOTAzOQ== | 5,765 | df.to_json() slower in 0.13.x vs 0.12.0 | {
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Version 0.12.0:
``` python
Python 2.7.5+ (default, Sep 17 2013, 15:31:50)
In [1]: import pandas as pd, numpy as np
In [2]: df = pd.DataFrame(np.random.rand(100000,10))
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https://api.github.com/repos/pandas-dev/pandas/issues/5766 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5766/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5766/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5766/events | https://github.com/pandas-dev/pandas/issues/5766 | 24,723,889 | MDU6SXNzdWUyNDcyMzg4OQ== | 5,766 | BUG: IndexError on read_csv/read_table when using usecols/names parameters and omitting last column | {
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"followers_url": "https://api.github.com/users/wesm... | 4 | 2013-12-23T20:57:58Z | 2013-12-25T02:05:13Z | 2013-12-25T02:05:13Z | CONTRIBUTOR | null | Example code:
``` python
from StringIO import StringIO
import pandas as pd
names = ["a","b","c"]
data = """\
0,1,2
3,4,5
6,7,8"""
# usecols works as expected if all columns are named
print pd.read_csv(StringIO(data), header=None, usecols=[1,2], names=names)
print pd.read_csv(StringIO(data), header=None, usecols=[0,... | {
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#... | {
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``` python
df.sort_index(..., inplace=False)
```
but is
``` python
df.reindex_axis(..., copy=True)
```
Any reason why we shouldn't just use the same keyword (either `copy` or `inplace`) in all functions to determine whether to modify the original object or make a new one?... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5770 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5770/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5770/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5770/events | https://github.com/pandas-dev/pandas/pull/5770 | 24,759,654 | MDExOlB1bGxSZXF1ZXN0MTEwODEyMjE= | 5,770 | BUG: regression in read_csv parser handling of usecols GH5766 | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2013-12-25T11:41:55Z | 2013-12-25T13:08:03Z | 2013-12-25T13:07:52Z | NONE | null | ``` python
import pandas as pd
a = pd.Series(index=[4,5,6], data=0)
print a.loc[4:5]
a.loc[4:5] += 1
```
Yields:
```
4 0
5 0
Traceback (most recent call last):
File "temp1.py", line 9, in <module>
dtype: int64
a.loc[4:5] += 1
File "lib\site-packages\pandas\core\indexing.py", line 88, in __setitem__
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5773 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5773/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5773/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5773/events | https://github.com/pandas-dev/pandas/issues/5773 | 24,771,422 | MDU6SXNzdWUyNDc3MTQyMg== | 5,773 | BUG: Panel, MultiIndex, _setitem_with_indexer | {
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``` python
idx = MultiIndex.from_tuples([(1, 'one'), (1, 'two'), (2, 'one'),
(2, 'two')])
df = DataFrame([[1, 'a', 1], [2, 'b', 1], [3, 'c', 1], [4, 'd', 1]],
columns=['A', 'B', 'C'], index=idx)
wp = Panel(... | {
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----
Basically the problem is if you want to do a bar plot with time series
```
df.plot(kind='bar')
```
it will create a label for every date entry instead one clean label and more dates when you zoom in.
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https://api.github.com/repos/pandas-dev/pandas/issues/5775 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5775/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5775/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5775/events | https://github.com/pandas-dev/pandas/issues/5775 | 24,793,708 | MDU6SXNzdWUyNDc5MzcwOA== | 5,775 | Add `_get_numeric_data()` to the public API? | {
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"color": "AD... | closed | false | null | [] | null | 7 | 2013-12-26T18:39:32Z | 2014-09-18T17:52:48Z | 2013-12-27T18:10:17Z | CONTRIBUTOR | null | Hi, I'm testing out some code on the 0.13 release candidate and I've run into problems with a fairly common (for me) pattern. It's no longer possible to use a boolean Series to index a numpy array. E.g.:
```
import numpy as np
import pandas as pd
x = np.random.randn(30)
mask = pd.Series(np.random.rand(30) > .5)
x[mask... | {
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``` python
(pandas-dev) ~/E/p/l/p/s/p/vb_suite (to-frame-multi=) python test_perf.py -h
Traceback (most recent call last):
File "test_perf.py", line 55, in <module>
import pandas as pd
File "/Users/tom/Envs/pandas-dev/lib/... | {
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======================================================================
ERROR: test_read_write_dta11 (pandas.io.tests.test_stata.TestStata)
----------------------------------------------------------------------
Traceback (most recent call last):
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https://api.github.com/repos/pandas-dev/pandas/issues/5779 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5779/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5779/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5779/events | https://github.com/pandas-dev/pandas/issues/5779 | 24,827,399 | MDU6SXNzdWUyNDgyNzM5OQ== | 5,779 | Failing timeseries tests on debian sparc buildbot | {
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======================================================================
ERROR: test_to_timedelta_on_missing_values (pandas.tseries.tests.test_timedeltas.TestTimedeltas)
----------------------------------------------------------------------
Traceback (most recent call last):
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https://api.github.com/repos/pandas-dev/pandas/issues/5780 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5780/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5780/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5780/events | https://github.com/pandas-dev/pandas/pull/5780 | 24,828,007 | MDExOlB1bGxSZXF1ZXN0MTExMTY1NDY= | 5,780 | TST: close sparc test failures | {
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"followers_url": "https://api.github.com/users/wesm... | 4 | 2013-12-27T17:57:54Z | 2014-07-16T08:44:26Z | 2013-12-27T20:08:13Z | CONTRIBUTOR | null | TST: closes #5778, failing tests on non-little endian for stata (spac)
TST: closes #5779, big endian compensation for datelike dtypes
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https://api.github.com/repos/pandas-dev/pandas/issues/5781 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5781/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5781/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5781/events | https://github.com/pandas-dev/pandas/issues/5781 | 24,831,581 | MDU6SXNzdWUyNDgzMTU4MQ== | 5,781 | TST/BUG: stata failures on big endian | {
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"html_url": "https://github.com/pandas-dev/pandas/milestone/24",
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Investigate/fix whether the test failures (currently skipped on big-endian) are actual bugs or just an odd test.
cc @PKEuS
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https://api.github.com/repos/pandas-dev/pandas/issues/5782 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5782/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5782/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5782/events | https://github.com/pandas-dev/pandas/issues/5782 | 24,840,769 | MDU6SXNzdWUyNDg0MDc2OQ== | 5,782 | test_aggregate_item_by_item fails on SPARC py3 | {
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=============================================================
=========
FAIL: test_aggregate_item_by_item (pandas.tests.test_groupby.TestGroupBy)
----------------------------------------------------------------------
Traceback (most recent call last):
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https://api.github.com/repos/pandas-dev/pandas/issues/5783 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5783/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5783/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5783/events | https://github.com/pandas-dev/pandas/pull/5783 | 24,840,930 | MDExOlB1bGxSZXF1ZXN0MTExMjMxMDY= | 5,783 | TST: ensure_clean skips test when fs doesn't support unicode (sparc) | {
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These checks were removed from the tests during a refactor to use ensure_clean
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https://api.github.com/repos/pandas-dev/pandas/issues/5784 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5784/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5784/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5784/events | https://github.com/pandas-dev/pandas/pull/5784 | 24,840,956 | MDExOlB1bGxSZXF1ZXN0MTExMjMxMTc= | 5,784 | BLD: print_versions get uname() via cross-platform API | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5785 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5785/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5785/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5785/events | https://github.com/pandas-dev/pandas/issues/5785 | 24,848,269 | MDU6SXNzdWUyNDg0ODI2OQ== | 5,785 | Series ravel() doesn't accept order keyword | {
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"gis... | null | 1 | 2013-12-28T16:55:32Z | 2013-12-28T16:57:39Z | 2013-12-28T16:57:39Z | CONTRIBUTOR | null | ndarray's ravel() allows an optional order keyword. For compat, `Series` ravel should either accept `order='C'` or just take `*args, **kwargs` and pass it on downwards.
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https://api.github.com/repos/pandas-dev/pandas/issues/5786 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5786/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5786/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5786/events | https://github.com/pandas-dev/pandas/issues/5786 | 24,852,277 | MDU6SXNzdWUyNDg1MjI3Nw== | 5,786 | idxmax() not available on groupby anymore | {
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```
df.groupby(...).idxmax()
```
This worked in 0.12, but not anymore in 0.13 as it is not in the whitelist.
- Should this be added to the whitelist? ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5787 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5787/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5787/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5787/events | https://github.com/pandas-dev/pandas/pull/5787 | 24,853,012 | MDExOlB1bGxSZXF1ZXN0MTExMjc1OTM= | 5,787 | Add idxmax/idxmin to groupby dispatch whitelist (#5786) | {
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```
import pandas as pd
from StringIO import StringIO
s="""2011.05.16,00:00,1.40893
2011.05.16,01:00,1.40760
2011.05.16,02:00,1.40750
2011.05.16,03:00,1.40649
2011.05.17,02:00,1.40893
2011.05.17,03:00,1.40760
2011.05.17,04:00,1.40750
2011.05.17,05:00,1.40649
2011.05.18,02:00,1.40893
2011.05.18,03... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5789 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5789/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5789/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5789/events | https://github.com/pandas-dev/pandas/issues/5789 | 24,853,217 | MDU6SXNzdWUyNDg1MzIxNw== | 5,789 | BUG: hour string automatically converted to datetime in groupby apply | {
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"followers_url": "https://api.github.com/users/wesm... | 0 | 2013-12-28T23:44:21Z | 2013-12-29T16:23:22Z | 2013-12-29T16:23:22Z | MEMBER | null | (Encountered with same SO [question](http://stackoverflow.com/questions/20819702/hourly-frequency-count-with-python/20820166#20820166) as #5786 and #5788. With following dataframe:
```
from StringIO import StringIO
s="""2011.05.16,00:00,1.40893
2011.05.16,01:00,1.40760
2011.05.16,02:00,1.40750
2011.05.16,03:00,1.40649... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5790 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5790/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5790/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5790/events | https://github.com/pandas-dev/pandas/pull/5790 | 24,855,398 | MDExOlB1bGxSZXF1ZXN0MTExMjg0Mzk= | 5,790 | BUG: dont' always coerce reductions in a groupby always to datetimes | {
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closes #5789
TST: tests for idxmax used in an apply
closes #5788
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https://api.github.com/repos/pandas-dev/pandas/issues/5791 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5791/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5791/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5791/events | https://github.com/pandas-dev/pandas/pull/5791 | 24,869,654 | MDExOlB1bGxSZXF1ZXN0MTExMzI5ODc= | 5,791 | TST: aggregate_item_by_item test failure (GH5782) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5792 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5792/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5792/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5792/events | https://github.com/pandas-dev/pandas/pull/5792 | 24,878,512 | MDExOlB1bGxSZXF1ZXN0MTExMzY5ODM= | 5,792 | DOC: fix minor doc build warnings | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5793 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5793/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5793/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5793/events | https://github.com/pandas-dev/pandas/issues/5793 | 24,879,135 | MDU6SXNzdWUyNDg3OTEzNQ== | 5,793 | Related to Issue 3922: Panda still crashes with pivot() Function | {
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Old issue: https://github.com/pydata/pandas/issues/3922?source=c
Doing the example on http://pandas.pydata.org/pandas-docs/stab... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5794 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5794/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5794/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5794/events | https://github.com/pandas-dev/pandas/pull/5794 | 24,886,343 | MDExOlB1bGxSZXF1ZXN0MTExNDEyNjM= | 5,794 | COMPAT: back compat for HDFStore with a Term | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5795 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5795/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5795/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5795/events | https://github.com/pandas-dev/pandas/issues/5795 | 24,888,652 | MDU6SXNzdWUyNDg4ODY1Mg== | 5,795 | Variable not changed from integer to float on conditional update | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2013-12-30T15:54:19Z | 2013-12-30T16:00:13Z | 2013-12-30T16:00:02Z | CONTRIBUTOR | null | I want to create a dataframe variable, set all rows to zero, then conditionally update some rows with a floating point value. When I don't explicitly create the variable as a float, subsequent conditional operations produce unexpected output.
See the three examples below.
df['C'] is created as an integer -- result o... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5796 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5796/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5796/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5796/events | https://github.com/pandas-dev/pandas/issues/5796 | 24,891,659 | MDU6SXNzdWUyNDg5MTY1OQ== | 5,796 | Tagging 0.13 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5797 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5797/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5797/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5797/events | https://github.com/pandas-dev/pandas/issues/5797 | 24,896,600 | MDU6SXNzdWUyNDg5NjYwMA== | 5,797 | Series replace values using timestamps in a dict | {
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"followers_url": "https://api.github.com/users/... | 9 | 2013-12-30T19:22:28Z | 2014-01-02T22:59:01Z | 2014-01-02T22:59:01Z | CONTRIBUTOR | null | I was working with financial data and was replacing dates that were not valid trading days. It seems that replace does not work on any dict between two timestamps. Here is an example. This simply throws an exception on 0.12.
```
import pandas.io.data as web
ibm = web.DataReader("IBM", "yahoo", "1993/01/01").reset_i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5799 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5799/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5799/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5799/events | https://github.com/pandas-dev/pandas/issues/5799 | 24,900,456 | MDU6SXNzdWUyNDkwMDQ1Ng== | 5,799 | version.py version and short_version are inconsistent | {
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"followers_url": "https://api.github.com/users/... | 1 | 2013-12-30T21:04:48Z | 2018-11-16T13:55:54Z | 2013-12-31T01:00:26Z | NONE | null | The new dev versioning scheme from #4046 introduced an inconsistency:
```
user1@localhost ~/src/pandas (git)-[master] % cat pandas/version.py
version = '0.13.0-1-gaf9c025'
short_version = '0.14.0'
```
https://github.com/pydata/pandas/issues/5796#issuecomment-31368550
short_version means we're in the 0.14.0 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5800 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5800/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5800/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5800/events | https://github.com/pandas-dev/pandas/pull/5800 | 24,901,377 | MDExOlB1bGxSZXF1ZXN0MTExNDkzMjk= | 5,800 | This fixes issue 5797 and allows replace using timestamps. | {
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"followers_url": "https://api.github.com/users/... | 6 | 2013-12-30T21:28:59Z | 2014-07-25T08:41:04Z | 2013-12-31T01:25:48Z | CONTRIBUTOR | null | this fixes https://github.com/pydata/pandas/issues/5797
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