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https://api.github.com/repos/pandas-dev/pandas/issues/9002 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9002/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9002/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9002/events | https://github.com/pandas-dev/pandas/issues/9002 | 51,029,381 | MDU6SXNzdWU1MTAyOTM4MQ== | 9,002 | StopIteration error when trying to import specific columns from Excel file using parse_cols | {
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df = pd.read_excel(r'\\path_to_Excel_file',
'Sheet1', parse_cols=['MODEL_YEAR'])
returns:
---------------------------------------------------------------------------
StopIteration Traceback (most recent call last)
<ipython-input-29-336e4fd9eea1> in <module>()
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https://api.github.com/repos/pandas-dev/pandas/issues/9003 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9003/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9003/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9003/events | https://github.com/pandas-dev/pandas/issues/9003 | 51,034,159 | MDU6SXNzdWU1MTAzNDE1OQ== | 9,003 | Memory leak with pandas plot | {
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Seems to be a leak memory bug with pandas.plot. It works well with plt.plot(df.index, df.test) (see below)
Simple case here :
```
import sys
import gc
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9004 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9004/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9004/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9004/events | https://github.com/pandas-dev/pandas/pull/9004 | 51,038,261 | MDExOlB1bGxSZXF1ZXN0MjU1MzQyNTM= | 9,004 | update NDFrame __setattr__ to match behavior of __getattr__ | {
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"followers_url": "https://api.github.com/users/jr... | 12 | 2014-12-04T22:29:27Z | 2014-12-07T21:13:31Z | 2014-12-07T15:15:07Z | CONTRIBUTOR | null | This addresses the issue raised in #8994.
Here is the behavior before this PR:
``` python
data = pd.DataFrame({'x':[1, 2, 3]})
data.y = 2
data['y'] = [2, 4, 6]
data.y = 5
print(data.y)
#2
print(data['y'].values)
# [5, 5, 5]
```
Here is the behavior after this PR:
``` python
data = pd.DataFrame({'x':[1, 2, 3]})
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https://api.github.com/repos/pandas-dev/pandas/issues/9005 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9005/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9005/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9005/events | https://github.com/pandas-dev/pandas/issues/9005 | 51,042,657 | MDU6SXNzdWU1MTA0MjY1Nw== | 9,005 | BUG: comparing 'NaT' in series with series returns True | {
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When having a 'NaT' in a datetime series and comparing this to a datetime series, the comparison with NaT returns True (and shouldn't comparisons with NA not always return False?) Comparing it with a scalar does return False:
```
In [54]: s = pd.Series([pd.Timestamp('2012-01-0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9006 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9006/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9006/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9006/events | https://github.com/pandas-dev/pandas/issues/9006 | 51,044,980 | MDU6SXNzdWU1MTA0NDk4MA== | 9,006 | BUG: comparing multicolumn dataframe with datetime64 values to series gives TypeError | {
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... | 4 | 2014-12-04T23:41:06Z | 2021-04-11T06:00:29Z | null | MEMBER | null | When trying to compare a dataframe to a column/series (I know, in the following case not useful due to the alignement of the series with the columns of the dataframe and not the rows, but it is something typical users will try), I get the correct results if there are strings in the dataframe and series, but a TypeError... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9007 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9007/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9007/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9007/events | https://github.com/pandas-dev/pandas/pull/9007 | 51,048,270 | MDExOlB1bGxSZXF1ZXN0MjU1NDA3MjA= | 9,007 | Fix groupby().transform() example in cookbook.rst | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-12-05T00:24:42Z | 2014-12-05T06:11:47Z | 2014-12-05T02:11:13Z | CONTRIBUTOR | null | @jorisvandenbossche : Fixes code in example, and makes final averaging by len(x) stylistically similar to previous adds.
New pull request replacing my earlier one, which contained some other erroneous commits.
closes #8944
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closes #8866
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When saving some financial data this will cause loss of precision. For example, 2-year treasury fut... | {
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```
>>> options_object = web.Options('^spxpm', 'yahoo')
>>> options_object.get_call_data( expiry=datetime.date(2014, 12, 20) )
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/pollyp/anaconda/lib/python2... | {
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import pandas as pd
a = pd.TimedeltaIndex(range(3),unit='S')
print (a[1])
```
gives output
```
11574 days 01:46:40
```
I would expect the same output as from
``` python
import pandas as pd
import numpy as np
npa = np.array(range(3),dtype='timedelta64[s]')
a = pd.TimedeltaIndex(npa)
print(a[1])
```
givin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9012 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9012/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9012/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9012/events | https://github.com/pandas-dev/pandas/issues/9012 | 51,102,009 | MDU6SXNzdWU1MTEwMjAwOQ== | 9,012 | Plotting problem in pandas 0.15.1 for DataFrame with datetime-index | {
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```
from datetime import datetime
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
plot_df = pd.DataFrame(
np.random.rand(21, 2),
index=pd.bdate_range(datetime(2000, 1, 1), datetime(2000, 1, 31)),
columns=['a', 'b'])
fig = plt.figure()
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-12-05T14:23:10Z | 2014-12-05T14:37:09Z | 2014-12-05T14:30:23Z | NONE | null | Dropping rows is removing the values from a multiindex dataframe but not removing the key values from the multiindex. I don't think this is intended behavior. This is pandas 15.1
``` python
In [33]: s = pd.Series(np.random.randn(8), index=arrays)
In [34]: df = pd.DataFrame(np.random.randn(8, 4), index=arrays)
In [35... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9014 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9014/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9014/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9014/events | https://github.com/pandas-dev/pandas/pull/9014 | 51,139,403 | MDExOlB1bGxSZXF1ZXN0MjU1OTU3NjM= | 9,014 | ENH: Implement Series.StringMethod.slice_replace | {
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"followers_url": "https://api.github.com/users/jr... | 7 | 2014-12-05T19:57:58Z | 2015-01-08T02:01:29Z | 2015-01-08T01:59:16Z | CONTRIBUTOR | null | closes #8888
This does not implement immerrr's suggestion of implementing `__setitem__`, as all `StringMethod` methods return a new `Series` (or `DataFrame`) rather than mutating.
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https://api.github.com/repos/pandas-dev/pandas/issues/9015 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9015/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9015/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9015/events | https://github.com/pandas-dev/pandas/pull/9015 | 51,143,336 | MDExOlB1bGxSZXF1ZXN0MjU1OTgyODU= | 9,015 | TST: better testing for test_where (GH8997) | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-12-05T20:38:36Z | 2015-05-05T08:23:02Z | 2014-12-06T15:17:00Z | CONTRIBUTOR | null | closes #8996
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https://api.github.com/repos/pandas-dev/pandas/issues/9016 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9016/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9016/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9016/events | https://github.com/pandas-dev/pandas/issues/9016 | 51,148,846 | MDU6SXNzdWU1MTE0ODg0Ng== | 9,016 | Bitwise operation weirdness | {
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"followers_url": "https://api.github.com/users/jr... | 10 | 2014-12-05T21:36:18Z | 2015-02-05T11:37:52Z | 2015-02-05T11:37:52Z | NONE | null | It seems like `pd.Series([x]) | pd.Series([y])` with `x, y` integers returns `pd.Series([x | y]).astype(bool)`. This is a reasonable semantic, but `pd.Series([x]) & pd.Series([y])` seems to return `pd.Series([x & y % 2]) == 1`, which is a lot weirder. Is there a justification for this? I couldn't find one in the docume... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9017 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9017/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9017/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9017/events | https://github.com/pandas-dev/pandas/issues/9017 | 51,152,828 | MDU6SXNzdWU1MTE1MjgyOA== | 9,017 | Pandas Dataflow | {
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As long as I am writing library for data processing / machine learning, I eager to create some... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9018 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9018/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9018/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9018/events | https://github.com/pandas-dev/pandas/pull/9018 | 51,164,233 | MDExOlB1bGxSZXF1ZXN0MjU2MTE0NzA= | 9,018 | BUG: Prevent index header column from being added on MultiIndex when ind... | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-12-06T01:01:08Z | 2014-12-07T22:27:24Z | 2014-12-07T22:27:17Z | CONTRIBUTOR | null | Fix for #8452
Index column was added when index=False.
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https://api.github.com/repos/pandas-dev/pandas/issues/9019 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9019/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9019/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9019/events | https://github.com/pandas-dev/pandas/pull/9019 | 51,187,034 | MDExOlB1bGxSZXF1ZXN0MjU2MjAyMTI= | 9,019 | reindex multi-index at level with reordered labels | {
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on branch:
```
>>> df
vals
first second third
mid 3rd 992 1.96
562 12.06
1st 73 -6.46
818 -15.75
658 5.90
btm 2nd 915 9.75
474 -1.47
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https://api.github.com/repos/pandas-dev/pandas/issues/9020 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9020/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9020/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9020/events | https://github.com/pandas-dev/pandas/issues/9020 | 51,187,589 | MDU6SXNzdWU1MTE4NzU4OQ== | 9,020 | CLN: reorg sorting algos | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-12-06T16:11:36Z | 2017-02-27T21:47:19Z | 2017-02-27T21:47:15Z | CONTRIBUTOR | null | currently much of the sorting algorithms are in groupby.py (e.g. _index_from_factorized, _lexsort_indexer), the whole section under 'misc utilities'.
I think it makes sense to move these to algorithms.py. (OR maybe to sorting.py). Likewise might make sense to pull out 'sorting' type cython algos and to add a section /... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9021 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9021/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9021/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9021/events | https://github.com/pandas-dev/pandas/issues/9021 | 51,188,058 | MDU6SXNzdWU1MTE4ODA1OA== | 9,021 | TST: dateutil 2.3 | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-12-06T16:28:33Z | 2014-12-07T22:26:13Z | 2014-12-07T22:26:13Z | CONTRIBUTOR | null | cc @dbew
xref #8639
appears that python-dateutil 2.3 (just release) is breaking everything on windows (linux/mac) seem to be ok
I think that the naming convention changed
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-12-06T18:27:51Z | 2014-12-22T14:55:29Z | 2014-12-07T21:01:06Z | CONTRIBUTOR | null | closes #9000
I opted to not change np_datetime_strings but instead short-circuit in Timestamp. I don't have a strong preference one way or another.
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closes #9399
closes #9406
closes #9533
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https://api.github.com/repos/pandas-dev/pandas/issues/9024 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9024/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9024/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9024/events | https://github.com/pandas-dev/pandas/pull/9024 | 51,193,769 | MDExOlB1bGxSZXF1ZXN0MjU2MjI4NDg= | 9,024 | Gh9010 yahoo options parsing bug | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9026 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9026/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9026/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9026/events | https://github.com/pandas-dev/pandas/pull/9026 | 51,195,400 | MDExOlB1bGxSZXF1ZXN0MjU2MjM1MDM= | 9,026 | BUG: Datareader index name shows unicode characters | {
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In [6]: df = DataFrame({'A' : [pd.Timedelta('1 day 1 sec')],'B' : [5], 'C' : [pd.Timestamp('20130101') ]})
In [7]: df
Out[7]:
A B C
0 1 days 00:00:01 5 2013-01-01
In [8]: df.dtypes
Out[8]:
A timedelta64[ns]
B int64
C datetime64[ns]
dtype: object
In [9]: df[['A']].... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9028 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9028/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9028/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9028/events | https://github.com/pandas-dev/pandas/pull/9028 | 51,198,650 | MDExOlB1bGxSZXF1ZXN0MjU2MjQ3NTM= | 9,028 | Implement timedeltas for to_json | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9029 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9029/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9029/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9029/events | https://github.com/pandas-dev/pandas/pull/9029 | 51,199,327 | MDExOlB1bGxSZXF1ZXN0MjU2MjUwMTM= | 9,029 | BUG: Fixed maximum columns limit when using usecols for csv. #8985 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9030 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9030/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9030/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9030/events | https://github.com/pandas-dev/pandas/pull/9030 | 51,200,481 | MDExOlB1bGxSZXF1ZXN0MjU2MjU0Njg= | 9,030 | Calling qcut with too many duplicates now gives an informative error | {
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... | 4 | 2014-12-06T23:27:06Z | 2015-05-09T16:05:51Z | 2015-05-09T16:05:51Z | NONE | null | Closes #7751.
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https://api.github.com/repos/pandas-dev/pandas/issues/9031 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9031/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9031/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9031/events | https://github.com/pandas-dev/pandas/issues/9031 | 51,203,165 | MDU6SXNzdWU1MTIwMzE2NQ== | 9,031 | FrozenNDArray cannot repr scalars | {
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"followers_url": "https://api.github... | 4 | 2014-12-07T01:11:21Z | 2018-10-30T12:29:32Z | 2018-10-30T12:29:32Z | CONTRIBUTOR | null | on master:
```
>>> from pandas.core.base import FrozenNDArray
>>> a = FrozenNDArray(1)
>>> a
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/lib/python3.4/site-packages/pandas-0.15.1_192_g7bd1b24-py3.4-linux-x86_64.egg/pandas/core/base.py", line 65, in __repr__
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https://api.github.com/repos/pandas-dev/pandas/issues/9032 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9032/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9032/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9032/events | https://github.com/pandas-dev/pandas/issues/9032 | 51,204,873 | MDU6SXNzdWU1MTIwNDg3Mw== | 9,032 | DOC: cleanup outdated caveats for HTML parsing (Anaconda LXML) | {
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... | 5 | 2014-12-07T02:37:01Z | 2016-11-26T02:19:06Z | 2016-11-25T22:47:50Z | CONTRIBUTOR | null | Anaconda now ships with lxml 3.4.0:
- http://docs.continuum.io/anaconda/pkg-docs.html
http://pandas.pydata.org/pandas-docs/stable/gotchas.html#html-table-parsing
> Issues with using Anaconda
>
> Anaconda ships with lxml version 3.2.0; the following workaround for Anaconda was successfully used to deal with the versi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9033 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9033/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9033/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9033/events | https://github.com/pandas-dev/pandas/issues/9033 | 51,220,796 | MDU6SXNzdWU1MTIyMDc5Ng== | 9,033 | API: make attribute setting de-facto insert column | {
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"f... | 7 | 2014-12-07T15:20:52Z | 2021-04-11T06:01:01Z | null | CONTRIBUTOR | null | xref #8994
xref #5904
xref #8572
This might be a bit controversial, but the issues raised in #8994 and #5904
point to some continued confusion w.r.t. attribute setting 'being' column setting
so if we now have
```
df = DataFrame({'A' : [1,2,3], 'B' : 5 })
df.C = 5
```
is an attribute set
it _could_ be a column ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9034 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9034/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9034/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9034/events | https://github.com/pandas-dev/pandas/issues/9034 | 51,227,579 | MDU6SXNzdWU1MTIyNzU3OQ== | 9,034 | Selection on MultiIndex wrong after applying .iloc[::n] on unsorted Series/DataFrame | {
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When slicing a Series/DataFrame which has a multilevel index which is not sorted on the first level, selecting on the first level with .ix or .loc returns an empty dataframe instead of the true values.
``` python
In [524]: s = pd.Series(range(30),index=pd.MultiIndex.from_arrays([["A"]*10+["C"]*10+["B"]*10,range(30... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9035 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9035/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9035/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9035/events | https://github.com/pandas-dev/pandas/pull/9035 | 51,230,569 | MDExOlB1bGxSZXF1ZXN0MjU2MzY5Mjg= | 9,035 | DOC: fix categorical comparison example (GH8946) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9036 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9036/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9036/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9036/events | https://github.com/pandas-dev/pandas/pull/9036 | 51,231,070 | MDExOlB1bGxSZXF1ZXN0MjU2MzcxNDE= | 9,036 | COMPAT: dateutil fixups for 2.3 (GH9021, GH8639) | {
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but going to reopen #8639
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https://api.github.com/repos/pandas-dev/pandas/issues/9037 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9037/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9037/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9037/events | https://github.com/pandas-dev/pandas/issues/9037 | 51,231,210 | MDU6SXNzdWU1MTIzMTIxMA== | 9,037 | PERF: json should process data column-by-column (and not use .values) | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-12-07T20:56:17Z | 2014-12-24T15:53:33Z | 2014-12-24T15:53:33Z | CONTRIBUTOR | null | xref #9027
So `to_json` first converts all the a DataFrame by using `.values`. This converts everything to object dtype (if its a mixed frame) and is pretty expensive perf wise.
If you do this column by column you get excellent perf (and tiny bit more complexity in the code).
cc @Komnomnomnom
@cpcloud
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https://api.github.com/repos/pandas-dev/pandas/issues/9038 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9038/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9038/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9038/events | https://github.com/pandas-dev/pandas/pull/9038 | 51,232,020 | MDExOlB1bGxSZXF1ZXN0MjU2Mzc1NTI= | 9,038 | DOC: expand docs on sql type conversion | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9039 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9039/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9039/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9039/events | https://github.com/pandas-dev/pandas/issues/9039 | 51,265,525 | MDU6SXNzdWU1MTI2NTUyNQ== | 9,039 | append & data_columns=True | {
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"descript... | closed | false | null | [] | null | 5 | 2014-12-08T07:34:55Z | 2014-12-11T11:34:49Z | 2014-12-11T11:34:49Z | NONE | null | Hello
i create a new store and i am trying to append it.
all is right when i did :
store.append("table", dataframe)
but when i did the whole thing with data_columns=dataframe.columns or data_columns=True
i can write the first append and then nothing ....
no more data input
tore.append("table", dataframe,data_columns=d... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9040 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9040/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9040/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9040/events | https://github.com/pandas-dev/pandas/pull/9040 | 51,265,725 | MDExOlB1bGxSZXF1ZXN0MjU2NDk4Njg= | 9,040 | Return from to_timedelta is forced to dtype timedelta64[ns]. | {
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I have also added more tests, and moved them to the `test_timedeltas` function (next to the other tests... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9041 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9041/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9041/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9041/events | https://github.com/pandas-dev/pandas/pull/9041 | 51,267,881 | MDExOlB1bGxSZXF1ZXN0MjU2NTExMTg= | 9,041 | ENH: Store in SQL using double precision | {
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"followers_url": "https://api.github.com/users/jr... | 17 | 2014-12-08T08:17:20Z | 2015-01-25T18:01:21Z | 2015-01-25T18:01:04Z | CONTRIBUTOR | null | Closes #9009 . @jorisvandenbossche -- do you think this should test/use single precision ? We could test for float32 perhaps? My own feeling is that this is the safer default.
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https://api.github.com/repos/pandas-dev/pandas/issues/9042 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9042/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9042/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9042/events | https://github.com/pandas-dev/pandas/issues/9042 | 51,291,959 | MDU6SXNzdWU1MTI5MTk1OQ== | 9,042 | API/ENH: query an HDF5 store with a named index | {
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... | 5 | 2014-12-08T11:22:11Z | 2021-04-11T06:01:14Z | null | CONTRIBUTOR | null | from [SO](http://stackoverflow.com/questions/27354281/query-term-is-not-valid-condition-none/27356827#27356827)
```
In [1]: df = pd.DataFrame.from_dict({'A':[1,2],'B':[100,200], 'C':[42,11]})
In [2]: df_a = df.set_index('A')
In [3]: df_a
Out[3]:
B C
A
1 100 42
2 200 11
In [4]: store = pd.HDFStore... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9043 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9043/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9043/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9043/events | https://github.com/pandas-dev/pandas/pull/9043 | 51,309,073 | MDExOlB1bGxSZXF1ZXN0MjU2NzAxOTU= | 9,043 | BUG: series.fillna() fails with quoted numbers | {
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... | 3 | 2014-12-08T14:44:13Z | 2015-05-09T16:05:40Z | 2015-05-09T16:05:40Z | NONE | null | Here's a simple example:
``` python
import pandas as pd
import numpy as np
x = pd.Series(range(5))
x.iloc[1] = np.nan
x.fillna(0) # works
x.fillna('foo') # works
x.fillna('0') # crash
```
in the function `_putmask_smart()`, two numpy arrays are compared to determine if they have compatible dtypes. However if one arr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9044 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9044/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9044/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9044/events | https://github.com/pandas-dev/pandas/pull/9044 | 51,314,088 | MDExOlB1bGxSZXF1ZXN0MjU2NzMzMzA= | 9,044 | Fix timedelta json on windows | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9045 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9045/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9045/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9045/events | https://github.com/pandas-dev/pandas/issues/9045 | 51,315,919 | MDU6SXNzdWU1MTMxNTkxOQ== | 9,045 | read_csv and read_table fail with some CSV files. May be related to universal-newline | {
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] | closed | false | null | [] | null | 6 | 2014-12-08T15:45:38Z | 2019-12-12T02:09:15Z | 2019-12-12T02:09:15Z | NONE | null | Using pandas 0.15.1
I have a csv file which unfortunately I cannot share (sanitizing it resolved the error) that gives me trouble when reading using the default (c) engine for parsing files. I switched to the python version which also failed but gave me the hint that it might be a problem with "universal-newline".
If ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9046 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9046/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9046/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9046/events | https://github.com/pandas-dev/pandas/issues/9046 | 51,316,614 | MDU6SXNzdWU1MTMxNjYxNA== | 9,046 | DataFrame.to_latex() should honor na_rep after formatter. | {
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"description": "np.nan, pd.NaT, pd.NA, d... | closed | false | null | [] | {
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```
In [3]: df = pd.DataFrame({'a': np.arange(3), 'b': [0.1, np.nan, 0.2]})
In [4]: df
Out[4]:
a b
0 0 0.1
1 1 NaN
2 2 0.2
In [5]: print(df.to_latex(formatters={'b': lambda x: '{:0.4f}'.format(x)}, na_rep='aaah'))
\begin{tabu... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9047 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9047/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9047/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9047/events | https://github.com/pandas-dev/pandas/pull/9047 | 51,376,349 | MDExOlB1bGxSZXF1ZXN0MjU3MTI1MTI= | 9,047 | TST: dateutil fixes (GH8639) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9048 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9048/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9048/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9048/events | https://github.com/pandas-dev/pandas/issues/9048 | 51,420,301 | MDU6SXNzdWU1MTQyMDMwMQ== | 9,048 | COMPAT: Floating point fractional hours for timedeltas gives unexpected precision issue | {
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... | 6 | 2014-12-09T12:12:51Z | 2020-03-31T04:31:46Z | null | NONE | null | Creating a timedelta with fractional hours gives an unexpected large round-off error.
```
>>> to_timedelta(1.0/3, unit='h')
Timedelta('0 days 00:19:59.998800')
```
This is indicates a precision around 2x10^-7 ( 1/(1000_60_60) ), which is less than a single precision float.
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"followers_url": "https://api.github.com/users/jr... | 4 | 2014-12-09T14:19:34Z | 2015-02-10T14:52:04Z | 2015-02-10T14:52:04Z | NONE | null | Problem:
data.sum(level=...) for multi-index table produce different result (lots of NAs) than groupby
in certain cases. It's also much slower than groupby. Seems that the new version
produced a cross join of the keys and produce NAs for pair of keys with no data, which makes
the result bigger and significantly slower... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9050 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9050/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9050/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9050/events | https://github.com/pandas-dev/pandas/pull/9050 | 51,553,489 | MDExOlB1bGxSZXF1ZXN0MjU4MTg5MTE= | 9,050 | BUG: fix PeriodConverter issue when given a list of integers (GH9012) | {
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Closes #9012
test and whatsnew are coming
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https://api.github.com/repos/pandas-dev/pandas/issues/9051 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9051/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9051/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9051/events | https://github.com/pandas-dev/pandas/issues/9051 | 51,578,584 | MDU6SXNzdWU1MTU3ODU4NA== | 9,051 | lexsort_depth not returning the correct number | {
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"descript... | closed | false | null | [] | null | 9 | 2014-12-10T16:27:04Z | 2014-12-11T16:35:25Z | 2014-12-10T22:11:21Z | NONE | null | ``` python
keys = [('a', 'b', 'c'), ('d', 'e', 'f', 'g', 'h'), ('i', 'j', 'k', 'l')]
pd.MultiIndex.from_tuples(keys).lexsort_depth
Out[106]: 5
```
work correctly while:
``` python
keys = [('spot_es', 'spot', 'es'),
('prod_de_wind_ecen', 'prod', 'de', 'wind', 'ecen'),
('avu_fr_maxe-1', 'avu', 'fr', 'maxe-1')]
pd.M... | {
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"followers_url": "https://api.github.com/users/jr... | 12 | 2014-12-10T19:47:53Z | 2017-01-28T15:02:37Z | 2016-02-15T20:28:58Z | CONTRIBUTOR | null | I didn't realize this was possible, and didn't see it in the docs.
```
df = pd.DataFrame({'A': [1, 2, 3], 'B': ['a', 'a', 'b'], 'C': [3, 4, 5]})
df.groupby('B').agg({'A': {'mean1': 'mean', 'med1': 'median'}, 'C': {'mean2': 'mean', 'med2': 'median'}})
```
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... | open | false | null | [] | null | 1 | 2014-12-11T10:03:00Z | 2017-11-24T15:18:30Z | null | MEMBER | null | If you do a time series plot:
```
s = pd.Series(np.random.randn(100), index=pd.date_range('1970-01-02', periods=100, freq='T'))
fig, ax = plt.subplots()
s.plot(ax=ax)
```
and then want to add a line through matplotlib using the index or datetime64 values, this does not work (it plots the data at a totally wrong place... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-12-11T10:10:25Z | 2015-04-14T16:14:49Z | 2015-04-14T16:14:49Z | MEMBER | null | I didn't directly find something about this, but is there a reason why the `Period(Index)` constructor does not take datetime64 values? As it does accept `datetime`:
```
In [15]: t = pd.Timestamp('2012-01-01')
In [16]: t.to_pydatetime()
Out[16]: datetime.datetime(2012, 1, 1, 0, 0)
In [17]: t.asm8
Out[17]: numpy.date... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9055 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9055/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9055/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9055/events | https://github.com/pandas-dev/pandas/pull/9055 | 51,670,153 | MDExOlB1bGxSZXF1ZXN0MjU4ODk3MTg= | 9,055 | TST: start tests for PeriodConverter | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2014-12-11T10:29:35Z | 2014-12-12T15:25:07Z | 2014-12-12T15:25:07Z | MEMBER | null | @jreback The tests I started related to PR #9050
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https://api.github.com/repos/pandas-dev/pandas/issues/9056 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9056/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9056/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9056/events | https://github.com/pandas-dev/pandas/issues/9056 | 51,672,194 | MDU6SXNzdWU1MTY3MjE5NA== | 9,056 | Period(Index) claims to be relative to 0001-01-01 00:00:00 | {
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... | 6 | 2014-12-11T10:50:54Z | 2017-06-01T19:59:44Z | 2017-06-01T19:59:44Z | MEMBER | null | See the docstring of PeriodIndex: https://github.com/pydata/pandas/blob/master/pandas/tseries/period.py#L557, it says:
```
A value of 1 is the period containing the Gregorian proleptic datetime Jan 1, 0001 00:00:00.
This ordinal representation is from the scikits.timeseries project.
For instance,
# construct peri... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9057 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9057/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9057/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9057/events | https://github.com/pandas-dev/pandas/issues/9057 | 51,676,364 | MDU6SXNzdWU1MTY3NjM2NA== | 9,057 | BUG: to_hdf failing with integer columns and data_columns=True | {
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"followers_url": "https://api.github.... | 1 | 2014-12-11T11:36:40Z | 2015-06-07T22:28:37Z | 2015-06-07T22:28:37Z | CONTRIBUTOR | null | ```
In [39]: N = 1000
In [40]: df = DataFrame(np.random.randint(0,8,size=N*400).astype('uint8').reshape(N,-1),index=pd.date_range('20130206',periods=N,freq='ms'))
In [41]: df.to_hdf('test.h5','df',mode='w',format='table')
In [42]: df.to_hdf('test.h5','df',mode='w',format='table',data_columns=True)
AttributeError: 'n... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9058 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9058/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9058/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9058/events | https://github.com/pandas-dev/pandas/pull/9058 | 51,686,674 | MDExOlB1bGxSZXF1ZXN0MjU4OTk1NzA= | 9,058 | DOC: fix-up docs for 0.15.2 release | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-12-11T13:32:05Z | 2014-12-11T13:41:59Z | 2014-12-11T13:41:59Z | MEMBER | null | @jreback some more clean-up of whatsnew
- some small fixes so now everything builds ok, ready for release
I also reworded a little bit the intro of the minor release (I thought was a bit more appropriate for minor release vs major release)
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https://api.github.com/repos/pandas-dev/pandas/issues/9059 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9059/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9059/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9059/events | https://github.com/pandas-dev/pandas/issues/9059 | 51,718,088 | MDU6SXNzdWU1MTcxODA4OA== | 9,059 | bunch of errored/failed tests with 0.15.2 | {
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"followers_url": "https://api.github.... | 3 | 2014-12-11T18:00:54Z | 2015-06-02T19:25:19Z | 2015-05-15T20:26:36Z | CONTRIBUTOR | null | tried to build on my debian box and got flooded... for now just a quick report and I would appreciate any help/advise
full build log http://www.onerussian.com/tmp/pandas_0.15.2-1_amd64.build
```
ERROR: test moving from daylight savings to standard time
ERROR: test moving from standard to daylight savings
ERROR: test_t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9060 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9060/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9060/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9060/events | https://github.com/pandas-dev/pandas/issues/9060 | 51,758,846 | MDU6SXNzdWU1MTc1ODg0Ng== | 9,060 | Python3: No module named 'openpyxl.style' | {
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"de... | closed | false | null | [] | null | 6 | 2014-12-12T00:59:14Z | 2014-12-14T01:41:50Z | 2014-12-14T01:31:39Z | NONE | null | There is no module named openpyxl.style on the Python3 version of openpyxl. There is, however a openpyxl.styles module in the namespace of openpyxl. But a simply name change update on line 577 of pandas/io/excel.py isn't the quick fix as there are other differences causing errors.
My offending code:
`diff_output = di... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9061 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9061/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9061/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9061/events | https://github.com/pandas-dev/pandas/pull/9061 | 51,763,005 | MDExOlB1bGxSZXF1ZXN0MjU5NDc4Mzk= | 9,061 | pivot & unstack with nan in the index | {
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on branch:
```
>>> df
a b c
0 R1 C1 10
1 R2 C2 15
2 NaN C3 17
3 R4 C4 20
>>> df.pivot('a', 'b', 'c').fillna('.')
b C1 C2 C3 C4
a
NaN . . 17 .
R1 10 . . .
R2 . 15 . .
R4 . . . 20
>>> df.pivot('b', 'a', 'c').... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9062 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9062/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9062/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9062/events | https://github.com/pandas-dev/pandas/issues/9062 | 51,763,525 | MDU6SXNzdWU1MTc2MzUyNQ== | 9,062 | File size increase by import/export from/to Stata | {
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"descript... | closed | false | null | [] | null | 3 | 2014-12-12T02:20:57Z | 2015-01-07T02:42:03Z | 2015-01-07T02:42:03Z | NONE | null | Hi,
I have noticed that importing/exporting data from/to Stata seems to increase file size a lot (sometimes more than double). I thought it mostly was caused by export to Stata, where string variables would be initially set to a length of 256 or something like that (usually after exporting I have to run the compress c... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9063 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9063/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9063/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9063/events | https://github.com/pandas-dev/pandas/issues/9063 | 51,799,441 | MDU6SXNzdWU1MTc5OTQ0MQ== | 9,063 | generic.py: NDFrame.truncate() parameter meaning swapped | {
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The code returns a `slice(before, after)` so `before` actually is the lower-bound and everything _after_ it is returned; and vice versa for `after`.
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https://api.github.com/repos/pandas-dev/pandas/issues/9064 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9064/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9064/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9064/events | https://github.com/pandas-dev/pandas/issues/9064 | 51,811,261 | MDU6SXNzdWU1MTgxMTI2MQ== | 9,064 | ENH: add to_offset method to Timedelta | {
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This works, but I think `td.to_offset()` makes sense
```
In [1]: td = Timedelta('1h')
In [2]: td
Out[2]: Timedelta('0 days 01:00:00')
In [7]: pd.DateOffset(hours=td.hours)
Out[7]: <DateOffset: kwds={'hours': 1}>
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https://api.github.com/repos/pandas-dev/pandas/issues/9065 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9065/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9065/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9065/events | https://github.com/pandas-dev/pandas/issues/9065 | 51,814,091 | MDU6SXNzdWU1MTgxNDA5MQ== | 9,065 | update() produces 'invalid type promotion' error when used with datetime columns and overwrite=False | {
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To reproduce:
``` python
import pandas as pd
df = pd.DataFrame({'A': [1, 2, 3],
'B': ['20140101', nan, '20140101'],
'C': [nan, nan, nan]})
df2 = pd.DataFrame({'A': [1, 2],
'B': ['20140104', '20140105'],
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https://api.github.com/repos/pandas-dev/pandas/issues/9066 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9066/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9066/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9066/events | https://github.com/pandas-dev/pandas/issues/9066 | 51,828,011 | MDU6SXNzdWU1MTgyODAxMQ== | 9,066 | expanduser in to_file methods | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-12-12T16:57:43Z | 2014-12-24T19:11:56Z | 2014-12-24T19:11:56Z | CONTRIBUTOR | null | Right now AFAIK there isn't any ~ expansion. Seems like nice, low-hanging fruit.
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https://api.github.com/repos/pandas-dev/pandas/issues/9067 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9067/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9067/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9067/events | https://github.com/pandas-dev/pandas/issues/9067 | 51,830,369 | MDU6SXNzdWU1MTgzMDM2OQ== | 9,067 | Strip header names? | {
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```
name, amount
Alice,100
Bob,200
```
Loaded dataframes can sometimes have column names with leading or trailing whitespace. Should these column names be stripped by default?
``` Python
In [4]: pd.read_csv('foo.csv').columns
Out[4]: Index([u'name', u' amount'], dtype='objec... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9068 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9068/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9068/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9068/events | https://github.com/pandas-dev/pandas/issues/9068 | 51,834,672 | MDU6SXNzdWU1MTgzNDY3Mg== | 9,068 | ENH: add StringMethods (e.g. .str) to Index | {
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`Series.str.strip()` works
but
`Index(Series(Index.values).str.strip())` would be necessary for an index
should be very straightforward to move the `.str` accessor to `IndexOpsMixin` (from Series)
to support this (would need to prevent Index sub-classes from using it though as they don't support string op... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9069 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9069/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9069/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9069/events | https://github.com/pandas-dev/pandas/issues/9069 | 51,870,679 | MDU6SXNzdWU1MTg3MDY3OQ== | 9,069 | Feature request: Categorical plotting | {
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"followers_url": "https://api.github.com/users/jorisva... | 5 | 2014-12-13T01:07:55Z | 2017-07-08T02:32:50Z | 2017-07-08T02:32:47Z | CONTRIBUTOR | null | In the case of the index being a DateTimeIndex, I think there's a nice easy default case for plotting a categorical column: Let each category assume one value on the y-axis (user-providable, or range(len(categories)) by default) and plot a symbol ('*' by default maybe) at every point in time the categorical value has a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9070 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9070/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9070/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9070/events | https://github.com/pandas-dev/pandas/pull/9070 | 51,885,373 | MDExOlB1bGxSZXF1ZXN0MjYwMjA1Nzg= | 9,070 | ENH: Open Document Format ODS support in read_excel() | {
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... | 59 | 2014-12-13T11:45:25Z | 2019-02-24T07:00:20Z | 2015-09-01T18:52:24Z | CONTRIBUTOR | null | This work should eventually lead to a reader and writer for ods spreadsheets (LibreOffice / OpenOffice Open Document Format). I am doing this work in the master of my clone of pandas. From the wiki I understood it is fine for me to commit to my master and rebase with upstream from time to time. Please let me know if I ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9071 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9071/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9071/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9071/events | https://github.com/pandas-dev/pandas/issues/9071 | 51,897,091 | MDU6SXNzdWU1MTg5NzA5MQ== | 9,071 | Feature request: add interval kwarg to pandas.io.data.get_data_yahoo | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-12-13T19:28:52Z | 2015-01-05T23:50:41Z | 2015-01-05T23:50:41Z | CONTRIBUTOR | null | Please, expose the interval flag of the Yahoo CSV API. Right now is hardcoded to have daily interval.
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https://api.github.com/repos/pandas-dev/pandas/issues/9072 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9072/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9072/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9072/events | https://github.com/pandas-dev/pandas/pull/9072 | 51,897,124 | MDExOlB1bGxSZXF1ZXN0MjYwMjUyNjE= | 9,072 | ENH: add interval kwarg to get_data_yahoo issue #9071 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9073 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9073/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9073/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9073/events | https://github.com/pandas-dev/pandas/issues/9073 | 51,900,493 | MDU6SXNzdWU1MTkwMDQ5Mw== | 9,073 | saving on memory can cost both memory and performance | {
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] | closed | false | null | [] | null | 2 | 2014-12-13T21:38:33Z | 2019-10-06T01:08:57Z | 2019-10-06T01:08:57Z | CONTRIBUTOR | null | xref: https://github.com/pydata/pandas/pull/8676#issuecomment-66888559
**memory cost**:
with `int16` labels:
```
$ python -m memory_profiler mem-profile.py
Filename: mem-profile.py
Line # Mem usage Increment Line Contents
================================================
4 80.156 MiB 0.000 MiB @... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9074 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9074/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9074/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9074/events | https://github.com/pandas-dev/pandas/pull/9074 | 51,910,674 | MDExOlB1bGxSZXF1ZXN0MjYwMzA5Nzc= | 9,074 | fixing highly confusing typo. | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-12-14T06:05:46Z | 2014-12-14T22:14:09Z | 2014-12-14T21:50:02Z | CONTRIBUTOR | null | The power of an 'e'.
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https://api.github.com/repos/pandas-dev/pandas/issues/9075 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9075/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9075/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9075/events | https://github.com/pandas-dev/pandas/issues/9075 | 51,929,421 | MDU6SXNzdWU1MTkyOTQyMQ== | 9,075 | change in MultiIndex.has_duplicates behavior from 0.15.0 -> 0.15.2 | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-12-14T19:51:04Z | 2014-12-18T11:40:22Z | 2014-12-18T11:40:22Z | NONE | null | The following code prints False when run with Pandas 0.15.0, but True with 0.15.2; I'm using Python 2.7.6 on Ubuntu 14.04.1 in both cases. Is this change in behavior expected? (I was using has_duplicates to detect duplicate tuples in the index.)
```
import pandas as pd
t = [(u'x', u'out', u'z', 5, u'y', u'in', u'z', 1... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9076 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9076/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9076/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9076/events | https://github.com/pandas-dev/pandas/pull/9076 | 51,933,506 | MDExOlB1bGxSZXF1ZXN0MjYwMzk4NjU= | 9,076 | Add SparseSeries.to_coo method, a single test and one example. | {
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closes #8048
This passes locally run nosetests but is failing on Travis. I think the latest Travis CI changes might have caused failures. I was able to get master to pass on Travis last week but now it is failing.
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https://api.github.com/repos/pandas-dev/pandas/issues/9077 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9077/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9077/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9077/events | https://github.com/pandas-dev/pandas/pull/9077 | 51,937,288 | MDExOlB1bGxSZXF1ZXN0MjYwNDEzODQ= | 9,077 | BUG: Bug in MultiIndex.has_duplicates when having many levels causes an indexer overflow (GH9075) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9078 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9078/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9078/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9078/events | https://github.com/pandas-dev/pandas/pull/9078 | 51,958,881 | MDExOlB1bGxSZXF1ZXN0MjYwNTI2ODE= | 9,078 | Closes #8943: COMPAT: periods needs coercion to np.int64 | {
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closes #8943
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https://api.github.com/repos/pandas-dev/pandas/issues/9079 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9079/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9079/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9079/events | https://github.com/pandas-dev/pandas/issues/9079 | 51,983,535 | MDU6SXNzdWU1MTk4MzUzNQ== | 9,079 | Pandas v0.15.2 breaks read_csv with skiprows, delim_whitespace=True and explicit naming of columns | {
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The latest version of pandas 0.15.2 can no longer read a file that was no problem before.
The file has the following format.
```
SMOSMANIA SMOSMANIA Narbonne 43.15000 2.95670 112.00 0.05 0.05 ThetaProbe-ML2X
2007/01/01 01:00 0.2140 U M
2007/01/01 02:00 0.2140 U M
2007/01/01 03:0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9080 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9080/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9080/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9080/events | https://github.com/pandas-dev/pandas/issues/9080 | 51,989,999 | MDU6SXNzdWU1MTk4OTk5OQ== | 9,080 | Problem assigning values to a 1d slice of Panel with MultiIndex along major axis | {
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```
import pandas as pd
import numpy as np
pn = pd.Panel(np.zeros((3, 3, 3)))
pn.loc[0, :, 0] = [1, 2, 3]
pn.major_axis =... | {
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"color": "AD7FA8"... | closed | false | null | [] | null | 3 | 2014-12-15T14:28:43Z | 2014-12-23T18:28:36Z | 2014-12-23T18:28:36Z | NONE | null | Now rolling functions like _rolling_mean_ give NaN's if the window size is outside the input series. I would like to have an extra option that the window size shrinkes if the window is outside the input series. Or to put it different: use an expanding mean for the first values and the rolling mean for all the intermedi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9082 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9082/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9082/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9082/events | https://github.com/pandas-dev/pandas/issues/9082 | 51,996,222 | MDU6SXNzdWU1MTk5NjIyMg== | 9,082 | BUG: "index_col=False" not working when "usecols" is specified in read_csv | {
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```
[9]: cat test.csv... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9083 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9083/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9083/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9083/events | https://github.com/pandas-dev/pandas/issues/9083 | 51,998,905 | MDU6SXNzdWU1MTk5ODkwNQ== | 9,083 | BUG: error in handling a sqlalchemy type with arguments (instantiated type, not class) | {
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```
times = ['201412120154', '201412110254']
df = pd.DataFrame()
df['time'] = pd.to_datetime(times, utc=True)
df.time.to_sql('test', engine, dtype={'time': sqlalchemy.TIMESTAMP(timezone=True)})
```
The error ... | {
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... | 2 | 2014-12-15T16:21:49Z | 2021-04-12T04:38:51Z | null | MEMBER | null | `pd.io.sql.get_schema` can be used to see the schema 'create table' statement. This function should support including the index (which is actually the default for `to_sql`)
```
In [31]: df = pd.DataFrame({'col':[1,2,3]}, index=pd.date_range('2012-01-01', periods=3))
In [33]: print pd.io.sql.get_schema(df, 'test_schem... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9085 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9085/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9085/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9085/events | https://github.com/pandas-dev/pandas/issues/9085 | 52,008,988 | MDU6SXNzdWU1MjAwODk4OA== | 9,085 | BUG: Timestamps in object column not written as DateTime data in to_sql | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-12-15T16:44:17Z | 2014-12-20T22:30:13Z | 2014-12-20T22:30:13Z | MEMBER | null | When you have datetime data with timezone info attached, the data is stored as `Timestamp` objects in a `object` dtyped column, instead of in a ´datetime64´ column (as this cannot hold the timezone info).
But, this causes `to_sql` to gives this the `TEXT` type:
With a postgresql engine:
```
In [48]: times = ['201412... | {
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"followers_url": "https://api.github... | 2 | 2014-12-15T16:49:41Z | 2018-11-08T14:55:50Z | 2018-11-08T14:55:50Z | MEMBER | null | This currently works a bit for datetime values in the index (not in the columns, reason for this is that is then are object columns: #9085).
I say 'a bit', as it does give a 'timestamp with time zone' type (example for postgresql), but it is the time localized in your local timezone (I suppose because this is the way ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9087 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9087/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9087/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9087/events | https://github.com/pandas-dev/pandas/issues/9087 | 52,010,877 | MDU6SXNzdWU1MjAxMDg3Nw== | 9,087 | SQL: test with oldest supported sqlalchemy | {
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... | 2 | 2014-12-15T16:58:53Z | 2019-12-30T18:51:39Z | 2019-12-30T18:51:39Z | MEMBER | null | Noticed when looking at #9083 that we used an sqlalchemy feature in #8926 that is not supported in at least sqlalchemy
Concrete, it is about `import sqlalchemy.sql.type_api as type_api` (https://github.com/pydata/pandas/blob/v0.15.2/pandas/io/sql.py#L1162). I cannot import this 0.8.2 (and in any case, this should bet... | {
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This line is undocumented and there is no way to remove it without a hack. ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9089 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9089/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9089/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9089/events | https://github.com/pandas-dev/pandas/issues/9089 | 52,040,557 | MDU6SXNzdWU1MjA0MDU1Nw== | 9,089 | Period.end_time should be exclusive or Period should provide duration property | {
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... | 7 | 2014-12-15T21:24:10Z | 2018-11-16T19:36:06Z | 2018-11-16T17:24:13Z | NONE | null | A user may expect that the end_time of a Period minus the start_time of a Period returns its duration. Unfortunately, the end_time of a Period is inclusive, consequently, subtracting start from end yields an incorrect period duration:
```
jan = Period('2014-01', freq='M')
(jan.end_time - jan.start_time).days # returns... | {
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Let me know if this makes sense
Problem mentioned in issue 8979 too
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https://api.github.com/repos/pandas-dev/pandas/issues/9091 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9091/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9091/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9091/events | https://github.com/pandas-dev/pandas/issues/9091 | 52,064,845 | MDU6SXNzdWU1MjA2NDg0NQ== | 9,091 | Panel.describe() method documented but raises NotImplementedError | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2014-12-16T02:03:07Z | 2018-07-06T20:21:06Z | 2017-07-10T21:06:38Z | NONE | null | Panel.describe() docs for v15.2 [here](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Panel.describe.html)
**Environment:**
fedora 20
pandas 15.2
Python 2.7.5
IPython 2.3.0
**To duplicate:**
```
$ pip install --upgrade pandas
In [8]: thresh = pd.Panel({'1': pd.DataFrame(pd.np.arange(2,3)), '2': pd.Da... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9092 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9092/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9092/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9092/events | https://github.com/pandas-dev/pandas/issues/9092 | 52,066,930 | MDU6SXNzdWU1MjA2NjkzMA== | 9,092 | Unexpected behaviour / potential bug in Dataframe.shift() with duplicated column titles | {
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I have recently come across an unexpexted behaviour of the dataframe "shift" function.
When column titles are duplicated (or present more often), a column-specific shift using index-based positioning (by "iloc") does not only shift the specified columns, but all columns sharing the same name. From the behaviour I ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9093 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9093/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9093/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9093/events | https://github.com/pandas-dev/pandas/issues/9093 | 52,084,453 | MDU6SXNzdWU1MjA4NDQ1Mw== | 9,093 | [Feature Request] Add concise xlabel=, ylabel=, option in plot() method | {
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"followers_url": "https://api.github.com/users/j... | 9 | 2014-12-16T08:15:59Z | 2020-06-26T00:37:09Z | 2020-06-26T00:37:09Z | CONTRIBUTOR | null | The current [plot()](http://pandas.pydata.org/pandas-docs/version/0.15.1/generated/pandas.DataFrame.plot.html#pandas.DataFrame.plot) method for Dataframe cannot set the x/y label in it. [Result](http://stackoverflow.com/questions/21487329/add-x-and-y-labels-to-a-pandas-plot?lq=1) is more lines of code for just doing th... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9094 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9094/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9094/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9094/events | https://github.com/pandas-dev/pandas/issues/9094 | 52,109,643 | MDU6SXNzdWU1MjEwOTY0Mw== | 9,094 | API: datetimeindex subtraction | {
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"followers_url": "https://api.github.com/users/jr... | 14 | 2014-12-16T12:58:35Z | 2016-09-13T21:34:01Z | 2015-03-11T10:21:41Z | CONTRIBUTOR | null | from [SO](http://stackoverflow.com/questions/27502406/convert-pandas-datetimeindex-to-fractional-day-of-year) and previous discussions
currently you cannot subtract 2 datetimeindexes ('-' is actually a set op). This is the ONLY valid numerical type of operation (e.g. you cannot add dti).
We current support pretty muc... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9095 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9095/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9095/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9095/events | https://github.com/pandas-dev/pandas/issues/9095 | 52,183,033 | MDU6SXNzdWU1MjE4MzAzMw== | 9,095 | v0.15.1 breaks index set operations | {
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"followers_url": "https://api.github.com/users/jr... | 12 | 2014-12-16T23:41:59Z | 2015-03-11T10:21:41Z | 2015-03-11T10:21:41Z | MEMBER | null | In 0.15.0, the `-` index set operation raises a warning as is explained in the whatsnew docs: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#deprecations
```
In [1]: pd.__version__
Out[1]: '0.15.0'
In [2]: idx = pd.Index([1,2])
In [3]: idx
Out[3]: Int64Index([1, 2], dtype='int64')
In [4]: idx - idx
C:\An... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9096 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9096/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9096/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9096/events | https://github.com/pandas-dev/pandas/issues/9096 | 52,217,764 | MDU6SXNzdWU1MjIxNzc2NA== | 9,096 | Groupby "negative dimensions are not allowed" error and bad key behaviour when there are NaNs values. | {
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"followers_url": "https://api.github.com/users/jr... | 10 | 2014-12-17T09:26:06Z | 2020-07-06T11:30:42Z | 2015-01-31T16:23:42Z | NONE | null | On a groupby with a composed key if the product of all possible values is bigger than 2^63 we get a `ValueError "negative dimensions are not allowed"` when we call `len(grouped_data)`.
A simple version to reproduce it:
``` python
values = range(55109)
data = pd.DataFrame.from_dict({'a': values, 'b': values, 'c': valu... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9097 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9097/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9097/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9097/events | https://github.com/pandas-dev/pandas/issues/9097 | 52,219,664 | MDU6SXNzdWU1MjIxOTY2NA== | 9,097 | TST: start testing with SQL server via appveyor CI | {
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We could add tests for SQL Server to test_sql.py, as AppVeyor supports this.
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https://api.github.com/repos/pandas-dev/pandas/issues/9098 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9098/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9098/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9098/events | https://github.com/pandas-dev/pandas/issues/9098 | 52,223,628 | MDU6SXNzdWU1MjIyMzYyOA== | 9,098 | index_col and usecols do not work reliably together in read_csv | {
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... | 10 | 2014-12-17T10:24:44Z | 2019-10-21T19:52:14Z | null | NONE | null | This code shows 3 situations.
``` python
import pandas as pd
from io import StringIO
import random
import sys
def fun(s,n,u):
random.seed(s)
names = [str(e) for e in range(1, n)]
data = ','.join([str(e) for e in names])
usecols = random.sample(names, u)
index_col = random.choice(usecols)
prin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9099 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9099/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9099/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9099/events | https://github.com/pandas-dev/pandas/issues/9099 | 52,243,312 | MDU6SXNzdWU1MjI0MzMxMg== | 9,099 | BUG: DataFrame constructor ignores copy=True argument if dtype is set | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9100 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9100/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9100/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9100/events | https://github.com/pandas-dev/pandas/issues/9100 | 52,273,870 | MDU6SXNzdWU1MjI3Mzg3MA== | 9,100 | 0.15.2: Iteration over datetime index | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-12-17T18:26:03Z | 2014-12-19T21:03:11Z | 2014-12-19T21:03:11Z | NONE | null | When iterating over a Series of datetime objects that have timezone info on them, the returned value has the timezone info but also alters the time according to that timezone info, as seen in example below:
`time_points` is the index of a dataframe with values:
```
[2014-12-01 03:32:39.987000-08:00, ..., 2014-12-01 0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9101 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9101/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9101/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9101/events | https://github.com/pandas-dev/pandas/pull/9101 | 52,314,081 | MDExOlB1bGxSZXF1ZXN0MjYyNzA4MTY= | 9,101 | overflow bug in multi-index when checking for duplicates | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-12-18T01:10:15Z | 2014-12-21T13:52:03Z | 2014-12-18T11:40:22Z | CONTRIBUTOR | null | closes https://github.com/pydata/pandas/issues/9075
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