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https://api.github.com/repos/pandas-dev/pandas/issues/11103 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11103/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11103/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11103/events | https://github.com/pandas-dev/pandas/issues/11103 | 106,558,035 | MDU6SXNzdWUxMDY1NTgwMzU= | 11,103 | SettingWithCopyWarning and pd.cut | {
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```
for chrom, df in grouped:
bins = np.arange(0, 2e6, 1e5)
df.ix[:,'Bins'] = pd.cut(df.Pos, bins)
```
A value is trying to be set on a copy of a slice from a DataF... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11104 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11104/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11104/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11104/events | https://github.com/pandas-dev/pandas/pull/11104 | 106,561,736 | MDExOlB1bGxSZXF1ZXN0NDUwNTE5ODU= | 11,104 | DOC: fix ref to template for plot accessor | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11105 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11105/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11105/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11105/events | https://github.com/pandas-dev/pandas/issues/11105 | 106,573,323 | MDU6SXNzdWUxMDY1NzMzMjM= | 11,105 | Pandas options data not working | {
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RemoteDataError: Parsed URL 'http://finance.yahoo.com/q/op?s=SPY' has no rootelement
Actual code:
from pandas.io.data import Options
SPYD = Options('spy', 'yahoo')
data = SPYD.get_all_data()
My pandas version is 0.16.2
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https://api.github.com/repos/pandas-dev/pandas/issues/11106 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11106/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11106/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11106/events | https://github.com/pandas-dev/pandas/issues/11106 | 106,573,544 | MDU6SXNzdWUxMDY1NzM1NDQ= | 11,106 | TST/COMPAT: update ci when available | {
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... | 1 | 2015-09-15T14:52:00Z | 2017-02-15T18:56:05Z | 2017-02-15T18:56:05Z | CONTRIBUTOR | null | these are left out of `ci/requirements-3.5.txt` as not available yet
- `beautiful-soup`
- `bottleneck`
these are left out of `ci/requirements-3.5.txt` as not available yet
- `blosc` (prob need a new version)
- `nose`, need to use the newest version as a deprecation warning in `inspect`
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https://api.github.com/repos/pandas-dev/pandas/issues/11107 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11107/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11107/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11107/events | https://github.com/pandas-dev/pandas/issues/11107 | 106,577,857 | MDU6SXNzdWUxMDY1Nzc4NTc= | 11,107 | Pandas options data not working | {
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RemoteDataError: Parsed URL 'http://finance.yahoo.com/q/op?s=SPY' has no rootelement
Actual code:
from pandas.io.data import Options
SPYD = Options('spy', 'yahoo')
data = SPYD.get_all_data()
My pandas version is 0.16.2
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https://api.github.com/repos/pandas-dev/pandas/issues/11108 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11108/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11108/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11108/events | https://github.com/pandas-dev/pandas/issues/11108 | 106,580,681 | MDU6SXNzdWUxMDY1ODA2ODE= | 11,108 | COMPAT: return instead of raising StopIteration in generator | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-09-15T15:25:08Z | 2015-11-18T11:36:54Z | 2015-11-18T11:36:54Z | CONTRIBUTOR | null | And a couple other changes for [PEP479](https://www.python.org/dev/peps/pep-0479/) to avoid warnings. Will submit a PR if others agree.
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https://api.github.com/repos/pandas-dev/pandas/issues/11109 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11109/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11109/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11109/events | https://github.com/pandas-dev/pandas/issues/11109 | 106,581,537 | MDU6SXNzdWUxMDY1ODE1Mzc= | 11,109 | Pandas options data not working (Data Reader) | {
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RemoteDataError: Parsed URL 'http://finance.yahoo.com/q/op?s=SPY' has no rootelement
Actual code:
from pandas.io.data import Options
SPYD = Options('spy', 'yahoo')
data = SPYD.get_all_data()
My pandas version is 0.16.2
NO... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11110 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11110/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11110/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11110/events | https://github.com/pandas-dev/pandas/pull/11110 | 106,582,460 | MDExOlB1bGxSZXF1ZXN0NDUwNjQ0Njg= | 11,110 | COMPAT: Add Google BigQuery support for python 3 #11094 | {
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Adds gbq support for python 3.4
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this is with `pandas-0.17rc1`
```
......F......E..FF...FE..F./home/jreback/miniconda/envs/pandas/lib/python2.7/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11112 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11112/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11112/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11112/events | https://github.com/pandas-dev/pandas/issues/11112 | 106,584,044 | MDU6SXNzdWUxMDY1ODQwNDQ= | 11,112 | COMPAT/TST: warnings for sql installs on python 3.5 | {
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... | 2 | 2015-09-15T15:39:56Z | 2019-02-03T03:58:37Z | 2019-02-03T03:58:36Z | CONTRIBUTOR | null | These are actually from the current version of `nose` (e.g. it has a deprecation warning in inspect).
currently I have `sqlalchemy` and friends not installing on 3.5 (though they _can_ be), they are commented out in `requirements-3.5.txt`
So can do things like this (e.g. I did this in `test_pytables.py`), until a new... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11113 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11113/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11113/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11113/events | https://github.com/pandas-dev/pandas/issues/11113 | 106,586,016 | MDU6SXNzdWUxMDY1ODYwMTY= | 11,113 | qcut does not handle infinite values correctly | {
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"id": 16... | open | false | null | [] | null | 2 | 2015-09-15T15:49:43Z | 2021-10-16T17:17:26Z | null | CONTRIBUTOR | null | Calling qcut with infinite values in a pandas Series should be a well-defined operation, but it tends to produce wrong results or raise (un-obvious) exceptions. I'm using the following snippet to test:
```
data = range(10) + [np.inf] * n
s = pd.Series(data, index=data)
pd.qcut(s, [0.1, 0.9])
```
When called with n=1,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11114 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11114/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11114/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11114/events | https://github.com/pandas-dev/pandas/pull/11114 | 106,594,855 | MDExOlB1bGxSZXF1ZXN0NDUwNzE5MTY= | 11,114 | COMPAT: compat for python 3.5, #11097 | {
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- update install / compat docs for 3.5
- use visit_Call based on the version of python
- skip if html5lib is not installed in test_data
- bug in nose causes deprecation warning in some pytables tests
- remove superfluous socket timeout
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https://api.github.com/repos/pandas-dev/pandas/issues/11115 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11115/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11115/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11115/events | https://github.com/pandas-dev/pandas/issues/11115 | 106,597,397 | MDU6SXNzdWUxMDY1OTczOTc= | 11,115 | interpolate erroneously fills NaNs at start of series when limit_direction == 'both' | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-09-15T16:42:54Z | 2015-09-16T23:04:33Z | 2015-09-16T23:04:33Z | CONTRIBUTOR | null | PR #10691 had a bug in computing the NaN mask in certain cases.
Specifically, when a NaN occurs within `limit` of the beginning of the series and `limit_direction` is set to `'both'`, the interpolation code will erroneously interpolate these NaNs rather than masking them off.
From the PR:
```
In [43]: ser = pd.Serie... | {
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0.16.2:
``` python
In [2]: import pandas as pd
...: from StringIO import StringIO
...: x="""foo,bar
...: 2015-09-14,True
...: 2015-09-15,
...: """
...: df=pd.read_csv(StringIO(x),sep=',').convert_objects('coerce')
...: df.info()
<cl... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11117 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11117/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11117/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11117/events | https://github.com/pandas-dev/pandas/issues/11117 | 106,636,775 | MDU6SXNzdWUxMDY2MzY3NzU= | 11,117 | read_clipboard() Windows to Linux | {
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] | closed | false | null | [] | null | 5 | 2015-09-15T20:15:16Z | 2015-09-17T17:27:39Z | 2015-09-17T17:27:39Z | NONE | null | I have an IPython (Jupyter) Notebook running on a webserver (Ubuntu) and am trying to read_clipboard() from a Windows computer. I have xclip installed on the ubuntu machine. Here is the code:
```
import pandas as pd
from pandas import Series,DataFrame
test = pd.read_clipboard()
print test
```
It appears that the ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11118 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11118/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11118/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11118/events | https://github.com/pandas-dev/pandas/issues/11118 | 106,665,579 | MDU6SXNzdWUxMDY2NjU1Nzk= | 11,118 | Possible bug!! Replacing str in dataframe delete entire number | {
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"descript... | closed | false | null | [] | null | 4 | 2015-09-15T22:59:19Z | 2015-09-16T00:37:19Z | 2015-09-16T00:16:58Z | NONE | null | ```
df.head()
OSymbol
0 .GGP:150918:C:18.0
1 .GGP:150918:C:19.0
2 .GGP:150918:C:20.0
3 .GGP:150918:C:21.0
4 .GGP:150918:C:22.0
df['OSymbol'].str.replace(".0", "")
0 .GGP:1918:C:18
1 .GGP:1918:C:19
2 .GGP:1918:C:
3 .GGP:1918:C:21
4 .GGP:1918:C:22
```
L... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11119 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11119/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11119/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11119/events | https://github.com/pandas-dev/pandas/issues/11119 | 106,665,773 | MDU6SXNzdWUxMDY2NjU3NzM= | 11,119 | Slicing multiple DataFrame columns doesn't work with boolean column names | {
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... | 3 | 2015-09-15T23:01:11Z | 2021-04-18T23:44:29Z | null | CONTRIBUTOR | null | Setup:
```
import pandas as pd
df = pd.DataFrame({True: [1,2,5,9],
False: [6,1,13,8]})
```
`df[True]` and `df[False]` work fine; but `df[[True,False]]` throws an exception:
```
---------------------------------------------------------------------------
ValueError Tr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11120 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11120/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11120/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11120/events | https://github.com/pandas-dev/pandas/pull/11120 | 106,681,671 | MDExOlB1bGxSZXF1ZXN0NDUxMjM0MTA= | 11,120 | BF: do not assume that expanduser would replace all ~ | {
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Better to check either new path is absolute. Removed 1 test which had no value
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This change is required for #11110
At the same time, I also implemented the following list functions: `list_dataset... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11122 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11122/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11122/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11122/events | https://github.com/pandas-dev/pandas/issues/11122 | 106,754,601 | MDU6SXNzdWUxMDY3NTQ2MDE= | 11,122 | BLD: Import error during python 2.7 builds on travis | {
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Recently the Python 2.7 builds on travis have been failing with the same error message.
```
Traceback (most recent call last):
File "setup.py", line 566, in <module>
**setuptools_kwargs)
File "/home/travis/miniconda/envs/pandas/lib/python2.7/distutils/core.py... | {
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... | 16 | 2015-09-16T11:42:39Z | 2019-06-09T11:53:21Z | 2019-06-09T11:48:38Z | CONTRIBUTOR | null | Hi everyone,
I just stumbled across this odd behaviour:
For a daily time series, I would expect `resample('B', how='last')` to be equivalent to selecting rows whose weekday is not Saturday or Sunday. However, `resample` groups together Fridays, Saturdays and Sundays and hence we get Sunday's value on Friday.
In... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11124 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11124/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11124/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11124/events | https://github.com/pandas-dev/pandas/pull/11124 | 106,827,646 | MDExOlB1bGxSZXF1ZXN0NDUyMDQyMjk= | 11,124 | BUG: Fix computation of invalid NaN indexes for interpolate. | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-09-16T18:03:12Z | 2015-09-16T23:04:13Z | 2015-09-16T23:04:10Z | CONTRIBUTOR | null | Fixes issue #11115.
This change fixes up a couple edge cases for the computation of invalid NaN indexes for interpolation limits.
I've also added a test explicitly for the reported bug (and similar behaviors at the opposite end of the series) in #11115.
/cc @jreback
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https://api.github.com/repos/pandas-dev/pandas/issues/11125 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11125/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11125/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11125/events | https://github.com/pandas-dev/pandas/issues/11125 | 106,838,325 | MDU6SXNzdWUxMDY4MzgzMjU= | 11,125 | to_dict(orent='records') converted to strange dict | {
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"descript... | closed | false | null | [] | null | 3 | 2015-09-16T18:53:50Z | 2015-09-16T20:13:03Z | 2015-09-16T20:13:03Z | NONE | null | Dear gurus,
I am trying to convert a DataFrame to dict and then to json. However, json.dumps or simplejson.dumps kept reporting error "TypeError: _ is not JSON serializable". I created a small code to reproduce the problem. Just copy and paste to run those codes:
df1=pd.DataFrame([{'t1':1,'t2':0}])
dict1=df1.to_dict(o... | {
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... | 18 | 2015-09-16T19:55:07Z | 2020-04-14T05:20:26Z | 2020-04-14T05:20:26Z | CONTRIBUTOR | null | http://stackoverflow.com/questions/32553207/values-missing-when-loaded-from-pandas-hdf5-file/32587108?noredirect=1#comment53034458_32587108
e.g.
if I
```
df.to_hdf('foo.h5','df',encoding='utf-8')
```
then
```
pd.read_hdf('foo.h5','df')
```
should pick up the encoding for each table (unless the user overrides by ... | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2015-09-16T21:02:57Z | 2015-09-16T23:01:46Z | 2015-09-16T23:01:46Z | CONTRIBUTOR | null | closes #11122
dependency resolution in the `pandas` channel is a bit challenging as the current script tries to install all deps up front before building. But `statsmodels` requires pandas, so a current version is installed (e.g. the rc), and several of the deps are changed.
So fixed, but installing only the build ... | {
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```
In [1]: import calendar
In [25]: s = pd.Series(list(range(10)), pd.date_range('2015-09-01', '2015-09-10'))
In [26]: s2 = s.to_frame('value').assign(weekday=Series(s.index.week... | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2015-09-16T23:13:18Z | 2015-09-17T11:45:05Z | 2015-09-17T11:45:05Z | CONTRIBUTOR | null | Related to #10160 / PR https://github.com/pydata/pandas/pull/10269
```
In [2]: from datetime import timedelta
...: from pandas import *
...: td_as_int = [1, 2, 3, 4]
...:
...: def create_data(constructor):
...: return dict((i, {constructor(s): 2*i}) for i, s in enumerate(td_as_int))
...:
...: data_timedelta64 =... | {
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... | 2 | 2015-09-16T23:38:24Z | 2021-04-18T23:46:14Z | null | CONTRIBUTOR | null | Docs currently explicitly mention float64 as the type of columns for `expanding_max` and `expanding_min`, and indeed, it does a conversion to float64 for other types:
```
In [6]: x = pd.date_range('2008/01/01', periods=3).to_series()
In [7]: x
Out[7]:
2008-01-01 2008-01-01
2008-01-02 2008-01-02
2008-01-03 2008... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11131 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11131/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11131/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11131/events | https://github.com/pandas-dev/pandas/pull/11131 | 106,886,556 | MDExOlB1bGxSZXF1ZXN0NDUyMzc3NjE= | 11,131 | ERR: make sure raising TypeError on invalid nanops reductions xref #10472 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11132 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11132/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11132/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11132/events | https://github.com/pandas-dev/pandas/issues/11132 | 106,889,390 | MDU6SXNzdWUxMDY4ODkzOTA= | 11,132 | API: gbq new methods naming | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2015-09-17T00:19:12Z | 2015-09-25T09:13:57Z | 2015-09-25T09:13:57Z | CONTRIBUTOR | null | we need to make the API's more explicit/consistent.
```
create_table
delete_table
table_exists
```
should these be
```
table_create
table_delete
table_exists
```
cc @parthea
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https://api.github.com/repos/pandas-dev/pandas/issues/11133 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11133/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11133/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11133/events | https://github.com/pandas-dev/pandas/pull/11133 | 106,895,595 | MDExOlB1bGxSZXF1ZXN0NDUyNDM0MjI= | 11,133 | API: convert_objects, xref #11116, instead of warning, raise a ValueError | {
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This is a lot more noisy that the current impl. It pretty much raises on the old-style input if it had `coerce` in it. This is correct as the actual behavior of `coerce` has changed (in that it now it much more strict).
errror on old-style input
- raise a ValueError for df.convert_objects('coerce')
- ra... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11134 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11134/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11134/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11134/events | https://github.com/pandas-dev/pandas/pull/11134 | 106,895,602 | MDExOlB1bGxSZXF1ZXN0NDUyNDM0Mjg= | 11,134 | BUG: nested construction with timedelta #11129 | {
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Per discussion in issue this adds similar hash equality to `_Timedelta` / `datetime.timedelta`
that exists for `_Timestamp` / `datetime.datime`.
I tried inlining `_Timedelta._ensure_components` and it actually hurt performance a bit, so I left it
as a plain `def` but did build a seperate `_has_ns` check... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11136 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11136/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11136/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11136/events | https://github.com/pandas-dev/pandas/issues/11136 | 107,048,858 | MDU6SXNzdWUxMDcwNDg4NTg= | 11,136 | Plot uses incorrect colors when columns have the same name | {
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"followers_url": "https://api.github.com/users/j... | 2 | 2015-09-17T18:51:21Z | 2020-03-12T04:52:29Z | 2020-03-12T04:52:29Z | NONE | null | It seems like the `plot` function jumbles up the colors when columns in a DataFrame have the same name:
``` python
pd.concat([pd.DataFrame({'b': [0, 1, 0], 'a': [1, 2, 3]}), pd.DataFrame({'a': [2, 4, 6]})], axis=1).plot();
```
![image](https://cloud.githubusercontent.com/assets/3666725/9942860/5770cf74-5d32-11e5-98b9... | {
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'0.17.0rc1+31.g9be2180'
and a column of tuples like so:
``` python
df.BINNING_SET.head()
TIME_OF_INT
2014-10-18 07:36:19.926570 (0, 1, 319, 11)
2014-10-18 07:36:19.926570 (0, 1, 441, 11)
2014-10-18 07:36:59.675040 (52, 4, 89, 115)
2014-10-18 07:36:59.675040 (2, 34, 96, 115)
2014-10-18 07:55:27.9... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11138 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11138/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11138/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11138/events | https://github.com/pandas-dev/pandas/pull/11138 | 107,061,768 | MDExOlB1bGxSZXF1ZXN0NDUzMzQyMzI= | 11,138 | TST: Verify fix for buffer overflow in read_csv with engine='c' | {
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``` python
pd.SparseSeries([1.] * 10) # works
pd.SparseSeries([1.] * 100) # error
```
I've copied the error below:
```
.../miniconda/lib/python2.7/site-packages/pandas/core/format.pyc in __init__(self, series, buf, length, header... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11140 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11140/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11140/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11140/events | https://github.com/pandas-dev/pandas/pull/11140 | 107,114,267 | MDExOlB1bGxSZXF1ZXN0NDUzNjE5Mzk= | 11,140 | BUG: remove midrule in latex output with header=False | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2015-09-18T01:56:09Z | 2015-10-09T13:21:28Z | 2015-10-09T13:21:28Z | CONTRIBUTOR | null | This bug fix addresses issue #7124. If `to_latex` is called with option `header=False`, the output should not contain a `\midrule` which is used to separate the column headers from the data.
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https://api.github.com/repos/pandas-dev/pandas/issues/11141 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11141/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11141/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11141/events | https://github.com/pandas-dev/pandas/pull/11141 | 107,115,699 | MDExOlB1bGxSZXF1ZXN0NDUzNjI1MTU= | 11,141 | BUG: Issue in the gbq module when authenticating on remote servers #8489 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11142 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11142/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11142/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11142/events | https://github.com/pandas-dev/pandas/issues/11142 | 107,189,460 | MDU6SXNzdWUxMDcxODk0NjA= | 11,142 | PERF: infer_datetime_format fails without zero-padding | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-09-18T12:06:01Z | 2015-09-20T19:21:37Z | 2015-09-20T19:21:37Z | CONTRIBUTOR | null | I think this can be fixed by just padding tokens in the inference step. The dates _do_ parse, just always fall back to the slow path, even with `infer_datetime_format=True`
```
In [22]: from pandas.tseries.tools import _guess_datetime_format
In [23]: _guess_datetime_format('02/02/2014')
Out[23]: '%m/%d/%Y'
In [24]:... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11143 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11143/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11143/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11143/events | https://github.com/pandas-dev/pandas/issues/11143 | 107,194,394 | MDU6SXNzdWUxMDcxOTQzOTQ= | 11,143 | ENH: scatter_matrix doesn't handle columns with dtype 'pd.Categorical' or any other non-numeric | {
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Right now, all columns of `DataFrame` which aren't numeric are dropped before visualization procedure of `scatter_matrix`.
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I've added preliminary tests for openpyxl >= 2.2 styles. Unfortunately, I don't know how to get a whole test class to be skipped so tests will only run with either the Openpyxl20 or Openpyxl22 test class disabled, depending upon which version is installed. I hope this can be fixed fairly easily. Some co... | {
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Testing with tox locally I get 1 failure using either matplotlib 1.4 or 1.5. I may have messed up my tox config though. Still need to cleanup a bunch of stuff, I just threw in changes to get each test passing as I went.
release notes et. al com... | {
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-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
groupby_transform_series2 | 6.3464 | 167.3844 | 0.037... | {
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fix for the bug: Convert datetimelike index to strings with astype(str)
going to send pull request for test
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https://api.github.com/repos/pandas-dev/pandas/issues/11149 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11149/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11149/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11149/events | https://github.com/pandas-dev/pandas/pull/11149 | 107,349,827 | MDExOlB1bGxSZXF1ZXN0NDU0ODIwMDM= | 11,149 | API: multi-line, not inplace eval | {
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closes #8664
This is just a proof of concept at this point - the idea is to allow multiple assignments within an eval block, and also include an `inplace` argument (currently default True to match old behavior, although maybe that should be changed) for chaining.
```
In [15]: df = pd.DataFrame({'a': np.l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11150 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11150/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11150/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11150/events | https://github.com/pandas-dev/pandas/pull/11150 | 107,351,905 | MDExOlB1bGxSZXF1ZXN0NDU0ODI3MDc= | 11,150 | BUG: axis kw not propogating on pct_change | {
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"color": "a1... | closed | false | null | [] | null | 3 | 2015-09-19T19:45:45Z | 2015-09-21T14:16:41Z | 2015-09-21T14:16:41Z | NONE | null | We ran a profiler comparing both the .ix and .loc methods for pandas, in both versions, and got substantially slower results when using 0.16.2. Why is that?
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https://api.github.com/repos/pandas-dev/pandas/issues/11152 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11152/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11152/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11152/events | https://github.com/pandas-dev/pandas/pull/11152 | 107,360,016 | MDExOlB1bGxSZXF1ZXN0NDU0ODU5Njk= | 11,152 | PERF: improves performance in groupby.size | {
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``` python
In [1]: n = 100000
In [2]: np.random.seed(2718281)
In [3]: dr = date_range('2015-09-19', periods=n, freq='T')
In [4]: ts = Series(np.random.choice(n, n), index=np.random.choice(dr, n))
In [5]: %timeit ts.resample('5T', how='size')
1 loops, best of 3: 538 ms per loop
```
on branch:
``` pytho... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11153 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11153/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11153/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11153/events | https://github.com/pandas-dev/pandas/pull/11153 | 107,360,214 | MDExOlB1bGxSZXF1ZXN0NDU0ODYwNDI= | 11,153 | (WIP) BUG: DatetimeTZBlock.fillna raises TypeError | {
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import pandas as pd
idx = pd.DatetimeIndex(['2011-01-01', pd.NaT, '2011-01-03'], tz='Asia/Tokyo')
s = pd.Series(idx)
s
#0 2011-01-01 00:00:00+09:00
#1 NaT
#2 2011-01-03 00:00:00+09:00
# dtype: datetime64[ns, Asia/Tokyo]
# NG, the result must be DatetimeTZBlock
s.fillna(pd.Timestamp('201... | {
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xref #8790
Adds new `indicator` keyword to `DataFrame.merge` as well
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https://api.github.com/repos/pandas-dev/pandas/issues/11157 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11157/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11157/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11157/events | https://github.com/pandas-dev/pandas/pull/11157 | 107,418,032 | MDExOlB1bGxSZXF1ZXN0NDU1MDQyNjQ= | 11,157 | DEPR: deprecate SparsePanel | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11158 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11158/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11158/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11158/events | https://github.com/pandas-dev/pandas/pull/11158 | 107,426,100 | MDExOlB1bGxSZXF1ZXN0NDU1MDc0OTU= | 11,158 | PERF: nested dict DataFrame construction | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-09-21T00:13:11Z | 2015-09-24T02:16:41Z | 2015-09-21T14:17:23Z | CONTRIBUTOR | null | Part of #11084
http://pydata.github.io/pandas/#frame_ctor.frame_ctor_nested_dict_int64.time_frame_ctor_nested_dict_int64
```
before after ratio
[d28fd70 ] [48c588 ]
- 325.06ms 72.25ms 0.22 frame_ctor.frame_ctor_nested_dict.time_frame_ctor_nested_dict
- 364.35ms 106.67ms 0.29 frame... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11159 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11159/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11159/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11159/events | https://github.com/pandas-dev/pandas/pull/11159 | 107,426,508 | MDExOlB1bGxSZXF1ZXN0NDU1MDc1NzE= | 11,159 | PERF: Series.dropna with non-nan dtype blocks | {
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```
import numpy as np
import pandas as pd
s = pd.Series(np.random.randint(0, 1000, 50000000))
# before
%timeit s.dropna()
#1 loops, best of 3: 1.58 s per loop
# after
%timeit s.dropna()
#1 loops, best of 3: 568 ms per l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11160 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11160/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11160/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11160/events | https://github.com/pandas-dev/pandas/issues/11160 | 107,457,180 | MDU6SXNzdWUxMDc0NTcxODA= | 11,160 | Add Python 3.5 OSX wheel to pypi? | {
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https://travis-ci.org/MacPython/pandas-wheels/builds/81332167
The Python 3.5 wheel is at the usual http://wheels.scipy.org location:
http://wheels.scipy.org/pandas-0.16.2-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macos... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11161 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11161/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11161/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11161/events | https://github.com/pandas-dev/pandas/pull/11161 | 107,499,058 | MDExOlB1bGxSZXF1ZXN0NDU1NDE5NTc= | 11,161 | DOC: minor doc formatting fixes | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11162 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11162/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11162/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11162/events | https://github.com/pandas-dev/pandas/issues/11162 | 107,551,006 | MDU6SXNzdWUxMDc1NTEwMDY= | 11,162 | DataFrame.unstack() issues DeprecationWarning with MultiIndex | {
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>>> import warnings
>>> warnings.simplefilter('error')
>>> import pandas as pd
>>> pd.__version__
u'0.17.0rc1'
>>> df = pd.DataFrame({'A': list('aabb'), 'B': [0, 1, 0, 1], 'C': range(4)})
>>> gf = df.groupby(['A', 'B']).sum()
>>> gf
C
A B
a 0 0
1 1
b 0 2
1 3
>>> gf.unstack()
Traceback (mos... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11163 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11163/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11163/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11163/events | https://github.com/pandas-dev/pandas/issues/11163 | 107,579,072 | MDU6SXNzdWUxMDc1NzkwNzI= | 11,163 | ENH: make Series.ptp() handle missing values | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-09-21T19:11:29Z | 2015-11-14T15:04:01Z | 2015-11-14T15:04:01Z | CONTRIBUTOR | null | Currently (in master), `Series.ptp()` is just implemented using `np.ptp()` and so the method will return `nan` for any Series that has one or more missing values:
```
>>> s = pd.Series([5, 0, np.nan, -3, 2])
>>> s.ptp()
nan
```
It is simple to write `s.max() - s.min()` instead, but the `ptp()` result is surprising as... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11164 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11164/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11164/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11164/events | https://github.com/pandas-dev/pandas/issues/11164 | 107,610,683 | MDU6SXNzdWUxMDc2MTA2ODM= | 11,164 | Passing a level argument to max/min prevents non-numeric columns from being dropped | {
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... | 3 | 2015-09-21T22:24:41Z | 2021-04-18T23:49:51Z | 2021-04-18T23:49:51Z | CONTRIBUTOR | null | When passing a `level` argument and `numeric_only=True` to `max` and `min`, non-numeric columns are not dropped in the result:
```
>>> df = pd.DataFrame({'a': [1,1,2,2], 'b': [1,4,2,6],
'c': [6,3,2,3], 'd': ['w','x','y','z']})
>>> df.set_index(['a', 'b'])
>>> df
c d
a b
1 1 6 w
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11165 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11165/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11165/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11165/events | https://github.com/pandas-dev/pandas/pull/11165 | 107,651,246 | MDExOlB1bGxSZXF1ZXN0NDU2Mjk0MTU= | 11,165 | DOC: Stating to install NumPY | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11166 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11166/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11166/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11166/events | https://github.com/pandas-dev/pandas/issues/11166 | 107,685,602 | MDU6SXNzdWUxMDc2ODU2MDI= | 11,166 | read_csv C-engine CParserError: Error tokenizing data | {
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... | 19 | 2015-09-22T10:25:00Z | 2021-03-26T18:18:18Z | 2018-10-31T19:40:44Z | NONE | null | Hi,
I have encountered a dataset where the C-engine read_csv has problems. I am unsure of the exact issue but I have narrowed it down to a single row which I have [pickled and uploaded it to dropbox](https://www.dropbox.com/s/cm6gz5nv2679dvi/faulty_row.pkl?dl=0). If you obtain the pickle try the following:
``` python... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11167 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11167/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11167/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11167/events | https://github.com/pandas-dev/pandas/issues/11167 | 107,745,772 | MDU6SXNzdWUxMDc3NDU3NzI= | 11,167 | ENH: `min_weight` in addition to `min_periods` for ewma | {
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... | 5 | 2015-09-22T16:00:13Z | 2020-05-08T19:28:17Z | null | CONTRIBUTOR | null | Currently the exponential functions, such as `pd.ewma`, use a `min_periods` argument to ensure there's enough data to specify generate a valid value. While this works well for the rolling functions, it's not effective for exponential functions because points have weight forever, albeit ever decreasing:
``` python
In [... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11168 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11168/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11168/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11168/events | https://github.com/pandas-dev/pandas/pull/11168 | 107,750,688 | MDExOlB1bGxSZXF1ZXN0NDU2ODUzODE= | 11,168 | BF: for version comparison first arg should be the LooseVersion | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11169 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11169/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11169/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11169/events | https://github.com/pandas-dev/pandas/issues/11169 | 107,751,247 | MDU6SXNzdWUxMDc3NTEyNDc= | 11,169 | test_constructor_compound_dtypes and test_invalid_index_types fail in parse_datetime_string | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-09-22T16:28:36Z | 2016-07-19T13:06:23Z | 2016-07-19T13:06:23Z | CONTRIBUTOR | null | Debian stretch/sid, cython 0.22.1-2, pandas v0.17.0rc1-92-gc6bcc99
```
$> locale
LANG=en_US.UTF-8
LANGUAGE=
LC_CTYPE="en_US.UTF-8"
LC_NUMERIC="en_US.UTF-8"
LC_TIME="en_US.UTF-8"
LC_COLLATE="en_US.UTF-8"
LC_MONETARY="en_US.UTF-8"
LC_MESSAGES="en_US.UTF-8"
LC_PAPER="en_US.UTF-8"
LC_NAME="en_US.UTF-8"
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https://api.github.com/repos/pandas-dev/pandas/issues/11170 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11170/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11170/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11170/events | https://github.com/pandas-dev/pandas/issues/11170 | 107,765,895 | MDU6SXNzdWUxMDc3NjU4OTU= | 11,170 | Test failure due to Timestamp not being imported on master | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-09-22T17:51:32Z | 2015-09-27T14:28:49Z | 2015-09-27T14:28:49Z | CONTRIBUTOR | null | I am seeing test failures (both local and Travis) due to
https://github.com/pydata/pandas/blob/master/pandas/tests/test_internals.py#L667
which uses `Timestamp`, not `pd.Timestamp`. Is this expected?
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https://api.github.com/repos/pandas-dev/pandas/issues/11171 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11171/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11171/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11171/events | https://github.com/pandas-dev/pandas/pull/11171 | 107,777,349 | MDExOlB1bGxSZXF1ZXN0NDU3MDE2NTA= | 11,171 | Added density of a categorical #10949 | {
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closes #10949.
Assuming it is I will go ahead and add some documentation for this enhancement. Let me know if you have any feedback.
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https://api.github.com/repos/pandas-dev/pandas/issues/11172 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11172/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11172/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11172/events | https://github.com/pandas-dev/pandas/pull/11172 | 107,795,749 | MDExOlB1bGxSZXF1ZXN0NDU3MTI5MzI= | 11,172 | ENH: make Series.ptp ignore NaN values (GH11163) | {
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`Series.ptp` will now ignore missing values when calculating the peak to peak difference.
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https://api.github.com/repos/pandas-dev/pandas/issues/11173 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11173/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11173/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11173/events | https://github.com/pandas-dev/pandas/pull/11173 | 107,806,730 | MDExOlB1bGxSZXF1ZXN0NDU3MTkzOTA= | 11,173 | ENH: Restore original convert_objects and add _convert | {
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version of _convert
Adds to_numeric for directly converting numeric data
closes #11116
closes #11133
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https://api.github.com/repos/pandas-dev/pandas/issues/11174 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11174/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11174/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11174/events | https://github.com/pandas-dev/pandas/issues/11174 | 107,822,711 | MDU6SXNzdWUxMDc4MjI3MTE= | 11,174 | Segmentation fault: 11 during pandas to_csv operation | {
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] | closed | false | null | [] | null | 22 | 2015-09-22T23:23:08Z | 2017-04-24T06:42:54Z | 2015-09-25T12:07:57Z | NONE | null | Following a suggestion on [StackOverflow](http://stackoverflow.com/questions/32720514/segmentation-fault-11-during-pandas-to-csv-operation), I'm posting this here:
I'm working on Mac OS 10.10.5, using a Python 2.7 virtualenv and pandas installed via pip.
I have a Pandas dataFrame (called 'pivot') which is 13843 rows ... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-09-23T11:35:04Z | 2015-09-23T23:19:53Z | 2015-09-23T11:53:01Z | CONTRIBUTOR | null | Fixed a typo where I had `header=False`
Side note, it might be nice to change the actual behavior, not the first time it's tripped me up. I guess there already is an issue, #6113
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https://api.github.com/repos/pandas-dev/pandas/issues/11177 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11177/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11177/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11177/events | https://github.com/pandas-dev/pandas/pull/11177 | 107,940,064 | MDExOlB1bGxSZXF1ZXN0NDU3OTAxNjQ= | 11,177 | Update 10min.rst | {
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```
sysuse auto.dta
describe
```
gives something like
| variable name | storage type | variable label |
| --- | --- | --- |
| make | str18 | Make and Model |
| price | int... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11180 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11180/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11180/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11180/events | https://github.com/pandas-dev/pandas/pull/11180 | 108,023,946 | MDExOlB1bGxSZXF1ZXN0NDU4NDE4NjQ= | 11,180 | improves groupby.get_group_index when shape is a long sequence | {
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xref https://github.com/pydata/pandas/issues/10161#issuecomment-142701582
``` python
In [5]: df = DataFrame(np.random.randn(5000, 100).astype(str))
In [6]: %timeit df.duplicated()
1 loops, best of 3: 151 ms per loop
In [7]: %timeit df.T.duplicated()
1 loops, best of 3: 1.39 s per loop
```
part of th... | {
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I think it would make sense to, at least if the names are all the same. Happy to do a PR if people agree.
``` python
In [17]: from collections import namedtuple... | {
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Passing `header=True|False` to `read_csv` (and brethren), `read_excel`, and `read_html` will now raise a `TypeError`, rather than being coerced to an int.
I had thought about converting `False` to `None` but thought that could break someone's code in a very subtle way if they were somehow depending on t... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-09-24T08:54:12Z | 2015-09-25T12:11:12Z | 2015-09-25T12:11:12Z | MEMBER | null | @kshedden `XportReader` is not top-level API, so it was erroring in the doc build.
I now removed it from api.rst (the `TextFileReader` what you get back with chunksize for read_csv is also not included), but I can also adapt it to use `.. currentmodule:: pandas.io.sas` so it builds correctly if you want.
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https://api.github.com/repos/pandas-dev/pandas/issues/11184 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11184/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11184/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11184/events | https://github.com/pandas-dev/pandas/pull/11184 | 108,092,655 | MDExOlB1bGxSZXF1ZXN0NDU4NzYzOTY= | 11,184 | DOC: fix bunch of doc build warnings | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11185 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11185/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11185/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11185/events | https://github.com/pandas-dev/pandas/issues/11185 | 108,097,684 | MDU6SXNzdWUxMDgwOTc2ODQ= | 11,185 | Grouping a 2 rows DataFrame by time and columns doesn't work as expected | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-09-24T09:55:45Z | 2015-10-02T22:03:02Z | 2015-10-02T22:03:01Z | NONE | null | Hi guys,
Working with pandas is great, however I might have notice a bug while grouping a 2 rows DataFrame by time and columns:
``` python
>>> import pandas as pd
>>> import numpy as np
>>> from datetime import datetime
>>> freq = 's'
>>> t1 = np.datetime64(datetime.utcnow(), freq)
>>> index = pd.date_range(start=t1... | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-09-24T11:30:54Z | 2015-11-13T22:28:09Z | 2015-11-13T22:27:29Z | CONTRIBUTOR | null | xref #11145
- [ ] change ci/requirements
- [ ] remove checks for '0+unknown' in version checks (bug already fixed in matplotlib)
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https://api.github.com/repos/pandas-dev/pandas/issues/11188 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11188/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11188/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11188/events | https://github.com/pandas-dev/pandas/issues/11188 | 108,302,305 | MDU6SXNzdWUxMDgzMDIzMDU= | 11,188 | COMPAT: reading generic PyTables Table format fails with sub-selection | {
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``` python
pd.read_hdf(output_fname, '/floats/trajectories', start=0, stop=10)
```
gives
```
ValueError: Shape of passed values is (1, 10), indices ... | {
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In [1]: df = pd.DataFrame({"id":[1,2,3,4,5,6], "grade":['a', 'b', 'b', 'a', 'a', 'e']})
In [2]: df.groupby("grade").size()
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-3-d8e387418f9d> in <modul... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11190 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11190/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11190/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11190/events | https://github.com/pandas-dev/pandas/issues/11190 | 108,408,686 | MDU6SXNzdWUxMDg0MDg2ODY= | 11,190 | [Request] pd.rolling_apply - apply a given function to a rolling window of data | {
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https://github.com/pydata/pandas/blob/master/pandas/tseries/frequencies.py#L515
```
import pandas as pd
x = pd.tseries.frequencies.get_offset('D')
x.__dict__
# {'normalize': False, 'kwds': {}, 'n': 1, '_offset': datetime.timedelta(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11193 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11193/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11193/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11193/events | https://github.com/pandas-dev/pandas/issues/11193 | 108,435,857 | MDU6SXNzdWUxMDg0MzU4NTc= | 11,193 | API/BUG: Index creation with named Index resets name | {
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"id": 35818298,... | closed | false | null | [] | {
"closed_at": "2016-03-12T16:19:08Z",
"closed_issues": 469,
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import pandas as pd
idx = pd.Index([1, 2 ,3], name='x')
pd.Index(idx)
# Int64Index([1, 2, 3], dtype='int64')
```
A point is whether to reset existing Index name in below case. Current impl can't distinguish whether name is not passed, or passed `None` explicitly.
```
pd.Index(idx, name=None)
# -> should reset nam... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11194 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11194/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11194/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11194/events | https://github.com/pandas-dev/pandas/pull/11194 | 108,463,655 | MDExOlB1bGxSZXF1ZXN0NDYwODE3ODg= | 11,194 | PERF: compare freq strings (timeseries plotting perf) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11195 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11195/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11195/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11195/events | https://github.com/pandas-dev/pandas/issues/11195 | 108,484,869 | MDU6SXNzdWUxMDg0ODQ4Njk= | 11,195 | DataFrame.shift unexpected result | {
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``` python
df = pd.DataFrame([1,2,4,35,356,3425,24,24,12,24,6,7,8,8,4], columns=['one'])
df['two'] = np.log(df['one'])
df['three'] = np.log10(df['one'])
df['four'] = np.exp(df['one'])
df['five'] = df['two'] * df['three']
```
This gives:
```
In [8]: df
Out[8]:
one two t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11196 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11196/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11196/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11196/events | https://github.com/pandas-dev/pandas/issues/11196 | 108,533,572 | MDU6SXNzdWUxMDg1MzM1NzI= | 11,196 | TST: invalid generator tests in in test_internals.py | {
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... | 3 | 2015-09-27T13:06:51Z | 2019-10-06T02:15:15Z | 2019-10-06T02:15:15Z | CONTRIBUTOR | null | `nosetests pandas/tests/test_internals.py:TestBlockManager.test_insert` runs successfully even when I tweak the `yield` statement to something false, such as `yield self.assertIs, 1, 2`.
This is because generator tests are not discovered inside subclasses of `TestCase`.
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https://api.github.com/repos/pandas-dev/pandas/issues/11197 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11197/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11197/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11197/events | https://github.com/pandas-dev/pandas/pull/11197 | 108,534,023 | MDExOlB1bGxSZXF1ZXN0NDYxMDA4NTY= | 11,197 | CLN: GH11170, * import is removed from test_internals.py | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-09-27T13:11:46Z | 2015-09-27T14:28:49Z | 2015-09-27T14:28:49Z | CONTRIBUTOR | null | closes #11170
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https://api.github.com/repos/pandas-dev/pandas/issues/11198 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11198/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11198/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11198/events | https://github.com/pandas-dev/pandas/pull/11198 | 108,543,497 | MDExOlB1bGxSZXF1ZXN0NDYxMDMxNDc= | 11,198 | API: read_excel signature | {
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"followers_url": "https://api.github.com/users/jr... | 20 | 2015-09-27T15:46:20Z | 2015-10-04T17:01:35Z | 2015-09-30T22:05:27Z | CONTRIBUTOR | null | Replace the `**kwds` in `read_excel` with the actual list of supported keyword args. This doesn't
change any functionality, just nicer for interactive use. Also a bit of clarification on the `thousands`
arg in the docstring.
Additionally, `chunksize` was a parameter in the `ExcelFile.parse` signature, but didn't do a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11199 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11199/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11199/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11199/events | https://github.com/pandas-dev/pandas/issues/11199 | 108,557,736 | MDU6SXNzdWUxMDg1NTc3MzY= | 11,199 | mean of int64 results in int64 instead of float64 | {
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xref #3707
Dear pandas team
My environment is:
```
numpy==1.9.3
pandas==0.16.2
```
On it, may it be possible that the bug [#10172](https://github.com/pydata/pandas/pull/10172) has been re-introduced? For instance, with a csv file (`mini.csv`) with three int columns generated as per the co... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11200 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11200/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11200/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11200/events | https://github.com/pandas-dev/pandas/issues/11200 | 108,686,601 | MDU6SXNzdWUxMDg2ODY2MDE= | 11,200 | Unexpected behavior with apply function on axis 0 | {
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"de... | closed | false | null | [] | null | 1 | 2015-09-28T15:43:34Z | 2015-09-28T17:49:16Z | 2015-09-28T17:49:05Z | NONE | null | Hi,
is this a expected behavior when using apply on axis 0?( apply iterates twice the first column a)
Thanks!
``` python
import pandas as pd
import numpy as np
pd.show_versions()
df3 = pd.DataFrame(np.random.randn(10, 5),columns=['a', 'b', 'c', 'd', 'e'])
```
```
INSTALLED VERSIONS
------------------
commit: None
pyt... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11201 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11201/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11201/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11201/events | https://github.com/pandas-dev/pandas/issues/11201 | 108,789,988 | MDU6SXNzdWUxMDg3ODk5ODg= | 11,201 | BUG: unexpected KeyError with Index.get_loc | {
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"f... | 12 | 2015-09-29T03:56:45Z | 2019-10-21T20:07:56Z | null | NONE | null | `Index.get_loc` raises unexpected `KeyError` when `data` is a 2-dimensional `numpy.ndarray` with non-unique, monotonically increasing values, i.e.,
```
>>> import numpy as np
>>> import pandas as pd
>>> ix = pd.Index(np.array([["A"], ["A"], ["B"]]))
>>> ix.get_loc(ix[0])
Traceback (most recent call last):
File "<std... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/11202 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11202/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11202/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11202/events | https://github.com/pandas-dev/pandas/pull/11202 | 108,938,176 | MDExOlB1bGxSZXF1ZXN0NDYzMTgzMjc= | 11,202 | BUG: groupby list of keys with same length as index | {
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... | closed | false | null | [] | {
"closed_at": "2015-10-09T18:34:35Z",
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-09-29T19:06:15Z | 2015-10-01T10:45:52Z | 2015-10-01T10:45:44Z | CONTRIBUTOR | null | Fixes issue #11185
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