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https://api.github.com/repos/pandas-dev/pandas/issues/1701 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1701/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1701/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1701/events | https://github.com/pandas-dev/pandas/issues/1701 | 5,909,069 | MDU6SXNzdWU1OTA5MDY5 | 1,701 | GroupBy.apply doesn't pass group key name onto index in all cases | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1702 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1702/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1702/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1702/events | https://github.com/pandas-dev/pandas/issues/1702 | 5,909,978 | MDU6SXNzdWU1OTA5OTc4 | 1,702 | concat DataFrame along timeseries indexes | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-07-30T03:01:24Z | 2012-08-10T16:03:00Z | 2012-08-10T16:03:00Z | NONE | null | Please see: http://stackoverflow.com/questions/11714768/concat-pandas-dataframe-along-timeseries-indexes
NumPy v1.6.3
Pandas v0.8.1
I have two largish (snippets provided) pandas DateFrames with unequal dates as indexes that I wish to concat into one:
```
NAB.AX CBA.AX
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1703 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1703/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1703/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1703/events | https://github.com/pandas-dev/pandas/issues/1703 | 5,914,440 | MDU6SXNzdWU1OTE0NDQw | 1,703 | Incorrect result when using to_datetime() on PeriodIndex | {
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"followers_url": "https://api.github.com/users/wesm/... | 0 | 2012-07-30T10:15:27Z | 2012-08-12T20:53:07Z | 2012-08-12T20:53:07Z | CONTRIBUTOR | null | Pandas 0.8.1:
```
import pandas as pd
index = pd.period_range('1/1/2012',periods=4,freq='D')
index.to_datetime()
```
returns incorrectly:
```
<class 'pandas.tseries.index.DatetimeIndex'>
[1970-01-01 00:00:00.000015340, ..., 1970-01-01 00:00:00.000015343]
Length: 4, Freq: None, Timezone: None
```
The correct result ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1704 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1704/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1704/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1704/events | https://github.com/pandas-dev/pandas/issues/1704 | 5,914,496 | MDU6SXNzdWU1OTE0NDk2 | 1,704 | Incorrect result when using get_level_values on datetime index | {
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"gists_url": "https:/... | [] | closed | false | null | [] | null | 2 | 2012-07-30T10:20:28Z | 2012-08-19T16:06:19Z | 2012-08-19T16:06:19Z | CONTRIBUTOR | null | Pandas 0.8.1:
```
import pandas as pd
import datetime as dt
tuples = [(dt.datetime(2012,1,1),1),(dt.datetime(2012,1,1),2),(dt.datetime(2012,1,2),1),(dt.datetime(2012,1,2),2)]
index = pd.MultiIndex.from_tuples(tuples)
index.get_level_values(level=0)
```
incorrectly returns:
```
array([1970-01-16 224:00:00, 1970-01-16... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1705 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1705/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1705/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1705/events | https://github.com/pandas-dev/pandas/issues/1705 | 5,914,645 | MDU6SXNzdWU1OTE0NjQ1 | 1,705 | Incorrect behaviour when using periods in a hierarchical index | {
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... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/wesm/... | 0 | 2012-07-30T10:29:53Z | 2012-08-12T20:18:39Z | 2012-08-12T20:18:39Z | CONTRIBUTOR | null | Pandas 0.8.1:
```
import pandas as pd
index = pd.date_range('1/1/2012',periods=4,freq='12H')
index_as_arrays = [index.to_period(freq='D'), index.hour]
pd.Series([0, 1, 2, 3], index_as_arrays)
```
incorrectly returns:
```
15340 0 0
12 1
15341 0 2
12 3
```
The correct result is obtained ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1706 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1706/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1706/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1706/events | https://github.com/pandas-dev/pandas/issues/1706 | 5,916,760 | MDU6SXNzdWU1OTE2NzYw | 1,706 | encode/decode method for string module (like in np.char.encode ) | {
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"followers_url": "https://api.github.com/users/wesm/... | 0 | 2012-07-30T12:49:57Z | 2012-08-12T01:48:40Z | 2012-08-12T01:48:40Z | NONE | null | This is already in included in numpy but for convenience it would be nice to have this in pandas.
```
series.str.decode('utf-8')
```
is nicer than for example
```
series = Series(['a','b','ä'])
Series(np.char.decode(series.values.astype('|S255'), 'utf-8'))
```
I find myself having to decode and encode a lot dependi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1707 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1707/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1707/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1707/events | https://github.com/pandas-dev/pandas/issues/1707 | 5,927,631 | MDU6SXNzdWU1OTI3NjMx | 1,707 | Can't save empty Series or DataFrame to hdf5 with HDFStore | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-07-30T19:55:06Z | 2012-08-12T01:31:59Z | 2012-08-12T01:31:39Z | NONE | null | With pandas 0.8.1 (and pytables 2.3.1), trying to save an empty Series or DataFrame when using HDFStore results in an exception after some (but not all) data has been written to the hdf5 file.
``` python
from pandas import DataFrame, Series, HDFStore
# These are all empty
s0 = Series()
s1 = Series(name='myseries')
d... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1708 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1708/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1708/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1708/events | https://github.com/pandas-dev/pandas/issues/1708 | 5,928,761 | MDU6SXNzdWU1OTI4NzYx | 1,708 | Unexpected result with union, intersection and diff on Index objects | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-07-30T20:33:54Z | 2012-08-10T16:55:17Z | 2012-08-10T16:55:00Z | CONTRIBUTOR | null | Pandas 0.8.1:
```
import pandas as pd
import datetime as dt
index_1 = pd.DatetimeIndex([dt.datetime(2012,1,1,0), dt.datetime(2012,1,1,12),
dt.datetime(2012,1,2,0), dt.datetime(2012,1,2,12)])
index_2 = index_1 + pd.DateOffset(hours=1)
index_1 & index_2
```
correctly returns:
```
<class 'pandas.tseries.index.Datet... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1709 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1709/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1709/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1709/events | https://github.com/pandas-dev/pandas/issues/1709 | 5,929,618 | MDU6SXNzdWU1OTI5NjE4 | 1,709 | include iris dataset | {
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... | closed | false | null | [] | {
"closed_at": "2013-01-18T04:50:20Z",
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-07-30T21:07:09Z | 2012-10-21T18:08:42Z | 2012-10-21T18:08:42Z | CONTRIBUTOR | null | I just noticed the very nice radviz graphing feature added to pandas 0.8.1 (http://pandas.pydata.org/pandas-docs/dev/visualization.html#scatter-plot-matrix). Most of the graphs in the pandas documentation use randomly generated graphs, however the radviz examples uses the iris data set. The iris dataset, however, is n... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1710 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1710/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1710/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1710/events | https://github.com/pandas-dev/pandas/issues/1710 | 5,930,158 | MDU6SXNzdWU1OTMwMTU4 | 1,710 | represent x-y plots with points instead of lines | {
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Is there a way that each x-y position can be represented as points rather than as a line? For example the following will... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1711 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1711/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1711/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1711/events | https://github.com/pandas-dev/pandas/issues/1711 | 5,942,018 | MDU6SXNzdWU1OTQyMDE4 | 1,711 | pandas.Series.plot ignores color in **kwarg | {
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``` python
pandas.Series(randn(10)).plot(color='red')
```
Whose output is:
This used to work correctly in pandas 0.7.2
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https://api.github.com/repos/pandas-dev/pandas/issues/1712 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1712/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1712/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1712/events | https://github.com/pandas-dev/pandas/issues/1712 | 5,946,311 | MDU6SXNzdWU1OTQ2MzEx | 1,712 | Series get function returns None instead of NaN on missing key | {
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s.get('f')
nan
however, when 'f' is not a key of a Series, the get function returns None, as in:
s.get('f') is None
True
A workaround is to use get(..., NaN), as in:
s.get('f', NaN)
nan
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https://api.github.com/repos/pandas-dev/pandas/issues/1713 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1713/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1713/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1713/events | https://github.com/pandas-dev/pandas/issues/1713 | 5,947,680 | MDU6SXNzdWU1OTQ3Njgw | 1,713 | Inserting subclass/composition of Series into DataFrame strips 'extra' functions/properties | {
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"f... | 15 | 2012-07-31T16:34:30Z | 2017-05-04T13:35:39Z | 2017-05-04T13:35:39Z | NONE | null | When trying to insert/append a subclass (or composition) of a pandas Series into a DataFrame, any and all of the 'extra' functions that come with my subclass (or composition) are stripped and a Series is created:
``` python
In [7]: df = read_csv('some/data/from/file.csv')
In [8]: sp = SpatialSeries(df.the_geom) # Spa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1714 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1714/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1714/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1714/events | https://github.com/pandas-dev/pandas/issues/1714 | 5,950,551 | MDU6SXNzdWU1OTUwNTUx | 1,714 | On windows+IDLE 2.7 get_terminal_size() returns default (80,25) | {
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"created_at": "2015-02-26T19:29:05Z",
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"followers_url": "https://api.github.com/users/jorisva... | 5 | 2012-07-31T18:38:20Z | 2016-09-29T22:44:19Z | 2016-09-29T22:16:29Z | CONTRIBUTOR | null | From [stackoverflow](http://stackoverflow.com/questions/11707586/python-pandas-widen-output-display)
```
Python/IDLE 2.7.3
Pandas 0.8.1
Notepad++ 6.1.4 (UNICODE)
Windows Vista SP2
```
``` python
pandas.util.terminal.get_terminal_size()
```
Fails to detect the real IDLE display size and returns default (80, 25)
work... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1715 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1715/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1715/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1715/events | https://github.com/pandas-dev/pandas/issues/1715 | 5,956,607 | MDU6SXNzdWU1OTU2NjA3 | 1,715 | Inconsistent Panel Assignment | {
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"f... | 2 | 2012-07-31T23:46:26Z | 2013-08-07T16:37:04Z | 2013-08-07T16:37:04Z | CONTRIBUTOR | null | Hi,
I've encountered some (seemingly) inconsistent behavior in assigning values to Panels. Here are some examples
``` python
In [2]: aapl = DataReader('AAPL','yahoo')
p = Panel({'stock':aapl})
print p['stock'][:5]
Out[2]: Open High Low Close Volume Adj Close
Date ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1716 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1716/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1716/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1716/events | https://github.com/pandas-dev/pandas/pull/1716 | 5,961,451 | MDExOlB1bGxSZXF1ZXN0MTk0MjEzOQ== | 1,716 | Fixes bug in tools.scatter_plot | {
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In [1]: import pandas
In [2]: from pandas.tools.plotting import scatter_plot
In [7]: df = pandas.DataFrame(np.random.randn(5,2), columns=['a','b'])
In [8]: df
Out[8]:
a b
0 0.032454 0.057020
1 -0.292223 -0.265303
2 -0.118943 1.315302
3 -2.754867 0.827289
4 0.497206 -1.360892
In [9]: df['... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1717 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1717/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1717/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1717/events | https://github.com/pandas-dev/pandas/issues/1717 | 5,965,308 | MDU6SXNzdWU1OTY1MzA4 | 1,717 | groupby.first() fails for np.datetime64 columns | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-08-01T10:52:31Z | 2012-08-09T03:14:33Z | 2012-08-09T03:11:50Z | NONE | null | numpy 1.7 dev and pandas-0.8.2.dev_f5a74d4-py2.7-linux-x86_64
```
import pandas as pd
import numpy as np
df = pd.DataFrame([(3,np.datetime64('2012-07-03')),(3,np.datetime64('2012-07-04'))], columns = ['a', 'date'])
df.groupby('a').first()
---------------------------------------------------------------------------
Val... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1718 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1718/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1718/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1718/events | https://github.com/pandas-dev/pandas/issues/1718 | 5,982,721 | MDU6SXNzdWU1OTgyNzIx | 1,718 | Resampling OHLC -> OHLC | {
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"f... | 9 | 2012-08-02T01:02:18Z | 2020-10-07T09:53:17Z | 2014-11-30T15:20:32Z | MEMBER | null | Be nice to be able to go from say 5-min OHLC to 1-day OHLC easily
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https://api.github.com/repos/pandas-dev/pandas/issues/1719 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1719/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1719/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1719/events | https://github.com/pandas-dev/pandas/issues/1719 | 5,982,960 | MDU6SXNzdWU1OTgyOTYw | 1,719 | concat with axis=1, join='outer' not working correctly | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-08-02T01:25:10Z | 2012-08-09T02:26:52Z | 2012-08-09T02:26:52Z | MEMBER | null | http://stackoverflow.com/questions/11761884/pandas-concatouter-not-doing-union
```
It looks pandas.concat is doing 'left outer' join instead of just union the indexes. Seems a bug to me but maybe I'm missing something obvious.
import pandas
import pandas.util.testing as put
ts1 = put.makeTimeSeries()
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https://api.github.com/repos/pandas-dev/pandas/issues/1720 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1720/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1720/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1720/events | https://github.com/pandas-dev/pandas/issues/1720 | 5,983,047 | MDU6SXNzdWU1OTgzMDQ3 | 1,720 | DataFrame.to_records failure with DatetimeIndex | {
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```
In [20]: df = read_clipboard(sep='\s+', parse_dates=True)
In [21]: df
Out[21]:
a b c
2012-08-01 2.355928 -2.465061 0.240094
2012-08-02 -0.952323 0.746623 -0.384021... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1721 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1721/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1721/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1721/events | https://github.com/pandas-dev/pandas/issues/1721 | 5,987,693 | MDU6SXNzdWU1OTg3Njkz | 1,721 | np.fix crashes with pandas time series | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-02T09:00:24Z | 2012-08-09T02:24:57Z | 2012-08-09T02:24:57Z | NONE | null | ```
import numpy as np
import pandas
x = pandas.TimeSeries(data = np.array([-0.54548407, 2.81105692, np.nan, -1.61954275, 1.3670269, -0.73211055, -0.22832786, 0.06384124, -1.7113508, -2.42429978]), index = np.arange(0,10))
```
`print np.fix(x)`
crashes with:
```
File "C:\Python27\lib\site-packages... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1722 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1722/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1722/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1722/events | https://github.com/pandas-dev/pandas/issues/1722 | 5,989,983 | MDU6SXNzdWU1OTg5OTgz | 1,722 | Confusing docstring | {
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"followers_url": "https://api.github.com/users/wesm/... | 0 | 2012-08-02T11:26:00Z | 2012-08-09T01:05:08Z | 2012-08-09T01:05:08Z | NONE | null | I just came across this one while browsing the code.
Maybe this should be Index.intersection in the docstring ?
```
def intersection(self, other):
"""
Specialized intersection for DatetimeIndex objects. May be much faster
than Index.union
Parameters
----------
other : ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1723 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1723/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1723/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1723/events | https://github.com/pandas-dev/pandas/issues/1723 | 5,990,831 | MDU6SXNzdWU1OTkwODMx | 1,723 | Add DatetimeIndex.day_of_year Method | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-02T12:22:31Z | 2012-08-09T09:02:11Z | 2012-08-09T01:09:31Z | CONTRIBUTOR | null | PeriodIndex has a day_of_year method, but DatetimeIndex doesn't. This makes it hard to write generic code which can take either.
Given they both have dayofyear attributes it may be best to remove the day_of_year method so that there is only one obvious way to do it.
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https://api.github.com/repos/pandas-dev/pandas/issues/1724 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1724/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1724/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1724/events | https://github.com/pandas-dev/pandas/issues/1724 | 6,004,415 | MDU6SXNzdWU2MDA0NDE1 | 1,724 | More flexibility in to_period | {
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```
Also noticed that `to_period` doesn't work for frequency QS:
In [110]: q = pd.date_range('01-Jan-2012', periods=8, freq='QS-Jan')
In [111]: p = q.to_period()
---------------------------------------------------------------------------
KeyError Traceback (most rec... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1725 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1725/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1725/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1725/events | https://github.com/pandas-dev/pandas/issues/1725 | 6,004,435 | MDU6SXNzdWU2MDA0NDM1 | 1,725 | QS frequency alias | {
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] | closed | false | null | [] | null | 0 | 2012-08-02T22:58:41Z | 2016-10-12T23:03:07Z | 2012-08-20T05:38:12Z | MEMBER | null | The table at http://pandas.pydata.org/pandas-docs/dev/timeseries.html#offset-aliases
appears to suggest there is a QS frequency
but when I try it I get the following traceback:
```
In [84]: pd.date_range('01-Jan-2012', periods=8, freq='QS')
---------------------------------------------------------------------------
Va... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1726 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1726/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1726/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1726/events | https://github.com/pandas-dev/pandas/issues/1726 | 6,007,572 | MDU6SXNzdWU2MDA3NTcy | 1,726 | Error with closed='left' and _adjust_bin_edges | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-03T03:49:52Z | 2013-11-24T13:44:10Z | 2012-08-13T01:08:30Z | CONTRIBUTOR | null | ``` python
import pandas as pd
#8/6/12 is a Monday
ind = pd.DatetimeIndex(start="8/6/2012", end="8/26/2012", freq="D")
n = len(ind)
data = [[x] * 5 for x in range(n)]
df = pd.DataFrame(data, columns=['open', 'high', 'low', 'close', 'vol'], index=ind)
df.resample('W-MON', how='first', closed='left', label='left')
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1727 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1727/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1727/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1727/events | https://github.com/pandas-dev/pandas/issues/1727 | 6,011,789 | MDU6SXNzdWU2MDExNzg5 | 1,727 | inconsistent results building a DataFrame from a dict of Series with MultiIndexes | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-03T10:13:51Z | 2012-08-12T21:35:09Z | 2012-08-12T21:34:54Z | NONE | null | I am trying to build a DataFrame from a dict of Series objects which have (not necessarily exactly matching) MultiIndex indices, sometimes I don't get any results for some particular data point and so I create an empty Series object and add that to the dict, as I need there to be a column present even without any data ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1728 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1728/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1728/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1728/events | https://github.com/pandas-dev/pandas/issues/1728 | 6,016,411 | MDU6SXNzdWU2MDE2NDEx | 1,728 | to_html issues | {
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] | closed | false | null | [] | null | 2 | 2012-08-03T14:54:44Z | 2016-10-12T23:03:07Z | 2012-08-05T19:45:44Z | CONTRIBUTOR | null | - doc string mentions a "justify" parameter that apparently does not exist and provokes an errore if used
- setting index=False produces no visible effect
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https://api.github.com/repos/pandas-dev/pandas/issues/1729 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1729/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1729/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1729/events | https://github.com/pandas-dev/pandas/issues/1729 | 6,033,100 | MDU6SXNzdWU2MDMzMTAw | 1,729 | Unexpected result when slicing time series intra day | {
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```
import pandas as pd
import datetime as dt
rng = pd.date_range('1/1/2012', periods=4, freq='12H')
a = pd.Series(index=rng)
a[dt.datetime(2011,1,1,3):]
```
incorrectly results:
```
2012-01-01 00:00:00 NaN
2012-01-01 12:00:00 NaN
2012-01-02 00:00:00 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1730 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1730/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1730/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1730/events | https://github.com/pandas-dev/pandas/issues/1730 | 6,033,230 | MDU6SXNzdWU2MDMzMjMw | 1,730 | Unexpected result when combining Series into a DataFrame | {
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```
import pandas as pd
rng_a = pd.date_range('1/1/2012',periods=4,freq='3H')
rng_b = pd.date_range('1/1/2012',periods=4,freq='4H')
a = pd.Series([0, 1, 2, 3], rng_a)
b = pd.Series([0, 1, 2, 3], rng_b)
pd.DataFrame({'a':a, 'b': b})
```
unexpectedly returns:
```
a b
1/1/2012 00:00:... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1731 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1731/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1731/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1731/events | https://github.com/pandas-dev/pandas/pull/1731 | 6,033,239 | MDExOlB1bGxSZXF1ZXN0MTk3NTE3MQ== | 1,731 | DOC: skipna not an argument of drop_duplicates | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-04T22:18:09Z | 2014-06-18T10:03:18Z | 2012-09-08T21:25:09Z | CONTRIBUTOR | null | From what I can tell, `skipna` keyword was both added and subsequently
removed in #1244. However, the docstring for DataFrame.drop_duplicates
still lists it as a parameter.
I remove this from the docs, so they accurately represent the code.
An alternative to this would be to put back the skipna functionality.
pinging... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1732 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1732/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1732/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1732/events | https://github.com/pandas-dev/pandas/issues/1732 | 6,033,377 | MDU6SXNzdWU2MDMzMzc3 | 1,732 | Error when trying to plot time series with different frequencies | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-08-04T22:42:38Z | 2016-10-12T23:03:07Z | 2012-08-20T05:36:24Z | CONTRIBUTOR | null | Pandas 0.8.1:
```
import pandas as pd
import matplotlib.pyplot as plt
rng_a = pd.date_range('1/1/2012', periods=4, freq='2H'')
rng_b = pd.date_range('1/1/2012', periods=4, freq='H')
rng_c = pd.date_range('1/1/2012', periods=4, freq='30T')
a = pd.Series([0, 1, 3, 6], rng_a)
b = pd.Series([0, 1, 3, 6], rng_b)
c = pd.Ser... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1733 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1733/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1733/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1733/events | https://github.com/pandas-dev/pandas/pull/1733 | 6,033,440 | MDExOlB1bGxSZXF1ZXN0MTk3NTI0MQ== | 1,733 | DOC: fixed some minor typos | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-04T22:57:14Z | 2012-08-12T21:44:19Z | 2012-08-12T21:44:19Z | CONTRIBUTOR | null | pandas is great, thank you!
I've only been using it for a couple of months now, and when I found one typo, I couldn't stop myself from pitching-in and going through all the relevant `.py` files and fixing the typos that popped out.
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https://api.github.com/repos/pandas-dev/pandas/issues/1734 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1734/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1734/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1734/events | https://github.com/pandas-dev/pandas/issues/1734 | 6,033,453 | MDU6SXNzdWU2MDMzNDUz | 1,734 | Fix statsmodels import in pandas.stats.var or remove module | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-04T23:00:11Z | 2012-08-10T16:49:40Z | 2012-08-10T16:49:40Z | MEMBER | null | cc @blais
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https://api.github.com/repos/pandas-dev/pandas/issues/1735 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1735/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1735/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1735/events | https://github.com/pandas-dev/pandas/pull/1735 | 6,033,768 | MDExOlB1bGxSZXF1ZXN0MTk3NTM2Ng== | 1,735 | Support for HTML class'es on DataFrame.to_html(). | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-08-05T00:03:28Z | 2014-06-19T18:08:10Z | 2012-08-13T04:05:24Z | CONTRIBUTOR | null | I really like to use sorttable.js and dragtable.js.
I need to be able to customize the HTML classes.
I also added a default class, so that people can use css on all Pandas generated tables by default.
Default class is "dataframe"
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https://api.github.com/repos/pandas-dev/pandas/issues/1736 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1736/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1736/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1736/events | https://github.com/pandas-dev/pandas/issues/1736 | 6,061,045 | MDU6SXNzdWU2MDYxMDQ1 | 1,736 | Series/DataFrame repr fails for MultiIndex level names with unicode | {
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"followers_url": "https://api.github.com/users/wesm/... | 0 | 2012-08-06T20:07:04Z | 2012-08-12T20:37:34Z | 2012-08-12T20:37:34Z | CONTRIBUTOR | null | ``` python
In [34]: tuples = [t for t in product(range(2), range(2))]
In [35]: index = pandas.MultiIndex.from_tuples(tuples, names=[u'\u0394', 'i1'])
In [36]: df = pandas.DataFrame(np.random.randn(4,4), index=index)
In [37]: s = pandas.Series(range(4), index=index)
In[38]: df
...
UnicodeEncodeError: 'ascii' codec c... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1737 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1737/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1737/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1737/events | https://github.com/pandas-dev/pandas/issues/1737 | 6,080,561 | MDU6SXNzdWU2MDgwNTYx | 1,737 | plot of Series fails | {
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"followers_url": "https://api.github.com/users/wesm/... | 5 | 2012-08-07T15:23:26Z | 2016-10-12T23:03:07Z | 2012-08-13T08:02:16Z | NONE | null | The example here fails with 0.8.1 (worked with 0.8.0)
http://pandas.pydata.org/pandas-docs/dev/computation.html?highlight=outlier#moving-rolling-statistics-moments
In [1]: from pandas import *
In [2]: from numpy.random import randn
In [3]: ts = Series(randn(1000), index=date_range('1/1/2000', periods=1000))
In [4]:... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1738 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1738/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1738/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1738/events | https://github.com/pandas-dev/pandas/issues/1738 | 6,089,141 | MDU6SXNzdWU2MDg5MTQx | 1,738 | Returning Series of dicts from DataFrame.apply | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-08-07T21:16:32Z | 2016-10-12T23:03:08Z | 2013-03-23T01:53:06Z | MEMBER | null | from the mailing list cc @lodagro
```
That is indeed odd.
There also seems to be a dependency on the dtype. Below an example for all ints and all floats.
In [121]: df
Out[121]:
A B
a 7 0
b 7 -2
In [122]: df.apply(foo, 1)
Out[122]:
A B
a NaN NaN
b NaN NaN
All NaN???
I would expect to see this:
In [1... | {
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"description": "IO issue... | closed | false | null | [] | {
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Would rely on BeatifulSoup to parse html data.
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https://api.github.com/repos/pandas-dev/pandas/issues/1740 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1740/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1740/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1740/events | https://github.com/pandas-dev/pandas/issues/1740 | 6,089,377 | MDU6SXNzdWU2MDg5Mzc3 | 1,740 | Multiple file reading performance issues | {
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"f... | 1 | 2012-08-07T21:25:30Z | 2014-05-29T00:31:21Z | 2014-05-29T00:31:21Z | MEMBER | null | from mailing list
```
Hi,
I'm using pandas to read in a set of tab delimited files into DataFrames. Each file has only 3-5 columns and roughly 20,000 rows. The files have a column that I'd like to index by, but some of the entries are duplicates. I find that it takes roughly 5 seconds to read a set of three such file... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1741 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1741/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1741/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1741/events | https://github.com/pandas-dev/pandas/issues/1741 | 6,089,468 | MDU6SXNzdWU2MDg5NDY4 | 1,741 | Errors in 0.8.1 when run with Django/uWSGI, but not with Django's dev runserver | {
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"followers_url": "https://api.github.com/users/wesm/... | 3 | 2012-08-07T21:29:23Z | 2012-09-08T21:11:23Z | 2012-09-08T21:11:23Z | CONTRIBUTOR | null | I'm using pandas in a Django application running on Ubuntu 12.04 and after upgrading from pandas 0.6.1 to 0.8.1 I'm getting some errors that completely prevent the application from running.
If I run Django's development server (manage.py runserver), everything works fine, but if instead I run uWSGI I see the following... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1742 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1742/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1742/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1742/events | https://github.com/pandas-dev/pandas/issues/1742 | 6,092,176 | MDU6SXNzdWU2MDkyMTc2 | 1,742 | qcut not working properly with groupby | {
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---
print pandas.**version**
0.8.1
frame = DataFrame({'data1': np.random.randn(1000), 'data2': np.random.randn(1000)})
factor = qcut(frame.data1, 4)
frame.data2.groupby(factor)
Out[43]: <pandas.core.groupby.SeriesGroupBy at 0x... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1744 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1744/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1744/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1744/events | https://github.com/pandas-dev/pandas/issues/1744 | 6,099,724 | MDU6SXNzdWU2MDk5NzI0 | 1,744 | Support creating a DataFrame from a list of dictionaries providing an index column | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-08-08T10:30:03Z | 2012-09-18T20:34:13Z | 2012-09-18T20:33:40Z | CONTRIBUTOR | null | Hey Wes,
Here's a use case that I think is not covered by Pandas.
It's a use case for creation of a DataFrame object from a
list of dicts.
I extract "documents" (dicts) from a MongoDB database.
From these dicts, one of the keys is meant to be used as
the index.
While I can do something like
df = DataFrame(docume... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1745 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1745/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1745/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1745/events | https://github.com/pandas-dev/pandas/issues/1745 | 6,100,949 | MDU6SXNzdWU2MTAwOTQ5 | 1,745 | Creating a DataFrame from Series with unsorted indeces gives completely bad data | {
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] | closed | false | null | [] | null | 5 | 2012-08-08T11:55:36Z | 2012-08-10T16:06:24Z | 2012-08-10T15:23:45Z | NONE | null | Creating a DataFrame from Series with unsorted indeces gives completely bad data.
I've [written a module](https://gist.github.com/3294509/e777009080fbcbe3c6c91baeb3a71fbb1a092cdc) that reproduces the bug—unless this is by design. Give it a try.
(I'm running `pandas==0.8.1`, Python 2.7.2, and OS X Mountain Lion.)
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https://api.github.com/repos/pandas-dev/pandas/issues/1746 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1746/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1746/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1746/events | https://github.com/pandas-dev/pandas/issues/1746 | 6,102,100 | MDU6SXNzdWU2MTAyMTAw | 1,746 | Extremely slow repr() on small data frame | {
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```
In [6]: x.shape
Out[6]: (4, 32)
```
Its repr() looks like this:
```
In [7]: print repr(x)
<class 'pandas.core.frame.DataFrame'>
MultiIndex: 4 entries, ('arquant9.crw', 10, 336640) to ('arquant9.crw', 10, 336652)
Data... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1747 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1747/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1747/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1747/events | https://github.com/pandas-dev/pandas/issues/1747 | 6,106,974 | MDU6SXNzdWU2MTA2OTc0 | 1,747 | Stable regression | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1748 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1748/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1748/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1748/events | https://github.com/pandas-dev/pandas/pull/1748 | 6,119,227 | MDExOlB1bGxSZXF1ZXN0MjAxMjAyMw== | 1,748 | Added options data functionality | {
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Answers issue #1739
Also cleaned up a bit of the /pandas/io/data.py file to comply better with PEP8.
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``` python
In [67]: s = pandas.Series([pandas.DataFrame(np.random.randn(2,2)) for i in range(5)])
In [68]: s
Exception ValueError: ValueError('Cannot call bool() on DataFrame.',) in 'util._checknull' ignore... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1750 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1750/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1750/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1750/events | https://github.com/pandas-dev/pandas/issues/1750 | 6,140,363 | MDU6SXNzdWU2MTQwMzYz | 1,750 | Assignment to DataFrame through .ix with non-unique MultiIndex | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-09T23:37:20Z | 2012-08-13T02:45:11Z | 2012-08-13T02:45:01Z | NONE | null | Hi,
I think there might be a bug in the assignment to a DataFrame object through .ix when non-unique MultiIndexes are involved. The next sample code describes this issue:
```
In [1]: from pandas import DataFrame, MultiIndex
In [2]:
In [2]: df = DataFrame([[1, 1, "x", "X"], [1, 1, "y", "Y"], [1, 2, "z", "Z"]],
.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1751 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1751/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1751/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1751/events | https://github.com/pandas-dev/pandas/issues/1751 | 6,147,046 | MDU6SXNzdWU2MTQ3MDQ2 | 1,751 | "adjust" kwarg missing in ewmcorr, ewmstd etc. | {
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"description": "2014-02-3: previous version released",
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"labels_url": "htt... | 2 | 2012-08-10T09:36:25Z | 2014-02-18T18:57:38Z | 2014-02-18T18:57:38Z | NONE | null | In 8.1, the "adjust" argument was added to pandas.moments.ewma, but not to ewmcorr, ewmcov, ewmstd, ewmvar, ewmvol Their doc string says all of them have the option to pass adjust, but that's not the case. It's a trivial change & I'll try to submit a pull request to fix it if I find the time.
discussion
https://grou... | {
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"f... | 17 | 2012-08-10T13:02:46Z | 2014-11-02T18:16:51Z | 2014-11-02T18:16:30Z | NONE | null | This was on the list, but so it doesn't get forgotten: https://groups.google.com/d/msg/pydata/EaPRB4KNeTQ/Y-3kG5gW3xMJ
Summary: storing a large multi-index takes a _lot_ of memory, with current pandas master, once it has been indexed into once. ~200 megabytes for a 1 mega-entry index. (As compared to ~20 megabytes pic... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1753 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1753/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1753/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1753/events | https://github.com/pandas-dev/pandas/issues/1753 | 6,154,126 | MDU6SXNzdWU2MTU0MTI2 | 1,753 | Failure when constructing a DataFrame from multiple time series. | {
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Constructing a DataFrame from multiple time series fails, all values from the resulting frame are NaN (which is not the case in the individual series).
Code to reproduce: http://pastebin.com/WTsCkKrL
I could reproduce it.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1755 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1755/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1755/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1755/events | https://github.com/pandas-dev/pandas/issues/1755 | 6,159,276 | MDU6SXNzdWU2MTU5Mjc2 | 1,755 | isnull returns a boolean for array-like inputs | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-10T18:42:45Z | 2012-08-10T22:10:22Z | 2012-08-10T22:10:21Z | CONTRIBUTOR | null | In numpy
``` python
>>> np.isnan([[False]])
array([[False]], dtype=bool)
```
In pandas
``` python
>>> pandas.isnull([[False]])
False
>>> pandas.isnull([[1],[2]])
False
```
I would expect these to return arrays for array-like input. Is there any reason not to?
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https://api.github.com/repos/pandas-dev/pandas/issues/1756 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1756/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1756/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1756/events | https://github.com/pandas-dev/pandas/issues/1756 | 6,162,186 | MDU6SXNzdWU2MTYyMTg2 | 1,756 | Time zone conversion routines assume monotonic timestamps | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1757 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1757/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1757/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1757/events | https://github.com/pandas-dev/pandas/issues/1757 | 6,165,207 | MDU6SXNzdWU2MTY1MjA3 | 1,757 | MultiIndexes containing >=1000000 elements do not work | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-08-10T22:23:29Z | 2012-08-13T09:24:39Z | 2012-08-13T03:20:13Z | NONE | null | With current master, any attempt to index into a Series (or whatever) with a MultiIndex and >=1000000 (= _SIZE_CUTOFF) elements simply raises an error:
```
In [5]: n = 1000000 - 1; pandas.Series(np.arange(n), pandas.MultiIndex.from_arrays((["a"] * n, np.arange(n))))[("a", 5)]
Out[5]: 5
In [6]: n = 1000000; pandas.Ser... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1758 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1758/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1758/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1758/events | https://github.com/pandas-dev/pandas/issues/1758 | 6,175,928 | MDU6SXNzdWU2MTc1OTI4 | 1,758 | Wrong defaults in the documentation for "merge" | {
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as of pandas '0.8.2.dev-ee9321f', the merge operation is using False as default value for the optional arguments "left_index" and "right_index". However, its docstring states that the default value for both arguments is True instead.
Thanks and regards.
Manu.
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https://api.github.com/repos/pandas-dev/pandas/issues/1759 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1759/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1759/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1759/events | https://github.com/pandas-dev/pandas/issues/1759 | 6,179,563 | MDU6SXNzdWU2MTc5NTYz | 1,759 | pandas.unique needs to be more careful on index types | {
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```
In [2]: mindex = MultiIndex.from_arrays([np.arange(5).repeat(5), np.tile(np.arange(5), 5)])
In [3]: pd.unique(mindex)
Out[3]: array([], dtype=object)
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1760 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1760/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1760/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1760/events | https://github.com/pandas-dev/pandas/issues/1760 | 6,186,204 | MDU6SXNzdWU2MTg2MjA0 | 1,760 | google search returns old documentation | {
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"followers_url": "https://api.github.com/users/wesm/... | 5 | 2012-08-13T09:34:02Z | 2012-09-10T09:45:20Z | 2012-09-10T03:27:18Z | CONTRIBUTOR | null | Searching google for "pandas groupby" returns links to the 0.7.0 or older documentation on sourceforge.net in the first few places and only then the pydata links. It would be nice if sourceforge could be cleaned up, so that google returns links to the current docs :-)
Thanks!
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https://api.github.com/repos/pandas-dev/pandas/issues/1761 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1761/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1761/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1761/events | https://github.com/pandas-dev/pandas/issues/1761 | 6,188,768 | MDU6SXNzdWU2MTg4NzY4 | 1,761 | DataFrame.corr() throws error on simple data | {
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df3 = DataFrame({"a":[1,2,3,4], "b":[1,2,3,4]})
df3
a b
0 1 1
1 2 2
2 3 3
3 4 4
df3.corr()
Traceback (most recent call last):
File "<console>", line 1, in <module>
File "C:\portabel\Python27\lib\site-packages\pandas\core\frame.py", line 3867, in corr
correl = lib.nancorr(mat)
File "moments.pyx... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1762 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1762/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1762/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1762/events | https://github.com/pandas-dev/pandas/issues/1762 | 6,189,604 | MDU6SXNzdWU2MTg5NjA0 | 1,762 | Slicing on series with integer index behaves positional. | {
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In [12]: s = pandas.Series(range(5), index=[0, 6, 20, 100, 134])
In [13]: s
Out[13]:
0 0
6 1
20 2
100 3
134 4
In [14]: s[1:3]
Out[14]:
6 1
20 2
```
Whereas `s.ix[]` works label based.
``` python
In [15]: s.ix[1:3]
Out[15]: Series([], dtype=int64)
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1763 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1763/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1763/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1763/events | https://github.com/pandas-dev/pandas/issues/1763 | 6,190,428 | MDU6SXNzdWU2MTkwNDI4 | 1,763 | pandas.DatetimeIndex.isin always returns an array of False | {
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``` python
import pandas
import pandas.util.testing as put
index = put.makeDateIndex(4)
index.isin(index) # returns array([False, False, False, False], dtype=bool)
```
It works fine with pandas 0.7.3, i.e. it returns an array of True instead. This works fine as well with a pandas.Int... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1764 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1764/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1764/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1764/events | https://github.com/pandas-dev/pandas/issues/1764 | 6,214,168 | MDU6SXNzdWU2MjE0MTY4 | 1,764 | How argument ignored in to_timestamp | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-14T11:58:32Z | 2016-10-12T23:03:08Z | 2012-11-04T21:21:59Z | CONTRIBUTOR | null | As discussed in https://groups.google.com/group/pydata/browse_thread/thread/180249bd46ed1944 the following fails:
``` python
def test_to_timstamp_how():
months = pd.period_range('01-Aug-2012', periods=1, freq='M')
assert months[0].asfreq('S','S').to_timestamp() == months.to_timestamp(how='start')[0]
#
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1765 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1765/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1765/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1765/events | https://github.com/pandas-dev/pandas/issues/1765 | 6,214,356 | MDU6SXNzdWU2MjE0MzU2 | 1,765 | Slicing a Panel doesn't work as expected | {
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``` python
p = pd.Panel(randint(0, 100, (4,5,2)),
pd.date_range('01-Jan-2012', periods=4, freq='MS').shift(15,'D'),
pd.date_range('01-Jan-2012', periods=5, freq='MS'))
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1766 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1766/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1766/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1766/events | https://github.com/pandas-dev/pandas/issues/1766 | 6,221,424 | MDU6SXNzdWU2MjIxNDI0 | 1,766 | Method for df | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2012-08-14T17:08:18Z | 2013-10-02T21:05:21Z | 2013-09-21T13:28:37Z | NONE | null | See http://stackoverflow.com/questions/11941492/selecting-rows-from-a-pandas-dataframe-with-a-compound-hierarchical-index
let's say I want to filter a DataFrame such that level[k] only contains the values x, y or z.
A vectorized possibility is:
```
df[np.in1d(df.index.labels[k], match([x, y, z], df.index.levels[k]))]... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1767 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1767/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1767/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1767/events | https://github.com/pandas-dev/pandas/pull/1767 | 6,223,578 | MDExOlB1bGxSZXF1ZXN0MjA1NjY5MA== | 1,767 | Update docs | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-08-14T18:36:41Z | 2014-06-30T23:58:04Z | 2012-09-08T22:12:31Z | CONTRIBUTOR | null | Minor docs correction for statsmodels and add statsmodels to intersphinx as per discussion in #1501.
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https://api.github.com/repos/pandas-dev/pandas/issues/1768 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1768/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1768/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1768/events | https://github.com/pandas-dev/pandas/issues/1768 | 6,236,413 | MDU6SXNzdWU2MjM2NDEz | 1,768 | console_encode() fails on unicode when using ipython-notebook | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1769 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1769/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1769/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1769/events | https://github.com/pandas-dev/pandas/issues/1769 | 6,240,552 | MDU6SXNzdWU2MjQwNTUy | 1,769 | DatetimeIndex constructor is inconsistent | {
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What it should never do is assume different formats for different strings in the same sequence (the current behaviour):
- If ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1770 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1770/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1770/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1770/events | https://github.com/pandas-dev/pandas/issues/1770 | 6,241,406 | MDU6SXNzdWU2MjQxNDA2 | 1,770 | Resampling sometimes returns an extra bin when closed left | {
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print pandas.__version__
```
0.8.1
```
dtrange = pandas.date_range(start='1-1-2009', periods=31, freq='D')
raw = pandas.Series(np.arange(len(dtrange)), index=dtrange)
test1 = raw.resample('M', how='count', closed='left', label='left')
test2 = raw.resample('M', how='mean', closed='left', label='left')
print test... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1771 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1771/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1771/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1771/events | https://github.com/pandas-dev/pandas/issues/1771 | 6,241,640 | MDU6SXNzdWU2MjQxNjQw | 1,771 | Resampling with custom freq length: "Values falls before first bin" | {
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print pandas.__version__
```
0.8.1
```
dtrange = pandas.date_range(start='1-1-2009', periods=21, freq='D')
raw = pandas.Series(np.arange(len(dtrange)), index=dtrange)
test1 = raw.resample('7D', how='count', closed='right')
print test1
```
2009-01-01 1
2009-01-08 7
2009-01-15 7
2009-01-22 6
```
tes... | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-16T03:01:34Z | 2012-09-11T01:13:59Z | 2012-09-11T01:11:58Z | CONTRIBUTOR | null | Simple Example
``` python
import pandas as pd
start = datetime.datetime(1999, 3, 1, 5)
# end hour is less than start
end = datetime.datetime(2012, 7, 31, 4)
bad_ind = pd.date_range(start, end, freq="30min")
df = pd.DataFrame({'close':1}, index=bad_ind)
try:
df.resample('AS', 'sum')
except ValueError as e:
prin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1773 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1773/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1773/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1773/events | https://github.com/pandas-dev/pandas/issues/1773 | 6,263,767 | MDU6SXNzdWU2MjYzNzY3 | 1,773 | DataFrame.drop_duplicates works literally only with list of column names, but fails when used on output of DataFrame.columns | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-16T13:00:45Z | 2013-12-04T00:57:58Z | 2012-09-04T20:28:13Z | NONE | null | `DataFrame.drop_duplicates()` does not properly handle array objects returned by `DataFrame.columns` (whether or not you use `DataFrame.columns.values` to get a NumPy array). If you compute
```
list(DataFrame.columns.values)
```
then it works, but this is needless overkill, especially when dealing with a large numbe... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1774 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1774/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1774/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1774/events | https://github.com/pandas-dev/pandas/issues/1774 | 6,285,287 | MDU6SXNzdWU2Mjg1Mjg3 | 1,774 | Error when using py2exe & pandas 0.8.1 | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-17T09:15:45Z | 2012-09-09T02:55:31Z | 2012-09-09T02:55:31Z | NONE | null | When compiling pandas 2 errors prevent the compiled installer from running:
In pandas.core.format (line 155) an unitintialised doc string is used:
**doc** += docstring_to_string
Easy solution:
if **doc**:
**doc** += docstring_to_string
else:
**doc** = docstring_to_string
In pandas.utils.decorators.py line ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1775 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1775/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1775/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1775/events | https://github.com/pandas-dev/pandas/issues/1775 | 6,293,191 | MDU6SXNzdWU2MjkzMTkx | 1,775 | date_range returning wrong dates and times | {
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In [163]: rng = date_range('01/01/2011', periods=72, freq='H')
In [164]: rng[:5]
Out[164]:
<class 'pandas.tseries.index.DatetimeIndex'>
[2051-05-17 05:40:40.331386880, ...,... | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-17T17:05:32Z | 2012-09-09T03:25:23Z | 2012-09-09T03:25:23Z | CONTRIBUTOR | null | As of pandas 0.8.1, the Period and PeriodIndex display uses the English abbreviations for the month. Suggest that ISO 8601, would be a better choice.
Annual Period is fine...
> z =PeriodIndex([Period('2012'), Period('2013')])
>
> z
> Out[182]:
> <class 'pandas.tseries.period.PeriodIndex'>
> freq: A-DEC
> [2012, ..... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1777 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1777/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1777/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1777/events | https://github.com/pandas-dev/pandas/issues/1777 | 6,294,721 | MDU6SXNzdWU2Mjk0NzIx | 1,777 | DatetimeIndex from timezone-aware datetimes fails | {
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"followers_url": "https://api.github.com/users/wesm/... | 3 | 2012-08-17T17:39:32Z | 2012-08-18T01:57:02Z | 2012-08-18T01:56:03Z | NONE | null | If you try to create a DatetimeIndex from a list of timezone aware datetimes, you get the exception: "Tz-aware datetime.datetime cannot be converted to datetime64 unless utc=True"
For example:
> > > import pandas, datetime, pytz
> > > d = [datetime.datetime(2012, 8, 19, tzinfo=pytz.timezone('US/Eastern'))]
> > > pand... | {
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> > > dr = pandas.date_range('03/06/2012 00:00', periods=25, freq='W-FRI', tz='US/Eastern')
> > > print dr
> > > <class 'pandas.tseries.index.DatetimeIndex'>
> > > [2012-03-09 00:00:00, ..., 2012-08-24 01:00:00]
> > > Length: 25, Freq: W-FRI, Timezone: US/Eastern
This is midnight at the start, but 1am at... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1779 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1779/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1779/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1779/events | https://github.com/pandas-dev/pandas/issues/1779 | 6,294,796 | MDU6SXNzdWU2Mjk0Nzk2 | 1,779 | DatetimeIndex.values gives bad output | {
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> > > dr = pandas.date_range('03/06/2012 00:00', periods=25, freq='W-FRI', tz='US/Eastern')
> > > dr.values
> > > array([1970-01-16 67:00:00, 1970-01-16 234:00:00, 1970-01-16 145:00:00,
> > > 1970-01-16 63:00:00, 1970-01-16 229:00:00, 1970-01-16 142:00:00,
> > > 1970-01-16 57:00:00, 1970-01-... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1780 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1780/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1780/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1780/events | https://github.com/pandas-dev/pandas/issues/1780 | 6,305,523 | MDU6SXNzdWU2MzA1NTIz | 1,780 | rolling_corr() doesn't handle nan well | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1781 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1781/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1781/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1781/events | https://github.com/pandas-dev/pandas/issues/1781 | 6,308,037 | MDU6SXNzdWU2MzA4MDM3 | 1,781 | typo in the IO documentation | {
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The [read_table documentation for white space](http://pandas.pydata.org/pandas-docs/dev/io.html#csv-text-files) should have a backslash in it.
wrong way:
da... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1782 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1782/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1782/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1782/events | https://github.com/pandas-dev/pandas/pull/1782 | 6,308,082 | MDExOlB1bGxSZXF1ZXN0MjA5NTg3MQ== | 1,782 | console_encode() fails on unicode when using ipython-notebook | {
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> > > pandas.common.console_encode(u"\u05d0")
> > > '?'
I traced this back to sys.stdin.encoding being set to None rather then 'utf-8' like in the shell.
Attached is a fix for your consideration. the test is just a stub since mocking is required
to reproduce the bug when testing i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1783 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1783/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1783/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1783/events | https://github.com/pandas-dev/pandas/issues/1783 | 6,310,014 | MDU6SXNzdWU2MzEwMDE0 | 1,783 | Default empty DataFrame to dtype=object | {
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``` python
import pandas as pd
data = {}
columns = ['symbol', 'price']
df = pd.DataFrame(data, columns=columns)
df.symbol == 'AAPL'
# TypeError: Could not compare <type 'str'> type with Series
```
The problem being that an empty dataframe's dtype defaults to float. I've adjusted for it by... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1784 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1784/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1784/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1784/events | https://github.com/pandas-dev/pandas/pull/1784 | 6,313,701 | MDExOlB1bGxSZXF1ZXN0MjA5NzUzMA== | 1,784 | Str contains na | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-08-19T17:32:42Z | 2014-07-16T09:23:17Z | 2012-09-09T00:41:37Z | CONTRIBUTOR | null | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1785 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1785/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1785/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1785/events | https://github.com/pandas-dev/pandas/pull/1785 | 6,316,354 | MDExOlB1bGxSZXF1ZXN0MjA5ODI4MQ== | 1,785 | Add expanding moment functions and related tests. | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-20T00:03:45Z | 2014-06-26T16:50:28Z | 2012-09-08T21:06:53Z | CONTRIBUTOR | null | Implement `expanding_` analogues to the `rolling_` moment functions available in `pandas/stats/moments.py` by calling the `rolling_` function with `window=len(arg)` and `min_periods` defaulting to the minimum number of data points to compute the statistic (`1` for most, `4` for kurtosis, etc.). Resolves Issue #849.
Th... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1786 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1786/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1786/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1786/events | https://github.com/pandas-dev/pandas/issues/1786 | 6,317,707 | MDU6SXNzdWU2MzE3NzA3 | 1,786 | inconsistency in text handling of pandas read_table() function | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-08-20T03:34:54Z | 2016-10-12T23:03:09Z | 2012-09-18T20:13:17Z | CONTRIBUTOR | null | I've been trying to get around an inconsistency in how pandas read_table() function handles two very similar tables. A few people have given some suggestions about how to handle this problem on [StackOverflow](http://stackoverflow.com/questions/12031532/possible-inconsistency-in-text-handling-of-pandas-read-table-funct... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1787 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1787/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1787/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1787/events | https://github.com/pandas-dev/pandas/issues/1787 | 6,319,588 | MDU6SXNzdWU2MzE5NTg4 | 1,787 | import error with pyinstaller, related to pythoncom; pywin32 | {
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My script contains only one line:
import pandas as pd
When I run the compiled executable created using pyinstaller in debug mode, i get the following error:
_MEIPASS2 is NULL
archivename is C:\pyinstaller-devel\TestImport\dist\TestImport\TestImport.ex... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1788 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1788/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1788/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1788/events | https://github.com/pandas-dev/pandas/issues/1788 | 6,326,693 | MDU6SXNzdWU2MzI2Njkz | 1,788 | pct_change() fails on series holding int64 | {
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] | closed | false | null | [] | null | 0 | 2012-08-20T14:31:12Z | 2012-08-22T18:38:29Z | 2012-08-22T18:38:29Z | CONTRIBUTOR | null | ``` python
In [132]: df
Out[132]:
A B
a 10 8
b 12 16
c 12 24
In [133]: df.dtypes
Out[133]:
A int64
B int64
In [134]: df.pct_change()
Out[134]:
A B
a NaN NaN
b 0.2 1.0
c 0.0 0.5
In [135]: df['A'].pct_change()
-------------------------------------------------------------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1789 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1789/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1789/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1789/events | https://github.com/pandas-dev/pandas/issues/1789 | 6,329,122 | MDU6SXNzdWU2MzI5MTIy | 1,789 | infer_freq end assumption | {
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... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-20T16:04:24Z | 2013-12-04T00:43:04Z | 2012-09-10T18:40:25Z | CONTRIBUTOR | null | I'm not sure whether this is something that should be fixed/changed or not, but right now infer_freq takes the first value in a DatetimeIndex and uses that to impose end of period assumptions. E.g., if I have
```
dates = sm.tsa.datetools.dates_from_range('1959Q2', '2009Q3')
pandas.Index(dates).inferred_freq
```
I ge... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1790 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1790/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1790/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1790/events | https://github.com/pandas-dev/pandas/issues/1790 | 6,331,816 | MDU6SXNzdWU2MzMxODE2 | 1,790 | Creating DatetimeIndex from timezone-aware datetimes shifts the times | {
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Using an easy way to get a list of datetimes by creating a DatetimeIndex and casting it to a list:
dr = pandas.date_range('2012-06-02', periods=10, tz=pytz.timezone('US/Eastern'))
<class 'pandas.t... | {
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```
np.version.full_version
#'1.6.1'
df = pandas.DataFrame(['jack and jill','jesse and frank'])
split_df = df[0].str.split(r'\s+and\s+')
split_df.to_csv('t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1792 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1792/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1792/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1792/events | https://github.com/pandas-dev/pandas/pull/1792 | 6,332,780 | MDExOlB1bGxSZXF1ZXN0MjEwNTU4Nw== | 1,792 | Handle NoneType docstrings to support the -OO interpreter option | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-08-20T18:50:10Z | 2014-06-18T22:10:25Z | 2012-09-08T21:10:54Z | CONTRIBUTOR | null | This fixes the issue I described in #1741.
When running uWSGI with the `--optimize` option set to `2`, it passes the `-OO` option to the interpreter and then there are no docstrings and pandas errors out during import.
I also noticed there was a note about this [here](https://github.com/pydata/pandas/blob/master/pand... | {
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```
In [1162]: Period('2012', freq='A-DEC') - Period(2002', freq='A-DEC')
File "<ipython-input-1162-41a08553f136>", line 1
Period('2012', freq='A-DEC') - Period(2002', freq='A-DEC')
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Now I do this by setting all experiments on a st... | {
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``` python
In [74]: df
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https://api.github.com/repos/pandas-dev/pandas/issues/1798 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1798/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1798/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1798/events | https://github.com/pandas-dev/pandas/issues/1798 | 6,372,582 | MDU6SXNzdWU2MzcyNTgy | 1,798 | Unexpected result when calculating standard deviation and variance | {
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] | closed | false | null | [] | {
"closed_at": "2012-10-06T19:22:59Z",
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"created_at": "2012-07-23T19:17:56Z",
"creator": {
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"followers_url": "https://api.github.com/users/wesm/... | 5 | 2012-08-22T09:09:49Z | 2012-09-26T23:10:51Z | 2012-09-26T23:10:51Z | CONTRIBUTOR | null | Pandas 0.8.1:
```
import pandas as pd
a=pd.Series([0, 1, 3, 6])
a.mean(), a.std(), a.var()
a.values.mean(), a.values.std(), a.values.var()
```
I would expect both last lines to return the same result. However, the former returned:
```
(2.5, 2.6457513110645907, 7.0)
```
and the latter:
```
(2.5, 2.2912878474779199,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1799 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1799/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1799/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1799/events | https://github.com/pandas-dev/pandas/issues/1799 | 6,375,476 | MDU6SXNzdWU2Mzc1NDc2 | 1,799 | .ix() failure for mixed-integer index | {
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"description": "Related to indexing on s... | closed | false | {
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"events_url": "https://api.github.com/users/wesm/events{/privacy}",
"followers_url": "https://api.github.com/users/wesm/... | 3 | 2012-08-22T12:11:18Z | 2012-09-11T02:40:30Z | 2012-09-11T02:40:30Z | CONTRIBUTOR | null | from [mailinglist](https://groups.google.com/forum/?fromgroups=#!topic/pystatsmodels/6n0wj9iLKTI)
cc @ruidc
```
With the following DataFrame:
df = pandas.DataFrame(index=[1, 10, 'C', 'E'], columns=[1, 2, 3])
df.ix[df.index[:-1]] works
df.ix[:-1] doesn't
df.ix[[1, 10]] does not work
df.ix[pandas.Index([1, 10], dtyp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1800 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1800/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1800/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1800/events | https://github.com/pandas-dev/pandas/issues/1800 | 6,375,548 | MDU6SXNzdWU2Mzc1NTQ4 | 1,800 | plot() fails with a combined bar and line graph | {
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... | closed | false | null | [] | {
"closed_at": "2013-12-30T19:53:14Z",
"closed_issues": 1076,
"created_at": "2012-11-15T23:33:37Z",
"creator": {
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"followers_url": "https://api.github.com/users/wesm... | 5 | 2012-08-22T12:16:11Z | 2016-10-12T23:03:09Z | 2013-09-21T13:36:28Z | NONE | null | When I plot one column of a df as a bar, run twinx(), and plot another as a line, I get the following error:
(using pandas 0.7.0 and numpy 1.5.1)
In [94]: Traceback (most recent call last):
File "/intucell/IntuRMS/intustall/deps/osx/lib/python2.7/site-packages/matplotlib/artist.py", line 55, in draw_wrapper
draw... | {
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} | https://api.github.com/repos/pandas-dev/pandas/issues/1800/timeline | null | null | null |
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