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In [24]: ts2.index
Out[24]:
<class 'pandas.tseries.index.DatetimeIndex'>
freq: <1 Day>, timezone: US/Central
[1990-01-01 00:00:00-06:00, ..., 2000-01-01 00:00:00-06:00]
length: 3653
In [25]: ts2.take(range(5)).index
Out[25]:
DatetimeIndex([1990-01-01 00:00:00, 1990-01-02 00:00:00, 1990-01-03 00:00:00,
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https://api.github.com/repos/pandas-dev/pandas/issues/1103 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1103/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1103/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1103/events | https://github.com/pandas-dev/pandas/issues/1103 | 4,227,233 | MDU6SXNzdWU0MjI3MjMz | 1,103 | How to store timestamps with time zone in Series/DataFrame? | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1104 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1104/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1104/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1104/events | https://github.com/pandas-dev/pandas/issues/1104 | 4,228,899 | MDU6SXNzdWU0MjI4ODk5 | 1,104 | Import error after update | {
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> > > Traceback (most recent call last):
> > > File "<stdin>", line 1, in <module>
> > > File "/usr/local/lib/python2.7/dist-packages/pandas-0.8.0.dev_be5cd06-py2.7-linux-x86_64.egg/pandas/**init**.py", line 22, in <module>
> > > from pandas.core.api import *
> > > File "/usr/local/... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1105 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1105/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1105/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1105/events | https://github.com/pandas-dev/pandas/issues/1105 | 4,231,913 | MDU6SXNzdWU0MjMxOTEz | 1,105 | More informative error message with malformed CSV file | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1106 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1106/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1106/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1106/events | https://github.com/pandas-dev/pandas/issues/1106 | 4,232,468 | MDU6SXNzdWU0MjMyNDY4 | 1,106 | Bug? numpy.dtype is not sortable. | {
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It looks like dtype does not support sorting:
``` python
>>> from numpy import dtype
>>> sorted([dtype('bool'), dtype('float64'), dtype('complex64'),
... dtype('float64... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1107 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1107/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1107/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1107/events | https://github.com/pandas-dev/pandas/issues/1107 | 4,235,731 | MDU6SXNzdWU0MjM1NzMx | 1,107 | nosetests pandas.tseries.tests.test_resample 'double free or corruption' | {
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(pandas)[1837][n] nosetests pandas.tseries.tests.test_resample
*** glibc detected *** ~/.virtualenvs/pandas/bin/python: double free or corruption (!prev): 0x0000000003d319f0 ***
======= Backtrace: =========
/lib64/libc.so.6[0x3d7047245f]
/lib64/libc.so.6(cfree+0x4b)[0x3d704728bb]
~/.virtualenvs/pandas/lib/python2.... | {
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see http://pandas.pydata.org/pandas-docs/stable/visualization.html for an example.
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In [6]: ts = ts.resample('M', kind='period')
In [7]: ts
Out[7]:
Jan-1990 -0.008004
Feb-1990 -0.117806
Mar-1990 0.291086
Apr-1990 -0.298024
May-1990 -0.306769
Jun-1990 0.173145
Jul-1990 0.144821
Aug-1990 -0.238503
Sep-1990 0.102926
Oct-1990 -0.023604
Nov-1990 0.043893
Dec-1990 -0.22933... | {
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... | closed | false | null | [] | {
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(Pdb) rng
<class 'pandas.tseries.index.DatetimeIndex'>
freq: <1 Day>, timezone: None
[2000-01-01 00:00:00, ..., 2000-01-31 00:00:00]
length: 31
(Pdb) rng2 = rng.repeat(5)
(Pdb) rng2
<class 'pandas.tseries.index.DatetimeIndex'>
freq: <1 Day>, timezone: None
[2000-01-01 00:00:00, ..., 2000-01-31 00:00:00]
length: 155... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1111 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1111/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1111/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1111/events | https://github.com/pandas-dev/pandas/issues/1111 | 4,246,158 | MDU6SXNzdWU0MjQ2MTU4 | 1,111 | Add tshift method for periodindex/datetimeindexed with frequency | {
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"events_url": "https://api.github.com/users/wesm/events{/privacy}",
"followers_url": "https://api.github.com/users/wesm/... | 0 | 2012-04-23T18:17:49Z | 2012-05-03T01:27:37Z | 2012-05-03T01:27:37Z | MEMBER | null | A bit tedious to have to specify the own frequency, e.g.:
`ts / ts.shift(freq='B')`
If freq is already `B` then you would like to just type: `ts / ts.tshift(1)`, this should raise an exception if no frequency set
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https://api.github.com/repos/pandas-dev/pandas/issues/1112 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1112/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1112/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1112/events | https://github.com/pandas-dev/pandas/issues/1112 | 4,246,195 | MDU6SXNzdWU0MjQ2MTk1 | 1,112 | Poor weekofyear performance | {
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In [14]: rng
Out[14]:
<class 'pandas.tseries.index.DatetimeIndex'>
freq: <1 Day>, timezone: None
[1800-01-01 00:00:00, ..., 2000-01-01 00:00:00]
length: 73049
In [15]: timeit rng.weekofyear
1 loops, best of 3: 501 ms per loop
In [16]: timeit rng.year
100 loops, best of 3: 3.48 ms per loop
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1113 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1113/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1113/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1113/events | https://github.com/pandas-dev/pandas/issues/1113 | 4,247,704 | MDU6SXNzdWU0MjQ3NzA0 | 1,113 | Check that quarterly time rules don't normalize away time of day | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1114 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1114/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1114/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1114/events | https://github.com/pandas-dev/pandas/issues/1114 | 4,247,740 | MDU6SXNzdWU0MjQ3NzQw | 1,114 | Handling of "non-full" PeriodIndex | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-04-23T19:46:12Z | 2012-05-12T17:01:55Z | 2012-05-12T17:01:55Z | MEMBER | null | scikits.timeseries notions of fill_missing_dates, duplicates possible, etc. Little to no testing in this regard
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https://api.github.com/repos/pandas-dev/pandas/issues/1115 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1115/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1115/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1115/events | https://github.com/pandas-dev/pandas/issues/1115 | 4,247,761 | MDU6SXNzdWU0MjQ3NzYx | 1,115 | Add missing fields from DatetimeIndex to Timestamp | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1116 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1116/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1116/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1116/events | https://github.com/pandas-dev/pandas/issues/1116 | 4,247,876 | MDU6SXNzdWU0MjQ3ODc2 | 1,116 | Test/fix Period.to_timestamp issues | {
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... | closed | false | null | [] | {
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"creator": {
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"followers_url": "https://api.github.com/users/wesm/... | 0 | 2012-04-23T19:52:57Z | 2012-04-26T22:58:14Z | 2012-04-26T22:58:14Z | MEMBER | null | Should conform with new PeriodIndex.to_timestamp, add lots of test for annual, quarterly, other frequencies
```
def start_time(self):
return self.to_timestamp(which_end='S')
def end_time(self):
return self.to_timestamp(which_end='E')
def to_timestamp(self, which_end='S'):
"""
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https://api.github.com/repos/pandas-dev/pandas/issues/1117 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1117/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1117/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1117/events | https://github.com/pandas-dev/pandas/issues/1117 | 4,248,211 | MDU6SXNzdWU0MjQ4MjEx | 1,117 | Implement take on PeriodIndex | {
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In [5]: rng
Out[5]:
<class 'pandas.tseries.period.PeriodIndex'>
freq: B
[28-Dec-1999, ..., 02-Jan-2001]
length: 54
In [6]: rng.take(np.random.permutation(len(rng)))
Out[6]:
Int64Index([521672, 521592, 521572, 521587, 521732, 521712, 521512, 521627,
521552, 521582, 521717, 521752, 521737, 521777, 521647, 5... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1118 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1118/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1118/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1118/events | https://github.com/pandas-dev/pandas/issues/1118 | 4,248,347 | MDU6SXNzdWU0MjQ4MzQ3 | 1,118 | PeriodIndex constructor should take frequency from start period if has one | {
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```
In [10]: PeriodIndex(val, periods=20)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/Users/wesm/code/pandas/<ipython-input-10-e39b42220b85> in <module>()
----> 1... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1119 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1119/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1119/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1119/events | https://github.com/pandas-dev/pandas/issues/1119 | 4,248,378 | MDU6SXNzdWU0MjQ4Mzc4 | 1,119 | Support for different "bases" with multiples of deltas | {
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`ts.resample('5min', base=2)`
base=0 should be the default (as it is now)
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https://api.github.com/repos/pandas-dev/pandas/issues/1120 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1120/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1120/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1120/events | https://github.com/pandas-dev/pandas/issues/1120 | 4,248,395 | MDU6SXNzdWU0MjQ4Mzk1 | 1,120 | Parsing mixed time strings? | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1121 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1121/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1121/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1121/events | https://github.com/pandas-dev/pandas/issues/1121 | 4,248,753 | MDU6SXNzdWU0MjQ4NzUz | 1,121 | build error in current master | {
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"followers_url": "https://api.github.com/users/wesm/... | 7 | 2012-04-23T20:43:06Z | 2012-04-26T21:47:47Z | 2012-04-26T21:38:36Z | CONTRIBUTOR | null | ```
creating build/lib.linux-x86_64-2.6/pandas/tseries/tests/data
copying pandas/tseries/tests/data/series.pickle -> build/lib.linux-x86_64-2.6/pandas/tseries/tests/data
copying pandas/tseries/tests/data/frame.pickle -> build/lib.linux-x86_64-2.6/pandas/tseries/tests/data
running build_ext
cythoning pandas/src/tseries.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1122 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1122/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1122/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1122/events | https://github.com/pandas-dev/pandas/issues/1122 | 4,249,648 | MDU6SXNzdWU0MjQ5NjQ4 | 1,122 | NaN group causes all groups to be NaN in groupby.transform with shift | {
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print df.groupby([0,1]).transform(lambda x: x)
```
2
```
0 3
1 4
2 NaN
3 NaN
print df.groupby([0,1]).transform(lambda x: x.shift(1))
2
0 NaN
1 NaN
2 NaN
3 NaN
expected:
2
0 NaN
1 3
2 NaN
3 NaN
use case would be group wise changes of another... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1123 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1123/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1123/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1123/events | https://github.com/pandas-dev/pandas/issues/1123 | 4,250,962 | MDU6SXNzdWU0MjUwOTYy | 1,123 | Integer overflow with period_asfreq on 32-bit system | {
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... | closed | false | null | [] | null | 3 | 2012-04-23T23:08:34Z | 2012-04-24T11:13:37Z | 2012-04-24T11:13:37Z | CONTRIBUTOR | null | This causes a lot of test failures on my system.
```
In [4]: ival_H = Period(freq='H', year=2007, month=1, day=1, hour=0)
In [5]: ival_H.asfreq('S','S')
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/home/thomas/... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1124 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1124/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1124/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1124/events | https://github.com/pandas-dev/pandas/issues/1124 | 4,255,796 | MDU6SXNzdWU0MjU1Nzk2 | 1,124 | sharex and sharey do not turn off redundant tick labeling | {
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[pandas.tools.plotting._subplots()](https://github.com/pydata/pandas/blob/master/pandas/tools/plotting.py#L923) is a copy from matplotlib, but the code to remove the redundant tick labeling w... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1125 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1125/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1125/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1125/events | https://github.com/pandas-dev/pandas/issues/1125 | 4,256,643 | MDU6SXNzdWU0MjU2NjQz | 1,125 | failing unittests on 32b linux machine | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-04-24T09:51:41Z | 2012-04-26T21:39:35Z | 2012-04-26T21:39:35Z | CONTRIBUTOR | null | Just did a fresh install of pandas on a 32bits linux machine (ubuntu), i suppose this is a supported platform.
Running nosetests shows many failures (one example at the bottom).
numpy 1.6.1
Cython 0.16
pandas from master
A lot of them are related to numpy issue:
``` python
In [11]: values = np.random.randn(100000, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1126 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1126/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1126/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1126/events | https://github.com/pandas-dev/pandas/issues/1126 | 4,261,760 | MDU6SXNzdWU0MjYxNzYw | 1,126 | Lost PeriodIndex plotting support | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-04-24T15:17:49Z | 2012-05-01T20:31:05Z | 2012-05-01T20:31:05Z | MEMBER | null | Lost it during the merge and the plot refactor. All that code (pandas/tseries/plotting.py) needs to be cleaned up
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"followers_url": "https://api.github.com/users/wesm/... | 0 | 2012-04-24T15:20:57Z | 2012-04-27T15:47:51Z | 2012-04-27T15:47:51Z | MEMBER | null | Suppose we're doing 5 minute data and want to get 9:34:59 instead of 9:35:00 for the resampled labels. want to do like:
```
ts.resample('5min', closed='left', label='right', loffset=timedelta(seconds=-1))
```
Straightforward to convert the timedelta into microseconds and adjust the datetime64 values
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https://api.github.com/repos/pandas-dev/pandas/issues/1128 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1128/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1128/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1128/events | https://github.com/pandas-dev/pandas/issues/1128 | 4,264,476 | MDU6SXNzdWU0MjY0NDc2 | 1,128 | Add level option to rank() for decile, quartile analysis | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-04-24T17:06:44Z | 2012-07-13T01:38:34Z | 2012-07-13T01:38:34Z | MEMBER | null | What do you think about a kwarg to rank, like "levels=None"? If None, it does the default, which is the 1...n rank. If levels=k, then it does the 1..k, eg 1..10. Then you could do
df.groupby(df.A.rank(levels=10)).mean()
which is a hell of a lot prettier than (df.A.rank()/float(len(df))*10.).astype(int)
Actuall... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1129 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1129/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1129/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1129/events | https://github.com/pandas-dev/pandas/issues/1129 | 4,265,400 | MDU6SXNzdWU0MjY1NDAw | 1,129 | Series/DataFrame.asfreq not implemented for PeriodIndex | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1130 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1130/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1130/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1130/events | https://github.com/pandas-dev/pandas/issues/1130 | 4,273,555 | MDU6SXNzdWU0MjczNTU1 | 1,130 | Method for selecting values at or as of time of day for each date | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1131 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1131/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1131/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1131/events | https://github.com/pandas-dev/pandas/issues/1131 | 4,288,827 | MDU6SXNzdWU0Mjg4ODI3 | 1,131 | Build error with np_datetime_strings on OS X 10.7 | {
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```
gcc-4.2 -DNDEBUG -g -fwrapv -Os -Wall -Wstrict-prototypes -pipe -arch x86_64 -I/Library/Python/2.7/site-packages/numpy-1.7.0.dev_3cb783e_20120425-py2.7-macosx-10.7-x86_64.egg/numpy/core/include -I/Syst... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1132 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1132/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1132/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1132/events | https://github.com/pandas-dev/pandas/issues/1132 | 4,291,391 | MDU6SXNzdWU0MjkxMzkx | 1,132 | Add normalization check / normalize method? | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1133 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1133/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1133/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1133/events | https://github.com/pandas-dev/pandas/issues/1133 | 4,291,467 | MDU6SXNzdWU0MjkxNDY3 | 1,133 | Add ability to set local frequency "context" via context manager or some such | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1134 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1134/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1134/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1134/events | https://github.com/pandas-dev/pandas/issues/1134 | 4,293,455 | MDU6SXNzdWU0MjkzNDU1 | 1,134 | pandas.Series.__eq__ is broken for series with different index | {
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"followers_url": "https://api.github.com/users/jr... | 14 | 2012-04-25T23:59:00Z | 2016-08-25T10:20:52Z | 2016-08-25T10:20:52Z | CONTRIBUTOR | null | Something seems to be wrong with s1 == s2 when s1 and s2 don't have the same index. Here is a snippet example:
``` python
import operator
import pandas
s1 = pandas.Series([1,2], ['a','b'])
s2 = pandas.Series([2,3], ['b','c'])
s1 == s2
s2 == s1
```
with the output:
```
InIn [5]: s1 == s2
Out[5]:
a False
b Fals... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1135 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1135/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1135/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1135/events | https://github.com/pandas-dev/pandas/issues/1135 | 4,297,151 | MDU6SXNzdWU0Mjk3MTUx | 1,135 | df.groupby('key').groups printed all: problem with large arrays | {
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I was working with a rather... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1136 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1136/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1136/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1136/events | https://github.com/pandas-dev/pandas/issues/1136 | 4,302,040 | MDU6SXNzdWU0MzAyMDQw | 1,136 | pandas and pyinstaller | {
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thanks a lot for this great tools.
I try to make a one file distribuable under window with pyinstaller.
This do not work becasue from what I anderstand : "pandas do hidden import" and need a hook-pandas in pyinstaller.
So question : does anyone have tried to use pyinstaller with pandas ?
Thanks a l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1137 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1137/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1137/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1137/events | https://github.com/pandas-dev/pandas/issues/1137 | 4,308,448 | MDU6SXNzdWU0MzA4NDQ4 | 1,137 | Different types returned for numpy 1.5.1 and 1.6.1 | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-04-26T18:14:37Z | 2012-06-21T22:44:55Z | 2012-06-21T22:44:55Z | NONE | null | I noticed that certain `numpy` functions return `pandas.Series` in 1.5.1 and `numpy.array` in 1.6.1. This makes it hard to write code that works for both versions when the index is not `0..n`, but something else like timestamps.
For example on Mac OS X 10.7.3 with numpy 1.5.1:
``` python
Python 2.7.1 (r271:86832, Ju... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1138 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1138/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1138/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1138/events | https://github.com/pandas-dev/pandas/issues/1138 | 4,309,981 | MDU6SXNzdWU0MzA5OTgx | 1,138 | Test joins and set ops with PeriodIndex-ed data | {
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... | closed | false | null | [] | {
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In [5]: idx
Out[5]:
<class 'pandas.tseries.period.PeriodIndex'>
freq: D
[01-Jan-2000, ..., 20-Jan-2000]
length: 20
In [6]: idx.join(idx[:-5], how='inner')
Out[6]:
Int64Index([730120, 730121, 730122, 730123, 730124, 730125, 730126, 730127,
730128, 730129, 730130, 730131, 730132, 730133, 730134])
In [7]: i... | {
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pandas/src/tseries.c: In Funktion »__pyx_pf_6pandas_8_tseries_236join_sorter«:
pandas/src/tseries.c:127783:14: Warnung: Variable »__pyx_bshape_0_where« gesetzt, aber nicht verwendet [-Wunused-but-set-variable]
pandas/src/tseries.c:127780:14: Warnung: Variable »__pyx_bshape_0_counts« gesetzt, aber nicht verwendet [-... | {
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I was wondering if there was a good reason why this works:
``` python
dat.ix[:,2] + 2
```
but not this:
``` python
dat.ix[:,2] = dat.ix[:,2] + 2
```
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In [19]: a
Out[19]:
<class 'pandas.tseries.index.DatetimeIndex'>
freq: D, timezone: None
[2000-01-01 00:00:00, ..., 2000-01-03 00:00:00]
length: 3
In [20]: DatetimeIndex(a)
Out[20]: DatetimeIndex([2000-01-01 00:00:00, 2000-01-02 00:00:00, 20... | {
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df2 = pd.DataFrame(columns=['A', 'B', 'C'], index=[1,2,3])
In [38]: df2
Out[38]:
A B C
1 NaN NaN NaN
2 NaN NaN NaN
3 NaN NaN NaN
In [40]: x = df2.ix[1] # create reference to index 1
In [42]: x['A'] = 3 # this changes the value in original df2
In [43]: df2
Out[43]:
A B C
1 3.0 ... | {
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Right now it's either aggregate whole chunks or 1D arrays, maybe should allow frame-by-frame
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https://api.github.com/repos/pandas-dev/pandas/issues/1151 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1151/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1151/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1151/events | https://github.com/pandas-dev/pandas/issues/1151 | 4,337,977 | MDU6SXNzdWU0MzM3OTc3 | 1,151 | Pickling sparse dataframes with hierarchical indexing results in loss of data | {
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thanks for all the awesome work with Pandas. I just started working on it, and I ran into two distinct bugs:
- The HDFStore function won't accept sparse_dataframes as objects - doing so raises a KeyError.
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In [3]: type(pytz.timezone('US/Eastern'))
Out[3]: pytz.tzfile.US/Eastern
In [4]: pytz.timezone('US/Eastern')._tzinfos
Out[4]:
{(datetime.timedelta(-1, 68400),
datetime.timedelta(0),
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https://api.github.com/repos/pandas-dev/pandas/issues/1157 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1157/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1157/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1157/events | https://github.com/pandas-dev/pandas/issues/1157 | 4,341,199 | MDU6SXNzdWU0MzQxMTk5 | 1,157 | Series.shift doesn't work with PeriodIndex | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1158 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1158/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1158/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1158/events | https://github.com/pandas-dev/pandas/issues/1158 | 4,341,218 | MDU6SXNzdWU0MzQxMjE4 | 1,158 | What should DatetimeIndex + 1 do? | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1159 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1159/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1159/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1159/events | https://github.com/pandas-dev/pandas/issues/1159 | 4,341,309 | MDU6SXNzdWU0MzQxMzA5 | 1,159 | Time zone support with PeriodIndex | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2012-04-29T15:10:33Z | 2018-07-06T20:20:59Z | 2018-07-06T19:34:27Z | MEMBER | null | This might be quite a bit of work, maybe leave for post 0.8.0
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https://api.github.com/repos/pandas-dev/pandas/issues/1160 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1160/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1160/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1160/events | https://github.com/pandas-dev/pandas/issues/1160 | 4,341,387 | MDU6SXNzdWU0MzQxMzg3 | 1,160 | Should avoid hash table creation in monotonic DatetimeIndex? | {
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```
ts[stamp]
```
will cause a hash table population to look up the location of `stamp`. If the index has, say, 10mm timestamps, the allocated hash table will take up at minimum 160 megabytes ((timestamp, location) pairs, each 8 bytes) probably rounded up to 256 megabytes. I... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1161 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1161/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1161/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1161/events | https://github.com/pandas-dev/pandas/issues/1161 | 4,341,498 | MDU6SXNzdWU0MzQxNDk4 | 1,161 | Time series branch, feature request for grouping by volume | {
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"f... | 4 | 2012-04-29T15:45:01Z | 2019-01-11T11:55:18Z | 2019-01-11T11:55:18Z | NONE | null | It looks like the time series branch already includes increased functionality for high performance time resampling between time frequencies. Will there be support for converting from higher frequency data to other grouping methods, such as tick data or 1s bars to 1000 volume bars? Perhaps this doesn't fall into true ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1162 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1162/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1162/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1162/events | https://github.com/pandas-dev/pandas/issues/1162 | 4,342,059 | MDU6SXNzdWU0MzQyMDU5 | 1,162 | Negative numbers not handled correctly in frequency strings | {
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In [2]: datetools.to_offset('-1S')
Out[2]: <1 Second>
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1163 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1163/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1163/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1163/events | https://github.com/pandas-dev/pandas/issues/1163 | 4,342,082 | MDU6SXNzdWU0MzQyMDgy | 1,163 | Frequency strings don't work with loffset parameter in resampling | {
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In [7]: ts
Out[7]:
2000-01-01 00:00:00 -1.135382
2000-01-01 00:01:00 1.295421
2000-01-01 00:02:00 0.625706
2000-01-01 00:03:00 0.235525
2000-01-01 00:04:00 0.254634
2000-01-01 00:05:00 -0.393107
2000-01-01 00:06:00 -1.881196
2000-01-01 00:07:00 -2.447050
2000-01-01 00:08:00 1.055716
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```
In [31]: df1.groupby( [ "Name", "City"] ).size()
Out[31]:
Name City
Alice Seattle 1
Bob Seattle 2
Mallory Portland 2
Seattle 1
In [32]: df1.groupby( [ "Name", "City"] ).si... | {
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```
In [44]: ts.resample('5min')
Out[44]:
2000-01-01 00:00:00 -0.744244
2000-01-01 00:05:00 -0.934083
2000-01-01 00:10:00 0.198829
2000-01-01 00:15:00 1.786013
Freq: 5T
In [45]: ts[2:].resample('5min')
Out[45]:
2000-01-01 00:02:00 -0.903645
2000-01-01 00:07:00 -... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1170 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1170/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1170/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1170/events | https://github.com/pandas-dev/pandas/issues/1170 | 4,343,736 | MDU6SXNzdWU0MzQzNzM2 | 1,170 | Dubious Period interpreting monthly date | {
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In [3]: Period(200701, freq='M')
Out[3]: Period('Jan-16726', 'M')
In [4]: Period('200701', freq='M')
Out[4]: Period('Jul-2020', 'M')
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1171 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1171/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1171/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1171/events | https://github.com/pandas-dev/pandas/issues/1171 | 4,344,078 | MDU6SXNzdWU0MzQ0MDc4 | 1,171 | More efficient "conform check" for array of dates and passed frequency | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1175 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1175/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1175/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1175/events | https://github.com/pandas-dev/pandas/pull/1175 | 4,361,174 | MDExOlB1bGxSZXF1ZXN0MTI2MjA1MQ== | 1,175 | BUG: work around missing NPY_FR_B in numpy 1.7 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1176 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1176/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1176/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1176/events | https://github.com/pandas-dev/pandas/issues/1176 | 4,369,083 | MDU6SXNzdWU0MzY5MDgz | 1,176 | Index(DatetimeIndex) loses freq info | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1177 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1177/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1177/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1177/events | https://github.com/pandas-dev/pandas/issues/1177 | 4,370,132 | MDU6SXNzdWU0MzcwMTMy | 1,177 | DataFrame.hist() doesn't work for DataFrame with only 1 column | {
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In [209]: a = DataFrame(np.asarray([1,2,3,4,5]).T)
In [210]: a
Out[210]:
0
0 1
1 2
2 3
3 4
4 5
In [211]: a.hist()
TypeError Traceback (most recent call last)
H:<ipython-input-211-351515a79fe3> in <module>()
----> 1 a.hist()
C:\Python27\lib\site-pac... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1178 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1178/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1178/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1178/events | https://github.com/pandas-dev/pandas/issues/1178 | 4,371,371 | MDU6SXNzdWU0MzcxMzcx | 1,178 | Add __slots__ to Series | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1179 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1179/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1179/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1179/events | https://github.com/pandas-dev/pandas/pull/1179 | 4,386,820 | MDExOlB1bGxSZXF1ZXN0MTI3MjUxNw== | 1,179 | EHN: (First commit) -- Began implementation of new regex methods for Se... | {
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"followers_url": "https://api.github.com/users/wesm/... | 8 | 2012-05-02T15:14:41Z | 2014-06-26T11:02:15Z | 2012-07-15T22:49:43Z | CONTRIBUTOR | null | ...ries class, performing element-wise regex matching (Series.str_find) and substitution (Series.string_sub).
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https://api.github.com/repos/pandas-dev/pandas/issues/1180 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1180/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1180/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1180/events | https://github.com/pandas-dev/pandas/issues/1180 | 4,389,448 | MDU6SXNzdWU0Mzg5NDQ4 | 1,180 | create a community supported set of typical converters for read_csv | {
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"description": "IO issue... | closed | false | null | [] | null | 6 | 2012-05-02T17:30:01Z | 2014-01-02T02:27:27Z | 2014-01-01T03:40:06Z | CONTRIBUTOR | null | Unfortauntely, nearly no input data file uses ISO format but rather random columns and formats.
Following
https://groups.google.com/forum/?fromgroups#!topic/pydata/pZjQMX_avmY
and
https://github.com/pydata/pandas/issues/854
I would suggest to insert:
https://github.com/pydata/pandas/tree/master/pandas/tseries/co... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1181 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1181/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1181/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1181/events | https://github.com/pandas-dev/pandas/issues/1181 | 4,389,620 | MDU6SXNzdWU0Mzg5NjIw | 1,181 | Don't create (or add option to not create) empty columns when unstacking | {
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```
Hello! I am using the pivot table functionality to good effect. One
issue I am running to, however, is that the columns end up being
roughly a full Cartesian product of the column pivots. That is, there
are blocks of all-NA columns. The row pivots appear to be pruned
already... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1182 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1182/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1182/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1182/events | https://github.com/pandas-dev/pandas/issues/1182 | 4,390,010 | MDU6SXNzdWU0MzkwMDEw | 1,182 | Add frequency for specifying non M-F business day calendar | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1183 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1183/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1183/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1183/events | https://github.com/pandas-dev/pandas/issues/1183 | 4,390,730 | MDU6SXNzdWU0MzkwNzMw | 1,183 | Series.apply bug when result same length as series | {
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In [2]: s = pandas.Series([1,2])
In [3]: s
Out[3]:
0 1
1 2
In [4]: s.apply(lambda x: (x, x+1))
Out[4]:
0 0 1
1 2
1 0 2
1 3
```
But:
```
In [8]: s = pandas.Series([1,2,3])
In [9]: s
Out[9]:
0 1
1 2
2 3
In [10]: s.apply(lambda x: (x, x+1))
Out[10]:
0 (1, 2)
1 (2, 3)
2 ... | {
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In [1]: date_range('1/1/2000', periods=10, freq='1B30min')
Out[1]:
<class 'pandas.tseries.index.DatetimeIndex'>
[2000-01-03 00:30:00, ..., 2000-01-13 04:30:00]
Length: 9, Freq: B, Timezone: None
In [2]: date_range('1/1/2000', periods=10, freq='1B30min').offset
Out[2]: <1 BusinessDay: offset=datetime.timedelta(0, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1185 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1185/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1185/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1185/events | https://github.com/pandas-dev/pandas/issues/1185 | 4,392,131 | MDU6SXNzdWU0MzkyMTMx | 1,185 | Define frequencies like "Last Xday of month" | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1186 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1186/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1186/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1186/events | https://github.com/pandas-dev/pandas/issues/1186 | 4,394,125 | MDU6SXNzdWU0Mzk0MTI1 | 1,186 | As tsfromtxt like ability to convert multiple text file columns into a single date column | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1187 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1187/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1187/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1187/events | https://github.com/pandas-dev/pandas/issues/1187 | 4,403,739 | MDU6SXNzdWU0NDAzNzM5 | 1,187 | reindexing / "'Index' object has no attribute 'freq'" | {
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I've created a DataFrame using read_clipboard() (Pandas built from Git trunk) and am having problems reindexing unless I select rows using the [:] notation. IIRC the index was defined using 'set_index("Timestamp")'.
In [47]:
df
Out[47]:
<class 'pandas.core.frame.DataFrame'>
Index:... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1188 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1188/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1188/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1188/events | https://github.com/pandas-dev/pandas/issues/1188 | 4,404,381 | MDU6SXNzdWU0NDA0Mzgx | 1,188 | Maybe add use_inferred_type option to Index constructor | {
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related to #1187
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https://api.github.com/repos/pandas-dev/pandas/issues/1189 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1189/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1189/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1189/events | https://github.com/pandas-dev/pandas/issues/1189 | 4,405,472 | MDU6SXNzdWU0NDA1NDcy | 1,189 | Add documentation regarding -mno-cygwin option when building on windows | {
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"""
The problem I'm hitting is in getting setup.py to run either with build_ext --inplace or develop, so I can run 'nosetests pandas'
cc1.exe: error: unrecognized command line option '-mno-cygwin'
error: command 'gcc' failed with exit status 1
Which looks like a possible case of http://... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1190 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1190/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1190/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1190/events | https://github.com/pandas-dev/pandas/issues/1190 | 4,405,754 | MDU6SXNzdWU0NDA1NzU0 | 1,190 | Add documentation regarding -mno-cygwin option when building on windows | {
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"""
The problem I'm hitting is in getting setup.py to run either with build_ext --inplace or develop, so I can run 'nosetests pandas'
cc1.exe: error: unrecognized command line option '-mno-cygwin'
error: command 'gcc' failed with exit status 1
Which looks like a possible case of http://... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1191 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1191/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1191/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1191/events | https://github.com/pandas-dev/pandas/issues/1191 | 4,408,488 | MDU6SXNzdWU0NDA4NDg4 | 1,191 | Implement DataFrame.to_timestamp and to_period | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1192 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1192/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1192/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1192/events | https://github.com/pandas-dev/pandas/issues/1192 | 4,409,646 | MDU6SXNzdWU0NDA5NjQ2 | 1,192 | Think about adding Period slicing | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2012-05-03T17:24:31Z | 2019-12-12T14:40:44Z | 2019-12-12T14:40:37Z | CONTRIBUTOR | null | Get subperiods via getitem
p = Period( 2001)
p[0, 'D'] => Period('01-Jan-2001', 'D')
p[0] => Period('2001Q1', 'Q-DEC')
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https://api.github.com/repos/pandas-dev/pandas/issues/1193 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1193/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1193/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1193/events | https://github.com/pandas-dev/pandas/issues/1193 | 4,411,935 | MDU6SXNzdWU0NDExOTM1 | 1,193 | logy argument not respected in pandas.tseries.plotting | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1194 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1194/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1194/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1194/events | https://github.com/pandas-dev/pandas/issues/1194 | 4,415,162 | MDU6SXNzdWU0NDE1MTYy | 1,194 | Add ability to plot Series/TimeSeries easily on secondary Y axis | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1195 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1195/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1195/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1195/events | https://github.com/pandas-dev/pandas/issues/1195 | 4,423,406 | MDU6SXNzdWU0NDIzNDA2 | 1,195 | DocumenTATION for timeseries API | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1196 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1196/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1196/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1196/events | https://github.com/pandas-dev/pandas/issues/1196 | 4,423,581 | MDU6SXNzdWU0NDIzNTgx | 1,196 | DataFrame.take raises exception on list input | {
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/pandas/pandas/core/common.pyc in _ensure_int32(arr)
687
688 def _ensure_int32(arr):
--> 689 if arr.dtype != np.int32:
690 arr = arr.astype(np.int32)
691 return arr
AttributeError: 'list' object has no attribute 'dtype'
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https://api.github.com/repos/pandas-dev/pandas/issues/1197 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1197/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1197/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1197/events | https://github.com/pandas-dev/pandas/issues/1197 | 4,427,084 | MDU6SXNzdWU0NDI3MDg0 | 1,197 | Add limit keyword to fillna method of sparse data frame | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1198 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1198/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1198/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1198/events | https://github.com/pandas-dev/pandas/issues/1198 | 4,432,735 | MDU6SXNzdWU0NDMyNzM1 | 1,198 | Standard deviation error? | {
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Haven't had a chance to dig into it deepe... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1199 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1199/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1199/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1199/events | https://github.com/pandas-dev/pandas/issues/1199 | 4,448,196 | MDU6SXNzdWU0NDQ4MTk2 | 1,199 | Remove period multipliers | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1200 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1200/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1200/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1200/events | https://github.com/pandas-dev/pandas/issues/1200 | 4,453,175 | MDU6SXNzdWU0NDUzMTc1 | 1,200 | failed tests | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-05-07T12:32:10Z | 2013-12-04T00:43:23Z | 2012-05-18T19:24:50Z | NONE | null | I'm running on Windows 7 32-bit, with Python 2.7.2. Dependencies installed, pandas cloned and built.
Here is the output when I run "nosetests pandas" :
................SS.........S...............S.................C:\Python27\lib\site-packages\scikits\statsmodels\tools\tools.py:256: FutureWarning: The default of `pre... | {
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