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https://api.github.com/repos/pandas-dev/pandas/issues/901 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/901/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/901/comments | https://api.github.com/repos/pandas-dev/pandas/issues/901/events | https://github.com/pandas-dev/pandas/issues/901 | 3,603,410 | MDU6SXNzdWUzNjAzNDEw | 901 | timeseries branch, intervals w/ alternate durations | {
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"f... | 11 | 2012-03-11T20:55:39Z | 2020-12-18T23:25:01Z | 2015-01-28T11:05:37Z | CONTRIBUTOR | null | Can the scikits.timeseries based interval code be extended to handle multiples of base durations?
Is it worth considering dropping the existing implementation and use, eg, start + end points (either two arrays, or one structured array), also have for fuzzier indexing some sort of
http://en.wikipedia.org/wiki/Interva... | {
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"f... | 1 | 2012-03-12T05:14:41Z | 2014-06-12T16:38:17Z | 2013-02-27T18:41:23Z | NONE | null | My attempt at a weighted rolling average. Doesn't force the weights to sum to 1. If the min period is less than the length of the arrays, the nan value is skipped along with weighted value. Should the weights be re-normed somehow?
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https://api.github.com/repos/pandas-dev/pandas/issues/904 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/904/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/904/comments | https://api.github.com/repos/pandas-dev/pandas/issues/904/events | https://github.com/pandas-dev/pandas/pull/904 | 3,608,177 | MDExOlB1bGxSZXF1ZXN0OTY1NjYx | 904 | Fixed a typo. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/905 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/905/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/905/comments | https://api.github.com/repos/pandas-dev/pandas/issues/905/events | https://github.com/pandas-dev/pandas/issues/905 | 3,608,944 | MDU6SXNzdWUzNjA4OTQ0 | 905 | Tests pandas.tests.test_graphics.XXX fail | {
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```
pandas.tests.test_tseries.test_pad_backfill_object_segfault ... ok
pandas.tests.test_tseries.test_arrmap ... ok
pandas.tests.test_tseries.test_series_grouper ... ok
=======================... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/906 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/906/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/906/comments | https://api.github.com/repos/pandas-dev/pandas/issues/906/events | https://github.com/pandas-dev/pandas/issues/906 | 3,609,087 | MDU6SXNzdWUzNjA5MDg3 | 906 | build updated Ubuntu packages daily based on repo status | {
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"f... | 9 | 2012-03-12T10:35:19Z | 2014-01-20T22:48:31Z | 2014-01-20T22:48:31Z | CONTRIBUTOR | null | Since pandas is developing very quickly, daily packages can help users to keep track of changes while using their usual software install mechanisms.
Launchpad offers inidvidual package repositories (PPA) and automatic build procedures based on the [bazaar repository](https://code.launchpad.net/+branch/~pythonxy/numpy/... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/907 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/907/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/907/comments | https://api.github.com/repos/pandas-dev/pandas/issues/907/events | https://github.com/pandas-dev/pandas/pull/907 | 3,611,695 | MDExOlB1bGxSZXF1ZXN0OTY3MDI2 | 907 | Patched _safe_fetch to ensure a list of tuples is returned. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/908 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/908/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/908/comments | https://api.github.com/repos/pandas-dev/pandas/issues/908/events | https://github.com/pandas-dev/pandas/issues/908 | 3,612,619 | MDU6SXNzdWUzNjEyNjE5 | 908 | Test Failed: pandas.io.tests.test_parsers.TestParsers | {
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Traceback (most recent call last):
File "C:\src\pandas\pandas\io\tests\test_parsers.py", line 219, in test_read_c
sv_no_index_name
self.assert_(df.ix[:, ['A', 'B', 'C', 'D']].values.dtype == np.float64)
File "C:\src\pandas\pandas\core\indexing.py", line ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/910 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/910/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/910/comments | https://api.github.com/repos/pandas-dev/pandas/issues/910/events | https://github.com/pandas-dev/pandas/issues/910 | 3,639,116 | MDU6SXNzdWUzNjM5MTE2 | 910 | Error when subtracting mixed type DataFrame | {
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import numpy as np
import pandas
X = np.random.rand(10,10)
Y = np.ones((10,1),dtype=int)
df1 = pandas.DataFrame(X)
df1 = df1.join(pandas.DataFrame(Y),lsuffix='.X')
print df1-df1.mean()
---
Traceback (most recent call last):
File "pls_model.py", line 383, in <module>
run(df... | {
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All values, except the one to be set, in the _DataFrame_ became _NaN_.
``` python
In [4]: df
Out[4]:
A B C
0 0.463981 0.163885 0.644793
1 0.979047 0.347373 0.736267
2 0.103155... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/912 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/912/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/912/comments | https://api.github.com/repos/pandas-dev/pandas/issues/912/events | https://github.com/pandas-dev/pandas/issues/912 | 3,648,519 | MDU6SXNzdWUzNjQ4NTE5 | 912 | DataFrame data alignment issue | {
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In [20]: df1 = pandas.DataFrame(np.random.rand(3,3), index=range(3), columns=list('ABC'))
In [21]: df1
Out[21]:
A B C
0 0.061189 0.035471 0.104002
1 0.894004 0.545950 0.852395
2 0.794040 0.448952 0.338134
In [22]: df2 = pandas.DataFrame(np.random.rand(3,3), index=range(3,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/913 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/913/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/913/comments | https://api.github.com/repos/pandas-dev/pandas/issues/913/events | https://github.com/pandas-dev/pandas/issues/913 | 3,650,892 | MDU6SXNzdWUzNjUwODky | 913 | Could be integrated with the Orange data mining suite | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2012-03-14T16:05:22Z | 2016-01-18T00:39:36Z | 2016-01-18T00:39:36Z | NONE | null | The open source Orange project (http://orange.biolab.si/) is a component-based data mining and machine learning suite that can be controlled through the visual Orange Canvas interface or (for experts) through the Python scripting interface. It has many advanced data mining algorithms, visualizations and is probably sui... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/914 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/914/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/914/comments | https://api.github.com/repos/pandas-dev/pandas/issues/914/events | https://github.com/pandas-dev/pandas/issues/914 | 3,659,473 | MDU6SXNzdWUzNjU5NDcz | 914 | improve docs on numpy boolean ops (for indexing) | {
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There's general stuff about boolean indexing but this actually is not a pandas feature but rather a NumPy feature (or-ing arrays with |). Could definitely use a section in the docs about this
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https://api.github.com/repos/pandas-dev/pandas/issues/915 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/915/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/915/comments | https://api.github.com/repos/pandas-dev/pandas/issues/915/events | https://github.com/pandas-dev/pandas/issues/915 | 3,659,912 | MDU6SXNzdWUzNjU5OTEy | 915 | read_csv gives incorrect chunks when chunking headerless single column file of data | {
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pred.dat
which has only two lines of content
0.001
0.051
(this being the actual test case where this happens).
if I do
``````
labchunks = read_csv(fromvw, sep=" ",header=None,chunksize = 100000) #
predchunks= read_table( preddat ,header=None, names=["prediction"],chunksize = 100000 )
print labchun... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/916 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/916/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/916/comments | https://api.github.com/repos/pandas-dev/pandas/issues/916/events | https://github.com/pandas-dev/pandas/issues/916 | 3,659,998 | MDU6SXNzdWUzNjU5OTk4 | 916 | Malformed block from DataFrame.GroupBy | {
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https://api.github.com/repos/pandas-dev/pandas/issues/917 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/917/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/917/comments | https://api.github.com/repos/pandas-dev/pandas/issues/917/events | https://github.com/pandas-dev/pandas/issues/917 | 3,660,227 | MDU6SXNzdWUzNjYwMjI3 | 917 | Potential out-of-bounds array access in Series | {
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```
s = Series([], index=[])
s[-1]
```
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https://api.github.com/repos/pandas-dev/pandas/issues/918 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/918/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/918/comments | https://api.github.com/repos/pandas-dev/pandas/issues/918/events | https://github.com/pandas-dev/pandas/pull/918 | 3,661,215 | MDExOlB1bGxSZXF1ZXN0OTg3NjI0 | 918 | Add sort_columns parameter to plot to allow unsorted plots | {
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I felt like the ordering I had defined in the DataFrame was a pretty decent proxy for how I wanted the subplots to be ordered, so I think this should be an option so I can over-ride the sorting and have the ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/919 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/919/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/919/comments | https://api.github.com/repos/pandas-dev/pandas/issues/919/events | https://github.com/pandas-dev/pandas/issues/919 | 3,667,418 | MDU6SXNzdWUzNjY3NDE4 | 919 | Add filtering capability to GroupBy | {
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"i... | 7 | 2012-03-15T15:13:56Z | 2013-06-06T21:07:08Z | 2013-06-06T21:06:26Z | MEMBER | null | Can be accomplished in a hackish way using apply, but a more structured approach would be nice
7/12/2012: Not sure what I was intending with this one
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https://api.github.com/repos/pandas-dev/pandas/issues/920 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/920/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/920/comments | https://api.github.com/repos/pandas-dev/pandas/issues/920/events | https://github.com/pandas-dev/pandas/issues/920 | 3,668,239 | MDU6SXNzdWUzNjY4MjM5 | 920 | Implement fixed-width file reader | {
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https://api.github.com/repos/pandas-dev/pandas/issues/921 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/921/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/921/comments | https://api.github.com/repos/pandas-dev/pandas/issues/921/events | https://github.com/pandas-dev/pandas/issues/921 | 3,670,621 | MDU6SXNzdWUzNjcwNjIx | 921 | ENH: specify header=['list', 'of', 'headers'] in DataFrame.write_csv() | {
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"description": "IO issue... | closed | false | null | [] | {
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"closed_issues": 485,
"created_at": "2011-08-24T19:15:47Z",
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-03-15T18:10:31Z | 2012-06-25T16:24:48Z | 2012-06-25T16:24:48Z | NONE | null | As with R's write.table col.names which can take a list of column headers to output instead of the
headers.
here's a start, though I'm unsure about hwo it interacts with the index label stuff.
``` Patch
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 248a4e9..8c93488 100644
--- a/pandas/core/frame.py... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/922 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/922/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/922/comments | https://api.github.com/repos/pandas-dev/pandas/issues/922/events | https://github.com/pandas-dev/pandas/issues/922 | 3,671,124 | MDU6SXNzdWUzNjcxMTI0 | 922 | Enable use of index level in joins by name | {
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"default": false,
"description": "Related ... | closed | false | null | [] | {
"closed_at": "2014-05-30T12:17:57Z",
"closed_issues": 755,
"created_at": "2014-01-03T20:19:04Z",
"creator": null,
"description": "2014-02-3: previous version released",
"due_on": "2014-05-31T07:00:00Z",
"html_url": "https://github.com/pandas-dev/pandas/milestone/24",
"id": 526062,
"labels_url": "htt... | 4 | 2012-03-15T18:44:05Z | 2016-10-12T23:02:51Z | 2014-02-18T20:26:57Z | MEMBER | null | ```
In [35]: A
Out[35]:
Aattr3 Aattr1 Aattr2
Aidx1
37 Delta East hard
59 Epsilon East hard
96 Zeta East hard
21 Gamma West medium hard
2 Alpha West soft
10 Beta West soft
In [36]: B
Out[36]:
Bname Batt... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/923 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/923/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/923/comments | https://api.github.com/repos/pandas-dev/pandas/issues/923/events | https://github.com/pandas-dev/pandas/issues/923 | 3,676,296 | MDU6SXNzdWUzNjc2Mjk2 | 923 | dropna able to accept a list/tuple for axis argument | {
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I sometimes work with square matricies that potentially could have a column (and row) of all na's
I find myself doing:
df.dropna(how='all',axis=0).dropna(how='all',axis=1)
so
df.dropna(how='all',axis=[0,1])
e.g.
_dropna = DataFrame.dropna
def revised_dropna(self, axis = None, **kwargs):
if isinstance... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/924 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/924/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/924/comments | https://api.github.com/repos/pandas-dev/pandas/issues/924/events | https://github.com/pandas-dev/pandas/issues/924 | 3,676,297 | MDU6SXNzdWUzNjc2Mjk3 | 924 | dropna able to accept a list/tuple for axis argument | {
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"description": "np.nan, ... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-03-16T01:17:54Z | 2012-09-18T16:34:43Z | 2012-09-18T16:34:30Z | CONTRIBUTOR | null | rationale:
I sometimes work with square matricies that potentially could have a column (and row) of all na's
I find myself doing:
`df.dropna(how='all',axis=0).dropna(how='all',axis=1)`
so
`df.dropna(how='all',axis=[0,1])`
e.g.
```
_dropna = DataFrame.dropna
def revised_dropna(self, axis = None, **kwargs):
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https://api.github.com/repos/pandas-dev/pandas/issues/925 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/925/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/925/comments | https://api.github.com/repos/pandas-dev/pandas/issues/925/events | https://github.com/pandas-dev/pandas/issues/925 | 3,682,815 | MDU6SXNzdWUzNjgyODE1 | 925 | Inconsistent NA handling in comparison ops with dtype=object | {
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"closed_at": "2012-03-16T16:11:29Z",
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test=PD.Series(index=PD.DateRange(DT.datetime(2012,3,15), DT.datetime(2012,3,16)), data=NP.ones(2))
test == test.shift(1)
```
vs
```
test2=PD.Series(index=PD.DateRange(DT.datetime(2012,3,15), DT.datetime(2012,3,16)), data=['a','a'])
test2 == test2.shift(1)
```
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https://api.github.com/repos/pandas-dev/pandas/issues/926 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/926/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/926/comments | https://api.github.com/repos/pandas-dev/pandas/issues/926/events | https://github.com/pandas-dev/pandas/issues/926 | 3,683,566 | MDU6SXNzdWUzNjgzNTY2 | 926 | File reader improvements: explicit dtype, usecols | {
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http://stackoverflow.com/questions/9695668/how-to-specify-dtype-when-using-pandas-read-csv-to-load-data-from-csv-files
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https://api.github.com/repos/pandas-dev/pandas/issues/927 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/927/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/927/comments | https://api.github.com/repos/pandas-dev/pandas/issues/927/events | https://github.com/pandas-dev/pandas/issues/927 | 3,686,430 | MDU6SXNzdWUzNjg2NDMw | 927 | pip install borked... | {
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```
$ virtualenv /tmp/pandatest
$ source /tmp/pandatest/bin/activate
$ pip install pandas
$ python
Python 2.6.6 (r266:84292, Sep 15 2010, 15:52:39)
[GCC 4.4.5] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import pandas
Traceback (most rece... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/928 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/928/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/928/comments | https://api.github.com/repos/pandas-dev/pandas/issues/928/events | https://github.com/pandas-dev/pandas/issues/928 | 3,689,691 | MDU6SXNzdWUzNjg5Njkx | 928 | Not able to change direction of sort on per column basis for DataFrame | {
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https://api.github.com/repos/pandas-dev/pandas/issues/929 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/929/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/929/comments | https://api.github.com/repos/pandas-dev/pandas/issues/929/events | https://github.com/pandas-dev/pandas/issues/929 | 3,690,456 | MDU6SXNzdWUzNjkwNDU2 | 929 | Add a replace method to Series/DataFrame | {
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"followers_url": "https://api.github.com/users/wesm/... | 0 | 2012-03-16T22:33:10Z | 2016-10-12T23:02:51Z | 2012-05-15T20:31:48Z | MEMBER | null | More generalized version of fillna. Want to be able to do stuff like:
```
s.replace([np.nan, ''], 'Missing')
```
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https://api.github.com/repos/pandas-dev/pandas/issues/930 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/930/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/930/comments | https://api.github.com/repos/pandas-dev/pandas/issues/930/events | https://github.com/pandas-dev/pandas/issues/930 | 3,690,674 | MDU6SXNzdWUzNjkwNjc0 | 930 | Short Version Number | {
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<snip>
ValueError: invalid version number '0.7.2.dev-81dcf10'
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https://api.github.com/repos/pandas-dev/pandas/issues/931 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/931/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/931/comments | https://api.github.com/repos/pandas-dev/pandas/issues/931/events | https://github.com/pandas-dev/pandas/issues/931 | 3,692,403 | MDU6SXNzdWUzNjkyNDAz | 931 | Series.kurt and DataFrame.kurt | {
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https://api.github.com/repos/pandas-dev/pandas/issues/932 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/932/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/932/comments | https://api.github.com/repos/pandas-dev/pandas/issues/932/events | https://github.com/pandas-dev/pandas/pull/932 | 3,692,438 | MDExOlB1bGxSZXF1ZXN0MTAwMDc4OA== | 932 | #931 Series.kurt and DataFrame.kurt | {
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https://api.github.com/repos/pandas-dev/pandas/issues/933 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/933/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/933/comments | https://api.github.com/repos/pandas-dev/pandas/issues/933/events | https://github.com/pandas-dev/pandas/issues/933 | 3,693,175 | MDU6SXNzdWUzNjkzMTc1 | 933 | (series == x) doesn't always produce a boolean series: bug? | {
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In [3]: a == 'a'
Out[3]:
0 True
1 NaN
2 False
# There is a NaN in Out[3]. This can't be the desired result because of the following error:
In [4]: b = pandas.Series(['a', 'b', 'c'])
In [5]: (a == 'a') & (b == 'a')
ValueError Trace... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/934 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/934/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/934/comments | https://api.github.com/repos/pandas-dev/pandas/issues/934/events | https://github.com/pandas-dev/pandas/issues/934 | 3,697,802 | MDU6SXNzdWUzNjk3ODAy | 934 | ddof no longer passed for Series.std and Series.var | {
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https://github.com/pydata/pandas/commit/fbb110247ea81e980bf9265cc1b0b26c8eb549be#L5L799
Series.std and Series.var no longer pass along ddof to the nanops.nanvar function.
Also since ddof defaults to 1 in pandas and 0 in numpy.
``` python
arr = np.arange(10)
s = Series(arr)
# False
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https://api.github.com/repos/pandas-dev/pandas/issues/935 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/935/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/935/comments | https://api.github.com/repos/pandas-dev/pandas/issues/935/events | https://github.com/pandas-dev/pandas/pull/935 | 3,698,757 | MDExOlB1bGxSZXF1ZXN0MTAwMjY3OQ== | 935 | scatter plot matrix | {
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I m... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/938 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/938/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/938/comments | https://api.github.com/repos/pandas-dev/pandas/issues/938/events | https://github.com/pandas-dev/pandas/issues/938 | 3,703,265 | MDU6SXNzdWUzNzAzMjY1 | 938 | Add groupby option to skip MultiIndex creation in apply | {
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https://api.github.com/repos/pandas-dev/pandas/issues/939 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/939/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/939/comments | https://api.github.com/repos/pandas-dev/pandas/issues/939/events | https://github.com/pandas-dev/pandas/issues/939 | 3,703,490 | MDU6SXNzdWUzNzAzNDkw | 939 | Add a more memory-efficient RangeIndex-sort of thing to avoid large arange(N) indexes in some cases | {
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https://api.github.com/repos/pandas-dev/pandas/issues/940 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/940/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/940/comments | https://api.github.com/repos/pandas-dev/pandas/issues/940/events | https://github.com/pandas-dev/pandas/issues/940 | 3,707,028 | MDU6SXNzdWUzNzA3MDI4 | 940 | DataFrame.to_excel() fails for boolean values. | {
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--> 796 for val in row])
seems to be the problem here (see below).
Maybe there should be something like (bool(val) if instance(val, np.bool_) ?
In [14]: df = DataFrame([(1,2,3),(4,5,6)],columns = ['a','b','c'])
In [16]: df['d'] = df.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/941 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/941/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/941/comments | https://api.github.com/repos/pandas-dev/pandas/issues/941/events | https://github.com/pandas-dev/pandas/issues/941 | 3,714,134 | MDU6SXNzdWUzNzE0MTM0 | 941 | Pass more than column names to rows/cols args in pivot_table | {
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https://api.github.com/repos/pandas-dev/pandas/issues/943 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/943/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/943/comments | https://api.github.com/repos/pandas-dev/pandas/issues/943/events | https://github.com/pandas-dev/pandas/issues/943 | 3,721,533 | MDU6SXNzdWUzNzIxNTMz | 943 | DataFrame gives uninformative error message when comparing to constants | {
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https://api.github.com/repos/pandas-dev/pandas/issues/944 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/944/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/944/comments | https://api.github.com/repos/pandas-dev/pandas/issues/944/events | https://github.com/pandas-dev/pandas/issues/944 | 3,730,848 | MDU6SXNzdWUzNzMwODQ4 | 944 | read_csv skiprows not working? | {
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Perhaps I'm just using read_csv incorrectly but I can't reproduce the issue using Std lib csv or by directly reading the file and parsing myself.
example:
In [31]: lehman = ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/945 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/945/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/945/comments | https://api.github.com/repos/pandas-dev/pandas/issues/945/events | https://github.com/pandas-dev/pandas/issues/945 | 3,734,397 | MDU6SXNzdWUzNzM0Mzk3 | 945 | unconsistent slicing + setting of values | {
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I have a DataFrame df
A B C
0 -1.191583 1.290778 -0.445384
1 -1.275654 -0.716870 1.068261
2 -0.179524 -1.783951 2.539275
3 -0.149163 0.621901 -0.326219
4 0.055287 -0.057617 1.015610... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/946 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/946/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/946/comments | https://api.github.com/repos/pandas-dev/pandas/issues/946/events | https://github.com/pandas-dev/pandas/issues/946 | 3,735,624 | MDU6SXNzdWUzNzM1NjI0 | 946 | Push label slicing into DataFrame.__getitem__ | {
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https://api.github.com/repos/pandas-dev/pandas/issues/947 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/947/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/947/comments | https://api.github.com/repos/pandas-dev/pandas/issues/947/events | https://github.com/pandas-dev/pandas/issues/947 | 3,750,322 | MDU6SXNzdWUzNzUwMzIy | 947 | Timeseries branch won't build with Python 3. | {
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cythoning pandas/src/tseries.pyx to pandas/src/tseries.c
## Error compiling Cython file:
...
to use start ('S') or end ('E') of interval.
"""
cdef:
long retval
```
if not isinstance(relation, basestring) or len(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/948 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/948/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/948/comments | https://api.github.com/repos/pandas-dev/pandas/issues/948/events | https://github.com/pandas-dev/pandas/issues/948 | 3,753,152 | MDU6SXNzdWUzNzUzMTUy | 948 | inconsistent comparison operation results | {
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In [5]: i
Out[5]: Int64Index([1, 2, 3, 4])
In [6]: i == i
Out[6]: Int64Index([ 1, 1, 1, 1])
In [7]: i == 0
Out[7]: array([False, False, False, False], dtype=bool)
In [8]: i == 1
Out[8]: array([ True, False, False, False], dtype=bool)
In [9]: i == np.array([1,2,3,4])
Out[9]: ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/949 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/949/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/949/comments | https://api.github.com/repos/pandas-dev/pandas/issues/949/events | https://github.com/pandas-dev/pandas/issues/949 | 3,754,191 | MDU6SXNzdWUzNzU0MTkx | 949 | Import fails with Python 3 and timeseries branch | {
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ImportError: /usr/local/lib/python3.2/site-packages/pandas-0.7.2.dev-py3.2-linux-x86_64.egg/pandas/_tseries.cpython-32m.so: undefined symbol: PyString_FromString
I couldn't figure out why it's tr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/950 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/950/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/950/comments | https://api.github.com/repos/pandas-dev/pandas/issues/950/events | https://github.com/pandas-dev/pandas/issues/950 | 3,762,687 | MDU6SXNzdWUzNzYyNjg3 | 950 | pip install does not check for openpyxl | {
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"followers_url": "https://api.github.com/users/wesm/f... | 5 | 2012-03-22T13:32:51Z | 2012-10-11T23:49:54Z | 2012-10-11T23:49:54Z | CONTRIBUTOR | null | Installed the newest pandas (live on the edge! ;) via pip.
When trying to read an xlsx file I got the known import error.
openpyxl was just not installed.
This should be added as a dependy to setup.py, I guess?
Regards,
Michael
System: Mac OSX 10.7.3, pandas version 0.7.0 installed into EPD 32-bit via pip
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https://api.github.com/repos/pandas-dev/pandas/issues/951 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/951/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/951/comments | https://api.github.com/repos/pandas-dev/pandas/issues/951/events | https://github.com/pandas-dev/pandas/issues/951 | 3,762,983 | MDU6SXNzdWUzNzYyOTgz | 951 | parsing excel with index_col set fails with openpyxl | {
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```
>>> excel = pandas.io.parsers.ExcelFile("BELA FM Screning Test data (2nd Batch)_KMA.xlsx")
```
This works
```
>>> bw = excel.parse("BW_clean")
```
but this fails
```
>>> bw = excel.parse("BW_clean",index_col=0)
---------------------------------------------------------------------------
Type... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/952 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/952/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/952/comments | https://api.github.com/repos/pandas-dev/pandas/issues/952/events | https://github.com/pandas-dev/pandas/pull/952 | 3,764,431 | MDExOlB1bGxSZXF1ZXN0MTAyOTM4MQ== | 952 | Added support for read_fwf() as in R. | {
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It also made sense to refactor read_csv() and read_table() to redirect to a new function _read() which takes the parser's class as input. I needed this for the FixedWidthFieldParser which needs to override the TextParser in order to provide a custom reader for the fields.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/953 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/953/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/953/comments | https://api.github.com/repos/pandas-dev/pandas/issues/953/events | https://github.com/pandas-dev/pandas/issues/953 | 3,765,729 | MDU6SXNzdWUzNzY1NzI5 | 953 | ValueError when slicing with NaN values | {
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In [30]: a = DataFrame([[1,2,3],['b',None,'a'],[1,'b',9]])
In [31]: a
Out[31]:
0 1 2
0 1 2 3
1 b None a
2 1 b 9
## In [32]: a[a[1]=='a']
ValueError Traceback (most recent call last)
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https://api.github.com/repos/pandas-dev/pandas/issues/954 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/954/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/954/comments | https://api.github.com/repos/pandas-dev/pandas/issues/954/events | https://github.com/pandas-dev/pandas/issues/954 | 3,768,450 | MDU6SXNzdWUzNzY4NDUw | 954 | DataFrame.plot() does not treat float index as numeric | {
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This is becasue `DataFrame.index.is_numeric()` returns `False` when the index holds floats.
`DataFrame.index.is_numeric()` checks on the dtype of the index to know if it holds numeric data. Apparently dtype of a float index is `object`.
example from the [mailin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/955 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/955/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/955/comments | https://api.github.com/repos/pandas-dev/pandas/issues/955/events | https://github.com/pandas-dev/pandas/issues/955 | 3,768,512 | MDU6SXNzdWUzNzY4NTEy | 955 | Easy function for making dummy variable matrices | {
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"closed_at": "2013-12-30T19:53:14Z",
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from an e-mail on the statsmodels mailing list
```
Here's a quick hack at it (not too dissimilar to Aman's code it looks
like)-- I should find a place in the library to put this:
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/957 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/957/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/957/comments | https://api.github.com/repos/pandas-dev/pandas/issues/957/events | https://github.com/pandas-dev/pandas/pull/957 | 3,771,489 | MDExOlB1bGxSZXF1ZXN0MTAzMjQ4MA== | 957 | A way to get alternative percentiles into describe | {
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https://api.github.com/repos/pandas-dev/pandas/issues/958 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/958/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/958/comments | https://api.github.com/repos/pandas-dev/pandas/issues/958/events | https://github.com/pandas-dev/pandas/issues/958 | 3,777,520 | MDU6SXNzdWUzNzc3NTIw | 958 | DataFrame bar plot ignores kwds argument if subplots==True | {
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Series(randn(10)).plot(kind='bar',color='black')
While this plots bars in default blue color, ignoring color keyword:
DataFrame(randn(10,3)).plot(kind='bar',subplots=True,color='black')
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https://api.github.com/repos/pandas-dev/pandas/issues/959 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/959/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/959/comments | https://api.github.com/repos/pandas-dev/pandas/issues/959/events | https://github.com/pandas-dev/pandas/issues/959 | 3,783,826 | MDU6SXNzdWUzNzgzODI2 | 959 | Add access to slices of data structures when using HDF5 | {
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"f... | 1 | 2012-03-23T17:29:12Z | 2014-05-29T05:47:58Z | 2014-05-29T05:47:58Z | CONTRIBUTOR | null | HDF5 is allows random access to large array data, enabling one to cherrypick fragments from enormous arrays that don't fit in memory. It would be good to have this supported in here https://github.com/wesm/pandas/blob/master/pandas/io/pytables.py.
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https://api.github.com/repos/pandas-dev/pandas/issues/960 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/960/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/960/comments | https://api.github.com/repos/pandas-dev/pandas/issues/960/events | https://github.com/pandas-dev/pandas/issues/960 | 3,783,871 | MDU6SXNzdWUzNzgzODcx | 960 | reindex kills IPython | {
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``` python
df = pandas.DataFrame({'A' : ['foo', 'bar', 'foo', 'bar',
'foo', 'bar', 'foo', 'foo'],
'B' : ['one', 'one', 'two', 'three',
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https://api.github.com/repos/pandas-dev/pandas/issues/961 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/961/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/961/comments | https://api.github.com/repos/pandas-dev/pandas/issues/961/events | https://github.com/pandas-dev/pandas/issues/961 | 3,787,879 | MDU6SXNzdWUzNzg3ODc5 | 961 | Add DataFrame.update method: in-place modification alternative to combine_first | {
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https://api.github.com/repos/pandas-dev/pandas/issues/962 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/962/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/962/comments | https://api.github.com/repos/pandas-dev/pandas/issues/962/events | https://github.com/pandas-dev/pandas/issues/962 | 3,791,170 | MDU6SXNzdWUzNzkxMTcw | 962 | add `comments` argument to text readers | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-03-24T09:02:13Z | 2016-10-12T23:02:52Z | 2012-05-15T01:07:37Z | CONTRIBUTOR | null | It would be very helpful if `read_table` and `read_csv` would support a `comments` keyarg, like `np.loadtxt`, to handle filesets with varying numbers of headers which are indicated by a comment character at the beginning.
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https://api.github.com/repos/pandas-dev/pandas/issues/964 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/964/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/964/comments | https://api.github.com/repos/pandas-dev/pandas/issues/964/events | https://github.com/pandas-dev/pandas/pull/964 | 3,793,326 | MDExOlB1bGxSZXF1ZXN0MTA0MTg0Mw== | 964 | Series and DataFrame.kurt | {
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https://api.github.com/repos/pandas-dev/pandas/issues/965 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/965/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/965/comments | https://api.github.com/repos/pandas-dev/pandas/issues/965/events | https://github.com/pandas-dev/pandas/pull/965 | 3,793,508 | MDExOlB1bGxSZXF1ZXN0MTA0MTg5OA== | 965 | adding ddof parameter back into std and var | {
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https://api.github.com/repos/pandas-dev/pandas/issues/966 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/966/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/966/comments | https://api.github.com/repos/pandas-dev/pandas/issues/966/events | https://github.com/pandas-dev/pandas/pull/966 | 3,793,640 | MDExOlB1bGxSZXF1ZXN0MTA0MTk0NA== | 966 | Short version number | {
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https://api.github.com/repos/pandas-dev/pandas/issues/967 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/967/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/967/comments | https://api.github.com/repos/pandas-dev/pandas/issues/967/events | https://github.com/pandas-dev/pandas/pull/967 | 3,804,584 | MDExOlB1bGxSZXF1ZXN0MTA0NTUwMg== | 967 | BUG: fix typo | {
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https://api.github.com/repos/pandas-dev/pandas/issues/968 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/968/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/968/comments | https://api.github.com/repos/pandas-dev/pandas/issues/968/events | https://github.com/pandas-dev/pandas/issues/968 | 3,809,859 | MDU6SXNzdWUzODA5ODU5 | 968 | Behavior of sum and infinity | {
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from pandas import Series
a = [np.nan, 1]
b = [np.inf, 1]
print Series(a).sum() #1
print Series(b).sum() #2
print np.sum(a) #3
print np.sum(b) #4
I understand that pandas has made the design decision that sums with nans will drop nans (#1), but why is infinity dropped in the same way? I don't see w... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/969 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/969/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/969/comments | https://api.github.com/repos/pandas-dev/pandas/issues/969/events | https://github.com/pandas-dev/pandas/issues/969 | 3,811,848 | MDU6SXNzdWUzODExODQ4 | 969 | DateRange.tz_normalize(tz) problem when tz=pytz.utc | {
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I believe there is a problem when using DateRange.tz_normalize(tz) when the tz is pytz.utc (but not other pytz timezones):
I create a DateRange using a DateOffset that is Week(weekday=1), and then use the built-in DateRange methods tz_localize and tz_normalize to account for time zones. However, I get something... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/970 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/970/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/970/comments | https://api.github.com/repos/pandas-dev/pandas/issues/970/events | https://github.com/pandas-dev/pandas/pull/970 | 3,813,964 | MDExOlB1bGxSZXF1ZXN0MTA0OTE5MQ== | 970 | Allow read_csv to take URLs | {
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https://api.github.com/repos/pandas-dev/pandas/issues/971 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/971/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/971/comments | https://api.github.com/repos/pandas-dev/pandas/issues/971/events | https://github.com/pandas-dev/pandas/pull/971 | 3,817,042 | MDExOlB1bGxSZXF1ZXN0MTA1MDUxNw== | 971 | Add an attach method to DataFrame | {
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nosetests test_frame.py --pdb --pdb-failure
You can indeed see that the tests will pa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/972 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/972/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/972/comments | https://api.github.com/repos/pandas-dev/pandas/issues/972/events | https://github.com/pandas-dev/pandas/issues/972 | 3,826,735 | MDU6SXNzdWUzODI2NzM1 | 972 | scoreateprecentile return wrong value | {
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```
In [1341]: a = np.random.rand(100)
In [1342]: b = pd.Series(a)
In [1343]: a[:10]
Out[1343]:
array([ 0.6131142 , 0.65266141, 0.24583156, 0.70179786, 0.33361506,
0.65042728, 0.70192276, 0.02727854, 0.65948894, 0.44326182])
In [1348]: scoreatp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/973 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/973/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/973/comments | https://api.github.com/repos/pandas-dev/pandas/issues/973/events | https://github.com/pandas-dev/pandas/issues/973 | 3,827,534 | MDU6SXNzdWUzODI3NTM0 | 973 | HDFStore does not conserve index correctly | {
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But when I retreive my DataFrame, there is a problem with the indices cause I get this error:
Exception: Index values are not unique
Here are the commands that produce the exception, I didn't test every possible case so I keep the commands in ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/974 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/974/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/974/comments | https://api.github.com/repos/pandas-dev/pandas/issues/974/events | https://github.com/pandas-dev/pandas/pull/974 | 3,832,869 | MDExOlB1bGxSZXF1ZXN0MTA1NjkwNQ== | 974 | ENH: assure elements of list are of base dict class while converting list of dicts to a DataFrame | {
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Cheers
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https://api.github.com/repos/pandas-dev/pandas/issues/975 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/975/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/975/comments | https://api.github.com/repos/pandas-dev/pandas/issues/975/events | https://github.com/pandas-dev/pandas/pull/975 | 3,841,289 | MDExOlB1bGxSZXF1ZXN0MTA1ODcyOQ== | 975 | BUG: Don't mutate DataFrame.from_records columns | {
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https://api.github.com/repos/pandas-dev/pandas/issues/976 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/976/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/976/comments | https://api.github.com/repos/pandas-dev/pandas/issues/976/events | https://github.com/pandas-dev/pandas/issues/976 | 3,854,137 | MDU6SXNzdWUzODU0MTM3 | 976 | Add support for openpyxl date/number formatting | {
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https://api.github.com/repos/pandas-dev/pandas/issues/977 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/977/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/977/comments | https://api.github.com/repos/pandas-dev/pandas/issues/977/events | https://github.com/pandas-dev/pandas/issues/977 | 3,866,917 | MDU6SXNzdWUzODY2OTE3 | 977 | Improve Series.apply docstring re: elementwise application | {
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https://api.github.com/repos/pandas-dev/pandas/issues/978 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/978/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/978/comments | https://api.github.com/repos/pandas-dev/pandas/issues/978/events | https://github.com/pandas-dev/pandas/issues/978 | 3,867,069 | MDU6SXNzdWUzODY3MDY5 | 978 | Implement optimized method to select subsets or rows of a DataFrame from groups by rank (-1 -> last) or order statistics | {
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... | 2 | 2012-03-28T22:42:09Z | 2018-12-10T13:18:23Z | 2018-12-10T13:18:22Z | MEMBER | null | Motivated by: http://stackoverflow.com/questions/9850954/pandas-get-most-recent-value-of-a-particular-column-indexed-by-another-column
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https://api.github.com/repos/pandas-dev/pandas/issues/979 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/979/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/979/comments | https://api.github.com/repos/pandas-dev/pandas/issues/979/events | https://github.com/pandas-dev/pandas/issues/979 | 3,869,463 | MDU6SXNzdWUzODY5NDYz | 979 | Improve Panel slicing speed | {
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```
To follow up:
I used timeit.Timer() to time this two different ways:
a) return a slice of a Panel using panel.ix[foo, bar, qux] (where foo,
bar, and qux are arrays)
b) i) iterate through the items of the panel that are in foo
ii) do a slice on each DataFrame with data.ix[bar, qux]
iii) s... | {
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```
import pandas
import numpy as np
import pandas
print pandas.__version__
0.7.2.dev-12d511f
df1 = pandas.DataFrame(data=None, columns=['A','B','C'])
df1 = df1.set_index(['A'])
df2 = pandas.DataFrame(data=[[1,4,7],[2,5,8],[3,6,9]],
columns=['A','B','C'])
df2 = df2.set_index(['A'])
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https://api.github.com/repos/pandas-dev/pandas/issues/981 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/981/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/981/comments | https://api.github.com/repos/pandas-dev/pandas/issues/981/events | https://github.com/pandas-dev/pandas/issues/981 | 3,895,839 | MDU6SXNzdWUzODk1ODM5 | 981 | Doesn't build on windows | {
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```
$ pip install pandas
...
...
running build_ext
building 'pandas._tseries' extension
creating build\temp.win-amd64-2.7
creating build\temp.win-amd64-2.7\Release
creating build\temp.win-amd64-2.7\Release\pandas
creating build\temp.win-amd64-2.7... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/982 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/982/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/982/comments | https://api.github.com/repos/pandas-dev/pandas/issues/982/events | https://github.com/pandas-dev/pandas/issues/982 | 3,896,653 | MDU6SXNzdWUzODk2NjUz | 982 | Boolean operations on Series (object dtype) with NaNs retain NaNs: breaks boolean indexing | {
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``` python
In [14]: example = pandas.Series(["Activated", "Inhibited", np.nan], dtype="object")
In [15]: example == "Inhibited"
Out[15]:
0 False
1 True
2 NaN
```
This breaks boolean indexing:
``` python
example[example == "Inihibted"]
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Just a quick question on NaN equality, I haven't specifically looked it up, but upgrading to 0.7.2 broke my code and it seems it's down to how testing for equality with NaN behaves:
```
a = pandas.Series(['abc', nan])
```
a == 'cba' outputs:
```
0 False
1 NaN
```
rather than all False. This seem... | {
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Got it. It only happens if the series is longer than 200
``` python
x = pandas.Series(np.random.random(201), name='x')
x.reshape((-1,1))
<snip>
```
This is part of what I was talking about that Series aren't quite
array-like. Something like this
np... | {
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Handle lower case time rules.
Parsing tuples e.g., ('Min', 5) as freq
Interval supports aliasing for frequency names
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```
import pandas
import StringIO
csv = """"year","name","percent","sex"
1880,"John",0.081541,"boy"
1880,"William",0.080511,"boy"
18... | {
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```
import pandas
import numpy
# works fine
df = pandas.DataFrame({"col1":[2,5.0,123,numpy.nan], "col2":[1,2,3,4]})
print df.sub(3)
# fails -- tries to do the subtraction with None
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```
In [7]: Series(date_range('1/1/2000', '12/30/2000 23:00:00', freq='BM'))
Out[7]:
0 2000-01-31 00:00:00
1 2000-02-29 00:00:00
2 2000-03-31 00:00:00
3 2000-04-28 00:00:00
4 2000-05-31 00:00:00
5 2000-06-30 00:00:00
6 2000-07-31 00:00:00
7 2000-08-31 00:00:00
8 2000-09-... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1000 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1000/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1000/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1000/events | https://github.com/pandas-dev/pandas/issues/1000 | 3,993,239 | MDU6SXNzdWUzOTkzMjM5 | 1,000 | col_space parameter in to_html and to_string for dataframe | {
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Thanks,
Tej
output.to_html()
<table border="1">
<thead>
<tr>
<th></th>
<th>nearby = ... | {
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