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In [1]: import pandas
In [2]: a = pandas.DataFrame(randn(2, 3))
In [3]: a
Out[3]:
0 1 2
0 -0.7262 0.9849 0.1685
1 -1.0241 -2.3102 -1.1348
In [4... | {
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ID Data
1 45.0
NA NA
2 34
I use read_clipboard in this example, but it affects also read_table:
``` python
In [4]: pandas.read_clipboard(sep="\s+")
Out[4]:
ID Data
0 1.0 45.
1 NaN NaN
2 2.0 34.
In [9]: pandas.read_clipboard(sep="\s+").dtypes
Out[9]:
ID float64
Data float64
``... | {
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- _float_format
- _column_space
- _precision
- _max_rows
- _max_columns
Now these are stored in pandas.core.common.GlobalPrintConfig, when setting the engineering float formatter it should alter GlobalPrintConfig and not the... | {
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I'd love an option to maintain the column order that I've specified. At the moment I do this:
```
print df.groupby('Status')['Duration'].agg({ 'Min': np.min,
'Max':np.max,
'Mean': np.mean,
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/611 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/611/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/611/comments | https://api.github.com/repos/pandas-dev/pandas/issues/611/events | https://github.com/pandas-dev/pandas/issues/611 | 2,810,288 | MDU6SXNzdWUyODEwMjg4 | 611 | TypeError in Cython with tuple subclasses in DataFrame.from_records | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-01-11T21:25:49Z | 2016-10-12T23:02:44Z | 2012-01-12T18:50:33Z | MEMBER | null | From user email
Hi there,
Just a quick bug report. I'm using psycopg2 with a NamedTupleCursor, which returns namedtuples for rows. I'm trying to use DataFrame.from_records like so:
df = DataFrame.from_records(rows, rows[0]._fields)
I get the following error:
```
TypeError Traceback ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/612 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/612/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/612/comments | https://api.github.com/repos/pandas-dev/pandas/issues/612/events | https://github.com/pandas-dev/pandas/issues/612 | 2,812,325 | MDU6SXNzdWUyODEyMzI1 | 612 | Pure python multi-key groupby can't handle non-numeric results | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-01-12T00:23:58Z | 2012-01-12T00:46:30Z | 2012-01-12T00:46:30Z | MEMBER | null | reported by @yarikoptic, could occur fairly easily in 0.6.1, now very pathological to reproduce
```
data = DataFrame({'A' : ['foo', 'foo', 'foo', 'foo',
'bar', 'bar', 'bar', 'bar',
'foo', 'foo', 'foo'],
'B' : ['o... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/613 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/613/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/613/comments | https://api.github.com/repos/pandas-dev/pandas/issues/613/events | https://github.com/pandas-dev/pandas/issues/613 | 2,813,479 | MDU6SXNzdWUyODEzNDc5 | 613 | DataFrame list of dicts example fails | {
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---
In [1]: from pandas import *
In [2]: import numpy as np
In [14]: pandas.version
Out[14]: <module 'pandas.version' from '/Library/Frameworks/Python.framework/Versions/7.2/lib/python2... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/614 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/614/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/614/comments | https://api.github.com/repos/pandas-dev/pandas/issues/614/events | https://github.com/pandas-dev/pandas/issues/614 | 2,813,546 | MDU6SXNzdWUyODEzNTQ2 | 614 | Indicate index of rows for which an apply() statement fails | {
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https://api.github.com/repos/pandas-dev/pandas/issues/615 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/615/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/615/comments | https://api.github.com/repos/pandas-dev/pandas/issues/615/events | https://github.com/pandas-dev/pandas/issues/615 | 2,813,962 | MDU6SXNzdWUyODEzOTYy | 615 | Test concat with MultiIndex, found a buglet | {
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https://api.github.com/repos/pandas-dev/pandas/issues/616 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/616/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/616/comments | https://api.github.com/repos/pandas-dev/pandas/issues/616/events | https://github.com/pandas-dev/pandas/issues/616 | 2,814,191 | MDU6SXNzdWUyODE0MTkx | 616 | Float formatting of mixed-type Series is incorrect | {
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In [3]: data.ix[4]
Out[3]:
A bar
B one
C NaN
D 0.1949
E 0.8223
F 1.335
Name: 4
```
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https://api.github.com/repos/pandas-dev/pandas/issues/617 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/617/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/617/comments | https://api.github.com/repos/pandas-dev/pandas/issues/617/events | https://github.com/pandas-dev/pandas/pull/617 | 2,815,732 | MDExOlB1bGxSZXF1ZXN0NjgwNzYz | 617 | Make sure not to use bottleneck when it is not installed. | {
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nosetests running fine
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https://api.github.com/repos/pandas-dev/pandas/issues/618 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/618/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/618/comments | https://api.github.com/repos/pandas-dev/pandas/issues/618/events | https://github.com/pandas-dev/pandas/issues/618 | 2,820,867 | MDU6SXNzdWUyODIwODY3 | 618 | Pure Python GroupBy bug | {
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ATM if groupping doesn't result in actually all possible combinations, the pandas spits out non-informative
```
/home/yoh/deb/gits/pkg-exppsy/pandas/pandas/core/groupby.py in _aggregate_series_pure_python(self, obj, func, ngroups)
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https://api.github.com/repos/pandas-dev/pandas/issues/619 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/619/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/619/comments | https://api.github.com/repos/pandas-dev/pandas/issues/619/events | https://github.com/pandas-dev/pandas/issues/619 | 2,822,925 | MDU6SXNzdWUyODIyOTI1 | 619 | Missing parameter in concat docstring | {
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https://api.github.com/repos/pandas-dev/pandas/issues/620 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/620/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/620/comments | https://api.github.com/repos/pandas-dev/pandas/issues/620/events | https://github.com/pandas-dev/pandas/issues/620 | 2,823,320 | MDU6SXNzdWUyODIzMzIw | 620 | Implement vectorized, NA-friendly friendly string utils, a la R's stringr | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-01-12T20:42:57Z | 2012-07-15T22:50:48Z | 2012-07-15T22:50:48Z | MEMBER | null | cc @hammer, @arthurgerigk. Not sure when will be able to make this happen, but this would be a very nice addition. I've often found myself doing stuff like:
```
df[col].map(lambda x: x[:10])
```
or various other forms of string munging / regex-processing.
Obviously that would fail if any of `df[col]` is NA. And ha... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/621 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/621/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/621/comments | https://api.github.com/repos/pandas-dev/pandas/issues/621/events | https://github.com/pandas-dev/pandas/issues/621 | 2,823,711 | MDU6SXNzdWUyODIzNzEx | 621 | DataFrame constructor speed | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-01-12T21:13:05Z | 2012-01-12T21:52:54Z | 2012-01-12T21:52:54Z | CONTRIBUTOR | null | Hi, i was playing around with constructing DataFrame's from nested dicts, and noticed that things have gotten a bit slower since v0.6.1.
Here's some sample code i was playing with:
import time
import pandas
print pandas.**version**
data = dict((i,dict((j,float(j)) for j in xrange(100))) for i in xrange(5000))
t0 = ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/622 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/622/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/622/comments | https://api.github.com/repos/pandas-dev/pandas/issues/622/events | https://github.com/pandas-dev/pandas/issues/622 | 2,831,503 | MDU6SXNzdWUyODMxNTAz | 622 | pandas converts int32 to int64 | {
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In [65]: a = np.random.randint(10, size=1e6)
In [66]: a.dtype
Out[66]: dtype('int32')
In [67]: b = np.random.randint(2, size=1e6)
In [68]: df = pandas.DataFrame({'a': a, 'b': b})
In [69]: df.dtypes
Out[69]:
a int64
b int64
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https://api.github.com/repos/pandas-dev/pandas/issues/623 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/623/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/623/comments | https://api.github.com/repos/pandas-dev/pandas/issues/623/events | https://github.com/pandas-dev/pandas/issues/623 | 2,833,082 | MDU6SXNzdWUyODMzMDgy | 623 | More float formatting bugs | {
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2000-01-03 NaN
2000-01-04 0.6095
2000-01-05 NaN
2000-01-06 1.24
2000-01-07 NaN
2000-01-10 1.43
2000-01-11 NaN
2000-01-12 0.6033
2000-01-13 NaN
2000-01-14 -0.2555
2000-01-17 NaN
2000-01-18 0.4684
2000-01-19 NaN
2000-01-20 -1.825
2000-01-21 NaN
2000-01-24 1.023
20... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/624 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/624/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/624/comments | https://api.github.com/repos/pandas-dev/pandas/issues/624/events | https://github.com/pandas-dev/pandas/pull/624 | 2,836,099 | MDExOlB1bGxSZXF1ZXN0Njg4NTY0 | 624 | DOC: added a bit more docs for 0.7 release | {
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https://api.github.com/repos/pandas-dev/pandas/issues/625 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/625/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/625/comments | https://api.github.com/repos/pandas-dev/pandas/issues/625/events | https://github.com/pandas-dev/pandas/pull/625 | 2,836,819 | MDExOlB1bGxSZXF1ZXN0Njg4ODU2 | 625 | Make _get_terminal_size_linux() work inside Emacs | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-01-13T21:32:16Z | 2014-07-06T10:27:56Z | 2012-01-13T22:52:29Z | CONTRIBUTOR | null | I'm using ipython inside Emacs. Detection of the console width and height is not working with the current implementation. ioctl seems to return (0,0). Therefore, performing an explicit check for cr == (0,0) (in addition to the check for not cr) before falling back to environment variables is a quick fix that I think sh... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/626 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/626/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/626/comments | https://api.github.com/repos/pandas-dev/pandas/issues/626/events | https://github.com/pandas-dev/pandas/issues/626 | 2,837,494 | MDU6SXNzdWUyODM3NDk0 | 626 | Unicode index handling in HDFStore | {
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https://api.github.com/repos/pandas-dev/pandas/issues/627 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/627/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/627/comments | https://api.github.com/repos/pandas-dev/pandas/issues/627/events | https://github.com/pandas-dev/pandas/issues/627 | 2,837,787 | MDU6SXNzdWUyODM3Nzg3 | 627 | Heavily document integer indexing API changes | {
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https://api.github.com/repos/pandas-dev/pandas/issues/628 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/628/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/628/comments | https://api.github.com/repos/pandas-dev/pandas/issues/628/events | https://github.com/pandas-dev/pandas/issues/628 | 2,837,919 | MDU6SXNzdWUyODM3OTE5 | 628 | Decide on and add API functions for integer-based indexing | {
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https://api.github.com/repos/pandas-dev/pandas/issues/629 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/629/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/629/comments | https://api.github.com/repos/pandas-dev/pandas/issues/629/events | https://github.com/pandas-dev/pandas/issues/629 | 2,837,968 | MDU6SXNzdWUyODM3OTY4 | 629 | Add level argument to DataFrame.xs | {
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https://api.github.com/repos/pandas-dev/pandas/issues/630 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/630/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/630/comments | https://api.github.com/repos/pandas-dev/pandas/issues/630/events | https://github.com/pandas-dev/pandas/issues/630 | 2,841,891 | MDU6SXNzdWUyODQxODkx | 630 | integration of scikits.timeseries | {
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"followers_url": "https://api.github.com/users/wesm/... | 4 | 2012-01-14T17:13:20Z | 2012-05-25T21:26:17Z | 2012-05-25T21:26:17Z | CONTRIBUTOR | null | This shall serve as meta issue for inclusion of the most needed functions from scikits.timeseries.
fucntions, use cases and scenarios shall be listed at:
https://github.com/wesm/pandas/wiki/Time-Series-Manipulation
It is an enhancement request/wish.
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https://api.github.com/repos/pandas-dev/pandas/issues/631 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/631/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/631/comments | https://api.github.com/repos/pandas-dev/pandas/issues/631/events | https://github.com/pandas-dev/pandas/issues/631 | 2,842,233 | MDU6SXNzdWUyODQyMjMz | 631 | Add JSON export option for DataFrame | {
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https://api.github.com/repos/pandas-dev/pandas/issues/632 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/632/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/632/comments | https://api.github.com/repos/pandas-dev/pandas/issues/632/events | https://github.com/pandas-dev/pandas/issues/632 | 2,842,804 | MDU6SXNzdWUyODQyODA0 | 632 | Create developer page for pandas | {
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- git basics
- possible areas for improvement in the library
- short notes on best practices
Basically a version of http://statsmodels.sourceforge.net/dev/index.html
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https://api.github.com/repos/pandas-dev/pandas/issues/633 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/633/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/633/comments | https://api.github.com/repos/pandas-dev/pandas/issues/633/events | https://github.com/pandas-dev/pandas/issues/633 | 2,844,185 | MDU6SXNzdWUyODQ0MTg1 | 633 | Add ability to build secondary indexes inside MultiIndex | {
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https://api.github.com/repos/pandas-dev/pandas/issues/634 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/634/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/634/comments | https://api.github.com/repos/pandas-dev/pandas/issues/634/events | https://github.com/pandas-dev/pandas/issues/634 | 2,853,008 | MDU6SXNzdWUyODUzMDA4 | 634 | Errors in example plots in documentation | {
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http://pandas.sourceforge.net/visualization.html#basic-plotting-plot
The following page talks about version 0.4 and this new feature so perhaps it ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/635 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/635/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/635/comments | https://api.github.com/repos/pandas-dev/pandas/issues/635/events | https://github.com/pandas-dev/pandas/pull/635 | 2,857,075 | MDExOlB1bGxSZXF1ZXN0Njk1MDE5 | 635 | ENH: ipython_directive to warning on exceptions when building docs | {
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https://api.github.com/repos/pandas-dev/pandas/issues/636 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/636/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/636/comments | https://api.github.com/repos/pandas-dev/pandas/issues/636/events | https://github.com/pandas-dev/pandas/issues/636 | 2,857,998 | MDU6SXNzdWUyODU3OTk4 | 636 | MultiIndex.reindex(Int64Index) -> unhelpful Cython error | {
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test_crosstab_margins (__main__.TestCrosstab) ... > /home/wesm/code/pandas/generated.pyx(132)pandas._tseries.merge_indexer_object (pandas/src/tseries.c:28324)()
(Pdb) u
> /home/wesm/code/pandas/pandas/core/index.py(1548)get_indexer()
-> indexer = self._merge_indexer(target_index, self_index.indexMap)
(Pdb) target_... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/637 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/637/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/637/comments | https://api.github.com/repos/pandas-dev/pandas/issues/637/events | https://github.com/pandas-dev/pandas/issues/637 | 2,867,208 | MDU6SXNzdWUyODY3MjA4 | 637 | The sort option of groupby does not work as stated | {
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```
In [38]: df2 = DataFrame({'X' : ['B', 'B', 'A', 'A'], 'Y' : [1, 2, 3, 4]})
In [39]: df2.groupby(['X'], sort=True).sum()
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https://api.github.com/repos/pandas-dev/pandas/issues/638 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/638/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/638/comments | https://api.github.com/repos/pandas-dev/pandas/issues/638/events | https://github.com/pandas-dev/pandas/issues/638 | 2,868,567 | MDU6SXNzdWUyODY4NTY3 | 638 | NaN in a join-result despite know value | {
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"followers_url": "https://api.github.com/users/wesm/... | 3 | 2012-01-17T13:43:08Z | 2012-01-18T20:27:49Z | 2012-01-18T19:32:12Z | CONTRIBUTOR | null | When performing a join on a data frame with a data series, the last entry of the new column is sometimes NaN. It only seems to happen when the last item in the column the join is done on is found in more than one row. Here is a minimal example:
```
In [1]: df = DataFrame({'a': [1, 1]})
In [2]: ds = Series([2], index=... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/639 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/639/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/639/comments | https://api.github.com/repos/pandas-dev/pandas/issues/639/events | https://github.com/pandas-dev/pandas/pull/639 | 2,871,739 | MDExOlB1bGxSZXF1ZXN0NzAwMDgx | 639 | FIX: multiindex error #636 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/640 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/640/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/640/comments | https://api.github.com/repos/pandas-dev/pandas/issues/640/events | https://github.com/pandas-dev/pandas/issues/640 | 2,872,897 | MDU6SXNzdWUyODcyODk3 | 640 | DataFrame picklability issue | {
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```
import cPickle
from pandas import DataFrame
df = DataFrame()
with open('df', 'wb') as f:
cPickle.dump(df, f)
with open('df', 'rb') as f:
df2 = cPickle.load(f)
print df2
```
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"followers_url": "https://api.github.com/users/wesm/... | 4 | 2012-01-17T19:55:35Z | 2012-01-18T22:08:04Z | 2012-01-17T20:33:37Z | CONTRIBUTOR | null | I get the following Traceback:
Traceback (most recent call last):
File "C:\src\OSR\OSR\flowering_start.py", line 171, in <module>
df_x = execute(x,df,conn)
File "C:\src\OSR\OSR\flowering_start.py", line 92, in execute
print result['Date']
File "C:\src\pandas\pandas\core\series.py", line 566, in **str**
... | {
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Something of this nature would be nice:
```
df.groupby(['A', 'B']).agg({'C' : [np.mean, np.std]})
```
Would also be nice to add some options to agg for what to do with the input dict (by default targets columns)
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The following
```
from pandas.core.api import Series
import datetime
data_seq = [.10, .23]
date_se... | {
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```
df = DataFrame({'A' : ['foo', 'bar', 'foo', 'bar', 'foo', 'bar', 'foo', 'foo'],
'B' : ['one', 'one', 'two', 'three', 'two', 'two', 'one', 'three'],
'C' : randn(8), 'D' : randn(8)})
gro... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/645 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/645/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/645/comments | https://api.github.com/repos/pandas-dev/pandas/issues/645/events | https://github.com/pandas-dev/pandas/issues/645 | 2,884,295 | MDU6SXNzdWUyODg0Mjk1 | 645 | Installation fails for Python 3 | {
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```
'install_requires': ['python-dateutil >= 2','numpy'],
```
in setup.py does the trick for me.
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https://api.github.com/repos/pandas-dev/pandas/issues/647 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/647/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/647/comments | https://api.github.com/repos/pandas-dev/pandas/issues/647/events | https://github.com/pandas-dev/pandas/issues/647 | 2,885,029 | MDU6SXNzdWUyODg1MDI5 | 647 | enh request: new functions cummax, cummin | {
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At fabriziop/pandas there is a forked branch with these changes, commit 660d5ddf05c49c55fabce072a41e5d5b5096e529 .
The new functions are dumbly derived from the cumsum function.
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-01-18T20:50:22Z | 2012-01-19T03:15:18Z | 2012-01-19T03:15:18Z | NONE | null | All built via homebrew, Numpy and SciPy masters from a week ago. Same setup for Python 2.7 works fine, pip-installing pandas 0.6.1 as well. So it's no big deal except for having to live without iterrows :-)
```
Traceback (most recent call last):
[...]
from pandas import DataFrame
File "/usr/local/Cellar/python... | {
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also another commit on **kwds -- depends on what was intended, but at least figsize should be passed
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> > > import numpy as np
> > > x=DataFrame(np.arange(9).reshape(3,3))
> > > x[0].iget([0,1])
> > > 0 0
> > > 1 3
> > > x.icol([0,1])
> > > 0 1
> > > 0 0 1
> > > 1 3 4
> > > 2 6 7
> > > x.irow([0,1])
Traceback (most recent call last):
File "<pyshell#5>", line 1, in <module>
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> > > y
> > > a 0
> > > 0 1
> > > 1 2
> > > Name: a
> > > y[0]
> > > 1 # expected
> > > y[[0,1]]
> > > a 0 # wrong?
> > > 0 1
> > > Name: a
> > > y[[... | {
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```
# In [4]: type(pd)
# Out[4]: pandas.sparse.frame.SparseDataFrame
memid = unique(pd.Member)
pan = {}
for mem in memid:
pan[mem] = pd[pd.Member==mem]
goal = pandas.Panel(pan)
```
comments
```
What are the dimensions (pd.shape) and density (pd.density) of the SparseDataFrame? Any change you can e-mail... | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-01-22T13:39:45Z | 2012-02-05T19:45:43Z | 2012-01-25T21:16:25Z | CONTRIBUTOR | null | Here is an attempt at fully resolving name conflict in merges when `left_on` or `right_on` keys are passed explicitly.
I am not sure my fix is correct but I include a new non-regression test to highlight the issue and the resolution does not introduce any regression findable by running `nosetests`.
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http://stackoverflow.com/questions/8957175/dataframe-to-panel-indexed-by-nonunique-column-with-pandas
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```
In [4]: df = tm.makeTimeDataFrame()
In [5]: df
Out[5]:
A B C D
2000-01-03 0.5694 1.15202 1.269872 -0.08819
2000-01-04 -0.3278 -0.39915 -0.591330 0.81658
2000-01-05 0.8175 0.15806 0.751025 0.61545
2000-01-06 0.2541 2.25491 -0.536671 -0.43782
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update: was actually slicing
```
s[:5.0]
```
may fail in some cases (or it might have been fixed, need to test)
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```
Q E A B C D
F G
0 0 x51CohYbqL aJBXfDaxvl -0.21474 -0.07802 0.37657 0.519663
1 2 Q07yrbfCLo RvNdHB9dl3 -0.16727 -1.26608 1.21477 -1.559552
2 4 uihKvB6NBA 5DjiMCJ8Sw -0.43737... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/672 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/672/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/672/comments | https://api.github.com/repos/pandas-dev/pandas/issues/672/events | https://github.com/pandas-dev/pandas/issues/672 | 2,945,374 | MDU6SXNzdWUyOTQ1Mzc0 | 672 | DataFrame.mul on vector gives inconsistent results depending on combination of axis and whether argument is boxed | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-01-24T02:55:33Z | 2012-01-24T17:36:07Z | 2012-01-24T17:36:07Z | NONE | null | When argument is boxed in a TimeSeries, the 'axis' argument is respected:
In [108]: a = DataFrame(reshape(range(9),(3,3)))
In [109]: a
Out[109]:
0 1 2
0 0 1 2
1 3 4 5
2 6 7 8
In [110]: a.mul(TimeSeries(range(3)))
Out[110]:
0 1 2
0 0 1 4
1 0 4 10
2 0 7 16
In [111]: a.mul(TimeSeries(ra... | {
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Out[12]: 6.9265549260634e-310
ideally it should throw a KeyError or something
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https://api.github.com/repos/pandas-dev/pandas/issues/674 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/674/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/674/comments | https://api.github.com/repos/pandas-dev/pandas/issues/674/events | https://github.com/pandas-dev/pandas/issues/674 | 2,949,311 | MDU6SXNzdWUyOTQ5MzEx | 674 | plot test not working in current master | {
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test_upsample_mean (pandas.tests.test_functions.TestReductions) ... ok
test_upsample_min (pandas.tests.test_functions.TestReductions) ... ok
test_boxplot (pandas.tests.test_graphics.TestDataFramePlots) ... ERROR
test_hist (pandas.tests.test_graphics.... | {
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"followers_url": "https://api.github.com/users/wesm/... | 3 | 2012-01-24T15:03:39Z | 2012-01-27T21:34:42Z | 2012-01-24T17:26:15Z | NONE | null | from pandas import DataFrame
df = DataFrame({0: [np.nan, 2], 1: [np.nan, 3], 2: [np.nan, 4]}, dtype=object)
df.mean(1)
Expected:
In [33]: df.mean(1)
Out[33]:
0 NaN
1 3.0
Actual:
In [31]: df.mean(1)
Out[31]:
0 NaN
1 NaN
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https://api.github.com/repos/pandas-dev/pandas/issues/677 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/677/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/677/comments | https://api.github.com/repos/pandas-dev/pandas/issues/677/events | https://github.com/pandas-dev/pandas/issues/677 | 2,953,068 | MDU6SXNzdWUyOTUzMDY4 | 677 | Feature request: allow multiple arguments in aggregate | {
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df.groupby('A').agg({('C', 'D'): lambda x, y: (x-y)**2})
Which would call the lambda function with row pairs of C and D for x and y, respectively. Obviously a toy example.
Apo... | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-01-24T17:50:13Z | 2012-01-24T23:24:33Z | 2012-01-24T23:24:33Z | CONTRIBUTOR | null | I found an issue related to having an Int64Index and using pivot_table.
Here's the code that illustrates the problem:
# Start code
import itertools
import datetime
import pandas
d = datetime.date.min
data = list(itertools.product(['foo', 'bar'], ['A', 'B', 'C'],['x1', 'x2'],[d + datetime.timedelta(i) for i in xrang... | {
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```
from pandas import Series
s = Series({'T1': 5})
print s.groupby({'T1': 'T2'}).agg(sum)
```
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df = DataFrame({u'c/\u03c3':[1,2,3]})
Try typing 'df' in IPython:
UnicodeEncodeError: 'ascii' codec can't encode character u'\u03c3' in position 5: ordinal not in range(128)
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```
from pandas import DataFrame
df = DataFrame({'a': [1, 2, 3], 'b': [4, 5, 6]})
df2 = DataFrame({'c': [2, 2], 'd': [3, 3]})
gp2 = df2.groupby('c')['d']
df.reindex(gp2.index)
ERROR: An... | {
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Currently:
DataFrame.asfreq(MonthEnd(0)) goes into infinite loop. I believe this is the case for all the Date *End subclasses
Desired:
Exception should be raised
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```
def combine_first(self, other):
"""
Combine Series values, choosing the calling Series's values
first. Result i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/689 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/689/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/689/comments | https://api.github.com/repos/pandas-dev/pandas/issues/689/events | https://github.com/pandas-dev/pandas/issues/689 | 2,981,441 | MDU6SXNzdWUyOTgxNDQx | 689 | concat over MultiIndex does not hierarchify further | {
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df2
Out[62]:
A B C D
level1a 0 foo one -0.3364 -1.212780
1 bar one 1.5044 0.832076
level1b 2 foo two 0.1210 -0.547690
3 bar three -0.6163 0.948797
level1c 4 foo two 0.4783 -1.295089
5 bar two -0.6558 -1.515122
level1d 6 foo one -1.1923 -0.88438... | {
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from pandas import Series
s = Series(range(3))
s2 = s.map(lambda x: np.where(x == 0, 0, 1))
print s2.dtype
In pandas 0.6.0, this returned 'float64', but now it returns 'object'. This change requires us to explicitly specify some dtypes to pandas constructors as a workaround. If this is the desired... | {
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df = pandas.DataFrame(data)
ix = df[df['title'] == 'bar'].index
# this doesn't work with a list of variables
df.ix[ix, ['title']] = 'foobar'
df.ix[ix, ['cruft']] = 0
print df
# but this does
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https://api.github.com/repos/pandas-dev/pandas/issues/697 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/697/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/697/comments | https://api.github.com/repos/pandas-dev/pandas/issues/697/events | https://github.com/pandas-dev/pandas/issues/697 | 2,987,857 | MDU6SXNzdWUyOTg3ODU3 | 697 | GroupBy by level bug | {
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```
In [11]: df
Out[11]:
a b c d
one two three
foo bar baz -0.2732 1 -0.2732 1
In [12]: df.groupby(level='three')
-----------------------------------------------------------... | {
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"followers_url": "https://api.github.com/users/wesm/... | 3 | 2012-01-26T23:16:02Z | 2012-12-28T15:08:25Z | 2012-12-28T15:08:21Z | MEMBER | null | Should just silently fail otherwise if the PyTables version in use does not have the indexing functionality. Should be fairly simple to add, only affects Table formatted objects
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