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https://api.github.com/repos/pandas-dev/pandas/issues/3201 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3201/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3201/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3201/events | https://github.com/pandas-dev/pandas/issues/3201 | 12,565,979 | MDU6SXNzdWUxMjU2NTk3OQ== | 3,201 | line_width failure | {
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``` python
In [1]: import pandas as pd
In [2]: pd.__version__
Out[2]: '0.11.0.dev-250c8e0'
In [3]: len(repr(pd.DataFrame(123456, range(5), range(15))).split('\n')[1])
Out[3]: 92
In [4]: pd.options.display.max_columns = 100
In [5]: len(repr(pd.Dat... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3202 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3202/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3202/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3202/events | https://github.com/pandas-dev/pandas/issues/3202 | 12,571,733 | MDU6SXNzdWUxMjU3MTczMw== | 3,202 | ENH: create out-of-core processing module | {
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"followers_url": "https://api.github.com/users/jorisva... | 32 | 2013-03-28T16:17:53Z | 2016-09-15T22:18:15Z | 2016-09-15T21:46:15Z | CONTRIBUTOR | null | Conceptually create a pipeline processor that performs out-of-core computation.
This is easily parallelizable (multi-core or machines), in theory cython / ipython / joblib / hadoop could operate with this
## requirements
the data set must support chunking, and the function must operate only on that chunk
Useful in cas... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3203 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3203/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3203/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3203/events | https://github.com/pandas-dev/pandas/pull/3203 | 12,574,164 | MDExOlB1bGxSZXF1ZXN0NDg2OTI1OA== | 3,203 | BLD: Cache 2to3 artifacts | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2013-03-28T17:07:05Z | 2014-07-16T06:25:18Z | 2013-04-14T14:12:39Z | NONE | null | This is the logical followup to the cython cache hack.
Using both, I put together a server on Redhat Openshift to serve as
network cache storage, and a travis build now takes 1.5 minutes bare,
and up to 4 minutes for a FULL_DEPS build.
The traffic used up by each build is significant, so the travis bit can't
be put ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3204 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3204/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3204/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3204/events | https://github.com/pandas-dev/pandas/pull/3204 | 12,576,695 | MDExOlB1bGxSZXF1ZXN0NDg3MDc5Nw== | 3,204 | TST: fix for tseries/test_period for py3k | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3205 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3205/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3205/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3205/events | https://github.com/pandas-dev/pandas/pull/3205 | 12,579,554 | MDExOlB1bGxSZXF1ZXN0NDg3MjMxOQ== | 3,205 | TST: fix tests in master | {
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BUG: fix in spare_frame for issue with running apply on a SparseFrame didn't
allow the setting of the columns with a rename to work properly
something broke this......
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https://api.github.com/repos/pandas-dev/pandas/issues/3206 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3206/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3206/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3206/events | https://github.com/pandas-dev/pandas/issues/3206 | 12,581,858 | MDU6SXNzdWUxMjU4MTg1OA== | 3,206 | using BDay for offsets I see a wrong result | {
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```
import datetime
import pandas
from pandas.tseries.offsets import *
X = datetime.datetime(2013, 3, 22, 0, 0)
pri... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3207 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3207/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3207/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3207/events | https://github.com/pandas-dev/pandas/pull/3207 | 12,586,583 | MDExOlB1bGxSZXF1ZXN0NDg3NTg1MQ== | 3,207 | Gh2836 resolve merge conflict | {
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(Is the correct thing to do here to set up a new branch? I wasn't brave enough to try and force directly to the pr...)
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https://api.github.com/repos/pandas-dev/pandas/issues/3208 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3208/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3208/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3208/events | https://github.com/pandas-dev/pandas/pull/3208 | 12,586,724 | MDExOlB1bGxSZXF1ZXN0NDg3NTkyNw== | 3,208 | BUG: take into account adjoin width, closes #3201 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3209 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3209/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3209/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3209/events | https://github.com/pandas-dev/pandas/issues/3209 | 12,590,628 | MDU6SXNzdWUxMjU5MDYyOA== | 3,209 | BUG: read_csv: dtype={'id' : np.str}: Datatype not understood | {
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When loading this file, the following works:
``` python
pd.read_csv(my_path, dtype={'id' : np.int})
```
but the following doesn't:
``` python
pd.read_csv(my_path, dtype={'id' : np.str})
```
n... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3210 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3210/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3210/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3210/events | https://github.com/pandas-dev/pandas/issues/3210 | 12,592,427 | MDU6SXNzdWUxMjU5MjQyNw== | 3,210 | DatetimeIndex bug when adding offset to tz-aware | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2013-03-29T01:33:40Z | 2013-04-08T04:46:30Z | 2013-04-08T04:46:30Z | MEMBER | null | Migrated from pydata mailing list
Let me begin by saying -- I have worked out a way around the problem using .shift(). But I still thought I would mention what I ran into and see if it's worthy of attention/fixing.
I create a DatetimeIndex with a timezone:
```
In [29]: dates = pd.DatetimeIndex(start='2012-11-01',pe... | {
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"color": "e1... | closed | false | null | [] | null | 4 | 2013-03-29T01:35:12Z | 2013-04-01T20:54:48Z | 2013-04-01T20:54:48Z | CONTRIBUTOR | null | ``` python
import pandas as pd
import numpy as np
print pd.__version__
#0.11.0.dev-184f2db
lev1 = np.arange(10)
lev2 = np.linspace(0, 9, 10)
mi = pd.MultiIndex.from_arrays([lev1, lev2])
# ints work fine
assert lev1.dtype == mi.levels[0].dtype
# failure
assert lev2.dtype == mi.levels[1].dtype
print lev2.dtype, mi.lev... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3212 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3212/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3212/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3212/events | https://github.com/pandas-dev/pandas/pull/3212 | 12,594,929 | MDExOlB1bGxSZXF1ZXN0NDg4MDE3MA== | 3,212 | API: return None when inplace=True. re #1893 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3213 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3213/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3213/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3213/events | https://github.com/pandas-dev/pandas/pull/3213 | 12,595,296 | MDExOlB1bGxSZXF1ZXN0NDg4MDMyOQ== | 3,213 | BUG: DatetimeIndex bug adding offsets to tz-aware indices #3210 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3214 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3214/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3214/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3214/events | https://github.com/pandas-dev/pandas/pull/3214 | 12,596,091 | MDExOlB1bGxSZXF1ZXN0NDg4MDc0NA== | 3,214 | BUG: anchored week to_timestamp conversion run #2742 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3215 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3215/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3215/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3215/events | https://github.com/pandas-dev/pandas/issues/3215 | 12,602,685 | MDU6SXNzdWUxMjYwMjY4NQ== | 3,215 | remove deprecated property _verbose_info for 0.13 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3216 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3216/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3216/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3216/events | https://github.com/pandas-dev/pandas/issues/3216 | 12,607,047 | MDU6SXNzdWUxMjYwNzA0Nw== | 3,216 | BUG: non-numeric asignment to numeric column not upcasting | {
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```
In [18]: df = pd.DataFrame([{"a": 1}, {"a": 3, "b": 2}])
In [19]: df['c'] = np.nan
In [21]: df.ix[0,'c'] = 'foo'
---------------------------------------------------------------------------
ValueError... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3217 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3217/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3217/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3217/events | https://github.com/pandas-dev/pandas/issues/3217 | 12,610,017 | MDU6SXNzdWUxMjYxMDAxNw== | 3,217 | BUG: change dtype of Series from non-object to object inplace | {
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test in tests/test_series.py (test_update)
but cannot be fixed until Series is not longer a ndarray sub-class
as numpy cannot handle the float64 to object _in-place_ dtype conversion
(which is why the sub-class issue comes up), if we have a single block
then can just swap out the block rather t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3219 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3219/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3219/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3219/events | https://github.com/pandas-dev/pandas/pull/3219 | 12,612,793 | MDExOlB1bGxSZXF1ZXN0NDg4ODkxNg== | 3,219 | BUG: GH3216 Upcast when needed to DataFrame when setitem with indexer | {
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BUG: GH3216 Upcast when needed to DataFrame when setitem with indexer
The following would raise previously
```
In [8]: df = pd.DataFrame([{"a": 1}, {"a": 3, "b": 2}])
In [9]: df['c'] = np.nan
In [10]: df.ix[0,'c'] = 'foo'
In [11]: df
Out[11]:
a b c
0 1 NaN foo
1 3 2 NaN
In [12]: df.dtyp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3221 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3221/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3221/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3221/events | https://github.com/pandas-dev/pandas/issues/3221 | 12,622,844 | MDU6SXNzdWUxMjYyMjg0NA== | 3,221 | ENH: read_csv to support start/stop | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2013-03-29T23:40:50Z | 2018-07-06T22:48:09Z | 2018-07-06T22:48:05Z | CONTRIBUTOR | null | would be useful (mainly for out-of-core) to be able to specify the start and stop rows and quickly skip to them to get a specific chunk out of a file.
these rows refer to data rows / alternately this could just return the nth chunk
(but skip parsing the n-1 chunks for efficiency)
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provide same API as append/select
use get_store to open/close files
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https://api.github.com/repos/pandas-dev/pandas/issues/3224 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3224/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3224/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3224/events | https://github.com/pandas-dev/pandas/pull/3224 | 12,634,070 | MDExOlB1bGxSZXF1ZXN0NDg5ODYwMQ== | 3,224 | PeriodIndex pickle roundtrip does not recreate freq GH2891 | {
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Only the usual fear and trembling associated with touching the pickle code.
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https://api.github.com/repos/pandas-dev/pandas/issues/3225 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3225/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3225/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3225/events | https://github.com/pandas-dev/pandas/pull/3225 | 12,634,226 | MDExOlB1bGxSZXF1ZXN0NDg5ODY1Mg== | 3,225 | BUG/ENH Index sub names | {
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Subtract list of tuples from MultiIndexs (without it dropping the names), and also no name dropping with subtracting arrays from Indexs.
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https://api.github.com/repos/pandas-dev/pandas/issues/3226 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3226/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3226/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3226/events | https://github.com/pandas-dev/pandas/pull/3226 | 12,648,682 | MDExOlB1bGxSZXF1ZXN0NDkwMzUzMA== | 3,226 | TST: more robust tests in HDFStore | {
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will print additional output if this somehow fails, which I have never seen (except on travis)
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https://api.github.com/repos/pandas-dev/pandas/issues/3227 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3227/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3227/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3227/events | https://github.com/pandas-dev/pandas/pull/3227 | 12,656,381 | MDExOlB1bGxSZXF1ZXN0NDkwNjY1MQ== | 3,227 | TST add regression test for GH2753 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3228 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3228/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3228/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3228/events | https://github.com/pandas-dev/pandas/pull/3228 | 12,659,525 | MDExOlB1bGxSZXF1ZXN0NDkwODA4OQ== | 3,228 | BUG: GH2808 Apply with invalid returned indices raise correct Exception | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3229 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3229/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3229/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3229/events | https://github.com/pandas-dev/pandas/issues/3229 | 12,660,536 | MDU6SXNzdWUxMjY2MDUzNg== | 3,229 | df.plot produces wrong result when x vals are unsorted. (Dupe #2726) | {
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```
import pandas
from matplotlib import pyplot
from numpy.random import randn
data = pandas.DataFrame(randn(6, 2))
pyplot.plot(data[0], data[1])
data.plot(0, 1)
```
One can actually implement a test for this by compari... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3230 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3230/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3230/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3230/events | https://github.com/pandas-dev/pandas/issues/3230 | 12,663,994 | MDU6SXNzdWUxMjY2Mzk5NA== | 3,230 | Enable applymap for dataframes with duplicate columns | {
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In 0.11, this raises a ValueError Exception, previously returned
wrong data.
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"i... | 6 | 2013-04-01T15:38:34Z | 2013-07-02T01:43:20Z | 2013-07-02T01:43:20Z | NONE | null | `generic.PandasObject` is not it since it applies to data containers, not `Period` or `TimeStamp` for example.
Should leverage subclasse's `__unicode__` to do the right thing
on py2/py3 when it comes to repr,str,bytes #3183
I suggest putting in a mandatory `self.random_example()` (name?) method
that generates a rand... | {
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I have a `DataFrame` (df) that stores live sensor data that is captured at a specific frequency. New raw data from sensor is updated at a set interval (an attempt at bandwidth conservation), which is parsed into a new df object.
These new update dataframes are of the same frequency, and contain data that i... | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2013-04-02T02:57:15Z | 2013-04-03T15:06:45Z | 2013-04-03T15:05:25Z | NONE | null | ``` python
df=mkdf(100,2,data_gen_f=lambda r,c: r+ rand(1)*5,r_idx_type='i')
df.plot()
# vs
df.C_l0_g0.plot()
```
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https://api.github.com/repos/pandas-dev/pandas/issues/3234 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3234/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3234/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3234/events | https://github.com/pandas-dev/pandas/issues/3234 | 12,693,457 | MDU6SXNzdWUxMjY5MzQ1Nw== | 3,234 | doc: add How to rearrange a python pandas dataframe | {
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Here's my change:
```
`How to rearrange a python pandas dataframe?
<http://stackoverflow.com/questions/15432659/how-to-rearrange-a-python-pandas-dataframe>`__ -- Turn a matrix with horus in columns and days in rows in a continous row sequence in form of a time ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3235 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3235/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3235/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3235/events | https://github.com/pandas-dev/pandas/issues/3235 | 12,699,369 | MDU6SXNzdWUxMjY5OTM2OQ== | 3,235 | assigning list to series with boolean indexing | {
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``` python
import pandas as pd
import numpy as np
x = pd.Series(np.arange(10))
sel = x < 5
len(x[sel])
x[s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3236 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3236/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3236/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3236/events | https://github.com/pandas-dev/pandas/pull/3236 | 12,702,388 | MDExOlB1bGxSZXF1ZXN0NDkyODEwNw== | 3,236 | BUG: GH3235 fix setitem on Series with boolean indexing and rhs of list | {
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``` python
In [1]: x = pandas.DataFrame({'a': [1,2,3], 'b': [4,5,6]})
In [2]: x.ix[0].a
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-8-8358f... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3238 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3238/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3238/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3238/events | https://github.com/pandas-dev/pandas/issues/3238 | 12,709,767 | MDU6SXNzdWUxMjcwOTc2Nw== | 3,238 | agg() swallows exceptions. | {
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This was the source of a hard-to-find bug today.
Here's a program that replicates the problem.
```
#!/usr/bin/env python ... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2013-04-02T17:40:12Z | 2015-01-26T00:48:04Z | 2015-01-26T00:48:04Z | NONE | null | `apply` looks at the returned values from the user-supplied transformer function
and does convenient things based on the type returned.
However, there's no opt-out if you just want to transform groups
into something and get it back as-is:
``` python
In [16]: df=mkdf(10,2,data_gen_f=lambda x,y: randint(1,10))
...... | {
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Right now:
``` python
In [16]: df=mkdf(10,2,data_gen_f=lambda x,y: randint(1,10))
...: df
...:
...:
...:
Out[16]:
C0 C_l0_g0 C_l0_g1
R0
R_l0_g0 9 1
R_l0_g1 3 7
R_l0_g2 8 1
R_l0_g3 4 3
R_l0_g4 5 ... | {
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pd.DataFrame([DataFrame([])])
/home/user1/src/pandas/pandas/core/frame.pyc in __getattr__(self, name)
1965 return self[name]
1966 raise AttributeError("'%s' object has no attribute '%s'" %
-> 1967 (type(self).__name__, name))
1968
1969 def __... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3244 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3244/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3244/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3244/events | https://github.com/pandas-dev/pandas/pull/3244 | 12,720,306 | MDExOlB1bGxSZXF1ZXN0NDkzNzU1Nw== | 3,244 | ENH: support top-level read/write API for HDFStore using read_hdf/to_hdf | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3245 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3245/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3245/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3245/events | https://github.com/pandas-dev/pandas/pull/3245 | 12,724,145 | MDExOlB1bGxSZXF1ZXN0NDkzOTU5Mw== | 3,245 | BUG: GH3243 accept list of DataFrames as constructor input | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3246 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3246/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3246/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3246/events | https://github.com/pandas-dev/pandas/pull/3246 | 12,726,375 | MDExOlB1bGxSZXF1ZXN0NDk0MDc5Nw== | 3,246 | BUG: setitem with list elements in the indexer broken | {
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In [4]: df = DataFrame(np.arange(9).reshape((3, 3)),
index=["A", "B", "C"], columns=["A", "B", "C"])
In [5]: df.iloc[[0,1],[1,2]] += 100
In [6]: df.iloc[[0,1],[1,2]]
Out[6]:
B C
A 101 102
B 104 105
In [7]: df
Out[7]:
A B C
A 0 101 102
B 3 104 105
C 6 7 8
```
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2013-04-03T02:43:06Z | 2013-04-03T20:04:18Z | 2013-04-03T20:04:18Z | NONE | null | When I try use log scales on a bar plot in pandas, the area of the bar disappears. Example in [this ipynb](http://nbviewer.ipython.org/urls/gist.github.com/gjx/5298007/raw/d1a0bd774a253fa1fc1f12a005dd70a697e8f360/pandas_bar_log)
I think the answer is to pass `log=True` to `bar`, as in [this SO answer](http://stackover... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3248 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3248/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3248/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3248/events | https://github.com/pandas-dev/pandas/pull/3248 | 12,748,623 | MDExOlB1bGxSZXF1ZXN0NDk1MTUyMQ== | 3,248 | DOC: io.rst cleanups | {
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I went along. Could you look this over and merge if these changes
look ok to you?
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"... | closed | false | null | [] | null | 1 | 2013-04-03T14:20:55Z | 2013-12-04T00:57:23Z | 2013-04-03T15:01:24Z | NONE | null | Hi,
I don't know if this is a bug or a feature, or even if you guys noticed it already and it's not an issue, but this caused me some problems so I thought I should report it.
When you use the read_csv command to read a csv, you can pass the columns you want to set as indexes. If those columns contain duplicated e... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3250 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3250/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3250/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3250/events | https://github.com/pandas-dev/pandas/pull/3250 | 12,757,176 | MDExOlB1bGxSZXF1ZXN0NDk1NTk3NQ== | 3,250 | BOOK: keep code examples in wes's book current, until the 2nd ed. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3251 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3251/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3251/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3251/events | https://github.com/pandas-dev/pandas/issues/3251 | 12,766,528 | MDU6SXNzdWUxMjc2NjUyOA== | 3,251 | _pprint_dict forces dictionary-style output for objects that inherit from dict | {
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"labels_url": "htt... | 2 | 2013-04-03T18:50:42Z | 2014-01-03T20:53:08Z | 2014-01-03T20:53:08Z | CONTRIBUTOR | null | Because pprint_thing checks isinstance(thing, dict), it also catches objects that inherit from dict and forces them to print in the {'a':1, ... } format regardless of the object's __unicode__, __str__, or __repr__ definitions. On my machine, I've changed the _pprint_dict function to just:
```
return unicode(seq)
```
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3252 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3252/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3252/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3252/events | https://github.com/pandas-dev/pandas/pull/3252 | 12,770,133 | MDExOlB1bGxSZXF1ZXN0NDk2MjY3OA== | 3,252 | BUG: pprint_thing should pprint and limit nested sequences in dicts GH3251 | {
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"i... | 6 | 2013-04-03T19:58:04Z | 2014-07-04T22:23:57Z | 2013-04-23T02:12:54Z | NONE | null | #3251
**before**
``` python
pd.options.display.max_seq_items= 5
print pd.core.common.pprint_thing(dict(foo=range(100)))
foo = range(5)
foo[0] = foo
print pd.core.common.pprint_thing(dict(foo=foo))
{'foo': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3253 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3253/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3253/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3253/events | https://github.com/pandas-dev/pandas/pull/3253 | 12,770,163 | MDExOlB1bGxSZXF1ZXN0NDk2MjY5OA== | 3,253 | BUG: honor repr() of proper subclasses of dict/ODict in pprint_thing | {
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Have to consider corner cases before merging, rebased on top of #3252
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https://api.github.com/repos/pandas-dev/pandas/issues/3254 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3254/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3254/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3254/events | https://github.com/pandas-dev/pandas/issues/3254 | 12,772,889 | MDU6SXNzdWUxMjc3Mjg4OQ== | 3,254 | log=True bar plots are raising with mpl 1.2.1 | {
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xref:https://github.com/matplotlib/matplotlib/issues/1882
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https://api.github.com/repos/pandas-dev/pandas/issues/3255 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3255/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3255/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3255/events | https://github.com/pandas-dev/pandas/issues/3255 | 12,779,605 | MDU6SXNzdWUxMjc3OTYwNQ== | 3,255 | Cross-platform compatibility of pickle files | {
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http://support.picloud.com/entries/23466073-Help-please-an-UnpicklingError-coming-from-pandas-index-with-freq-A-
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https://api.github.com/repos/pandas-dev/pandas/issues/3256 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3256/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3256/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3256/events | https://github.com/pandas-dev/pandas/pull/3256 | 12,796,478 | MDExOlB1bGxSZXF1ZXN0NDk3NTU5MQ== | 3,256 | ENH: In HDFStore, add select_column method, deprecate unique method | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3257 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3257/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3257/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3257/events | https://github.com/pandas-dev/pandas/issues/3257 | 12,796,754 | MDU6SXNzdWUxMjc5Njc1NA== | 3,257 | diff(0) causes ValueError on Series and TimeSeries | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2013-04-04T11:58:29Z | 2013-04-07T14:28:48Z | 2013-04-07T14:28:48Z | NONE | null | import pandas as pd
import scipy as sp
df = pd.DataFrame(sp.randn(5,2))
ts = df[0]
### If you run: `df.diff(0)`
Out[43]:
0 1
0 0 0
1 0 0
2 0 0
3 0 0
4 0 0
### This works as expeted but if you run `ts.diff(0)` :
---
ValueError Traceback (most recent call last)
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https://api.github.com/repos/pandas-dev/pandas/issues/3258 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3258/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3258/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3258/events | https://github.com/pandas-dev/pandas/issues/3258 | 12,819,311 | MDU6SXNzdWUxMjgxOTMxMQ== | 3,258 | read_csv, read_table in version 0.9.0 are parsing integers as double but reporting type as int64 | {
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```
>>> pandas.read_csv("file.log")
produces the following output:
Numbers
0 17007000002000192
1 17007000002000192
2 17007000002000192
3 17007000002000192
4 17007000002000192
5 17007000002000192
6 17007000002000192
7 17007000002000192
8 ... | {
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Very curious why this would be
```
In [17]: df1 = pd.DataFrame(dict(A = range(10000)),index=pd.date_range('20130101',periods=10000,freq='s'))
In [18]: df1
Out[18]:
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 100... | {
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due to the new build cache and perf tweaks to test_perf, I've set up a job to
gradually sample the commit history perf profile.
Even with the faster iterations, It'll still take a few days to collect the data
(I'm going back to 0.9.0), but h... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3262 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3262/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3262/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3262/events | https://github.com/pandas-dev/pandas/pull/3262 | 12,872,529 | MDExOlB1bGxSZXF1ZXN0NTAxNDgyNQ== | 3,262 | DOC: update scipy.py #2916 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3263 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3263/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3263/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3263/events | https://github.com/pandas-dev/pandas/issues/3263 | 12,879,698 | MDU6SXNzdWUxMjg3OTY5OA== | 3,263 | to_csv no longer supports file mode | {
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```
In [20]: f = pd.DataFrame({'a':[1,2,2,3,4], 'b':[4,3,2,1,4]})
In [21]: f.to_csv('bar.csv', mode='w')
In [22]: !cat bar.csv
,a,b
0,1,4
1,2,3
2,2,2
3,3,1
4,4,4
In [23]: f.to_csv('bar.csv', mode='a')
In [24]: !cat bar.csv
,a,b
0,1,4
1,2,3
2,2,2
3,3,1... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3265 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3265/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3265/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3265/events | https://github.com/pandas-dev/pandas/pull/3265 | 12,886,971 | MDExOlB1bGxSZXF1ZXN0NTAxOTQxMg== | 3,265 | DOC: update boxplot/truncate #2916 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3266 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3266/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3266/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3266/events | https://github.com/pandas-dev/pandas/pull/3266 | 12,895,465 | MDExOlB1bGxSZXF1ZXN0NTAyMTM0NQ== | 3,266 | DOC: fix docstring for date_parser option | {
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"i... | 0 | 2013-04-07T17:15:20Z | 2013-06-03T01:16:15Z | 2013-06-03T01:16:15Z | CONTRIBUTOR | null | If diagonal='kde', then the keyword arguments are passed to both plot and scatter. They don't have the same call signatures, so you can't do this. I guess you need separate keyword arguments. I would vote for removing **kwds from the diagonal plots entirely and just fixing those axes ex-post if you need something chang... | {
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... | 30 | 2013-04-07T18:43:42Z | 2019-01-01T17:30:09Z | 2019-01-01T17:30:08Z | NONE | null | Have you ever written code that looks like this:
```
if isinstance(d.index, MultiIndex):
results = []
for l in d.index.levels:
for x in baz(l):
results.append(foo)
elif isinstance(d.index, Index):
for x in d.index:
foo
```
I've had to special case the handling of inde... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3269 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3269/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3269/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3269/events | https://github.com/pandas-dev/pandas/issues/3269 | 12,900,165 | MDU6SXNzdWUxMjkwMDE2NQ== | 3,269 | Idea: Frame/series should support grep-like context specification | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2013-04-07T19:10:20Z | 2020-01-29T12:59:36Z | 2016-12-29T11:12:55Z | NONE | null | In shell grep you can do stuff like:
```
λ seq 1000 | grep -C 3 500
497
498
499
**500**
501
502
503
```
```
λ seq 1000 | grep -B 1 -A 3 500
499
**500**
501
502
503
```
I'd be glad to have something like
``` python
s.grep_index(pat_or_pred,A=1,B=3) # -> list of series/df , each of len(A+B) or C
s.grep_index(pat_or_p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3270 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3270/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3270/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3270/events | https://github.com/pandas-dev/pandas/pull/3270 | 12,900,855 | MDExOlB1bGxSZXF1ZXN0NTAyMjk1NA== | 3,270 | ENH: Fix for #1512, added StataReader and StataWriter to pandas.io.parsers | {
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"description": "Major release (formerly 0.11.1 bugfix but has outgrown its britches)",
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"i... | 71 | 2013-04-07T19:57:24Z | 2014-06-13T17:39:52Z | 2013-05-16T11:31:47Z | CONTRIBUTOR | null | This pull request aims at fixing ticket #1512 and contains both a reader and a writer for Stata .dta files.
The code basically comes from th statsmodels project, however, I adapted it to the needs of pandas and implemented support for reading out stata value labels. The writer does not write those labels back.
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https://api.github.com/repos/pandas-dev/pandas/issues/3271 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3271/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3271/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3271/events | https://github.com/pandas-dev/pandas/pull/3271 | 12,901,181 | MDExOlB1bGxSZXF1ZXN0NTAyMzA3Ng== | 3,271 | CLN: remove stale TODO.rst | {
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"f... | 3 | 2013-04-08T01:37:45Z | 2013-04-08T09:41:25Z | 2013-04-08T09:41:07Z | NONE | null | Earlier today I suggested allowing "sandbox" features into releases,
to make it easier to get some more testing and feedback before
commiting something into core proper.
Here's an example of how I imaging this to work:
```
In [1]: pd.describe_option("sandbox")
sandbox.experimental_feature: [default: False] [currentl... | {
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```
I have a sort of philosophical question about the use of
indexes (especially MultiIndexes) versus just keeping data in
columns. When using groupby, you tend to get a lot of results
with MultiIndexes, and the indexes are convenient for simple
accessing of items. However, I've found that index ob... | {
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partly fulfilles #3269, should be extended to an equivalent method on
index labels? (vectorized? numexpr?). Just experimenting with the API,
performance later (as much as possible with unindexed data).
- [x] need to add option to interpret multiple columns as a predicate expecting
a list of values correspondi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3280 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3280/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3280/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3280/events | https://github.com/pandas-dev/pandas/pull/3280 | 12,918,883 | MDExOlB1bGxSZXF1ZXN0NTAzMDY3MA== | 3,280 | ENH: add to_series() method to Index and subclasses GH3275 | {
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``` python
In [10]: df=mkdf(10,5,r_idx_nlevels=2)
In [11]: df.index
Out[11]:
MultiIndex
[R_l0_g0 R_l1_g0, R_l0_g1 R_l1_g1, R_l0_g2 R_l1_g2, R_l0_g3 R_l1_g3, R_l0_g4 R_l1_g4, R_l0_g5 R_l1_g5, R_l0_g6 R_l1_g6, R_l0_g7 R_l1_g7, R_l0_g8 R_l1_g8, R_l0_g9 R_l1_g9]
In [12]: # new method
...: df.index.t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3281 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3281/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3281/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3281/events | https://github.com/pandas-dev/pandas/issues/3281 | 12,919,542 | MDU6SXNzdWUxMjkxOTU0Mg== | 3,281 | Support pdf tables -> datframe | {
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"f... | 2 | 2013-04-08T11:49:42Z | 2013-09-28T20:54:56Z | 2013-09-28T20:54:28Z | NONE | null | If their install process ever becomes less ridiculous,
and the processing time reasonable it might be interesting
to make pdf tables -> pandas seamless. I know some civic
hacking people this would make happy.
https://github.com/jazzido/tabula
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https://api.github.com/repos/pandas-dev/pandas/issues/3282 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3282/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3282/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3282/events | https://github.com/pandas-dev/pandas/issues/3282 | 12,921,972 | MDU6SXNzdWUxMjkyMTk3Mg== | 3,282 | Initializing a Series with an OrderedDict | {
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```
from collections import OrderedDict
import pandas, random
data = OrderedDict([('col%s' % i, random.rand... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3283 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3283/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3283/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3283/events | https://github.com/pandas-dev/pandas/issues/3283 | 12,922,216 | MDU6SXNzdWUxMjkyMjIxNg== | 3,283 | Pivot table is making floats | {
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```
In [313]: f = pd.DataFrame({'a' : ['cat', 'bat', 'cat', 'bat'], 'v' : [1,2,3,4], 'i' : ['a','b','a','b']})
In [314]: z = pd.pivot_table(f, values='v', rows=['a'], cols=['i'], fill_value=0, aggfunc=np.sum)
In [315]... | {
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] | closed | false | null | [] | null | 2 | 2013-04-08T13:38:27Z | 2013-04-08T13:56:00Z | 2013-04-08T13:56:00Z | NONE | null | I can't seem to get the arguments on the apply function to work when there is only one argument. The following code reproduces my error in Pandas 0.91. It doesn't seem to recognize a single argument as a one element tupple.
``` python
data = {'state':['Ohio','Ohio','Ohio','Nevada','Nevada'], 'year':[2000,2001,2002,20... | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2013-04-08T14:38:43Z | 2013-04-08T16:54:29Z | 2013-04-08T16:54:21Z | CONTRIBUTOR | null | Added params argument to read_frame that is passed directly to the
execute method. This allows users to use a parameterized query
rather than having to pre-format the SQL themselves.
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https://api.github.com/repos/pandas-dev/pandas/issues/3287 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3287/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3287/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3287/events | https://github.com/pandas-dev/pandas/pull/3287 | 12,931,251 | MDExOlB1bGxSZXF1ZXN0NTAzNjkwNA== | 3,287 | BUG: suppress error raise by nonnumeric columns when plotting DataFrame ... | {
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suppressing AttributeError here so you can plot the DataFrame and automatically exclude non-numeric columns. @y-p @wesm @jreback any thoughts on 1) whether it should raise instead of exclude and 2) whether catching the AttributeError here is too dangerously broad?
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```
@slow
def test_time_series_plot_color_with_empty_kwargs(self):
import matplotlib.pyplot as plt
plt.close('all')
for i in range(3):
ax = Series(np.arange(12) + 1, index=date_range(
'1/1/2000', periods=12)).plot()
line_colors = [ l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3289 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3289/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3289/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3289/events | https://github.com/pandas-dev/pandas/issues/3289 | 12,950,639 | MDU6SXNzdWUxMjk1MDYzOQ== | 3,289 | DOC: add revised docs (in advanced indexing) in regards to GH3219 | {
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we now allow setting of mixed type frames with a ndarray/frame that can be aligned, docs mention the old behavior, need example maybe
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https://api.github.com/repos/pandas-dev/pandas/issues/3290 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3290/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3290/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3290/events | https://github.com/pandas-dev/pandas/pull/3290 | 12,952,179 | MDExOlB1bGxSZXF1ZXN0NTA0NzgxMQ== | 3,290 | BUG: test case showing why assigning to dtype is unsafe | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2013-04-09T01:15:53Z | 2013-05-18T15:13:52Z | 2013-04-09T14:40:02Z | MEMBER | null | @jreback this is a test case that shows why assigning to `dtype` is unsafe, namely that the dtype item sizes have to be compatible obviously =P Could you take a look at this and fix? This came up when I booted the windows box back up because Windows uses int32 by default.
There is a secondary bug here that the test ca... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3291 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3291/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3291/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3291/events | https://github.com/pandas-dev/pandas/issues/3291 | 12,952,868 | MDU6SXNzdWUxMjk1Mjg2OA== | 3,291 | Improper singleton-tuple repr | {
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In [3]: (5,)
Out[3]: (5,)
In [4]: Series([(4,), (5,), (6,)])
Out[4]:
0 (4)
1 (5)
2 (6)
dtype: object
```
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https://api.github.com/repos/pandas-dev/pandas/issues/3292 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3292/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3292/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3292/events | https://github.com/pandas-dev/pandas/pull/3292 | 12,953,289 | MDExOlB1bGxSZXF1ZXN0NTA0ODM0Mg== | 3,292 | BUG: fix unsafe dtype conversion in Series | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3293 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3293/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3293/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3293/events | https://github.com/pandas-dev/pandas/issues/3293 | 12,953,576 | MDU6SXNzdWUxMjk1MzU3Ng== | 3,293 | possible issue with DPI of plot images in docs | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2013-04-09T02:22:30Z | 2013-07-14T14:40:50Z | 2013-07-14T14:40:50Z | NONE | null | probably applies to ipython sphinx ext as well, I did always
find them somewhat grainy:
http://mail.scipy.org/pipermail/ipython-user/2011-October/008699.html
investigate.
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https://api.github.com/repos/pandas-dev/pandas/issues/3294 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3294/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3294/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3294/events | https://github.com/pandas-dev/pandas/issues/3294 | 12,954,611 | MDU6SXNzdWUxMjk1NDYxMQ== | 3,294 | pprint_thing doesn't handle sets properly | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3295 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3295/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3295/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3295/events | https://github.com/pandas-dev/pandas/issues/3295 | 12,969,994 | MDU6SXNzdWUxMjk2OTk5NA== | 3,295 | consistency of hist and boxplot | {
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"labels_url": "htt... | 2 | 2013-04-09T13:03:08Z | 2014-03-14T12:41:12Z | 2014-03-14T12:41:12Z | CONTRIBUTOR | null | Both `DataFrame.hist` and `DataFrame.boxplot` support `by` to create grouped plots, however, `DataFrame.hist` requires that any column in `by` is also included in `column` while `DataFrame.boxplot` its vice-versa.
Here is a minimal example::
```
>>> df = pd.DataFrame({'a': [1, 1, 2, 2, 2, 1], 'b': list('AAABBB')})
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https://api.github.com/repos/pandas-dev/pandas/issues/3296 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3296/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3296/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3296/events | https://github.com/pandas-dev/pandas/issues/3296 | 12,972,727 | MDU6SXNzdWUxMjk3MjcyNw== | 3,296 | DataFrame.hist ignores keyword arguments | {
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This would be useful in order to create normalized and/or cumulative histograms.
It req... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3297 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3297/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3297/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3297/events | https://github.com/pandas-dev/pandas/pull/3297 | 12,984,978 | MDExOlB1bGxSZXF1ZXN0NTA2NDU1NQ== | 3,297 | WIP: Support metadata at de/serialization time | {
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While collecting vbench data recently, it became painfully
obvious how useful it would be to be able to attach metadata
tags to serialized frames/series/panel.
This is a rough draft for something I'd like to see happen in 0.12.
It creates yet another version of pickle files, so much t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3298 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3298/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3298/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3298/events | https://github.com/pandas-dev/pandas/issues/3298 | 12,987,091 | MDU6SXNzdWUxMjk4NzA5MQ== | 3,298 | bar plot sets axhline(0) for log plots, mpl 1.2.1 disapproves | {
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fix shortly
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https://api.github.com/repos/pandas-dev/pandas/issues/3299 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3299/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3299/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3299/events | https://github.com/pandas-dev/pandas/pull/3299 | 12,987,365 | MDExOlB1bGxSZXF1ZXN0NTA2NTgwMA== | 3,299 | BUG: DataFrame.hist passes keyword arguments to mpl.hist; closes #3296 | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2013-04-09T19:15:11Z | 2013-04-10T07:01:03Z | 2013-04-10T07:01:03Z | CONTRIBUTOR | null | This is a fix for https://github.com/pydata/pandas/issues/3296 .
Now keyword arguments to `plotting.grouped_hist` are passed to `matplotlib.Axes.hist`. This allows you to create e.g. normalized, cumulative, or log scaled histograms::
```
df = pd.DataFrame(np.random.randn(500, 2), columns=['A', 'B'])
df['C'] = np.rand... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3300 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3300/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3300/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3300/events | https://github.com/pandas-dev/pandas/pull/3300 | 12,988,209 | MDExOlB1bGxSZXF1ZXN0NTA2NjI0OA== | 3,300 | Work around mpl 1.2.1 regression re bar log plot GH3298, GH3254 | {
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"followers_url": "https://api.github.com/users/wesm/... | 0 | 2013-04-09T19:34:39Z | 2013-04-09T20:39:25Z | 2013-04-09T20:39:25Z | NONE | null | #3298, #3254
added tests and Tested visually on 1.2.0 and 1.2.1.
y-p's 2nd rule of github - if you see an area in the codebase that you never ever want
to touch, you'll end up maintaining it.
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