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https://api.github.com/repos/pandas-dev/pandas/issues/8401 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8401/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8401/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8401/events | https://github.com/pandas-dev/pandas/pull/8401 | 44,130,268 | MDExOlB1bGxSZXF1ZXN0MjE4ODQ4NjQ= | 8,401 | BUG: Panel.fillna with method='ffill' ignores the axis parameter (GH8251) | {
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This can be done now.
Remove https://github.com/pandas-dev/pandas/blob/30eb48cc485bb7c7c47a4e7e26f87e469fbd8b8a/pandas/tests/plotting/test_boxplot_method.py#L24-L31
and its use in
https://github.com/pandas-dev/pandas/blob/30eb48cc485bb7c7c47a4e7e26f87e... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8403 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8403/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8403/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8403/events | https://github.com/pandas-dev/pandas/issues/8403 | 44,177,407 | MDU6SXNzdWU0NDE3NzQwNw== | 8,403 | Memory leak in resample? | {
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when using the resample method, additional memory is allocated which seems to remain after the call. Consider the following example:
``` python
import gc
import pandas as pd
import numpy as np
import objgraph
# taken from http://pandas.pydata.org/pandas-docs/stable/10min.html?highlight=resample
rng = pd.date_ran... | {
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Uses ngroups=10000 as suggested in the issue, which takes about 1 hour on my desktop.
For results (vb_suite.log, pkl file) see: https://gist.github.com/dlovell/ea3400273314e7612f6e
Note: gist references a different commit hash. I changed the commit message and added modification to doc/source/v0.15.0.tx... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8411 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8411/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8411/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8411/events | https://github.com/pandas-dev/pandas/issues/8411 | 44,243,245 | MDU6SXNzdWU0NDI0MzI0NQ== | 8,411 | BUG: using .dt.tz_localize('UTC') returns a tz-unaware object | {
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In [48]: s
Out[48]:
0 1411161507178
1 1411138436009
2 1411123732180
3 1411167606146
4 1411124780140
5 1411159331327
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Name: 1, dtype: int64
In [49]: pd.DatetimeIndex(pd.to_datetime(s,unit='ms')).tz_localize('UTC').tz_conve... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8412 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8412/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8412/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8412/events | https://github.com/pandas-dev/pandas/issues/8412 | 44,284,988 | MDU6SXNzdWU0NDI4NDk4OA== | 8,412 | Float64 and Int64 issues | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8413 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8413/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8413/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8413/events | https://github.com/pandas-dev/pandas/pull/8413 | 44,290,539 | MDExOlB1bGxSZXF1ZXN0MjE5MzI2Mzg= | 8,413 | Categorical doc fixups | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-09-29T13:04:23Z | 2014-09-29T21:36:53Z | 2014-09-29T21:36:42Z | CONTRIBUTOR | null | Minor doc updates as part of #8375
- docstring in in cut/qcut + docstring examples #8077 (comment)
- whatsnew: In the note change "levels" to "categories" and s/Schultz/Schulz/
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I guess just needs maybe a bit more references at the top-level some how.
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https://api.github.com/repos/pandas-dev/pandas/issues/8417 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8417/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8417/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8417/events | https://github.com/pandas-dev/pandas/pull/8417 | 44,309,418 | MDExOlB1bGxSZXF1ZXN0MjE5NDM5ODQ= | 8,417 | BUG: regression in groupby with a pass thru multiindex on axis=1 (GH7997) | {
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> > > pd.date_range(0, periods=5, freq='.5s')[1]
> > > Timestamp('1970-01-01 00:00:05', offset='5S')
> > > pd.date_range(0, periods=5, freq='500ms')[1]
> > > Timestamp('1970-01-01 00:00:00.50000... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8420 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8420/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8420/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8420/events | https://github.com/pandas-dev/pandas/issues/8420 | 44,327,279 | MDU6SXNzdWU0NDMyNzI3OQ== | 8,420 | categorical needs a searchsorted implmentation | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2014-09-29T18:00:20Z | 2014-12-05T13:36:36Z | 2014-12-05T13:36:36Z | CONTRIBUTOR | null | Currently the `Categorical.searchsorted()` raises `NotImplementedError`.
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https://api.github.com/repos/pandas-dev/pandas/issues/8421 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8421/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8421/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8421/events | https://github.com/pandas-dev/pandas/pull/8421 | 44,328,515 | MDExOlB1bGxSZXF1ZXN0MjE5NTI2MTE= | 8,421 | FIX: Add Categorical.searchsorted stub | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-09-29T18:06:20Z | 2014-09-29T20:52:03Z | 2014-09-29T20:52:02Z | CONTRIBUTOR | null | For https://github.com/pydata/pandas/pull/7447, add a searchsorted
stub, which simple raises `NotImplementedError`, so that we raise a
more clear error than attribute not found.
xref #8420
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https://api.github.com/repos/pandas-dev/pandas/issues/8422 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8422/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8422/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8422/events | https://github.com/pandas-dev/pandas/issues/8422 | 44,339,841 | MDU6SXNzdWU0NDMzOTg0MQ== | 8,422 | read_fwf engine issue | {
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df = pd.read_fwf(dpath,widths=widths,header=0,skiprows=[0,2,3],thousands=',',engine='c',dtype={'cusip':str})
I received an err... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8423 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8423/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8423/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8423/events | https://github.com/pandas-dev/pandas/pull/8423 | 44,361,695 | MDExOlB1bGxSZXF1ZXN0MjE5Njc1NjY= | 8,423 | DOC: create text.rst with string methods (GH8416) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8424 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8424/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8424/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8424/events | https://github.com/pandas-dev/pandas/pull/8424 | 44,386,440 | MDExOlB1bGxSZXF1ZXN0MjE5Nzk2ODU= | 8,424 | ENH: numerically stable rolling_skew and rolling_kurt | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8425 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8425/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8425/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8425/events | https://github.com/pandas-dev/pandas/issues/8425 | 44,411,384 | MDU6SXNzdWU0NDQxMTM4NA== | 8,425 | BUG: DataFrame from_dict constructor ignores Ordered dict when orient='index' | {
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I have been experimenting with OrderedDicts lately, and found a bug with the DataFrame from_dict constructor. Here is a sample code.
``` python
import collections
import pandas as pd
firstrow={}
firstrow['foo'] = 'bar'
firstrow['baz'] = 'buzz'
row1 = pd.Series(firstrow)
secondrow={}
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https://api.github.com/repos/pandas-dev/pandas/issues/8426 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8426/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8426/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8426/events | https://github.com/pandas-dev/pandas/issues/8426 | 44,431,869 | MDU6SXNzdWU0NDQzMTg2OQ== | 8,426 | Performance issues with groupby for large values of ngroups | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2014-09-30T12:04:01Z | 2018-07-06T21:49:27Z | 2018-07-06T21:49:21Z | CONTRIBUTOR | null | Per @jreback: https://github.com/pydata/pandas/pull/8410#issuecomment-57100206
Groupby for large values of ngroups, 10000 in this case, is very slow.
```
Invoked with :
--ncalls: 3
--repeats: 3
---------------------------------------------------------
Test name | #0 |
------... | {
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"f... | 8 | 2014-09-30T15:41:38Z | 2021-04-16T19:43:01Z | null | CONTRIBUTOR | null | This is incorrect, as this is applied column by column (as they are different dtypes)
so `_first_compat` should first compute the mask then use it.
from [SO](http://stackoverflow.com/questions/26108181/selecting-first-row-with-groupby-and-nan-columns)
```
In [18]: df = pd.DataFrame([{'id':"a",'val':np.nan, 'val2':-1}... | {
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"followers_url": "https://api.github.com/users/jre... | 1 | 2014-09-30T17:06:42Z | 2014-10-30T11:19:43Z | 2014-10-29T23:45:11Z | CONTRIBUTOR | null | I find the behavior of `str.split` a bit odd, and it should by default just return a `DataFrame` (or maybe have a new function / option). Its straightforward to coerce it, but could/should be done internally.
(and `str.extract` does return a DataFrame IIRC)
```
In [22]: s
Out[22]:
0 apple
1 apple, oran... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8429 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8429/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8429/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8429/events | https://github.com/pandas-dev/pandas/pull/8429 | 44,492,564 | MDExOlB1bGxSZXF1ZXN0MjIwMzA1MDI= | 8,429 | TST: Adjust boxplot tests following MPL API change | {
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Takes care of one part of https://github.com/pydata/pandas/issues/8402
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https://api.github.com/repos/pandas-dev/pandas/issues/8430 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8430/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8430/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8430/events | https://github.com/pandas-dev/pandas/issues/8430 | 44,502,841 | MDU6SXNzdWU0NDUwMjg0MQ== | 8,430 | BinGrouper breaks on DataFrame.transform | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-09-30T21:35:39Z | 2014-10-01T13:04:11Z | 2014-10-01T13:03:57Z | CONTRIBUTOR | null | ``` python
import pandas as pd
import numpy as np
from pandas.tseries.resample import TimeGrouper
import pandas.util.testing as tm
df = tm.makeTimeDataFrame()
tg = TimeGrouper('M')
func = lambda x: (x - 1)
df.groupby(tg).transform(func)
```
```
/externals/pandas/pandas/core/groupby.py in _get_compressed_labels(self... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8431 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8431/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8431/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8431/events | https://github.com/pandas-dev/pandas/issues/8431 | 44,527,100 | MDU6SXNzdWU0NDUyNzEwMA== | 8,431 | compat pickles don't have '_id' | {
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"followers_url": "https://api.github.com/users/jr... | 7 | 2014-10-01T04:26:01Z | 2014-10-03T19:12:07Z | 2014-10-03T19:12:07Z | CONTRIBUTOR | null | So I'm running into an issue with creating a `Panel` out of legacy `DataFrame` pickles. The issue is that `_id` is set to `None` and the current `Index.is_` logic treats any two Indexes with unset `_id` as the same.
I thought the issue was with the unpickling. But it looks like there was an attempt to address this
``... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8432 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8432/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8432/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8432/events | https://github.com/pandas-dev/pandas/issues/8432 | 44,539,810 | MDU6SXNzdWU0NDUzOTgxMA== | 8,432 | Indexing pd.Series much slower than indexing dict | {
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```
mydict = {'a': 3, 'b': 4}
myser = pd.Series(mydict)
%timeit mydict['a']
%timeit myser['a']
10000000 loops, best of 3: 39.4 ns per loop
100000 loops, best of 3: 4.9 µs per loop
```
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https://api.github.com/repos/pandas-dev/pandas/issues/8433 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8433/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8433/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8433/events | https://github.com/pandas-dev/pandas/issues/8433 | 44,548,691 | MDU6SXNzdWU0NDU0ODY5MQ== | 8,433 | BUG/API: data readers should return missing data as NaN rather than warn | {
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"followers_url": "https://api.github.com/users/jre... | 3 | 2014-10-01T10:21:34Z | 2014-11-06T11:26:17Z | 2014-11-06T11:26:17Z | NONE | null | I have pandas version: pandas-0.13.1-py2.7-win32.egg
Routine pandas.io.data._dl_mult_symbols has an "except IOError" where the following is executed:
stocks[sym] = np.nan
The next thing that happens is:
try:
return Panel(stocks).swapaxes('items', 'minor')
However, if any of the values in... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8434 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8434/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8434/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8434/events | https://github.com/pandas-dev/pandas/pull/8434 | 44,558,082 | MDExOlB1bGxSZXF1ZXN0MjIwNjk0MDQ= | 8,434 | BUG: Groupby.transform related to BinGrouper and GH8046 (GH8430) | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-10-01T12:34:42Z | 2014-10-01T13:03:57Z | 2014-10-01T13:03:57Z | CONTRIBUTOR | null | closes #8430
xref #8046
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https://api.github.com/repos/pandas-dev/pandas/issues/8435 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8435/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8435/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8435/events | https://github.com/pandas-dev/pandas/issues/8435 | 44,570,046 | MDU6SXNzdWU0NDU3MDA0Ng== | 8,435 | DEPR: QuarterBegin and BQuarterBegin return days that are not quarter beginnings | {
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"f... | 17 | 2014-10-01T14:32:33Z | 2021-04-11T05:12:36Z | null | NONE | null | In[43]: datetime(2014,10,10) + BQuarterBegin()
Out[43]: Timestamp('2014-12-01 00:00:00')
In[45]: datetime(2014,10,10) + QuarterBegin()
Out[45]: Timestamp('2014-12-01 00:00:00')
Expected output is 2015-01-01.
(Note QuarterEnd and BQuarterEnd _do_ produce the expected output of 2014-12-31)
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https://api.github.com/repos/pandas-dev/pandas/issues/8436 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8436/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8436/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8436/events | https://github.com/pandas-dev/pandas/issues/8436 | 44,589,583 | MDU6SXNzdWU0NDU4OTU4Mw== | 8,436 | passing index parameter shouldn't be necessary when applying pivot function | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2014-10-01T17:06:49Z | 2018-07-06T21:36:48Z | 2018-07-06T21:36:42Z | CONTRIBUTOR | null | Hello,
I have a Pandas DataFrame `df` like this:
```
name value
2014-01-01 temp 10.0
2014-01-01 p 101.0
2014-01-02 temp 11.5
2014-01-02 p 100.0
```
I wanted to get a new DataFrame `df2`like:
```
temp p
2014-01-01 10.0 101.0
2014-01-02 11.5 100.0
```
I did this:
``... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8437 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8437/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8437/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8437/events | https://github.com/pandas-dev/pandas/issues/8437 | 44,615,970 | MDU6SXNzdWU0NDYxNTk3MA== | 8,437 | DataFrame.equals false negatives with dtype=object | {
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``` python
In [1]: import pandas as pd
In [2]: import numpy as np
In [3]: temp = [pd.Series([False, np.nan]), pd.Series([False, np.nan]), pd.Series(index=range(2)), pd.Series(index=range(2)), ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8438 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8438/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8438/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8438/events | https://github.com/pandas-dev/pandas/issues/8438 | 44,622,676 | MDU6SXNzdWU0NDYyMjY3Ng== | 8,438 | DOC: more complete docs on offsets/frequencies needed | {
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"f... | 6 | 2014-10-01T21:43:35Z | 2018-11-01T06:18:57Z | 2018-11-01T06:18:57Z | MEMBER | null | Add these to the API docs:
The contents of `pd.tseries.offsets.__all__`
```
['Day',
'BusinessDay',
'BDay',
'CustomBusinessDay',
'CDay',
'CBMonthEnd',
'CBMonthBegin',
'MonthBegin',
'BMonthBegin',
'MonthEnd',
'BMonthEnd',
'SemiMonthEnd',
'SemiMonthBegin',
'BusinessHour',
'CustomBusiness... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8439 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8439/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8439/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8439/events | https://github.com/pandas-dev/pandas/pull/8439 | 44,640,875 | MDExOlB1bGxSZXF1ZXN0MjIxMTc1NzA= | 8,439 | DOC: mention 'category' in select_dtypes docstring | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-10-02T02:31:14Z | 2014-10-02T06:41:56Z | 2014-10-02T06:41:41Z | CONTRIBUTOR | null | Trivial update to select_dtypes docstring to hint on how to include Categorical types, as it's not part of the numpy type-hierarchy mentioned here.
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https://api.github.com/repos/pandas-dev/pandas/issues/8440 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8440/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8440/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8440/events | https://github.com/pandas-dev/pandas/pull/8440 | 44,662,395 | MDExOlB1bGxSZXF1ZXN0MjIxMjY2NDA= | 8,440 | API: SQL class definitions renaming | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-10-02T08:35:02Z | 2014-10-05T19:29:01Z | 2014-10-05T19:29:00Z | MEMBER | null | WIP, related to #7960
- [x] renaming of
- PandasSQLAlchemy -> SQLDatabase
- PandasSQLTable -> SQLTable
- PandasSQLLegacy -> SQLiteDatabase
- PandasSQLLegacyTable -> SQLiteTable
- SQLDatabase.read_sql -> read_query
- [ ] adding docstrings to public functions of SQLDatabase
- [x] read_query, read_table, to_s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8441 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8441/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8441/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8441/events | https://github.com/pandas-dev/pandas/issues/8441 | 44,665,463 | MDU6SXNzdWU0NDY2NTQ2Mw== | 8,441 | ValueError when union multi-indexes with tuples as level values | {
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"id": 71268330,... | closed | false | null | [] | null | 1 | 2014-10-02T09:15:47Z | 2014-10-02T11:35:24Z | 2014-10-02T11:35:11Z | NONE | null | I can create multi-indexes with tuples as level values and union levels:
```
>> import pandas as pd
>> pd.version.version
'0.14.1'
>> i1 = pd.MultiIndex.from_tuples([((1,2), 3), ((4, 5), 6)], names=['a', 'b'])
>> i2 = pd.MultiIndex.from_tuples([((2,2), 3), ((5, 5), 6)], names=['a', 'b'])
>> i1.levels[0]
Index([(1, 2),... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8442 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8442/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8442/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8442/events | https://github.com/pandas-dev/pandas/issues/8442 | 44,686,240 | MDU6SXNzdWU0NDY4NjI0MA== | 8,442 | BUG on plotting.py radviz | {
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the varable n in line 389: n = len(frame)
is wrongly asigned again in line 404: n = len(frame.columns) - 1
that brakes in line 409: for i in range(n):
This shuld fix the bug
line 389: rows = len(frame)
line 409: for i in range(rows):
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https://api.github.com/repos/pandas-dev/pandas/issues/8443 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8443/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8443/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8443/events | https://github.com/pandas-dev/pandas/pull/8443 | 44,689,133 | MDExOlB1bGxSZXF1ZXN0MjIxNDE3MTY= | 8,443 | BUG: NDFrame.equals gives false negatives with dtype=object (GH8437) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8444 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8444/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8444/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8444/events | https://github.com/pandas-dev/pandas/issues/8444 | 44,714,863 | MDU6SXNzdWU0NDcxNDg2Mw== | 8,444 | Indexing Series with DataFrame should throw an exception | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-10-02T17:37:00Z | 2014-10-05T17:03:01Z | 2014-10-05T17:03:01Z | CONTRIBUTOR | null | I came across this today when being a little bit careless when using a boolean array to index into a Series. The result was not what I expected which turned out to be because I was using a boolean index in a DataFrame to index a Series. Either we should make this work or throw an error that you cannot index a Series ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8445 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8445/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8445/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8445/events | https://github.com/pandas-dev/pandas/issues/8445 | 44,728,399 | MDU6SXNzdWU0NDcyODM5OQ== | 8,445 | DataFrame division returns infinity for 0 / 0 | {
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0 / 0 does not have a value, and should return NaN, not infinity.
``` python
>>> x = pd.DataFrame([[0, 0], [1, 0], [-1, 0]])
>>> x[0] / x[1]
0 inf <------------- here
1 inf
2 -inf
dtype: float64
```
numpy does this correctly:
``` python
>>> y = np.array([[0, 0], [1, ... | {
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In [1]: pd.**version**
Out[1]: '0.14.1'
In [2]: np.**version**
Out[2]: '1.9.0'
In [3]: from numpy.random import randn
In [4]: s = pd.Series([np.timedelta64(int(x), 'us') fo... | {
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- what the red line is (median)
- what the box shows (quartiles)
- what the whiskers show (?)
- by what rules the outliers are shown or not
A link to wikipedia and/or matplotlib docs would be nice too.
I could try to contribute... | {
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The 'decimal' option exists for read_csv method but not yet in 'to_csv' methods.
The lack of this option is particulary painful when we _have to_ work with Excel with European regional settings.
This modification add this option to both Series.to_csv and Dataframe.to_csv.
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https://api.github.com/repos/pandas-dev/pandas/issues/8450 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8450/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8450/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8450/events | https://github.com/pandas-dev/pandas/issues/8450 | 44,798,365 | MDU6SXNzdWU0NDc5ODM2NQ== | 8,450 | CI: Add durations to tests | {
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Can add `--durations=10` or something to list the 10 slowest tests.
We could add this to our setup.cfg so it's used by default. | {
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@jreback
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-10-03T15:49:28Z | 2014-12-07T22:59:39Z | 2014-12-07T22:27:38Z | NONE | null | I'm trying to use to_html() to print a DataFrame that has a MultiIndex column, and I want to hide the index. When I do, the column labels are shifted right by one column. I use:
``` python
import pandas as pd
from IPython.display import HTML
df = pd.DataFrame({'a': range(10), 'b': range(10,20), 'c': range(10,20), '... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-10-03T18:07:31Z | 2014-10-04T16:38:15Z | 2014-10-04T16:38:15Z | CONTRIBUTOR | null | So it seems by using a full Int64 array for the codes, plus the categorires we are actually using MORE memory to store a Categorical. Because the pointers are the same sized as an object array (plus have the categories).
So need to change the codes store to use a smaller dtype of int. Maybe switch this to a plain ndar... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8454 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8454/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8454/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8454/events | https://github.com/pandas-dev/pandas/pull/8454 | 44,833,685 | MDExOlB1bGxSZXF1ZXN0MjIyMjE2OTY= | 8,454 | BUG: reset identity on legacy index pickles (GH8431) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8455 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8455/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8455/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8455/events | https://github.com/pandas-dev/pandas/pull/8455 | 44,848,359 | MDExOlB1bGxSZXF1ZXN0MjIyMjkzNTA= | 8,455 | PERF: optimize storage type for codes in Categoricals (GH8453) | {
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So easy enough to optimize the dtype of the codes array depending on the number of categories. Most
of the time will simply be `int8`. So pretty good savings.
This doesn't completely solve the storage issues as currently `factorize` returns a `int64`, but can deal with that later (as might also need some... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8456 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8456/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8456/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8456/events | https://github.com/pandas-dev/pandas/issues/8456 | 44,849,589 | MDU6SXNzdWU0NDg0OTU4OQ== | 8,456 | PERF: optimize memory space for factorize / FrozenList (storage for MultiIndex) | {
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factorize returns int64s, prob need some cython updating to allow lower ints returns
FrozenList by default also uses a ndarray like (that is int64)
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-10-03T22:15:31Z | 2014-10-04T17:41:00Z | 2014-10-04T17:19:50Z | CONTRIBUTOR | null | closes https://github.com/pydata/pandas/issues/8258, but more generally, on pandas master, assignment with indexer will align _both rows and columns_ if all columns have the same type:
```
>>> cols, idx = ['jim', 'joe', 'jolie'], ['first', 'last']
>>> vals = np.arange(1, 7).reshape(2, 3, order='F')
>>> df = DataFrame(... | {
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The code has evolved quite a bit and could probably benefit from refactoring.
In particular warpping the busdaycalendar logic in a wrapper class could make the code easier.
Notes about the current implementation:
- `CustomBusinessDay` uses `np.busdaycalendar` to do the computations.
- To speed up crea... | {
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just a couple of minor tweaks to that and some PEP8 stuff.
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CLN: drop copy_if_needed kwarg of Index.reindex, it's True everywhere
TST: enable back empty-list loc/ix tests that failed before
DOC: Bump Index.reindex docstring
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TST: check index/columns types when doing empty loc/ix tests
CLN: don't _ensure_index in NDFrame._reindex_axes, it is done in Index.reindex
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installs now take 300+ seconds, vs 100+ before.
I think a big cause is the installation of some basic libraries that conda installs by default
e.g. Python 2.7.8. But I don't think this is necessary and maybe can skip some of these
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... | 1 | 2014-10-04T21:39:51Z | 2016-03-12T15:21:11Z | 2016-03-12T15:21:06Z | MEMBER | null | continued from #7447
- [ ] `timedelta64` tests
- [ ] more edge case testing
- [ ] `side` argument testing
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https://api.github.com/repos/pandas-dev/pandas/issues/8465 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8465/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8465/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8465/events | https://github.com/pandas-dev/pandas/pull/8465 | 44,895,558 | MDExOlB1bGxSZXF1ZXN0MjIyNDgzOTE= | 8,465 | CI: install version of miniconda corresponding to python version | {
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... | 3 | 2014-10-04T21:46:35Z | 2015-05-09T16:01:34Z | 2015-05-09T16:01:34Z | MEMBER | null | null | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8466 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8466/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8466/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8466/events | https://github.com/pandas-dev/pandas/issues/8466 | 44,902,152 | MDU6SXNzdWU0NDkwMjE1Mg== | 8,466 | PeriodIndex cannot infer frequency in cases where Period can | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2014-10-05T03:12:05Z | 2018-07-06T21:25:03Z | 2018-07-06T21:24:57Z | NONE | null | xref #6771
> Period("2000-01")
> Period('2000-01', 'M')
>
> PeriodIndex(["2000-01"])
> ValueError: freq not specified and cannot be inferred from first element
Same problem with 2000-Jan and Jan-2000. Works fine if I pass freq="M".
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https://api.github.com/repos/pandas-dev/pandas/issues/8467 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8467/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8467/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8467/events | https://github.com/pandas-dev/pandas/issues/8467 | 44,904,825 | MDU6SXNzdWU0NDkwNDgyNQ== | 8,467 | groupby(group_keys=True) ignored when apply returns unsliced data | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2014-10-05T05:07:32Z | 2014-10-06T22:56:15Z | 2014-10-06T13:54:51Z | NONE | null | I ran into this unexplained behaviour with `groupby` when using `group_keys=True` (the default),
it's not clear why using `x` vs. `x[:]` causes the `group_keys` argument to be ignored.
``` python
In [86]: df = DataFrame({'key': [1, 1, 1, 2, 2, 2, 3, 3, 3],
...: 'value': range(9)})
...: df
Out... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8468 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8468/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8468/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8468/events | https://github.com/pandas-dev/pandas/pull/8468 | 44,904,977 | MDExOlB1bGxSZXF1ZXN0MjIyNTE0MTk= | 8,468 | Let PeriodIndex infer frequency by converting first element to Period | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8469 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8469/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8469/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8469/events | https://github.com/pandas-dev/pandas/issues/8469 | 44,905,118 | MDU6SXNzdWU0NDkwNTExOA== | 8,469 | Feature Request: pd.DataFrame() should flatten nested dicts when given list of dicts | {
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Here's a common example of data:
``` python
In [95]: data=[dict(u... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8470 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8470/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8470/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8470/events | https://github.com/pandas-dev/pandas/pull/8470 | 44,910,402 | MDExOlB1bGxSZXF1ZXN0MjIyNTMxOTk= | 8,470 | SQL/ERR: raise error when insert failed with sqlite fallback (GH8341) | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-10-05T10:08:12Z | 2014-10-05T18:01:12Z | 2014-10-05T18:01:12Z | MEMBER | null | Related to #8341, does not closes it, but deals with the fact that it now fails silently
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https://api.github.com/repos/pandas-dev/pandas/issues/8471 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8471/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8471/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8471/events | https://github.com/pandas-dev/pandas/issues/8471 | 44,916,527 | MDU6SXNzdWU0NDkxNjUyNw== | 8,471 | BUG: allow .std() of timedelta types | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-10-05T14:57:48Z | 2014-10-05T23:52:47Z | 2014-10-05T23:52:47Z | CONTRIBUTOR | null | This currently raises `TypeError` as its disabled in `core/nanops.py`, see here: https://github.com/pydata/pandas/commit/d29d4c6623a29db36a4eb8d062bdcfe603e2b490
The issue is that `.var()` can generate a value that is too big for the timedeltas to hold propery, and std CALLS var.
solns:
- reduce the value of the time... | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-10-05T15:18:16Z | 2014-10-05T17:03:44Z | 2014-10-05T17:03:01Z | CONTRIBUTOR | null | Fixes #8444. I don't like importing DataFrame, but this was most obvious way to do it.
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```
dates = date_range('1/1/2000', periods=8)
df = DataFrame(randn(8, 4), index=dates, columns=['A', 'B', 'C', 'D'])
df.at[dates[-1]+1, 0] = 7
```
does now raise an error
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https://api.github.com/repos/pandas-dev/pandas/issues/8475 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8475/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8475/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8475/events | https://github.com/pandas-dev/pandas/pull/8475 | 44,928,365 | MDExOlB1bGxSZXF1ZXN0MjIyNTg3OTY= | 8,475 | BUG: .at indexing should allow enlargement scalars w/o regards to the type of index (GH8473) | {
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In issue #7750 there was some heated discussion about backwards compatibility and the fact we did or did not care enough about it. I don't want to start a new discussion on that topic again, rest assured (or not now :-)), but notwithstanding the at some point rather personal attacks in that discu... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-10-06T02:28:33Z | 2017-04-05T02:06:01Z | 2014-10-06T22:28:57Z | CONTRIBUTOR | null | Two things included:
1. Try to use ggplot style. If not, fall back to the previous 'default'.
2. Fixes some warnings in the doc build (part of https://github.com/pydata/pandas/issues/8234). There are some remaining warnings that I didn't have a chance to track down. Will see if I can later.
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... | 1 | 2014-10-06T02:31:53Z | 2017-04-05T02:06:08Z | 2015-05-09T16:00:59Z | CONTRIBUTOR | null | Chipping away at https://github.com/pydata/pandas/issues/8450
Unfortunately I wasn't able to find too much. Most of those tests are slow because they're checking a lot of things.
This will only shave about 30s off the test time. It's a start...
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```
>>> df
jim joe jolie
first last first last first last
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-10-06T12:37:37Z | 2014-10-06T13:21:02Z | 2014-10-06T13:21:02Z | CONTRIBUTOR | null | This is really superfluous as `.describe` is much more comprehensive.
It is only a very brief mention in the docs, only a single test (for a single dtype), and not implemented generically.
https://github.com/pydata/pandas/blob/master/pandas/tools/describe.py
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mixxing updates in indexing.rst
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Unlike the implementation offered in #7840, this version preserves the option to pass prefixes to the `orient` parameter.
I also rewrote the docstring to use the more readable list format from `pd.DataFrame.to_json`.
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```
WARNING:root:This function, oauth2client.tools.run(), and the use of the gflags library are deprecated and will be removed in a future version of the library.
Your browser has been opened to visit:
big-url-here
If your browser is on a different ... | {
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```
In [22]: ser = Series([3, 1, 2])
In [23]: a = ser.values
In [24]: a.searchsorted([0,3], sorter=np.argsort(a))
Out[24]: ar... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-10-06T20:02:02Z | 2014-10-11T19:27:25Z | 2014-10-11T19:27:25Z | MEMBER | null | Compare stable http://pandas.pydata.org/pandas-docs/stable/visualization.html#basic-plotting-plot vs dev docs http://pandas-docs.github.io/pandas-docs-travis/visualization.html#basic-plotting-plot
For the simple example of Series plotting, a legens is added with entry None when there should be no legend:
```
ts = Ser... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8492 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8492/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8492/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8492/events | https://github.com/pandas-dev/pandas/pull/8492 | 45,031,475 | MDExOlB1bGxSZXF1ZXN0MjIzMTEyMDA= | 8,492 | BUG: searchsorted sorter issue with 32bit platforms (GH8490) | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-10-06T20:21:42Z | 2014-10-06T22:01:43Z | 2014-10-06T21:58:41Z | MEMBER | null | Closes #8490
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https://api.github.com/repos/pandas-dev/pandas/issues/8493 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8493/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8493/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8493/events | https://github.com/pandas-dev/pandas/pull/8493 | 45,032,787 | MDExOlB1bGxSZXF1ZXN0MjIzMTE5MzM= | 8,493 | DOC: fix notes in plot() docstring | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8494 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8494/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8494/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8494/events | https://github.com/pandas-dev/pandas/issues/8494 | 45,034,067 | MDU6SXNzdWU0NTAzNDA2Nw== | 8,494 | Setting the label parameter in the call to DF.plot alters the DataFrame's index name | {
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"followers_url": "https://api.github.com/users/jre... | 1 | 2014-10-06T20:44:01Z | 2014-10-30T11:19:43Z | 2014-10-28T03:56:19Z | NONE | null | Setting the label parameter in the call to df.plot alters the DataFrame's index name. For example,
```
df = pd.DataFrame(data=np.random.rand(5,3), index=np.arange(5), columns=['A', 'B', 'C'])
df.index.name='RowNumber'
df.plot(y='B', label='Test')
print df.index.name
Out[1]: Test
```
See a better example at [StackOve... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8495 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8495/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8495/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8495/events | https://github.com/pandas-dev/pandas/issues/8495 | 45,050,775 | MDU6SXNzdWU0NTA1MDc3NQ== | 8,495 | DataFrame.from_csv doesn't use universal mode file opening | {
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"descript... | closed | false | null | [] | null | 4 | 2014-10-06T23:37:03Z | 2015-10-21T04:06:57Z | 2015-10-20T23:12:38Z | NONE | null | `DataFrame.from_csv` doesn't account for Windows' new lines. In the current implementation it returns a single row `DataFrame`, which is not accurate. The online suggested solution is to do something like: `mydata = csv.reader(open(mypath,'rU'))` but implementing within that method might be better.
cc: @ElDeveloper
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https://api.github.com/repos/pandas-dev/pandas/issues/8496 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8496/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8496/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8496/events | https://github.com/pandas-dev/pandas/issues/8496 | 45,092,887 | MDU6SXNzdWU0NTA5Mjg4Nw== | 8,496 | Add table id option to pandas.DataFrame.to_html | {
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"color": "006b7... | closed | false | null | [] | {
"closed_at": "2018-05-16T03:09:58Z",
"closed_issues": 1645,
"created_at": "2017-10-20T10:17:09Z",
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"followers_url": "https://api.github.com/users/j... | 4 | 2014-10-07T10:43:45Z | 2019-07-05T20:20:54Z | 2018-02-09T12:29:03Z | CONTRIBUTOR | null | I'm using the pandas.DataFrame.to_html() method to generate a table to embed into a a templated document which references the table via an id. It would be useful if pandas.DataFrame.to_html() supported a `table_id` parameter:
`df.to_html(table_id='myTable')`
to produce:
`<table border="1" class="dataframe" id='myta... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8497 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8497/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8497/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8497/events | https://github.com/pandas-dev/pandas/pull/8497 | 45,121,276 | MDExOlB1bGxSZXF1ZXN0MjIzNjA4MDI= | 8,497 | DOC/BUG:Added Missing Semicolon to Release Note v0.15 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8498 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8498/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8498/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8498/events | https://github.com/pandas-dev/pandas/pull/8498 | 45,122,903 | MDExOlB1bGxSZXF1ZXN0MjIzNjE3Nzc= | 8,498 | DOC: Another semicolon fix v0.15 | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-10-07T15:40:33Z | 2014-10-07T17:43:45Z | 2014-10-07T17:43:45Z | CONTRIBUTOR | null | Sorry for basically duplicate pr, noticed this one after.
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https://api.github.com/repos/pandas-dev/pandas/issues/8499 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8499/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8499/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8499/events | https://github.com/pandas-dev/pandas/issues/8499 | 45,128,841 | MDU6SXNzdWU0NTEyODg0MQ== | 8,499 | groupby().apply() executes the first item twice | {
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How to reproduce.
In the example below, the first item df['a'] = 1 is executed twice.
$ import pandas as pd
$ f = pd.DataFrame({'a':[1,2,3,1,1,2], 'b':[1,2,3,4,5,6]})
$ def fx(df):
print df
return df['b'].sum()
$ f.groupby('a').apply(fx)
a b
0 1 1
3 1 4
4 1 5
a b
0 1 1
3 1 ... | {
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"events_url": "https://api.github.com/users/jreback/events{/privacy}",
"followers_url": "https://api.github.com/users/jr... | 0 | 2014-10-07T16:31:32Z | 2014-10-07T21:52:42Z | 2014-10-07T21:52:42Z | CONTRIBUTOR | null | building using appveyor (windows CI)
closes #5561
https://ci.appveyor.com/project/jreback/pandas/build/1.0.455/job/2avadnw54tpv3lob
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