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https://api.github.com/repos/pandas-dev/pandas/issues/10303 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10303/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10303/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10303/events | https://github.com/pandas-dev/pandas/pull/10303 | 85,792,796 | MDExOlB1bGxSZXF1ZXN0MzcwOTQ2MTE= | 10,303 | ENH: added rsplit to StringMethods | {
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cc @sinhrks
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https://api.github.com/repos/pandas-dev/pandas/issues/10304 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10304/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10304/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10304/events | https://github.com/pandas-dev/pandas/pull/10304 | 85,800,125 | MDExOlB1bGxSZXF1ZXN0MzcwOTQ5MzU= | 10,304 | BUG: Categorical.remove_categories(np.nan) fails when underlying dtype is float | {
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"followers_url": "https://api.github.... | 8 | 2015-06-06T18:53:16Z | 2015-06-10T13:40:04Z | 2015-06-09T23:45:58Z | CONTRIBUTOR | null | Fixes GH #10156. This also makes different null values indistinguishable inside of remove_categories, but they're already indistinguishable in most other contexts:
``` .python
>>> pd.Categorical([], categories=[np.nan, None])
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "pandas/core/... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10305 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10305/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10305/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10305/events | https://github.com/pandas-dev/pandas/pull/10305 | 85,818,471 | MDExOlB1bGxSZXF1ZXN0MzcwOTc5NzA= | 10,305 | BUG: PeriodIndex.order doesnt preserve freq | {
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However, above change affects to the behavior of `Index.slice_locs`. Internally, the behavoir of `Index.get_slice_bound` seems to assume `lib.maybe_indices_to_slice` returns sl... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10306 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10306/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10306/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10306/events | https://github.com/pandas-dev/pandas/pull/10306 | 85,834,582 | MDExOlB1bGxSZXF1ZXN0MzcwOTk3NTE= | 10,306 | BUG: bug in json serialization when frame has mixed types | {
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"followers_url": "https://api.github.... | 1 | 2015-06-07T01:41:01Z | 2015-08-22T11:36:04Z | 2015-06-07T23:05:24Z | CONTRIBUTOR | null | closes https://github.com/pydata/pandas/issues/10289
on master:
``` python
>>> df
1st 2nd 3rd 4th 5th
a 10 1 foo 0.1 0.01
b 20 2 bar 0.2 0.02
c 30 3 baz 0.3 0.03
d 40 4 qux 0.4 0.04
>>> read_json(df.to_json(orient='index'), orient='index', convert_axes=False)
1st 2nd 3rd ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10308 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10308/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10308/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10308/events | https://github.com/pandas-dev/pandas/pull/10308 | 85,963,299 | MDExOlB1bGxSZXF1ZXN0MzcxMTU1MDk= | 10,308 | BUG: bug in setitem where type promotion is applied to entire block | {
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"followers_url": "https://api.github.... | 5 | 2015-06-07T23:34:30Z | 2015-06-09T23:30:23Z | 2015-06-09T14:43:27Z | CONTRIBUTOR | null | closes https://github.com/pydata/pandas/issues/10280
on master:
``` python
>>> df
foo bar baz
a 0 1 2
b 3 4 5
>>> df.dtypes
foo int64
bar int64
baz int64
dtype: object
>>> df.loc['a', 'bar'] = 3.14
>>> df.dtypes
foo float64
bar float64
baz float64
dtype: object
```
on branch:... | {
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As an example (which I previously posted on [StackOverflow](http://stackoverflow.com/questions/30627968/merge-pandas-dataframes-where-one-value-is-between-two-others)), I need to merge two pandas data... | {
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... | 0 | 2015-06-08T11:26:04Z | 2019-10-21T19:52:14Z | null | CONTRIBUTOR | null | from [SO](http://stackoverflow.com/questions/30587026/when-reading-huge-hdf5-file-with-pandas-read-hdf-why-do-i-still-get-memory)
```
In [2]: df = DataFrame(np.random.randn(1000,2),columns=list('AB'))
In [3]: df.to_hdf('test.h5','df',mode='w',format='table',data_columns=True)
In [4]: i = pd.read_hdf('test.h5','df',c... | {
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```
======================================================================
ERROR: test_file_like (pandas.io.tests.test_html.TestReadHtml)
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https://api.github.com/repos/pandas-dev/pandas/issues/10314 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10314/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10314/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10314/events | https://github.com/pandas-dev/pandas/pull/10314 | 86,255,599 | MDExOlB1bGxSZXF1ZXN0MzcxNzQzNzA= | 10,314 | Update v0.16.2.txt | {
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... | 5 | 2015-06-09T10:24:29Z | 2020-06-28T18:22:41Z | 2020-06-28T18:22:41Z | NONE | null | ```
pd.DatetimeIndex(['1976-W53'])
--> DateParseError: unknown string format
```
I tried to solve this with many libraries (dateutil, arrow, chrono, dt8601) and no one worked excepted this one : http://www.egenix.com/products/python/mxBase/mxDateTime/
```
import mx
mx.DateTime.ISO.ParseWeek("1976-W53").pydatetime()
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https://api.github.com/repos/pandas-dev/pandas/issues/10316 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10316/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10316/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10316/events | https://github.com/pandas-dev/pandas/issues/10316 | 86,573,870 | MDU6SXNzdWU4NjU3Mzg3MA== | 10,316 | DOC: API docs broken with sphinx 1.3.x | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2015-06-09T12:04:38Z | 2016-06-23T12:42:39Z | 2016-06-23T12:41:48Z | MEMBER | null | Just to track this on our side: as raised by @shoyer, there is a bug in the latest sphinx version that causes part of the API docs not to built.
Sphinx bug report: https://github.com/sphinx-doc/sphinx/issues/1822, pr: https://github.com/sphinx-doc/sphinx/pull/1828
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``` python
import pandas as pd
idx = pd.Categorical([1,2,3], categories=[1,2,3])
df = pd.DataFrame( { 'count' : pd.Series([3,2,2],index=idx) } )
# this will crash python (2.6.X or 2.7.X on linux 64 or win 64 wit... | {
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>>> d = '2013-02-02T02:12:34+0600'
>>> ts_from_str = pandas.Timestamp(d)
>>> ts_from_dt64 = pandas.Timestamp(numpy.datetime64(d))
>>> ts_from_dt64.tzinfo
>>> ts_from_str.tzinfo
pytz.FixedOffset(360)
```
NumPy documentation is clear about `datetime64` representing 'a single moment in time' and being 'always stored ... | {
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A quick search came up with this old issue: https://github.com/pydata/pandas/issues/2527.The issue was reproduced on 0.15 by tweaking the code from the previous report, which is below:
```
from pandas import date_range, S... | {
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```
results = []
for key, t1 in table1.groupby(level='id'):
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https://api.github.com/repos/pandas-dev/pandas/issues/10321 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10321/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10321/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10321/events | https://github.com/pandas-dev/pandas/pull/10321 | 86,785,199 | MDExOlB1bGxSZXF1ZXN0MzczMTUwODk= | 10,321 | BUG: Bug in to_json with certain orients and a CategoricalIndex would segfault, closes #10317 | {
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```
In [17]: df = DataFrame({ 'A' : pd.Series([3,2,2],index=pd.Categorical([1,2,3],categories=[1,2,3])), 'B' : pd.Categorical(list('aab')) })
In [18]: df
Out[18]:
A B
1 3 a
2 2 a
3 2 b
In [19]: df.index
Out[19]: CategoricalIndex([1, 2, 3], categories=[1, 2, 3], ordered=False, dtype='category'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10322 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10322/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10322/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10322/events | https://github.com/pandas-dev/pandas/pull/10322 | 86,789,275 | MDExOlB1bGxSZXF1ZXN0MzczMTU5ODE= | 10,322 | Bug in to_json causing segfault with a CategoricalIndex (GH #10317) | {
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"followers_url": "https://api.github.... | 5 | 2015-06-10T01:04:09Z | 2015-09-19T00:38:31Z | 2015-06-10T10:28:59Z | CONTRIBUTOR | null | Fixed GH #10317
Stole tests from #10321
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https://api.github.com/repos/pandas-dev/pandas/issues/10323 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10323/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10323/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10323/events | https://github.com/pandas-dev/pandas/issues/10323 | 86,862,278 | MDU6SXNzdWU4Njg2MjI3OA== | 10,323 | DOC: index's difference method not in API documentation | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2015-06-10T06:45:52Z | 2015-06-10T06:58:35Z | 2015-06-10T06:58:28Z | CONTRIBUTOR | null | http://pandas.pydata.org/pandas-docs/stable/api.html
e.g.
```
X_train.columns.difference(X_test.columns)
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10324 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10324/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10324/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10324/events | https://github.com/pandas-dev/pandas/issues/10324 | 87,098,278 | MDU6SXNzdWU4NzA5ODI3OA== | 10,324 | mapping with category data does not work | {
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"description": "pandas objects compatabi... | closed | false | null | [] | {
"closed_at": "2015-10-09T18:34:35Z",
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-06-10T20:34:49Z | 2015-07-01T13:46:10Z | 2015-07-01T13:46:10Z | NONE | null | ```
import pandas as pd
a = pd.Series([1, 2, 3, 4])
b = pd.Series(["even", "odd", "even", "odd"], dtype="category")
c = pd.Series(["even", "odd", "even", "odd"])
print("-- map by category")
try:
print(a.map(b))
except AttributeError as e:
print(e)
print("-- map by string")
print(a.map(c))
```
has the follo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10325 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10325/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10325/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10325/events | https://github.com/pandas-dev/pandas/issues/10325 | 87,115,533 | MDU6SXNzdWU4NzExNTUzMw== | 10,325 | Groupby - Apply method doesn't handle arguments correctly | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2015-06-10T21:36:24Z | 2015-06-11T08:47:37Z | 2015-06-10T21:39:14Z | NONE | null | The `apply` method on a groupby object appears to send all arguments to the applied function. As in, if you try to do `df.groupby(level='dt').apply(func, axis=1)`, the `axis=1` argument is passed to `func` rather than being parsed by `apply` as intended. The behavior is correct, however, in the `DataFrame.apply` method... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10326 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10326/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10326/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10326/events | https://github.com/pandas-dev/pandas/issues/10326 | 87,138,204 | MDU6SXNzdWU4NzEzODIwNA== | 10,326 | pivot_table passes junk to aggfunc when value column does not exist | {
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"followers_url": "https://api.github.com/users/wesm... | 5 | 2015-06-10T23:08:56Z | 2020-01-03T23:23:45Z | 2020-01-03T23:23:45Z | NONE | null | Expected behavior is that pivot_table would throw an exception explaining the missing column. Instead pivot_table passes DataFrames to aggfunc before checking.
Example:
``` python
def agg(l):
it = iter(l)
try:
value = next(it)
except StopIteration:
raise Exception("0 items in iterator")
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https://api.github.com/repos/pandas-dev/pandas/issues/10327 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10327/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10327/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10327/events | https://github.com/pandas-dev/pandas/issues/10327 | 87,154,775 | MDU6SXNzdWU4NzE1NDc3NQ== | 10,327 | Request for DataFrame.to_tsv() for reading tab delimited text | {
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] | closed | false | null | [] | null | 16 | 2015-06-11T00:22:03Z | 2019-01-29T20:49:54Z | 2015-09-22T08:52:02Z | CONTRIBUTOR | null | I propose a function, which can be called on a DataFrame, named to_tsv or to_table. The function is the equivalent of `to_csv()` with the argument `sep='\t'`. While `to_tsv()` contains the functionality to write tsv files, I find it annoying to always have to specify an additional argument. I prefer tsv files to csv fi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10328 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10328/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10328/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10328/events | https://github.com/pandas-dev/pandas/pull/10328 | 87,240,777 | MDExOlB1bGxSZXF1ZXN0Mzc0MzUxNDQ= | 10,328 | BUG/ENH: GH10319 added higher_precision argument to rolling_mean/sum | {
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```
>>> sum([0.00012456, 0.0003, -0.00012456, -0.0003])
-5.421010862427522e-20
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10329 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10329/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10329/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10329/events | https://github.com/pandas-dev/pandas/issues/10329 | 87,261,929 | MDU6SXNzdWU4NzI2MTkyOQ== | 10,329 | Strange error message when summing datetime64 and datetime.time column | {
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```
In [29]: df = pd.DataFrame({'date':pd.date_range('2012-01-01', periods=3), 'time':[datetime.time(i, i, i) for i in range(3)]})
In [30]: df
Out[30]:
date time
0 2012-01-01 00:00:00
1 2012-01-02 01:01:01
2... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10330 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10330/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10330/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10330/events | https://github.com/pandas-dev/pandas/pull/10330 | 87,331,646 | MDExOlB1bGxSZXF1ZXN0Mzc0NTg1NjQ= | 10,330 | DOC: Remove auto_close option form read_hdf | {
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This value is always ignored.
Also removes unreachable code.
xref #9327
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https://api.github.com/repos/pandas-dev/pandas/issues/10331 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10331/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10331/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10331/events | https://github.com/pandas-dev/pandas/issues/10331 | 87,410,161 | MDU6SXNzdWU4NzQxMDE2MQ== | 10,331 | Partial string matching for timestamps with multiindex | {
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``` python
test = pd.DataFrame({'l': ['A', 'B', 'C', 'C', 'B', 'A'], 'm': [pd.Timestamp('2014-06-11 14:26:27'), pd.Timestamp('2014-06-11 15:26:27'), pd.Timestamp('2014-06-11 16:26:27'), pd.Timestamp('2014... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10332 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10332/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10332/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10332/events | https://github.com/pandas-dev/pandas/issues/10332 | 87,419,103 | MDU6SXNzdWU4NzQxOTEwMw== | 10,332 | BUG: Panel.apply (2d) doesn't work when function returns a scalar of NumPy datatype in 0.16.1 | {
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test code is as follows:
```
import pandas
import numpy
panel = pandas.Panel(numpy.random.randn(5, 5, 5))
panel.apply(lambda df: 0, axis=[1, 2]) # OK
panel.apply(lambda df: 0.0, axis=[1, 2]) # OK
panel.apply(lambda df: numpy... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10333 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10333/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10333/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10333/events | https://github.com/pandas-dev/pandas/issues/10333 | 87,507,387 | MDU6SXNzdWU4NzUwNzM4Nw== | 10,333 | SciPy 2015 conference birds-of-a-feather session | {
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I'll be at SciPy and would definitely like to m... | {
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] | closed | true | null | [] | null | 8 | 2015-06-12T01:11:57Z | 2021-08-09T09:35:00Z | 2015-06-12T01:28:20Z | NONE | spam | I have tried the function `df.iterrows()` but its performance is horrible. Which is not surprising given that `iterrows()` returns a `Series` with full schema and meta data, not just the values (which all that I need).
The second method that I have tried is `for row in df.values`, which is significantly faster. Howeve... | {
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```
df_mask = pd.DataFrame({'AAA': [True] * 4,
'BBB': [False]*4,
'CCC': [True, False, True, False]}); print(df_mask)
```
```
AAA BBB CCC
0 True False True
1 True False False
2 True False T... | {
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So, I wasn't sure if I should be including a unit test for this. This issue was a segfault, which was happening when you do:
```
s = pd.Series([], index=pd.DatetimeIndex([]), dtype=np.object)
s.resample('d', how='count')
```
so I suppose I coul... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10339 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10339/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10339/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10339/events | https://github.com/pandas-dev/pandas/pull/10339 | 87,698,193 | MDExOlB1bGxSZXF1ZXN0Mzc1NTMzODc= | 10,339 | DOC: add versionadded to docstrings for 0.16.0 / 0.16.1 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10340 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10340/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10340/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10340/events | https://github.com/pandas-dev/pandas/issues/10340 | 87,782,445 | MDU6SXNzdWU4Nzc4MjQ0NQ== | 10,340 | doc/make.py only works for development build | {
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See this [SO que... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10341 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10341/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10341/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10341/events | https://github.com/pandas-dev/pandas/pull/10341 | 87,824,558 | MDExOlB1bGxSZXF1ZXN0Mzc1OTUzODY= | 10,341 | BUG: Check complib values | {
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"followers_url": "https://api.github.... | 4 | 2015-06-12T19:17:00Z | 2015-06-15T13:56:20Z | 2015-06-12T21:49:39Z | CONTRIBUTOR | null | Add check for complib when opening a HDFStore
closes #4582
closes #8874
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https://api.github.com/repos/pandas-dev/pandas/issues/10342 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10342/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10342/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10342/events | https://github.com/pandas-dev/pandas/issues/10342 | 87,866,799 | MDU6SXNzdWU4Nzg2Njc5OQ== | 10,342 | df.fillna inplace bug | {
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"color": "00... | closed | false | null | [] | null | 3 | 2015-06-12T22:25:23Z | 2015-06-12T22:43:33Z | 2015-06-12T22:43:18Z | NONE | null | This code:
```
a = df()
a['f'] = [None, None]
a['s'] = [None, None]
a['t'] = [None, None]
a.loc[:,['f','s']] = a.loc[:,['f','s']].fillna(-1) #works
a.loc[:,'f'].fillna(-1, inplace=True) #also works
a.loc[:,['f','s']].fillna(-1, inplace=True) #doesn't
```
It's not the biggest error, but still.
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... | 0 | 2015-06-13T02:37:15Z | 2019-10-21T20:06:20Z | null | CONTRIBUTOR | null | As discussed in #10266 `Series.asof` is effectively equivalent to `s.dropna().reindex(where, method='ffill')`. The implementation of `Series.asof` uses `Index.asof_locs`, which is used no where else in the code, and is untested. So deprecating `Series.asof` might make sense.
Let's add the impls discussed (IOW, implem... | {
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For copy/paste to Jupyter:
```
import numpy as np
import pandas as pd
from IPython.display ... | {
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"followers_url": "https://api.github.com/users/jr... | 15 | 2015-06-13T03:10:35Z | 2015-08-13T21:55:58Z | 2015-08-13T10:20:30Z | CONTRIBUTOR | null | closes #10343 and discussion on #10266 - deprecating `Series.asof(where)` in favour of `Series.reindex(where, method='ffill')`.
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... | 5 | 2015-06-13T13:35:44Z | 2021-04-18T07:01:42Z | null | CONTRIBUTOR | null | xref #7895
When reindexing on a multiindex with `method='ffill'` or `method='bfill'`, it would be very useful to be able to restrict the fill to certain groups/levels of the index.
For example, consider the following:
```
In [1]: dates = pd.date_range(start=pd.Timestamp('20080102'),
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This is applied on the online docs, but can be merged normally now
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xref #2494
xref #1071
custom meta-data
xref #2485
It would be very convenient if unit support could be integrated into pandas.
Idea: pandas checks for the presence of a unit-attribute of columns and - if present - uses it
- with 'print' to show the units e.g. below the column names
- to calculat... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10350 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10350/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10350/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10350/events | https://github.com/pandas-dev/pandas/pull/10350 | 88,078,932 | MDExOlB1bGxSZXF1ZXN0Mzc2MzI4MTg= | 10,350 | BUG: frequencies.get_freq_code raises an error against offset with n != 1 | {
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```
# OK
>>> import pandas.tseries.frequencies as f
>>> f.get_freq_code(('D', 3))
(6000, 3)
>>> import pandas.tseries.offsets as offsets
>>> f.get_freq_code(offsets.Day())
(6000, 1)
# NG!
>>> f.get_fre... | {
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For consistency and writing to files it would be good if pandas respects numpy fixed length strings.
```
import numpy as np
import pandas as pd
df = pd.DataFrame({'date': np.array(['2015-10-10', '2015-01-01'], dtype='S10')})
print(df.date.dtype)
```
Results in `dtype('O')... | {
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In pandas 0.16.2 (and already in 0.16.0), using std() for aggregation after a groupby( 'my_column', as_index=False) modifies 'my_column' by taking its sqrt(). Example:
``` python
df = pandas.DataFrame({
'a' : [1,1,1,2,2,2,3,3,3],
'b' : [1,2,3,4,5,6,7,8,... | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-06-15T09:46:16Z | 2015-08-19T21:39:47Z | 2015-08-19T21:39:47Z | NONE | null | The code sample in pandas/core/categorical.py needs a minor correction. In https://github.com/pydata/pandas/blob/master/pandas/core/categorical.py#L186:
```
>>> a = Categorical(['a','b','c','a','b','c'], ['c', 'b', 'a'])
>>> a.min()
```
Shouldn't a.is_ordered() come before a.min() ?
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https://api.github.com/repos/pandas-dev/pandas/issues/10357 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10357/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10357/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10357/events | https://github.com/pandas-dev/pandas/issues/10357 | 88,384,754 | MDU6SXNzdWU4ODM4NDc1NA== | 10,357 | TST: run doc-tests | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-06-15T10:32:42Z | 2015-06-15T10:41:18Z | 2015-06-15T10:41:18Z | CONTRIBUTOR | null | need to add the option `--with-doctest` in `ci/script.py` to run doc tests. Lots of these fail at them moment though.
We could run add these incrementally as the doc tests are fixed though, eg add lines line
`nosetests --with-doctest pandas/core` after the main tester
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https://api.github.com/repos/pandas-dev/pandas/issues/10358 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10358/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10358/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10358/events | https://github.com/pandas-dev/pandas/pull/10358 | 88,407,996 | MDExOlB1bGxSZXF1ZXN0Mzc2ODUzOTE= | 10,358 | Fixing the code sample in pandas/core/categorical.py | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10359 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10359/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10359/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10359/events | https://github.com/pandas-dev/pandas/pull/10359 | 88,450,933 | MDExOlB1bGxSZXF1ZXN0Mzc3MDA0NjU= | 10,359 | DOC: consistent imports (GH9886) part III | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10360 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10360/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10360/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10360/events | https://github.com/pandas-dev/pandas/issues/10360 | 88,483,152 | MDU6SXNzdWU4ODQ4MzE1Mg== | 10,360 | BUG: _NDFrameIndexer._setitem_with_indexer() doesn't handle MultiIndex and mixed types properly | {
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... | 6 | 2015-06-15T16:59:25Z | 2019-10-23T04:03:32Z | 2019-10-23T04:03:31Z | CONTRIBUTOR | null | Compare the behavior of the homogeneously typed `panel1` with that of the heterogeneously types `panel2`:
```
In [1]: import pandas as pd
In [29]: panel1 = pd.Panel([[[0., 0.]], [[0., 0.]]], items=['A', 'B'], minor_axis=['x', 'y'])
In [30]: panel2 = pd.Panel([[[0., 0.]], [['o', 'o']]], items=['A', 'B'], minor_axis=[... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10361 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10361/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10361/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10361/events | https://github.com/pandas-dev/pandas/issues/10361 | 88,525,164 | MDU6SXNzdWU4ODUyNTE2NA== | 10,361 | ERROR: test_creating_and_reading_multiple_sheets (pandas.io.tests.test_excel.ExcelReaderTests) | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2015-06-15T20:01:00Z | 2016-11-11T11:16:23Z | 2016-11-11T11:16:20Z | CONTRIBUTOR | null | ```
======================================================================
ERROR: test_creating_and_reading_multiple_sheets (pandas.io.tests.test_excel.ExcelReaderTests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10362 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10362/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10362/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10362/events | https://github.com/pandas-dev/pandas/issues/10362 | 88,531,198 | MDU6SXNzdWU4ODUzMTE5OA== | 10,362 | Improve Documentation for pandas.Series.interpolate as to how index is used | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2015-06-15T20:27:20Z | 2015-08-07T10:54:07Z | 2015-08-07T10:54:07Z | CONTRIBUTOR | null | From the docs:
> ‘linear’: ignore the index and treat the values as equally spaced. default
> ‘index’, ‘values’: use the actual numerical values of the index
but the remaining types, for example ‘quadratic’, ‘cubic’, ‘barycentric’, `krogh`, don't specify whether they assume equal spacing or use the index values.
I ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10363 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10363/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10363/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10363/events | https://github.com/pandas-dev/pandas/issues/10363 | 88,536,091 | MDU6SXNzdWU4ODUzNjA5MQ== | 10,363 | Inconsistent Series/scalar comparison behavior based upon the scalar's type | {
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] | closed | false | null | [] | null | 4 | 2015-06-15T20:46:32Z | 2015-06-15T21:08:49Z | 2015-06-15T21:01:34Z | NONE | null | It's pretty unexpected that the behavior of `x <= pd.Series(...)` depends on whether `x` is a python float or a `np.float64`:
``` python
>>> import pandas as pd
>>> import numpy as np
>>> 5 <= pd.Series(range(10))
0 False
1 False
2 False
3 False
4 False
5 True
6 True
7 True
8 True
9 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10364 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10364/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10364/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10364/events | https://github.com/pandas-dev/pandas/issues/10364 | 88,716,777 | MDU6SXNzdWU4ODcxNjc3Nw== | 10,364 | BUG/DOC: DataFrame.values return type when uint64 is mixed with signed int types | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2015-06-16T12:44:52Z | 2017-02-18T17:33:32Z | 2017-02-18T12:03:24Z | CONTRIBUTOR | null | `DataFrame.values`' doc mentions type promotion but leaves out that when `uint64` is mixed with signed `int` types, the return type is `int64`, which can be surprising. Perhaps consider returning `dtype(object)` in `internals._interleaved_dtype` when `uint64` and signed `int`s are present?
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... | 3 | 2015-06-16T15:09:18Z | 2021-03-09T17:00:02Z | 2021-03-09T17:00:01Z | CONTRIBUTOR | null | Using piecewise_polynomial results in `ZeroDivisionError`. I assume there is something else that needs to be passed (not `order`) to make this work:
``` python
test = pd.DataFrame({'a':range(1000)})
test.ix[3] = np.nan
test.interpolate(method='piecewise_polynomial')
```
``` py-tb
ZeroDivisionError ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10366 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10366/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10366/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10366/events | https://github.com/pandas-dev/pandas/issues/10366 | 88,776,630 | MDU6SXNzdWU4ODc3NjYzMA== | 10,366 | Irregular errors when reading certain categorical strings from hdf | {
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"description": "Unicode strings",
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"followers_url": "https://api.github.com/users/jr... | 8 | 2015-06-16T16:33:23Z | 2015-08-28T02:29:03Z | 2015-08-28T02:29:03Z | CONTRIBUTOR | null | It seems that there is something bad happening when we use certain strings with special characters AND the empty string with categoricals:
``` python
# -*- coding: latin-1 -*-
import pandas
import os
examples = [
pandas.Series(['EÉ, 17', '', 'a', 'b', 'c'], dtype='category'),
p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10367 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10367/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10367/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10367/events | https://github.com/pandas-dev/pandas/pull/10367 | 88,850,645 | MDExOlB1bGxSZXF1ZXN0Mzc4NDYzNjA= | 10,367 | BUG: drop_duplicates drops name(s). | {
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Based on @seth-p and @jreback 's fix, added tets for datetime-likes.
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https://api.github.com/repos/pandas-dev/pandas/issues/10368 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10368/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10368/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10368/events | https://github.com/pandas-dev/pandas/issues/10368 | 88,865,126 | MDU6SXNzdWU4ODg2NTEyNg== | 10,368 | Sparsification of Graphs | {
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http://arxiv.org/abs/0808.4134
Spectral Sparsification of Graphs
Daniel A. Spielman, Shang-Hua Teng
We introduce a new notion of graph sparsificaiton based on spectr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10369 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10369/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10369/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10369/events | https://github.com/pandas-dev/pandas/issues/10369 | 88,873,548 | MDU6SXNzdWU4ODg3MzU0OA== | 10,369 | pandas.read_msgpack(None) returns [78, 111, 110, 101] | {
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If someone is really sending empty msgpacks out there to transmit [78, 111, 110, 101], they could add a special case.
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https://api.github.com/repos/pandas-dev/pandas/issues/10370 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10370/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10370/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10370/events | https://github.com/pandas-dev/pandas/pull/10370 | 88,881,016 | MDExOlB1bGxSZXF1ZXN0Mzc4NTc1MjM= | 10,370 | CI: use versioneer to have PEP440 versions | {
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- use binstar build
- OSX stack testing, closes #7127
This removes all of the original manual-ish logic to create/manage the versioning in `setup.py`, and replaces with `versioneer.py` (bundled inline) to handle correct versioning for release, development, an... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10371 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10371/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10371/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10371/events | https://github.com/pandas-dev/pandas/issues/10371 | 88,902,151 | MDU6SXNzdWU4ODkwMjE1MQ== | 10,371 | Add note in docs for interpolate that Only `method=linear` interpolation is supported on MultiIndexes. | {
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"f... | 2 | 2015-06-17T03:41:16Z | 2015-07-15T23:36:26Z | 2015-07-15T23:36:26Z | CONTRIBUTOR | null | Trying to interpolate a DataFrame with MultiIndex:
```
lib/python2.7/site-packages/pandas/core/generic.pyc in interpolate(self, method, axis, limit, inplace, downcast, **kwargs)
2868
2869 if isinstance(self.index, MultiIndex) and method != 'linear':
-> 2870 raise ValueError("Only `method=lin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10372 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10372/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10372/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10372/events | https://github.com/pandas-dev/pandas/pull/10372 | 88,924,587 | MDExOlB1bGxSZXF1ZXN0Mzc4Njg3NzA= | 10,372 | ERR: GH9513 NaT methods now raise ValueError | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10373 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10373/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10373/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10373/events | https://github.com/pandas-dev/pandas/issues/10373 | 89,007,027 | MDU6SXNzdWU4OTAwNzAyNw== | 10,373 | TST: Make understandable assertion messages | {
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If it worth to be discussed, I'll prepare more e... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10374 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10374/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10374/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10374/events | https://github.com/pandas-dev/pandas/issues/10374 | 89,014,696 | MDU6SXNzdWU4OTAxNDY5Ng== | 10,374 | ENH: Add `categorize` method to Categoricals | {
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... | 4 | 2015-06-17T13:19:54Z | 2018-12-14T18:54:44Z | 2018-12-14T18:54:43Z | CONTRIBUTOR | null | I may be missing an existing method here. Didn't see anything though...
Given a Categorical
``` python
In [10]: s = pd.Series(['A', 'B', 'C', 'A'], dtype='category')
In [11]: s
Out[11]:
0 A
1 B
2 C
3 A
dtype: category
Categories (3, object): [A, B, C]
```
And some codes, `new_codes = pd.Series([0, 1, 0,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10375 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10375/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10375/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10375/events | https://github.com/pandas-dev/pandas/issues/10375 | 89,016,700 | MDU6SXNzdWU4OTAxNjcwMA== | 10,375 | PERF: groupby slower than pure numpy (for many aggregation functions) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10376 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10376/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10376/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10376/events | https://github.com/pandas-dev/pandas/pull/10376 | 89,035,501 | MDExOlB1bGxSZXF1ZXN0Mzc5MDc2NzM= | 10,376 | ENH: Enable ExcelWriter to construct in-memory sheets | {
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"followers_url": "https://api.github.com/users/jr... | 9 | 2015-06-17T14:37:38Z | 2015-06-20T16:20:16Z | 2015-06-20T16:20:11Z | CONTRIBUTOR | null | Add support for StringIO/BytesIO to ExcelWriter
Add vbench support for writing excel files
Add support for serializing lists/dicts to strings
Fix bug when reading blank excel sheets
closes #8188
closes #7074
closes #6403
closes #7171
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"de... | closed | false | null | [] | null | 3 | 2015-06-17T15:47:57Z | 2015-06-17T23:26:21Z | 2015-06-17T15:56:38Z | NONE | null | It appears that appending a dataframe with a column containing string representations of dates, to a dataframe containing datetime objects now results in a column of mixed types, previously the strings were converted to datetime. In addition filter operations using strings now no longer match the equivalent datetime o... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10378 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10378/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10378/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10378/events | https://github.com/pandas-dev/pandas/issues/10378 | 89,058,144 | MDU6SXNzdWU4OTA1ODE0NA== | 10,378 | Pass through the kwargs to the various interpolators | {
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For example the [spline](https://github.com/pydata/pandas/blob/821542fb1dfd55b0e0d25... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10379 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10379/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10379/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10379/events | https://github.com/pandas-dev/pandas/pull/10379 | 89,078,879 | MDExOlB1bGxSZXF1ZXN0Mzc5MjY5MjY= | 10,379 | Check for size=0 before setting item | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2015-06-17T17:38:44Z | 2015-06-18T15:43:28Z | 2015-06-18T15:36:21Z | CONTRIBUTOR | null | This is a second try at fixing #10193; the first try is in #10194. There is some useful discussion in that PR, so I didn't want to clobber that- not sure of the etiquette of multiple PRs for the same bug??
The discussion around setting values in views on #10194 is separate from the bug itself- I find that setting an i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10380 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10380/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10380/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10380/events | https://github.com/pandas-dev/pandas/issues/10380 | 89,082,838 | MDU6SXNzdWU4OTA4MjgzOA== | 10,380 | Spline Interpolation Should Use InterpolatedUnivariateSpline | {
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"description": "np.nan, ... | open | false | null | [] | null | 1 | 2015-06-17T17:56:47Z | 2021-04-18T07:02:26Z | null | CONTRIBUTOR | null | The spline Interpolation should probably use `InterpolatedUnivariateSpline` rather than [`UnivariateSpline`](https://github.com/pydata/pandas/blob/821542fb1dfd55b0e0d25e55eb4fee6555d01cbd/pandas/core/common.py#L1737) as it does now.
For some discussion: https://github.com/scipy/scipy/issues/4975#issuecomment-112867854... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10381 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10381/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10381/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10381/events | https://github.com/pandas-dev/pandas/issues/10381 | 89,088,349 | MDU6SXNzdWU4OTA4ODM0OQ== | 10,381 | BUG: DataFrame.to_hdf doesn't pass along min_itemsize for index | {
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``` python
In [21]: df = DataFrame(dict(A = 'foo', B = 'bar'),index=range(5)).set_index("A")
In [22]: df.to_hdf('store.h5', 'test', format='table', min_itemsize={'index': 10})
In [23]: store = pd.HDFStore('store.h5')
In [24]: store.get_storer('test').table
Out[24]:
/test/table (Tab... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10382 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10382/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10382/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10382/events | https://github.com/pandas-dev/pandas/issues/10382 | 89,118,179 | MDU6SXNzdWU4OTExODE3OQ== | 10,382 | Incorrect usage of float16 in algos.pyx | {
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... | 3 | 2015-06-17T20:29:14Z | 2018-01-12T11:08:28Z | 2018-01-12T11:08:27Z | NONE | null | Hi, everyone
According to [documentation](http://docs.scipy.org/doc/numpy-dev/reference/c-api.coremath.html#half-precision-functions), `np.float16` should **not** be used in C code as it is right now in pandas/algos.pyx:38 (assigning `np.NINF` to a `np.float16` container in "cython-eventually-converted-to-C" code
As... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10383 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10383/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10383/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10383/events | https://github.com/pandas-dev/pandas/pull/10383 | 89,206,159 | MDExOlB1bGxSZXF1ZXN0Mzc5NzMyMjI= | 10,383 | Allow passing other arguments to interpolation functions | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10384 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10384/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10384/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10384/events | https://github.com/pandas-dev/pandas/pull/10384 | 89,216,132 | MDExOlB1bGxSZXF1ZXN0Mzc5NzY2Mjk= | 10,384 | ENH: column label filtering via regexes to work for numeric names | {
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closes #10506
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https://api.github.com/repos/pandas-dev/pandas/issues/10385 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10385/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10385/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10385/events | https://github.com/pandas-dev/pandas/issues/10385 | 89,267,295 | MDU6SXNzdWU4OTI2NzI5NQ== | 10,385 | BUG: specifying multiple columns as primary keys broken in io.sql.get_schema | {
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I think this still works for the fallback sqlite version, but not for the new sqlalchemy implementation. in `PrimaryKeyConstraint`, the columns should be feeded as separate positional arguments instead of a list (https://github.com/pydata... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10386 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10386/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10386/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10386/events | https://github.com/pandas-dev/pandas/pull/10386 | 89,273,917 | MDExOlB1bGxSZXF1ZXN0Mzc5OTg3NDU= | 10,386 | BUG: fix multiple columns as primary key in io.sql.get_schema (GH10385) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10387 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10387/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10387/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10387/events | https://github.com/pandas-dev/pandas/pull/10387 | 89,297,729 | MDExOlB1bGxSZXF1ZXN0MzgwMDc2Mzc= | 10,387 | BUG: DataFrame.plot raises ValueError when color name is specified by multiple characters | {
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```
# OK
df = pd.DataFrame(np.random.randn(3, 3))
df[0].plot(color='green')
# single green line
# OK
df.plot(color=['green'])
# triple green lines
# NG
df.plot(color='green')
# ValueError... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10388 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10388/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10388/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10388/events | https://github.com/pandas-dev/pandas/issues/10388 | 89,302,139 | MDU6SXNzdWU4OTMwMjEzOQ== | 10,388 | NaT in MultiIndex throws ValueError when reset_index() is called. | {
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```
x = pp.DataFrame({
'other': ['a', np.nan],
'date': ['2015-03-22', np.nan],
'amount': [2, 3]
})
x.date = pp.to_datetime(x.date)
```
| index | amount | date | other |
| --- | --- | --- | --- |
| 0 | 2 | 2015-03-22 | a |
| 1 | 3 | NaT | NaN |
The reset_index here then fails ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10389 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10389/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10389/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10389/events | https://github.com/pandas-dev/pandas/pull/10389 | 89,432,413 | MDExOlB1bGxSZXF1ZXN0MzgwNjcyOTY= | 10,389 | BUG: closes bug in reset_index when index contains NaT | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-06-19T00:29:40Z | 2015-06-20T12:17:35Z | 2015-06-20T11:09:45Z | CONTRIBUTOR | null | closes https://github.com/pydata/pandas/issues/10388
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https://api.github.com/repos/pandas-dev/pandas/issues/10390 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10390/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10390/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10390/events | https://github.com/pandas-dev/pandas/issues/10390 | 89,445,710 | MDU6SXNzdWU4OTQ0NTcxMA== | 10,390 | BUG: DataFrame with tz-aware data and max(axis=1) returns NaN | {
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... | closed | false | null | [] | {
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"followers_url": "https://api.github... | 2 | 2015-06-19T02:08:00Z | 2019-01-16T01:36:21Z | 2019-01-16T01:36:21Z | NONE | null | I have a dataframe looks like this, and its column 2 is missing:
When I try to select the max date in each row, I got all NaN in return:
![img2](https://cloud.githubusercontent.com/assets/6269369/8246090/eea64... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10391 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10391/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10391/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10391/events | https://github.com/pandas-dev/pandas/issues/10391 | 89,580,543 | MDU6SXNzdWU4OTU4MDU0Mw== | 10,391 | groupby fails for pyhon 3 unsortable objects with sort=True | {
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] | closed | false | null | [] | null | 1 | 2015-06-19T14:41:08Z | 2015-06-20T11:17:01Z | 2015-06-20T11:16:53Z | NONE | null | The default groupby behaviour will try to sort every object. But python 3 does not define an ordering on everything and so the method will fail with the default parameters. In python 2 the order of objects is random (the id).
``` python
import pandas as pd
class A: pass
df = pd.DataFrame([[A(), i, i**2] for i in ra... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10392 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10392/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10392/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10392/events | https://github.com/pandas-dev/pandas/issues/10392 | 89,633,876 | MDU6SXNzdWU4OTYzMzg3Ng== | 10,392 | BUG: select_column does not preserve the column name | {
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... | closed | false | null | [] | {
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In [4]: df = DataFrame({'A' : np.random.randn(10), 'B' : 'foo'})
In [5]: df.to_hdf('test.h5','df',mode='w',format='table',data_columns=True)
# this should have a name of B
In [7]: with pd.HDFStore('test.h5') as store:
print store.select_column('df','B')
...:
0 foo
1 foo
2 foo
3 foo
4 fo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10394 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10394/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10394/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10394/events | https://github.com/pandas-dev/pandas/issues/10394 | 89,668,758 | MDU6SXNzdWU4OTY2ODc1OA== | 10,394 | moderate to large groupby computations hang in multithreading | {
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] | closed | false | null | [] | null | 1 | 2015-06-19T21:53:47Z | 2015-06-19T22:57:26Z | 2015-06-19T22:57:02Z | NONE | null | Since I am running calculations on very large sets of data, I have broken the data into moderate-sized chunks (using MutliIndex) and run the calculation in parallel. I first tried doing this using threading, but ended up using multiprocessing because some calculations 'hung' when I used threading.
Here is my system i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10395 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10395/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10395/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10395/events | https://github.com/pandas-dev/pandas/issues/10395 | 89,689,967 | MDU6SXNzdWU4OTY4OTk2Nw== | 10,395 | bug: interpolate() row-by-row doesn't work when setting inplace=True | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-06-20T00:20:55Z | 2015-06-23T14:00:40Z | 2015-06-23T14:00:40Z | NONE | null | ``` python
# pandas version 0.16.2
import numpy as np
import pandas as pd
np.random.seed(12345)
# simulate some data
df = pd.DataFrame(np.random.randn(250, 10), columns=np.arange(1, 11), index=pd.date_range('2015-01-01', periods=250, freq='B'))
# set 20% data to NaN
sel = np.random.choice([True, False], size=(250, 10... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10396 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10396/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10396/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10396/events | https://github.com/pandas-dev/pandas/pull/10396 | 89,744,620 | MDExOlB1bGxSZXF1ZXN0MzgxNjU0ODc= | 10,396 | PERF: parse and timedelta ops improvements, #6755 | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-06-20T09:27:26Z | 2015-06-22T09:16:22Z | 2015-06-22T08:34:19Z | CONTRIBUTOR | null | closes #6755
```
-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
dtype_infer_timedelta64_1 | 7.0527 | 119... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10397 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10397/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10397/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10397/events | https://github.com/pandas-dev/pandas/pull/10397 | 89,779,024 | MDExOlB1bGxSZXF1ZXN0MzgxNjkyMjg= | 10,397 | BLD: remove support for 3.2, #9118 | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-06-20T14:58:44Z | 2015-06-22T09:03:08Z | 2015-06-22T08:46:38Z | CONTRIBUTOR | null | closes #9118
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https://api.github.com/repos/pandas-dev/pandas/issues/10398 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10398/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10398/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10398/events | https://github.com/pandas-dev/pandas/issues/10398 | 89,790,392 | MDU6SXNzdWU4OTc5MDM5Mg== | 10,398 | Sorted dataframe resets after indexing | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2015-06-20T16:44:50Z | 2016-07-18T11:19:11Z | 2016-07-18T11:19:11Z | NONE | null | I found a in issue when sorting followed by indexing in pandas when reset_index() is not used. I'm not sure why but the ordering of the rows reverts back after indexing and hence results in dfList containing dataframes that are ordered differently.
reset_index() works and helped to overcome the problem. This is reall... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10399 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10399/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10399/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10399/events | https://github.com/pandas-dev/pandas/issues/10399 | 89,853,497 | MDU6SXNzdWU4OTg1MzQ5Nw== | 10,399 | potential dataframe apply bug | {
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"de... | closed | false | null | [] | null | 2 | 2015-06-21T02:47:33Z | 2015-06-22T09:13:45Z | 2015-06-22T08:16:30Z | CONTRIBUTOR | null | I seem to have a weird problem with DataFrame.apply(.., axis=1) not matching the axes/columns correctly, ONLY if there's a time column in the dataframe?
See details here: http://nbviewer.ipython.org/gist/anonymous/a0bcaa95a48327fadc63
but basically I try to apply this:
``` python
def combine_binning_data(row):
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https://api.github.com/repos/pandas-dev/pandas/issues/10400 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10400/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10400/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10400/events | https://github.com/pandas-dev/pandas/pull/10400 | 89,871,354 | MDExOlB1bGxSZXF1ZXN0MzgxNzk4OTQ= | 10,400 | BUG: GH10395 bug in DataFrame.interpolate with axis=1 and inplace=True | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10401 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10401/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10401/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10401/events | https://github.com/pandas-dev/pandas/pull/10401 | 89,925,697 | MDExOlB1bGxSZXF1ZXN0MzgxODYwNzI= | 10,401 | BUG: GH10392 bug where Table.select_column does not preserve column name | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10402 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10402/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10402/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10402/events | https://github.com/pandas-dev/pandas/issues/10402 | 89,946,116 | MDU6SXNzdWU4OTk0NjExNg== | 10,402 | density plot on zero series throws exception | {
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... | 4 | 2015-06-21T18:52:40Z | 2015-07-14T11:53:12Z | 2015-06-22T01:56:04Z | NONE | null | ``` python
pd.Series(np.zeros(4)).to_frame().plot(kind='kde')
```
Executing the above line throws the below exception.
```
LinAlgError Traceback (most recent call last)
<ipython-input-118-eac1a90078a2> in <module>()
----> 1 pd.Series(np.zeros(4)).to_frame().plot(kind='kde')
```
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