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https://api.github.com/repos/pandas-dev/pandas/issues/10003 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10003/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10003/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10003/events | https://github.com/pandas-dev/pandas/pull/10003 | 71,426,468 | MDExOlB1bGxSZXF1ZXN0MzQyMTk3NTM= | 10,003 | pivot table with margins (GH3335) | {
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"de... | closed | false | null | [] | null | 2 | 2015-04-27T23:12:09Z | 2015-05-09T20:18:50Z | 2015-05-09T20:18:50Z | NONE | null | closes #3335
Changed code to raise an exception when margin=True and All was being used in the table
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https://api.github.com/repos/pandas-dev/pandas/issues/10004 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10004/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10004/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10004/events | https://github.com/pandas-dev/pandas/issues/10004 | 71,555,097 | MDU6SXNzdWU3MTU1NTA5Nw== | 10,004 | DOC: add warning to top of 0.16.1 about datareader changing in 0.17.0 | {
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```
In [16]: pd.DataFrame(pd.Series([], dtype="int64"), columns=["D"]).dtypes
Out[16]:
D object
dtype: object
In [17]: pd.DataFrame(pd.Series([], dtype="int64")).dtypes
Out[17]:
0 int64
dtype: object
```
This came up in #9983 .
When this is fixed, the `check_dtype` flag should also b... | {
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Some of the string ... | {
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] | closed | false | null | [] | null | 20 | 2015-04-28T21:56:33Z | 2015-11-18T03:26:14Z | 2015-11-18T01:43:42Z | NONE | null | I've seen many developers post about incredible slowness when writing pandas dataframe to a SQL Server table. Some people labeled the issue "chunk size doesn't work" or "data incompatibility slowness" and what not. After a lengthy research I found the following explanation from SQLAlchemy:
http://docs.sqlalchemy.org/e... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-29T00:48:57Z | 2015-04-29T15:15:43Z | 2015-04-29T10:27:10Z | CONTRIBUTOR | null | It seems inconsistent that all the other `fillna()` methods (`DataFrame.fillna`, `Series.fillna`, etc) have `value` as the first kwarg but `Categorical` has `fill_value` instead
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https://api.github.com/repos/pandas-dev/pandas/issues/10013 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10013/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10013/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10013/events | https://github.com/pandas-dev/pandas/issues/10013 | 71,776,201 | MDU6SXNzdWU3MTc3NjIwMQ== | 10,013 | assert_almost_equal fails with KeyError on non-integer column names | {
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"d... | closed | false | null | [] | null | 4 | 2015-04-29T04:38:57Z | 2015-05-01T17:08:02Z | 2015-04-29T10:40:36Z | NONE | null | ```
import pandas as pd
df = pd.DataFrame(0:'b', index = ['c'])
pd.util.testing.assert_almost_equal(df, df) # SUCCESS
df = pd.DataFrame({'a':'b'}, index = ['c'])
pd.util.testing.assert_almost_equal(df, df) # FAIL KeyError
```
Top of the trace stack is:
- pandas\hashtable.pyd in pandas.hashtable.PyObjectHashTable.g... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10014 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10014/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10014/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10014/events | https://github.com/pandas-dev/pandas/pull/10014 | 71,854,019 | MDExOlB1bGxSZXF1ZXN0MzQzNTQ5MzI= | 10,014 | BUG: null group spills into final group when grouping on a categorical | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-04-29T11:48:50Z | 2015-04-29T23:08:00Z | 2015-04-29T23:05:42Z | CONTRIBUTOR | null | Fixes GH #9603
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https://api.github.com/repos/pandas-dev/pandas/issues/10015 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10015/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10015/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10015/events | https://github.com/pandas-dev/pandas/pull/10015 | 71,870,164 | MDExOlB1bGxSZXF1ZXN0MzQzNjA1Njg= | 10,015 | Only add the ga: prefix if it is required | {
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] | closed | false | null | [] | null | 2 | 2015-04-29T13:07:31Z | 2015-07-29T07:38:11Z | 2015-07-28T21:50:33Z | NONE | null | This checks if ga keys are already prefixed with ga: and only adds the
prefix if required. The previous behaviour was particularly anoying for
complex filters where keys within the filter would need a ga: prefix but
the first one could not have the prefix.
eg. Both the following would fail:
`ga:pagepath=/foo;ga:city=L... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10016 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10016/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10016/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10016/events | https://github.com/pandas-dev/pandas/pull/10016 | 71,872,400 | MDExOlB1bGxSZXF1ZXN0MzQzNjE0NzU= | 10,016 | Fix a bug in io.ga that requires an index_col | {
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] | closed | false | null | [] | null | 2 | 2015-04-29T13:18:03Z | 2015-07-29T07:38:01Z | 2015-07-28T21:50:26Z | NONE | null | See: http://stackoverflow.com/questions/26858077/pandas-io-ga-not-working-for-me-solved
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https://api.github.com/repos/pandas-dev/pandas/issues/10017 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10017/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10017/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10017/events | https://github.com/pandas-dev/pandas/issues/10017 | 71,893,554 | MDU6SXNzdWU3MTg5MzU1NA== | 10,017 | assigning column values to empty dataframe with loc | {
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"de... | closed | false | null | [] | null | 9 | 2015-04-29T14:37:29Z | 2020-06-11T09:07:33Z | 2015-04-29T22:26:27Z | NONE | null | I'm trying to add a column to an existing dataframe. The dataframe can be empty (0 rows) but I want the column to be added anyway.
```
import pandas as pd
import numpy as np
df = pd.DataFrame(index=np.arange(4))
df.loc[:,'col'] = 42 # this works fine!
df = pd.DataFrame(index=np.arange(0)) # empty dataframe
df.loc[:... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10018 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10018/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10018/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10018/events | https://github.com/pandas-dev/pandas/issues/10018 | 71,923,352 | MDU6SXNzdWU3MTkyMzM1Mg== | 10,018 | newline defaults for read_csv and write_csv are not consistent | {
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"description": "read_csv, to_csv",
... | open | false | null | [] | null | 12 | 2015-04-29T16:32:10Z | 2021-08-18T03:57:08Z | null | NONE | null | It's possible to write out a CSV file using the default settings (i.e., `line_terminator='\n'` in `DataFrame.to_csv`) that can't be read back in using the default settings (i.e., `lineterminator=None`).
This problem arises when there's a text column that doesn't get quotes around it (e.g., if it has no commas) but h... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10019 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10019/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10019/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10019/events | https://github.com/pandas-dev/pandas/issues/10019 | 71,950,145 | MDU6SXNzdWU3MTk1MDE0NQ== | 10,019 | support for 3d scatter plot if both axes are numerical values | {
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... | closed | false | null | [] | null | 4 | 2015-04-29T18:23:15Z | 2020-01-30T09:38:41Z | 2015-04-29T22:17:58Z | NONE | null | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10020 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10020/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10020/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10020/events | https://github.com/pandas-dev/pandas/issues/10020 | 71,950,465 | MDU6SXNzdWU3MTk1MDQ2NQ== | 10,020 | optional argument to interpolation function for interpolating on new columns or indices | {
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"description": "Arithmet... | open | false | null | [] | null | 2 | 2015-04-29T18:24:21Z | 2019-01-13T00:58:43Z | null | NONE | null | Here is a workaround how to achieve this manually:
```
import pandas as pd
import numpy as np
from numpy.random import rand
dfPP=pd.DataFrame(rand(3,5),columns=rand(5),index=rand(3))
nanarr=np.empty(dfPP.shape[0])
nanarr[:]=np.NAN
new_point=dfPP.columns.values.mean()
dfPP.loc[:,new_point]=nanarr
dfPP.sort(axis=1,inpl... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10021 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10021/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10021/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10021/events | https://github.com/pandas-dev/pandas/pull/10021 | 71,956,165 | MDExOlB1bGxSZXF1ZXN0MzQzOTM2OTA= | 10,021 | ENH: support __radd__ operation on Index | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-04-29T18:49:37Z | 2015-05-08T16:13:11Z | 2015-05-08T13:24:44Z | CONTRIBUTOR | null | closed #10083
Currently the following would raise a `TypeError`:
```
In [1]: import pandas as pd
In [2]: idx = pd.Index(list('abc'))
In [3]: idx + '1'
Out[3]: Index(['a1', 'b1', 'c1'], dtype='object')
In [4]: '1' + idx
---------------------------------------------------------------------------
TypeError ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10022 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10022/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10022/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10022/events | https://github.com/pandas-dev/pandas/issues/10022 | 71,967,445 | MDU6SXNzdWU3MTk2NzQ0NQ== | 10,022 | read_csv(engine='c') can insert spurious rows full of NaNs | {
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This is with git master.
I won't bother to upload the CSV file in question because I think I've tracked down the problem. It seems th... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10023 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10023/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10023/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10023/events | https://github.com/pandas-dev/pandas/pull/10023 | 71,968,212 | MDExOlB1bGxSZXF1ZXN0MzQzOTc5MzY= | 10,023 | read_csv newline fix | {
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"followers_url": "https://api.github.com/users/jr... | 13 | 2015-04-29T19:37:05Z | 2015-05-09T00:42:05Z | 2015-05-08T04:25:52Z | CONTRIBUTOR | null | Slight change to the logic in the `tokenize_delimited()` and `tokenize_delim_customterm()` functions of the C parser.
Fixes #10022.
I believe the new logic is correct, but perhaps someone with more familiarity can double-check.
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https://api.github.com/repos/pandas-dev/pandas/issues/10024 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10024/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10024/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10024/events | https://github.com/pandas-dev/pandas/pull/10024 | 71,984,736 | MDExOlB1bGxSZXF1ZXN0MzQ0MDM3ODM= | 10,024 | Speed up max_len_string_array | {
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``` python
In [5]: x = np.array(['abcd', 'abcde', 'abcdef', 'abcdefg'] * int(1e7), object)
In [2]: f = pd.lib.max_len_string_array
In [6]: %timeit f(x)
1 loops, best of 3: 501 ms per loop
```
After:
``` python
In [1]: x = np.array(['abcd', 'abcde', 'abcdef', 'abcdefg'] * int(1e7), object)
In [2]: f = pd.l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10025 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10025/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10025/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10025/events | https://github.com/pandas-dev/pandas/issues/10025 | 72,042,031 | MDU6SXNzdWU3MjA0MjAzMQ== | 10,025 | BUG: Index constructor does not set name when given a TimedeltaIndex as data | {
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... | closed | false | null | [] | {
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In [46]: tdi = pd.timedelta_range(start=0, periods=4, freq='D')
In [47]: pd.Index(tdi, name='foo').name is None
Out[47]: True
In [48]: pd.Index(tdi.values, name='foo').name is None
Out[48]: False
```
Other index types seem to work fine:
```
In [51]: dti = pd.date_range(start='2000-01-01', periods=4, freq='D')
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https://api.github.com/repos/pandas-dev/pandas/issues/10026 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10026/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10026/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10026/events | https://github.com/pandas-dev/pandas/pull/10026 | 72,070,580 | MDExOlB1bGxSZXF1ZXN0MzQ0MzAzMzQ= | 10,026 | Fix TimedeltaIndex constructor fastpath when name is set | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10027 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10027/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10027/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10027/events | https://github.com/pandas-dev/pandas/pull/10027 | 72,078,477 | MDExOlB1bGxSZXF1ZXN0MzQ0MzIxOTM= | 10,027 | DOC: mention other packages in IO docs (for now, just xray for netCDF) | {
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This would also be a nice place to mention other packages that connect the
pandas DataFrames with other file formats. Right now, the only one I can think
of off-hand is `root_pandas` (#9378, CC @ibab), but I'm sure there are more.
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https://api.github.com/repos/pandas-dev/pandas/issues/10028 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10028/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10028/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10028/events | https://github.com/pandas-dev/pandas/issues/10028 | 72,102,599 | MDU6SXNzdWU3MjEwMjU5OQ== | 10,028 | Pivot_table with categorical data gives ValueError | {
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... | closed | false | null | [] | null | 1 | 2015-04-30T08:49:02Z | 2015-04-30T10:03:27Z | 2015-04-30T10:03:07Z | MEMBER | null | This errors for me on master as well: http://stackoverflow.com/questions/29945342/pandas-error-with-pivot-table-and-categorical-data
```
category1 category2 numeric
0 grey complete 1
1 grey complete 2
2 NaN incomplete 3
3 blue complete 4
```
```
In [13]:... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10029 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10029/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10029/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10029/events | https://github.com/pandas-dev/pandas/issues/10029 | 72,113,478 | MDU6SXNzdWU3MjExMzQ3OA== | 10,029 | pandas.to_datetime silently fails for invalid input string | {
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```
>>> a = pd.to_datetime('1991-02-30')
>>> a
'1991-02-30'
>>> a = pd.to_datetime('1991-02302')
>>> a
'1991-02302'
>>> a = pd.to_datetime('199102302')
>>> a
'199102302'
>>> ... | {
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... | 52 | 2015-04-30T15:24:04Z | 2021-03-16T17:27:00Z | null | NONE | null | A "weights" labeled parameter in the df.mean method would be extremely useful. In numpy this functionality is provided via np.average instead of np.mean which I'm assuming is how similar functionality would be added to pandas.
ex requested feature:
```
> a = np.array([[2,4,6],[8,10,12]])
> w = [.5, 0, .5]
> np_avg = ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10031 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10031/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10031/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10031/events | https://github.com/pandas-dev/pandas/pull/10031 | 72,207,477 | MDExOlB1bGxSZXF1ZXN0MzQ0NzU0OTM= | 10,031 | ENH: Added str.normalize to use unicodedata.normalize | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-04-30T16:12:18Z | 2015-05-07T02:39:22Z | 2015-05-06T10:40:18Z | MEMBER | null | Derived from #9111. Can this be considered in v0.16.1? Otherwise will change the milestone.
> [`unicodedata.normalize`](https://docs.python.org/2/library/unicodedata.html?highlight=unicodedata#unicodedata.normalize) is quite useful to standardize multi-bytes characters. I think it is nice if `StringMethods.normalize`... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10032 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10032/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10032/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10032/events | https://github.com/pandas-dev/pandas/pull/10032 | 72,214,291 | MDExOlB1bGxSZXF1ZXN0MzQ0Nzc0NzI= | 10,032 | pd.lib.infer_dtype infers bytes in Python3 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10033 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10033/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10033/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10033/events | https://github.com/pandas-dev/pandas/issues/10033 | 72,232,489 | MDU6SXNzdWU3MjIzMjQ4OQ== | 10,033 | Index constructor should always make a shallow copy, never returning the same object | {
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as discussed in #10026.
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https://api.github.com/repos/pandas-dev/pandas/issues/10034 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10034/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10034/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10034/events | https://github.com/pandas-dev/pandas/issues/10034 | 72,247,663 | MDU6SXNzdWU3MjI0NzY2Mw== | 10,034 | Box Plot X Axis Labels | {
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... | open | false | null | [] | null | 2 | 2015-04-30T18:46:18Z | 2021-04-18T06:40:20Z | null | NONE | null | It would be nice if there was an option to have box plot X axis labels match line plot's X axis labels. Specifically, when plotting a time series, box plot labels each tick whereas line plot's labels are more spread apart.
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https://api.github.com/repos/pandas-dev/pandas/issues/10035 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10035/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10035/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10035/events | https://github.com/pandas-dev/pandas/pull/10035 | 72,254,844 | MDExOlB1bGxSZXF1ZXN0MzQ0OTEyODU= | 10,035 | DOC: added fredapi module to ecosystem list | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-30T19:10:57Z | 2015-04-30T22:10:15Z | 2015-04-30T22:00:29Z | CONTRIBUTOR | null | kind of a shameless plug here, but would love to have my pandas-based project on this page :)
please let me know what you think. Thanks.
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https://api.github.com/repos/pandas-dev/pandas/issues/10036 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10036/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10036/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10036/events | https://github.com/pandas-dev/pandas/pull/10036 | 72,258,301 | MDExOlB1bGxSZXF1ZXN0MzQ0OTI0NzU= | 10,036 | DOC: use _shared_docs for fillna methods | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-30T19:25:35Z | 2015-05-05T00:08:19Z | 2015-05-04T21:35:28Z | CONTRIBUTOR | null | currently the docstring for `DataFrame.fillna` is shown for `Series.fillna` and `Panel.fillna`. http://pandas.pydata.org/pandas-docs/version/0.16.0/generated/pandas.Panel.fillna.html?highlight=fillna#pandas.Panel.fillna
this is not accurate in particular for the `axis` values. This PR makes it such that they share th... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10037 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10037/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10037/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10037/events | https://github.com/pandas-dev/pandas/issues/10037 | 72,286,820 | MDU6SXNzdWU3MjI4NjgyMA== | 10,037 | 2 spaces in csv file between date and time | {
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df.to_csv(path_or_buf=f, sep=' ', header=False,
index=True, mode='a', quoting=QUOTE_NONE, escapechar=' ',
date_format='%m/%d/%Y %H:%M:%S')
```
generates 2 spaces in csv file between date and time. It should only be one space since sep=' '.
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https://api.github.com/repos/pandas-dev/pandas/issues/10038 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10038/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10038/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10038/events | https://github.com/pandas-dev/pandas/issues/10038 | 72,300,419 | MDU6SXNzdWU3MjMwMDQxOQ== | 10,038 | No deprecation warning raised for index - list operation | {
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```
idx = pd.Index(['a', 'b', 'c', 'd'])
idx - ['a', 'd']
idx - pd.Index(['a', 'd'])
```
gives:
```
In [1]: idx = pd.Index(['a', 'b', 'c', 'd'])
In [2]: idx - ['a', 'd']
Out[2]: Index([u'b', u'c'], dtype='object')
In [3]: idx - pd.Index(['a', 'd'])
c:\users\vdbosscj\scipy\pandas-joris\pandas\core\inde... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-04-30T23:02:08Z | 2015-05-04T12:45:51Z | 2015-05-04T12:45:51Z | MEMBER | null | Related with the issue I just opened (#10038), I relooked at the set operation deprecation issues we had before (xref #8227, #9095, #9630).
To make a summary:
- in 0.15.0 we deprecated set operations, only for new TimedeltaIndex it is already numeric operation
- in 0.15.1, for numeric indexes this was by accident conv... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10040 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10040/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10040/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10040/events | https://github.com/pandas-dev/pandas/issues/10040 | 72,445,433 | MDU6SXNzdWU3MjQ0NTQzMw== | 10,040 | Median returns odd value when applied to timedeltas | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-05-01T14:39:15Z | 2015-05-07T20:53:20Z | 2015-05-07T20:53:20Z | NONE | null | ``` python
from pandas import DataFrame
from numpy import datetime64
data = ['2015-02-03', '2015-02-07']
data = DataFrame(data, dtype=datetime64)
data.diff().median()
```
This code returns
``` python
0 -53374 days +00:06:21.572612
dtype: timedelta64[ns]
```
while I would expect it to return the same as data.diff(... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-05-01T15:59:58Z | 2016-03-06T20:44:23Z | 2016-03-06T20:44:23Z | CONTRIBUTOR | null | Looks like a bug: When passing a YYYYMMDDTHHMMSS.f string to `pd.Timestamp`, the resolution seems limited to micro- rather than nano-seconds:
``` python
>>> pd.Timestamp('20130101T000000.000001+0000')
Timestamp('2013-01-01 00:00:00.000001+0000', tz='UTC')
>>> pd.Timestamp('20130101T000000.0000001+0000')
Timestamp('20... | {
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closes #10039
- `CategoricalIndex` now raise `TypeError` on ops like : `idx - idx` (we are moving all non-numeric Indexes to this, but just deprecated for now on existing index types)
- Index ops with lists will now show the same warning (e.g. `idx - ['a','b']`)
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We call `df.iloc[indices]` and that breaks with a read-only dataframe. I feel that it shouldn't though, as it is not writing.
Minimal r... | {
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@sinhrks @jreback
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```
easy_install -U Cython
git clone git://github.com/pydata/pandas.git
python setup.py install
```
The generated code for the line from `pandas/algos.pyx`
``` python
cdef np.float16_... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10048 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10048/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10048/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10048/events | https://github.com/pandas-dev/pandas/issues/10048 | 72,592,456 | MDU6SXNzdWU3MjU5MjQ1Ng== | 10,048 | Strange behaviour when setting columns to a DataFrame | {
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... | 2 | 2015-05-02T05:56:09Z | 2018-11-12T23:18:17Z | 2018-11-12T23:18:17Z | CONTRIBUTOR | null | Not sure if this is a bug, but seems like weird behaviour.... it came up on [SO](http://stackoverflow.com/q/29997115/1240268).
```
In [11]: d = {"a": pd.DataFrame([[1], [2]], index=[0, 2], columns=['Z']),
"b": pd.DataFrame([[3], [4]], index=[0, 2], columns=['Z'])}
In [12]: pd.concat(d).unstack(0) # exp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10049 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10049/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10049/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10049/events | https://github.com/pandas-dev/pandas/issues/10049 | 72,622,508 | MDU6SXNzdWU3MjYyMjUwOA== | 10,049 | Strange behavior of to_dict() inside apply | {
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I don't know if that's a misunderstanding from my side but
```
import pandas as pd
df_task = pd.DataFrame({
"Name": ["Saint Auban", "Go", "Coupe S", "3 Eveches", "DORMILLOUSE FORT", "Saint Auban"],
"Lat": [44.054901123046875, 44.015087127685547, 44.053600311279297, 44.288883209228516, 44.41444778442382... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10050 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10050/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10050/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10050/events | https://github.com/pandas-dev/pandas/issues/10050 | 72,651,783 | MDU6SXNzdWU3MjY1MTc4Mw== | 10,050 | Type error on using datetime64's microseconds in datetime.timedelta | {
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... | 2 | 2015-05-02T14:16:40Z | 2015-05-12T19:58:49Z | 2015-05-12T19:58:49Z | NONE | null | Using Pandas' datetime64 dtype to convert to a datetime.timedelta object results in this type error:
``` python
TypeError: unsupported type for timedelta microseconds component: numpy.int32
```
Reproduce:
``` python
# set up a dataframe with a datetime value in it
from datetime import datetime
import pandas as pd
df... | {
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I guess PeriodIndex don't show up in the API docs at all. Not sure if I'll get to any more.
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note that this handles both py2 and py3 as the signature for `str.translate` has changed from py2 to py3
@sinhrks @jreback
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https://api.github.com/repos/pandas-dev/pandas/issues/10053 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10053/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10053/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10053/events | https://github.com/pandas-dev/pandas/pull/10053 | 72,824,198 | MDExOlB1bGxSZXF1ZXN0MzQ2MDMxMTI= | 10,053 | DOC: Add infer frequency to docs | {
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I set out looking for a feature like this, searching "guess frequency", "auto detect frequency".
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closes #8790
Adds a new column (`_merge`) to DataFrames being merged that takes on a value of `1` if observation was only in left df, `2` if only in right df, and `3` if in both. Designed to address #7412 and #8790.
**Update:** new column now categorical with more informative labels of `left_only`, `righ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10055 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10055/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10055/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10055/events | https://github.com/pandas-dev/pandas/pull/10055 | 72,908,707 | MDExOlB1bGxSZXF1ZXN0MzQ2MTM0ODI= | 10,055 | BUG: read_hdf modifying passed columns list (GH7212) | {
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... | 10 | 2015-05-04T03:07:47Z | 2015-05-26T04:11:28Z | 2015-05-26T04:06:27Z | CONTRIBUTOR | null | Closes #7212. If this object is a list, make a copy and then pass to process_axes - otherwise, just pass the object directly (in this case it is most likely none).
A test for this behavior seems complex and somewhat contrived when compared with what exists in test_pytables.py, so I didn't add one --- let me know any t... | {
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"description": "Concat, ... | closed | false | null | [] | null | 11 | 2015-05-04T16:30:31Z | 2019-07-12T14:38:04Z | 2019-07-12T14:38:04Z | NONE | null | When passing a list OrderedDict objects to `pd.DataFrame`, the ordering of the columns is not kept:
``` python
od = OrderedDict([('Z', 5), ('xx', 8), ('uno', 2), ('etc', 1), ('j', 76), ('e', 7)])
l = [od]*4
pd.DataFrame(l).columns
#Out[23]: Index(['Z', 'e', 'etc', 'j', 'uno', 'xx'], dtype='object')
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10057 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10057/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10057/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10057/events | https://github.com/pandas-dev/pandas/pull/10057 | 73,134,157 | MDExOlB1bGxSZXF1ZXN0MzQ2Nzc2MDI= | 10,057 | ENH: Series.resample performance with datetime64[ns] #7754 | {
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"description": "Memory or... | closed | false | null | [] | {
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"followers_url": "https://api.github.... | 8 | 2015-05-04T21:34:41Z | 2015-06-02T19:26:59Z | 2015-05-12T13:06:06Z | CONTRIBUTOR | null | It fixes the performance drop.
See %timeit result [here](http://nbviewer.ipython.org/gist/scari/1173a9519d8b89000c08).
closes #7754
@jreback Would you review this PR? Thanks!
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https://api.github.com/repos/pandas-dev/pandas/issues/10058 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10058/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10058/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10058/events | https://github.com/pandas-dev/pandas/pull/10058 | 73,239,009 | MDExOlB1bGxSZXF1ZXN0MzQ3MDE5MjE= | 10,058 | BUG: Panel.from_dict does not set dtype when specified | {
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"followers_url": "https://api.github.... | 4 | 2015-05-05T07:45:14Z | 2015-06-02T19:26:59Z | 2015-05-18T11:45:06Z | CONTRIBUTOR | null | currently `Panel.from_dict` is just ignoring the `dtype` argument:
```
In [1]: import pandas as pd
In [2]: import numpy as np
In [3]: df = pd.DataFrame(np.array(range(6)).reshape(3, 2))
In [4]: pa = pd.Panel.from_dict({'a': df, 'b': df}, dtype=float)
In [5]: pa.dtypes
Out[5]:
a int64
b int64
dtype: object
```
t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10059 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10059/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10059/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10059/events | https://github.com/pandas-dev/pandas/issues/10059 | 73,240,913 | MDU6SXNzdWU3MzI0MDkxMw== | 10,059 | Pandas and h5py load the same data (ndarray) differently: hvl_t support. | {
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] | closed | false | null | [] | null | 6 | 2015-05-05T07:56:52Z | 2015-05-05T12:07:25Z | 2015-05-05T10:30:36Z | NONE | null | Based off this [question](http://stackoverflow.com/q/29986826/232794). In fact more or less copied and pasted :)
I have a file in HDF5 format. It was created using the HDF5's C++ API using these:
``` c++
struct SignalDefH5
{
char id [128];
char name [ 64];
char units[ 16];
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10060 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10060/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10060/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10060/events | https://github.com/pandas-dev/pandas/issues/10060 | 73,273,276 | MDU6SXNzdWU3MzI3MzI3Ng== | 10,060 | Problem constructing Series from dict with datetime.date in level of MultiIndex | {
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"descript... | closed | false | null | [] | null | 4 | 2015-05-05T10:25:51Z | 2015-05-05T11:19:50Z | 2015-05-05T10:43:02Z | NONE | null | When calling the Series constructor on a dict with tuple keys containing a datetime.date object
the values are converted to NaNs as this example demonstrates:
```
In [52]:
pd.Series({(1, datetime.date(2012, 1, 1)): 1,
(2, datetime.date(2012, 1, 2)): 2})
Out[52]:
1 2012-01-01 NaN
2 2012-01-02 NaN
``... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10061 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10061/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10061/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10061/events | https://github.com/pandas-dev/pandas/pull/10061 | 73,290,780 | MDExOlB1bGxSZXF1ZXN0MzQ3MTU5NDI= | 10,061 | DOC: add warning for datareader changes in 0.17.0 (GH10004) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10062 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10062/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10062/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10062/events | https://github.com/pandas-dev/pandas/issues/10062 | 73,306,907 | MDU6SXNzdWU3MzMwNjkwNw== | 10,062 | rpy2 / R interface (v0.16.0) | {
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Using the last pandas version, the command : "import pandas.rpy.common as com"
produces the following warning :
"The pandas.rpy module is deprecated and will be removed in a future version. We refer to external packages like rpy2, found here: http://rpy.sourceforge.net "like rpy2, found here: ttp://rpy.sourcef... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10063 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10063/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10063/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10063/events | https://github.com/pandas-dev/pandas/issues/10063 | 73,313,216 | MDU6SXNzdWU3MzMxMzIxNg== | 10,063 | Grouped timeseries operations fail on multi-indexed DataFrames | {
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``` python
import pandas as pd
import pandas.io.data as web
# Get some market data
df = web.DataReader(['AAPL', 'GOOG'], 'yahoo', pd.Timestamp('2013'), pd.Timestamp('2014')).to_frame()
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https://api.github.com/repos/pandas-dev/pandas/issues/10064 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10064/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10064/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10064/events | https://github.com/pandas-dev/pandas/pull/10064 | 73,332,217 | MDExOlB1bGxSZXF1ZXN0MzQ3MzAyMzM= | 10,064 | BUG: Bug in grouping with multiple pd.Grouper where one is non-time based (GH10063) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10066 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10066/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10066/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10066/events | https://github.com/pandas-dev/pandas/pull/10066 | 73,464,688 | MDExOlB1bGxSZXF1ZXN0MzQ3Nzg0NjA= | 10,066 | DOC: remove use of deprecated index set operation (follow-up GH10042) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10067 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10067/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10067/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10067/events | https://github.com/pandas-dev/pandas/pull/10067 | 73,498,417 | MDExOlB1bGxSZXF1ZXN0MzQ3ODU4OTk= | 10,067 | BUG: Series.align resets name when fill_value is specified | {
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"followers_url": "https://api.github.... | 3 | 2015-05-06T03:09:14Z | 2015-06-02T19:26:59Z | 2015-05-30T13:41:38Z | MEMBER | null | ```
import pandas.util.testing as tm
ts = tm.makeTimeSeries()
ts.name = 'ts'
a, b = ts[2:], ts[:5]
# OK (names are preserved)
aa, ba = a.align(b)
aa.name
# ts
ba.name
# ts
# NG, specifying fill_value resets names
aa, ba = a.align(b, fill_value=-1)
aa.name
# None
ba.name
# None
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10068 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10068/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10068/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10068/events | https://github.com/pandas-dev/pandas/issues/10068 | 73,518,989 | MDU6SXNzdWU3MzUxODk4OQ== | 10,068 | BUG/API: Series arithmetic ops inconsistently hold names | {
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```
import pandas as pd
s1 = pd.Series([1, 2, 3], name='a')
s2 = pd.Series([3, 4, 5], name='b')
(s1 + s2).name
# None
s1.add(s2).name
# a
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10070 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10070/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10070/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10070/events | https://github.com/pandas-dev/pandas/pull/10070 | 73,677,577 | MDExOlB1bGxSZXF1ZXN0MzQ4Mzc0MTk= | 10,070 | BUG make take_nd support readonly arrays | {
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- `copy()` cannot be accessed from python, one currently needs to re-implement `copy()` if one wants to duplicate a `BlockPlacement` instance
- `copy()` tries to infer a slice for any array contained in the `BlockPlacement`.
- After `copy()` pa... | {
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"... | closed | false | null | [] | null | 3 | 2015-05-07T11:19:02Z | 2015-06-02T10:53:55Z | 2015-06-02T10:53:55Z | NONE | null | closes #9266
np.uin8 should be np.uint8
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- Fixed broken link
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https://api.github.com/repos/pandas-dev/pandas/issues/10077 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10077/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10077/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10077/events | https://github.com/pandas-dev/pandas/pull/10077 | 74,075,357 | MDExOlB1bGxSZXF1ZXN0MzQ5NDE4MzA= | 10,077 | Corrected typo in Grammar of Graphics | {
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```
from pandas import Series, DataFrame, Timestamp
tdf = DataFrame({'day': {0: Timestamp('2015-02-24 00:00:00'), 1: Timestamp('2015-02-24 00:00:00'),... | {
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```
trains = np.arange(100)
tresholds = [10, 20, 30, 40, 50, 60]
tuples = []
for i in trains:
for j in tresholds:
tuples.append((i, j))
index = pd.MultiIndex.from_tuples(tuples, names=['trains'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10080 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10080/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10080/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10080/events | https://github.com/pandas-dev/pandas/pull/10080 | 74,132,501 | MDExOlB1bGxSZXF1ZXN0MzQ5NTk4OTc= | 10,080 | Fix for GH9992 - use create_tempfile to remove permission-related errors when running tests | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-05-07T21:24:03Z | 2015-05-08T13:19:38Z | 2015-05-08T13:19:38Z | CONTRIBUTOR | null | Fixes #9992.
I wanted to take a stab at developing pandas. I am a novice at both git/github and I hope I did the merge and PR correctly.
@jreback, please let me know if there is anything I can fix.
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on big enough strings this might be quite useful for a number of string ops.
```
import pandas as pd
import random
import numpy as np
from StringIO import StringIO
def make_ip():
return '.'... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-05-08T02:05:11Z | 2015-05-08T16:12:06Z | 2015-05-08T13:45:18Z | CONTRIBUTOR | null | 1. currently `Series.shift()` and `DataFrame.shift()` are both missing `axis` information in the docstring.
2. comment in `timeseries.rst` about shifting only possible along `index` or `major_axis` is not true anymore
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-05-08T04:46:34Z | 2015-05-08T19:16:35Z | 2015-05-08T13:25:08Z | MEMBER | null | #### Series (OK)
```
s = pd.Series(['A', 'B'])
'x' + s
#0 xA
#1 xB
# dtype: object
s + 'y'
#0 Ay
#1 By
# dtype: object
```
#### Index (NG)
```
idx = pd.Index(['A', 'B'])
# NG
'x' + idx
# Index([u'Ax', u'Bx'], dtype='object')
# OK
idx + 'y'
# Index([u'Ay', u'By'], dtype='object')
```
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... | 1 | 2015-05-08T15:40:56Z | 2017-10-08T16:31:13Z | 2017-10-08T16:31:08Z | CONTRIBUTOR | null | so it appears that [9] is wrong, should be consistent with [7],[8]
```
In [1]: index = date_range('20130101',freq='2D',periods=6)
In [2]: df = DataFrame(np.arange(20).reshape(5,4),columns=list('ABCD'),index=index.take([0,1,2,3,4]))
In [3]: df.resample('2D',how='max')
Out[3]:
A B C D
2013-01-01 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10085 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10085/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10085/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10085/events | https://github.com/pandas-dev/pandas/pull/10085 | 74,495,777 | MDExOlB1bGxSZXF1ZXN0MzUwNDY5MTY= | 10,085 | DEPR: Deprecate str.split return_type | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-05-08T21:07:34Z | 2015-05-09T21:15:32Z | 2015-05-09T15:34:05Z | MEMBER | null | Closes #9847, Closes #9870. Default value is `expand=False` to be compat with`return_type='series'`. May better to change the default to True in future (and show warning about it)?
CC @jreback @jorisvandenbossche @sreejata
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This is essentially just calling `.format()` on a datetimelike lindex (which handles `NaT` and such)
```
In [1]: dates = pd.to_datetime(pd.Series(['20010101', '20010331']), format = '%Y%m%d')
In [2]: dates
Out[2]:
0 2001-01-01
1 2001-03-31
dtype: datetime64[ns]
In ... | {
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"followers_url": "https://api.github.... | 2 | 2015-05-08T23:13:05Z | 2015-06-02T19:25:20Z | 2015-05-12T10:47:23Z | CONTRIBUTOR | null | Categorical Series have a special repr that looks at display.width, which can be None if following the Options and Settings docs. Unlike Python 2, in Python 3 an integer vs None comparison throws an exception.
(on current master, and has been true for several releases now)
``` python
Python 3.4.0 (default, Apr 11 201... | {
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] | closed | false | null | [] | null | 1 | 2015-05-09T03:22:04Z | 2015-05-09T15:25:54Z | 2015-05-09T15:25:46Z | NONE | null | - Added yahoo-actions data_source to DataReader;
- Added get_data_yahoo_actions that returns a DataFrame containing
DIVIDEND and SPLIT corporate actions fetched from Yahoo! Finance;
- Added unit tests;
- Added documentation example.
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-05-09T04:42:15Z | 2015-11-13T16:05:41Z | 2015-11-13T16:05:41Z | MEMBER | null | Related to #6194. There seems no direct way to replace `NaN`s in `Index`?
I think a point is what types are acceptable via `value`.
- scalar: OK
- dict: NG (or accept {iloc : value} dict?)
- Series : NG
- DataFrame : NG
- http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.fillna.html
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"followers_url": "https://api.github.... | 12 | 2015-05-09T05:21:22Z | 2015-06-05T16:54:19Z | 2015-06-05T16:54:04Z | CONTRIBUTOR | null | Closes #10081.
This simply removes the unnecessary `Series()` in the creation of the DataFrame for the split values in `str_split`. It vastly improves performance (20ms vs 3s for a series of 20,000 strings as a test) while not changing current behavior.
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https://api.github.com/repos/pandas-dev/pandas/issues/10092 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10092/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10092/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10092/events | https://github.com/pandas-dev/pandas/pull/10092 | 74,742,935 | MDExOlB1bGxSZXF1ZXN0MzUwNzE3OTQ= | 10,092 | BUG: Series.fillna() raises if given a numerically convertible string | {
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I think it'd be good to patch this bug. @jreback please let me know which release this should go to and I can add a release note. Thanks.
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The docstring of `DataFrame.sub` states `Binary operator sub`, so if you don't directly see the link with "subtraction", this is not very clear
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The ones that changed the most are the datetime-like. A search for `<class 'pandas.tseries.period.PeriodIndex'>` and alike can help there.
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- also splitting the attributes part over multiple lines if this is very long
- for truncated output: now hard-code at 10 elements, but this could maybe also be 1 line? (and possibly with a minimum number of elements for longer strings) Because now, small integers don't fill the full line with 10 ele... | {
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Also added `daysinmonth` and `dayofweek` properties to `NaT` and perform tests.
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closes #9382
Followup for #9484
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column types
closes #9057
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``` python
grouped = df.groupby('somekey')
dfAggregated = grouped.agg([np.mean, np.std])
```
That works well, but sometimes (all the time, actually) I would also like to be able to us... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10102 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10102/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10102/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10102/events | https://github.com/pandas-dev/pandas/issues/10102 | 75,222,584 | MDU6SXNzdWU3NTIyMjU4NA== | 10,102 | BUG: Different timezones for DatetimeIndex versus elements of DatetimeIndex | {
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I've noticed an inconsistency. The following `DatetimeIndex` object reports a different timezone compared to its elements:
``` python
In [1]: import pandas as pd
In [2]: idx = pd.date_range("2015-01-01", "2015-01-03", freq="D", tz="US/Eastern")
In [3]: idx.tz
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