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https://api.github.com/repos/pandas-dev/pandas/issues/10903 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10903/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10903/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10903/events | https://github.com/pandas-dev/pandas/issues/10903 | 102,992,544 | MDU6SXNzdWUxMDI5OTI1NDQ= | 10,903 | Supporting shifting by business days in DateOffset's constructor | {
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"descript... | closed | false | null | [] | null | 1 | 2015-08-25T10:06:07Z | 2015-08-26T00:51:11Z | 2015-08-26T00:51:01Z | NONE | null | Now it is not possible to create a `DateOffset` which would incorporate shifting by a certain number of _business_ days in addition to any other offset rules. In my view, it would be useful to include a `bdays` argument which would act similarly to `days` parameter.
NOTE: It is also impossible to create such a `DateOf... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10904 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10904/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10904/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10904/events | https://github.com/pandas-dev/pandas/issues/10904 | 103,130,382 | MDU6SXNzdWUxMDMxMzAzODI= | 10,904 | pandas.Series.tolist should convert Series contents from numpy datatypes to native Python datatypes | {
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numpy.array.tolist converts all of the array'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10905 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10905/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10905/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10905/events | https://github.com/pandas-dev/pandas/issues/10905 | 103,265,528 | MDU6SXNzdWUxMDMyNjU1Mjg= | 10,905 | ascending/descending on multiple index levels with `sortlevel` | {
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"de... | closed | false | null | [] | null | 2 | 2015-08-26T13:11:00Z | 2015-08-26T13:19:52Z | 2015-08-26T13:13:50Z | CONTRIBUTOR | null | In [#928](https://github.com/pydata/pandas/issues/928), support for list of boolean/binary values was added to control ascending/descending when sorting on multiple columns.
This doesn't work with `sortlevel`, but nor does it raise an error. This seems potentially "dangerous" to me.
```
In [23]: levels = list('ABC')
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10906 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10906/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10906/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10906/events | https://github.com/pandas-dev/pandas/issues/10906 | 103,270,478 | MDU6SXNzdWUxMDMyNzA0Nzg= | 10,906 | TST: fix pythonxy changed links in test_html.py | {
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but would like to replace these with something new testing the same functionaility.
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https://api.github.com/repos/pandas-dev/pandas/issues/10907 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10907/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10907/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10907/events | https://github.com/pandas-dev/pandas/issues/10907 | 103,281,892 | MDU6SXNzdWUxMDMyODE4OTI= | 10,907 | diff(axis=1) after insert results in unexpected NaN column | {
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``` python
>>> import pandas as pd
>>> df = pd.DataFrame({'y': pd.Series([2]), 'z': pd.Series([3])})
>>> df
y z
0 2 3
>>> df.insert(0, 'x', 1)
>>> df.diff(axis=1)
x y z
0 NaN NaN 1
```
The following workaround produces the expected result:
`... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10908 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10908/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10908/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10908/events | https://github.com/pandas-dev/pandas/pull/10908 | 103,354,277 | MDExOlB1bGxSZXF1ZXN0NDM0NDU5ODM= | 10,908 | API: Closes #7879: (drops not nan in panel.to_frame() by default) | {
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Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
groupby_ngroups_10000_value_counts | 11.4880 | 6698.5627 | 0.00... | {
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https://github.com/pydata/pandas/issues/10898
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Note: I use "" in the output even though that isn't shown, if I didn't the markup would become messed ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10912 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10912/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10912/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10912/events | https://github.com/pandas-dev/pandas/issues/10912 | 103,537,160 | MDU6SXNzdWUxMDM1MzcxNjA= | 10,912 | inplace operation for Series causes reappearance popped column | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-08-27T15:36:23Z | 2015-08-28T23:28:06Z | 2015-08-28T23:28:06Z | NONE | null | Hi, Thanks for all efforts for the great tool!
I've found a strange behavior like this...
``` python
In [1]: a = pd.DataFrame([[1,2,3],[4,5,6]], columns=['A','B','C'], index=['X','Y'])
In [2]: a
Out[2]:
A B C
X 1 2 3
Y 4 5 6
In [3]: b = a.pop('B')
In [4]: a
Out[4]:
A C
X 1 3
Y 4 6
In [5]: b
O... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10913 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10913/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10913/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10913/events | https://github.com/pandas-dev/pandas/pull/10913 | 103,574,814 | MDExOlB1bGxSZXF1ZXN0NDM1NTQ2ODY= | 10,913 | ERR between_time and empty pandas.Series | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10914 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10914/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10914/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10914/events | https://github.com/pandas-dev/pandas/issues/10914 | 103,595,900 | MDU6SXNzdWUxMDM1OTU5MDA= | 10,914 | Series.resample fails with how='nunique' | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-08-27T21:10:48Z | 2015-08-28T12:24:43Z | 2015-08-28T12:22:23Z | CONTRIBUTOR | null | Works on 0.16.2, fails on git master.
``` python
import pandas as pd
import numpy as np
index = pd.date_range(start='20120102', periods=24*60*3, freq='T').values
index = index[::2]
s = pd.Series(np.arange(len(index), dtype='f8'), index=pd.Index(index))
expected = s.resample('30T', how='nunique')
```
Traceback:
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https://api.github.com/repos/pandas-dev/pandas/issues/10915 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10915/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10915/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10915/events | https://github.com/pandas-dev/pandas/issues/10915 | 103,629,381 | MDU6SXNzdWUxMDM2MjkzODE= | 10,915 | execute str.upper() on multi-type data type column will change number data to NA | {
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"color": "0052cc"... | closed | false | null | [] | null | 6 | 2015-08-28T01:51:58Z | 2015-08-29T02:05:06Z | 2015-08-29T02:04:51Z | NONE | null | Version : 0.16.2
OS : Mac
What I think is when use .str need first change compulsory change dtype to str, but in my situation, pandas change my number data to NA.
And when I use .astype('str') first, I got the output I need, but I think this may may somebody confused and make some mistake without .astype('str') .
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https://api.github.com/repos/pandas-dev/pandas/issues/10916 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10916/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10916/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10916/events | https://github.com/pandas-dev/pandas/pull/10916 | 103,638,646 | MDExOlB1bGxSZXF1ZXN0NDM1ODk1MTI= | 10,916 | Revert "Merge pull request #10727 from jorisvandenbossche/sphinx-traceback | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-08-28T03:06:21Z | 2015-08-29T00:17:38Z | 2015-08-28T03:08:45Z | CONTRIBUTOR | null | This reverts commit d40627398cf78347f5a49fa060bad1c40514908a, reversing
changes made to bd804aa75ac9b7a55c00101dbea01571cbdfd068.
@jorisvandenbossche reverting so that the docs build
pls rebsumit when you can
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master
```
In [1]: np.random.seed(1234)
In [2]: df = DataFrame({'A' : np.random.randint(0,10000,size=1000000)})
In [3]: %timeit df.drop_duplicates()
10 loops, best of 3: 36.9 ms per loop
```
PR
```
In [2]: df = DataFrame({'A' : np.random.rand... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10918 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10918/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10918/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10918/events | https://github.com/pandas-dev/pandas/pull/10918 | 103,639,946 | MDExOlB1bGxSZXF1ZXN0NDM1OTAyMTA= | 10,918 | BUG: closes bug in BinGrouper.group_info where returned values are not compatible with base class | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10919 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10919/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10919/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10919/events | https://github.com/pandas-dev/pandas/issues/10919 | 103,707,656 | MDU6SXNzdWUxMDM3MDc2NTY= | 10,919 | d | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10920 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10920/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10920/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10920/events | https://github.com/pandas-dev/pandas/pull/10920 | 103,719,946 | MDExOlB1bGxSZXF1ZXN0NDM2MjgwODg= | 10,920 | DEPR: Series.nlargest/nsmallest take_last. | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-08-28T13:34:45Z | 2015-08-29T00:10:30Z | 2015-08-29T00:03:43Z | MEMBER | null | Closes #10792.
Because using `deprecate_kwargs` hides original impl, used ugly workaround for `GroupBy`...
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https://api.github.com/repos/pandas-dev/pandas/issues/10921 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10921/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10921/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10921/events | https://github.com/pandas-dev/pandas/issues/10921 | 103,757,868 | MDU6SXNzdWUxMDM3NTc4Njg= | 10,921 | Complex number operation on DataFrame | {
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"descript... | closed | false | null | [] | null | 7 | 2015-08-28T17:09:50Z | 2015-09-02T10:39:19Z | 2015-08-28T17:57:15Z | NONE | null | Hello,
Would it be possible to add complex function operation on DataFrame ?
Function like np.sin, np.abs works properly on Pandas DataFrame containing complex numbers and
returns a DataFrame (as expected).
However, np.real, np.imag, np.angle operation return an numpy.ndarray array instead of DataFrame...
``` pytho... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10922 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10922/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10922/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10922/events | https://github.com/pandas-dev/pandas/pull/10922 | 103,773,266 | MDExOlB1bGxSZXF1ZXN0NDM2NTgxMjQ= | 10,922 | BUG: Bug in clearing the cache on DataFrame.pop and a subsequent inplace op #10912 | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-08-28T18:36:05Z | 2015-08-28T23:28:06Z | 2015-08-28T23:28:06Z | CONTRIBUTOR | null | closes #10912
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https://api.github.com/repos/pandas-dev/pandas/issues/10923 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10923/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10923/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10923/events | https://github.com/pandas-dev/pandas/issues/10923 | 103,777,325 | MDU6SXNzdWUxMDM3NzczMjU= | 10,923 | groupby.transform inconsistent behavior when grouping by columns containing NaN | {
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... | closed | false | null | [] | null | 4 | 2015-08-28T19:03:58Z | 2017-07-26T19:57:19Z | 2015-08-28T20:18:43Z | NONE | null | This is similar to #9697, which was fixed in 0.16.1. I give a (very) slightly modified example here to show some related behavior which is at least inconsistent and should probably be handled cleanly.
It's not entirely clear to me what the desired behavior is in this case; it's possible that transform should not work ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10924 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10924/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10924/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10924/events | https://github.com/pandas-dev/pandas/issues/10924 | 103,789,722 | MDU6SXNzdWUxMDM3ODk3MjI= | 10,924 | Series.dot returns undocumented ndarray type | {
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"descript... | closed | false | null | [] | null | 4 | 2015-08-28T20:23:45Z | 2015-08-28T21:52:58Z | 2015-08-28T20:33:58Z | CONTRIBUTOR | null | According to the documentation `pandas.Series.dot` returns a `pandas.Series` or a scalar value. Certainly, the output type is depending on the type and dimension of the first positional argument of the `pandas.Series.dot` function. The following example outputs a value of type `numpy.ndarray` using pandas (0.16.2):
``... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10925 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10925/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10925/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10925/events | https://github.com/pandas-dev/pandas/pull/10925 | 103,816,037 | MDExOlB1bGxSZXF1ZXN0NDM2ODM4NzM= | 10,925 | Revert "Revert "Merge pull request #10727 from jorisvandenbossche/sph… | {
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... | 8 | 2015-08-29T00:18:09Z | 2016-02-12T17:40:30Z | 2016-01-07T01:35:44Z | MEMBER | null | Reverts pydata/pandas#10916
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https://api.github.com/repos/pandas-dev/pandas/issues/10926 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10926/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10926/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10926/events | https://github.com/pandas-dev/pandas/pull/10926 | 103,821,270 | MDExOlB1bGxSZXF1ZXN0NDM2ODY1NTI= | 10,926 | BUG: Bug in incorrection computation of .mean() on timedelta64[ns] because of overflow #9442 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10927 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10927/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10927/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10927/events | https://github.com/pandas-dev/pandas/pull/10927 | 103,833,529 | MDExOlB1bGxSZXF1ZXN0NDM2ODk5MTM= | 10,927 | PERF: GH10213 kth_smallest GIL release | {
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```
import timeit
setup_seq = '''
import pandas
import numpy
numpy.random.seed(1234)
x = numpy.random.randn(10000000)
a = x.copy()
b = x.copy()
def f(s):
pandas.algos.kth_smallest(s, 500000)
def seq():
f(a)
f(b)
'''
setup_parallel = '''
import pandas
import numpy
import threadi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10928 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10928/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10928/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10928/events | https://github.com/pandas-dev/pandas/pull/10928 | 103,839,902 | MDExOlB1bGxSZXF1ZXN0NDM2OTEyODU= | 10,928 | Updates for asv suite | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2015-08-29T08:40:42Z | 2015-09-01T19:25:40Z | 2015-08-29T22:42:36Z | CONTRIBUTOR | null | @jorisvandenbossche As you requested in #10849, here's the current state of affairs. The changes are:
- First patch:
- Fix the translation script so that functions defined in the vbench `setup` string get defined as classmethods and called appropriately. This fixes most failing tests.
- Some backwards-compatibility... | {
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Closes https://github.com/pydata/pandas/issues/10748
I have to run for now, but will pick this up later today.
I think I'm missing a few in the tests, since the warning is showing up in a bunch of places (there's a way to convert those to errors for testing right?)
I had to refactor a couple function that ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10931 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10931/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10931/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10931/events | https://github.com/pandas-dev/pandas/pull/10931 | 103,868,020 | MDExOlB1bGxSZXF1ZXN0NDM2OTkxOTc= | 10,931 | Add tests to ensure sort preserved by groupby, add docs | {
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closes #8588
Adds test to ensure the sort of a target object is preserved within `groupby()` groups, modifies docs to make it clear sort is preserved within groups.
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https://api.github.com/repos/pandas-dev/pandas/issues/10932 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10932/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10932/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10932/events | https://github.com/pandas-dev/pandas/pull/10932 | 103,909,704 | MDExOlB1bGxSZXF1ZXN0NDM3MTAyMjg= | 10,932 | ENH: #10143 Function to walk the group hierarchy of a PyTables HDF5 file | {
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This implementation is inspired by os.walk and follows the interface as much as possible.
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https://api.github.com/repos/pandas-dev/pandas/issues/10933 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10933/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10933/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10933/events | https://github.com/pandas-dev/pandas/issues/10933 | 103,911,284 | MDU6SXNzdWUxMDM5MTEyODQ= | 10,933 | EuroSciPy 2015 Sprint: Problem installing pandas from source on a Mac OS X | {
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> > > import pandas as pd
> > > Traceback (most recent call last):
> > > File "/Users/peadarcoyle/OpenSource/pandas/p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10934 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10934/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10934/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10934/events | https://github.com/pandas-dev/pandas/pull/10934 | 103,917,088 | MDExOlB1bGxSZXF1ZXN0NDM3MTExNTc= | 10,934 | DOC: consistent imports (GH9886) part V | {
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Does anyone have any objections to what I did?
I notice a few problems with the rebase though first - that's 12 commits rather than one.
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I didn't notice warnings or errors associated with those modifications when building the docs.
No more `FutureWarning` either (except in a the v. 0.13 what's new, which is legit)...
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https://api.github.com/repos/pandas-dev/pandas/issues/10939 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10939/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10939/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10939/events | https://github.com/pandas-dev/pandas/pull/10939 | 103,921,362 | MDExOlB1bGxSZXF1ZXN0NDM3MTI2ODI= | 10,939 | ENH: Add Series.dt.total_seconds GH #10817 | {
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closes #10817
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https://api.github.com/repos/pandas-dev/pandas/issues/10940 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10940/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10940/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10940/events | https://github.com/pandas-dev/pandas/pull/10940 | 103,924,952 | MDExOlB1bGxSZXF1ZXN0NDM3MTM3MTI= | 10,940 | DOC: consistent imports (GH9886) part V Fix of I#10934 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10943 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10943/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10943/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10943/events | https://github.com/pandas-dev/pandas/pull/10943 | 103,928,854 | MDExOlB1bGxSZXF1ZXN0NDM3MTQyODc= | 10,943 | BUG: passing columns and dict with scalar values should raise error | {
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``` Python
>>> pd.DataFrame({'a':0.1}, columns=['b'])
ValueError: If using all scalar values, you must pass an index
```
Trying to raise this error was slightly trickier than I anticipated - this was the only way that didn't break existing tests. If no i... | {
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part of #9862 master issue
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``` python
In [4]: ts
Out[4]:
a 1 0
2 1
b 2 2
NaN 3
c 1 4
2 5
dtype: int64
In [5]: ts.count(level=1)
Out[5]:
1 2
2 4 # <<< BUG!
dtype: int64
In [6]: from string import ascii_lowercase
In [7]: np.random.seed(2... | {
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However when I try to do so, I get a... | {
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] | closed | false | null | [] | null | 2 | 2015-08-31T12:45:27Z | 2018-10-21T01:31:41Z | 2018-10-21T01:31:36Z | NONE | null | I would like to have the group index of each instance.
I managed to do something like:
```
labels = {idx:(groupKey) for groupKey,idxList in g.groups.items() for idx in idxList}
```
But I wish it would be part of pandas for other to use. How do I do that?
Maybe this function already exists and I am not aware of it?
I... | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2015-08-31T13:48:14Z | 2015-10-20T17:48:06Z | 2015-10-20T17:48:06Z | CONTRIBUTOR | null | I think `s.cat.density` is appropriate here
```
In [1]: s = Series(list('aabbcccc')).astype('category')
In [2]: 100*len(s.cat.categories)/len(s)
Out[2]: 37
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10950 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10950/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10950/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10950/events | https://github.com/pandas-dev/pandas/issues/10950 | 104,061,709 | MDU6SXNzdWUxMDQwNjE3MDk= | 10,950 | Incorrect dtype coercion with panel assignment | {
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```
import numpy as np
randn = np.random.randn
from pandas import *
```
the following code creates a panel:
```
## Create pseudo panel data ##
numindivs = 2 # Number of individuals
numwaves = 5 # Number of time periods (waves)
# Create panel object
wp = Panel(np.random.randint(12, size=(numindivs, nu... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-08-31T17:02:11Z | 2015-09-03T13:25:32Z | 2015-09-03T13:25:32Z | CONTRIBUTOR | null | NumPy array of complex64 is implicitly converted to complex128 when used as data for DataFrame:
``` python
>>> a=np.random.randn(10).astype(np.complex64)
>>> a.dtype
dtype('complex64')
>>> pd.DataFrame({'a': a}).a.dtype
dtype('complex128')
>>>
```
The problem does not affect Series:
``` python
In [7]: Series(a).dty... | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2015-08-31T17:20:37Z | 2015-09-05T22:26:15Z | 2015-09-05T22:26:10Z | CONTRIBUTOR | null | closes #4893
Extends the eval parser to accept calling math functions.
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"color": "AD... | open | false | null | [] | null | 40 | 2015-08-31T17:31:07Z | 2020-09-06T18:47:08Z | null | CONTRIBUTOR | null | As `pandas` approaches its 1.0 release, I would like to raise a concern about one aspect of the `pandas` architecture that I think is a threat to its widespread adoption: how `pandas` works with copies and views when setting values (what I will refer to here as the `SettingWithCopyWarning` issue).
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] | closed | false | null | [] | null | 6 | 2015-08-31T20:42:01Z | 2018-08-24T14:44:18Z | 2018-08-24T14:44:18Z | NONE | null | I'm working with [vega-lite](https://github.com/uwdata/vega-lite) in a pipeline that goes from pandas to vega-lite. I would like to take a pandas DataFrame, output it as json, and incorporate it into a vega-lite JSON structure. Unfortunately none of pandas's DataFrame.to_json() "orient" options matches what vega-lite e... | {
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It would be nice to support this in pandas, too. Currently, attempting to do this throws KeyError:
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10959 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10959/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10959/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10959/events | https://github.com/pandas-dev/pandas/issues/10959 | 104,247,571 | MDU6SXNzdWUxMDQyNDc1NzE= | 10,959 | Discretizing a group of float columns using (apply + cut ) does not work | {
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"de... | closed | false | null | [] | null | 1 | 2015-09-01T11:43:29Z | 2015-09-01T11:53:21Z | 2015-09-01T11:52:48Z | NONE | null | This does not work
``` python
df = pd.DataFrame(np.arange(20).reshape(4,5)).astype(float)
df.apply(lambda x:pd.cut(x,2))
```
Here the result is pd.Series
This works
``` python
df = pd.DataFrame(np.arange(20).reshape(4,5))
df.apply(lambda x:pd.cut(x,2))
```
Here the result is a dataframe
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https://api.github.com/repos/pandas-dev/pandas/issues/10960 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10960/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10960/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10960/events | https://github.com/pandas-dev/pandas/pull/10960 | 104,258,009 | MDExOlB1bGxSZXF1ZXN0NDM4NzEwMTI= | 10,960 | BUG: Fixed bug that Timedelta raises error when slicing from 0s (issue #10583) | {
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I tried to use the clip function on a basic Panel but it seems that the axis management is not working as expected. I believe this is an update to issue https://github.com/pydata/pandas/issues/8344
```
import numpy as np
import pandas as pd
data = np.random.randn(3, 4, 5)
panel = pd.Panel(data)
panel.clip(0, 1... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10962 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10962/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10962/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10962/events | https://github.com/pandas-dev/pandas/pull/10962 | 104,296,627 | MDExOlB1bGxSZXF1ZXN0NDM4OTI3ODE= | 10,962 | BUG: DataFrame subplot with duplicated columns output incorrect result | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-09-01T15:52:12Z | 2015-09-05T02:14:56Z | 2015-09-05T02:14:54Z | MEMBER | null | When `DataFrame` has duplicated column name, each subplot will contain all the lines with same name.
```
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.rand(5, 5), columns=list('aaaaa'))
df.plot(subplots=True)
```
![figure_1](https://cloud.githubusercontent.com/assets/1696302/9609047/7acba4d0-510c... | {
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## In [6]: df1.to_sql(name='webshoptracks2', con=engine)
UnicodeEncodeError Traceback (most recent call las... | {
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"followers_url": "https://api.github.com/users/jr... | 11 | 2015-09-01T20:32:15Z | 2015-09-05T20:24:26Z | 2015-09-05T17:22:03Z | CONTRIBUTOR | null | This PR implements more flexible Excel (spreadsheet) reader tests. The work was originally part of the larger but unsuccessful PR #9070.
This PR includes:
- Excel reader base class tests to facilitate adding the similar tests for other readers
- not all Excel file formats (xls, xlsm, xlsx) had a corresponding test fi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10966 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10966/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10966/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10966/events | https://github.com/pandas-dev/pandas/issues/10966 | 104,371,685 | MDU6SXNzdWUxMDQzNzE2ODU= | 10,966 | Unpickling of pre 0.15 gzip-compressed objects not possible | {
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] | closed | false | null | [] | null | 6 | 2015-09-01T23:05:06Z | 2015-09-02T12:39:17Z | 2015-09-02T11:38:04Z | NONE | null | I pickled and gzip_compressed DataFrames in a tuple pre-0.15
```
with gzip.open('/tmp/test.pklz', 'wb') as datafile:
pickle.dump((df1,df2), datafile)
```
Pre-0.15 i would load them again like:
```
with gzip.open('/tmp/test.pklz', 'rb') as datafile:
df1, df2 = pickle.load(datafile)
```
Now after updating pan... | {
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xref #10564
Output of `to_excel` should now be fully round-trippable with `read_excel` with the
right combination of `index_col` and `header`.
To make the semantics match `read_csv`, an index column name (`has_index_names=True`) is
always assumed if something is passed to `index_col` - this should be non... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10970 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10970/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10970/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10970/events | https://github.com/pandas-dev/pandas/issues/10970 | 104,442,704 | MDU6SXNzdWUxMDQ0NDI3MDQ= | 10,970 | Data corruption during Excel export | {
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It's is not a problem of Excel reading (the data inside the sheet1.xml of the .xlsx file is also incorrect).
The same DataFrame exported to ".csv" is correct.
The problem could be "solved" by renaming the column header as [col-1, col-2,...]. Maybe a... | {
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```
In [1]: from pandas import *
In [7]: p = period_range('2013',periods=10)
In [8]: p
Out[8]:
PeriodIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04',
'2013-01-05', '2013-01-06', '2013-01-07', '2013-01-08',
'2013-01-09', '2013-01-10'],
dtype='int... | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-09-02T18:00:54Z | 2017-02-27T21:38:08Z | 2017-02-27T21:38:08Z | CONTRIBUTOR | null | xref #11444, #13046 for addtl tests
``` python
In [27]: df = pd.DataFrame({'a': np.random.randint(0, 5, 365), 'b': pd.date_range('2015-01-01', periods=365, freq='D')})
In [28]: df.head()
Out[28]:
a b
0 3 2015-01-01
1 3 2015-01-02
2 4 2015-01-03
3 2 2015-01-04
4 4 2015-01-05
In [29]: df.groupby('a').... | {
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- deprecates the option `mode.chained_assignment` as its now unused (it shows the deprecation if you are explicity using it, more friendly this way).
- deprecate `NDFrame.is_copy` property
- remove `SettingWithCopyWarning` entirely
TODO:
- [ ] some systematic testing of the chaining might help (e.g. iter... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10975 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10975/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10975/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10975/events | https://github.com/pandas-dev/pandas/pull/10975 | 104,586,907 | MDExOlB1bGxSZXF1ZXN0NDQwNTIwMjM= | 10,975 | BUG: DataFrame constructor should not promote complex64 dtypes (GH10952) | {
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When passing an array with complex64 dtype to the DataFrame constructor, that array will no longer be automatically promoted to the complex128 dtype (different complex dtypes are now allowed).
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https://api.github.com/repos/pandas-dev/pandas/issues/10977 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10977/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10977/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10977/events | https://github.com/pandas-dev/pandas/pull/10977 | 104,595,269 | MDExOlB1bGxSZXF1ZXN0NDQwNTcxODI= | 10,977 | DOC: Examples for Series.apply docstring | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10978 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10978/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10978/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10978/events | https://github.com/pandas-dev/pandas/issues/10978 | 104,639,262 | MDU6SXNzdWUxMDQ2MzkyNjI= | 10,978 | BDay offset behaviour vs docs & implementation | {
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from the docs :
DateOffsets can be created to move dates forward a given number of valid dates. For example, Bday(2) can be added to a date to move it two business days forward. If the date does not start on a valid date, first it is moved to a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10979 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10979/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10979/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10979/events | https://github.com/pandas-dev/pandas/issues/10979 | 104,654,898 | MDU6SXNzdWUxMDQ2NTQ4OTg= | 10,979 | Unexpected behaviour when grouping datetime column containing null-values, SeriesGroupby | {
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df = p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10980 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10980/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10980/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10980/events | https://github.com/pandas-dev/pandas/issues/10980 | 104,695,552 | MDU6SXNzdWUxMDQ2OTU1NTI= | 10,980 | REGR: if someone wants to find where this was fixed would be gr8 | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-09-03T13:38:13Z | 2015-09-08T00:32:36Z | 2015-09-08T00:32:36Z | CONTRIBUTOR | null | Regression from 0.16.2 to 0.16.1, but fixed in master, doced here: https://github.com/pydata/pandas/commit/2748e82ae99511f23f0f5134332706bde0798ef5
xref #10979 #9345
Ideally want identify where this happened, and if we have enough test coverage.
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https://api.github.com/repos/pandas-dev/pandas/issues/10981 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10981/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10981/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10981/events | https://github.com/pandas-dev/pandas/issues/10981 | 104,711,832 | MDU6SXNzdWUxMDQ3MTE4MzI= | 10,981 | TST: type / coercion issues, xref #10976 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10982 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10982/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10982/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10982/events | https://github.com/pandas-dev/pandas/issues/10982 | 104,714,589 | MDU6SXNzdWUxMDQ3MTQ1ODk= | 10,982 | .to_excel() cuts off columns | {
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You can reproduce this by downloading `Features.pkl` from [here](https://dl.dropboxu... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10983 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10983/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10983/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10983/events | https://github.com/pandas-dev/pandas/pull/10983 | 104,732,390 | MDExOlB1bGxSZXF1ZXN0NDQxMjcyMDE= | 10,983 | TST/DOC #10846 Test and document use of SQLAlchemy expressions in read_sql() | {
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It attempts to address #10846 by explaining how this feature is already supported by pandas.
Closes #10846
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https://api.github.com/repos/pandas-dev/pandas/issues/10984 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10984/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10984/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10984/events | https://github.com/pandas-dev/pandas/issues/10984 | 104,803,409 | MDU6SXNzdWUxMDQ4MDM0MDk= | 10,984 | BUG? Parser adds empty MultiIndex level names | {
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In [179]: midx = MultiIndex.from_tuples([('A', 1, 2), ('A', 1, 2), ('B', 1, 2)])
...: df = DataFrame(np.random.randn(3, 3), index=midx,
...: columns=['x', 'y', 'z'])
In [180]: df
Out[180]:
x y z
A 1 2 1.236013 2.239172 -1.513059
2 -0.159620 0.222250 -1.6... | {
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But I am having trouble testing this change. When I run `nosetests pandas/io/tests/test_parsers.py`, it says `Segmentation fault: 11` and this pops up `Python quit unexpectedly while using the parser.so plug-in.`
Any ideas of how to deal with this?
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```
for field in ["release_date", "date"]:
if field in df:
df[field] = pd.to_datetime(df[field], unit="ms")
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10989 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10989/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10989/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10989/events | https://github.com/pandas-dev/pandas/issues/10989 | 104,923,169 | MDU6SXNzdWUxMDQ5MjMxNjk= | 10,989 | BUG: pivot_table with margins=True fails for categorical dtype | {
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``` python
In [22]: pd.__version__
Out[22]: '0.16.2'
In [23]: data = pd.DataFrame({'x': np.arange(99),
'y': np.arange(99) // 50,
'z': np.arange(99) % 3})
In [24]: data.pivot_table('x', 'y', 'z')
Out[24]:
z 0 ... | {
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``` python
...
File "/home/tyler/repos/switchy/switchy/apps/measure/metrics.py", line 164, in append_row
self._store.append('data', self._df, dropna=False)
File "/usr/lib/python2.7/site-packages/pandas/io/pytables.py", line 912, in append
**kwargs)
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-09-04T19:16:02Z | 2015-09-05T14:19:49Z | 2015-09-05T14:19:49Z | CONTRIBUTOR | null | - makes the toc 4 levels
- increases the width of the side bar a bit
- increases the overall width just a bit
![io tools text csv hdf5 pandas 0 16 2 557... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10993 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10993/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10993/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10993/events | https://github.com/pandas-dev/pandas/pull/10993 | 104,960,190 | MDExOlB1bGxSZXF1ZXN0NDQyNTU5MjQ= | 10,993 | BUG: pivot_table with margins=True fails for categorical dtype, #10989 | {
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"default"... | closed | false | null | [] | null | 3 | 2015-09-04T21:08:50Z | 2015-09-04T22:37:06Z | 2015-09-04T21:33:17Z | NONE | null | ``` python
import pandas as pd
from numpy import random
# Make a dataframe
foo = pd.DataFrame(random.rand(5,6),
columns=pd.MultiIndex.from_tuples(
[('A','1'), ('A','2'),('B','1'),('B','2'),('C','1'),('C','2')]))
# Select a subset of columns based on level[0] labels
fooAB = foo[[... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10995 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10995/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10995/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10995/events | https://github.com/pandas-dev/pandas/issues/10995 | 104,977,862 | MDU6SXNzdWUxMDQ5Nzc4NjI= | 10,995 | DOC: Improve reindex docstring and examples | {
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could use some improvement
- mention that `ffill`, `bfill`, `method` only available for monotonically increasing and decreasing indices
- add a ton of examples to help users navigate all the various options
- add no... | {
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Done/waiting for feedback.
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This is an example of how they can be cleaned up (grouping benchmarks with the same setup in common classes, removing a lot of the setup functions in this way)
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https://api.github.com/repos/pandas-dev/pandas/issues/11000 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11000/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11000/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11000/events | https://github.com/pandas-dev/pandas/pull/11000 | 105,024,847 | MDExOlB1bGxSZXF1ZXN0NDQyODIzMDc= | 11,000 | ENH: Reduce for loops in df.corr(method='kendall') | {
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Don't need to loop through lower triangle of the matrix.
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might pay to do this somewhat in some other sections just to break the sub-sections up a bit
- http://pandas-docs.github.io/pandas-docs-travis/dsintro.html
maybe other places as well
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https://api.github.com/repos/pandas-dev/pandas/issues/11002 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/11002/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/11002/comments | https://api.github.com/repos/pandas-dev/pandas/issues/11002/events | https://github.com/pandas-dev/pandas/issues/11002 | 105,039,813 | MDU6SXNzdWUxMDUwMzk4MTM= | 11,002 | pd.to_pickle() and pd.read_pickle() bug? | {
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"description": "IO issues that don't fit... | closed | false | null | [] | {
"closed_at": "2015-10-09T18:34:35Z",
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"created_at": "2015-03-23T10:47:38Z",
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"events_url": "https://api.github.com/users/jreback/events{/privacy}",
"followers_url": "https://api.github.com/users/jr... | 1 | 2015-09-05T17:46:24Z | 2015-09-05T23:22:57Z | 2015-09-05T23:22:57Z | NONE | null | I'm on windows 7, anaconda, python 2.7.9, 32bit
pandas 0.16.2
try this:
``` python
import pandas as pd
df4 = pd.DataFrame(index=P.date_range('1750-1-1', '2050-1-1', freq='7D')
pd.to_pickle(df4, '7d.test')
pd.read_pickle('7d.test')
In [84]: P.read_pickle('7d.test')
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