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https://api.github.com/repos/pandas-dev/pandas/issues/10803 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10803/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10803/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10803/events | https://github.com/pandas-dev/pandas/pull/10803 | 100,481,298 | MDExOlB1bGxSZXF1ZXN0NDIyMDk5OTE= | 10,803 | BUG: Allow read_sql_table to read from views | {
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Follow-up from #10771
'read_sql_table' will now allow reading from views.
Added also a note in whatsnew and a unit test to check the behaviour.
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https://api.github.com/repos/pandas-dev/pandas/issues/10804 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10804/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10804/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10804/events | https://github.com/pandas-dev/pandas/issues/10804 | 100,521,161 | MDU6SXNzdWUxMDA1MjExNjE= | 10,804 | PERF: categorical value_counts can be much faster | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2015-08-12T11:20:35Z | 2015-08-22T20:03:01Z | 2015-08-22T20:03:01Z | CONTRIBUTOR | null | The internal impl of `Categorical.value_counts` should just do this. I think it is factorizing multiple times when it is not necessary.
```
In [32]: np.random.seed(1234)
In [33]: n = 500000
In [34]: u = int(0.1*n)
In [35]: arr = [ "s%04d" % i for i in np.random.randint(0,u,size=n) ]
In [36]: c = pd.Series(arr).ast... | {
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"description": "Duplicate... | closed | false | null | [] | null | 2 | 2015-08-12T15:08:54Z | 2015-08-12T15:32:02Z | 2015-08-12T15:15:10Z | CONTRIBUTOR | null | I believe this is a bug in the definition of memorial day in `pandas.tseries.holiday`:
```
USMemorialDay = Holiday('MemorialDay', month=5, day=24, offset=DateOffset(weekday=MO(1)))
```
should be
```
USMemorialDay = Holiday('MemorialDay', month=5, day=31, offset=DateOffset(weekday=MO(-1)))
```
as memorial day is alw... | {
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This is possible, just not implemented
```
In [3]: df = DataFrame(np.arange(16).reshape(4, 4), index=[1, 2, 3, 4], columns=['A', 'B', 'C', 'D'])
In [4]: df
Out[4]:
A B C D
1 0 1 2 3
2 4 5 6 7
3 8 9 10 11
4 12 13 14 15
In [5]: df.sort_values(by=1,axis=1)
ValueError:... | {
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```
import tables as tb
import pandas as pd
class TestTable(tb.IsDescription):
field1 = tb.UInt32Col()
field2 = tb.UInt32Col()
field3 = tb.UInt32Col()
h5file = tb.open_file('test.h5', mode = "w", title = "Test File")
table = h5file.create_table('/', 'test_table', TestTable, "Test Table")
h5f... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10808 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10808/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10808/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10808/events | https://github.com/pandas-dev/pandas/pull/10808 | 100,631,745 | MDExOlB1bGxSZXF1ZXN0NDIyODY5MTg= | 10,808 | BUG: fix bounds for negative ints when using iloc (GH 10779) | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-08-12T20:47:31Z | 2015-08-15T12:46:01Z | 2015-08-14T18:40:52Z | CONTRIBUTOR | null | This fixes the issues raised in [GH 10779](https://github.com/pydata/pandas/issues/10779).
closes #10547
Previously, negative integers used in `iloc` were not stopped from going beyond the bounds of the Series. For instance, if `s = pd.Series([1,2,3])` then `s.iloc[-4]` returned bytes from memory outside `s`. This wi... | {
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... | closed | false | null | [] | null | 3 | 2015-08-12T20:56:15Z | 2015-08-13T19:36:44Z | 2015-08-12T22:23:06Z | NONE | null | Note how the string 'M15' becomes somehow 8/15/2015!
> > > pandas.Series([datetime.datetime(2015,1,1), 'M15'])
> > > 0 2015-01-01
> > > 1 2015-08-15
> > > dtype: datetime64[ns]
Compare other arbitrary strings that are left alone:
> > > pandas.Series([datetime.datetime(2015,1,1), 'MM15'])
> > > 0 2015-01-01 00... | {
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CC @patricktokeeffe @bilderbuchi
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```
df.reindex(df.index.tolist()+new_values).sort().interpolate().ix[new_values]
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10812 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10812/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10812/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10812/events | https://github.com/pandas-dev/pandas/pull/10812 | 100,715,089 | MDExOlB1bGxSZXF1ZXN0NDIzMjY3MTE= | 10,812 | Deprecate combineAdd and combineMult (GH10735) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10813 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10813/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10813/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10813/events | https://github.com/pandas-dev/pandas/issues/10813 | 100,749,739 | MDU6SXNzdWUxMDA3NDk3Mzk= | 10,813 | to_csv with lists of strings and unicode encoding produces wrong output | {
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"created_at": "2015-02-26T19:29:05Z",
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"followers_url": "https://api.github.com/users/jorisva... | 11 | 2015-08-13T11:50:25Z | 2019-07-30T03:22:55Z | 2019-07-30T03:22:49Z | NONE | null | If I have a dataframe with cells containing lists of strings (or unicode strings), then these lists are broken when I use `to_csv()` with the `encoding` parameter set. The error does not occur if the `encoding` is not set.
Here is an example (using pandas version 0.16.2):
```
df = pd.DataFrame.from_records(
[('Ma... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10814 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10814/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10814/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10814/events | https://github.com/pandas-dev/pandas/issues/10814 | 100,798,445 | MDU6SXNzdWUxMDA3OTg0NDU= | 10,814 | pandas 0.16.2 groupby and transform does not properly work with datetime objects | {
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... | closed | false | null | [] | null | 3 | 2015-08-13T15:25:58Z | 2015-08-13T15:43:59Z | 2015-08-13T15:32:39Z | NONE | null | In the 0.16.2 version, transform returns original values, while in the 0.15.2 version it properly transforms the values into group counts. The problem seems to be with how pandas deal with datetime objects.
The only difference is the pandas version, and everything else is the same.
---
```
import pandas as pd
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https://api.github.com/repos/pandas-dev/pandas/issues/10815 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10815/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10815/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10815/events | https://github.com/pandas-dev/pandas/pull/10815 | 100,799,319 | MDExOlB1bGxSZXF1ZXN0NDIzNjM4NzE= | 10,815 | API: Series.sum() will now return 0.0 for all-NaN series | {
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... | 10 | 2015-08-13T15:29:06Z | 2015-09-03T14:19:27Z | 2015-09-03T14:19:26Z | CONTRIBUTOR | null | compat with `numpy` >= 1.8.2 and `bottleneck` >= 1.0, #9422
note that passing skipna=False will still return a NaN
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https://api.github.com/repos/pandas-dev/pandas/issues/10816 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10816/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10816/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10816/events | https://github.com/pandas-dev/pandas/issues/10816 | 100,854,375 | MDU6SXNzdWUxMDA4NTQzNzU= | 10,816 | API: select levels of a MultiIndex | {
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... | 8 | 2015-08-13T19:53:42Z | 2021-04-18T23:27:20Z | null | MEMBER | null | Say you have a multi-index:
```
In [34]: idx = pd.MultiIndex.from_product([['a', 'b', 'c'], [1, 2, 3], ['f', 'g'
]], names=['lev0', 'lev1', 'lev2'])
In [35]: df = pd.DataFrame(range(len(idx)), index=idx)
In [36]: df
Out[36]:
0
lev0 lev1 lev2
a 1 f 0
g 1
2 f 2
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https://api.github.com/repos/pandas-dev/pandas/issues/10817 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10817/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10817/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10817/events | https://github.com/pandas-dev/pandas/issues/10817 | 100,874,075 | MDU6SXNzdWUxMDA4NzQwNzU= | 10,817 | Add .dt.total_seconds() method for timedelta64 Series | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2015-08-13T21:34:40Z | 2015-09-02T15:59:34Z | 2015-09-02T11:52:39Z | CONTRIBUTOR | null | Background: I am trying to build a horizonal bar graph that shows me when various builds on a server started and ended, so that I can see visually which builds overlapped in time. But the idea that a horizontal bar graph's bar-width would be a timedelta seems completely foreign to all of the plotting libraries that I h... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10818 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10818/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10818/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10818/events | https://github.com/pandas-dev/pandas/issues/10818 | 100,898,484 | MDU6SXNzdWUxMDA4OTg0ODQ= | 10,818 | non-NDFFrame object error using pandas.SparseSeries.from_coo() function | {
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... | 5 | 2015-08-14T00:11:59Z | 2016-04-03T07:45:23Z | 2016-04-03T07:45:23Z | NONE | null | There appears to be an issue with the .from_coo() sparse function. If the frame is viewed, it gives a "non-NDFFrame error". It could potentially be due to overlapping entries on the same index (this is handled in sparse.coo_matrix by adding the entries by default).
More details here:
http://stackoverflow.com/question... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10819 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10819/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10819/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10819/events | https://github.com/pandas-dev/pandas/issues/10819 | 100,910,677 | MDU6SXNzdWUxMDA5MTA2Nzc= | 10,819 | plotting with Gridspec : index is out of bounds | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-08-14T01:54:26Z | 2015-09-01T12:06:24Z | 2015-09-01T12:06:24Z | NONE | null | I came across the same error described in [this stack post.](https://stackoverflow.com/questions/30623162/plotting-with-gridspec-index-is-out-of-bounds) I didn't experience the error until upgrading to 0.16.2. Like others who commented, downgrading to 0.15.2 fixed the issue. I couldn't find it reported anywhere else so... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10820 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10820/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10820/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10820/events | https://github.com/pandas-dev/pandas/issues/10820 | 100,988,334 | MDU6SXNzdWUxMDA5ODgzMzQ= | 10,820 | nunique performance for groupby with large number of groups | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2015-08-14T10:53:45Z | 2015-08-24T18:33:56Z | 2015-08-24T18:33:56Z | CONTRIBUTOR | null | It looks like `len(set)` beats both `len(np.unique)` and `pd.Series.nunique` if done naively -- here's an example with a large number of groups where we try to compute unique counts of a column when grouping by another column:
``` python
>>> df = pd.DataFrame({'a': np.random.randint(10000, size=100000),
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https://api.github.com/repos/pandas-dev/pandas/issues/10821 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10821/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10821/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10821/events | https://github.com/pandas-dev/pandas/issues/10821 | 101,050,276 | MDU6SXNzdWUxMDEwNTAyNzY= | 10,821 | PERF: implement value_counts_float64 | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-08-14T16:40:56Z | 2015-08-18T23:37:27Z | 2015-08-18T23:37:27Z | CONTRIBUTOR | null | int64/object are implemented. This is slightly tricky as have to count `nan` but not too difficult.
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https://api.github.com/repos/pandas-dev/pandas/issues/10822 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10822/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10822/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10822/events | https://github.com/pandas-dev/pandas/issues/10822 | 101,053,143 | MDU6SXNzdWUxMDEwNTMxNDM= | 10,822 | TST: testing issue on windows | {
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@sinhrks
This fails on windows (actually doesn't on a windows vm, you need an actual windows machine....weird)
```
======================================================================
ERROR: test_invalid_index_type... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10823 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10823/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10823/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10823/events | https://github.com/pandas-dev/pandas/issues/10823 | 101,090,555 | MDU6SXNzdWUxMDEwOTA1NTU= | 10,823 | Inconsistency with MovingOLS min_periods | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2015-08-14T19:51:00Z | 2015-08-18T10:47:43Z | 2015-08-18T10:47:43Z | CONTRIBUTOR | null | I'm not sure if this is a bug or a typo in the documentation but for the `min_periods` parameter in MovingOLS the documentation claims
```
min_periods : int
Threshold of non-null data points to require.
If None, defaults to size of window.
```
However this does not seem to be the case? From line 640-648... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10824 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10824/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10824/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10824/events | https://github.com/pandas-dev/pandas/issues/10824 | 101,153,739 | MDU6SXNzdWUxMDExNTM3Mzk= | 10,824 | BUG: Merge with empty DataFrame raise IndexError | {
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import numpy as np
import pandas as pd
df1 = pd.DataFrame([], columns=['a', 'b', 'c'])
df2 = pd.DataFrame(np.random.randn(3, 3), columns=['x', 'y', 'z'])
# OK
pd.merge(df1, df2, how='right', left_index=True, right_index=True)
# a b c x y z
#0 NaN NaN NaN 0.665359 0.087728 -... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10825 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10825/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10825/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10825/events | https://github.com/pandas-dev/pandas/pull/10825 | 101,181,038 | MDExOlB1bGxSZXF1ZXN0NDI1MTk5ODc= | 10,825 | Fix handling of EOF in 'c' csv parser | {
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fixes #10548.
Also fixes:
- '\r' followed by EOF should be considered a blank line
- Escape character followed by EOF should produce an exception
- Line containing only whitespace should be skipped if `skip_blank_lines` and `delim_whitespace` are both `True`
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https://api.github.com/repos/pandas-dev/pandas/issues/10826 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10826/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10826/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10826/events | https://github.com/pandas-dev/pandas/pull/10826 | 101,181,083 | MDExOlB1bGxSZXF1ZXN0NDI1MjAwMDU= | 10,826 | BUG: Merge with empty dataframe may raise IndexError | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10828 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10828/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10828/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10828/events | https://github.com/pandas-dev/pandas/issues/10828 | 101,214,157 | MDU6SXNzdWUxMDEyMTQxNTc= | 10,828 | TST: add tests for ABC Types | {
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```
p = pd.Period(....)
self.assertTrue(isinstance(p, ABCPeriod))
```
for all of the ABC types defined.
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https://api.github.com/repos/pandas-dev/pandas/issues/10830 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10830/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10830/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10830/events | https://github.com/pandas-dev/pandas/issues/10830 | 101,319,325 | MDU6SXNzdWUxMDEzMTkzMjU= | 10,830 | Can't access 'Strike' column in option dataframe | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10831 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10831/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10831/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10831/events | https://github.com/pandas-dev/pandas/issues/10831 | 101,337,693 | MDU6SXNzdWUxMDEzMzc2OTM= | 10,831 | 0.16.2: HTML docs fail to make, "TypeError: an integer is required (got type str)" | {
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] | closed | false | null | [] | null | 2 | 2015-08-17T04:42:31Z | 2015-08-18T10:21:01Z | 2015-08-18T10:21:01Z | NONE | null | - `pip3 install --upgrade pandas` # installed 0.16.2
- Download 0.16.2 source, unzip, use `pip3` to install Sphinx (1.3.1, and dependencies such as sphinx-rtd-theme (0.1.8))
- run `make.py html` in `doc` folder
```
C:\Python34\pandas-0.16.2\doc>c:\Python34\python.exe make.py html
Traceback (most recent call last):
F... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10832 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10832/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10832/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10832/events | https://github.com/pandas-dev/pandas/issues/10832 | 101,385,399 | MDU6SXNzdWUxMDEzODUzOTk= | 10,832 | Categorical can not be used as key in merges | {
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"events_url": "https://api.github.com/users/jreback/events{/privacy}",
"followers_url": "https://api.github.com/users/jr... | 2 | 2015-08-17T10:01:34Z | 2015-08-17T11:01:12Z | 2015-08-17T11:00:22Z | CONTRIBUTOR | null | ```
df1 = pd.DataFrame({"a": list("ABCD"), "b": [1,2,3,4]})
df2 = pd.DataFrame({"a": list("BCDF"), "b": [1,2,3,4]})
df1["c"] = df1["a"].astype("category")
df2["c"] = df2["a"].astype("category")
pd.merge(df1, df2, on=["c"], how="outer")
```
Results in:
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10833 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10833/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10833/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10833/events | https://github.com/pandas-dev/pandas/issues/10833 | 101,451,670 | MDU6SXNzdWUxMDE0NTE2NzA= | 10,833 | BUG: Error while saving DataFrame with TimedeltaIndex to .csv | {
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"... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-08-17T15:45:54Z | 2015-08-21T14:10:24Z | 2015-08-21T14:10:24Z | CONTRIBUTOR | null | I'm trying to save pd.DataFrame using `.to_csv` method.
If DataFrame has TimedeltaIndex the error is risen:
```
>>> dt = pd.Timedelta(seconds=10)
>>> timestamps = [dt, 2*dt, 3*dt]
>>> df = pd.DataFrame({'obs': [11,22,33]}, index=timestamps)
>>> df
obs
00:00:10 11
00:00:20 22
00:00:30 33
>>> df.to_csv(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10834 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10834/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10834/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10834/events | https://github.com/pandas-dev/pandas/issues/10834 | 101,463,695 | MDU6SXNzdWUxMDE0NjM2OTU= | 10,834 | passing of `test_to_datetime_with_non_exact` depends on OS language. | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-08-17T16:52:16Z | 2015-08-17T20:50:10Z | 2015-08-17T20:50:10Z | CONTRIBUTOR | null | The abbreviations of the names of months in `format_regex` are language specific. Thus the test fails on non-english systems:
`format_regex` on this machine is
`re.compile('(?P<d>3[0-1]|[1-2]\\d|0[1-9]|[1-9]| [1-9])(?P<b>jan|feb|m\\är|apr|mai|jun|jul|aug|sep|okt|nov|dez)(?P<y>\\d\\d)', re.IGNORECASE)`
```
ERROR: t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10835 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10835/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10835/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10835/events | https://github.com/pandas-dev/pandas/issues/10835 | 101,469,999 | MDU6SXNzdWUxMDE0Njk5OTk= | 10,835 | Test failure: test_none_comparison | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2015-08-17T17:30:03Z | 2015-08-22T20:12:18Z | 2015-08-22T20:12:18Z | CONTRIBUTOR | null | `test_none_comparison` fails for me for all versions of `numpy>=1.9.0`. I don't see this issue in any `numpy-1.8.x` version.
```
ERROR: test_none_comparison (pandas.tests.test_base.TestIndexOps)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/Users/ch... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10836 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10836/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10836/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10836/events | https://github.com/pandas-dev/pandas/pull/10836 | 101,471,019 | MDExOlB1bGxSZXF1ZXN0NDI2MTM0OTY= | 10,836 | skipped failing test on non-engish locales | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-08-17T17:36:22Z | 2015-08-17T20:50:15Z | 2015-08-17T20:50:10Z | CONTRIBUTOR | null | Should fix https://github.com/pydata/pandas/issues/10834
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https://api.github.com/repos/pandas-dev/pandas/issues/10837 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10837/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10837/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10837/events | https://github.com/pandas-dev/pandas/issues/10837 | 101,478,301 | MDU6SXNzdWUxMDE0NzgzMDE= | 10,837 | testArrayNumpyLabelled fails on Python 2.7.10 | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2015-08-17T18:12:32Z | 2015-08-19T10:53:27Z | 2015-08-19T10:53:27Z | CONTRIBUTOR | null | ```
FAIL: testArrayNumpyLabelled (pandas.io.tests.test_json.test_ujson.NumpyJSONTests)
----------------------------------------------------------------------
Traceback (most recent call last):
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https://api.github.com/repos/pandas-dev/pandas/issues/10838 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10838/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10838/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10838/events | https://github.com/pandas-dev/pandas/pull/10838 | 101,535,242 | MDExOlB1bGxSZXF1ZXN0NDI2NDgzNzY= | 10,838 | BUG: Panel setitem with a multiindex #10360 (partial) | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-08-18T00:03:35Z | 2019-08-10T19:45:05Z | 2015-08-18T10:44:03Z | CONTRIBUTOR | null | partial on #10360
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https://api.github.com/repos/pandas-dev/pandas/issues/10839 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10839/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10839/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10839/events | https://github.com/pandas-dev/pandas/issues/10839 | 101,535,273 | MDU6SXNzdWUxMDE1MzUyNzM= | 10,839 | BUG: Panel indexing with partial setting | {
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takes care of full slices, e.g. `p.iloc[0,0,:] = [1,2,3]`, but the following is still failing
(whether mixed blocks or not)
```
In [8]: axes = dict(items = pd.MultiIndex.from_tuples([('A','a'), ('B','b')]), major_axis = pd.MultiIndex.from_tuples([('A',1),('A',2)]), minor_axis=pd.MultiIndex.from_... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10840 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10840/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10840/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10840/events | https://github.com/pandas-dev/pandas/pull/10840 | 101,552,462 | MDExOlB1bGxSZXF1ZXN0NDI2NTQ3Nzg= | 10,840 | PERF: value_counts_float64 #10821 | {
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"followers_url": "https://api.github.com/users/jr... | 23 | 2015-08-18T02:13:15Z | 2015-08-19T00:53:03Z | 2015-08-18T23:37:09Z | CONTRIBUTOR | null | Adresses #10821 - I get a doubling of performance for `value_counts` for a `Series` with a float dtype. Couldn't think of any new tests needed not covered by existing [here](https://github.com/pydata/pandas/blob/master/pandas/tests/test_algos.py#L416)
```
In [1]: f = np.hstack([np.hstack(np.linspace(0,1,1000) for _ ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10841 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10841/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10841/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10841/events | https://github.com/pandas-dev/pandas/pull/10841 | 101,552,837 | MDExOlB1bGxSZXF1ZXN0NDI2NTQ4OTY= | 10,841 | DOC: Fix for #10823, updating min_periods docstring | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10842 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10842/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10842/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10842/events | https://github.com/pandas-dev/pandas/issues/10842 | 101,600,930 | MDU6SXNzdWUxMDE2MDA5MzA= | 10,842 | Weird behaviour of groupby with quantile | {
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```
import pandas as pd
X = pd.DataFrame(dict(g=['a','a','b','b','b'],a=range(5)))
```
For some reason this loses the grouping variable 'g':
```
X.groupby(['g'],as_index=False).quantile(0.5)
a
0 0.5
1 3.0
```
I was expecting this output:
```
X.groupby(['g']).quantile(0.5).reset_index()
g a
0 a ... | {
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] | closed | false | null | [] | null | 9 | 2015-08-18T09:49:49Z | 2019-10-08T09:24:58Z | 2015-08-18T10:37:54Z | NONE | null | The simplest way to access underlying data (ndarray) for dataframe column is `df['column_name'].values`. But it is so slow, that special cache is used for it:
``` python
>>> import pandas as pd
>>> import numpy as np
>>> df = pd.DataFrame(np.zeroes((1000, 5)), columns=list('abcde'))
>>> %timeit df['a'].values; df._ite... | {
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- [x] add docs on how to use / add tests (in contributing.md / contributing.rst)
- [x] add/update vbenches to current
- [x] whatsnew note (put in highlites that this is added)
- [ ] test on Windows (basicly works, but had to do some small adjustments)
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I created tests for this issue here: https://github.com/pydata/pandas/issues/10828. This is my first time working on Pandas, so please let me know if there is anything wrong with the way I have coded these tests. I haven't updated the documentation, I was unsure of what version I should update and wheth... | {
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[39] should raise.
```
In [38]: pd.DataFrame({'a':0.1})
ValueError: If using all scalar values, you must pass an index
In [39]: pd.DataFrame({'a':0.1}, columns=['b'])
Out[39]:
Empty DataFrame
Columns: [b]
Index: []
```
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closes #10652
- Added ability to automatically create a table using the gbq.to_gbq function if destination table does not exist
- Added `gbq.gbq_table_exists()` function to the gbq module
- Added `gbq.create_gbq_table()` function to the gbq module
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https://api.github.com/repos/pandas-dev/pandas/issues/10858 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10858/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10858/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10858/events | https://github.com/pandas-dev/pandas/pull/10858 | 102,027,520 | MDExOlB1bGxSZXF1ZXN0NDI4NzkwNDA= | 10,858 | removes categories & ordered from CategoricalIndex attributes | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-08-20T00:10:29Z | 2015-08-20T23:32:06Z | 2015-08-20T12:48:09Z | CONTRIBUTOR | null | `categories` and `ordered` are properties not attributes ([index.py#L3085-L3091](https://github.com/pydata/pandas/blob/3e35c842f37265ac7339908869d4cc7bdef784d9/pandas/core/index.py#L3085-L3091)). The side effect is that the categories are rehashed too often:
on master:
``` ipython
In [1]: from pandas.core.index impor... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10859 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10859/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10859/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10859/events | https://github.com/pandas-dev/pandas/pull/10859 | 102,078,552 | MDExOlB1bGxSZXF1ZXN0NDI4OTg4MDM= | 10,859 | Tests for ABC Types | {
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I used self.assertIsInstance(obj, type) and inlined as many of the expressions as I could while staying PEP8 compliant. I added in the two tests that I took out, that was an accident. Let me know if this looks okay!
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https://api.github.com/repos/pandas-dev/pandas/issues/10860 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10860/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10860/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10860/events | https://github.com/pandas-dev/pandas/issues/10860 | 102,139,673 | MDU6SXNzdWUxMDIxMzk2NzM= | 10,860 | pandas.io.wb.download returned DataFrame does not contain iso_code | {
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I commented out ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10861 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10861/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10861/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10861/events | https://github.com/pandas-dev/pandas/issues/10861 | 102,144,296 | MDU6SXNzdWUxMDIxNDQyOTY= | 10,861 | DEPR: deprecate datareader in 0.17.0 | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-08-20T13:55:43Z | 2015-08-23T10:27:03Z | 2015-08-23T10:27:03Z | CONTRIBUTOR | null | xref https://github.com/pydata/pandas/pull/10061
closes #8961
point to [pandas-datareader package](https://github.com/pydata/pandas-datareader)
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https://api.github.com/repos/pandas-dev/pandas/issues/10862 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10862/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10862/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10862/events | https://github.com/pandas-dev/pandas/issues/10862 | 102,147,689 | MDU6SXNzdWUxMDIxNDc2ODk= | 10,862 | TST: create legacy_pickles/msgpacks for older versions | {
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... | 0 | 2015-08-20T14:08:34Z | 2016-03-25T13:30:15Z | 2016-03-25T13:30:15Z | CONTRIBUTOR | null | using https://github.com/pydata/pandas/blob/master/pandas/io/tests/generate_legacy_storage_files.py
its quite easy to produce a library of pickles/msgpacks from prior versions that we then store to test for back-compat with the current version (IOW, these have generated tests which run).
Ideally like to fill this out... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10863 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10863/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10863/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10863/events | https://github.com/pandas-dev/pandas/issues/10863 | 102,164,318 | MDU6SXNzdWUxMDIxNjQzMTg= | 10,863 | BUG: frame creation with multi-index and tuples in dict | {
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In [1]: import pandas;import numpy;import datetime;
In [2]: v = datetime.date.today()
In [3]: pandas.DataFrame({v : pandas.Series(range(3),index=range(3))}, columns=[v])
Out[3]:
2015-08-20
0 0
1 1
2 2
In [4]: v = v, v
In [5]: pandas.DataFrame({v : pandas.Series(range(3),index=range(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10864 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10864/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10864/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10864/events | https://github.com/pandas-dev/pandas/issues/10864 | 102,166,137 | MDU6SXNzdWUxMDIxNjYxMzc= | 10,864 | Add dask._merge to toplevel | {
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How about adding `_merge` function which can handle `dict`, `Base` and nested list for internal use? It accepts `_merge(dask, seq)`.
```
def _merge(*dasks, **kwargs):
""" Merge a collection of dask instances and dicts """
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https://api.github.com/repos/pandas-dev/pandas/issues/10865 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10865/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10865/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10865/events | https://github.com/pandas-dev/pandas/issues/10865 | 102,167,274 | MDU6SXNzdWUxMDIxNjcyNzQ= | 10,865 | Add Base.to_graphviz | {
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- When using IPython, `.visualize` outputs unnecessary image file
- Sometimes we want to modify graphviz instance directly
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https://api.github.com/repos/pandas-dev/pandas/issues/10866 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10866/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10866/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10866/events | https://github.com/pandas-dev/pandas/pull/10866 | 102,176,533 | MDExOlB1bGxSZXF1ZXN0NDI5NDkyNTg= | 10,866 | ENH: Period pickle | {
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closes #10441
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"de... | closed | false | null | [] | null | 7 | 2015-08-20T21:24:14Z | 2015-08-21T15:53:10Z | 2015-08-20T21:38:22Z | CONTRIBUTOR | null | Just stumbled about a very nasty subtle dtype inconsistency after join operation that crippled by out-of-core-join-many-result-files pipeline for unfitting index sizes for the HDF append operation.
See the example code here:
https://nbviewer.jupyter.org/gist/michaelaye/1c34cda54872046b5989
or here as screenshot:
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``` python
In [1]: import pandas as pd
i
In [2]: import numpy as np
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I fixed the import statement and added a test to check for proper behavior when accessing a mixed-integer index with a list of values.
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``` ipython
In [1]: np.random.seed(2718281)
In [2]: n = 500000
In [3]: u = int(0.1*n)
In [4]: arr = ["s%04d" % i for i in np.random.randint(0, u, size=n)]
In [5]: ts = pd.Series(arr).astype('category')
In [6]: %timeit ts.value_counts()
10 loops, best of 3: 82.7... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10875 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10875/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10875/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10875/events | https://github.com/pandas-dev/pandas/issues/10875 | 102,288,239 | MDU6SXNzdWUxMDIyODgyMzk= | 10,875 | BUG: Index name is not preserved during some conversions | {
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```
In [42]: vec = ['01:02:03', '01:02:04']
In [43]: i = pd.Index(vec, name='label')
In [44]: i
Out[44]: Index(['01:02:03', '01:02:04'], dtype='object', name='label')
In [45]: pd.to_datetime(i)
Out[45]: D... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10876 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10876/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10876/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10876/events | https://github.com/pandas-dev/pandas/pull/10876 | 102,326,524 | MDExOlB1bGxSZXF1ZXN0NDMwMTUwOTA= | 10,876 | BUG: GH10747 where 'timestamp' is not inferred to be datetime column | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10877 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10877/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10877/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10877/events | https://github.com/pandas-dev/pandas/issues/10877 | 102,329,796 | MDU6SXNzdWUxMDIzMjk3OTY= | 10,877 | EuroScipy 2015 pandas sprint | {
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The sprints will take place at the Seminar Centre of the Hauser Forum (very near to the conference venue) from 10am to 5pm.
This issue will be the landing page for contributors.
[pandas](http://pandas.p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10878 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10878/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10878/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10878/events | https://github.com/pandas-dev/pandas/issues/10878 | 102,409,015 | MDU6SXNzdWUxMDI0MDkwMTU= | 10,878 | DEPR: deprecate legacy offsets | {
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discussed at bit in #7832
Leave these common aliases.
| Legacy Time Rule | Offset Alias |
| --- | --- |
| min | T |
| ms | L |
| us | U |
Deprecate These
| Legacy Time Rule | Offset Alias |
| --- | --- |
| WEEKDAY | B |
| EOM | BM ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10879 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10879/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10879/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10879/events | https://github.com/pandas-dev/pandas/pull/10879 | 102,409,178 | MDExOlB1bGxSZXF1ZXN0NDMwNTI2OTQ= | 10,879 | BUG: DataFrame.plot may raise IndexError / show unnessesary minor ticklabels | {
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Following is an example notebook how the fix works.
- https://gist.github.com/sinhrks/2d29e2e8ef26f2757e92
CC @TomAugspurger ... | {
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This might be able to be merged quicker than the other one.
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https://api.github.com/repos/pandas-dev/pandas/issues/10881 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10881/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10881/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10881/events | https://github.com/pandas-dev/pandas/pull/10881 | 102,480,177 | MDExOlB1bGxSZXF1ZXN0NDMwOTA5MTA= | 10,881 | ERR/DEPR: Fix quantile error message / remove percentile_width | {
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```
s = pd.Series([1, 2, 3])
s.quantile(2)
# File ".../numpy/lib/function_base.py", line 3078, in _percentile
# raise ValueError("Percentiles must be in the range [0,100]")
# ValueError: Percentiles must be in the range [0,100]
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10882 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10882/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10882/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10882/events | https://github.com/pandas-dev/pandas/issues/10882 | 102,496,642 | MDU6SXNzdWUxMDI0OTY2NDI= | 10,882 | Feature Request: skipcols in .read_csv | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10884 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10884/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10884/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10884/events | https://github.com/pandas-dev/pandas/pull/10884 | 102,521,359 | MDExOlB1bGxSZXF1ZXN0NDMxMDA5MDE= | 10,884 | BUG: 10720 - Test error message enhancement | {
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Let me know what you think.
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-08-22T11:05:50Z | 2015-08-24T11:37:58Z | 2015-08-24T11:37:58Z | NONE | null | Hi Pandas devs!
This call produces 3 timestamps when it has to produce only two:
pd.date_range('2005-01-12 10:00', '2005-01-12 16:00', freq='345min')
this gives:
<class 'pandas.tseries.index.DatetimeIndex'>
[2005-01-12 10:00:00, ..., 2005-01-12 **21:30:00**]
Length: 3, Freq: 345T, Timezone: None
strangely, for an... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-08-22T12:15:06Z | 2015-08-31T01:03:13Z | 2015-08-31T01:03:13Z | MEMBER | null | Follow-up for #10726.
There, the specific section on sorting in basics.rst is adapted, but the rest of the docs should be updated as well.
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https://api.github.com/repos/pandas-dev/pandas/issues/10887 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10887/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10887/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10887/events | https://github.com/pandas-dev/pandas/pull/10887 | 102,542,391 | MDExOlB1bGxSZXF1ZXN0NDMxMDQ1NjM= | 10,887 | BUG: GH10885 where an edge case in date_range produces an extra point | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-08-22T14:48:11Z | 2015-08-24T13:59:27Z | 2015-08-24T11:37:59Z | CONTRIBUTOR | null | closes #10885
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https://api.github.com/repos/pandas-dev/pandas/issues/10888 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10888/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10888/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10888/events | https://github.com/pandas-dev/pandas/issues/10888 | 102,543,733 | MDU6SXNzdWUxMDI1NDM3MzM= | 10,888 | Unexpected keyword argument for some arguments documented in to_latex | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-08-22T15:07:09Z | 2015-09-09T14:56:11Z | 2015-09-09T14:56:11Z | NONE | null | To reproduce the errors:
```
import pandas as pd
names = ['Bob','Jessica','Mary','John','Mel']
births = [968, 155, 77, 578, 973]
BabyDataSet = zip(names, births)
df = pd.DataFrame(data=BabyDataSet, columns=['Names', 'Births'])
```
Any of these will yield a `TypeError`:
```
print df.to_latex(frame=None)
print df.to_... | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-08-22T20:20:30Z | 2015-08-28T02:29:10Z | 2015-08-28T02:29:04Z | CONTRIBUTOR | null | closes #10366
replaces #10454
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https://api.github.com/repos/pandas-dev/pandas/issues/10890 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10890/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10890/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10890/events | https://github.com/pandas-dev/pandas/pull/10890 | 102,569,437 | MDExOlB1bGxSZXF1ZXN0NDMxMTA5Mjc= | 10,890 | DEPR: Bunch o deprecation removals | {
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remove `colSpace`
remove auto time series broadcasting, xref #2304
deprecate `TimeSeries` (forgot was not actually deprecated)
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] | closed | false | null | [] | null | 7 | 2015-08-23T05:49:25Z | 2021-04-18T23:25:20Z | 2021-04-18T23:25:20Z | CONTRIBUTOR | null | I'm doing this:
``` python
df[df.CHANNEL=='MUV'].loc['2015'].DET_TEMP.plot()
```
with the index being a DatetimeIndex and if I don't plot it all works fine:
``` python
df[df.CHANNEL=='MUV'].loc['2015'][['CHANNEL','DET_TEMP']].head()
```
![screenshot 2015-08-22 23 47 18](https://cloud.githubusercontent.com/assets/69... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-08-23T12:44:39Z | 2015-08-24T18:24:19Z | 2015-08-24T18:24:19Z | CONTRIBUTOR | null | - Remove the table keyword in HDFStore.put/append, in favor of using format= #4645
- Remove unused keyword `kind` in `read_excel/ExcelFile` #4712
- Remove `infer_type` keyword from `pd.read_html` as its unused, #4770, #7032
- Remove `offset` and `timeRule` keywords from `Series.tshift/shift`, in favor of `freq`, #4853... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10893 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10893/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10893/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10893/events | https://github.com/pandas-dev/pandas/issues/10893 | 102,645,959 | MDU6SXNzdWUxMDI2NDU5NTk= | 10,893 | DOC: date_range docstring should list allowed frequencies | {
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---
So far it just says this:
```
freq : string or DateOffset, default ‘D’ (calendar daily)
Frequency strings can have multiples, e.g. ‘5H’
```
but it should also either refer to a doc where possible frequencies are being discussed or list them here.
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on master:
``` ipython
In [2]: df = pd.DataFrame({'a': np.random.randint(10000, size=100000),
...: 'b': np.random.randint(10, size=100000)})
In [3]: %timeit df.groupby('a')['b'].nunique()
1 loops, best of 3: 1.66 s per loop
In [4]: %timeit d... | {
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It would be great to see easy import a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10897 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10897/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10897/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10897/events | https://github.com/pandas-dev/pandas/issues/10897 | 102,851,965 | MDU6SXNzdWUxMDI4NTE5NjU= | 10,897 | Handle between_time on empty series | {
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``` python
import datetime as dt
import pandas as pd
s = pd.Series([])
s.between_time(dt.time(0, 0), dt.ti... | {
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"descript... | closed | false | null | [] | null | 5 | 2015-08-24T18:08:28Z | 2015-08-26T14:28:48Z | 2015-08-26T01:13:13Z | CONTRIBUTOR | null | Here's my file:
```
;;;;
;;;;
;;;;
;;;;
;;;;
;;;;
;;;;
;;;;
;;;;
;;;;
date;Param1;Param2;Param4;Param5
;m²;°C;m²;A
;;;;
01.01.1990 00:00;1;1;2;3
01.01.1990 01:00;5;3;4;5
01.01.1990 02:00;9;5;6;7
01.01.1990 03:00;13;7;8;9
01.01.1990 04:00;17;9;10;11
01.01.1990 05:00;21;11;12;13
```
If I read it with the fo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10899 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10899/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10899/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10899/events | https://github.com/pandas-dev/pandas/issues/10899 | 102,883,035 | MDU6SXNzdWUxMDI4ODMwMzU= | 10,899 | read_sql should accept a sql_params parameter | {
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I wonder if current use of `read_sql` couldn't lead to SQL injection.
I read in https://docs.python.org/2/library/sqlite3.html
```
# Never do this -- insecure!
symbol = 'RHAT'
c.execute("SELECT * FROM stocks WHERE symbol = '%s'" % symbol)
# Do this instead
t = ('RHAT',)
c.execute('SELECT * FROM stocks WHERE ... | {
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"de... | closed | false | null | [] | null | 5 | 2015-08-24T23:33:32Z | 2015-08-26T01:09:52Z | 2015-08-26T00:57:14Z | CONTRIBUTOR | null | I am quite perplexed about this:
A function applied to rows of dataframes that returns a tuple throws an error if the result is stored into a new column, but does not if the column already exists? This does not happen if I return just a number.
Get the example notebook here:
https://gist.github.com/a83ed19c43fe2eaac6a... | {
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I'm using fused types here instead of adding to `generated.pyx` - as far as I can tell that is working well, looking back through the ol... | {
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"name": "Enhancement",
"node_id": "MDU6TGFiZWw3NjgxMg==",
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"description": "DateOffs... | open | false | null | [] | {
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"created_at": "2015-01-13T10:53:19Z",
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... | 6 | 2015-08-25T09:37:43Z | 2019-10-21T19:52:15Z | null | NONE | null | It is convenient to be able to add one DateOffset to another one:
``` python
from pandas.tseries.offsets import DateOffset as DO
DO(hour=2) + DO(hour=3) # raises ValueError
```
Currently it is not supported. Note that `DateOffset`s basically replicates the functionality of `relativedelta`s from `dateutil` module whic... | {
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