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https://api.github.com/repos/pandas-dev/pandas/issues/7501 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7501/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7501/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7501/events | https://github.com/pandas-dev/pandas/issues/7501 | 36,024,133 | MDU6SXNzdWUzNjAyNDEzMw== | 7,501 | Can't slice float indices, but can slice integer indices? | {
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... | 94 | 2014-06-18T20:26:40Z | 2020-04-15T22:12:59Z | null | NONE | null | Using pandas 0.14, the slicing changed strangely. I can slice rows using start/end with an integer index, but not a float index:
``` python
In [18]: df = pandas.DataFrame(np.random.randn(10, 5), index=np.arange(10, 20))
In [19]: df
Out[19]:
0 1 2 3 4
10 -1.878123 -0.581537... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7502 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7502/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7502/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7502/events | https://github.com/pandas-dev/pandas/pull/7502 | 36,026,249 | MDExOlB1bGxSZXF1ZXN0MTczMTg1MzA= | 7,502 | BUG: offsets.apply may return datetime | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-06-18T20:50:11Z | 2014-06-21T22:30:16Z | 2014-06-21T20:13:29Z | MEMBER | null | Currently, `offsets.appy`, `rollforward` and `rollback` returns `Timestamp` if argument is `Timestamp` or `np.datetime64`.
If input is `datetime`, these functions return `datetime` or `Timestamp` inconsistently depending on internal process. It may better to always return `Timestanp`?
### Affected Offsets
- 'pandas.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7503 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7503/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7503/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7503/events | https://github.com/pandas-dev/pandas/pull/7503 | 36,030,176 | MDExOlB1bGxSZXF1ZXN0MTczMjEyODQ= | 7,503 | BUG: Bug in timeops with non-aligned Series (GH7500) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7504 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7504/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7504/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7504/events | https://github.com/pandas-dev/pandas/pull/7504 | 36,031,422 | MDExOlB1bGxSZXF1ZXN0MTczMjIxMjA= | 7,504 | BUG: float64index slicing with getitem bug | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7505 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7505/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7505/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7505/events | https://github.com/pandas-dev/pandas/pull/7505 | 36,034,733 | MDExOlB1bGxSZXF1ZXN0MTczMjQzNTM= | 7,505 | BUG, TST: Fix pandas.core.strings.str_contains when handling regex=False and case=False | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7506 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7506/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7506/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7506/events | https://github.com/pandas-dev/pandas/pull/7506 | 36,040,109 | MDExOlB1bGxSZXF1ZXN0MTczMjc3ODE= | 7,506 | BUG: Bug in DataFrame.where with a symmetric shaped frame and a passed other of a DataFrame | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7507 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7507/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7507/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7507/events | https://github.com/pandas-dev/pandas/issues/7507 | 36,041,464 | MDU6SXNzdWUzNjA0MTQ2NA== | 7,507 | BUG: np.round()/np.around() fails on Float64Index | {
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] | closed | false | null | [] | null | 2 | 2014-06-19T00:55:50Z | 2014-06-19T11:40:26Z | 2014-06-19T11:40:20Z | NONE | null | Seems that it's looking for an attribute that's invalid.
```
print type(idx)
<class 'pandas.core.index.Float64Index'>
```
Where I created Float64Index elsewhere...
```
np.round(idx)
Traceback (most recent call last):
File "/home/glue/Desktop/PYUVVIS/pyuvvis/pyuvvis/core/timespectra.py", line 1, in <module>
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https://api.github.com/repos/pandas-dev/pandas/issues/7508 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7508/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7508/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7508/events | https://github.com/pandas-dev/pandas/issues/7508 | 36,079,905 | MDU6SXNzdWUzNjA3OTkwNQ== | 7,508 | Incorrect truncating of Series according to max_rows | {
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```
In [146]: s = pd.Series(np.random.randn(20))
In [147]: pd.options.display.max_rows = 10
In [148]: s
Out[148]:
0 1.545202
1 -1.427565
2 -0.961094
...
17 0.125228
18 2.153724
19 -0.384024
Length: 20, dtype: float... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7509 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7509/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7509/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7509/events | https://github.com/pandas-dev/pandas/issues/7509 | 36,085,695 | MDU6SXNzdWUzNjA4NTY5NQ== | 7,509 | combine_first not retaining dtypes | {
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``` python
In [1]: from datetime import datetime
In [2]: import pandas as pd
In [3]: pd.__version__
Out[3]: '0.13.1'
In [4]: dfa = pd.DataFrame([[datetime.now(), 2]], columns=['a','b... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7510 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7510/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7510/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7510/events | https://github.com/pandas-dev/pandas/issues/7510 | 36,086,422 | MDU6SXNzdWUzNjA4NjQyMg== | 7,510 | CI: use cython 0.20.1 for build/test | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-06-19T15:01:01Z | 2014-06-20T22:15:59Z | 2014-06-20T22:15:59Z | CONTRIBUTOR | null | some warnings are generated (parser.pyx, msgpack.pyx) that are new
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https://api.github.com/repos/pandas-dev/pandas/issues/7511 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7511/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7511/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7511/events | https://github.com/pandas-dev/pandas/issues/7511 | 36,094,900 | MDU6SXNzdWUzNjA5NDkwMA== | 7,511 | Unhelpful error message when groupby() called with a column that is duplicated | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-06-19T16:31:31Z | 2014-09-10T19:51:03Z | 2014-09-10T19:51:03Z | NONE | null | The following code:
```
import pandas as pd
p1 = {'name': 'willy', 'age': 10}
p2 = {'name': 'willy', 'age': 11}
p3 = {'name': 'zoe', 'age': 10}
df = pd.DataFrame([p1, p2, p3])
df = df[['name','name','age']]
df.groupby('name')
```
gives the following error:
```
TypeError: 'DataFrame' object is not callable
```
Inste... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7512 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7512/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7512/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7512/events | https://github.com/pandas-dev/pandas/issues/7512 | 36,098,746 | MDU6SXNzdWUzNjA5ODc0Ng== | 7,512 | BUG: {expanding,rolling}_{cov,corr} functions between objects with different index sets | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2014-06-19T17:16:44Z | 2014-07-01T10:14:18Z | 2014-07-01T10:14:18Z | CONTRIBUTOR | null | related #7514
There appears to be a bug in the expanding_{cov,corr} functions when dealing with two objects with different indexes.
First, there is a problem with series. See example below, where I would expect expanding_corr(s1, s2) to produce the result produced by expanding_corr(s1, s2a).
The problem is due to th... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7513 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7513/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7513/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7513/events | https://github.com/pandas-dev/pandas/issues/7513 | 36,105,669 | MDU6SXNzdWUzNjEwNTY2OQ== | 7,513 | concat all the things | {
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"f... | 2 | 2014-06-19T18:39:52Z | 2021-04-11T04:50:37Z | 2021-04-11T04:50:37Z | CONTRIBUTOR | null | Faster way to concat a mixture of of axis=0 and axis=1 (axis='meh') ?
I don't know what a good api would be for this... (assuming there isn't one already).
http://stackoverflow.com/a/24301138/1240268
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https://api.github.com/repos/pandas-dev/pandas/issues/7514 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7514/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7514/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7514/events | https://github.com/pandas-dev/pandas/issues/7514 | 36,110,467 | MDU6SXNzdWUzNjExMDQ2Nw== | 7,514 | BUG: _flex_binary_moment() problems with different index sets | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2014-06-19T19:36:24Z | 2014-06-28T17:29:42Z | 2014-06-28T17:29:42Z | CONTRIBUTOR | null | There are several issues with _flex_binary_moment().
A. When pairwise=True, it doesn't properly handle two DataFrames with different index sets. In the following example, I believe [6], [7], and [8] should all produce the result in [9].
```
In [1]: from pandas import DataFrame, expanding_corr
In [2]: df1 = DataFrame... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7515 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7515/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7515/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7515/events | https://github.com/pandas-dev/pandas/pull/7515 | 36,110,874 | MDExOlB1bGxSZXF1ZXN0MTczNzE1ODY= | 7,515 | BUG: area plot raises ValueError with tz-aware data | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-06-19T19:41:30Z | 2014-07-05T04:46:54Z | 2014-07-05T01:31:30Z | MEMBER | null | Closes #7471.
Must be revisit after #7322.
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https://api.github.com/repos/pandas-dev/pandas/issues/7516 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7516/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7516/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7516/events | https://github.com/pandas-dev/pandas/issues/7516 | 36,115,960 | MDU6SXNzdWUzNjExNTk2MA== | 7,516 | BUG: Panel.iloc[] bug with MultiIndex axis (another one) | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-06-19T20:44:59Z | 2014-06-20T12:04:29Z | 2014-06-20T12:04:29Z | CONTRIBUTOR | null | I'd expect the [7] to produce the same result as [6], but instead it gives an error.
```
Python 3.4.0 (v3.4.0:04f714765c13, Mar 16 2014, 19:25:23) [MSC v.1600 64 bit (AMD64)]
Type "copyright", "credits" or "license" for more information.
IPython 2.1.0 -- An enhanced Interactive Python.
? -> Introduction and o... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7517 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7517/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7517/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7517/events | https://github.com/pandas-dev/pandas/issues/7517 | 36,123,939 | MDU6SXNzdWUzNjEyMzkzOQ== | 7,517 | Unable to import pandas | {
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] | closed | false | null | [] | null | 12 | 2014-06-19T22:18:08Z | 2020-03-20T13:36:38Z | 2014-10-05T01:01:36Z | NONE | null | I've installed pandas using pip. I got the following versions of pip and numpy:
```
pvadrevu@MacPro~$ sudo pip freeze|grep pandas
pandas==0.14.0
pvadrevu@MacPro~$ sudo pip freeze|grep numpy
numpy==1.8.1
```
I am using this on OSX 10.9.2. I get the following error when trying to import pandas
```
numpy.dtype has the ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7518 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7518/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7518/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7518/events | https://github.com/pandas-dev/pandas/issues/7518 | 36,129,620 | MDU6SXNzdWUzNjEyOTYyMA== | 7,518 | read_csv() ignores na_filter=False for index columns | {
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"followers_url": "https://api.github.com/users/jorisva... | 6 | 2014-06-19T23:49:06Z | 2017-12-22T19:19:01Z | 2017-12-22T19:18:44Z | NONE | null | Using 0.14.0. `pandas.io.parsers.read_csv` is supposed to ignore blank-looking values if `na_filter=False`, but it **does not do this** for `index_col` columns.
foo.csv:
```
fruit,size,sugar
apples,medium,2
pear,medium,3
grape,small,4
durian,,1
```
The default behavior gives a dataframe with a NaN in place of the em... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7519 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7519/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7519/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7519/events | https://github.com/pandas-dev/pandas/pull/7519 | 36,132,225 | MDExOlB1bGxSZXF1ZXN0MTczODQ3MjY= | 7,519 | BUG: Bug in Panel indexing with a multi-index axis (GH 7516) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7520 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7520/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7520/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7520/events | https://github.com/pandas-dev/pandas/issues/7520 | 36,135,356 | MDU6SXNzdWUzNjEzNTM1Ng== | 7,520 | ubuntu 12.04: test_nanargmin failure | {
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] | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-06-20T02:21:00Z | 2014-06-21T13:40:30Z | 2014-06-21T13:40:30Z | CONTRIBUTOR | null | ```
======================================================================
ERROR: test_nanargmin (pandas.tests.test_nanops.TestnanopsDataFrame)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/tmp/buildd/pandas-0.14.0+git213-g741b2fa/debian/tmp/usr/lib/p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7521 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7521/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7521/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7521/events | https://github.com/pandas-dev/pandas/pull/7521 | 36,136,678 | MDExOlB1bGxSZXF1ZXN0MTczODczMzQ= | 7,521 | DOC: fix startrow typo in docstrings | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7522 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7522/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7522/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7522/events | https://github.com/pandas-dev/pandas/issues/7522 | 36,148,205 | MDU6SXNzdWUzNjE0ODIwNQ== | 7,522 | API: fancier fancy indexing to enable coordinate lookup? | {
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"gists_url": "https://... | [] | closed | false | null | [] | null | 6 | 2014-06-20T08:08:46Z | 2014-07-10T18:20:41Z | 2014-07-07T15:44:16Z | CONTRIBUTOR | null | While wading through setitem-related code I've come across a reference to a GH issue (?? — _will fill this in later, the browser history is on a different computer_), where a poster complained about weird numpy fancy indexing:
``` python
In [11]: arr = np.arange(27).reshape(3,3,3)
In [12]: arr
Out[12]:
array([[[ 0, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7523 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7523/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7523/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7523/events | https://github.com/pandas-dev/pandas/issues/7523 | 36,156,884 | MDU6SXNzdWUzNjE1Njg4NA== | 7,523 | Slicing non-unique index fails when slice endpoint is not in index | {
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"color": "e1... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2014-06-20T10:32:59Z | 2014-06-20T13:53:41Z | 2014-06-20T13:53:41Z | CONTRIBUTOR | null | This looks like a regression from 0.13.1. If you have a simple dataframe with a non-unique but sorted index like:
``` python
df = pd.DataFrame(np.arange(5.), index=[datetime(2001, 1, i, 10, 00)
for i in [1,2,2,3,4]])
df
Out[23]:
0
2001-01-01 10:00:00 0
200... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7524 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7524/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7524/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7524/events | https://github.com/pandas-dev/pandas/issues/7524 | 36,161,695 | MDU6SXNzdWUzNjE2MTY5NQ== | 7,524 | TST: YahooOptions get_all_data failure | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-06-20T12:02:05Z | 2014-06-21T13:48:20Z | 2014-06-21T13:48:20Z | CONTRIBUTOR | null | cc @dstephens99
Almost certainly a bad data failure
for the first should guard this with a `try: except:` (and make that value nan)
2nd needs a guard on the test to skip with a RemoteError? (I think this is done with some of the other tests)?
```
======================================================================... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7525 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7525/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7525/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7525/events | https://github.com/pandas-dev/pandas/pull/7525 | 36,165,348 | MDExOlB1bGxSZXF1ZXN0MTc0MDQxNzg= | 7,525 | REGR: Regression in datetimelike slice indexing with a duplicated index and non-exact end-points (GH7523) | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-06-20T13:05:25Z | 2014-06-20T13:53:41Z | 2014-06-20T13:53:41Z | CONTRIBUTOR | null | closes #7523
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https://api.github.com/repos/pandas-dev/pandas/issues/7526 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7526/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7526/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7526/events | https://github.com/pandas-dev/pandas/issues/7526 | 36,170,198 | MDU6SXNzdWUzNjE3MDE5OA== | 7,526 | Handling datetimes in columns | {
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"color": "005... | closed | false | null | [] | null | 6 | 2014-06-20T14:10:38Z | 2014-06-20T15:08:15Z | 2014-06-20T14:53:21Z | CONTRIBUTOR | null | I couldn't see anything like this in the issues list. It's a change in behaviour between `0.13.1` and `master/HEAD` which might be intended, might not :)
Suppose you create a dataframe like this:
``` python
from datetime import datetime
B = pd.DataFrame(data = np.array([[1, datetime(2001, 1, 1)],
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https://api.github.com/repos/pandas-dev/pandas/issues/7527 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7527/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7527/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7527/events | https://github.com/pandas-dev/pandas/issues/7527 | 36,173,665 | MDU6SXNzdWUzNjE3MzY2NQ== | 7,527 | Strange reindex behavior | {
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regressors = regressors.reindex(index=factors.index)
logger.debug('Regressors have the same index as factors: {}'.format(regressors.index is factors.index))
logger.debug('Regressors and factors indexes are the same: {}'.format(all(map(lambda x, y: x == y, regressors.index, factors.index))))
```
Results in this:
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https://api.github.com/repos/pandas-dev/pandas/issues/7528 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7528/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7528/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7528/events | https://github.com/pandas-dev/pandas/issues/7528 | 36,198,480 | MDU6SXNzdWUzNjE5ODQ4MA== | 7,528 | BUG: Bad axis limits when using DataFrame.boxplot() with odd number of columns (excluding 1) and 'by' parameter. | {
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... | closed | false | null | [] | {
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```
count1 count2 totalcount season
0 3 13 16 1
1 8 32 40 1
2 5 27 32 1
3 3 10 13 1
4 0 1 1 1
```
I'd... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7529 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7529/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7529/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7529/events | https://github.com/pandas-dev/pandas/pull/7529 | 36,199,958 | MDExOlB1bGxSZXF1ZXN0MTc0MjYwNzg= | 7,529 | BUG: DatetimeIndex comparison handles NaT incorrectly | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-06-20T20:28:40Z | 2014-06-21T02:39:07Z | 2014-06-20T21:38:59Z | MEMBER | null | Derived from #7485. Comparison with `DatetimeIndex` result incorrectly if `NaT` is included.
```
idx1 = pd.DatetimeIndex(['2011-01-01', pd.NaT], freq='M')
idx2 = pd.DatetimeIndex([pd.NaT, '2011-01-01'], freq='M')
print(idx1 > idx2)
# [True, False]
# it must be [False, False]
```
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https://api.github.com/repos/pandas-dev/pandas/issues/7530 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7530/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7530/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7530/events | https://github.com/pandas-dev/pandas/pull/7530 | 36,211,112 | MDExOlB1bGxSZXF1ZXN0MTc0MzMzNDA= | 7,530 | TST: io.data.Options changes to avoid test failures on bad data. | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-06-20T23:46:44Z | 2014-06-21T13:48:24Z | 2014-06-21T13:48:20Z | CONTRIBUTOR | null | Added try, except to underlying price / quote_time function.
Changed to RemoteDataError in the event that some tables are found, but the correct table is not available.
Fixes #7524.
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https://api.github.com/repos/pandas-dev/pandas/issues/7531 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7531/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7531/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7531/events | https://github.com/pandas-dev/pandas/pull/7531 | 36,216,708 | MDExOlB1bGxSZXF1ZXN0MTc0MzYzNjQ= | 7,531 | WIP/ENH: allow read_excel to accept URLs (GH6809) | {
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This borrows the mechanisms already used in read_csv to enable reading of Excel objects via URLs.
Not sure what tests are appropriate, and I'm not certain what the various decorators do, so I tried to mirror the read_csv tests as best I could.
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https://api.github.com/repos/pandas-dev/pandas/issues/7532 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7532/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7532/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7532/events | https://github.com/pandas-dev/pandas/pull/7532 | 36,218,395 | MDExOlB1bGxSZXF1ZXN0MTc0MzcxODQ= | 7,532 | BUG: single column bar plot is misaligned | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7533 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7533/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7533/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7533/events | https://github.com/pandas-dev/pandas/pull/7533 | 36,219,000 | MDExOlB1bGxSZXF1ZXN0MTc0Mzc0MjY= | 7,533 | BUG: df.reset_index loses tz | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7534 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7534/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7534/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7534/events | https://github.com/pandas-dev/pandas/pull/7534 | 36,219,095 | MDExOlB1bGxSZXF1ZXN0MTc0Mzc0NzE= | 7,534 | BUG: Timestamp.tz_localize resets nanosecond | {
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```
t = pd.Timestamp('2011-01-01') + pd.offsets.Nano(1)
t.tz_localize('US/Eastern')
# Warning: discarding nonzero nanoseconds
#2011-01-01 00:00:00-05:00
```
Even though `DatetimeIndex.tz_convert` can preserve it.
```
idx = pd.date_range('3/11/2012 04:00', periods=10, freq... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7535 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7535/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7535/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7535/events | https://github.com/pandas-dev/pandas/pull/7535 | 36,223,426 | MDExOlB1bGxSZXF1ZXN0MTc0MzkxMzE= | 7,535 | should fix issue #7520, test_nanargmin fails with datetime64 objects | {
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"d... | closed | false | null | [] | null | 4 | 2014-06-21T12:52:19Z | 2014-06-26T10:28:55Z | 2014-06-21T13:40:17Z | CONTRIBUTOR | null | I think this will fix the issue #7520. The issue appears to be that older versions of `numpy`, probably less than `1.7.0`, can't handle `datetime64` dtypes very well. I have added simple check to see if `numpy` can handle a standard operation with `datetime64` dtypes, and if not it skips those tests.
I can't test th... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7536 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7536/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7536/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7536/events | https://github.com/pandas-dev/pandas/issues/7536 | 36,224,818 | MDU6SXNzdWUzNjIyNDgxOA== | 7,536 | CLN: frame.py executable? | {
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```
-rwxr-xr-x 1 dsm dsm 178861 Jun 21 09:51 pandas/core/frame.py
```
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https://api.github.com/repos/pandas-dev/pandas/issues/7537 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7537/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7537/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7537/events | https://github.com/pandas-dev/pandas/pull/7537 | 36,225,131 | MDExOlB1bGxSZXF1ZXN0MTc0Mzk4NTk= | 7,537 | CLN: Remove executable flag from frame.py | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7538 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7538/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7538/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7538/events | https://github.com/pandas-dev/pandas/pull/7538 | 36,225,406 | MDExOlB1bGxSZXF1ZXN0MTc0NDAwMDI= | 7,538 | DOC: Release note correction for GH7534 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7539 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7539/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7539/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7539/events | https://github.com/pandas-dev/pandas/issues/7539 | 36,225,901 | MDU6SXNzdWUzNjIyNTkwMQ== | 7,539 | API: DatetimeIndex.asobject raises ValueError when contains NaT | {
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Currently, `DatetimeIndex.asobject` raises `ValueError` when it contains `NaT`, otherwise `PeriodIndex` doesn't inconsistently.
I think these should work the same way, and would like to confirm `PeriodIndex` should raise `ValueError`, or `DatetimeIndex.asobject` allows `NaT`. There may be historical... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7540 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7540/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7540/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7540/events | https://github.com/pandas-dev/pandas/issues/7540 | 36,226,043 | MDU6SXNzdWUzNjIyNjA0Mw== | 7,540 | BUG/API: PeriodIndex.unique returns ndarray | {
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I'd like to ask which is better to fix all `Index.unique` to return `Index` for consistency, o... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7541 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7541/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7541/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7541/events | https://github.com/pandas-dev/pandas/pull/7541 | 36,230,320 | MDExOlB1bGxSZXF1ZXN0MTc0NDIyMzI= | 7,541 | BUG: expanding_{cov,corr} for objects of different lengths | {
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"description": "Arithmetic, Comparison, ... | closed | false | null | [] | null | 4 | 2014-06-21T19:27:09Z | 2014-06-28T13:54:28Z | 2014-06-28T13:54:28Z | CONTRIBUTOR | null | Closes https://github.com/pydata/pandas/issues/7512 and https://github.com/pydata/pandas/issues/7514.
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https://api.github.com/repos/pandas-dev/pandas/issues/7542 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7542/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7542/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7542/events | https://github.com/pandas-dev/pandas/issues/7542 | 36,230,536 | MDU6SXNzdWUzNjIzMDUzNg== | 7,542 | BUG: _flex_binary_moment() doesn't preserve column order or handle multiple columns with the same label | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-06-21T19:39:51Z | 2014-07-25T14:34:07Z | 2014-07-25T14:34:07Z | CONTRIBUTOR | null | _flex_binary_moment() sorts the columns alphabetically. I think it should preserve the order.
```
In [23]: df = DataFrame([[2,4],[1,2],[5,2],[8,1]], columns=['B','A'])
In [24]: expanding_corr(df, df, pairwise=True)[3]
Out[24]:
A B
A 1.000000 -0.670166
B -0.670166 1.000000
```
(I originally mentio... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7543 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7543/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7543/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7543/events | https://github.com/pandas-dev/pandas/issues/7543 | 36,231,873 | MDU6SXNzdWUzNjIzMTg3Mw== | 7,543 | BUG: ewma() doesn't adjust weights properly for missing values | {
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"followers_url": "https://api.github.com/users/jr... | 11 | 2014-06-21T21:01:56Z | 2014-07-24T17:07:33Z | 2014-07-24T17:07:33Z | CONTRIBUTOR | null | I mentioned this originally on https://groups.google.com/forum/#!topic/pydata/woxbB8na3C8.
ewma() simply ignores missing values, effectively calculating the exponentially weighted moving average on the compacted series without the missing values. I think this is incorrect, and that values should be weighted based on t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7544 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7544/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7544/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7544/events | https://github.com/pandas-dev/pandas/pull/7544 | 36,234,242 | MDExOlB1bGxSZXF1ZXN0MTc0NDM5NjU= | 7,544 | BUG: DatetimeIndex.asobject raises ValueError when contains NaT | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2014-06-21T23:37:26Z | 2014-06-26T10:59:59Z | 2014-06-24T11:49:40Z | MEMBER | null | Closes #7539.
Also, this fixed #7112 case 3 and case 4 to preserve tz. I've modified the tests for it.
Related to #6469.
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https://api.github.com/repos/pandas-dev/pandas/issues/7545 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7545/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7545/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7545/events | https://github.com/pandas-dev/pandas/pull/7545 | 36,235,206 | MDExOlB1bGxSZXF1ZXN0MTc0NDQ0MTY= | 7,545 | DOC: Use correct, non-deprecated arg name | {
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] | closed | false | null | [] | null | 7 | 2014-06-22T02:44:32Z | 2017-05-20T13:16:58Z | 2015-10-20T22:26:27Z | NONE | null | Hi,
In R, there is a way to perform a rolling join as shown below.
library("data.table")
DT <-
data.table(
x = rep(c("a", "b", "c"), each = 3),
y = c(1, 3, 6),
v = 1:9)
setkey(DT, x, y) # Necessary for following self join.
DT[J("a", 4:6)]
DT[J("a", 4:6), roll = TRUE]
The relevant output looks like th... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7548 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7548/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7548/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7548/events | https://github.com/pandas-dev/pandas/issues/7548 | 36,247,844 | MDU6SXNzdWUzNjI0Nzg0NA== | 7,548 | BUG: tuple as index not possible anymore in pandas 0.14? | {
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... | 20 | 2014-06-22T17:23:48Z | 2018-12-11T06:29:52Z | 2018-12-11T06:29:52Z | NONE | null | I used to do convert a dict with tuple keys to DataFrame like
```
DataFrame.from_dict(a_dict, 'index')
```
but it produces "IndexError: index out of bounds" from pandas 0.14. Is there a way that I still can use tuple as Dataframe label? My old codes do not work with 0.14.
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https://api.github.com/repos/pandas-dev/pandas/issues/7549 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7549/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7549/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7549/events | https://github.com/pandas-dev/pandas/pull/7549 | 36,252,567 | MDExOlB1bGxSZXF1ZXN0MTc0NTE5ODA= | 7,549 | TST: some yahoo options tests missing network decorator | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7550 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7550/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7550/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7550/events | https://github.com/pandas-dev/pandas/pull/7550 | 36,290,641 | MDExOlB1bGxSZXF1ZXN0MTc0NzM3NjQ= | 7,550 | DOC: correct relase note | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7551 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7551/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7551/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7551/events | https://github.com/pandas-dev/pandas/issues/7551 | 36,306,798 | MDU6SXNzdWUzNjMwNjc5OA== | 7,551 | BUG: iloc setitem indexing with list of lists | {
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```
In [1]: df = DataFrame(dict(A = np.arange(5), B = np.arange(5,10)))
In [2]: df
Out[2]:
A B
0 0 5
1 1 6
2 2 7
3 3 8
4 4 9
In [4]: df.iloc[2:4] = [[10,11],[12,13]]
In [5]: df
Out[5]:
A B
0 0 5
1 1 6
2 10 11
3 12 13
4 4 9
```
```
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https://api.github.com/repos/pandas-dev/pandas/issues/7553 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7553/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7553/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7553/events | https://github.com/pandas-dev/pandas/pull/7553 | 36,316,542 | MDExOlB1bGxSZXF1ZXN0MTc0ODk3MDI= | 7,553 | DOC: fix docstring for DataFrame.interpolate | {
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"followers_url": "https://api.github.com/users/jr... | 15 | 2014-06-23T18:11:36Z | 2014-07-07T00:07:17Z | 2014-07-07T00:02:26Z | CONTRIBUTOR | null | In the old docstring, `'index'` is listed as a valid value for the `method` kwarg for `DataFrame.interpolate`. It looks like a typo, because there was no comma after `'index'`, and the explanation for `'index'` corresponded to `'values'`. Furthermore, it appears `'index'` is not a valid value for `method`:
``` python
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```
logger.debug('Indexes are identical: {}'.format(data_frame.index is categories.index))
logger.debug('Index is unique: {}'.format(data_frame.index.is_unique))
logger.debug('All columns are in data_frame: {}'.format(all(map(lambda x: x in data_frame, columns_regression))))
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https://api.github.com/repos/pandas-dev/pandas/issues/7555 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7555/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7555/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7555/events | https://github.com/pandas-dev/pandas/issues/7555 | 36,364,608 | MDU6SXNzdWUzNjM2NDYwOA== | 7,555 | Performance decrease of groupby.first for datetime64 in 0.14 | {
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Here is an example:
``` python
from time import time
d = pd.DataFrame({'a': pd.date_range('1/1/2011', periods=100000, freq='s'), 'b': range(100000)})
t = time()
d.groupby('b').first()
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https://api.github.com/repos/pandas-dev/pandas/issues/7556 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7556/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7556/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7556/events | https://github.com/pandas-dev/pandas/pull/7556 | 36,364,619 | MDExOlB1bGxSZXF1ZXN0MTc1MTkzMzE= | 7,556 | DOC: Cookbook recipe for emulating R's expand.grid() (#7426) | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-06-24T08:49:09Z | 2014-06-25T05:01:27Z | 2014-06-25T05:01:27Z | CONTRIBUTOR | null | closes #7426
As suggested by @jreback in #7426, I've added a quick cookbook recipe for emulating R's `expand.grid()`, which creates a dataframe from every combination of the values you give it.
None of the existing sections really seemed to apply, so I've added it in a new section.
Example usage:
``` python
import... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7557 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7557/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7557/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7557/events | https://github.com/pandas-dev/pandas/pull/7557 | 36,378,361 | MDExOlB1bGxSZXF1ZXN0MTc1Mjc5MzA= | 7,557 | BUG: isnull doesnt handle PeriodNaT properly | {
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... | 12 | 2014-06-24T12:20:47Z | 2015-11-14T05:26:39Z | 2015-05-09T16:08:45Z | MEMBER | null | Related to #7485, `isnull` and `notnull` is required to be changed.
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https://api.github.com/repos/pandas-dev/pandas/issues/7558 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7558/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7558/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7558/events | https://github.com/pandas-dev/pandas/issues/7558 | 36,378,515 | MDU6SXNzdWUzNjM3ODUxNQ== | 7,558 | Series.min(skipna=True) includes nan/inf? | {
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"description": "np.nan, pd.NaT, pd.NA, d... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-06-24T12:23:01Z | 2016-10-12T23:04:58Z | 2014-06-24T12:30:34Z | CONTRIBUTOR | null | ```
In[31]: s2 = pd.Series(["a","z",np.nan])
In[32]: s2.max()
Out[32]: 'z'
In[33]: s2.min()
Out[33]: inf
In[34]: s2.min(skipna=True)
Out[34]: inf
```
Reading the docs I get the impression that it should return "a" in both cases (as skipna defaults to True).
If so, #7217 also needs to change.
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https://api.github.com/repos/pandas-dev/pandas/issues/7559 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7559/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7559/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7559/events | https://github.com/pandas-dev/pandas/issues/7559 | 36,379,492 | MDU6SXNzdWUzNjM3OTQ5Mg== | 7,559 | BUG: groupby-nth failure | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-06-24T12:37:37Z | 2014-06-30T11:05:58Z | 2014-06-30T11:05:58Z | CONTRIBUTOR | null | This is a vbench/groupby.py
```
In [1]: df = DataFrame(np.random.randint(1, 100, (10000, 2)))
In [2]: df[1].groupby(df[0]).nth(0)
IndexError: index 9999 is out of bounds for size 9999
```
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https://api.github.com/repos/pandas-dev/pandas/issues/7560 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7560/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7560/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7560/events | https://github.com/pandas-dev/pandas/pull/7560 | 36,382,062 | MDExOlB1bGxSZXF1ZXN0MTc1MzAyNzY= | 7,560 | PERF: vbench for mixed groupby with datetime (GH7555) | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-06-24T13:13:05Z | 2014-06-24T13:32:37Z | 2014-06-24T13:32:37Z | CONTRIBUTOR | null | closes #7555
```
-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
groupby_mixed_first | 10.8150 | 3900... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7561 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7561/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7561/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7561/events | https://github.com/pandas-dev/pandas/issues/7561 | 36,387,692 | MDU6SXNzdWUzNjM4NzY5Mg== | 7,561 | TST: get options issue | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-06-24T14:15:47Z | 2014-06-25T14:50:17Z | 2014-06-25T14:50:17Z | CONTRIBUTOR | null | https://travis-ci.org/pydata/pandas/jobs/28313605
@cpcloud
cc @dstephens99
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https://api.github.com/repos/pandas-dev/pandas/issues/7562 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7562/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7562/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7562/events | https://github.com/pandas-dev/pandas/issues/7562 | 36,390,897 | MDU6SXNzdWUzNjM5MDg5Nw== | 7,562 | Timezone information lost after pandas.concat | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-06-24T14:46:40Z | 2017-11-22T03:28:03Z | 2014-06-24T14:50:40Z | NONE | null | I found that when using pandas.concat on dataframes with timezone information, the timezone might be lost when using 'innder' join:
```
In [1]: import pandas as pd
In [2]: import numpy as np
In [3]: from pandas.util.print_versions import show_versions
In [4]: show_versions()
INSTALLED VERSIONS
------------------
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https://api.github.com/repos/pandas-dev/pandas/issues/7563 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7563/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7563/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7563/events | https://github.com/pandas-dev/pandas/issues/7563 | 36,412,444 | MDU6SXNzdWUzNjQxMjQ0NA== | 7,563 | regex=False as default behavior, and expand regex disabling options | {
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... | 3 | 2014-06-24T18:34:15Z | 2021-04-11T04:51:12Z | null | CONTRIBUTOR | null | I was very happy to see pr #5879, allowing disabling the auto-regex feature for functions in the .str namespace. Doing something about this has been on my todo list for a while. Automatic promotion of strings to regular expressions is one of the two big points of difficulty for beginners using pandas (in my experience ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7564 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7564/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7564/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7564/events | https://github.com/pandas-dev/pandas/pull/7564 | 36,444,582 | MDExOlB1bGxSZXF1ZXN0MTc1Njk0NTQ= | 7,564 | TST: Remove else after except in tests for io.data.Options. | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-06-25T02:48:04Z | 2014-06-25T14:50:24Z | 2014-06-25T14:50:17Z | CONTRIBUTOR | null | Also moved no tables found error to get_options_tables method (url was not defined in the get_option_data method).
Fixes #7561
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https://api.github.com/repos/pandas-dev/pandas/issues/7565 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7565/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7565/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7565/events | https://github.com/pandas-dev/pandas/pull/7565 | 36,447,221 | MDExOlB1bGxSZXF1ZXN0MTc1NzA5OTE= | 7,565 | ENH: Implement _Openpyxl2Writer for pandas.io.excel | {
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closes #7177
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https://api.github.com/repos/pandas-dev/pandas/issues/7566 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7566/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7566/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7566/events | https://github.com/pandas-dev/pandas/pull/7566 | 36,449,057 | MDExOlB1bGxSZXF1ZXN0MTc1NzIwMDg= | 7,566 | DOC: Fix parameter in reindex_axis docstring | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7567 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7567/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7567/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7567/events | https://github.com/pandas-dev/pandas/issues/7567 | 36,457,081 | MDU6SXNzdWUzNjQ1NzA4MQ== | 7,567 | datetime64 columns not supported with sqlite fallback | {
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```
import sqlite3
con = sqlite3.connect(':memory:')
df = pd.DataFrame({'date':pd.date_range('2014-01-01', periods=10)})
df.to_sql('test_datetime', con, index=False, if_exists='append')
```
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https://api.github.com/repos/pandas-dev/pandas/issues/7568 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7568/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7568/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7568/events | https://github.com/pandas-dev/pandas/pull/7568 | 36,476,012 | MDExOlB1bGxSZXF1ZXN0MTc1ODgwNjA= | 7,568 | BUG/PERF: perf issues in object groupby aggregations (GH7555) | {
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```
-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
groupby_object_last | 15.2340 | 417... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7569 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7569/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7569/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7569/events | https://github.com/pandas-dev/pandas/issues/7569 | 36,477,399 | MDU6SXNzdWUzNjQ3NzM5OQ== | 7,569 | PERF: groupby nth w/o dropna can use the cython routines | {
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- `nth` is a fair bit slower than `first/last` which are calling cython routines. In a case where you don't `dropna` you can simply call the cython aggregation routines
- side issue is to move the `group_last_object/group_nth_object` from `algos.pyx` to `generate_code.py` (simply move `group_last/group_nth` ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7570 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7570/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7570/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7570/events | https://github.com/pandas-dev/pandas/issues/7570 | 36,480,588 | MDU6SXNzdWUzNjQ4MDU4OA== | 7,570 | PERF/API: alias len/size in groupby.transform | {
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... | 7 | 2014-06-25T13:46:48Z | 2021-04-11T04:51:39Z | null | CONTRIBUTOR | null | alias `len/size` to `groupby.transform` speedup table (as these are already implemented as `size`,`count`` in cython, just a matter of transforming them
see here: http://stackoverflow.com/questions/24438273/aggregation-on-pandas-datetime-series-only-returns-as-datetime-series/24438366#24438366
(`len` is suspect for `... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7571 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7571/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7571/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7571/events | https://github.com/pandas-dev/pandas/issues/7571 | 36,516,887 | MDU6SXNzdWUzNjUxNjg4Nw== | 7,571 | Long integer values are changed by pandas SQLite driver database using to_sql | {
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http://stackoverflow.com/questions/24416140/long-integer-values-in-pandas-dataframe-change-when-sent-to-sqlite-database-usin?noredirect=1#comment37772983_24416140
I am using pandas to organize and manipulate data I am getting from the twitter API. The 'id' key returns a very long integer (int64) that pandas has n... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7572 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7572/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7572/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7572/events | https://github.com/pandas-dev/pandas/pull/7572 | 36,544,184 | MDExOlB1bGxSZXF1ZXN0MTc2Mjk0Mzg= | 7,572 | BUG: Error in rolling_var if window is larger than array, fixes #7297 | {
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Other rolling window functions rely on the logic in `_check_minp`, and split the iteration into the ranges `[0, minp-1)` and `(minp-1, N)`. Because of the way `rolling_var` handles things, splitting the iteration into `[0, win)` and `(win, N)` makes more sense. Added also some comments as to what is going ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7573 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7573/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7573/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7573/events | https://github.com/pandas-dev/pandas/issues/7573 | 36,552,347 | MDU6SXNzdWUzNjU1MjM0Nw== | 7,573 | DOC: mention syntax for using parameters in read_sql in Notes in docstring | {
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Add a note mentioning this is driver-dependent which works, and they have to look at their drivers documentation.
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-06-26T13:28:07Z | 2014-07-02T16:04:34Z | 2014-07-02T16:04:34Z | CONTRIBUTOR | null | Suppose I have this simple DataFrame:
``` python
In [91]: df = pd.DataFrame({'ref':[1, 2, 3], 'symbol':['GOOGL', 'IBM', 'MSFT'], 'price':[585.93, 180.72, 42.03]}, columns=['ref', 'symbol', 'price'])
In [92]: df
Out[92]:
ref symbol price
0 1 GOOGL 585.93
1 2 IBM 180.72
2 3 MSFT 42.03
In [93]: ... | {
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... | 3 | 2014-06-26T15:02:17Z | 2021-04-11T04:51:56Z | null | CONTRIBUTOR | null | The `column_space` option doesn't seem to work.
```
In [28]: df=pd.DataFrame(np.array([np.random.randn(6), np.random.randint(1,9,6)*.1,
np.zeros(6)]).T, columns=['A', 'B', 'C'], dtype='float')
In [29]: pd.set_option('column_space', 12)
In [30]: df
Out[30]:
A B C
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```
In [24]: df=pd.DataFrame(np.random.randn(5,5), index=pd.date_range('1/15/2000',periods=5, freq='D'))
In [25]: pd.set_option('date_dayfirst', True)
In [26]: df
Out[26]:
0 1 2 3 4
2000-01-15 0.487978 -0.22... | {
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closes #3104
Breakout "options" section for docs, heavily using info already in `basics.rst`. Expands examples, and turns `describe_options` into a table.
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related #7287
And some improvements when using any/all for nth
(still the nth are 10x slower than the cythonized first/last, but that's another issue)
```
-------------------------------------------------------------------------------
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https://api.github.com/repos/pandas-dev/pandas/issues/7581 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7581/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7581/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7581/events | https://github.com/pandas-dev/pandas/pull/7581 | 36,609,541 | MDExOlB1bGxSZXF1ZXN0MTc2Njk0NTk= | 7,581 | SQL: don't reflect full database GH7396 | {
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For now, let PandasSQLAlchemy not reflect anything by default, and `read_sql_table` provides its own reflected meta. Had to change some of the other functions to get this working.
@danielballan @mangecoeur Can someone review? (it feeled a bit messy)
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closes #2685
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https://api.github.com/repos/pandas-dev/pandas/issues/7583 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7583/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7583/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7583/events | https://github.com/pandas-dev/pandas/issues/7583 | 36,627,214 | MDU6SXNzdWUzNjYyNzIxNA== | 7,583 | Pandas to_json changing dtype | {
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I create a dataframe with 2 integer columns and 1 float column
``` python
import pandas as pd
df = pd.DataFrame([[1,2,0.2],[3,2,0.1]])
df.info()
```
```
<class 'pandas.core.frame.DataFrame'>
Int64Index: 2 entries, 0 to 1
Data columns (total 3 columns):
0 2 non-null int... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7585 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7585/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7585/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7585/events | https://github.com/pandas-dev/pandas/issues/7585 | 36,638,675 | MDU6SXNzdWUzNjYzODY3NQ== | 7,585 | Chained assignment yields unexpected result with timedelta64 values (np v1.8, pd v0.13.1) | {
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```
In [2]: A = pd.DataFrame(np.random.rand(10,4), index=np.random.rand(10))
In [3]: A.loc[A.index] = A.loc[A.index]
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https://api.github.com/repos/pandas-dev/pandas/issues/7589 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7589/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7589/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7589/events | https://github.com/pandas-dev/pandas/issues/7589 | 36,667,985 | MDU6SXNzdWUzNjY2Nzk4NQ== | 7,589 | read_csv in Pandas 0.14 loads NaNs when namedtuple is used for column names | {
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"followers_url": "https://api.github... | 8 | 2014-06-27T14:20:31Z | 2018-07-25T12:05:57Z | 2018-07-25T12:05:56Z | CONTRIBUTOR | null | Using a `namedtuple` as a column name for `read_csv` in Pandas 0.14 results `NaNs` being loaded.
Here is a simple demonstration of the problem (this code works in Pandas 0.13.1):
``` python
import pandas as pd
from collections import namedtuple
from StringIO import StringIO
TestTuple = namedtuple('test', ['a'])
CSV... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7591 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7591/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7591/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7591/events | https://github.com/pandas-dev/pandas/pull/7591 | 36,691,650 | MDExOlB1bGxSZXF1ZXN0MTc3MTc5MDI= | 7,591 | ENH: read_{csv,table} look for index columns in row after header with C engine | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-06-27T18:25:31Z | 2014-06-30T21:05:10Z | 2014-06-30T19:26:49Z | CONTRIBUTOR | null | Closes #6893.
Currently the Python parser can read data with the index columns specified on the first line after the header, e.g.
``` python
In [3]: pd.__version__
Out[3]: '0.14.0-271-gf8b101c'
In [4]: text = """ A B C D E
one two three four
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https://api.github.com/repos/pandas-dev/pandas/issues/7594 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7594/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7594/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7594/events | https://github.com/pandas-dev/pandas/issues/7594 | 36,704,696 | MDU6SXNzdWUzNjcwNDY5Ng== | 7,594 | Timezone-aware times are inconsistent using object or datetime64 | {
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```
import pytz
import datetime
from pandas import DataFrame
tz = pytz.timezone('US/Eastern'... | {
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cc @dstephens99
@cpcloud
odd.?
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Allows `DatetimeIndex.__init__` to accept `NaT` string representation.
### Updated Description
The original problem is caused by the inconsistencies in parsing function. Make following results to be consistent.
```
date_str = '2011Q3'
pd.tseries.tools.parse_time_string(date_str)[0]
#2011-07-... | {
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- `GroupBy.size` created by `TimeGrouper` raises `AttributeError`
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