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https://api.github.com/repos/pandas-dev/pandas/issues/9202 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9202/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9202/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9202/events | https://github.com/pandas-dev/pandas/issues/9202 | 53,543,111 | MDU6SXNzdWU1MzU0MzExMQ== | 9,202 | Pandas Dataframe apply() method row object vanishes | {
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] | closed | false | null | [] | null | 4 | 2015-01-06T17:59:51Z | 2015-01-07T10:49:12Z | 2015-01-07T10:49:12Z | NONE | null | See the following code. Does it mean I have to go via route `.iterrows`?
``` python
df = pd.DataFrame({'x': range(5)})
df['y'] = df['x'].astype(str)
b = df.apply(lambda row: [row], axis=1)
0 [[nan, nan]]
1 [[nan, nan]]
2 [[nan, nan]]
3 [[nan, nan]]
4 [[nan, nan]]
```
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https://api.github.com/repos/pandas-dev/pandas/issues/9203 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9203/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9203/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9203/events | https://github.com/pandas-dev/pandas/pull/9203 | 53,555,192 | MDExOlB1bGxSZXF1ZXN0MjY5MTMwOTE= | 9,203 | DOC: Edited doc string of pandas/core/frame.duplicated(). Redefined take... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9204 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9204/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9204/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9204/events | https://github.com/pandas-dev/pandas/issues/9204 | 53,568,148 | MDU6SXNzdWU1MzU2ODE0OA== | 9,204 | BUG: wide_to_long modifies stubnames | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-01-06T21:51:56Z | 2015-01-18T20:59:16Z | 2015-01-18T20:59:16Z | CONTRIBUTOR | null | This is not a serious issue, but the list of stubnames passed into `wide_to_long` is modified by the function call.
## INSTALLED VERSIONS
commit: None
python: 2.7.6.final.0
python-bits: 64
OS: Linux
OS-release: 3.13.0-43-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
panda... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9205 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9205/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9205/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9205/events | https://github.com/pandas-dev/pandas/issues/9205 | 53,574,184 | MDU6SXNzdWU1MzU3NDE4NA== | 9,205 | pandas error kills IPython kernel | {
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"description": "read_csv, to_csv",
"... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 20 | 2015-01-06T22:52:45Z | 2015-02-05T11:35:06Z | 2015-02-05T11:35:06Z | CONTRIBUTOR | null | Doing this simple thing can kill an IPython 2 notebook kernel (version:GH master):
``` python
url = 'http://nssdc.gsfc.nasa.gov/planetary/factsheet/index.html'
pd.read_table(url)
```
Note that I know this will fail, I just don't expect it to kill a notebook kernel?
Version:
pandas: 128ce857f1cd
IPython: 13facaf02062... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9206 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9206/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9206/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9206/events | https://github.com/pandas-dev/pandas/pull/9206 | 53,649,428 | MDExOlB1bGxSZXF1ZXN0MjY5Njc1OTM= | 9,206 | 9203 SQUASHED - DOCS: doc string edited pandas/core/frame.duplicated() | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-01-07T16:16:56Z | 2015-01-07T16:33:34Z | 2015-01-07T16:25:16Z | CONTRIBUTOR | null | Redefined `take_last` variable in doc string. Original definition only
made sense for drop_duplicates()
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https://api.github.com/repos/pandas-dev/pandas/issues/9207 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9207/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9207/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9207/events | https://github.com/pandas-dev/pandas/issues/9207 | 53,651,896 | MDU6SXNzdWU1MzY1MTg5Ng== | 9,207 | Shift Inplace in DF | {
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"de... | closed | false | null | [] | null | 6 | 2015-01-07T16:36:26Z | 2018-02-22T19:58:37Z | 2015-01-09T02:39:02Z | NONE | null | Is it possible to add in place shifting
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https://api.github.com/repos/pandas-dev/pandas/issues/9208 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9208/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9208/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9208/events | https://github.com/pandas-dev/pandas/issues/9208 | 53,684,841 | MDU6SXNzdWU1MzY4NDg0MQ== | 9,208 | read_excel drops columns when reading a one row file with a MultiIndex | {
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"followers_url": "https://api.github... | 2 | 2015-01-07T21:32:12Z | 2018-11-14T19:14:49Z | 2018-11-13T17:32:52Z | CONTRIBUTOR | null | I'm seeing the weirdest error.
When I read an .xlsx excel file with only one row (example below)...
... and try to set the `index_col`, then pandas incorrectly reads the columns:
I.e. for a file with only one... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9209 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9209/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9209/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9209/events | https://github.com/pandas-dev/pandas/pull/9209 | 53,696,918 | MDExOlB1bGxSZXF1ZXN0MjY5OTcwMjE= | 9,209 | added mising numeric_only option for DataFrame.std/var/sem | {
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"followers_url": "https://api.github.com/users/jr... | 10 | 2015-01-07T23:36:46Z | 2015-04-29T15:31:04Z | 2015-03-12T12:08:53Z | CONTRIBUTOR | null | closes https://github.com/pydata/pandas/issues/9201, the `numeric_only` option is missing for `DataFrame.std()` (and also `DataFrame.var()` and `DataFrame.sem()`), this is a fix for it
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https://api.github.com/repos/pandas-dev/pandas/issues/9210 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9210/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9210/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9210/events | https://github.com/pandas-dev/pandas/pull/9210 | 53,704,864 | MDExOlB1bGxSZXF1ZXN0MjcwMDE5NTk= | 9,210 | BUG: bug in left join on multi-index with sort=True or nulls | {
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```
In [8]: left
Out[8]:
1st 2nd 3rd
0 c c 13
1 b b 79
2 a a 27
3 b b 27
4 c a 86
In [9]: right
Out[9]:
4th
1st 2nd
c a -86
b b -79
c c -13
b b -27
a a -27
```
`sort=True` is ignored, and the result is not sorted by the join key:
```
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https://api.github.com/repos/pandas-dev/pandas/issues/9211 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9211/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9211/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9211/events | https://github.com/pandas-dev/pandas/issues/9211 | 53,720,092 | MDU6SXNzdWU1MzcyMDA5Mg== | 9,211 | drop_duplicates() on a float64 type column containing NaN values will cause CPU 100% occupied forever | {
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"default"... | open | false | null | [] | null | 5 | 2015-01-08T06:43:25Z | 2020-05-13T02:10:10Z | null | NONE | null | I'm using 0.15.0 version, and I find when I apply drop_duplicates() on "PostCode" column, it will occupy all the CPU forever, and I have to kill the process to stop it.
dataset = pd.read_csv(dataset_path, encoding = 'GB2312')
dataset['PostCode'].drop_duplicates()
"PostCode" column contains a list of integers but with... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9212 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9212/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9212/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9212/events | https://github.com/pandas-dev/pandas/issues/9212 | 53,730,230 | MDU6SXNzdWU1MzczMDIzMA== | 9,212 | sort_index behavior differs for the same DataFrame? | {
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```
In [1]: import pandas as pd
In [2]: pd.__version__
Out[2]: '0.15.2'
In [3]: tuples = [(' foo', 'bar'), ('foo', 'bar'), (' foo ()'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9213 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9213/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9213/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9213/events | https://github.com/pandas-dev/pandas/issues/9213 | 53,744,252 | MDU6SXNzdWU1Mzc0NDI1Mg== | 9,213 | Indexing semantics vary according to runtime values | {
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"description": "Related to indexing o... | open | false | null | [] | null | 10 | 2015-01-08T12:14:10Z | 2021-04-12T04:49:54Z | null | CONTRIBUTOR | null | Depending on the runtime value used in `[` indexing on a series, the semantics may be array-indexing, or slicing based on a MultiIndex. This is extremely error-prone behavior in a very basic operation.
Is the answer that production code should always use `.loc`/`.ix` instead of `[`? If so, I don't think the [docs](htt... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9214 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9214/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9214/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9214/events | https://github.com/pandas-dev/pandas/issues/9214 | 53,813,014 | MDU6SXNzdWU1MzgxMzAxNA== | 9,214 | BUG/ENH: groupby head returns empty result for negative n | {
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... | 9 | 2015-01-08T23:02:53Z | 2019-12-11T16:20:58Z | 2019-12-11T16:20:57Z | CONTRIBUTOR | null | More drive-by reports. I'll try to close some of these issues sometime...
``` python
In [8]: s = pd.Series(np.random.randn(10))
In [9]: s.groupby(s > 0).apply(lambda x: x.head(-1)) # works nicely
Out[9]:
False 0 -0.277400
1 -0.875231
3 -0.315087
4 -0.966649
6 -0.474389
7... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9215 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9215/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9215/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9215/events | https://github.com/pandas-dev/pandas/pull/9215 | 53,819,553 | MDExOlB1bGxSZXF1ZXN0MjcwNzE3OTY= | 9,215 | BUG FIX: wide_to_long modifies stubnames | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2015-01-09T00:25:22Z | 2015-01-18T20:59:05Z | 2015-01-18T20:59:05Z | CONTRIBUTOR | null | Simple fix that prevents modification of the list `stubnames`, which is an argument to `wide_to_long`.
Closes #9204
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https://api.github.com/repos/pandas-dev/pandas/issues/9216 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9216/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9216/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9216/events | https://github.com/pandas-dev/pandas/issues/9216 | 53,822,681 | MDU6SXNzdWU1MzgyMjY4MQ== | 9,216 | No way to construct mixed dtype DataFrame without total copy, proposed solution | {
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"f... | 59 | 2015-01-09T01:12:00Z | 2021-05-18T22:11:05Z | null | NONE | null | After hours of tearing my hair, I've come to the conclusion that it is impossible to create a mixed dtype DataFrame without copying all of its data in. That is, no matter what you do, if you want to create a mixed dtype DataFrame, you will inevitably create a temporary version of the data (e.g. using np.empty), and the... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9217 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9217/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9217/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9217/events | https://github.com/pandas-dev/pandas/issues/9217 | 53,908,910 | MDU6SXNzdWU1MzkwODkxMA== | 9,217 | BUG/API: interpolate with limit=0 should mean no interpolation | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2015-01-09T20:05:25Z | 2017-02-14T13:34:23Z | 2017-02-14T13:34:23Z | MEMBER | null | Current behavior:
```
In [28]: s = pd.Series([1, 2, np.nan, np.nan, 5])
In [29]: s
Out[29]:
0 1
1 2
2 NaN
3 NaN
4 5
dtype: float64
In [30]: s.interpolate(limit=0)
Out[30]:
0 1
1 2
2 3
3 4
4 5
dtype: float64
```
But in fact, `limit=0` in contrast to `limit=None` should mean no interpol... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9218 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9218/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9218/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9218/events | https://github.com/pandas-dev/pandas/issues/9218 | 53,912,396 | MDU6SXNzdWU1MzkxMjM5Ng== | 9,218 | DOC/API: limit argument to interpolate is somewhat non-intuitive | {
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"description": "np.nan, pd.NaT, pd.NA... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 10 | 2015-01-09T20:40:56Z | 2018-08-31T18:37:25Z | 2015-09-01T12:04:25Z | MEMBER | null | The current documentation for the limit parameter looks like this:
```
limit : int, default None.
Maximum number of consecutive NaNs to fill.
```
Several features were not immediately obvious to me and could probably be resolved by slightly better docstring or API design:
1. What happens where the max number of c... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9219 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9219/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9219/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9219/events | https://github.com/pandas-dev/pandas/issues/9219 | 53,923,916 | MDU6SXNzdWU1MzkyMzkxNg== | 9,219 | DataFrame.to_hdf fails in Python 3.4 | {
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"descript... | closed | false | null | [] | null | 7 | 2015-01-09T22:35:44Z | 2017-03-28T12:48:04Z | 2015-01-09T23:16:46Z | CONTRIBUTOR | null | This may be more of a PyTables issue but it affects Pandas users too
``` Python
>>> import pandas as pd
>>> df = pd.DataFrame({'a': [1, 2, 3]})
>>> df.to_hdf('myfile.hdf5', '/data', append=True)
File "/home/mrocklin/Software/anaconda/envs/py34/lib/python3.4/site-packages/tables/attributeset.py", line 381, in _g__set... | {
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"f... | 9 | 2015-01-09T23:21:58Z | 2020-11-20T04:44:02Z | null | MEMBER | null | open issues & xref
* (fillna) #19205
* #10382
* #15517
* #2511
* #16686
think this should be a bug. When calling the fill_na method in a pandas Series of type np.float16 it raises a ValueError, because of invalid dtype. May be there is a reason for that I can't guess, but I think it's a bug because it d... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9221 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9221/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9221/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9221/events | https://github.com/pandas-dev/pandas/issues/9221 | 53,959,022 | MDU6SXNzdWU1Mzk1OTAyMg== | 9,221 | DataFrame.groupby.fillna for axis=1, no filling happens | {
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The bug exists for 15.1 and 15.2
Works for 13.1
```
import pandas as pd
import numpy as np
print pd.__version__
test = pd.DataFrame(index=pd.MultiIndex.from_product([['value1','value2'],pd.date_range('2014-01-01','2014-01-06')]),
columns=pd.Index(['1... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9223 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9223/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9223/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9223/events | https://github.com/pandas-dev/pandas/issues/9223 | 53,962,093 | MDU6SXNzdWU1Mzk2MjA5Mw== | 9,223 | ENH: add a "name" field to DataFrame, consistent with Series | {
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It would also be useful when loading/saving DataFrames to files and DBs, for example at the moment to save to HDF you a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9224 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9224/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9224/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9224/events | https://github.com/pandas-dev/pandas/issues/9224 | 53,984,291 | MDU6SXNzdWU1Mzk4NDI5MQ== | 9,224 | Syntax error thrown by python at pandas/scripts/windows_builder/check_and_build.py +52 | {
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$ python scripts/windows_builder/check_and_build.py
File "scripts/windows_builder/check_and_build.py", line 52
password=############
^
SyntaxError: invalid syntax
Fix: password='############' ?
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https://api.github.com/repos/pandas-dev/pandas/issues/9225 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9225/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9225/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9225/events | https://github.com/pandas-dev/pandas/pull/9225 | 53,987,031 | MDExOlB1bGxSZXF1ZXN0MjcxNjA3Nzc= | 9,225 | Fix randomly failing test in test_frame.py | {
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"followers_url": "https://api.github.com/users/jr... | 9 | 2015-01-11T09:44:43Z | 2015-01-15T03:25:21Z | 2015-01-15T03:25:17Z | CONTRIBUTOR | null | @jreback I noticed a randomly failing test while doing a full suite run a week or two ago. The test is using random integers as part of a `MultiIndex`, which randomly leads to a non-unique index. Attempting to re-index the `DataFrame` therefore randomly fails. The solution is to just sample without replacement.
The fo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9226 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9226/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9226/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9226/events | https://github.com/pandas-dev/pandas/pull/9226 | 54,018,044 | MDExOlB1bGxSZXF1ZXN0MjcxNzM4MjY= | 9,226 | ENH: add to_offset method to Timedelta #9064 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9227 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9227/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9227/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9227/events | https://github.com/pandas-dev/pandas/pull/9227 | 54,018,055 | MDExOlB1bGxSZXF1ZXN0MjcxNzM4MzU= | 9,227 | TST: Clean test_format.py | {
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"followers_url": "https://api.github.com/users/jr... | 10 | 2015-01-12T03:39:43Z | 2015-03-05T23:35:52Z | 2015-03-05T23:35:47Z | CONTRIBUTOR | null | Mostly just stylistic changes. The only substantive one is the test now on line 56 (`has_horizontally_truncated_repr`). I can't figure what the test was supposed to be doing. Suggestions?
Original Test:
``` python
def has_horizontally_truncated_repr(df):
try: # Check header row
fst_line = np.array(repr(df... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9228 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9228/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9228/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9228/events | https://github.com/pandas-dev/pandas/issues/9228 | 54,052,501 | MDU6SXNzdWU1NDA1MjUwMQ== | 9,228 | TestDataFrameFormatting error when stty columns = 0 | {
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... | 5 | 2015-01-12T13:21:08Z | 2019-10-07T01:09:15Z | 2019-10-07T01:09:14Z | CONTRIBUTOR | null | When stty columns = 0, I guess this test error.
```
======================================================================
FAIL: test_auto_detect (pandas.tests.test_format.TestDataFrameFormatting)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/Library... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9229 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9229/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9229/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9229/events | https://github.com/pandas-dev/pandas/issues/9229 | 54,057,312 | MDU6SXNzdWU1NDA1NzMxMg== | 9,229 | API/ENH: Add mutate like method to DataFrames | {
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"followers_url": "https://api.github.com/users/jr... | 23 | 2015-01-12T14:10:28Z | 2015-03-01T14:51:09Z | 2015-03-01T14:51:09Z | CONTRIBUTOR | null | In my [notebook](http://nbviewer.ipython.org/6e052140eaa5fdb6e8c0) comparing dplyr and pandas, I gained a new level of appreciation for the ability to chain strings of operations together. In my own code, the biggest impediment to this is adding additional columns that are calculations on existing columns. For example
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https://api.github.com/repos/pandas-dev/pandas/issues/9230 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9230/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9230/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9230/events | https://github.com/pandas-dev/pandas/pull/9230 | 54,083,087 | MDExOlB1bGxSZXF1ZXN0MjcyMTE1NTA= | 9,230 | COMPAT: Need to read Bytes on Python | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9231 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9231/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9231/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9231/events | https://github.com/pandas-dev/pandas/issues/9231 | 54,083,457 | MDU6SXNzdWU1NDA4MzQ1Nw== | 9,231 | read_stata failing with URL | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-01-12T17:41:41Z | 2015-01-16T12:48:10Z | 2015-01-16T12:48:10Z | CONTRIBUTOR | null | I'm not entirely sure the root cause yet. It's something to do with the default encoding I think. I'm pretty sure Stata uses `iso-8859-1` not `cp1252`. Changing this inside `pandas.io.maybe_read_encoded_stream` works, but changing the encoding in StataReader breaks something else that I don't have time to debug.
Can s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9232 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9232/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9232/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9232/events | https://github.com/pandas-dev/pandas/issues/9232 | 54,097,934 | MDU6SXNzdWU1NDA5NzkzNA== | 9,232 | BUG: DataFrame constructor incorrect with Series input depending on name | {
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``` python
In [55]: x = pd.Series(range(5), name=1)
In [56]: y = pd.Series(range(5), name=0)
In [57]: pd.DataFrame(x, columns=[0])
Out[57]:
Empty DataFrame
Columns: [0]
Index: []
In [58]: pd.DataFrame(x, columns=[1])
Out[58]:
1
0 0
1 1
2 2
3 3
4 4
```
and for y, the name and... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9233 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9233/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9233/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9233/events | https://github.com/pandas-dev/pandas/issues/9233 | 54,098,732 | MDU6SXNzdWU1NDA5ODczMg== | 9,233 | pip install pandas not working | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9234 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9234/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9234/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9234/events | https://github.com/pandas-dev/pandas/pull/9234 | 54,107,248 | MDExOlB1bGxSZXF1ZXN0MjcyMjY0MjI= | 9,234 | DOC: update docstring of DataFrame.append | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-01-12T21:11:42Z | 2015-01-19T13:58:49Z | 2015-01-19T13:58:48Z | MEMBER | null | I always thought that `append` was for appending rows, not columns. So, unless I am completely missing something, the docstring was saying the wrong thing.
So I reworded it a bit, see below.
Apart from that, there were some other things that are not fully clear to me in the docstring:
- The docstring says that `other... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9235 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9235/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9235/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9235/events | https://github.com/pandas-dev/pandas/issues/9235 | 54,111,451 | MDU6SXNzdWU1NDExMTQ1MQ== | 9,235 | Apply vs Transform on a group object | {
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"id": 233160... | closed | false | null | [] | null | 4 | 2015-01-12T21:47:19Z | 2015-01-13T11:08:58Z | 2015-01-13T11:08:47Z | CONTRIBUTOR | null | Hi,
I understand this ticket is a borderline usage question, but I think it may signal an example of inconsistency either in the documentation or on the way these methods work.
The original question on SO is [here](http://stackoverflow.com/questions/27517425/apply-vs-transform-on-a-group-object).
Consider the follow... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9236 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9236/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9236/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9236/events | https://github.com/pandas-dev/pandas/issues/9236 | 54,139,116 | MDU6SXNzdWU1NDEzOTExNg== | 9,236 | DataFrame.groupby fails with MultiIndex containing pd.NaT | {
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``` python
midx = pd.MultiIndex(levels=[[pd.NaT, pd.datetime(2012,1,2),
pd.datetime(2012,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9237 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9237/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9237/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9237/events | https://github.com/pandas-dev/pandas/pull/9237 | 54,141,701 | MDExOlB1bGxSZXF1ZXN0MjcyNDMwNTM= | 9,237 | BUG: fix DataFrame constructor w named Series | {
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Closes https://github.com/pydata/pandas/issues/9232
Problem was passing Series w/ a name to DataFrame w/ the `columns` kwarg.
Before:
``` python
In [55]: x = pd.Series(range(5), name=1)
In [56]: y = pd.Series(range(5), name=0)
In [57]: pd.DataFrame(x, columns=[0])
Out[57]:
Empty DataFrame
Columns: [0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9238 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9238/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9238/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9238/events | https://github.com/pandas-dev/pandas/pull/9238 | 54,145,031 | MDExOlB1bGxSZXF1ZXN0MjcyNDQ4MTI= | 9,238 | DOC: Small syntax change to indexing.rst to address GH8686. | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-01-13T02:54:36Z | 2015-01-13T08:09:48Z | 2015-01-13T08:09:37Z | CONTRIBUTOR | null | Brings indexing.rst docs for .loc into line with .iloc. Closes https://github.com/pydata/pandas/issues/8686.
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https://api.github.com/repos/pandas-dev/pandas/issues/9239 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9239/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9239/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9239/events | https://github.com/pandas-dev/pandas/pull/9239 | 54,193,793 | MDExOlB1bGxSZXF1ZXN0MjcyNzA5Mzk= | 9,239 | API: Add DataFrame.assign method | {
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signature: `DataFrame.transform(**kwargs)`
- the keyword is the name of the new column (existing columns are overwritten if there's a name conflict, as in dplyr)
- the value is either
- called on self if it's callable. The callable should be a function of 1 argumen... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9240 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9240/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9240/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9240/events | https://github.com/pandas-dev/pandas/issues/9240 | 54,204,738 | MDU6SXNzdWU1NDIwNDczOA== | 9,240 | Dataframe.query regex support | {
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] | closed | false | null | [] | null | 2 | 2015-01-13T15:14:04Z | 2015-01-13T23:47:40Z | 2015-01-13T23:47:35Z | NONE | null | Hi,
I was wondering if I could make a regex query (re.search say) in the query expression.
Dataframe.filter supports it. Is there any particular reason that query does not?
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https://api.github.com/repos/pandas-dev/pandas/issues/9241 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9241/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9241/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9241/events | https://github.com/pandas-dev/pandas/issues/9241 | 54,210,280 | MDU6SXNzdWU1NDIxMDI4MA== | 9,241 | First assignment with logical indexing is slow for Series (but OK for DataFrames) | {
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"color": "a1... | closed | false | null | [] | null | 6 | 2015-01-13T15:57:17Z | 2015-01-14T14:25:34Z | 2015-01-14T14:15:55Z | CONTRIBUTOR | null | First assignment with logical indexing is 1000 slower than second, third, etc. for pandas.Series:
```
import pandas.io.data as web
f = web.DataReader("MSFT", 'yahoo')['Adj Close']
%time f[f==0] = np.NaN
%time f[f==0.1] = np.NaN
```
It gives
```
CPU times: user 1.52 s, sys: 1.65 ms, total: 1.52 s
Wall time: 1.52 s
CP... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9242 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9242/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9242/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9242/events | https://github.com/pandas-dev/pandas/issues/9242 | 54,225,644 | MDU6SXNzdWU1NDIyNTY0NA== | 9,242 | timezone aware columns | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2015-01-13T17:59:38Z | 2015-02-27T10:56:10Z | 2015-01-13T23:40:09Z | NONE | null | At the moment, I don't see any way to have performant, timezone aware columns. This seems rather surprising, as generally when you have a column with timestamps, they will all likely be of the same timezone. Right now, as far as I can see you have two options:
1) Columns that are basically just numpy datetime64[ns] typ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9243 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9243/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9243/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9243/events | https://github.com/pandas-dev/pandas/issues/9243 | 54,234,553 | MDU6SXNzdWU1NDIzNDU1Mw== | 9,243 | Truncate on series causes core dump when TZ is specified on index | {
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"followers_url": "https://api.github... | 6 | 2015-01-13T19:13:32Z | 2018-06-28T10:23:02Z | 2018-06-28T10:23:02Z | NONE | null | Hello
I am getting a core dump when truncating a series with a timezone specified on the index. Please see below:
This works fine:
```
import pandas
import datetime
import numpy as np
rng = pandas.date_range('1/2/2005', '11/1/2010', freq='D')
ts = pandas.Series(np.random.randn(len(rng)), index=rng)
ts.truncate(d... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9244 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9244/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9244/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9244/events | https://github.com/pandas-dev/pandas/issues/9244 | 54,255,547 | MDU6SXNzdWU1NDI1NTU0Nw== | 9,244 | Modulo (%) operator not supported anymore for Index since 0.15 | {
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```
In [1]: pd.__version__
Out[1]: '0.14.1'
In [2]: intidx = pd.Index(range(10))
In [3]: intidx % 2
Out[3]: Int64Index([0, 1, 0, 1, 0, 1, 0, 1, 0, 1], dtype='int64')
```
now:
```
In [1]: pd.__version__
Out[1]: '0.15.2'
In [2]: intidx = pd.Index(range(10))
In [3]: intidx % 2
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https://api.github.com/repos/pandas-dev/pandas/issues/9245 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9245/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9245/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9245/events | https://github.com/pandas-dev/pandas/pull/9245 | 54,280,810 | MDExOlB1bGxSZXF1ZXN0MjczMjUwODc= | 9,245 | FIX: Fix encoding to allow StataReader to read urls | {
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closes #9231
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https://api.github.com/repos/pandas-dev/pandas/issues/9246 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9246/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9246/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9246/events | https://github.com/pandas-dev/pandas/issues/9246 | 54,289,566 | MDU6SXNzdWU1NDI4OTU2Ng== | 9,246 | df.to_hdf() does not support BytesIO | {
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In [1]: import io
In [2]: xx = io.BytesIO()
In [4]: from pandas import DataFrame
In [5]: from numpy.random import randn
In [6]: df = DataFrame(randn(1000000,2),columns=list('AB'))
----> 1 df.to_hdf(xx,'xx')
/root/pyenvs/aft_env/lib/python3.4/site-packages/pandas/core/generic.py in to_hdf(self, path_or_buf, key, *... | {
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In [70]: tds = pd.Series(pd.timedelta_range('1 days', periods=5, freq='2 h'), index=list('ABCDE'))
In [71]: tds
Out[71]:
A 1 days 00:00:00
B 1 days 02:00:00
C 1 days 04:00:00
D 1 days 06:00:00
E 1 days 08:00:00
dtype: timedelta64[ns]
In [72]: tds.dt.hours
Out[72]:
A 0
B 2
C 4
D 6
E 8
dtyp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9248 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9248/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9248/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9248/events | https://github.com/pandas-dev/pandas/pull/9248 | 54,324,364 | MDExOlB1bGxSZXF1ZXN0MjczNTA5Mjc= | 9,248 | BUG: Bug in the returned Series.dt.components index was reset to the default index (GH9247) | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-01-14T13:55:39Z | 2015-01-14T14:39:57Z | 2015-01-14T14:39:57Z | CONTRIBUTOR | null | closes #9247
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https://api.github.com/repos/pandas-dev/pandas/issues/9249 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9249/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9249/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9249/events | https://github.com/pandas-dev/pandas/issues/9249 | 54,327,394 | MDU6SXNzdWU1NDMyNzM5NA== | 9,249 | *__tmp_to_csv_deprecated_options__ are left behind | {
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] | closed | false | null | [] | {
"closed_at": "2016-05-05T00:34:40Z",
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"followers_url": "https://api.github.com/users/jr... | 6 | 2015-01-14T14:25:22Z | 2016-04-09T14:34:51Z | 2016-04-09T14:34:51Z | CONTRIBUTOR | null | which fills up the /tmp on a test box:
```
/tmp# ls -l *tmp_to_csv* | nl | tail
56 -rw------- 1 buildslave buildslave 1509 Jan 13 08:22 tmpuI3G3o__tmp_to_csv_deprecated_options__
57 -rw------- 1 buildslave buildslave 1514 Jan 13 06:04 tmpVmc8Qa__tmp_to_csv_deprecated_options__
58 -rw------- 1 buildslave... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9250 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9250/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9250/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9250/events | https://github.com/pandas-dev/pandas/issues/9250 | 54,338,376 | MDU6SXNzdWU1NDMzODM3Ng== | 9,250 | Setting with enlargement fails in presence of MultiIndex | {
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In [1]:
import pandas as pd
import numpy as np
print pd.__version__
a = np.linspace(0, 10, 11)
idx = [('test1', i) for i in range(5)]
idx.extend([('test2', i) for i in range(6)])
idx = pd.MultiIndex.from_tuples(idx)
0.15.2-80-ge69deae
In [2]:
a = pd.Series(a, idx)
a
Out[2]:
test1 0 0
1 1
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https://api.github.com/repos/pandas-dev/pandas/issues/9251 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9251/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9251/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9251/events | https://github.com/pandas-dev/pandas/issues/9251 | 54,340,150 | MDU6SXNzdWU1NDM0MDE1MA== | 9,251 | Problem assigning values to a multi-indexed DataFrame column when repeated indices are passed to .loc | {
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... | 1 | 2015-01-14T16:09:50Z | 2021-04-12T04:54:39Z | null | NONE | null | Consider the following:
```
ix = pd.MultiIndex.from_product([range(3), list('abc')])
df = pd.DataFrame(0, index = ix, columns = ['A','B'])
df.loc[[1, 1, 2], 'A']
Out[1896]:
1 a 0
b 0
c 0
2 a 0
b 0
c 0
```
Note that I've passed the index 1 twice (pointless I know). Now if I try to use ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9252 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9252/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9252/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9252/events | https://github.com/pandas-dev/pandas/issues/9252 | 54,344,324 | MDU6SXNzdWU1NDM0NDMyNA== | 9,252 | BUG: SparsePanel cross sectional not working | {
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... | 2 | 2015-01-14T16:40:27Z | 2015-09-20T21:16:30Z | 2015-09-20T21:16:30Z | CONTRIBUTOR | null | My understanding is that SparsePanel is supposed to have the same API as Panel, so I expected `sparse_pan[:,:,1]` to work:
``` python
In [11]: data = np.zeros((3,3,3))
In [12]: data[:] = np.nan
In [13]: data[1,1,1] = 1
In [14]: pan = pd.Panel(data)
In [15]: pan[:,:,1]
Out[15]:
0 1 2
0 NaN NaN NaN
1 NaN ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9253 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9253/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9253/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9253/events | https://github.com/pandas-dev/pandas/issues/9253 | 54,345,548 | MDU6SXNzdWU1NDM0NTU0OA== | 9,253 | Plotting NaT with matplotlib results in error | {
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"description": "np... | closed | false | null | [] | null | 2 | 2015-01-14T16:49:12Z | 2021-04-12T04:58:34Z | 2021-04-12T04:58:34Z | NONE | null | Trying to plot the NaT (not a time) value of pandas gives an error, where plotting NaN does not.
Expected (and hereby requested) is that NaT is treated just like NaN - i.e., ignore it.
``` python
from pylab import *
import pandas as pd
plot(pd.NaT,5)
```
```
-----------------------------------------------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9254 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9254/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9254/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9254/events | https://github.com/pandas-dev/pandas/issues/9254 | 54,364,621 | MDU6SXNzdWU1NDM2NDYyMQ== | 9,254 | Groupby added to original frame has different index based on how it is accessed | {
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```
In [11]:otms['LastOrd'] = otms.EVENTTIME.where(otms.EVENT=='Submitted')
otms.LastOrd = otms.groupby(['OPTION','EXCHANGE','BUYSELL', 'TRIGGER',]).LastOrd.shift(1)
otms.LastOrd... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9255 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9255/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9255/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9255/events | https://github.com/pandas-dev/pandas/pull/9255 | 54,398,578 | MDExOlB1bGxSZXF1ZXN0MjczOTc1NTM= | 9,255 | ENH: add Timestamp.to_datetime64 | {
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"followers_url": "https://api.github.com/users/jr... | 7 | 2015-01-15T00:47:10Z | 2015-01-15T04:43:16Z | 2015-01-15T04:43:11Z | MEMBER | null | This PR adds a `Timestamp.to_datetime64()` method to complement the `Timedelta.to_timedelta64()` method I added in #8884. It is a continuation of the aborted #8916.
Arguably, there should also be the alias `Timestamp.values` to complement the series property but I haven't added that yet.
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https://api.github.com/repos/pandas-dev/pandas/issues/9256 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9256/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9256/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9256/events | https://github.com/pandas-dev/pandas/pull/9256 | 54,400,633 | MDExOlB1bGxSZXF1ZXN0MjczOTg4ODc= | 9,256 | BUG: bug in multi-index where insert fails | {
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on master:
```
>>> df
3rd
1st 2nd
a b 0
b d 1
>>> df.loc[('b', 'x'), '3rd'] = 2 # this works!
>>> df
3rd
1st 2nd
a b 0
b d 1
x 2
>>> df.loc[('b', 'a'), '3rd'] = -1 # fails! sets everything to -1
>>> ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9257 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9257/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9257/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9257/events | https://github.com/pandas-dev/pandas/pull/9257 | 54,405,600 | MDExOlB1bGxSZXF1ZXN0Mjc0MDIwOTI= | 9,257 | API: restore full datetime.timedelta compat with Timedelta w.r.t. seconds/microseconds accessors (GH9185, GH9139) | {
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closes #9139
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https://api.github.com/repos/pandas-dev/pandas/issues/9258 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9258/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9258/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9258/events | https://github.com/pandas-dev/pandas/pull/9258 | 54,415,140 | MDExOlB1bGxSZXF1ZXN0Mjc0MDc3MDQ= | 9,258 | API/ENH: add method='nearest' to Index.get_indexer/reindex and method to get_loc | {
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Currently only an index method; I'm open to ideas for how to expose it more
directly -- maybe `df.loc_nearest`?.
In particular, I think this is usually a more useful way to do indexing for
floats than pandas's reindex based `.loc`, because floats are inherently
imprecise.
CC @jreback @jorisvandenbossche ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9259 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9259/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9259/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9259/events | https://github.com/pandas-dev/pandas/issues/9259 | 54,429,203 | MDU6SXNzdWU1NDQyOTIwMw== | 9,259 | Bug: Pandas indexing with at/iat fails with multi-index | {
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... | 3 | 2015-01-15T09:40:59Z | 2021-04-12T04:59:23Z | null | NONE | null | Split off from: #9250
```
In [6]:
# Dataframe now:
cols = [('a_col', chr(i+65)) for i in range(5)]
cols.extend([('b_col', chr(i+65)) for i in range(5, 10)])
idx = [('a_row', chr(i+65)) for i in range(5)]
idx.extend([('b_row', chr(i+65)) for i in range(5, 10)])
df = pd.DataFrame(np.linspace(1, 100, 100).reshape(10,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9260 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9260/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9260/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9260/events | https://github.com/pandas-dev/pandas/issues/9260 | 54,429,276 | MDU6SXNzdWU1NDQyOTI3Ng== | 9,260 | Constructing DataFrame from dict | {
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] | closed | false | null | [] | null | 4 | 2015-01-15T09:42:01Z | 2015-06-24T21:06:19Z | 2015-01-16T12:38:11Z | NONE | null | If think it was possible to construct a DataFrame from a dict, which gives an error with v0.15
``` python
In [4]: td = {'one': 1, 'two': 2}
In [5]: pd.DataFrame(td)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9261 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9261/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9261/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9261/events | https://github.com/pandas-dev/pandas/issues/9261 | 54,430,781 | MDU6SXNzdWU1NDQzMDc4MQ== | 9,261 | read_sql_query does not convert invalid dates to NaT | {
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Using:
```
df = pd.DataFrame({'col1':[0,1], 'col2':pd.date_range('2012-01-01', periods=2, freq='1h')})
df.to_sql('test_invalid_date', engine_postgres, if_exists='replace', index... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9262 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9262/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9262/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9262/events | https://github.com/pandas-dev/pandas/issues/9262 | 54,442,438 | MDU6SXNzdWU1NDQ0MjQzOA== | 9,262 | 'Incorrect table name error' in sql query, though table name is correct | {
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] | closed | false | null | [] | null | 3 | 2015-01-15T12:11:24Z | 2015-01-15T13:42:22Z | 2015-01-15T13:38:40Z | NONE | null | An error message about 'incorrect table name' is given by the input below, though the table name is correct. I get the impression that the real 'error' is the length of the sql statement, perhaps in combination with the underscores. The queries sql and sql5 below give an error message about incorrect tables, the other ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9263 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9263/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9263/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9263/events | https://github.com/pandas-dev/pandas/issues/9263 | 54,470,708 | MDU6SXNzdWU1NDQ3MDcwOA== | 9,263 | Clipboard functions don't support Unicode on Windows | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2015-01-15T16:33:41Z | 2015-12-05T15:33:54Z | 2015-12-05T15:33:54Z | CONTRIBUTOR | null | Recent versions of pyperclip (`pandas.util.clipboard`) use CF_UNICODETEXT getting data from and putting data to the WIndows Clipboard.
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https://api.github.com/repos/pandas-dev/pandas/issues/9264 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9264/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9264/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9264/events | https://github.com/pandas-dev/pandas/pull/9264 | 54,498,122 | MDExOlB1bGxSZXF1ZXN0Mjc0NTg0MDk= | 9,264 | FIX: Add endianness missing flag when reading data | {
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closes #8688
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... | 3 | 2015-01-16T00:11:05Z | 2021-11-02T02:40:59Z | null | CONTRIBUTOR | null | Recognizing that this is probably not very high on the priority list, I'll document that a user tried to use clip on sparse structures and wished that it worked.
Some ideas for what to do in order of best to worst solution:
1. Make it work in a memory and cpu efficient way.
2. Raise a NotImplementedError (possibly sug... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9266 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9266/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9266/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9266/events | https://github.com/pandas-dev/pandas/issues/9266 | 54,541,329 | MDU6SXNzdWU1NDU0MTMyOQ== | 9,266 | uin8 should be uint8 in io/parsers.py | {
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https://github.com/pydata/pandas/blob/072e40b0b5beab36c2adda9e0bcbb26755e1928f/pandas/io/parsers.py#L989
in which there is a np.uin8 which I'm pretty sure should be a np.uint8
apologise if this has already been submitted - I did a search on uin8 and... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9267 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9267/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9267/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9267/events | https://github.com/pandas-dev/pandas/issues/9267 | 54,551,700 | MDU6SXNzdWU1NDU1MTcwMA== | 9,267 | Appending with enlargment doesn't work for .ix in empty dataframe | {
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"color": "00... | closed | false | null | [] | null | 1 | 2015-01-16T08:38:18Z | 2015-01-16T12:31:26Z | 2015-01-16T12:31:26Z | NONE | null | Similar as https://github.com/pydata/pandas/issues/5226
Enlargment doesn't work for .ix on empty dataframe.
.loc works fine.
Affected version 0.15.2
```
df = pd.DataFrame(columns = ['a', 'b'])
df.ix[1] =[1, 1]
```
```
---------------------------------------------------------------------------
ValueError ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9268 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9268/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9268/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9268/events | https://github.com/pandas-dev/pandas/issues/9268 | 54,562,905 | MDU6SXNzdWU1NDU2MjkwNQ== | 9,268 | _repr_html_ creates extra scrollbar in ipython notebook | {
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"color": "006b7... | closed | false | null | [] | {
"closed_at": "2015-06-13T17:49:05Z",
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"followers_url": "https://api.github.... | 7 | 2015-01-16T10:54:43Z | 2016-07-04T14:06:05Z | 2016-07-04T14:05:55Z | NONE | null | This line: div style="max-height:1000px;max-width:1500px;overflow:auto;" is added to the output if the df is too large. This behaviour is handled in ipython anyway so should be removed or optional.
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https://api.github.com/repos/pandas-dev/pandas/issues/9269 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9269/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9269/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9269/events | https://github.com/pandas-dev/pandas/issues/9269 | 54,570,660 | MDU6SXNzdWU1NDU3MDY2MA== | 9,269 | adding new row to frame breaks types | {
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"followers_url": "https://api.github.com/users/jorisva... | 5 | 2015-01-16T12:30:52Z | 2016-09-30T20:42:23Z | 2016-09-30T20:42:14Z | CONTRIBUTOR | null | xref https://github.com/pydata/pandas/issues/8596
```
>>> df
a
0 1
>>> df.dtypes
a int64
dtype: object
>>> df.loc[1, 'a'] = 2
>>> df
a
0 1
1 2
>>> df.dtypes
a float64
dtype: object
```
in an intermediate step `nan` is inserted, and the data are casted to floats
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https://api.github.com/repos/pandas-dev/pandas/issues/9270 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9270/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9270/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9270/events | https://github.com/pandas-dev/pandas/issues/9270 | 54,584,591 | MDU6SXNzdWU1NDU4NDU5MQ== | 9,270 | DatetimeIndex loses TZ awareness when pushed from / pulled to HDF5 | {
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... | 3 | 2015-01-16T15:03:21Z | 2015-01-16T15:11:02Z | 2015-01-16T15:08:32Z | NONE | null | I found that when retrieving a DataFrame which had a MultiIndex containing a DatetimeIndex from a HDFStore, the TZ awareness was somehow lost.
Here is a demonstration:
```
import datetime as dt
import pandas as pd
start, end = dt.datetime(2015, 1, 16, 8), dt.datetime(2015, 1, 16, 17)
times = pd.date_range(start, end,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9271 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9271/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9271/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9271/events | https://github.com/pandas-dev/pandas/pull/9271 | 54,585,363 | MDExOlB1bGxSZXF1ZXN0Mjc1MTEzODg= | 9,271 | TST: Remove tests using proprietary data | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-01-16T15:10:36Z | 2015-01-18T22:42:19Z | 2015-01-18T20:41:28Z | CONTRIBUTOR | null | Removes three tests that use proprietary data that is not available for testing.
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https://api.github.com/repos/pandas-dev/pandas/issues/9272 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9272/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9272/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9272/events | https://github.com/pandas-dev/pandas/issues/9272 | 54,609,297 | MDU6SXNzdWU1NDYwOTI5Nw== | 9,272 | BUG: inconsistent constructors for sparse and dense objects | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-01-16T18:39:04Z | 2015-01-29T11:33:24Z | 2015-01-29T11:33:24Z | CONTRIBUTOR | null | Continuing on my recent sparse kick...
I appreciate the fact that `Series()`, `DataFrame()`, and `Panel()` all return empty versions of themselves. I think it's reasonable to expect that their sparse counterparts would behave the same way, but this is only the case for `SparseDataFrame()` (it's even [tested](https://g... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9273 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9273/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9273/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9273/events | https://github.com/pandas-dev/pandas/issues/9273 | 54,609,947 | MDU6SXNzdWU1NDYwOTk0Nw== | 9,273 | pd.Timedelta constructor should accept nanoseconds attribute in the arguments | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-01-16T18:45:17Z | 2015-01-19T03:17:20Z | 2015-01-19T03:17:20Z | CONTRIBUTOR | null | xref #9226
Noticing an inconsistency. pd.Timedelta doesn't allow nanoseconds in constructor but its components list till nanoseconds. Here is what I can reproduce. (used then current master on OS X 10.10.1)
Example:
<pre>
Python 2.7.9 (v2.7.9:648dcafa7e5f, Dec 10 2014, 10:10:46)
[GCC 4.2.1 (Apple Inc. build 5666) (... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9274 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9274/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9274/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9274/events | https://github.com/pandas-dev/pandas/issues/9274 | 54,619,704 | MDU6SXNzdWU1NDYxOTcwNA== | 9,274 | dataframe.plot accepts undocumented 'by=' keyword but ignores it. | {
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... | 3 | 2015-01-16T20:13:41Z | 2015-03-05T23:50:24Z | null | CONTRIBUTOR | null | Maybe this is a request for enhancement, or documentation of a bug - I don't know.
A tutorial showed that `DataFrame.boxplot()` can take a `by=` keyword to produced plot stratified by the values in one column. I naively assumed I could apply that to other plots as well. `DataFrame.plot()` accepts `by=` but seems ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9275 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9275/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9275/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9275/events | https://github.com/pandas-dev/pandas/issues/9275 | 54,619,769 | MDU6SXNzdWU1NDYxOTc2OQ== | 9,275 | ENH/DOC: catalog/raise NotImplemented errors for sparse structure methods | {
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... | 2 | 2015-01-16T20:14:17Z | 2019-09-18T14:02:17Z | 2019-09-18T14:02:17Z | CONTRIBUTOR | null | 1. Catalog and document all of the methods that don't currently work on sparse structures.
2. Raise NotImplemented exceptions for these methods.
Would be happy for suggestions for how to do this systematically.
Originally suggested by @jreback in #9265.
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https://api.github.com/repos/pandas-dev/pandas/issues/9276 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9276/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9276/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9276/events | https://github.com/pandas-dev/pandas/issues/9276 | 54,622,173 | MDU6SXNzdWU1NDYyMjE3Mw== | 9,276 | BUG: common.is_hashable returns False for np.float64 on Python 3 | {
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xref #9193
Here are [some test results](https://travis-ci.org/shoyer/pandas/builds/47184451) on Travis-CI illustrating the issue and my [commit](https://github.com/shoyer/pandas/commit/f8eb1c687164274a6b9a9640e565de60293ad2c1)
Any ideas for the fix? This is quite likely a numpy bug, but it's one we need to... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9277 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9277/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9277/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9277/events | https://github.com/pandas-dev/pandas/pull/9277 | 54,627,689 | MDExOlB1bGxSZXF1ZXN0Mjc1MzgxNzY= | 9,277 | allow for empty SparseSeries SparsePanel constructors | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-01-16T21:34:05Z | 2015-01-29T11:33:13Z | 2015-01-29T11:33:13Z | CONTRIBUTOR | null | Closes #9272.
Note that my solution is to provide a default `data=[]` for SparseSeries and `frames={}` for SparsePanel. This differs from the dense implementations that have `None` defaults that are then changed to the above. Doesn't seem like a big deal to me, but I can do that here if needed.
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https://api.github.com/repos/pandas-dev/pandas/issues/9278 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9278/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9278/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9278/events | https://github.com/pandas-dev/pandas/pull/9278 | 54,647,399 | MDExOlB1bGxSZXF1ZXN0Mjc1NTA0MTY= | 9,278 | BUG: Subplotting boxplot shows unnecessary warnings | {
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Because `legend=True` is default, `DataFrame.plot(kind='box', subplots=True)` shows unnecessary warnings.
```
# OK, no legend / no warnings
df.plot(kind='box')
```
```
# NG: no legend and warnings
df.plot(kind='box', subplots=True)
# UserWarning: No label... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9279 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9279/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9279/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9279/events | https://github.com/pandas-dev/pandas/issues/9279 | 54,649,104 | MDU6SXNzdWU1NDY0OTEwNA== | 9,279 | ENH: Allow function in Series/DataFrame get syntax | {
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"color": "AD... | closed | false | null | [] | null | 1 | 2015-01-17T03:31:05Z | 2015-01-21T19:20:27Z | 2015-01-21T19:20:27Z | NONE | null | Currently, pandas makes clever use of `__getitem__` to filter/mask Series and DataFrame. At times, the current abstraction is leaky - for instance, `df[18 < df['age'] < 25]` would raise an exception, even though cascaded compare symbols in that manner are legal Python syntax.
It would be awesome to also be able to pa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9280 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9280/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9280/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9280/events | https://github.com/pandas-dev/pandas/issues/9280 | 54,650,540 | MDU6SXNzdWU1NDY1MDU0MA== | 9,280 | BUG: where incorrectly coerces to str | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-01-17T04:41:29Z | 2015-01-18T20:36:40Z | 2015-01-18T20:36:40Z | MEMBER | null | Replacing some numeric values using `where` affects to dtype unrelated to the condition.
```
s = pd.Series(np.random.randn(5))
u = s.where(s<0, 'X', axis=1)
u
#0 -1.01421184508
#1 X
#2 X
#3 -0.228117839063
#4 -0.393903873887
# dtype: object
```
The result looks OK, but inte... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9281 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9281/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9281/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9281/events | https://github.com/pandas-dev/pandas/issues/9281 | 54,653,549 | MDU6SXNzdWU1NDY1MzU0OQ== | 9,281 | test.sh shows couple of failures on OSX 10.10.1 | {
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---
FAIL: test_now (pandas.tseries.tests.test_tslib.TestTimestamp)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/Users/tvyomkesh/pand... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9282 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9282/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9282/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9282/events | https://github.com/pandas-dev/pandas/pull/9282 | 54,657,405 | MDExOlB1bGxSZXF1ZXN0Mjc1NTQ5NjY= | 9,282 | ENH: StringMethods supports is_xxx methods | {
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Add following methods to be compat with standard `str`.
- StringMethods.isalnum
- StringMethods.isalpha
- StringMethods.isdigit
- StringMethods.isspace
- StringMethods.islower
- StringMethods.isupper
- StringMethods.istitle
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https://api.github.com/repos/pandas-dev/pandas/issues/9283 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9283/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9283/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9283/events | https://github.com/pandas-dev/pandas/pull/9283 | 54,658,016 | MDExOlB1bGxSZXF1ZXN0Mjc1NTUyMTI= | 9,283 | BUG: where coerces numeric to str incorrectly | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-01-17T10:35:48Z | 2015-01-19T14:31:31Z | 2015-01-18T20:36:40Z | MEMBER | null | Closes #9280.
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https://api.github.com/repos/pandas-dev/pandas/issues/9284 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9284/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9284/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9284/events | https://github.com/pandas-dev/pandas/issues/9284 | 54,662,962 | MDU6SXNzdWU1NDY2Mjk2Mg== | 9,284 | Adding tseries.offsets.Nano to other offsets throws error | {
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<pre>
In [11]: from pandas.tseries import offsets
In [12]: t1 = offsets.Nano(100)
In [13]: t2 = offsets.Micro(1)
In [14]: t3 = t1 + t2
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-14... | {
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"followers_url": "https://api.github.com/users/jr... | 10 | 2015-01-17T16:32:01Z | 2015-03-23T13:55:59Z | 2015-03-06T23:06:34Z | CONTRIBUTOR | null | Closes #4987
This is my first non-doc PR, so please bare with me. Is it worth my while to go through the tests and standarize all of the test HTML to all block-strings, or is the mix of individual lines/blocks ok?
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https://api.github.com/repos/pandas-dev/pandas/issues/9286 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9286/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9286/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9286/events | https://github.com/pandas-dev/pandas/issues/9286 | 54,669,252 | MDU6SXNzdWU1NDY2OTI1Mg== | 9,286 | Pandas returns 0/y=inf, even when y is a non-zero dataframe or series. | {
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``` python
import pandas as pd
y=pd.Series(range(1,10))
print 0/y # wrong
```
However, this operation would work:
``` python
for i in y:print 0/i # correct
```
I'm using Pandas 0.15.2-1.
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"de... | closed | false | null | [] | null | 3 | 2015-01-17T23:16:49Z | 2020-09-23T16:15:29Z | 2015-01-17T23:30:29Z | CONTRIBUTOR | null | Apologies if this feature has been suggested before. Many of the IO functions (e.g. `read_csv`) allow use to easily specify the format for each column using a dictionary. As far as I understand, this is **not**
possible with the regular dataframe construction, e.g:
``` python
df = pd.DataFrame(data=data, columns=colu... | {
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"id": ... | closed | false | null | [] | null | 1 | 2015-01-18T02:54:44Z | 2015-01-18T20:24:56Z | 2015-01-18T20:24:45Z | NONE | null | I am reading the book "Python for Data Analysis" and try some examples. But I found something strange.
On page 256, it says:
Quote:
Indexing a GroupBy object created from a DataFrame with a column name or array of column names has the effect of selecting those columns for aggregation. This means that:
```
df.groupb... | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-01-18T05:56:43Z | 2015-01-19T06:47:47Z | 2015-01-19T03:17:20Z | CONTRIBUTOR | null | closes #9273
This patch adds nanoseconds keyword support in Timedelta constructor.
<pre>
In [1]: from pandas import Timedelta
In [2]: td = Timedelta(nanoseconds=1)
In [3]: td1 = Timedelta(microseconds=1)
In [4]: td.components
Out[4]: Components(days=0, hours=0, minutes=0, seconds=0, milliseconds=0, microseconds=0... | {
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https://travis-ci.org/MacPython/scipy-stack-osx-testing/jobs/47389975#L757
Here's an example error:
```
======================================================================
ERROR: tes... | {
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closes https://github.com/pydata/pandas/issues/7401
closes https://github.com/pydata/pandas/issues/7403
closes https://github.com/pydata/pandas/issues/7405
minor code change to https://github.com/pydata/pandas/pull/9061; otherwise only tests. the code change is to av... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9293 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9293/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9293/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9293/events | https://github.com/pandas-dev/pandas/pull/9293 | 54,725,910 | MDExOlB1bGxSZXF1ZXN0Mjc1ODQ5MjQ= | 9,293 | Update plotting.py (issue #2916) | {
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] | closed | false | null | [] | {
"closed_at": "2015-03-23T10:50:37Z",
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-01-19T04:45:17Z | 2015-01-19T09:33:44Z | 2015-01-19T09:33:27Z | CONTRIBUTOR | null | Added ax docstring.
Address issue generated by `scripts/find_undoc_args.py`:
[+2892 tools/plotting.py boxplot_frame_groupby()](https://github.com/pydata/pandas/blob/master/pandas/tools/plotting.py#L2892): Missing[1/9]=['ax']
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https://api.github.com/repos/pandas-dev/pandas/issues/9294 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9294/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9294/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9294/events | https://github.com/pandas-dev/pandas/issues/9294 | 54,740,295 | MDU6SXNzdWU1NDc0MDI5NQ== | 9,294 | csv parsing is too restrictive | {
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"descript... | closed | false | null | [] | null | 9 | 2015-01-19T09:08:03Z | 2017-04-26T15:19:31Z | 2015-01-19T12:20:08Z | NONE | null | On this csv file:
```
DecisionM,IntelligentM,freq,total
0, 5, 9, 20
0, 6, 21,33
0, 7, 35,65
0, 8, 35,83
0, 9, 14,41
0, 10, 10,26
1, 5, 11,20
1, 6, 12,33
1, 7, 30,65
1, 8, 48,83
1, 9, 27, 41,,
1, 10, 16, 26
```
`pandas.read_csv()` gives me
```
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https://api.github.com/repos/pandas-dev/pandas/issues/9295 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9295/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9295/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9295/events | https://github.com/pandas-dev/pandas/issues/9295 | 54,740,611 | MDU6SXNzdWU1NDc0MDYxMQ== | 9,295 | csv parsing gets confused on first line commas | {
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"descript... | closed | false | null | [] | null | 2 | 2015-01-19T09:12:01Z | 2015-01-19T12:22:03Z | 2015-01-19T12:21:52Z | NONE | null | This csv file loads fine:
```
DecisionM,IntelligentM,freq,total
0, 5, 9, 20
0, 6, 21,33
0, 7, 35,65
0, 8, 35,83
0, 9, 14,41
0, 10, 10,26
1, 5, 11,20
1, 6, 12,33
1, 7, 30,65
1, 8, 48,83
1, 9, 27, 41
1, 10, 16, 26
```
```
In [11]: pandas.read_csv("speeddating.csv")
Out[11]:
DecisionM IntelligentM freq total
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9296 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9296/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9296/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9296/events | https://github.com/pandas-dev/pandas/pull/9296 | 54,741,761 | MDExOlB1bGxSZXF1ZXN0Mjc1OTM2MTY= | 9,296 | BUG: Fixes #9281: fixes to tseries.tests.test_tslib.TestTimestamp | {
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}
] | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-01-19T09:26:05Z | 2015-01-19T19:32:00Z | 2015-01-19T12:14:11Z | CONTRIBUTOR | null | closes #9281
The last test of both test_now and test_today was passing for anyone with a timezone
of UTC-5 or greater (but failed, for example, in US/Pacific). The test was not
testing what the original author meant it to (which is that the times are very close
together) so I added abs(.) around the Timedeltas and a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9297 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9297/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9297/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9297/events | https://github.com/pandas-dev/pandas/issues/9297 | 54,749,703 | MDU6SXNzdWU1NDc0OTcwMw== | 9,297 | API: DataFrame.eval, inplace option | {
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}
] | closed | false | null | [] | {
"closed_at": "2016-03-12T16:19:08Z",
"closed_issues": 469,
"created_at": "2015-07-19T20:18:45Z",
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"followers_url": "https://api.github.com/users/jr... | 9 | 2015-01-19T10:52:09Z | 2016-01-04T02:17:37Z | 2016-01-04T02:17:37Z | MEMBER | null | Building off of #9229, it's generally much better to create new dataframes rather than to modify existing ones. It's both more chainable and less prone to the bugs/errors associated with mutable state.
So it seems to me that a saner API design would be to make assignment operations with eval/query return a new frame r... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9298 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9298/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9298/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9298/events | https://github.com/pandas-dev/pandas/issues/9298 | 54,752,963 | MDU6SXNzdWU1NDc1Mjk2Mw== | 9,298 | In Panel having data as a scalar in the constructor does not work | {
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"description": "D... | closed | false | null | [] | null | 1 | 2015-01-19T11:27:37Z | 2015-01-19T12:15:36Z | 2015-01-19T12:15:36Z | NONE | null | When you want to initialise a DF to a particular value you can use `data = 0.`. But this does not work in Panel
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https://api.github.com/repos/pandas-dev/pandas/issues/9299 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9299/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9299/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9299/events | https://github.com/pandas-dev/pandas/issues/9299 | 54,761,494 | MDU6SXNzdWU1NDc2MTQ5NA== | 9,299 | Exception in get_group() with invalid index | {
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... | open | false | null | [] | {
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... | 1 | 2015-01-19T13:07:17Z | 2021-04-12T05:02:08Z | null | NONE | null | Hello,
I'm using the pandas function "pandas.core.groupby.GroupBy.get_group()" to parallelize my code.
This function raises a "KeyError" exception if the passed index is not contained in the index list of the grouped DataFrame.
A basic example is:
data = DataFrame({'ind':[0,0,2,2]})
gb=a.groupby('ind')
gb.get_group(1... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9300 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9300/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9300/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9300/events | https://github.com/pandas-dev/pandas/issues/9300 | 54,763,809 | MDU6SXNzdWU1NDc2MzgwOQ== | 9,300 | groupby first can return values not in group | {
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},
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"default": false,
"description": "Unexpected or b... | closed | false | null | [] | null | 4 | 2015-01-19T13:33:26Z | 2015-01-25T23:26:59Z | 2015-01-25T23:12:23Z | NONE | null | Not that familiar (at all :) with pandas internals, but I don't think this is expected behaviour.
``` python
f3 = DataFrame(
[
[95820843523155097, 1, 'director', 1],
[95820843523155098, 1, 'director', 2],
[95820843523155099, 1, 'director', 3],
[95820843523155100, 2, 'director', 4],... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9301 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9301/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9301/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9301/events | https://github.com/pandas-dev/pandas/issues/9301 | 54,777,327 | MDU6SXNzdWU1NDc3NzMyNw== | 9,301 | DOC: Revise "Merge, join, and concatenate" doc with graphical examples | {
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] | closed | false | null | [] | {
"closed_at": "2015-05-11T15:46:03Z",
"closed_issues": 237,
"created_at": "2014-10-07T14:39:07Z",
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"events_url": "https://api.github.com/users/jreback/events{/privacy}",
"followers_url": "https://api.github.com/users/jr... | 3 | 2015-01-19T15:30:32Z | 2015-05-08T07:45:25Z | 2015-05-08T07:45:25Z | MEMBER | null | I think the doc is little difficult for beginners, because examples use slicing to prepare input which cannot imagine immediately.
- http://pandas.pydata.org/pandas-docs/stable/merging.html
The alternative is using diagrams like below. I've prepared a function to output it using #6661, thus it can be generated during... | {
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