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https://api.github.com/repos/pandas-dev/pandas/issues/12204 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12204/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12204/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12204/events | https://github.com/pandas-dev/pandas/pull/12204 | 130,687,223 | MDExOlB1bGxSZXF1ZXN0NTc5ODgyOTA= | 12,204 | CI: install sphinx with conda for doc build | {
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so not needed to isntall this separately with pip to get latest version.
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Other functions to add: `write_frame`, `tquery`, `uquery`
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https://api.github.com/repos/pandas-dev/pandas/issues/12206 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12206/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12206/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12206/events | https://github.com/pandas-dev/pandas/issues/12206 | 130,720,004 | MDU6SXNzdWUxMzA3MjAwMDQ= | 12,206 | DOC: improve s3 access doc-strings / docs | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12207 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12207/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12207/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12207/events | https://github.com/pandas-dev/pandas/pull/12207 | 130,740,606 | MDExOlB1bGxSZXF1ZXN0NTgwMTM3OTk= | 12,207 | ENH: formatting integers in FloatIndex as floats | {
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Previous Behavior:
``` python
In [2]: s = Series([1,2,3], index=np.arange(3.))
In [3]: s
Out[3]:
0 1
1 2
2 3
dtype: int64
In [4]: s.index
Out[4]: Float64Index([0.0, 1.0, 2.0], dtype='float64')
In [5]: print(s.to_csv(path=None))
0,1
1,2
2,3
```
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https://api.github.com/repos/pandas-dev/pandas/issues/12208 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12208/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12208/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12208/events | https://github.com/pandas-dev/pandas/pull/12208 | 130,753,777 | MDExOlB1bGxSZXF1ZXN0NTgwMjA0Mjk= | 12,208 | STYLE: final flake8 fixes, add back check for travis-ci | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12209 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12209/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12209/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12209/events | https://github.com/pandas-dev/pandas/pull/12209 | 130,756,535 | MDExOlB1bGxSZXF1ZXN0NTgwMjE4MzI= | 12,209 | DOC: Added deprecation to convert_objects docstring#12052 | {
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Closes #12052
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https://api.github.com/repos/pandas-dev/pandas/issues/12210 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12210/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12210/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12210/events | https://github.com/pandas-dev/pandas/issues/12210 | 130,787,708 | MDU6SXNzdWUxMzA3ODc3MDg= | 12,210 | pivot_table throws exception with multiple aggregations per column and margins=True | {
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... | 14 | 2016-02-02T19:21:36Z | 2021-04-23T00:44:41Z | null | NONE | null | When applying multiple aggregations to columns and setting margins=True I receive a KeyError. I believe that because multiple aggregations are applied the columns become a MultiIndex, which is unexpected when computing margins.
``` python
>>> import pandas as pd
>>> import numpy as np
>>> import random
>>> df = pd.D... | {
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```
import pandas as pd
from datetime import datetime
from pytz import UTC
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... | closed | false | null | [] | null | 2 | 2016-02-02T22:29:38Z | 2016-02-02T22:37:14Z | 2016-02-02T22:34:15Z | NONE | null | This is a useful format for streamed applications.
It's basically the records orientation without the brackets and commas after each line.
http://jsonlines.org
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https://api.github.com/repos/pandas-dev/pandas/issues/12213 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12213/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12213/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12213/events | https://github.com/pandas-dev/pandas/issues/12213 | 130,841,150 | MDU6SXNzdWUxMzA4NDExNTA= | 12,213 | Support Infinity, -Infinity and NaN in read_json | {
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For example Google's GSON Library or python's json module in the standard library.
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https://api.github.com/repos/pandas-dev/pandas/issues/12214 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12214/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12214/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12214/events | https://github.com/pandas-dev/pandas/issues/12214 | 130,860,938 | MDU6SXNzdWUxMzA4NjA5Mzg= | 12,214 | pd.concat() from list of DataFrames read with pd.read_hdf() without .copy() results in 100X slower concat! | {
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] | closed | false | null | [] | null | 5 | 2016-02-03T00:04:20Z | 2016-02-03T03:12:16Z | 2016-02-03T03:12:16Z | NONE | null | ```
pandas: 0.17.1
numpy: 1.9.2
```
I have two example DataFrames written to hdf5 files on disk. I use pd.read_hdf() to I/O them into a list. When I attempt to pd.concat([list,of,frames]) it takes 100X longer if I don't explicitly call .copy() right after the pd.read_hdf(). :confused:
Did something change in the pd.r... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12215 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12215/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12215/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12215/events | https://github.com/pandas-dev/pandas/pull/12215 | 130,862,686 | MDExOlB1bGxSZXF1ZXN0NTgwNzIxMzc= | 12,215 | BUG: Strings like '2E' are incorrectly parsed as valid floats | {
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"followers_url": "https://api.github.com/users/jr... | 17 | 2016-02-03T00:12:18Z | 2016-02-09T22:15:54Z | 2016-02-09T22:03:11Z | CONTRIBUTOR | null | A work colleague, David Chase, encountered some surprising behaviour, which can be reduced to the following. The data-frame
```
DataFrame({'x': [2.5], 'y': [42], 'z': ['2E']})
```
does not round-trip correctly. The string '2E' is interpreted as a valid float, but it should not be (according to man strtod(3), which ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12216 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12216/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12216/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12216/events | https://github.com/pandas-dev/pandas/pull/12216 | 130,893,607 | MDExOlB1bGxSZXF1ZXN0NTgwODQ0NjE= | 12,216 | DEPR: Change boxplot return_type kwarg | {
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Deprecation started in https://github.com/pydata/pandas/pull/7096
Changes the default value of `return_type` in DataFrame.boxplot
and DataFrame.plot.box from None to 'axes'.
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https://api.github.com/repos/pandas-dev/pandas/issues/12217 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12217/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12217/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12217/events | https://github.com/pandas-dev/pandas/issues/12217 | 130,965,001 | MDU6SXNzdWUxMzA5NjUwMDE= | 12,217 | Concatenating two localized datetimes returns NaTs | {
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``` python
import pandas as pd
from datetime import datetime
### Concat'ing two UTC times works
first = pd.DataFrame([[datetime(2016, 1, 1)]])
first[0] = first[0].dt.tz_localize('UTC')
second = pd.DataFrame([[datetime(2016, 1, 2)]])
second[0] = second[0].dt.tz_localize('UTC')
print pd.concat([first, second])... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12218 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12218/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12218/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12218/events | https://github.com/pandas-dev/pandas/issues/12218 | 131,008,780 | MDU6SXNzdWUxMzEwMDg3ODA= | 12,218 | Empty TypeError message with bad column selection | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-02-03T12:24:39Z | 2016-02-24T00:05:40Z | 2016-02-24T00:05:40Z | CONTRIBUTOR | null | I was trying to guess, in a dataframe with multi-indexed columns, how to select all columns with a given second-level value.
And then I hit an empty `TypeError` message
```
In [8]: df = pd.DataFrame(columns=['i', 'c', 'x', 'y'], data=[[0, 0, 1, 2], [1, 0, 3, 4], [0, 1, 1, 2], [1, 1, 3, 4]])
In [9]: dg
Out[9]:
x ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12219 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12219/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12219/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12219/events | https://github.com/pandas-dev/pandas/pull/12219 | 131,012,976 | MDExOlB1bGxSZXF1ZXN0NTgxMzE3NDU= | 12,219 | ERR automatic broadcast for merging different levels, #9455 | {
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But I confess I'm a bit surprised by the result:
```
n [2]: df1 = DataFrame(columns=['a', 'b'], data=[[0, 1]])
In [3]: df2a = DataFrame(columns=['c', 'd'], data=[[2, 3]])
In [4]: df2b = DataFrame(columns=['c', 'e'], data=[[4, 5]])
In [5]: d... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12220 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12220/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12220/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12220/events | https://github.com/pandas-dev/pandas/issues/12220 | 131,018,454 | MDU6SXNzdWUxMzEwMTg0NTQ= | 12,220 | DataFrame.idxmax may return modified index/column dtype | {
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"color": "00... | closed | false | null | [] | null | 1 | 2016-02-03T13:02:26Z | 2016-02-03T13:39:33Z | 2016-02-03T13:39:33Z | NONE | null | In some circumstances, `idxmax` may return a Series with unexpected `dtype`:
``` python
>>> df = pandas.DataFrame(data=[[0.0, 1.0], [0.0, 1.0]], columns=[1,2], index=[1,2])
>>> df.idxmax(axis=0)
1 1
2 1
dtype: int64
```
``` python
>>> df = pandas.DataFrame(data=[[-inf, 1.0], [-inf, 1.0]], columns=[1,2], index=[... | {
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"color": "5319... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-02-03T15:07:21Z | 2016-02-11T02:55:17Z | 2016-02-11T02:55:17Z | MEMBER | null | ```
list(pd.HDFStore("non_existing_store.hdf"))
```
should, I think, return `[]`, instead it yields:
```
KeyError: 'No object named 0 in the file'
```
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"followers_url": "https://api.github.com/users/j... | 4 | 2016-02-03T16:10:53Z | 2019-05-18T14:16:55Z | 2019-05-18T14:16:55Z | NONE | null | This is a very obscure bug in a corner-case, but it's still a bug which I ran into. It's easiest to understand by seeing it in action. I'm running **pandas version 0.17.1**.
```
>>> import pandas as pd
>>> import datetime
>>> df = pd.DataFrame({'a': [datetime.datetime(2015,1,1)], 'b': [None], 'c': [None], 'd': [''], '... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12223 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12223/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12223/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12223/events | https://github.com/pandas-dev/pandas/issues/12223 | 131,087,982 | MDU6SXNzdWUxMzEwODc5ODI= | 12,223 | multi-index display bug | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-02-03T17:01:14Z | 2017-02-24T20:18:20Z | 2017-02-24T20:18:20Z | NONE | null | Thanks for great tool!
When printing a long DataFrame with multi-index which are result of set_index(..., append=True),
displaying index values look strange.
``` py
import pandas as pd
def func(n):
x = [
[['a1-%d' % i, 'a2-%d' % i] for i in range(n)],
[['b1-%d' % i, 'b2-%d' % i] for i in range(n... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12224 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12224/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12224/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12224/events | https://github.com/pandas-dev/pandas/issues/12224 | 131,094,282 | MDU6SXNzdWUxMzEwOTQyODI= | 12,224 | read_csv's na_values dict format cannot parse float type | {
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"color": "d7e102",
"default": false,
"description": "np.nan, pd.NaT, pd.NA, d... | closed | false | null | [] | {
"closed_at": "2016-10-03T08:52:13Z",
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"created_at": "2016-03-11T21:24:45Z",
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"followers_url": "https://api.github.com/users/jr... | 10 | 2016-02-03T17:21:54Z | 2018-01-08T23:14:59Z | 2016-08-21T19:34:41Z | NONE | null | Minor issue regarding `read_csv`'s `na_values` argument in `dict` format. I note that the list format works fine when the NA value is given as a float-type (which is often the intuitive choice), e.g.:
``` python
co2 = pd.read_csv("ftp://aftp.cmdl.noaa.gov/products/trends/co2/co2_mm_mlo.txt",
comment... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12225 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12225/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12225/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12225/events | https://github.com/pandas-dev/pandas/issues/12225 | 131,103,605 | MDU6SXNzdWUxMzExMDM2MDU= | 12,225 | msgpack reads python 2 string as bytes | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2016-02-03T17:54:06Z | 2017-02-03T15:30:51Z | 2017-02-03T15:29:59Z | CONTRIBUTOR | null | This maybe is just a doc warning - but caught me by surprise. I would prefer the `read_csv` behavior, but it would be backwards incompatible.
``` python
In [57]: pd.read_csv('path/doesn_exist')
---------------------------------------------------------------------------
IOError: File path/doesn_exist does not exist
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12226 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12226/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12226/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12226/events | https://github.com/pandas-dev/pandas/issues/12226 | 131,123,330 | MDU6SXNzdWUxMzExMjMzMzA= | 12,226 | Query on Series | {
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"color": "02... | closed | false | null | [] | null | 3 | 2016-02-03T19:09:04Z | 2016-02-03T20:54:55Z | 2016-02-03T19:36:04Z | CONTRIBUTOR | null | I often find myself building a chain of logic, and then wanting to slice over some expression. Here's a contrived example:
``` python
In [12]: pd.Series(range(10)).mul(5).pipe(lambda x: x**2).pipe(lambda x: x-500)
Out[12]:
0 -500
1 -475
2 -400
3 -275
4 -100
5 125
6 400
7 725
8 1100
9 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12227 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12227/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12227/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12227/events | https://github.com/pandas-dev/pandas/pull/12227 | 131,129,736 | MDExOlB1bGxSZXF1ZXN0NTgxODg1MzA= | 12,227 | Use correct prop_cycle in the mpl_stylesheet. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12228 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12228/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12228/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12228/events | https://github.com/pandas-dev/pandas/issues/12228 | 131,171,577 | MDU6SXNzdWUxMzExNzE1Nzc= | 12,228 | Pandas read_csv with chunksize stops before end of file | {
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... | 0 | 2016-02-03T22:15:36Z | 2019-10-21T19:52:15Z | null | CONTRIBUTOR | null | I have a massive csv file (54 GB, ~2.7 billion records) that I'm trying to process in chunks using chunksize. The csv reader stopped before hitting the end of the file. Upon further investigation, I found that it stopped after reading 2147483648 rows, which, is (2**32)/2. I assume there's an overflow happening somewher... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12229 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12229/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12229/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12229/events | https://github.com/pandas-dev/pandas/issues/12229 | 131,233,961 | MDU6SXNzdWUxMzEyMzM5NjE= | 12,229 | BadZipfile: File is not a zip file on Windows not on Mac OS | {
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"descript... | closed | false | null | [] | null | 3 | 2016-02-04T04:02:07Z | 2017-08-07T14:45:59Z | 2016-02-05T17:29:20Z | NONE | null | When trying to run code on my computer that my partner wrote on his computer, I get this error when I run
``` python
def read_excel(file):
xl = pd.ExcelFile(file)
df = xl.parse(0)
return df
```
Here's the Error messages:
File "C:\Users\wjayn_000\Documents\GitHub\tippecanoe\app\views\lodging.py", line 19, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12230 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12230/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12230/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12230/events | https://github.com/pandas-dev/pandas/issues/12230 | 131,318,477 | MDU6SXNzdWUxMzEzMTg0Nzc= | 12,230 | Regarding pd.DataFrame.std() function | {
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] | closed | false | null | [] | null | 5 | 2016-02-04T11:25:46Z | 2016-02-05T05:48:35Z | 2016-02-05T02:26:24Z | NONE | null | It looks like it calculates an adjusted value of std, i.e. a squared deviation from the mean, (x_i - x_bar) *\* 2, divided by n-1 instead of n.
It is a reasonable measure for cases when n <= 50 allowing to avoid underestimation of std. But in cases when n > 50 actually there is no difference what number is used in the ... | {
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... | closed | false | null | [] | null | 6 | 2016-02-04T14:36:38Z | 2016-02-10T19:21:45Z | 2016-02-05T17:25:44Z | CONTRIBUTOR | null | The cookbook [Data In/Out](http://pandas-docs.github.io/pandas-docs-travis/cookbook.html#data-in-out) points to: [how to read in multiple files, appending to create a single dataframe](http://stackoverflow.com/questions/25210819/speeding-up-data-import-function-pandas-and-appending-to-dataframe/25210900#25210900).
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https://api.github.com/repos/pandas-dev/pandas/issues/12232 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12232/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12232/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12232/events | https://github.com/pandas-dev/pandas/issues/12232 | 131,478,562 | MDU6SXNzdWUxMzE0Nzg1NjI= | 12,232 | issue with StataReader for stata files versions 108 and older | {
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I have pandas: 0.17.1.
The following is the python code I am trying to run:
```
import sys
reload(sys).setdefaultencoding('utf-8')
import pandas as pd
from pandas.io import stata
sr=stata.StataReader(fileName)
```
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https://api.github.com/repos/pandas-dev/pandas/issues/12233 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12233/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12233/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12233/events | https://github.com/pandas-dev/pandas/pull/12233 | 131,562,624 | MDExOlB1bGxSZXF1ZXN0NTgzOTEyODA= | 12,233 | Read very old stata DTA files | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2016-02-05T05:53:06Z | 2016-02-08T15:19:29Z | 2016-02-08T15:18:59Z | CONTRIBUTOR | null | This should close #12232, although the issue may resurface for files containing double values (I can't determine the old type code for doubles).
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https://api.github.com/repos/pandas-dev/pandas/issues/12235 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12235/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12235/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12235/events | https://github.com/pandas-dev/pandas/issues/12235 | 131,676,162 | MDU6SXNzdWUxMzE2NzYxNjI= | 12,235 | 3.5 builds failing on linux | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-02-05T15:46:02Z | 2016-09-28T10:25:14Z | 2016-09-28T10:25:14Z | CONTRIBUTOR | null | `scipy` is not install `libgfortran`, see issue [here](https://github.com/conda/conda/issues/2028)
log [here](https://travis-ci.org/pydata/pandas/jobs/107252670)
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https://api.github.com/repos/pandas-dev/pandas/issues/12236 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12236/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12236/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12236/events | https://github.com/pandas-dev/pandas/issues/12236 | 131,691,514 | MDU6SXNzdWUxMzE2OTE1MTQ= | 12,236 | BUG: read_hdf is not read-threadsafe | {
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... | 17 | 2016-02-05T16:45:56Z | 2019-10-29T12:18:22Z | null | CONTRIBUTOR | null | xref: https://github.com/pydata/pandas/issues/2397
xref #14263 (example)
I _think_ that we should protect the file open/closes with a lock to avoid this problem.
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"... | closed | false | null | [] | null | 2 | 2016-02-05T17:27:29Z | 2016-08-21T02:41:54Z | 2016-08-21T02:41:54Z | CONTRIBUTOR | null | The data-frame
``` python
DataFrame({'x': [2.5], 'y': [42], 'z': ['2E']})
```
does not round-trip correctly via CSV. The string `'2E'` is interpreted as a valid float, but it should not be (according to man strtod(3), which seems a reasonable spec).
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https://api.github.com/repos/pandas-dev/pandas/issues/12238 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12238/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12238/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12238/events | https://github.com/pandas-dev/pandas/issues/12238 | 131,733,709 | MDU6SXNzdWUxMzE3MzM3MDk= | 12,238 | np.searchsorted fails on Index due to Index.searchsorted not taking a sorter argument. | {
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import numpy, pandas
ix = pandas.Float64Index([1,2,3])
numpy.searchsorted(ix, 2.5)
```
leads to
```
TypeError
..../site-packages/numpy/core/fromnumeric.pyc in searchsorted(a, v, side, sorter)
1086 except AttributeError:
1087 return _wrapit(a, 'searchsorted', v, side, sorter)
-> 1088 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12240 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12240/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12240/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12240/events | https://github.com/pandas-dev/pandas/issues/12240 | 131,830,558 | MDU6SXNzdWUxMzE4MzA1NTg= | 12,240 | Travis build fails on master | {
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This happens since the last commit, which was merging a pull request of mine... but Travis was green for me, and beside I can't see no connection between that:
```
ERROR: test_nankurt (pandas.tests.test_nanops.TestnanopsDataFrame)
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-02-06T14:03:34Z | 2016-02-11T23:43:23Z | 2016-02-11T23:35:54Z | MEMBER | null | Closes #11718.
- Ops with `NaT` and `Timestamp` with `tz` results in `NaT`
- Ops with `NaT` and `DatetimeIndex` / `TimedeltaIndex` results in corresponding `Index` filled with `NaT`.
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https://api.github.com/repos/pandas-dev/pandas/issues/12242 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12242/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12242/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12242/events | https://github.com/pandas-dev/pandas/issues/12242 | 131,865,511 | MDU6SXNzdWUxMzE4NjU1MTE= | 12,242 | HDFStore.append fails when appending dataframe with empty string column for which min_itemsize < 8 | {
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"followers_url": "https://api.github... | 4 | 2016-02-06T15:17:52Z | 2018-11-01T17:06:53Z | 2018-11-01T17:06:53Z | CONTRIBUTOR | null | Reproduced as follows:
```
In [3]: store = pd.HDFStore('teststore.h5', 'w')
In [4]: chunk = pd.DataFrame({'V1':['a','b','c','d','e'], 'data':np.arange(5)})
In [5]: store.append('df', chunk, min_itemsize={'V1': 4})
In [6]: chunk = pd.DataFrame({'V1':['', ''], 'data': [3, 5]})
In [7]: store.append('df', chunk, min_i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12243 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12243/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12243/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12243/events | https://github.com/pandas-dev/pandas/pull/12243 | 131,878,542 | MDExOlB1bGxSZXF1ZXN0NTg1MjUyMDM= | 12,243 | TST: Skip scipy NaN test on 0.17 for now | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-02-06T17:31:31Z | 2016-02-06T19:32:09Z | 2016-02-06T19:31:59Z | CONTRIBUTOR | null | Working around https://github.com/pydata/pandas/issues/12240 which we'll leave open until I (or someone more knowledgeable) can properly fix these.
This skips the following tests when on scipy 0.17
- test_nansem
- test_nanskew
- test_nankurk
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https://api.github.com/repos/pandas-dev/pandas/issues/12244 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12244/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12244/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12244/events | https://github.com/pandas-dev/pandas/issues/12244 | 131,883,954 | MDU6SXNzdWUxMzE4ODM5NTQ= | 12,244 | BUG: DataFrame.apply fails on timezone aware datetime data | {
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In [29]: df = pd.DataFrame({'dt': pd.date_range("2015-01-01", periods=3, tz='Europe/Brussels')})
In [30]: df
Out[30]:
dt
0 2015-01-01 00:00:00+01:00
1 2015-01-02 00:00:00+01:00
2 2015-01-03 00:00:00+01:00
In [31]: df.apply(lambda x: x)
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"followers_url": "https://api.github.com/users/jr... | 19 | 2016-02-06T19:18:21Z | 2016-03-12T19:19:12Z | 2016-03-12T16:18:52Z | CONTRIBUTOR | null | so I am thinking of a RC1, friday feb 12th & release on or about friday feb 26th assuming nothing major comes up.
any objections
@jorisvandenbossche @shoyer @wesm @cpcloud @TomAugspurger @sinhrks
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https://api.github.com/repos/pandas-dev/pandas/issues/12246 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12246/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12246/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12246/events | https://github.com/pandas-dev/pandas/pull/12246 | 131,893,945 | MDExOlB1bGxSZXF1ZXN0NTg1MjkwNzU= | 12,246 | DEPR: removal of deprecation warnings for float indexers | {
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closes #11836
similar to numpy in 1.11 [here](https://github.com/numpy/numpy/pull/6271)
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https://api.github.com/repos/pandas-dev/pandas/issues/12247 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12247/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12247/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12247/events | https://github.com/pandas-dev/pandas/pull/12247 | 131,918,962 | MDExOlB1bGxSZXF1ZXN0NTg1MzUyOTI= | 12,247 | TST: allow assert_almost_equal to handle pandas instances | {
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Because many existing tests expects `assert_almost_equal` to compare `pandas` instances, it looks better to call appropriate test functions rather than raise.
I've also fixed some failure cases caused by the change (comparing `Series` and `list`, etc).
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https://api.github.com/repos/pandas-dev/pandas/issues/12250 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12250/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12250/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12250/events | https://github.com/pandas-dev/pandas/issues/12250 | 131,974,833 | MDU6SXNzdWUxMzE5NzQ4MzM= | 12,250 | Inconsistent results when concatenating parsed csv files with function application on windows | {
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closes #10381
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https://api.github.com/repos/pandas-dev/pandas/issues/12253 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12253/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12253/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12253/events | https://github.com/pandas-dev/pandas/pull/12253 | 131,978,657 | MDExOlB1bGxSZXF1ZXN0NTg1NDkzMjg= | 12,253 | ENH: Make HDFStore iterable | {
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HDFStore is not an iterator - but being iterable, it can return an iterator of itself (i.e. of `.keys()`).
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The issue below was created in Python 2.7.11 with Pandas 0.17.1 (and 0.17.1+311.g70f79ce)
When grouping a categorical column with both a period and date column, unexpected rows appear in the grou... | {
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```
>>> import pandas as pd
>>> import numpy as np
>>> df = pd.DataFrame([[1, 2, 'a'], [3, 4, 'b']], dtype=np.float32)
>>> A = df.ix[:, 0:1].values
>>> df.ix[:, 0:1] = A
>>> df[0].dtype
dtype('float64')
```
Shouldn't the result be `dtype('f... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12256 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12256/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12256/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12256/events | https://github.com/pandas-dev/pandas/pull/12256 | 132,065,106 | MDExOlB1bGxSZXF1ZXN0NTg1NzUxMjE= | 12,256 | DOC: pd.read_csv doc-string clarification #11555 | {
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Updated IO Tools documentation for read_csv() and read_table() to be consistent with the doc-string,
also reordered keywords to group them more logically. Also updated merging.rst docs for concat.
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The most of time is spent on `self._data.fillna` (core/generic.py:2833)
```
import pandas as pd
pd.set_option("mode.use_inf_as_null", True) #+/-inf -> None
s=pd.read_msgpack(r"D:\slow_fillna.msgpack", encoding='utf-8')
s2=s.fillna("<Н/Д>... | {
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```
In [2]: pd.Series(index=pd.MultiIndex.from_product([[], [0,1], []], names=['var', 'per', 'extr']))
Out[2]: Series([], dtype: float64)
In [3]: pd.Series(index=pd.MultiIndex.from_product([[], [0,1,2,3], []], names=['var', 'per', 'extr']))
Out[3]: Series([], dtype: float64)
In [4]:... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12259 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12259/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12259/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12259/events | https://github.com/pandas-dev/pandas/issues/12259 | 132,160,340 | MDU6SXNzdWUxMzIxNjAzNDA= | 12,259 | ValueError: Data type datetime64[ns] not currently understood. Please report an error to the developers. | {
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"color": "5319... | closed | false | null | [] | null | 4 | 2016-02-08T14:45:49Z | 2016-07-21T10:59:35Z | 2016-07-21T10:59:35Z | NONE | null | I do what I am told to do ;-)
I have a big dataframe with the following columns
```
daily_news.dtypes
Out[11]:
stock_ric object
obs_day datetime64[ns]
next_dayfirst datetime64[ns]
sentimentmean float32
sentimentcount int64
companyName... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12260 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12260/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12260/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12260/events | https://github.com/pandas-dev/pandas/pull/12260 | 132,174,300 | MDExOlB1bGxSZXF1ZXN0NTg2MjQ5Mjk= | 12,260 | BUG: Make Styler ignore None index names to match to_html behaviour | {
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"followers_url": "https://api.github.com/users/jr... | 9 | 2016-02-08T15:37:34Z | 2016-03-04T13:35:00Z | 2016-03-03T19:06:28Z | CONTRIBUTOR | null | Addresses https://github.com/pydata/pandas/pull/12090#issuecomment-180695902 by making the `Styler` behaviour match regular `to_html` behaviour.
This PR is based from #12162.
##### New behaviour
<img width="596" alt="screen shot 2016-02-08 at 10 35 23 am" src="https://cloud.githubusercontent.com/assets/3064019/12890... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12261 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12261/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12261/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12261/events | https://github.com/pandas-dev/pandas/issues/12261 | 132,194,367 | MDU6SXNzdWUxMzIxOTQzNjc= | 12,261 | sort_index doesn't sort MultiIndex when .loc[] referred to non-existent label on other axis | {
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In [2]: df = pd.DataFrame(0, columns=[], index=pd.MultiIndex.from_product([[], []]))
In [3]: df.loc['b', '2'] = 1
In [4]: df.loc['a', '3'] = 1
In [5]: df.sort_index()
Out[5]:
2 3
b 1.0 NaN
a NaN 1.0
In [6]: df.sort_index().index.is_monotonic
Out[6]: False
```
Am I missing anything obvious?!
(No... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12262 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12262/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12262/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12262/events | https://github.com/pandas-dev/pandas/issues/12262 | 132,197,599 | MDU6SXNzdWUxMzIxOTc1OTk= | 12,262 | high temporary memory usage on creation of DataFrame from list | {
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"default"... | closed | false | null | [] | null | 3 | 2016-02-08T16:56:35Z | 2016-02-09T20:51:05Z | 2016-02-09T20:50:59Z | NONE | null | When I create a DataFrame from a list of arrays, it temporarily uses a lot more memory and is slower than if I convert the list to an array first (if you want to test this, make sure you have enough memory or change the size of `a`):
``` python
In [1]: import numpy as np
...: import pandas as pd
In [2]: a = np.rand... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12263 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12263/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12263/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12263/events | https://github.com/pandas-dev/pandas/pull/12263 | 132,217,601 | MDExOlB1bGxSZXF1ZXN0NTg2NDU0NDA= | 12,263 | PEP8: fix sql.py and test_sql.py | {
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Strange that it did not fail on travis before merging ?
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https://api.github.com/repos/pandas-dev/pandas/issues/12264 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12264/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12264/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12264/events | https://github.com/pandas-dev/pandas/issues/12264 | 132,279,030 | MDU6SXNzdWUxMzIyNzkwMzA= | 12,264 | timezones discarded when calling .values and .unique() | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2016-02-08T22:48:02Z | 2016-02-09T07:56:19Z | 2016-02-08T22:52:44Z | NONE | null | Calling `values` to get a column of timestamps seems to be dropping the timezone whether it is a standard column or an index. `unique` also has problems for df columns, though indexes appear to work. Running 0.17.1 through conda.
```
>>> from pytz import timezone
>>> import pandas as pd
>>> EASTERN = timezone('US/East... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12265 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12265/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12265/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12265/events | https://github.com/pandas-dev/pandas/issues/12265 | 132,372,202 | MDU6SXNzdWUxMzIzNzIyMDI= | 12,265 | Reading table with chunksize still pumps the memory | {
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"followers_url": "https://api.github.com/users/jorisva... | 12 | 2016-02-09T09:39:47Z | 2020-10-02T13:14:56Z | 2016-02-09T10:47:25Z | CONTRIBUTOR | null | I'm trying to migrate database tables from MySQL to SQL Server:
``` python
import pandas as pd
from sqlalchemy import create_engine
my_engine = create_engine("mysql+pymysql://root:pass@localhost/gen")
ms_engine = create_engine('mssql+pyodbc://localhost/gen?driver=SQL Server')
for table_name in ['topics', 'fiction', ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12266 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12266/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12266/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12266/events | https://github.com/pandas-dev/pandas/issues/12266 | 132,384,928 | MDU6SXNzdWUxMzIzODQ5Mjg= | 12,266 | ValueError when opening a read-only hdf twice | {
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In [3]: with pd.HDFStore('/tmp/file_I_can_only_read.hdf') as store:
...: store['test'] = pd.Series(range(3))
...:
In [4]: os.chmod('/tmp/file_I_can_only_read.hdf', 0o400)
In [5]: store1 = pd.HDFStore('/tmp/file_I_can_only_read.hdf')
Opening /tmp/file_I_can_only_read.hdf in read-only mode
In [6]: s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12267 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12267/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12267/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12267/events | https://github.com/pandas-dev/pandas/pull/12267 | 132,389,354 | MDExOlB1bGxSZXF1ZXN0NTg3MzE4MTQ= | 12,267 | Do not raise error when reopening a read-only HDFStore. | {
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] | closed | false | null | [] | null | 1 | 2016-02-09T10:58:43Z | 2017-03-08T17:01:59Z | 2016-02-09T14:49:33Z | MEMBER | null | closes #12266
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... | 4 | 2016-02-09T21:12:01Z | 2021-04-23T00:48:03Z | null | CONTRIBUTOR | null | `DatetimeIndex` looks like it can benefit from `RangeIndex` #11892 .
Use case 1: Evenly-spaced time-series analysis
Use case 2: I sometimes (ab)use `date_range` like a PY3 `range` in a for loop, which I think is quite neat. It would be cooler if it were lazily evaluated.
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I think that this warning could be useful either way for no non-daily hdf user:
- Telling that string method is preferred
- Adding a warning
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https://api.github.com/repos/pandas-dev/pandas/issues/12277 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12277/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12277/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12277/events | https://github.com/pandas-dev/pandas/pull/12277 | 132,661,147 | MDExOlB1bGxSZXF1ZXN0NTg4NzE4ODA= | 12,277 | API: to_msgpack and read_msgpack encoding defaults to utf-8 | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-02-10T10:31:03Z | 2016-02-10T16:20:58Z | 2016-02-10T16:20:49Z | CONTRIBUTOR | null | closes #12170
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https://api.github.com/repos/pandas-dev/pandas/issues/12278 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12278/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12278/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12278/events | https://github.com/pandas-dev/pandas/issues/12278 | 132,662,500 | MDU6SXNzdWUxMzI2NjI1MDA= | 12,278 | Performance: .unique / .nunique of categorical series slow on large data set | {
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"followers_url": "https://api.github.com/users/jr... | 13 | 2016-02-10T10:36:56Z | 2017-12-01T00:34:55Z | 2016-02-23T14:57:16Z | NONE | null | I've noticed that `Series.unique` and `Series.nunique` when used with a categorical series can be slow on large dataset. Presumably its not utilising the shortcuts:
```
Series.unique = Series.cat.categories
Series.nunique = len(Series.cat.categories)
```
Heres an example in iPhython:
```
s = pd.Series(np.random.choi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12279 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12279/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12279/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12279/events | https://github.com/pandas-dev/pandas/issues/12279 | 132,683,900 | MDU6SXNzdWUxMzI2ODM5MDA= | 12,279 | ENH: Conditional mpl formatting | {
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"id": 241332... | open | false | null | [] | null | 3 | 2016-02-10T12:17:34Z | 2021-04-23T00:50:04Z | null | CONTRIBUTOR | null | In line with
- [ENH: Conditional HTML Formatting](https://github.com/pydata/pandas/pull/10250)
- [Support for Conditional HTML Formatting](http://pandas.pydata.org/pandas-docs/version/0.17.1/whatsnew.html#whatsnew-0171-style)
- [Style](http://pandas-docs.github.io/pandas-docs-travis/style.html)
add the same possibili... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12280 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12280/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12280/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12280/events | https://github.com/pandas-dev/pandas/issues/12280 | 132,692,095 | MDU6SXNzdWUxMzI2OTIwOTU= | 12,280 | Helper class to keep enable autocomplete of the columns in notebooks | {
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] | closed | false | null | [] | null | 10 | 2016-02-10T12:53:21Z | 2016-02-10T17:07:39Z | 2016-02-10T15:07:43Z | NONE | null | When working on the notebook I am always annoyed that column names do not autocomplete in all scenarios.
`dataframe = pd.DataFrame({'COL1':[1,2,3],'COL2':[2,3,4]})`
When typing
`dataframe['CO <--- The notebook will suggest COL1 and COL2 when pressing TAB`
but im lost when using
`pd.pivot_table(index='CO <... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12281 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12281/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12281/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12281/events | https://github.com/pandas-dev/pandas/pull/12281 | 132,704,537 | MDExOlB1bGxSZXF1ZXN0NTg4OTIxNDY= | 12,281 | DOC: extract/extractall clarifications | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-02-10T13:47:37Z | 2016-02-10T16:22:59Z | 2016-02-10T16:22:36Z | CONTRIBUTOR | null | This PR clarifies the new documentation for extract and extractall.
It was requested by @jreback in https://github.com/pydata/pandas/pull/11386#issuecomment-182105142
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https://api.github.com/repos/pandas-dev/pandas/issues/12282 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12282/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12282/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12282/events | https://github.com/pandas-dev/pandas/issues/12282 | 132,724,735 | MDU6SXNzdWUxMzI3MjQ3MzU= | 12,282 | BUG: Series.reindex using TimedeltaIndex/PeriodIndex/DatetimeIndex as index will erase the data to np.NaN | {
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the result will have np.NaN as data
``` python
In [1]: import pandas as pd
In [2]: # Case of `TimedeltaIndex`
In [3]: a = pd.Series(['A'] * 3)
In [4]: t_d_idx = pd.to_timedelta([0, 10, 20], unit='s')
In [5]: type(t_d_idx)
Ou... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12283 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12283/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12283/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12283/events | https://github.com/pandas-dev/pandas/issues/12283 | 132,769,000 | MDU6SXNzdWUxMzI3NjkwMDA= | 12,283 | DOC: show how to use to_xarray then use xarray to perform analysis on Panels | {
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"followers_url": "https://api.github.com/users/jr... | 9 | 2016-02-10T17:42:04Z | 2017-04-12T10:32:06Z | 2017-04-12T10:32:06Z | CONTRIBUTOR | null | I think we need a section to address this, not really sure where should put it. Also want to link from the doc-string.
also prob need some examples in the doc-string.
xref #11972
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https://api.github.com/repos/pandas-dev/pandas/issues/12284 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12284/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12284/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12284/events | https://github.com/pandas-dev/pandas/pull/12284 | 132,770,161 | MDExOlB1bGxSZXF1ZXN0NTg5MjY5NDQ= | 12,284 | BUG: Allow 'apply' to be used with non-numpy-dtype DataFrames | {
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when using a development pandas instance, if `pandas.test()` is called while the working directory of the python interpreter is within the pandas repository, it fails to detect any tests, at least on windows:
```
[pandas_dev] C:\Users... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12286 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12286/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12286/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12286/events | https://github.com/pandas-dev/pandas/issues/12286 | 132,842,157 | MDU6SXNzdWUxMzI4NDIxNTc= | 12,286 | Feature suggestion: flexible hierarchical data (json) importer (will implement if interest exists) | {
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I recently wrote a very flexible module for flattening hierarchical (json) data into CSV: https://github.com/tkluck/Text-CSV-Flatten.
It encodes the exact semantics of the flattening by a pattern string. For example, the pattern `.<index>.*` flattens in the same way as `orient="records"`. The pattern `.*.<i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12287 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12287/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12287/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12287/events | https://github.com/pandas-dev/pandas/pull/12287 | 132,897,844 | MDExOlB1bGxSZXF1ZXN0NTg5OTQ0NjU= | 12,287 | BUG: Fixes KeyError when indexes don't overlap. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12288 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12288/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12288/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12288/events | https://github.com/pandas-dev/pandas/issues/12288 | 132,924,678 | MDU6SXNzdWUxMzI5MjQ2Nzg= | 12,288 | RangeIndex copy behaviour differs from other indices | {
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"description": "Related to indexing on s... | closed | false | null | [] | {
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```
In [2]: i = pd.Int64Index(range(10))
In [3]: i.name = 'original'
In [4]: j = pd.Int64Index(i)
In... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12289 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12289/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12289/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12289/events | https://github.com/pandas-dev/pandas/pull/12289 | 132,928,390 | MDExOlB1bGxSZXF1ZXN0NTkwMDc3Mjc= | 12,289 | BUG: provide chunks with progressively numbered (default) indices | {
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Notice the test I fix was indeed wrong - I had written that line as a workaround waiting for this fix.
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https://api.github.com/repos/pandas-dev/pandas/issues/12290 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12290/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12290/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12290/events | https://github.com/pandas-dev/pandas/issues/12290 | 132,945,185 | MDU6SXNzdWUxMzI5NDUxODU= | 12,290 | Computing time difference with timezone in Series with one row gives wrong result | {
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```
In [133]: import pandas as pd
In [134]: df = pd.DataFrame(columns=['s', 'f'])
In [135]: df.s = [pd.Timestamp('2016-02-08 13:43:14.605000', tz='America/... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12291 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12291/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12291/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12291/events | https://github.com/pandas-dev/pandas/pull/12291 | 132,945,910 | MDExOlB1bGxSZXF1ZXN0NTkwMTcxNzQ= | 12,291 | ENH: add empty() methods for DataFrame and Series | {
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"followers_url": "https://api.github.com/users/jorisva... | 30 | 2016-02-11T11:18:36Z | 2019-11-18T02:56:00Z | 2016-02-11T12:02:49Z | MEMBER | null | Added `empty()` methods to the `Series` and `DataFrame` classes analogous to the `empty()` function in the `numpy` library that can also accept `scipy` duck-type `dtypes` in addition to `numpy` `dtypes`.
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https://api.github.com/repos/pandas-dev/pandas/issues/12292 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12292/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12292/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12292/events | https://github.com/pandas-dev/pandas/issues/12292 | 132,966,302 | MDU6SXNzdWUxMzI5NjYzMDI= | 12,292 | read_excel crash with empty Exception | {
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Small test case: content of excel file:
| A | B | C | D |
| --- | --- | --- | --- |
| | 1 | 100 | f |
| | 2 | 200 | f |
| | 3 | 300 | f |
| | 4 | 400 | f |
Run:
```
import pandas as pd
pd.read_excel("test_excel_.xls", par... | {
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"followers_url": "https://api.github.com/users/jr... | 7 | 2016-02-11T14:30:25Z | 2016-02-12T14:46:07Z | 2016-02-12T14:46:07Z | CONTRIBUTOR | null | Don't think an issue has been made? It's been failing for a while (`complex128` comparison, `numexpr` related?), but didn't always fail until 81e3303
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"followers_url": "https://api.github.com/users/jr... | 4 | 2016-02-11T15:13:40Z | 2016-02-12T14:30:34Z | 2016-02-12T14:30:24Z | CONTRIBUTOR | null | Closes #7222
Missing freqstr 'C' in `_period_code_map`
I found `pandas/tseries/tests/test_frequencies.py:TestFrequencyCode.test_freq_code` cover this change.
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https://api.github.com/repos/pandas-dev/pandas/issues/12295 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12295/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12295/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12295/events | https://github.com/pandas-dev/pandas/pull/12295 | 133,001,807 | MDExOlB1bGxSZXF1ZXN0NTkwNDUyNTc= | 12,295 | BUG: Refine validation of parameters to RangeIndex.__init__ | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12296 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12296/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12296/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12296/events | https://github.com/pandas-dev/pandas/pull/12296 | 133,041,486 | MDExOlB1bGxSZXF1ZXN0NTkwNjgzNzA= | 12,296 | Fix #12292 : error when read one empty column from excel file | {
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also fix #9002
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https://api.github.com/repos/pandas-dev/pandas/issues/12297 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12297/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12297/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12297/events | https://github.com/pandas-dev/pandas/pull/12297 | 133,091,551 | MDExOlB1bGxSZXF1ZXN0NTkwOTYyNTQ= | 12,297 | Improvements to str_cat | {
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closes #11334.
Modified behavior of str_cat to ignore NaN values in the Series by default.
Added some doc examples to make the behavior with nan more clear, and catch an error condition when a sep is passed instead of an others (array) as an argument and print a more intuitive error message.
This is a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12298 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12298/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12298/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12298/events | https://github.com/pandas-dev/pandas/issues/12298 | 133,101,017 | MDU6SXNzdWUxMzMxMDEwMTc= | 12,298 | crosstab is not respecting filtered scope when dtype=category | {
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There is some issue with crosstab, when applied on a DataFrame which has been derived from a DataFrame consisting of categorized columns.
Let's consider the following example df:
```
import... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12299 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12299/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12299/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12299/events | https://github.com/pandas-dev/pandas/pull/12299 | 133,104,609 | MDExOlB1bGxSZXF1ZXN0NTkxMDQ1MTg= | 12,299 | BUG: Make dict iterators real iterators, provide "next()" in Python 2 | {
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```
In [3]: next(six.itervalues({1:2}))
Out[3]: 2
```
with
```
In [4]: next(pd.compat.itervalues({1:2}))
---------------------------------------------------------------------------
TypeError T... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12300 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12300/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12300/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12300/events | https://github.com/pandas-dev/pandas/pull/12300 | 133,111,670 | MDExOlB1bGxSZXF1ZXN0NTkxMDkxMDM= | 12,300 | NaT.isoformat() returns 'NaT'. | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2016-02-11T23:06:54Z | 2016-02-15T22:57:28Z | 2016-02-15T22:57:14Z | CONTRIBUTOR | null | NaT.isoformat() returning 'NaT' allows users to use Timestamp to
rehydrate any _Timestamp object from its isoformat. This means that it
is safe to use _Timestamp.isoformat() as a serialization format for
timestamps where NaT is a valid value.
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https://api.github.com/repos/pandas-dev/pandas/issues/12301 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12301/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12301/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12301/events | https://github.com/pandas-dev/pandas/issues/12301 | 133,121,032 | MDU6SXNzdWUxMzMxMjEwMzI= | 12,301 | ERR: stat function kwarg interpretation | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12302 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12302/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12302/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12302/events | https://github.com/pandas-dev/pandas/pull/12302 | 133,128,050 | MDExOlB1bGxSZXF1ZXN0NTkxMTc5NzY= | 12,302 | BUG: Fix subtraction with timezone Series | {
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objects containing tz-aware objects would return a timedelta of zero, even though it visually could not be the case.
The bug was traced to the conversion of the contained timezones to UTC, in which the method call was somehow... | {
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... | 21 | 2016-02-12T00:43:14Z | 2020-04-19T21:25:07Z | 2020-04-19T21:25:06Z | NONE | null | Converting floating-point value NaN to any integer data type is an undefined behavior in C. However, it actually happens in numpy extension module, which is probably caused by incorrect usage of it from pandas. If the former is built with Clang+UBSan (http://clang.llvm.org/docs/UndefinedBehaviorSanitizer.html), there a... | {
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