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https://api.github.com/repos/pandas-dev/pandas/issues/9702 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9702/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9702/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9702/events | https://github.com/pandas-dev/pandas/pull/9702 | 63,584,380 | MDExOlB1bGxSZXF1ZXN0MzE2OTY1NTQ= | 9,702 | DOC: add automatic content to 0.16.1 whatsnew file | {
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... | closed | false | null | [] | null | 2 | 2015-03-23T00:51:44Z | 2015-03-23T01:26:44Z | 2015-03-23T01:26:31Z | CONTRIBUTOR | null | This behavior seems strange to me. Starting with a multiindex dataframe with unbalanced levels:
``` python
In [3]: pd.__version__
Out[3]: '0.15.2'
In [4]: df = pd.read_csv(StringIO('''
A,B,x
three,a,1
three,b,2
three,c,3
two,a,4
two,b,5
one,a,6'''), index_col=list('AB'))
In [5]: df
Out[5]:
x
A B
thr... | {
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... | 1 | 2015-03-23T04:20:16Z | 2020-06-28T04:37:46Z | null | MEMBER | null | Compare the output of these three groupby/apply calls:
```
In [66]: df = pd.DataFrame({'a': [1, 1, 2, 2], 'b': range(4)})
In [67]: df
Out[67]:
a b
0 1 0
1 1 1
2 2 2
3 2 3
In [68]: df.groupby('a')['b'].apply(lambda x: 2 * x)
Out[68]:
0 0
1 2
2 4
3 6
dtype: int64
In [69]: df.groupby('a').apply... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9705 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9705/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9705/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9705/events | https://github.com/pandas-dev/pandas/pull/9705 | 63,629,530 | MDExOlB1bGxSZXF1ZXN0MzE3MDYwMTY= | 9,705 | DOC: add DataFrame.assign to API docs | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-03-23T05:32:39Z | 2015-03-25T00:49:17Z | 2015-03-24T10:36:05Z | MEMBER | null | @TomAugspurger does this look like the right place to put this?
@jorisvandenbossche can we possibly merge this into the docs for v0.16?
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https://api.github.com/repos/pandas-dev/pandas/issues/9706 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9706/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9706/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9706/events | https://github.com/pandas-dev/pandas/pull/9706 | 63,672,088 | MDExOlB1bGxSZXF1ZXN0MzE3MTQ3MDI= | 9,706 | DOC: try to use matplotlib style (mpl >= 1.4) in all docs | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9708 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9708/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9708/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9708/events | https://github.com/pandas-dev/pandas/issues/9708 | 63,707,877 | MDU6SXNzdWU2MzcwNzg3Nw== | 9,708 | Allow to select index in drop_duplicates and duplicated | {
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... | 8 | 2015-03-23T12:11:47Z | 2020-03-11T13:58:00Z | 2015-03-25T22:56:58Z | CONTRIBUTOR | null | there’s no way to drop rows with duplicated index using `drop_duplicates`.
we’d have to add a copy of the index as column, or do this:
``` python
df[np.logical_not(df.index.duplicated(take_last=True).values)]
```
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https://api.github.com/repos/pandas-dev/pandas/issues/9709 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9709/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9709/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9709/events | https://github.com/pandas-dev/pandas/issues/9709 | 63,717,744 | MDU6SXNzdWU2MzcxNzc0NA== | 9,709 | printing a dataframe ignores timezone information of columns containing datetime64 | {
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"descript... | closed | false | null | [] | null | 1 | 2015-03-23T12:59:26Z | 2015-03-23T14:49:18Z | 2015-03-23T14:48:59Z | NONE | null | I have a dataframe with a column containing dates (I do not want to use this column as the index of my dataframe). When printing the dataframe, the timezone information is lost. Directly accessing the _.values_ shows the correct timezone.
This might be related to #6415
``` python
import pandas as pd
print "pandas v... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9710 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9710/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9710/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9710/events | https://github.com/pandas-dev/pandas/issues/9710 | 63,724,227 | MDU6SXNzdWU2MzcyNDIyNw== | 9,710 | read_csv skips rows with value 0 if having initial space | {
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I have something like the following csv file:
```
MyColumn
0
1
0
1
```
Note the initial space in each row.
Upgrading from 0.14.1 to 0.16 I recognized that read_csv started throwing away the 0 rows
```
In [28]: import pandas
In [29]: from StringIO import StringIO
In [30]: data = 'MyColumn\n 0\n 1... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9711 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9711/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9711/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9711/events | https://github.com/pandas-dev/pandas/pull/9711 | 63,725,834 | MDExOlB1bGxSZXF1ZXN0MzE3MzI3Mjc= | 9,711 | SAS xport file reader | {
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"followers_url": "https://api.github.com/users/jr... | 31 | 2015-03-23T13:45:08Z | 2015-11-12T23:43:34Z | 2015-08-14T15:40:16Z | CONTRIBUTOR | null | Here is an initial attempt to port Jack Cushman's xport file reader into Pandas.
Partially addresses #4052 (but this only deals with xport files, not sas7bdat files)
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https://api.github.com/repos/pandas-dev/pandas/issues/9712 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9712/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9712/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9712/events | https://github.com/pandas-dev/pandas/issues/9712 | 63,795,241 | MDU6SXNzdWU2Mzc5NTI0MQ== | 9,712 | to_csv and bytes on Python 3. | {
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"i... | open | false | null | [] | null | 12 | 2015-03-23T18:21:21Z | 2020-06-29T15:36:49Z | null | CONTRIBUTOR | null | Is this desired behavior and something I need to work around or a bug? Notice the byte type marker is written to disk so you can't round-trip the data. This works fine in Python 2 with unicode AFAICT.
```
In [1]: pd.__version__
Out[1]: '0.15.2-252-g0d35dd4'
In [2]: pd.DataFrame.from_dict({'a': ['a', 'b', 'c']}).a.str... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9713 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9713/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9713/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9713/events | https://github.com/pandas-dev/pandas/issues/9713 | 63,822,502 | MDU6SXNzdWU2MzgyMjUwMg== | 9,713 | On demand imports failing in pandas.io.gbq | {
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"description": "pandas-gbq compatability... | closed | false | null | [] | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9714 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9714/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9714/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9714/events | https://github.com/pandas-dev/pandas/issues/9714 | 63,866,408 | MDU6SXNzdWU2Mzg2NjQwOA== | 9,714 | to_datetime 1000x slower for timezone-aware strings vs timezone-agnostic | {
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```
dates = pd.Series(pd.date_range('1/1/2000', periods=2000))
string_dates = dates.apply(lambda s: str(s))
tz_string_dates = string_dates.apply(lambda dt: dt + ' -0800')
%timeit p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9715 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9715/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9715/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9715/events | https://github.com/pandas-dev/pandas/pull/9715 | 63,913,297 | MDExOlB1bGxSZXF1ZXN0MzE3OTk4ODY= | 9,715 | PERF: add initial asv config and vbench->asv conversion script | {
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"followers_url": "https://api.github.com/users/jr... | 27 | 2015-03-24T06:13:49Z | 2015-08-19T00:44:21Z | 2015-08-19T00:32:16Z | CONTRIBUTOR | null | @jorisvandenbossche Here's the initial pass I was referencing in our discussion in #9660; also relevant closes #8361.
A few caveats:
- The `eval` suite will have to be converted by hand, as my `ast` transformer isn't parsing the string in `eval("df1 + df2")`
- Lots of test failures that I haven't even looked at
- `... | {
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Lately I have started to use pandas heavily with relatively big files.
When the RAM becomes full I delete (with del and gc) the big objects (Data
frames), though this doesn't clear the memory.
Can some onr please advise how to clear variables from RAM, similar to R with rm(some_object) ; gc()
Additionally did so... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9717 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9717/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9717/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9717/events | https://github.com/pandas-dev/pandas/pull/9717 | 63,987,780 | MDExOlB1bGxSZXF1ZXN0MzE4MjI4MzI= | 9,717 | Documentation how to drop duplicate indices | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-03-24T12:50:10Z | 2015-03-25T22:57:26Z | 2015-03-25T22:57:26Z | CONTRIBUTOR | null | fixes #9708
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https://api.github.com/repos/pandas-dev/pandas/issues/9718 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9718/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9718/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9718/events | https://github.com/pandas-dev/pandas/issues/9718 | 64,032,397 | MDU6SXNzdWU2NDAzMjM5Nw== | 9,718 | to_csv keyword arguments missing? | {
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```
dflabels.to_csv('labels.do', encoding='utf-8', index=False, sep='\n', quoting=False, quotechar=' ')
```
I get the following error
```
TypeError Traceback (most recent call last)
<ipython-input-20-33258... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9719 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9719/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9719/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9719/events | https://github.com/pandas-dev/pandas/issues/9719 | 64,039,775 | MDU6SXNzdWU2NDAzOTc3NQ== | 9,719 | Cannot get Yahoo option data using Remote Data Access of Pandas | {
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from pandas.io.data... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9720 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9720/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9720/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9720/events | https://github.com/pandas-dev/pandas/issues/9720 | 64,046,925 | MDU6SXNzdWU2NDA0NjkyNQ== | 9,720 | Problem subtracting two datetime64 columns with non unique index | {
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```
df = pd.DataFrame({'A': pd.date_range('20150301', '20150304'),
'B': pd.date_range('20150303', '20150306')},
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https://api.github.com/repos/pandas-dev/pandas/issues/9721 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9721/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9721/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9721/events | https://github.com/pandas-dev/pandas/pull/9721 | 64,095,849 | MDExOlB1bGxSZXF1ZXN0MzE4NjgxNDM= | 9,721 | DOC: fix api documentation for accessors | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-03-24T20:46:41Z | 2015-05-11T12:47:19Z | 2015-05-11T12:28:04Z | MEMBER | null | Closes #9599
With this I updated the docs (assign docstring included in API, and the cat/str/dt accessors now documented correctly).
The Categorical page without methods and attributes is not yet working.
Will complete this for the v0.16.1 docs
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https://api.github.com/repos/pandas-dev/pandas/issues/9722 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9722/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9722/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9722/events | https://github.com/pandas-dev/pandas/pull/9722 | 64,172,038 | MDExOlB1bGxSZXF1ZXN0MzE4OTI5MjQ= | 9,722 | Moved imports into functions that use them | {
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closes #8327
Changes to be committed:
modified: pandas/io/gbq.py
Moved google api imports into functions that call them, removed unused imports. This fixes #9713
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https://api.github.com/repos/pandas-dev/pandas/issues/9723 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9723/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9723/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9723/events | https://github.com/pandas-dev/pandas/pull/9723 | 64,245,180 | MDExOlB1bGxSZXF1ZXN0MzE5MTI2NjA= | 9,723 | BUG: _retry_read_url retries connection even if successful | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9724 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9724/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9724/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9724/events | https://github.com/pandas-dev/pandas/issues/9724 | 64,246,895 | MDU6SXNzdWU2NDI0Njg5NQ== | 9,724 | Scatter plot colour incorrect for 3 scatter points. | {
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... | open | false | null | [] | null | 2 | 2015-03-25T11:26:11Z | 2021-04-18T05:57:13Z | null | CONTRIBUTOR | null | Based on the Stack Overflow question [here](http://stackoverflow.com/q/29253027/3005188) I believe I've found a bug for when a scatter plot only has three points. The full details are in the question but I'll sketch out the details here.
The code (below) will create a scatter plot where each of the points has a differ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9725 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9725/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9725/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9725/events | https://github.com/pandas-dev/pandas/pull/9725 | 64,249,559 | MDExOlB1bGxSZXF1ZXN0MzE5MTQ0NTY= | 9,725 | TST: Fix dateutil version check | {
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"description": ... | closed | false | null | [] | null | 2 | 2015-03-25T11:44:34Z | 2015-03-25T22:48:08Z | 2015-03-25T22:06:21Z | CONTRIBUTOR | null | This allows the test to pass when using dateutil version 2.4.0
```
In [2]: '2.4.0' <= LooseVersion('2.4')
Out[2]: False
In [3]: '2.4.0' <= LooseVersion('2.4.0')
Out[3]: True
```
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https://api.github.com/repos/pandas-dev/pandas/issues/9726 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9726/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9726/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9726/events | https://github.com/pandas-dev/pandas/issues/9726 | 64,252,679 | MDU6SXNzdWU2NDI1MjY3OQ== | 9,726 | "c"-engine read_table sigsegv when chunksize close to multiple of file length? | {
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```
table_generator = pd.io.parsers.read_table(chromosome_file, sep="\t", engine="c",
chunksize=50000, names=["Start", "End", "Strand"],
usecols=[1, 2, 5])
for chunk in table_generator:
prin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9727 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9727/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9727/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9727/events | https://github.com/pandas-dev/pandas/pull/9727 | 64,261,842 | MDExOlB1bGxSZXF1ZXN0MzE5MTkwMDU= | 9,727 | ENH: Add an axis parameter to DataFrame.diff | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9728 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9728/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9728/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9728/events | https://github.com/pandas-dev/pandas/issues/9728 | 64,289,766 | MDU6SXNzdWU2NDI4OTc2Ng== | 9,728 | iterrows turns some columns from int64 to float64 | {
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"color": "005... | closed | false | null | [] | null | 5 | 2015-03-25T14:53:38Z | 2015-09-16T11:25:53Z | 2015-03-25T15:19:47Z | CONTRIBUTOR | null | ``` python
>>> import pandas as pd
>>> pd.version.version
'0.15.2'
>>> df = pd.DataFrame({u'A': {123.0: 2.0}, u'B': {123.0: 1}})
>>> df
A B
123 2 1
>>> df['B'].dtype
dtype('int64')
>>> type(df.iterrows().next()[1]['B'])
<type 'numpy.float64'>
```
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... | 9 | 2015-03-25T17:18:20Z | 2021-04-18T05:58:08Z | null | NONE | null | As per http://pandas.pydata.org/pandas-docs/stable/io.html#handling-bad-lines, records with too many fields cause (depending on error_bad_lines) an exception to be thrown, or stderr to be written to.
Would it be possible to add an option, defaulting to False, that gave similar warnings/errors if there are _too few_ fi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9730 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9730/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9730/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9730/events | https://github.com/pandas-dev/pandas/issues/9730 | 64,344,895 | MDU6SXNzdWU2NDM0NDg5NQ== | 9,730 | Pandas concat breaks with axis specified | {
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InvalidIndexError: Reindexing only valid with uniquely valued Index objects
Pandas version: 0.16.0
OS: Ubuntu 14.04 LTS x64
Here's the pickle of the data structure causing this (it's rather large, ~60 megs, but it's my real use ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9731 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9731/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9731/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9731/events | https://github.com/pandas-dev/pandas/issues/9731 | 64,366,318 | MDU6SXNzdWU2NDM2NjMxOA== | 9,731 | [] (__getitem__) boolean indexing assignment bug with nans | {
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"description": "Related to indexing on s... | closed | false | null | [] | {
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``` python
import pandas as pd
import numpy as np
temp = pd.Series(np.random.randn(10))
temp[3:6] = np.nan
temp[8] = np.nan
nan_index = np.isnan(temp)
# this works
temp1 = temp.copy()
temp1[nan_index] = [99, 99, 99, 99]
temp1[nan_index]
3 99
4 99
5 99
8 99
dtype: float64
# this doesn't... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9732 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9732/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9732/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9732/events | https://github.com/pandas-dev/pandas/issues/9732 | 64,394,513 | MDU6SXNzdWU2NDM5NDUxMw== | 9,732 | Inconsistent behavior of partial string indexing vs straight indexing for timeseries data | {
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... | open | false | null | [] | {
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... | 2 | 2015-03-25T23:19:53Z | 2021-06-26T22:40:16Z | null | NONE | null | I recently ran into an issue where pandas is not handling the "<=" logical operator when comparing dates in an interesting way.
```
import pandas as pd
rng = pd.date_range('1/1/2011', periods=72, freq='H')
df = pd.DataFrame(rng)
df.columns=['date']
crit = (df['date'] >= '2011-01-01') & (df['date'] <= '2011-01-02')
df... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9733 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9733/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9733/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9733/events | https://github.com/pandas-dev/pandas/issues/9733 | 64,537,629 | MDU6SXNzdWU2NDUzNzYyOQ== | 9,733 | Series.sum has inconsistent return type | {
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"color": "0e8... | closed | false | null | [] | {
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"created_at": "2015-02-26T19:29:05Z",
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"followers_url": "https://api.github.com/users/jorisva... | 5 | 2015-03-26T14:18:03Z | 2018-07-06T22:49:29Z | 2018-07-06T22:49:17Z | NONE | null | Series.sum returns a numpy type, except when it's empty, in which case it returns a python int of value "0":
```
In [2]: type(pd.Series([0]).sum())
Out[2]: numpy.int64
In [3]: type(pd.Series().sum())
Out[3]: int
```
This poses a problem when I do `1 / myserie.sum()` because I expect to obtain `np.inf` rather than a ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9734 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9734/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9734/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9734/events | https://github.com/pandas-dev/pandas/issues/9734 | 64,542,211 | MDU6SXNzdWU2NDU0MjIxMQ== | 9,734 | HDFStore: AttributeError: __exit__ in with statement | {
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"descript... | closed | false | null | [] | null | 7 | 2015-03-26T14:37:00Z | 2015-03-27T13:57:41Z | 2015-03-27T13:57:41Z | NONE | null | I have this method in a class:
```
def save(self, filename, key='/'):
"""Saves to an HDF5 store."""
with pd.HDFStore(filename) as store:
for g in self.GENDERS:
df = getattr(self, g)
store.put(key+g, df,
data_columns=df.columns,
format=... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9735 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9735/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9735/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9735/events | https://github.com/pandas-dev/pandas/issues/9735 | 64,547,932 | MDU6SXNzdWU2NDU0NzkzMg== | 9,735 | BUG: read_csv, engine='c' error | {
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] | closed | false | null | [] | {
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```
info
2681087 53329 1287215 1287215 53328
RSA 53328 53328 1287215 0
(I14) ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9736 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9736/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9736/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9736/events | https://github.com/pandas-dev/pandas/issues/9736 | 64,550,576 | MDU6SXNzdWU2NDU1MDU3Ng== | 9,736 | DataFrame.where does not respect axis parameter for n x n frames | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-03-26T15:06:50Z | 2015-08-18T11:20:29Z | 2015-08-18T11:20:29Z | CONTRIBUTOR | null | ```
In [3]: df = pd.DataFrame(np.random.randn(5, 5))
In [4]: s = pd.Series(range(5))
In [5]: df.where(df.isnull(), s, axis=0)
Out[5]:
0 1 2 3 4
0 0 1 2 3 4
1 0 1 2 3 4
2 0 1 2 3 4
3 0 1 2 3 4
4 0 1 2 3 4
In [6]: df.where(df.isnull(), s, axis=1)
Out[6]:
0 1 2 3 4
0 0 1 2 3 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9737 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9737/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9737/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9737/events | https://github.com/pandas-dev/pandas/issues/9737 | 64,593,912 | MDU6SXNzdWU2NDU5MzkxMg== | 9,737 | plotting: passing in ax is removing the wrong x labels | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2015-03-26T17:52:47Z | 2015-09-01T14:14:18Z | 2015-04-02T14:30:11Z | CONTRIBUTOR | null | The following code will show the x labels on the right side, but actually it should show the labels at the bottom (or better: should show all!)
```
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib as mpl
import matplotlib.gridspec as gridspec
import pandas as pd
gs = mpl.gridspec.GridSpec(2, 2)
ax_... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9738 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9738/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9738/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9738/events | https://github.com/pandas-dev/pandas/issues/9738 | 64,675,716 | MDU6SXNzdWU2NDY3NTcxNg== | 9,738 | Raise warning when automatically converting datatypes | {
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... | 12 | 2015-03-27T02:25:52Z | 2021-04-18T06:05:37Z | 2021-04-18T06:05:37Z | CONTRIBUTOR | null | A frequent bug I end up fixing in my own code when working with integer data results from my data auto converting to float, usually on a merge, reindex, unstack, or pivot.
```
In [6]: df = pd.DataFrame(np.random.randn(5, 5), columns=list('abcde'), dtype=int)
In [7]: df.dtypes
Out[7]:
a int64
b int64
c int64
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https://api.github.com/repos/pandas-dev/pandas/issues/9739 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9739/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9739/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9739/events | https://github.com/pandas-dev/pandas/issues/9739 | 64,723,255 | MDU6SXNzdWU2NDcyMzI1NQ== | 9,739 | Yahoo Datareader RemoteDataError when end date added in Python 3 | {
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http://stackoverflow.com/questions/29296045/pandas-yahoo-datareader-remotedataerror-when-end-date-added?noredirect=1#comment46788752_29296045
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https://api.github.com/repos/pandas-dev/pandas/issues/9740 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9740/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9740/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9740/events | https://github.com/pandas-dev/pandas/pull/9740 | 64,765,634 | MDExOlB1bGxSZXF1ZXN0MzIxMDg2MDk= | 9,740 | Plotting: don't change visibility of xaxis labels and ticklabels if passing in a axis | {
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- fix for changing the wrong xlabels/xticklabels if a gridspec is used and the ax is passed in (not sure about using subplot without gridspec)
- changes the default behaviour for sharex if an axis is passed in: before the visibility changes were applied per default, now they are only applied if ex... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9741 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9741/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9741/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9741/events | https://github.com/pandas-dev/pandas/pull/9741 | 64,859,915 | MDExOlB1bGxSZXF1ZXN0MzIxNDg4OTk= | 9,741 | ENH: support CategoricalIndex (GH7629) | {
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xref #8613
xref #8074
- [x] docs / whatsnew
- [x] ~~auto-create a `CategoricalIndex` when grouping by a `Categorical` (this doesn't ATM)~~
- [x] adding a value not in the Index, e.g. `df2.loc['d'] = 5` should do what? (currently will coerce to an `Index`)
- [x] `pd.concat([df2,df])` should STILL have a `... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9742 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9742/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9742/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9742/events | https://github.com/pandas-dev/pandas/pull/9742 | 64,893,230 | MDExOlB1bGxSZXF1ZXN0MzIxNTg1MDU= | 9,742 | BUG: Bring pandas up to date with pandas-datareader | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-03-28T03:30:41Z | 2015-04-07T09:05:49Z | 2015-03-29T17:10:43Z | CONTRIBUTOR | null | Two bug fixes from pandas-datareader.
pydata/pandas-datareader#25
pydata/pandas-datareader#24
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The main issue is when the destination and source arrays have different lengths, `np.putmask` doesn't behave like `arr[mask] = values`:
"Sets `a.flat[n] = values[n]` for each n where `mask.flat[n]==True`"
We have to use `np.place` instead. A secondary issue is that `np.place` doesn't automatically conve... | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2015-03-28T17:42:50Z | 2015-04-09T15:13:42Z | 2015-04-09T15:13:42Z | CONTRIBUTOR | null | Line 334: raw_locales = [] deletes the data received from locale_getter, so the return from this function is always a blank list.
``` python
try:
raw_locales = locale_getter()
except:
return None
try:
# raw_locales is "\n" seperated list of locales
# it may contain non-decoda... | {
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Tested at the block manager level and above it at the frame level.
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``` python
In [2]: df = pd.DataFrame({'x':['a', 'a', 'b'], 'y':['j', 'k', 'j'], 'z':[0, 1, 2]})
In [3]: df.set_index(['x', 'y']).unstack()
Out[3]:
z
y j k
x
a 0 1
b 2 NaN
```
If I want to fill with -1, i need to `fillna` and then `astype` back to `int`. Ideally:
``` python
In [3]: df.set_index... | {
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```
======================================================================
ERROR: test_basics_with_nan (pandas.io.tests.test_excel.Openpyxl2Tests)
------------------------------------------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9748 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9748/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9748/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9748/events | https://github.com/pandas-dev/pandas/issues/9748 | 65,107,624 | MDU6SXNzdWU2NTEwNzYyNA== | 9,748 | ENH: support CategoricalIndex Followups | {
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... | 3 | 2015-03-29T23:34:21Z | 2019-10-21T20:06:20Z | null | CONTRIBUTOR | null | followup to #9741
These are all commented in `pandas/core/test_frame/test_categorical_indexing_index`
- [ ] support slice semantics
- [x] fix index name issue on selection for non-existant label that IS in the categories
- [x] fix index name issue on assignment for non-existan label that IS in the categories
- [ ] du... | {
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I used line 124 to look into the problem.
```
# for codes see: http://www.gummy-stuff.org/[redacted]-data.htm
```
Is another reliable source available?
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df = pandas.DataFrame([[1, 1, 1],[2, 1, 1],[2, 1, 1],[numpy.nan, numpy.nan, numpy.nan]], columns=["a","b","c"])
I try different methods to fill missing values. These work as expected:
df.fillna(df.mean())
df.fillna(df.median())
But this doesnt work:
df.fillna(df.mode())
Inspecting the output... | {
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... | 3 | 2015-03-31T00:30:34Z | 2021-04-18T06:10:33Z | null | NONE | null | I have a dictionary of Series that I'm converting to a DataFrame via `DataFrame.from_dict`, and the Series have index values that are tuples, as in these examples:
``` python
In [39]: pd.DataFrame.from_dict({'a': pd.Series([1, 2, 3], index=[('x',), ('y',), ('z',)])}, orient='index')
Out[39]:
x y z
a 1 2 3
In ... | {
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"followers_url": "https://api.github.com/users/wesm... | 4 | 2015-03-31T00:35:32Z | 2019-12-12T21:05:08Z | 2019-12-12T21:05:08Z | CONTRIBUTOR | null | I came across some inconsistencies in how `first_valid_index()` works on empty `Series` and `DataFrames` (and `last_valid_index()`).
``` python
>>> print(pd.DataFrame().first_valid_index())
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/will/.virtualenvs/dev3/lib/python3.4/site-... | {
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] | closed | false | null | [] | null | 1 | 2015-03-31T01:43:02Z | 2019-12-13T20:38:40Z | 2019-12-13T20:38:40Z | NONE | null | Hey folks --
I'm writing a large CSV (100M rows) to a sqlite database through Pandas in 10k chunks.
```
disk_engine = create_engine('sqlite:///100M.db')
chunksize = 10000
index_start = 0
for df in pd.read_csv('100M_rows.csv', chunksize=chunksize, iterator=True, encoding='utf-8'):
df.index += index_start
df.to... | {
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"followers_url": "https://api.github.com/users/jr... | 13 | 2015-03-31T02:23:20Z | 2015-05-05T18:03:08Z | 2015-04-03T00:41:09Z | CONTRIBUTOR | null | Closes #6232
In working with the various "Contributing" documents recently it was clear that we needed to combine them. This is a stab at doing so. I took the various components from pydata.org, CONTRIBUTING.md, various wiki pages, and the already included Documentation documents and created this file. I think it'... | {
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The arrays passed to the date_parser function is different when `names` and `use_cols` are specified to limit the number of parsed columns.
When running the example code below, the date_parser function receives two arguments, one array with '20140101' strings, and one array with integers. The default `da... | {
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In [1]: index = pd.DatetimeIndex(start='20150101', end='20150331', freq='B')
In [2]: df = pd.DataFrame(index=index, data=len(index)*[0])
In [3]: df.resample('BM', how='last')
Out[3]:
0
2015-01-30 0
2015-02-27 0
2015-03-31 0
2015-04-30 NaN
```
This is both in 0.14.1 and 0.15.2
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```
import pandas as pd
pd.Series([pd.Timestamp('2010-01-04 00:00:00')]).astype(str)
TypeError: cannot astype a datetimelike from [datetime64[ns]] to [|S0]
```
str(pd.Timestamp) works though, so why astype shouldn't?
Also the type representation "|S0" is not entirely clear to me.
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https://api.github.com/repos/pandas-dev/pandas/issues/9758 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9758/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9758/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9758/events | https://github.com/pandas-dev/pandas/pull/9758 | 65,433,152 | MDExOlB1bGxSZXF1ZXN0MzIzMTQzMzE= | 9,758 | BUG: allow conversion of Timestamp and Timedelta to string in astype | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9759 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9759/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9759/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9759/events | https://github.com/pandas-dev/pandas/issues/9759 | 65,434,346 | MDU6SXNzdWU2NTQzNDM0Ng== | 9,759 | FloatArrayFormatter._format_strings cannot handle float arrays containing NaNs | {
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"color": "ffa... | closed | false | null | [] | null | 7 | 2015-03-31T11:55:39Z | 2015-04-08T12:22:22Z | 2015-04-04T18:34:13Z | CONTRIBUTOR | null | Get `FloatingPointError` ([stack trace](http://pastebin.com/m1fZH4ie)) if call `to_html` method of a DataFrame that contains some NaN values. To reproduce:
``` python
import pandas as pd
import numpy as np
pd.DataFrame(data=[np.nan, 3, 4]).to_html()
```
The problem seems to be that `FloatArrayFormatter._format_strin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9760 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9760/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9760/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9760/events | https://github.com/pandas-dev/pandas/issues/9760 | 65,450,274 | MDU6SXNzdWU2NTQ1MDI3NA== | 9,760 | USMemorialDay defined incorrectly. | {
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```
>>> from pandas.tseries.holiday import AbstractHolidayCalendar, USMemorialDay
>>> class MemorialDayCalendar(AbstractHolidayCalendar): rules=[USMemorialDay]
>>> MemorialDayCalendar().holidays('2021','2022')
<class 'pandas.tseries.index.DatetimeIndex'>
[2021-05-24]
Length: 1, Fr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9761 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9761/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9761/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9761/events | https://github.com/pandas-dev/pandas/pull/9761 | 65,452,978 | MDExOlB1bGxSZXF1ZXN0MzIzMjI4Mzc= | 9,761 | **BUG**: GH9759 - allow FloatArrayFormatter to format arrays with NaNs | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9762 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9762/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9762/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9762/events | https://github.com/pandas-dev/pandas/issues/9762 | 65,458,026 | MDU6SXNzdWU2NTQ1ODAyNg== | 9,762 | API: DataFrame constructor for subclassing Series | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-03-31T13:58:19Z | 2015-04-18T23:18:33Z | 2015-04-18T23:18:33Z | MEMBER | null | `Series.to_frame` uses `pandas.DataFrame` statically as frame constructor. It is nice if `Series` has overridable property to specify frame-like constructor, like `DataFrame` has `_constructor_sliced`.
How about `Series._constructor_frame`?
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https://api.github.com/repos/pandas-dev/pandas/issues/9763 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9763/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9763/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9763/events | https://github.com/pandas-dev/pandas/pull/9763 | 65,496,185 | MDExOlB1bGxSZXF1ZXN0MzIzNDE0OTA= | 9,763 | BUG: incorrectly defined Memoridal Day holiday | {
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Memorial Day was incorrectly defined.
It is the last Monday in May, so the earliest it could be is the 25th (not the 24th).
This change fixes the problem.
```
>>> from pandas.tseries.holiday import AbstractHolidayCalendar, USMemorialDay
>>> class MemorialDayCalendar(AbstractHolidayCalendar):rules=[USMem... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9764 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9764/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9764/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9764/events | https://github.com/pandas-dev/pandas/issues/9764 | 65,498,174 | MDU6SXNzdWU2NTQ5ODE3NA== | 9,764 | Displaying DataFrame with values from range [1e-7, 5e-7] shows 0 in some situations. | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-03-31T16:53:40Z | 2015-04-06T00:18:30Z | 2015-04-06T00:18:30Z | CONTRIBUTOR | null | Hi,
For illustration purpose, I'll assume the following dataset:
``` python
In [1]: d=pd.DataFrame({'col1':[9.999e-8, 1e-7, 1.0001e-7, 2e-7, 4.999e-7, 5e-7, 5.0001e-7, 6e-7]})
In [2]: d
Out[2]:
col1
0 9.999000e-08
1 1.000000e-07
2 1.000100e-07
3 2.000000e-07
4 4.999000e-07
5 5.000000e-07
6 5.00010... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9765 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9765/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9765/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9765/events | https://github.com/pandas-dev/pandas/issues/9765 | 65,532,244 | MDU6SXNzdWU2NTUzMjI0NA== | 9,765 | concat erroneously sets series to NaN | {
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`concat` fails when:
1. Using a SparseDataFrame
2. AND that SparseDataFrame has a column of all `0.0` and a `fill_value` of `0.0`
If that SparseDataFrame doesn't have an all `0.0` column, it works beautifully.
``` python
import unittest
import pandas as pd
from pandas.util.testing import assert_frame_equa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9766 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9766/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9766/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9766/events | https://github.com/pandas-dev/pandas/pull/9766 | 65,542,594 | MDExOlB1bGxSZXF1ZXN0MzIzNjQ1MTk= | 9,766 | ENH: Add StringMethods.capitalize and swapcase | {
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... | 5 | 2015-03-31T22:56:10Z | 2020-10-23T22:07:24Z | null | CONTRIBUTOR | null | This is pandas 0.15.2
```
In [1]: from pandas import *
In [2]: df = DataFrame({"A" : [1,2,3,4,5], "B": [3.1, 4, 5, 6, 7]})
In [3]: df[["A", "B"]]["A"] = 5 # no warning - bug?!
In [4]: df
Out[4]:
A B
0 1 3.1
1 2 4.0
2 3 5.0
3 4 6.0
4 5 7.0
In [5]: df[["A"]]["A"] = 5
C:\Anaconda\Scripts\ipython-script.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9768 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9768/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9768/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9768/events | https://github.com/pandas-dev/pandas/issues/9768 | 65,637,712 | MDU6SXNzdWU2NTYzNzcxMg== | 9,768 | Invalid comparison of object Series objects containing None | {
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```
from pandas import Series
a = Series(['A', None])
b = Series(['A', None])
a == b
```
gives
```
0 True
1 False
dtype: bool
```
while `a[1] == b[1]` gives `True`. This is a) inconsistent and b) the behaviour of `a == b` is wrong (None is equal to None, so `a==b` should return `[True, True... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9769 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9769/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9769/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9769/events | https://github.com/pandas-dev/pandas/pull/9769 | 65,662,237 | MDExOlB1bGxSZXF1ZXN0MzI0MDk2Mzg= | 9,769 | Added documentation for mode() | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9770 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9770/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9770/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9770/events | https://github.com/pandas-dev/pandas/pull/9770 | 65,669,439 | MDExOlB1bGxSZXF1ZXN0MzI0MTI4NTM= | 9,770 | ENH: Add option in read_csv to infer compression type from filename | {
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"followers_url": "https://api.github.com/users/jr... | 10 | 2015-04-01T12:11:53Z | 2015-04-18T03:41:12Z | 2015-04-18T02:53:14Z | CONTRIBUTOR | null | Ideally, I would love for this to be the default, but that wouldn't be backwards-compatible in the case where the filename ends in '.gz' or '.bz2' and you want to treat it as uncompressed. That seems like it would be very rare, though.
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https://api.github.com/repos/pandas-dev/pandas/issues/9771 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9771/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9771/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9771/events | https://github.com/pandas-dev/pandas/issues/9771 | 65,686,760 | MDU6SXNzdWU2NTY4Njc2MA== | 9,771 | Website links to incorrect doc versions | {
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] | closed | false | null | [] | null | 2 | 2015-04-01T13:41:02Z | 2015-05-27T13:08:30Z | 2015-05-27T13:07:49Z | NONE | null | http://pandas.pydata.org/pandas-docs/dev/index.html PDF linnk returns a 0.14.x version of the document, other PDF links return 404. It all depends on how you get to the link. I suggest checking all the documentation links on the website to verify they are linking to the appropriate version of the documentation.
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https://api.github.com/repos/pandas-dev/pandas/issues/9772 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9772/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9772/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9772/events | https://github.com/pandas-dev/pandas/issues/9772 | 65,688,699 | MDU6SXNzdWU2NTY4ODY5OQ== | 9,772 | Groupby built by columns : cannot use .head() or .apply() | {
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"followers_url": "https://api.github.com/users/j... | 7 | 2015-04-01T13:50:32Z | 2020-11-13T04:43:10Z | 2020-11-13T04:43:10Z | CONTRIBUTOR | null | ``` python
import numpy as np
import pandas as pd
df = pd.DataFrame({i:pd.Series(np.random.normal(size=10),
index=range(10)) for i in range(11)})
df_g = df.groupby(['a']*6+['b']*5, axis=1)
```
This, if I well understood, should build a groupby object grouping columns, and so give the ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9773 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9773/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9773/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9773/events | https://github.com/pandas-dev/pandas/pull/9773 | 65,690,492 | MDExOlB1bGxSZXF1ZXN0MzI0MjEyMzc= | 9,773 | ENH: Add StringMethods.partition and rpartition | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9774 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9774/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9774/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9774/events | https://github.com/pandas-dev/pandas/issues/9774 | 65,694,889 | MDU6SXNzdWU2NTY5NDg4OQ== | 9,774 | pd.concat() fails with two large Series with datetime | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2015-04-01T14:08:43Z | 2016-07-11T13:28:23Z | 2016-07-11T13:28:20Z | CONTRIBUTOR | null | I have two multi-index dataframes `a_df` and `b_df`. When I try to concat them, the operation fails, but it works if `head` them first to a small size.
More specifically, note the following:
```
> pd.concat([a, b],
join='outer', axis=1, verify_integrity=True).dropna()
Empty DataFrame
Columns: [budget, de... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9775 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9775/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9775/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9775/events | https://github.com/pandas-dev/pandas/issues/9775 | 65,698,135 | MDU6SXNzdWU2NTY5ODEzNQ== | 9,775 | KeyError when key is present | {
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I have a TimeSeries created from a dp.read_sql_query using a sqlalchemy engine for a sqlite database.
I use this TimeSeries as a storage for data to work on. In each iteration I work on some data and errase it from the series with drop inplace.
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https://api.github.com/repos/pandas-dev/pandas/issues/9776 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9776/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9776/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9776/events | https://github.com/pandas-dev/pandas/issues/9776 | 65,700,186 | MDU6SXNzdWU2NTcwMDE4Ng== | 9,776 | BUG: DataFrame doesn't hold _metadata when sliced by slice instance | {
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] | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-01T14:31:30Z | 2015-04-04T18:32:40Z | 2015-04-04T18:32:40Z | MEMBER | null | ```
import pandas as pd
class TestDataFrame(pd.DataFrame):
_metadata = ['testattr']
@property
def _constructor(self):
return TestDataFrame
df = TestDataFrame({0: [1, 2, 3], 1: [1, 2, 3]})
df.testattr = 'XXX'
df.testattr
# XXX
# Using list is OK
df.iloc[[0, 1], :].testattr
# XXX
# Using slice ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9777 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9777/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9777/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9777/events | https://github.com/pandas-dev/pandas/issues/9777 | 65,704,870 | MDU6SXNzdWU2NTcwNDg3MA== | 9,777 | Predictable order for columns in assign through sorting | {
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"followers_url": "https://api.github.com/users/jr... | 7 | 2015-04-01T14:53:48Z | 2016-09-09T21:22:15Z | 2015-04-07T22:36:59Z | CONTRIBUTOR | null | The order of columns coming out of `.assign` is hard to predict
``` Python
In [1]: import pandas as pd
In [2]: df = pd.DataFrame({'a': [1], 'b': [2]})
In [3]: df
Out[3]:
a b
0 1 2
In [4]: df.assign(d=df.a*10, a=df.b*10, e=df.a*20)
Out[4]:
a b e d
0 20 2 20 10
```
Would it be reasonable to keep... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9778 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9778/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9778/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9778/events | https://github.com/pandas-dev/pandas/issues/9778 | 65,708,727 | MDU6SXNzdWU2NTcwODcyNw== | 9,778 | Wrong number of row in to_latex output for MultiIndex Dataframe | {
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``` python
pd.DataFrame.from_dict({
('c1', 0): pd.Series({x: x for x in range(4)}),
('c1', 1): pd.Series({x: x+4 for x in range(4)}),
('c2', 0): pd.Series({x: x for x in range(4)}),
('c2', 1): pd.Series({x: x+4 for x in range(4)}),
('c3', 0): pd.Series({x: x for x in... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9779 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9779/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9779/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9779/events | https://github.com/pandas-dev/pandas/issues/9779 | 65,714,847 | MDU6SXNzdWU2NTcxNDg0Nw== | 9,779 | secondary_y plot shows in separate figure | {
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"followers_url": "https://api.github.com/users/jr... | 11 | 2015-04-01T15:43:04Z | 2015-04-09T15:21:34Z | 2015-04-05T13:52:22Z | NONE | null | Hi, don't know if this is my Python/some module version.. but when I try to do the following, I end up with two figures popping up, instead of the expected one:
```
df[[0, 1]].plot(kind='bar', stacked=True, ylim=(0, 100))
df[[2]].plot(secondary_y=True, color='orange', linewidth=2.0)
```
The data in both plots looks r... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9780 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9780/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9780/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9780/events | https://github.com/pandas-dev/pandas/issues/9780 | 65,726,464 | MDU6SXNzdWU2NTcyNjQ2NA== | 9,780 | pd.merge() doesn't merge int and str column dtypes but no warning or error | {
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"created_at": "2017-10-20T10:17:09Z",
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"followers_url": "https://api.github.com/users/j... | 15 | 2015-04-01T16:36:12Z | 2018-03-19T21:45:09Z | 2017-12-10T15:41:37Z | NONE | null | When merging an int dtype with a str dtype the join does not work:
``` python
>>> import pandas as pd
>>> df1 = pd.DataFrame({"A":[0]})
>>> df2 = pd.DataFrame({"A":["0"]})
>>> pd.merge(df1, df2, on=["A"])
Empty DataFrame
Columns: [A]
Index: []
```
I think it would be better to get a warning that the join is performed... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9781 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9781/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9781/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9781/events | https://github.com/pandas-dev/pandas/issues/9781 | 65,768,497 | MDU6SXNzdWU2NTc2ODQ5Nw== | 9,781 | bug in dataframe.to_json causing segfault with 0.16.0 | {
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"description": "read_json, to_json, json... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2015-04-01T20:06:37Z | 2015-04-03T22:42:19Z | 2015-04-03T22:42:19Z | NONE | null | calling to_json on an apparently empty dataframe may segfault.
using the same dataframe with 0.15.2 works.
A git bisect says that commit a67bef49e0b8e89e785c08011e8331e9eb7e54b8 is when the problem first appeared.
segfault:
Program terminated with signal SIGSEGV, Segmentation fault.
#0 0x00007fd42aae8735 in PdBlock_... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9782 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9782/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9782/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9782/events | https://github.com/pandas-dev/pandas/issues/9782 | 65,782,709 | MDU6SXNzdWU2NTc4MjcwOQ== | 9,782 | Boolean negation gives wrong output when dtype is not boolean | {
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```
In [1]: import pandas as pd
In [2]: s = pd.Series([None,True])
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9783 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9783/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9783/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9783/events | https://github.com/pandas-dev/pandas/pull/9783 | 65,808,087 | MDExOlB1bGxSZXF1ZXN0MzI0NzQ4OTE= | 9,783 | Fix zlib and blosc imports in to_msgpack | {
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"followers_url": "https://api.github.com/users/jr... | 21 | 2015-04-02T00:52:27Z | 2015-04-13T16:01:48Z | 2015-04-13T16:01:48Z | CONTRIBUTOR | null | 6717aa06dcaa1950ffb46fef454f5df9404209bd removed zlib and blosc from the global namespace.
```
from pandas import read_csv
table = read_csv('aadhaar_data.csv')
table.to_msgpack('d.msg')
# NameError: global name 'blosc' is not defined
table.to_msgpack('d-blosc.msg', compress='blosc')
# NameError: global name 'zlib' i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9784 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9784/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9784/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9784/events | https://github.com/pandas-dev/pandas/issues/9784 | 65,818,583 | MDU6SXNzdWU2NTgxODU4Mw== | 9,784 | DataFrame.to_string truncates long strings | {
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"closed_at": "2020-01-30T12:18:05Z",
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``` text
FILENAME OBS_ID XUV
0 'mvn_iuv_l1a_IPH3-cycle00007-mode040-muvdark... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9785 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9785/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9785/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9785/events | https://github.com/pandas-dev/pandas/issues/9785 | 65,861,392 | MDU6SXNzdWU2NTg2MTM5Mg== | 9,785 | Error when comparing equality of indexes | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-02T07:15:43Z | 2015-04-14T13:41:01Z | 2015-04-14T13:41:01Z | CONTRIBUTOR | null | In 0.16.0 comparing MultiIndices using `==` raises an exception.
``` python
from StringIO import StringIO
import pandas as pd
# create a series using a multiindex
df = pd.read_csv(StringIO('a,b,c\n1,2,3'), index_col=[0, 1])
series = df['c']
series.index == series.index
# File "/Users/dan/venvs/pandas-0.16.0/lib/py... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9786 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9786/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9786/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9786/events | https://github.com/pandas-dev/pandas/issues/9786 | 65,889,422 | MDU6SXNzdWU2NTg4OTQyMg== | 9,786 | Timedeltaindex as columns + groupby fails | {
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"id": ... | closed | false | null | [] | null | 3 | 2015-04-02T09:35:10Z | 2015-04-02T12:37:45Z | 2015-04-02T12:01:46Z | CONTRIBUTOR | null | ``` python
import numpy as np
import pandas as pd
df = pd.DataFrame(np.random.normal(size=(10,15)))
df.columns = pd.timedelta_range(start='0s',periods=15,freq='1s')
df.groupby(['a']*5+['b']*5)
```
fails (throwing ValueError), whereas
``` python
df.transpose().groupby(['a']*5+['b']*5,axis=1)
```
doesn't.
```
INSTAL... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-02T11:02:27Z | 2015-04-14T13:28:04Z | 2015-04-14T13:28:04Z | NONE | null | This worked fine with pandas 0.15:
``` python
In [24]: import pandas as pd
In [25]: from decimal import Decimal
In [26]: s = pd.Series([Decimal(10)] * 10)
In [27]: s / Decimal(5)
Out[27]:
0 2
1 2
2 2
3 2
4 2
5 2
6 2
7 2
8 2
9 2
dtype: object
```
When I use 0.16.0, it raises:
```
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... | closed | false | null | [] | null | 1 | 2015-04-02T11:49:45Z | 2015-04-02T12:00:07Z | 2015-04-02T11:59:47Z | NONE | null | ```
import datetime as dt; import pandas as pd
d2 = dt.datetime(2015, 4, 2, 12, 23, 12, 567000)
df = pd.DataFrame([['Bar', d2]], columns=['name', 'date'])
df2 = df.sort('date').groupby('name').last().reset_index()
```
`df2` is
name date
0 Bar 2015-04-02 12:23:12.567000064
i.e. 64 nanoseconds were added to the t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9789 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9789/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9789/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9789/events | https://github.com/pandas-dev/pandas/issues/9789 | 65,954,852 | MDU6SXNzdWU2NTk1NDg1Mg== | 9,789 | pandas.Grouper documentation thin | {
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... | closed | false | null | [] | {
"closed_at": "2015-10-09T18:34:35Z",
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- convention is not described at all
- default values are not described for any of the additional kwargs
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https://api.github.com/repos/pandas-dev/pandas/issues/9790 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9790/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9790/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9790/events | https://github.com/pandas-dev/pandas/issues/9790 | 65,956,662 | MDU6SXNzdWU2NTk1NjY2Mg== | 9,790 | ERR: better error reporting for passing list to level grouper on non-MultiIndex | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2015-04-02T15:53:03Z | 2020-01-03T23:23:44Z | 2020-01-03T23:23:44Z | NONE | null | `groupy(level=[0])` doesn't work on a unique index. I guess it is semantics whether one allows not only level=0, but also level=[0], but if not, the error message should be different:
```
df = pd.DataFrame(np.arange(0,9).reshape(3,3))
df.groupby(level=[0])
ValueError: level > 0 only valid with MultiIndex
```
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https://api.github.com/repos/pandas-dev/pandas/issues/9791 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9791/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9791/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9791/events | https://github.com/pandas-dev/pandas/issues/9791 | 65,979,247 | MDU6SXNzdWU2NTk3OTI0Nw== | 9,791 | Issue when installing Pandas 0.16 on Windows using Conda | {
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I tried installing pandas .16 using conda in windows but am getting the following issue. I tried reinstalling using an admin console but it doesn't work. I've downgraded to 0.15.2 which works again but could use help.
This is my first time posting so if this is not the appropriate channel please let me know.
Than... | {
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"followers_url": "https://api.github.com/users/jr... | 11 | 2015-04-02T21:56:56Z | 2016-02-11T19:10:53Z | 2015-04-17T12:35:41Z | NONE | null | Try to the following code, and you will find column labels mismatched with the data in the Excel file :
`cols = pd.MultiIndex.from_tuples([('site',''),('2014','height'),('2014','weight')])`
`df = pd.DataFrame(np.random.randn(10,3), columns=cols)`
`df.to_excel('test.xlsx', index=False)`
I am using pandas v0.16.0.
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https://api.github.com/repos/pandas-dev/pandas/issues/9795 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9795/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9795/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9795/events | https://github.com/pandas-dev/pandas/issues/9795 | 66,033,108 | MDU6SXNzdWU2NjAzMzEwOA== | 9,795 | Unexpected in-place changes when saving a DataFrame to Stata with write_index=False | {
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`df = pd.DataFrame(np.random.randn(5,4), columns=list('abcd'))`
`df.ix[2, 'a':'c'] = np.nan`
`print df`
`df.to_stata('test.dta', write_index=False)`
`print df`
I a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9796 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9796/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9796/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9796/events | https://github.com/pandas-dev/pandas/pull/9796 | 66,052,982 | MDExOlB1bGxSZXF1ZXN0MzI1NjU2Mjc= | 9,796 | DOC: add doc/source/contributing.rst as the CONTRIBUTING.md | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-03T02:04:49Z | 2015-04-03T11:07:53Z | 2015-04-03T11:07:53Z | CONTRIBUTOR | null | xref #9754
I just did
`pandoc doc/source/contributing.rst -t markdown > CONTRIBUTING.md`
to generate the new CONTRIBUTING file.
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https://api.github.com/repos/pandas-dev/pandas/issues/9797 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9797/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9797/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9797/events | https://github.com/pandas-dev/pandas/pull/9797 | 66,075,668 | MDExOlB1bGxSZXF1ZXN0MzI1NzAwMTk= | 9,797 | DOC: regenerate CONTRIBUTING.md | {
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"followers_url": "https://api.github.com/users/jr... | 11 | 2015-04-03T04:54:57Z | 2015-04-03T19:58:47Z | 2015-04-03T17:18:52Z | MEMBER | null | This is an alternative to #9796.
I simply did a couple of changes to the restructuredtext source so it generates cleaner markdown. The main thing was making the categories not quite so nested. (Was that [heavy nesting](http://pandas-docs.github.io/pandas-docs-travis/contributing.html#committing-your-code) intentional?... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9798 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9798/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9798/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9798/events | https://github.com/pandas-dev/pandas/issues/9798 | 66,099,766 | MDU6SXNzdWU2NjA5OTc2Ng== | 9,798 | read_csv() interprets index_col="True" as "1" | {
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"name": "API Design",
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},
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"default": false,
"description": "I... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-03T07:38:16Z | 2015-04-11T00:52:18Z | 2015-04-09T15:03:48Z | NONE | null | epi.txt
```
OBS ID PERIOD TMT Y0 AGE COUNT
1 1 1 0 11 31 5
2 1 2 0 11 31 3
3 1 3 0 11 31 3
4 1 4 0 11 31 3
5 2 1 0 11 30 3
6 2 2 0 11 30 5
7 2 3 0 11 30 3
8 2 4 0 11 30 3
9 3 1 0 6 25 2
10 3 2 0 6 25 4
```
```
epi = pandas.read_csv("./epi.datn.txt", sep=" ", index_col=True)
print(epi)
```
```
OBS PERIOD TMT Y... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9799 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9799/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9799/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9799/events | https://github.com/pandas-dev/pandas/issues/9799 | 66,107,033 | MDU6SXNzdWU2NjEwNzAzMw== | 9,799 | .. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9800 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9800/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9800/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9800/events | https://github.com/pandas-dev/pandas/pull/9800 | 66,140,131 | MDExOlB1bGxSZXF1ZXN0MzI1ODY3MTI= | 9,800 | Closes #9795 (Stata writer changes input frame) | {
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Just needed to move the data frame copy earlier in the execution path.
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https://api.github.com/repos/pandas-dev/pandas/issues/9801 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9801/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9801/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9801/events | https://github.com/pandas-dev/pandas/pull/9801 | 66,151,222 | MDExOlB1bGxSZXF1ZXN0MzI1ODk5NDk= | 9,801 | DOC: str.split to use return_type in an example | {
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