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https://api.github.com/repos/pandas-dev/pandas/issues/2601 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2601/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2601/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2601/events | https://github.com/pandas-dev/pandas/issues/2601 | 9,545,135 | MDU6SXNzdWU5NTQ1MTM1 | 2,601 | read_table/csv unexpected type dependence on delimiter | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2012-12-27T20:13:30Z | 2012-12-28T14:35:37Z | 2012-12-28T14:35:37Z | CONTRIBUTOR | null | While answering a question on SO I came across something which puzzled me:
```
>>> import pandas as pd
>>> pd.__version__
'0.10.0b1'
>>> repr(open('cusip.txt').read())
"'65248E10 11\\n55555E55 22\\n'"
>>> !cat cusip.txt
65248E10 11
55555E55 22
>>> df = pd.read_table("cusip.txt", header=None, sep=" ")
>>> df
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https://api.github.com/repos/pandas-dev/pandas/issues/2602 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2602/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2602/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2602/events | https://github.com/pandas-dev/pandas/issues/2602 | 9,545,410 | MDU6SXNzdWU5NTQ1NDEw | 2,602 | Series StringMethods very slow | {
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"followers_url": "https://api.github.com/users/wesm/f... | 1 | 2012-12-27T20:27:24Z | 2012-12-28T14:26:57Z | 2012-12-28T14:26:20Z | NONE | null | I understand the benefit of Series.str methods which automatically handle NA, but the implementation seems really slow.
```
>>> s = pd.Series(['abcdefg', np.nan]*500000)
>>> timeit s.str[:5]
1 loops, best of 3: 2.55 s per loop
>>> timeit s.map(lambda row: row[:5], na_action='ignore')
1 loops, best of 3: 558 ms per loo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2603 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2603/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2603/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2603/events | https://github.com/pandas-dev/pandas/issues/2603 | 9,547,308 | MDU6SXNzdWU5NTQ3MzA4 | 2,603 | Concat series with axis=1 does not preserve names when reindexing is necessary | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2604 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2604/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2604/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2604/events | https://github.com/pandas-dev/pandas/issues/2604 | 9,548,742 | MDU6SXNzdWU5NTQ4NzQy | 2,604 | Indexes created from datetimes that are tz aware but tz=None (pytz.FixedOffset()) lose tz awareness | {
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"followers_url": "https://api.github.com/users/wesm/f... | 1 | 2012-12-28T00:03:16Z | 2016-10-12T23:03:27Z | 2012-12-28T18:42:39Z | NONE | null | The index created from datetimes with a FixedOffset tz get converted to the correct UTC time but lose their timezone awareness so that further operations with tz aware datetimes fail.
pytz.FixedOffset() timezones have tzname() return None
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https://api.github.com/repos/pandas-dev/pandas/issues/2605 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2605/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2605/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2605/events | https://github.com/pandas-dev/pandas/issues/2605 | 9,551,516 | MDU6SXNzdWU5NTUxNTE2 | 2,605 | AssertionError when using apply after GroupBy | {
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"followers_url": "https://api.github.com/users/wesm/f... | 3 | 2012-12-28T05:01:32Z | 2012-12-28T16:43:45Z | 2012-12-28T13:48:05Z | NONE | null | The following code raises an AssertionError with pandas 0.10.0, but works fine in 0.9.1. The error still exists in the latest dev version here. The code comes from Wes' book, pages 33-36. The data files are from https://github.com/pydata/pydata-book
``` python
import pandas as pd
years = range(1880, 2011)
pieces = [... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2607 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2607/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2607/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2607/events | https://github.com/pandas-dev/pandas/pull/2607 | 9,561,920 | MDExOlB1bGxSZXF1ZXN0MzUwMDk4OQ== | 2,607 | BUG: fixed old version compatibility warnings | {
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"followers_url": "https://api.github.com/users/wesm/f... | 5 | 2012-12-28T16:51:51Z | 2014-06-24T17:11:46Z | 2013-01-06T04:33:36Z | CONTRIBUTOR | null | - added copy method to allow file upgrades to new version
- refactor to add Storer class to represent all non-tables
- add shape field to display for non-tables
- close GH #2637
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I've put together a small example to reproduce it: https://gist.github.com/... | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2012-12-28T21:40:27Z | 2013-01-20T05:00:55Z | 2013-01-20T05:00:55Z | CONTRIBUTOR | null | Migrated from [StackOverflow](http://stackoverflow.com/questions/14075326/pandas-runtimeerror-in-tseries-convertor-when-plotting). The following gives an exception (when trying to plot a DataFrame with date indices). I'm using '0.10.0b1'.
```
In [1]: df = DataFrame(randn(3,1),index=[date(2012,10,1),date(2012,9,1),date... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2610 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2610/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2610/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2610/events | https://github.com/pandas-dev/pandas/issues/2610 | 9,573,237 | MDU6SXNzdWU5NTczMjM3 | 2,610 | describe() fails with stacktrace for an empty DataFrame | {
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"followers_url": "https://api.github.com/users/wesm/f... | 1 | 2012-12-29T13:09:34Z | 2013-01-02T17:21:00Z | 2013-01-02T17:21:00Z | CONTRIBUTOR | null | This is from a first try to select all rows where an ID is in another dataset. The code does not work as intended (see last line), but I think that the `describe()` call shouldn't fail.
[column names changed in output; output from last call shortened]
```
In [47]: all
Out[47]:
<class 'pandas.core.frame.DataFrame'>
I... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2611 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2611/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2611/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2611/events | https://github.com/pandas-dev/pandas/issues/2611 | 9,573,692 | MDU6SXNzdWU5NTczNjky | 2,611 | read_csv can show the correct string when the string is chinese text | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2012-12-29T14:18:04Z | 2012-12-30T08:55:52Z | 2012-12-30T08:55:52Z | NONE | null | the csv file structure below:
(header:) Chinese string , Chinese string, Chinese string ,Chines string
(row1 :) 新浪行业, 生物制药 , swzy, 0
while using
data=pd.read_csv(filepath,encoding='utf-8')
the read_csv can parse the file content, but when use print data, the Chines string represents like "???" ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2612 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2612/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2612/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2612/events | https://github.com/pandas-dev/pandas/issues/2612 | 9,573,987 | MDU6SXNzdWU5NTczOTg3 | 2,612 | Unicode column misalignment | {
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In [17]: open('/home/wesm/tmp/foo.csv', 'rb').read()
Out[17]: '\xe6\xb8\xac\xe8\xa9\xa6\xe4\xb8\x80,\xe6\xb8\xac\xe8\xa9\xa6\xe4\xb8\x89\r\nabc@example.com,\xe6\xb8\xac\xe8\xa9\xa6\xe4\xb8\x80\r\ndef@example.com,\xe6\xb8\xac\xe8\xa9\xa6\xe4\xba\x8c\r\nghi@example.com,\xe6\xb8\xac\xe8\xa9\xa6\xe4\xb8\x89\r\n'
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https://api.github.com/repos/pandas-dev/pandas/issues/2613 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2613/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2613/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2613/events | https://github.com/pandas-dev/pandas/issues/2613 | 9,575,388 | MDU6SXNzdWU5NTc1Mzg4 | 2,613 | ExcelFile has non existent argument "kind" in the docstring | {
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class ExcelFile(object):
"""
Class for parsing tabular excel sheets into DataFrame objects.
Uses xlrd for parsing .xls files or openpyxl for .xlsx files.
See ExcelFile.parse for more documentation
Parameters
----------
path : string or file-like object
Path to xls file
kind ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2614 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2614/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2614/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2614/events | https://github.com/pandas-dev/pandas/pull/2614 | 9,575,632 | MDExOlB1bGxSZXF1ZXN0MzUwNjY2MQ== | 2,614 | BUG: trivial fix in vb_bench/timeseries.py | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2615 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2615/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2615/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2615/events | https://github.com/pandas-dev/pandas/issues/2615 | 9,577,784 | MDU6SXNzdWU5NTc3Nzg0 | 2,615 | Enable referring to index level in functions like DataFrame.sort_index | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2012-12-29T21:42:30Z | 2015-01-26T00:39:04Z | 2015-01-26T00:39:04Z | MEMBER | null | re: http://stackoverflow.com/questions/14085517/pandas-sorting-pivot-table-or-grouping-dataframe
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https://api.github.com/repos/pandas-dev/pandas/issues/2616 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2616/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2616/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2616/events | https://github.com/pandas-dev/pandas/issues/2616 | 9,578,496 | MDU6SXNzdWU5NTc4NDk2 | 2,616 | Weird IndexError /segfault for df.groupby(level="levelname") if na in level | {
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(fully functional code depending on the requests and xlrd library and a berlin open data set)
```
import pandas as pd
import requests
the_data = requests.get('http://www.berlin.de/imperia/md/content/senatsve... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2617 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2617/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2617/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2617/events | https://github.com/pandas-dev/pandas/issues/2617 | 9,585,733 | MDU6SXNzdWU5NTg1NzMz | 2,617 | HTML reprs not properly escaped | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2012-12-30T21:04:22Z | 2016-10-12T23:03:27Z | 2013-01-20T01:46:13Z | CONTRIBUTOR | null | Object representations are not escaped for HTML when giving HTML repr to IPython Notebook,
for instance if the items themselves are types, whose reprs include `<`, and are interpreted as tags.
[an example notebook](http://nbviewer.ipython.org/4415176)
Originally from [this SO question](http://stackoverflow.com/questi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2618 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2618/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2618/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2618/events | https://github.com/pandas-dev/pandas/issues/2618 | 9,587,446 | MDU6SXNzdWU5NTg3NDQ2 | 2,618 | Possible date parsing bug in read_table | {
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"closed_at": "2013-05-10T10:57:28Z",
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"created_at": "2013-01-18T03:58:28Z",
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"followers_url": "https://api.github.com/users/wesm/... | 3 | 2012-12-31T01:02:31Z | 2013-03-28T05:54:41Z | 2013-03-28T05:54:41Z | NONE | null | I recently updated Pandas to 0.10.0 under Python 2.7.3. I have encountered problems with the read_table function. My program read in the following file:
> ftp://ftp.ncdc.noaa.gov/pub/data/anomalies/monthly.land_ocean.90S.90N.df_1901-2000mean.dat
Here's the head of the file:
<pre>
1880 1 -0.0760
1880 2 -0.2099
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https://api.github.com/repos/pandas-dev/pandas/issues/2619 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2619/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2619/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2619/events | https://github.com/pandas-dev/pandas/issues/2619 | 9,590,862 | MDU6SXNzdWU5NTkwODYy | 2,619 | dtype parameter of read_csv is not documented | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2012-12-31T10:28:29Z | 2013-01-20T18:56:44Z | 2013-01-20T18:56:34Z | CONTRIBUTOR | null | The docs at http://pandas.pydata.org/pandas-docs/stable/generated/pandas.io.parsers.read_csv.html do not explain how the dtype parameter is to be used.
Using google, it seems to be a dict with keys=columnnames, but what are the possible values in that dict?.
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https://api.github.com/repos/pandas-dev/pandas/issues/2620 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2620/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2620/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2620/events | https://github.com/pandas-dev/pandas/pull/2620 | 9,592,140 | MDExOlB1bGxSZXF1ZXN0MzUxMjA4Ng== | 2,620 | BUG: fix partial date parsing occuring on certain execution dates #2618 | {
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"f... | 5 | 2012-12-31T12:16:57Z | 2014-07-11T12:00:15Z | 2013-03-06T20:22:32Z | NONE | null | closes #2618.
when parsing partial dates, will fill in missing day as first of the month, rather then now().day
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https://api.github.com/repos/pandas-dev/pandas/issues/2621 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2621/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2621/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2621/events | https://github.com/pandas-dev/pandas/issues/2621 | 9,598,733 | MDU6SXNzdWU5NTk4NzMz | 2,621 | DatetimeIndex.drop is losing timezone information | {
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"followers_url": "https://api.github.com/users/wesm/f... | 1 | 2012-12-31T22:47:32Z | 2013-01-20T02:45:41Z | 2013-01-20T02:45:41Z | NONE | null | ``` python
def test_index_tz(self):
ind = pd.date_range("2012-12-01", periods=10, tz="utc")
ind = ind.drop(ind[-1])
self.assertIsNone(ind.tz)
```
That seems counter-intuitive.
Freq information is also dropped, but that is IMHO less important
This is on pandas 0.10
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https://api.github.com/repos/pandas-dev/pandas/issues/2622 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2622/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2622/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2622/events | https://github.com/pandas-dev/pandas/issues/2622 | 9,602,060 | MDU6SXNzdWU5NjAyMDYw | 2,622 | Pull data from the World Bank API | {
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"f... | 9 | 2013-01-01T13:08:53Z | 2014-08-09T13:55:55Z | 2013-12-18T20:05:10Z | NONE | null | There already appears to be an excellent Python interface for the World Bank API called [wbdata](https://github.com/OliverSherouse/wbdata) written by Oliver Sherouse. Currently outputs data into Pandas DataFrame, but would be nice to have country-year Panels instead.
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https://api.github.com/repos/pandas-dev/pandas/issues/2623 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2623/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2623/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2623/events | https://github.com/pandas-dev/pandas/issues/2623 | 9,603,957 | MDU6SXNzdWU5NjAzOTU3 | 2,623 | DataFrame.from_records incorrectly up-converts dtypes to object. | {
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"followers_url": "https://api.github.com/users/wesm/... | 4 | 2013-01-01T19:07:33Z | 2013-03-22T21:48:21Z | 2013-03-22T21:48:21Z | CONTRIBUTOR | null | ``` python
rows = []
rows.append([pd.datetime(2010, 1, 1), 1])
rows.append([pd.datetime(2010, 1, 2), 'hi']) # test col upconverts to obj
df2_obj = pd.DataFrame.from_records(rows, columns=['date', 'test'])
print df2_obj.date.dtype # object
```
If the `'hi'` is changed to an `int` then `df2_obj.date.dtype` is equal to... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2624 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2624/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2624/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2624/events | https://github.com/pandas-dev/pandas/issues/2624 | 9,604,028 | MDU6SXNzdWU5NjA0MDI4 | 2,624 | pd.concat merges object-datetime and np.datetime columns incorrectly. | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2013-01-01T19:18:45Z | 2013-12-04T00:40:13Z | 2013-01-20T19:51:00Z | CONTRIBUTOR | null | ``` python
rows = []
rows.append([pd.datetime(2010, 1, 1), 1])
rows.append([pd.datetime(2010, 1, 2), 'hi']) # test col upconverts to obj
df2_obj = pd.DataFrame.from_records(rows, columns=['date', 'test'])
ind = pd.date_range(start="2000/1/1", freq="D", periods=10)
df1 = pd.DataFrame({'date': ind, 'test':range(10)})
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https://api.github.com/repos/pandas-dev/pandas/issues/2625 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2625/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2625/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2625/events | https://github.com/pandas-dev/pandas/issues/2625 | 9,620,125 | MDU6SXNzdWU5NjIwMTI1 | 2,625 | quantile throws error if not convertible to float | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2013-01-02T16:38:13Z | 2013-01-05T14:18:01Z | 2013-01-05T14:18:01Z | CONTRIBUTOR | null | If we try and `quantile` a DataFrame with string entries which are not convertible, there is a ValueError. Should this behave like mean (and ignore these entries)? (taken from [this StackOverflow question](http://stackoverflow.com/questions/14125428/how-to-apply-quantile-to-pandas-groupby-object)).
```
In [1]: df = Da... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2626 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2626/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2626/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2626/events | https://github.com/pandas-dev/pandas/issues/2626 | 9,624,465 | MDU6SXNzdWU5NjI0NDY1 | 2,626 | Series.combine_first() misbehaves with Timestamp data | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2013-01-02T19:18:52Z | 2013-01-20T04:33:14Z | 2013-01-20T04:33:14Z | NONE | null | Best illustrated by example:
In [957]: s0 = pd.Series(["2010", np.NaN])
In [958]: s1 = pd.Series([np.NaN, "2011"])
In [959]: s0.combine_first(s1)
Out[959]:
0 2010
1 2011
In [960]: s0 = pd.to_datetime(pd.Series(["2010", np.NaN]))
In [961]: s1 = pd.to_datetime(pd.Series([np.NaN, "2011"]))
In [962]: s0.combin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2627 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2627/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2627/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2627/events | https://github.com/pandas-dev/pandas/issues/2627 | 9,626,958 | MDU6SXNzdWU5NjI2OTU4 | 2,627 | apply on np.datetime col doesn't upconvert to Timestamp | {
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import pandas as pd
s = pd.Series(pd.date_range(start="2000/1/1", freq="D", periods=10))
s.apply(lambda x: x.date())
# AttributeError: 'numpy.datetime64' object has no attribute 'date'
```
This is an error from some unit tests. Did something major change with how datetimes are handled? I recall that np.da... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2628 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2628/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2628/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2628/events | https://github.com/pandas-dev/pandas/issues/2628 | 9,631,523 | MDU6SXNzdWU5NjMxNTIz | 2,628 | DataFrame.groupby().groups should truncate output | {
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"f... | 3 | 2013-01-02T23:40:49Z | 2018-12-19T12:02:48Z | 2018-12-19T12:02:47Z | NONE | null | The output from .groups on a grouped DataFrame should be handled similarly to a large DataFrame, where beyond a certain length, the data is displayed in a summary form rather than output in its entirety.
This truncation should occur both at the group level (large number of groups) and per-group (large amount of data p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2629 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2629/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2629/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2629/events | https://github.com/pandas-dev/pandas/issues/2629 | 9,636,144 | MDU6SXNzdWU5NjM2MTQ0 | 2,629 | Subtracting Series of Timestamps gives wrong result | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2013-01-03T05:30:30Z | 2016-10-12T23:03:27Z | 2013-01-20T02:33:16Z | NONE | null | Example:
In [11]: d0 = pd.to_datetime(pd.Series(["12/1/2011"]))
In [12]: d1 = pd.to_datetime(pd.Series(["12/3/2011"]))
In [13]: d1[0] - d0[0]
Out[13]: datetime.timedelta(2)
In [14]: (d1 - d0)[0]
Out[14]: 2000 days, 0:00:00
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https://api.github.com/repos/pandas-dev/pandas/issues/2630 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2630/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2630/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2630/events | https://github.com/pandas-dev/pandas/pull/2630 | 9,655,000 | MDExOlB1bGxSZXF1ZXN0MzUzOTExOA== | 2,630 | BUG: Series op with datetime64 values misbehaves in numpy 1.6 #2629 | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2013-01-03T20:24:17Z | 2014-06-25T19:18:04Z | 2013-01-20T02:33:06Z | CONTRIBUTOR | null | converts to i8 then back to timedelta64[ns] if both datetime64
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https://api.github.com/repos/pandas-dev/pandas/issues/2631 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2631/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2631/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2631/events | https://github.com/pandas-dev/pandas/issues/2631 | 9,658,323 | MDU6SXNzdWU5NjU4MzIz | 2,631 | read_csv, integer dtype and empty cells | {
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"followers_url": "https://api.github.com/users/wesm/f... | 4 | 2013-01-03T22:26:01Z | 2019-10-05T18:49:17Z | 2013-01-20T00:10:56Z | CONTRIBUTOR | null | Reading in a csv file with an integer column which has empty cells will cast that column to float (which in the end will resulted in problems with merging this dataframe on that column with a dataframe where the corresponding column is int).
It would be nice if a warning could be printed when such conversation (maybe ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2632 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2632/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2632/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2632/events | https://github.com/pandas-dev/pandas/pull/2632 | 9,658,689 | MDExOlB1bGxSZXF1ZXN0MzU0MTE2Mw== | 2,632 | Autopep8 | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2013-01-03T22:39:00Z | 2014-06-12T14:19:52Z | 2013-01-05T20:31:20Z | CONTRIBUTOR | null | Used [autopep8](https://github.com/hhatto/autopep8) to make all of pandas py files more PEP8 compliant (Excluding 230 `E501 lines too long` (over 80 chars), and 6 changes which had to be reverted to fix test failures - in second commit). See statistics in my comment.
I iterated over every py file in the package using ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2633 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2633/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2633/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2633/events | https://github.com/pandas-dev/pandas/issues/2633 | 9,662,040 | MDU6SXNzdWU5NjYyMDQw | 2,633 | DataFrame.from_records() KeyError when passed empty list | {
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"followers_url": "https://api.github.com/users/wesm/f... | 4 | 2013-01-04T01:28:46Z | 2019-12-19T14:29:50Z | 2013-01-19T23:55:20Z | NONE | null | What it says on the tin. from_records() fails with a KeyError if passed an empty list. If the list is empty, an empty DataFrame should be created, conforming to the other arguments (columns, etc).
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https://api.github.com/repos/pandas-dev/pandas/issues/2634 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2634/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2634/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2634/events | https://github.com/pandas-dev/pandas/issues/2634 | 9,663,263 | MDU6SXNzdWU5NjYzMjYz | 2,634 | Sums not treating NaN as zero. | {
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```
In [136]: dfa
Out[136]:
clicks
ad
327 3
In [137]: dfc
Out[137]:
clicks
ad
326 1
In [138]: dfa + dfc
Out[138]:
clicks
ad
326 NaN
327 NaN
#Expected
In [138]: dfa + dfc
Out[138]:
clicks
ad
326 1
327 3
```
Per d... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2635 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2635/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2635/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2635/events | https://github.com/pandas-dev/pandas/pull/2635 | 9,663,547 | MDExOlB1bGxSZXF1ZXN0MzU0MzYwOQ== | 2,635 | Try to fix BUG #2599 | {
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"followers_url": "https://api.github.com/users/wesm/f... | 3 | 2013-01-04T03:26:59Z | 2014-06-27T22:59:58Z | 2013-01-05T21:21:44Z | CONTRIBUTOR | null | Not sure if this is a good way to go about it, but it seems to work.
Might be good to get rid of all the INT64_MAX/MIN stuff in parser.pyx and replace with np.iinfo(np.int64).max/min instead.
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Reading compressed csv files in _R_ is done without any additional input by the user, and is also already supporte... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2637 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2637/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2637/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2637/events | https://github.com/pandas-dev/pandas/issues/2637 | 9,691,665 | MDU6SXNzdWU5NjkxNjY1 | 2,637 | HDFStore.select with Timestamp data_column doesn't behave as expected. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2639 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2639/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2639/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2639/events | https://github.com/pandas-dev/pandas/issues/2639 | 9,699,608 | MDU6SXNzdWU5Njk5NjA4 | 2,639 | BLD: add 0.9.0,0.9.1 docs to website; change 0.11.0 to 0.10.1, update dev builds for 0.10.1 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2640 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2640/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2640/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2640/events | https://github.com/pandas-dev/pandas/issues/2640 | 9,701,887 | MDU6SXNzdWU5NzAxODg3 | 2,640 | DataFrame.resample() fails on empty DataFrame | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2641 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2641/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2641/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2641/events | https://github.com/pandas-dev/pandas/issues/2641 | 9,707,085 | MDU6SXNzdWU5NzA3MDg1 | 2,641 | df.decribe() with boolean column | {
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"f... | 1 | 2013-01-05T16:21:28Z | 2013-04-02T12:46:28Z | 2013-04-02T12:46:28Z | CONTRIBUTOR | null | it would be nice if one could use `df.describe()` with a boolean column (resulting in output like casting the column to int).
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I'm using pandas to analyze data for my PhD thesis and I was dreading to use a database and having to learn SQL but up to now pandas handled everything I've thrown at it with ease (1.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2643 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2643/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2643/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2643/events | https://github.com/pandas-dev/pandas/issues/2643 | 9,707,470 | MDU6SXNzdWU5NzA3NDcw | 2,643 | Improve pivot_table for more complex aggregation function specs | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2644 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2644/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2644/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2644/events | https://github.com/pandas-dev/pandas/issues/2644 | 9,709,652 | MDU6SXNzdWU5NzA5NjUy | 2,644 | No API reference for DataFrameGroupBy and "combining" step | {
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"f... | 36 | 2013-01-05T20:56:27Z | 2014-04-25T12:13:04Z | 2014-04-23T21:29:28Z | CONTRIBUTOR | null | At least by searching google, I found no references for the DataFrameGroupBy. The docs at http://pandas.pydata.org/pandas-docs/dev/groupby.html speak about a "GroupBy object"...
What are all the functions of that object? Using IPython, I get inline help, but this informations seems to be missing in the online docs.
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C:\code\pandas>c:\python27\scripts\nosetests.exe pandas\io\tests\test_pytables.py
.S......SSS...........F.F...S..S...E....F..E..E.....E........E........E....
======================================================================
ERROR: test_put (pandas.io.tests.test_pytables.TestHDFStore)
--------------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2646 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2646/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2646/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2646/events | https://github.com/pandas-dev/pandas/issues/2646 | 9,712,660 | MDU6SXNzdWU5NzEyNjYw | 2,646 | multi-index indexing for 3-level index behaving mysteriously. | {
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I wrote a pretty detailed investigation here:
http://nbviewer.ipython.org/4465051/
with the gist
https://gist.github.com/4465051
In short words:
2-level indexing for a 3-level multi-index fails for me, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2647 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2647/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2647/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2647/events | https://github.com/pandas-dev/pandas/issues/2647 | 9,714,023 | MDU6SXNzdWU5NzE0MDIz | 2,647 | reset_index does not allow to specify level | {
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newseries has the time-index only:
```
newseries.head()
time
2009-07-20 00:00:00.045000 312.591132
2009-07-20 00:00:00.173000 312.589225
2009-07-20 00:00:00.301000 312.587320
2009-07-20 00:00:00.429000 312.585419
2009-07-20 00:00:00.5... | {
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"followers_url": "https://api.github.com/users/wesm/f... | 1 | 2013-01-06T21:34:29Z | 2013-01-20T20:15:38Z | 2013-01-20T20:15:38Z | CONTRIBUTOR | null | I've seen this error lot's of times in the last few days and usually it usuall took me a long time to get it working (and mostly I had no idea why it worked when I did something differently :-( ). The below error is actually from https://github.com/statsmodels/statsmodels/pull/582/files
Would it be possibleto let the ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2650 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2650/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2650/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2650/events | https://github.com/pandas-dev/pandas/issues/2650 | 9,721,001 | MDU6SXNzdWU5NzIxMDAx | 2,650 | DOC: can't find data file in compatibility section of HDF5 docs | {
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"f... | 3 | 2013-01-06T22:16:02Z | 2013-01-18T19:53:50Z | 2013-01-18T19:53:50Z | CONTRIBUTOR | null | see this section
http://pandas.pydata.org/pandas-docs/dev/io.html#compatibility
this file legacy_0.10.h5 is in
pandas/doc/sources/_static
on website it's not finding it (find ok when I build docs locally)
any thoughts?
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https://api.github.com/repos/pandas-dev/pandas/issues/2651 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2651/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2651/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2651/events | https://github.com/pandas-dev/pandas/issues/2651 | 9,724,341 | MDU6SXNzdWU5NzI0MzQx | 2,651 | Regression: pandas 0.10 fails to read an excel file that pandas 0.9 can read | {
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```
fname = sys.argv[1]
xlsx = pd.ExcelFile(fname)
sheet = xlsx.sheet_names[0] ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2652 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2652/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2652/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2652/events | https://github.com/pandas-dev/pandas/pull/2652 | 9,733,314 | MDExOlB1bGxSZXF1ZXN0MzU2ODUzOA== | 2,652 | Writing doc about I/O SQL features. See #2541 | {
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I wrote some contents about I/O SQL pandas features:
- some examples about the `read_frame` function with SQLite ;
- list other functions such as `tquery` (without example) ;
- write a tiny note about `write_frame` function.
I'm not sure about the title of this section. Any proposal is welcome ! Don't hesi... | {
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Just add docstring to a function in the `io.sql` module.
##
Damien G.
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https://api.github.com/repos/pandas-dev/pandas/issues/2654 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2654/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2654/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2654/events | https://github.com/pandas-dev/pandas/issues/2654 | 9,741,515 | MDU6SXNzdWU5NzQxNTE1 | 2,654 | read_csv in combination with index_col and usecols | {
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http://pandas.pydata.org/pandas-docs/stable/io.html#index-columns-and-trailing-delimiters
If there is one more column of data than there are colum names, usecols exhibits some (at least for me) unintuitive behavior:
``` python
>>> data = 'a,b,c\n4,apple,bat,5.7\n8,orange,cow,10'
>>> pd.read_csv(Strin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2655 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2655/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2655/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2655/events | https://github.com/pandas-dev/pandas/issues/2655 | 9,760,645 | MDU6SXNzdWU5NzYwNjQ1 | 2,655 | index.levels not being updated by groupby | {
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"description": "Related to inde... | closed | false | null | [] | null | 6 | 2013-01-08T08:15:50Z | 2013-12-01T10:54:18Z | 2013-11-30T12:08:45Z | CONTRIBUTOR | null | Summary:
Input:
``` python
df.D.ix['c1','d1']
t1 0
t2 0
t3 1
t4 1
t5 1
Name: D
```
Operation:
``` python
grouped = df.groupby('D')
for i,j in grouped:
print 'D:',i
print 'Actual index[2]:',j.index[0][2]
print 'First element of levels[2]:',j.index.levels[2][0]
```
Output:
``` python
D: 0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2656 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2656/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2656/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2656/events | https://github.com/pandas-dev/pandas/issues/2656 | 9,771,922 | MDU6SXNzdWU5NzcxOTIy | 2,656 | The apply method over a group seems to visit the first group twice | {
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"closed_at": "2019-07-19T00:34:29Z",
"closed_issues": 1289,
"created_at": "2018-10-23T02:34:15Z",
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"followers_url": "https://api.github.com/users/j... | 8 | 2013-01-08T15:39:44Z | 2019-01-26T15:19:17Z | 2013-09-21T12:38:36Z | NONE | null | It seems that the apply method of a group invokes the function passed as parameter once for each group, as expectes. However, the function is invoked twice for the first group. Enclose is a short code reproducing this behavior. Is it a normal behavior or am I doing something wrong here.
I run the code with pandas 0.10... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2657 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2657/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2657/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2657/events | https://github.com/pandas-dev/pandas/issues/2657 | 9,773,049 | MDU6SXNzdWU5NzczMDQ5 | 2,657 | Clip Could take Series/DataFrames | {
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"f... | 4 | 2013-01-08T16:10:59Z | 2018-10-20T13:53:15Z | 2018-10-19T22:01:32Z | NONE | null | I was a little surprised when clip would not take other pandas objects as parameters. I hacked a little something below, but for readability I thought I might suggest that this feature be added.
```
df1 = DataFrame(ones((2, 2)))
data = ones((2, 2))
data[0, 0] = 0
data[1, 1] = 2
df2 = DataFrame(data)
print df2.clip(1... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2658 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2658/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2658/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2658/events | https://github.com/pandas-dev/pandas/issues/2658 | 9,782,584 | MDU6SXNzdWU5NzgyNTg0 | 2,658 | DateTime indexing: DateParseError: global name 'tz' is not defined | {
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"followers_url": "https://api.github.com/users/wesm/f... | 4 | 2013-01-08T20:54:08Z | 2013-01-10T23:37:49Z | 2013-01-10T23:37:49Z | NONE | null | I have a DataFrame with a DateTime index that I have read from a CSV file:
```
In [131]: d=pd.read_csv('data.csv', parse_dates=[0], index_col=0)
```
The index values consist of ISO-8601-formatted timestamps of the form "2012-12-28T09:00:54.273000-0500", which Pandas seems to handle perfectly:
```
In [132]: d.index
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2659 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2659/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2659/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2659/events | https://github.com/pandas-dev/pandas/issues/2659 | 9,783,930 | MDU6SXNzdWU5NzgzOTMw | 2,659 | Cyclic GC issues | {
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"followers_url": "https://api.github.com/users/wesm/... | 15 | 2013-01-08T21:33:27Z | 2021-10-07T08:55:09Z | 2013-03-28T05:09:16Z | MEMBER | null | A mystery to be debugged soon:
``` python
import pandas as pd
import numpy as np
arr = np.random.randn(100000, 5)
def leak():
for i in xrange(10000):
df = pd.DataFrame(arr.copy())
result = df.xs(1000)
# result = df.ix[5000]
if __name__ == '__main__':
leak()
```
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https://api.github.com/repos/pandas-dev/pandas/issues/2660 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2660/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2660/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2660/events | https://github.com/pandas-dev/pandas/issues/2660 | 9,784,208 | MDU6SXNzdWU5Nzg0MjA4 | 2,660 | dataframe merge does not work correctly when dataframe sizes are bigger | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2661 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2661/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2661/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2661/events | https://github.com/pandas-dev/pandas/pull/2661 | 9,785,508 | MDExOlB1bGxSZXF1ZXN0MzU5MzcyMw== | 2,661 | missing imports in tseries/tools/dateutil_parse #2658 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2663 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2663/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2663/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2663/events | https://github.com/pandas-dev/pandas/issues/2663 | 9,788,870 | MDU6SXNzdWU5Nzg4ODcw | 2,663 | ExcelWriter not in docs | {
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"followers_url": "https://api.github.com/users/wesm/... | 3 | 2013-01-09T00:18:10Z | 2013-03-17T01:41:53Z | 2013-03-17T01:41:53Z | CONTRIBUTOR | null | [Searching for "ExcelWriter"](http://pandas.pydata.org/pandas-docs/stable/search.html?q=excelwriter&check_keywords=yes&area=default) on the documentation doesn't find anything about [`pandas.io.parser.ExcelWriter`](https://github.com/pydata/pandas/blob/master/pandas/io/parsers.py#L2101).
Is this intentional or is it n... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2664 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2664/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2664/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2664/events | https://github.com/pandas-dev/pandas/issues/2664 | 9,798,124 | MDU6SXNzdWU5Nzk4MTI0 | 2,664 | MultiIndex generates IndexErrors for valid indices in large DataFrames | {
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``` python
In [134]: len(data)
Out[134]: 59693
In [135]: data.index.names
Out[135]: ['chr', 'name', 'start', 'end']
In [136]: data.head()
Out[136]:
coverage covered total percentage
chr name start end ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2665 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2665/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2665/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2665/events | https://github.com/pandas-dev/pandas/issues/2665 | 9,799,777 | MDU6SXNzdWU5Nzk5Nzc3 | 2,665 | Incorrect resampling from hourly to monthly values | {
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... | 9 | 2013-01-09T10:37:45Z | 2020-03-31T03:23:39Z | null | NONE | null | EDIT: Modern reproducible example:
```
In [1]: import pandas as pd
In [2]: dates = pd.date_range('3/20/2000', '5/20/2000', freq='1h')
In [4]: ts = pd.Series(range(len(dates)), index=dates)
In [5]: def start(x):
...: return x.index[0]
...:
...: def end(x):
...: return x.index[-1]
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https://api.github.com/repos/pandas-dev/pandas/issues/2666 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2666/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2666/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2666/events | https://github.com/pandas-dev/pandas/issues/2666 | 9,804,127 | MDU6SXNzdWU5ODA0MTI3 | 2,666 | FAIL: test_to_string_repr_unicode | {
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windows 7 32bit english
python 2.7.3
when I run nose test:
```
nosetests pandas
```
issue:
FAIL: test_to_string_repr_unicode (pandas.tests.test_format.TestDataFrameFormatting)
Traceback (most recent call last):
File "D:\Python27\lib\site-packages\pandas\tests\test_format.py", line 141, in
test_to_string_r... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2667 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2667/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2667/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2667/events | https://github.com/pandas-dev/pandas/issues/2667 | 9,805,695 | MDU6SXNzdWU5ODA1Njk1 | 2,667 | multi-character line_terminator in to_csv can improperly convert scientific notation numbers to strings | {
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... | 6 | 2013-01-09T14:13:55Z | 2016-08-01T10:45:57Z | 2016-08-01T10:18:33Z | CONTRIBUTOR | null | Test case:
``` python
In [12]: test = pandas.DataFrame({"A": [1,2,3], "B": [1e-10,4.3434323e-8,3]})
In [13]: test.to_csv("test.txt", sep="\t", line_terminator="\n---\n")
In [14]: cat test.txt
A B
---
0 1 "1e-10"
---
1 2 "4.3434322999999997e-08"
---
2 3 3.0
---
`... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2668 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2668/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2668/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2668/events | https://github.com/pandas-dev/pandas/issues/2668 | 9,808,163 | MDU6SXNzdWU5ODA4MTYz | 2,668 | Odd behaviour in read_csv | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2013-01-09T15:25:55Z | 2013-01-20T01:29:48Z | 2013-01-20T01:29:42Z | CONTRIBUTOR | null | This is a strange example from [this StackOverflow question](http://stackoverflow.com/questions/14237749/pandas-read-csv-strange-behavior-for-empty-default-values):
```
Date,Currenncy,Symbol,Type,Units,UnitPrice,Cost,Tax
2012-03-14,USD,AAPL,BUY,1000
2012-05-12,USD,SBUX,SELL,500
```
```
In [1]: pd.read_csv('ttt.csv', ... | {
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"labels_url": "htt... | 11 | 2013-01-09T16:44:02Z | 2014-05-15T15:55:43Z | 2014-01-29T13:22:01Z | NONE | null | Please could you add this functionality on top of the already existing kde functionality.
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https://api.github.com/repos/pandas-dev/pandas/issues/2670 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2670/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2670/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2670/events | https://github.com/pandas-dev/pandas/pull/2670 | 9,822,144 | MDExOlB1bGxSZXF1ZXN0MzYxMDk2Mg== | 2,670 | add support for microsecond periods (GH2145) | {
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Alrighty. This should be fine. There may be a few formatting changes that I rolled back through the git diff / apply patch, but all not-skipped tests pass so I figured it wasn't a big deal. Here's what I did to fix the problem, which was continually merging with upstream:
``` shell
function get_my_c... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2671 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2671/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2671/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2671/events | https://github.com/pandas-dev/pandas/issues/2671 | 9,823,618 | MDU6SXNzdWU5ODIzNjE4 | 2,671 | nosetests: ERROR: test using ndim tables in new ways | {
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> #
> ## ERROR: test using ndim tables in new ways
>
> Traceback (most recent call last):
> File "C:\Python27\lib\site-packages\pandas\io\tests\test_pytables.py", line 34
> 6, in test_ndim_indexables
> tm.assert_panel4d_equal(self.store['p4d'], p4d)
> File "C:\Python2... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2672 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2672/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2672/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2672/events | https://github.com/pandas-dev/pandas/issues/2672 | 9,825,834 | MDU6SXNzdWU5ODI1ODM0 | 2,672 | version 0.10.0: read_table() mangles the first two lines of data if they contain fewer columns than the header | {
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Create a file text.txt with tabs as delimiters:
key1 key2 x1 x2 x3
1 a 0 100
2 b 100 0
3 c 25 75
4 d 35 65
5 e 15 85
Notice that all data lines have 4 columns while the header has 5 columns.
Load this file into a ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2673 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2673/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2673/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2673/events | https://github.com/pandas-dev/pandas/pull/2673 | 9,832,034 | MDExOlB1bGxSZXF1ZXN0MzYxNTg4MQ== | 2,673 | DOC: Fix grammar typo in dsintro, "a series is alike" -> "a series is like" | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2675 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2675/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2675/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2675/events | https://github.com/pandas-dev/pandas/pull/2675 | 9,841,092 | MDExOlB1bGxSZXF1ZXN0MzYxOTc3OQ== | 2,675 | BUG: HDFStore fixes | {
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- data_orientation was potentitally returning non-ints in a tuple (fixed downstream), fixes GH #2671, though fixed downstream anyhow
- fix for contains with a non-natural name (GH #2694 )
- added ability to read generic PyTables flavor tables
-... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2676 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2676/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2676/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2676/events | https://github.com/pandas-dev/pandas/issues/2676 | 9,845,443 | MDU6SXNzdWU5ODQ1NDQz | 2,676 | Community: Dev Builds For 2.7 | {
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It would be really appreciated if someone could upload a build, for 0.10.1.dev.
Or is there a reason why this is not supported?
Thanks,
Chris.
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https://api.github.com/repos/pandas-dev/pandas/issues/2677 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2677/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2677/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2677/events | https://github.com/pandas-dev/pandas/pull/2677 | 9,845,521 | MDExOlB1bGxSZXF1ZXN0MzYyMTY0OA== | 2,677 | TST: fix test to rely on display.encoding rather then utf8, GH2666 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2678 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2678/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2678/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2678/events | https://github.com/pandas-dev/pandas/issues/2678 | 9,845,646 | MDU6SXNzdWU5ODQ1NjQ2 | 2,678 | BLD: need to add travis bld under different encoding | {
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most devs have utf-8 boxes, so it's not tested.
example: #2666
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```
dt = datetime(2012, 1, 1)
for i in range(1,10):
print i, (dt - i * BDay()).strftime('%m/%d/%Y')
```
1 12/30/2011
2 12/29/2011
3 12/28/2011
4 12/27/2011
5 12/26/2011
6 12/22/2011
7 12/21/2011
8 12/20/2011
9 12/19/2011
however when the start date is onoffset it ... | {
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"f... | 2 | 2013-01-10T19:31:05Z | 2014-05-28T22:52:09Z | 2014-05-28T22:52:09Z | MEMBER | null | Currently TimeSeries.asof will do this for an array of datetimes-- it shouldn't be too difficult to sugar this to generate the appropriate dates from a `datetime.time` object.
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https://api.github.com/repos/pandas-dev/pandas/issues/2683 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2683/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2683/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2683/events | https://github.com/pandas-dev/pandas/issues/2683 | 9,864,605 | MDU6SXNzdWU5ODY0NjA1 | 2,683 | plot dies with tzoffset exception | {
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I find I need to call tz_convert() on my DataFrame before I can plot it. By default the index tz is a "tzoffset" I get an exception when plottng.
``` python
AttributeError: 'module' object has no attribute 'tz'
d=pd.read_csv('vix.dlmp.csv', parse_dates=[0], index_co... | {
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Unfortunately I can't provide the data set.
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"followers_url": "https://api.github.com/users/wesm/f... | 1 | 2013-01-11T16:44:55Z | 2014-06-19T13:19:40Z | 2013-01-20T03:28:34Z | CONTRIBUTOR | null | - fixed assignment with a boolean indexer and a non-scalar as the value (see below)
- 2nd commit fixed the alignment issue; that is if the value is not a full series, align first (using where machinery)
- add neg and inv methods
- _check_bool_indexer now coerces to bool if needed (otherwise weird effects when doing neg... | {
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This may or may not be a bug. I'm unsure of which functionality you were intending.
I have a timestamp created by
```
rng = pd.date_range(start_date, periods = 100, freq='2H')
A = DataFrame(rng) # We'll leave it as a generic index for now, not important.
```
I then have a function which is applied to that dataf... | {
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"followers_url": "https://api.github.com/users/wesm/f... | 1 | 2013-01-14T09:32:28Z | 2013-01-20T00:12:22Z | 2013-01-19T23:39:12Z | CONTRIBUTOR | null | Hi Wes, Not sure if this is real, but opening to follow up on a comment in http://stackoverflow.com/questions/14199168/combinatorial-explosion-when-merging-dataframes-in-pandas. Here's a fabricated example to reproduce `MergeError: Combinatorial explosion! (boom)` in tools/merge.py:
```
df1 = pd.DataFrame(np.random.r... | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2013-01-14T14:24:18Z | 2018-07-06T21:53:24Z | 2018-07-06T21:53:17Z | CONTRIBUTOR | null | For indexing a sub-series of some TimeSeries, one can use indices that don't completely specify the moment. For example, in a Series
```
s = Series(randn(1000), index=pd.date_range(start='2001-01-23 00:00', periods=1000, freq='H'))
```
I can say s['2001-01-23'] to get a Series for all the values for that day. This, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2692 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2692/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2692/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2692/events | https://github.com/pandas-dev/pandas/issues/2692 | 9,952,924 | MDU6SXNzdWU5OTUyOTI0 | 2,692 | groupby().sum() very slow when applied to boolean columns | {
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"followers_url": "https://api.github.com/users/wesm/f... | 1 | 2013-01-14T18:52:07Z | 2013-12-04T00:40:09Z | 2013-01-19T23:23:56Z | NONE | null | While upgrading pandas from 0.7.2 to 0.9.1 we have bumped into slowness of certain groupby().sum() operations. Here is a simple example:
N=10000
aa=DataFrame({'ii':range(N),'bb':[True for x in range(N)]})
timeit aa.sum() # fast
timeit aa.groupby('bb').sum() #fast
timeit aa.groupby('ii').sum() # very slow (~ 1000 tim... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2693 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2693/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2693/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2693/events | https://github.com/pandas-dev/pandas/issues/2693 | 9,954,494 | MDU6SXNzdWU5OTU0NDk0 | 2,693 | bug in row slicing in df.ix | {
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when slicing rows using df.ix[], it returns more rows than it should
In [2]: df=DataFrame({'a':range(5),'b':range(5)})
In [3]: df.ix[1:3,:] # should return rows 1,2
Out[3]:
a b
1 1 1
2 2 2
3 3 3 # this last row should not here
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"f... | 2 | 2013-01-14T23:27:22Z | 2014-05-28T23:18:29Z | 2014-05-28T23:18:29Z | NONE | null | Problem:
A data set is distributed over multiple csv files generated by different instances. Some of these instances log the 'header' line multiple times (when restarted). Currently I'm cleaning out these spurious header lines and doing pd.concat.
But this results in the dtype of columns being object as columns from f... | {
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If any of the entries in a column are in scientific format, all of the entries are converted to that and loose precision. Only happens if a number in the column is 12 digits or more (either representation... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2699 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2699/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2699/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2699/events | https://github.com/pandas-dev/pandas/issues/2699 | 9,982,280 | MDU6SXNzdWU5OTgyMjgw | 2,699 | pandas.to_datetime called on existing datetime64 Series results in bad data | {
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In [7]: df.date
Out[7]:
0 2007-10-29 00:00:00
1 2007-10-30 00:00:00
2 2007-10-31 00:00:00
3 2007-11-01 00:00:00
4 2007-11-02 00:00:00
5 2007-11-05 00:00:00
6 2007-11-06 00:00:00
7 2007-11-07 00:00:00
8 2007-11-08 00:00:00
9 2007-11-09 00:00:00
10 2007-11-12 00:00:00
11 2007-11-13... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/2700 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/2700/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/2700/comments | https://api.github.com/repos/pandas-dev/pandas/issues/2700/events | https://github.com/pandas-dev/pandas/issues/2700 | 9,986,960 | MDU6SXNzdWU5OTg2OTYw | 2,700 | groupby().max() operation removes string columns | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2013-01-15T17:24:16Z | 2013-01-20T01:41:36Z | 2013-01-20T01:41:22Z | NONE | null | While upgrading pandas from 0.7.2 to 0.9.1 we have found that groupby().max() operation now removes non-numeric columns. This broke our code in several places. Workaround is to use groupby().aggregate(np.max).
Here is an example demonstrating the problem:
aa=DataFrame({'nn':[11,11,22,22],'ii':[1,2,3,4],'ss':4*['mama... | {
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