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https://api.github.com/repos/pandas-dev/pandas/issues/3401
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3,401
FMT: allow datetime/timedelta formatting on a column to be better
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28
2013-04-19T12:31:45Z
2014-01-15T02:57:34Z
2014-01-15T02:57:34Z
CONTRIBUTOR
null
http://stackoverflow.com/questions/16103238/pandas-timedelta-in-days/16104567#16104567 Its easy to think about, e.g. if no dates in a particular column have time values, then can print them w/o the time values (e.g. just 2001-01-01 maybe), I think this would be nice as the default (maybe add an option for it?) ``` In...
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13,407,575
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3,402
ENH: Linked Datasets (RDF)
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2013-04-19T16:01:53Z
2016-06-20T10:54:47Z
2014-02-04T21:44:22Z
CONTRIBUTOR
null
## ENH: Linked Datasets (RDF) - This is very much a meta ticket. - There are a number of bare links here. - They are for documentation (UPDATE: see https://github.com/westurner/pandas-rdf/issues/1) ### Use Case So I: - retrieved some data - from somewhere - about a certain #topic - perfomed analysis - with cert...
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3,403
python parser does not handle encoding parameter correctly
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2013-04-19T19:45:04Z
2013-09-22T00:34:41Z
2013-09-22T00:34:41Z
CONTRIBUTOR
null
read_table with encoding="ISO-8859-2" and sep="::" does not convert movies.dat movielens dataset to unicode correctly.
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3,404
Multicharacter delimiters + non-UTF8 encoding doesn't work correctly in parsers
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2013-04-19T20:33:54Z
2016-07-28T23:43:39Z
2016-07-28T23:43:39Z
MEMBER
null
The new C parser handles user-specified encoding properly. The Python parser not so much (I think it may only be an issue when regular-expression parsing is used).
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3,405
TST: added testing and error messages for passing datetimes with timezones
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2013-04-20T16:26:09Z
2014-06-25T07:53:00Z
2013-04-20T16:51:42Z
CONTRIBUTOR
null
(not yet implemented, and error message was a little misleading) CLN: better error messages on invalid appends
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13,437,825
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3,406
TextFileReader.get_chunk returns full file DataFram despite of chunksize specified in read_csv
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2013-04-20T16:26:42Z
2013-06-20T11:03:20Z
2013-04-22T23:52:41Z
NONE
null
TextFileReader.get_chunk returns full file DataFram despite of chunksize specified in read_csv.
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13,440,125
MDU6SXNzdWUxMzQ0MDEyNQ==
3,407
Infinite loop in Python when doing simple operations
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2013-04-20T19:45:26Z
2016-09-29T22:44:20Z
2016-09-29T22:29:46Z
NONE
null
Hi there, I have a ginormous problem right now. When doing simple operations, a python interpreter subprocess keeps running in the background (even when my application finished) and eats a lot of CPU (25%) continually, and forever. It seems that whenever I do some simple operations, such as: ``` df / serie2 df.div(...
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3,408
CLN: move excel from io.parsers to io.excel
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2013-04-20T20:10:30Z
2013-07-26T12:40:28Z
2013-07-26T12:40:28Z
CONTRIBUTOR
null
for consistency should create read_excel io.api method
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3,409
BUG: don't rely on sys.getdefaultencoding if we don't need to
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2013-04-21T07:22:08Z
2014-07-23T06:58:59Z
2013-04-21T15:13:08Z
NONE
null
pending confirm on fixing #3360.
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3,410
Period.strftime should return unicode strings always
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NONE
null
pending confirmed of fix to #3363
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MDU6SXNzdWUxMzQ1MDAzNQ==
3,411
CLN: create io.api for io relegated read_xxx
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1
2013-04-21T14:38:28Z
2013-12-04T00:57:16Z
2013-05-30T16:39:25Z
CONTRIBUTOR
null
related to #3418 should auto generate class methods for the io and delay the imports until actually called (including html, excel, csv, hdf, dta) deprecate these methods as well: https://mail.google.com/mail/u/0/?shva=1#inbox/13ec1cd9b60c5bda at the very least should deprecate: ``` from_csv -> pd.read_csv from_dt...
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3,412
Panel with int64 index resulting data to be NaN
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2013-04-22T01:29:11Z
2013-05-10T10:41:07Z
2013-05-10T10:41:07Z
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a = pandas.Series([1,2]) b = pandas.Series([3,4]) c = pandas.DataFrame( {'a':a, 'b':b}) d = pandas.DataFrame( {'a':a, 'b':b}) e = pandas.Panel({1365455239396772380:c, 1365455239396772380:d}) In [21]: e[1365455239396772380] Out[21]: a b 0 NaN NaN 1 NaN NaN
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3,413
Multiple series for FRED data
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2013-04-22T03:39:32Z
2013-11-27T18:31:21Z
2013-11-27T18:31:21Z
CONTRIBUTOR
null
I haven't looked under the hood yet, but it doesn't look like you can grab multiple series from FRED data at the moment. This works ``` from pandas.io.data import DataReader merge = lambda x,y : x.merge(y, left_index=True, right_index=True) dta = reduce(merge, [DataReader(i, "fred") for i in ["AKUR", "ALUR","GAUR"]])...
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astype(object) with dtype datetime64 does wacky things when value is NaT
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2013-04-22T04:52:37Z
2013-05-09T00:43:14Z
2013-05-09T00:43:14Z
CONTRIBUTOR
null
Similar to #3416, failing in 0.11 Calling astype(object) when the dtype is datetime64 and there are NaT values, sets them to 2262-04-10 00:12:43.145224 I would have thought they should be set to None. See attached test case.
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3,415
Possibility to include np.inf as end point in pd.cut bins.
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2013-04-22T08:24:40Z
2013-09-25T15:10:49Z
2013-09-25T15:10:49Z
NONE
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I don't know if it is desirable, but I think it would be nice to be able to include an infinity value as the endpoint to the bins in pandas cut function. ``` pd.cut([10, 20], [1, 5, np.inf], right=False) ```
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BUG: conversion from np.datetime64 has odd numpy buglet
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2013-04-22T13:41:21Z
2014-03-30T09:25:39Z
2013-05-08T21:52:21Z
CONTRIBUTOR
null
see #3414 The resulting dtype is wrong (should be datetime64[ns]), and should either raise on dtype='datetime64' or deal with it in Series ``` In [1]: dates = [ ...: np.datetime64(datetime.date(2013, 1, 1)), ...: np.datetime64(datetime.date(2013, 1, 2)), ...: np.datetime64(datetime.date(2013, 1, ...
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3,417
DataFrame.groupby(as_index=False).apply() ignores option and sets wrong indices
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2013-04-22T16:52:27Z
2013-08-27T00:20:23Z
2013-08-27T00:20:23Z
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The following code starts from a 9 by 2 DataFrame with 3 groups, no index. When applying a function to each group that returns a 1 by 2 DataFrame, an index is introduced that doesn't seem to make sense, and the as_index=False option is ignored: ``` df = pd.DataFrame({ 'a' : [1,1,1,2,2,2,3,3,3], ...
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API: read_csv inconsistent with from_csv -- parses ints as dates
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2013-04-22T17:23:43Z
2013-09-30T13:07:28Z
2013-09-30T13:07:28Z
NONE
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Using pandas 0.10.1. I read the docs, but didn't see any explanation of why this would be true. pandas.read_csv() works exactly as you'd expect, but pandas.DataFrame.from_csv() is different. Looks like the latter method assumes you're probably dealing with time series data, so it sets defaults parameters to automatical...
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investigate travis warning in py2.6
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2013-04-30T04:15:23Z
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``` Exception RuntimeError: 'maximum recursion depth exceeded while calling a Python object' in <type 'exceptions.RuntimeError'> ignored ```
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DOC: Adding parameters to frequencies, offsets (issue #2916)
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2013-04-22T20:53:51Z
2014-06-14T00:34:08Z
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CONTRIBUTOR
null
My first PR...
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hierarchical slices
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2013-04-22T22:10:07Z
2013-05-10T10:40:08Z
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Consider the following data: ``` python In [36]: index = pd.MultiIndex.from_arrays([['a','a','b','b','c','c'], [1,2,1,2,1,2]], names=['first','second']) In [37]: data = pd.DataFrame(np.random.rand(len(index),2), index=index, columns=['A','B']) In [38]: data Out[38]: A B first second ...
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DOC: Adding parameters address issue sub-points 8 and 10 - 24 (issue #2916)
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2013-04-22T23:43:22Z
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CLN: convert_objects(convert_dates='force') should use to_datetime()
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2013-04-23T00:07:55Z
2013-05-08T21:51:34Z
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CONTRIBUTOR
null
http://stackoverflow.com/questions/16157939/pandas-read-csv-fills-empty-values-with-string-nan/16158762#16158762 The convert_objects(convert_dates='force') should really just to to_datetime().... ``` In [1]: In [1]: data = """ ...: ...: value date id ...: ...: 0 2 2013-3-1 a ...: ...:...
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Alignment for Dataframe addition operation not working for datetime index
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2013-04-23T00:29:34Z
2013-04-23T01:23:03Z
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CONTRIBUTOR
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See details here: http://nbviewer.ipython.org/5439745 Version: '0.11.0.dev-9167213' Expected outcome: Same as `pd.concat([df1, df2], axis=1)`
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BUG: what to do with astype on datetime64
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2013-04-23T00:46:29Z
2013-12-04T00:57:16Z
2013-05-08T21:51:55Z
CONTRIBUTOR
null
http://stackoverflow.com/questions/16158795/cant-convert-dates-to-datetime64 prob should raise if u try to convert to something other than object or datetime64[ns] otherwise can have weird things happen
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TODO: more pprint imporvements
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2013-04-23T02:11:49Z
2018-07-06T22:16:25Z
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#### TODO - [ ] dicts with many keys should be summarized (Update: I can no longer remember the use case for dicts printed via pprint_thing). - [ ] summarization should match numpy [a.a.a ... b b b] not [a a a ...] - [ ] add np.set_printoptions(edgeitems) analogue. <del> - [ ] options.display.max_seq_items should ha...
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read excel support for python3
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2013-04-23T02:54:28Z
2013-07-22T20:31:51Z
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#3164 was merged (for diff reasons). enable on travis, enable some tests, and kick the tires a little bit.
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Inconsistent comparison between datetime and series of datetime
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2013-04-23T09:03:17Z
2013-09-25T16:23:43Z
2013-08-24T00:37:13Z
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similar to #3416 (also failing in 0.11) Using pandas 0.10.1 and numpy 1.6.1: ``` >>> import pandas; import numpy >>> s = pandas.Series(pandas.date_range('2013-01-01', periods=3)) >>> d = numpy.datetime64('2013-01-02') >>> s > d 0 False 1 False 2 True >>> d < s 0 True 1 True 2 True >>> s.dtype dtype...
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df summary view should show dtype associated with column, not just overall counts.
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NONE
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MDU6SXNzdWUxMzUzMTMzOQ==
3,430
Go through package docstrings and markup code snippets as such
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2013-04-23T12:11:00Z
2014-01-10T21:49:03Z
2014-01-10T12:10:12Z
NONE
null
Noted by @karmel in #3422, sphinx supports syntax highlighting/code quoting in code (ReST) docstrings using double colon + new line: ``` rst For example:: make_axis_dummies(panel, axis='major', transform=lambda d: d.weekday()) ``` sphinx 'autodoc' will pick these up and make...
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3,431
numpydoc sphinx extension disabled. was: Docstring convention
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2013-04-23T12:52:18Z
2013-04-30T04:16:24Z
2013-04-23T13:16:37Z
NONE
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**edit:** totally misguided. Sphinx has great support for method signature metadata in docstrings, there are python standars for ReST docstrings, and tooling to leverage and generate the docstrings. <del>In practice pandas uses an ad-hoc "visual" format for docstrings, which confuses sphinx and impedes automation. M...
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3,432
Sphinx autodoc is too selective in what it includes, use sphinx-apidoc
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2013-04-23T12:56:03Z
2014-01-10T12:27:15Z
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NONE
null
http://sphinx-doc.org/man/sphinx-apidoc.html?highlight=apidoc
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MDU6SXNzdWUxMzUzNTIwNg==
3,433
BUG: groupby regression
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1
2013-04-23T13:49:59Z
2013-09-22T00:36:35Z
2013-09-22T00:36:35Z
CONTRIBUTOR
null
in #2893 we changed the groupby behavior to return a series if a simple index is passed in and only have 1 group (rather than return a mi) I hit this regression as I doing several groupby's on different input, all of which yield multiple groups, except for 1, so I result with a bunch of frames and 1 series in 0.10.1...
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MDU6SXNzdWUxMzUzNjE1OQ==
3,434
WARN: possible windows x64 issue with older numpy MKL
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2013-04-23T14:10:36Z
2018-03-26T00:26:15Z
2018-03-26T00:26:15Z
CONTRIBUTOR
null
I happened to have an older verion of numpy 1.6.2 MKL installed on a windows machines very intermittently (I think you hae to be using a really big frame) sometimes I got a: OMP : Error # 134 Cannot set thread affinity mask which I think is caused by numexpr operations see this http://software.intel.com/en-us/foru...
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3,435
fillna() does not work when value parameter is a list
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2013-04-23T15:52:43Z
2020-06-19T11:17:51Z
2013-05-13T22:51:49Z
NONE
null
Should raise on a passed list to `value` The results from the fillna() method are very strange when the value parameter is given a list. For example, using a simple example DataFrame: > df = pandas.DataFrame({'A': [numpy.nan, 1, 2], 'B': [10, numpy.nan, 12], 'C': [[20, 21, 22], [23, 24, 25], numpy.nan]}) > df > ...
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3,436
Make convert_objects less aggressive
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8
2013-04-23T18:17:44Z
2014-04-03T17:05:50Z
2013-04-23T18:43:22Z
MEMBER
null
I find the following highly counterintuitive: ``` python df = DataFrame([["2003-1-1", "1"]], columns=["a", "b"]) conv = df.convert_objects(convert_numeric=True, convert_dates="coerce") conv.b.dtype == dtype('<M8[ns]') ``` I think date and numeric conversion should be independent between columns and dependent between...
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BUG: to_csv issue when multiple datetime64[ns] columns with some NaT
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2013-04-23T20:38:47Z
2016-10-12T23:03:45Z
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CONTRIBUTOR
null
http://stackoverflow.com/questions/16175761/pandas-to-csv-drops-values/16178032?noredirect=1#comment23125823_16178032
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3,438
BUG: GH3437 to_csv issue with large number of rows and some NaT in multi datetime64[ns] cols
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2013-04-23T21:05:03Z
2014-07-02T07:30:22Z
2013-04-24T12:49:50Z
CONTRIBUTOR
null
fixes #3437
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13,557,689
MDU6SXNzdWUxMzU1NzY4OQ==
3,439
Flesh out examples included in docstrings
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2013-04-23T21:12:36Z
2018-08-17T07:20:12Z
2018-08-17T07:20:12Z
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``` .../pandas$ nosetests -v --with-doctest -I .*test /.../.virtualenvs/myenv/local/lib/python2.7/site-packages/scikits/statsmodels/__init__.py:2: UserWarning: scikits.statsmodels namespace is deprecated and will be removed in 0.5, please use statsmodels instead warnings.warn('scikits.statsmodels namespace is depreca...
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13,558,621
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3,440
Panel attribute naming conflict if item is named 'a'
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2013-04-23T21:33:55Z
2013-08-05T01:44:08Z
2013-08-05T01:44:08Z
CONTRIBUTOR
null
Including an item named 'a' breaks the expected attribute-retrieval behavior for Panels ``` import numpy as np from pandas import DataFrame, Panel df0 = DataFrame(np.zeros([3,4])) df1 = DataFrame(np.ones([3,4])) p = Panel({'a':df0, 'b':df1}) p.b Out[6]: 0 1 2 3 0 1 1 1 1 1 1 1 1 1 2 1 1 1 1 p.a...
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3,441
Allow ExcelWriter() to add sheets to existing workbook
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40
2013-04-23T22:22:18Z
2020-03-20T16:11:29Z
2018-06-19T01:03:15Z
NONE
null
The ability of ExcelWriter to save different dataframes to different worksheets is great for sharing those dfs with the python-deficient. But this quickly leads to a need to _add_ worksheets to an existing workbook, not just creating one from scratch; something like: ``` df0=pd.DataFrame(np.arange(3)) df0.to_excel('f...
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3,442
Adding column to empty DataFrame doesn't work
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5
2013-04-23T23:02:13Z
2013-04-24T10:08:20Z
2013-04-24T04:07:04Z
NONE
null
``` python df = pd.DataFrame() df["test"] = 7 df["test2"] = pd.Series({"a" : "b"}) df ``` Returns: ``` Empty DataFrame Columns: [test, test2] Index: [] ``` Tested on pandas 0.10.1 and 0.11.0
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3,443
Support for multidimensional dtypes
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2013-04-24T13:49:52Z
2016-10-05T13:05:50Z
2016-10-05T11:25:28Z
NONE
null
With 0.11 out, Pandas supports more dtypes than before, which is very useful to us science folks. However, some data is intrinsically multi-dimensional, high enough dimensional so that using labels on columns is impractical (for instance, images). I understand DataFrames or Panels are usually the recommended panacea ...
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DOC: Adding Panel docs to API, and shortening line length in panel.py
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2013-04-24T15:31:12Z
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2013-04-24T15:50:16Z
CONTRIBUTOR
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13,595,431
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3,445
Deprecating the trellis rplot module
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2013-04-24T15:54:46Z
2018-06-09T14:38:19Z
2015-03-05T08:58:07Z
NONE
null
Original title: rplot.rst needs cleaning up --- http://pandas.pydata.org/pandas-docs/dev/rplot.html plot style, dimensions, grids, legend.
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3,446
Should HDFStore raise an Exception or a Warning when I remove a nonexistent object?
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2013-04-24T17:01:42Z
2013-04-30T04:14:50Z
2013-04-25T14:25:43Z
CONTRIBUTOR
null
Here is a case where I where the HDFStore would complain: ``` In [60]: store Out[60]: <class 'pandas.io.pytables.HDFStore'> File path: water/expected2.h5 /spelling series (shape->[2]) In [61]: store.remove('spellllling') ``` Is there a reason to keep it silent?
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BUG: Removing a nonexistent store raises a KeyError (GH3346)
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2013-04-24T18:17:18Z
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CONTRIBUTOR
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3,448
BUG: selection from unordered time-series has incorrect / odd behavior
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2013-04-24T21:30:46Z
2013-04-30T04:14:54Z
2013-04-25T14:24:18Z
CONTRIBUTOR
null
original mods made < 0.11 in #3136 / #2437 incorrect selections, depending on the start:end pos gettting weird values also should be able to select a value that's bigger/smaller than the contained range and have it work (this is how ordered series works) ``` [21]: s = Series(randn(10),date_range('20130101',periods=1...
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loc: label index does not raise KeyError with list of ints
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2013-04-24T22:07:11Z
2013-04-30T04:15:05Z
2013-04-25T01:56:02Z
CONTRIBUTOR
null
I didn't expect the last line of code to pass. ``` import numpy as np import pandas as pd pd.__version__ #[Out]# '0.12.0.dev-5c3ccdb' np.random.seed(33) df = pd.DataFrame(np.random.random((3, 3)), index=['a', 'b', 'c'], columns=['e', 'f', 'g']) # raise a KeyError? df.loc[[1, 2], ...
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3,450
BUG: index.map fast path raises recursion warnings on index.time GH3419
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2013-04-24T22:39:37Z
2014-07-16T08:06:17Z
2013-04-24T22:39:44Z
NONE
null
fyi @hayd #3419
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2013-04-25T00:05:20Z
2014-06-22T03:25:32Z
2013-04-25T01:55:28Z
CONTRIBUTOR
null
closes #3449
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BUG: GH3448 Unordered time series selection was misbehaving when using label slicing
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2013-04-25T01:10:17Z
2014-07-16T08:06:20Z
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CONTRIBUTOR
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closes #3448
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read_csv parse issues with \r line ending and quoted items
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2013-04-25T05:22:37Z
2013-06-02T23:27:57Z
2013-06-02T23:26:45Z
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There seems to be an issue with quotes containing the separator in read_csv ``` shell >>> pd.read_csv(StringIO.StringIO(' a,b,c\r"a,b","e,d","f,f"'), header=None) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/john/app/venv/lib/python2.7/site-packages/pandas/io/parsers.py", line...
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[BUG] to_csv() cols parameter not working properly.
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<b>pandas version:</b> 0.11 python version: 2.7.4 platforms: linux & windows When using cols parameter of to_csv() method only the order of the header is changed, while actual values are not. ``` python import pandas as pd from cStringIO import StringIO data = """\ date,time,X1,X2 2013-1-1,0030,0.1,0.4 2013-1-1,0100...
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fancy indexing with dupe columns yields unexpected ordering
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2013-04-25T10:49:27Z
2013-05-03T17:15:39Z
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``` In [16]: from pandas.util.testing import makeCustomDataframe as mkdf ...: df= mkdf(10, 3) ...: df.columns = ['a','a','b'] ...: cols = ['b','a'] ...: df[['b','a']].columns Out[16]: Index([a, a, b], dtype=object) ``` expected to see ``` ['b','a','a'] ``` Once fixed, can relax format.py:CSVFormatte...
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Index repr uses np.printoptions for "...", consolidate with display.options
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2013-04-25T11:43:54Z
2016-04-19T20:40:50Z
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use max_seq_len, after setting default to close #3391. also duplicate behaviour of "..." in other situations, rather then always printing 6 items
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engine='python' df.to_csv() duplicate columns doesn't work
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example from 0.10.1, and carried on to `to_csv(engine='python')` in 0.11 note the first columns duplicates the second columns, which shouldn't be. Corrolary #3454 ``` from pandas.util.testing import makeCustomDataframe as mkdf N=10 df= mkdf(N, 3) df.columns = ['a','a','b'] path = "/tmp/k.csv" df.to_csv("/tmp/k.csv"...
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BUG: to_csv handles cols= reordering,dupe cols GH3454
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#3454, #3457, #3455 @jreback, comments?
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BUG: GH3455 Duplicate indexes with getitem will return items in the correct order
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2013-04-25T14:17:46Z
2014-06-28T10:24:30Z
2013-04-25T14:38:06Z
CONTRIBUTOR
null
BUG: GH3457 to_csv writing duplicate columns incorrectly closes #3455, #3457
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13,644,466
MDU6SXNzdWUxMzY0NDQ2Ng==
3,460
tweak unicode() for PeriodIndex to yield valid python code
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2013-04-25T15:36:06Z
2013-05-10T09:30:13Z
2013-05-10T09:30:13Z
NONE
null
``` _p=PeriodIndex([u'2000-01-03'],freq='B') print unicode(_p) PeriodIndex([u'2000-01-03'], dtype=int64) ``` can't recreate object with result from `str(self)`.
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MDU6SXNzdWUxMzY0NTQ3Mg==
3,461
Sorting on Timestamp broken version 0.11
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2013-04-25T15:48:23Z
2013-04-30T04:14:24Z
2013-04-25T21:57:05Z
NONE
null
Issue: `frame.sort_index` uses `argsort` for a single sort column, but `_lexsort_indexer` for multi-columns need to do a transform on datetimens[64] before passing to ``_lexsort_`indexer` In [54]: a.columns Out[54]: Index([ticker, disclosuredate, txnid], dtype=object) In [55]: a.values Out[55]: array([[A, 2010-03-0...
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MDU6SXNzdWUxMzY0NTQ5MQ==
3,462
Dataframe fancy indexing behaviour with Periodindex via strings
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2013-04-25T15:48:34Z
2015-10-09T23:28:35Z
2015-10-09T23:28:35Z
NONE
null
``` cols=period_range('2000',periods=2) df=DataFrame([[1,2],[3,4]],columns=cols) cols = map(unicode,cols) df.loc[:,cols] KeyError: "[[u'2000-01-01', u'2000-01-02']] are not in ALL in the [columns]" ``` @jreback , not sure whether to call this a bug.
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https://api.github.com/repos/pandas-dev/pandas/issues/3463
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3,463
CLN: series to now inherit from NDFrame
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2013-04-25T18:40:30Z
2014-07-10T19:18:54Z
2013-04-29T14:37:13Z
CONTRIBUTOR
null
Major refactor primarily to make Series inherit from NDFrame Preserves pickle compat very few tests were changed (and only for compat on return objects) a few performance enhancements, a couple of regressions (see bottom) _obviously this is a large change in terms of the codebase, but it brings more consistency betwee...
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3,464
BUG: GH3461 Fix sorting in a frame with a list of columns which contains datetime64
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2013-04-25T21:27:25Z
2014-07-03T18:23:38Z
2013-04-25T21:56:33Z
CONTRIBUTOR
null
closes #3461
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13,701,442
MDU6SXNzdWUxMzcwMTQ0Mg==
3,465
Strange index/str repr behavior
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2
2013-04-26T18:11:36Z
2016-10-12T23:03:45Z
2013-04-26T18:52:57Z
MEMBER
null
I love the idea of valid-python-code reprs, but this just seems plain wrong: ![weird-repr](https://f.cloud.github.com/assets/417981/432123/aaae270a-ae9c-11e2-9ad6-3983ca576cf4.png) This throws an exception if you try to eval it.
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3,466
Fix pprint of index, summarizes according to display.max_seq_items
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2013-04-26T18:51:30Z
2014-06-22T23:23:22Z
2013-04-26T18:52:46Z
NONE
null
#3465 makes #3391 a very good idea.
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3,467
BUG: adjust to_latex column format when no index
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2013-04-26T21:14:43Z
2014-07-16T08:06:35Z
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CONTRIBUTOR
null
`to_latex` was adding an extra alignment to `column_format` when the `index` argument was False
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3,468
Pandas inconsistenly handles identically named columns in csv export and merging
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2013-04-26T21:25:39Z
2013-07-10T13:53:19Z
2013-07-10T13:53:19Z
NONE
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Using pandas 0.10.1 Pandas allows creating a dataframe with two columns with the same name. (I disagree that it should be allowed, but it is allowed, so OK). However, it doesn't handle that correctly in several cases. Pandas ought to either completely disallow duplicate named columns _or_ handle them everywhere. Bu...
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ENH: Adding '.' as an na_value for FRED.
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CONTRIBUTOR
null
The St. Louis Fed's [FRED](http://research.stlouisfed.org/fred2/) uses '.' as an NaN marker. I don't think the user has any way to specify the na_value via DataReader, so this just hard codes '.' as an na_value in the fred data-fetching function. Before: ``` python In [4]: from pandas.io.data import DataReader In [...
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ENH: Bring Series.dot up to par with DataFrame.dot
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2013-04-27T03:19:17Z
2014-07-16T08:06:39Z
2013-04-29T17:43:37Z
CONTRIBUTOR
null
If second argument is Series or DataFrame, ensures alignment of indices. If second argument is some type of ndarray, just fall back to np.dot on the values. This mirrors the behavior in DataFrame.dot Includes unittest
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module compiled against API version 8 but this version of numpy is 7
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8
2013-04-27T07:54:23Z
2013-10-13T02:08:21Z
2013-04-29T16:40:04Z
NONE
null
After upgrading to pandas 0.11.0 using pip, I get the following errors: ``` In [1]: import pandas --------------------------------------------------------------------------- RuntimeError Traceback (most recent call last) RuntimeError: module compiled against API version 8 but this version ...
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3,472
DOC: add note about pickle security and trusted sources.
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2013-04-30T04:13:46Z
2013-04-29T21:54:45Z
NONE
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ENH: Scatterplot Method added
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2013-04-27T21:06:11Z
2014-06-12T20:43:38Z
2013-10-17T12:50:56Z
CONTRIBUTOR
null
closes #2215 This is a simple pull request that creates a shortcut for scatter plots from a df. This is in reference to #2215 (and #1527) and follows the same pattern as df.hist(). ``` #where you would previously have had to do: from pandas.tools.plotting import scatter_plot scatter_plot(df, x = "x", y = 'y') ...
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3,474
scatter_plot produces double plots
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2013-04-28T00:44:16Z
2013-08-23T13:08:18Z
2013-08-23T13:08:18Z
NONE
null
following #3473: ``` import pandas as pd import numpy as np from pandas.tools.plotting import scatter_plot df = pd.DataFrame( np.random.randn(100,4)) scatter_plot(df,x=1,y=2) **Plot** **Same Plot Again** ```
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False ValueError in `pandas.to_datetime`?
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4
2013-04-28T01:10:48Z
2013-04-28T01:30:39Z
2013-04-28T01:30:39Z
NONE
null
While trying to convert a Series of string dates to datetime objects using `pandas.to_datetime`, I get a ValueError indicating a bogus date: ``` In [11]: hospitalized['birth_date'] = pd.to_datetime(hospitalized.child_birth_date, errors='raise', format='%Y-%m-%d') newborns['birth_date'] = pd.to_datetime(newborns.bi...
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3,476
Add coverage support to travis via coveralls.io
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2013-04-28T15:27:23Z
2013-10-07T14:44:58Z
2013-04-29T01:04:52Z
MEMBER
null
It might be nice to add support for coverage info via [coveralls](http://coveralls.io). [Here](https://coveralls.io/info/features) are some of the features. Looks like [this Python interface](https://github.com/coagulant/coveralls-python) is slightly more actively developed and would be the way to go. Not sure if this ...
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Read html tables into DataFrames
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2013-04-28T18:01:06Z
2014-06-16T01:32:21Z
2013-05-03T16:54:13Z
MEMBER
null
This PR adds new functionality for reading HTML tables from a URI, string, or file-like object into a DataFrame. #3369
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DataFrame constructor raises exception with masked recarray
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2013-04-29T05:50:47Z
2013-09-14T20:34:53Z
2013-09-14T20:34:53Z
CONTRIBUTOR
null
The `DataFrame` constructor supports numpy's ndarray of primitive type, recarray (or structured array) or a masked array of simple type. It breaks when given a masked recarray: ``` python >>> a = np.ma.mrecords.fromrecords([(1,2)], names=['a', 'b'], mask=False) >>> pandas.DataFrame(a) ... TypeError: cannot perform red...
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Support mrecarrays in DataFrame constructor
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9
2013-04-29T06:00:17Z
2014-07-17T09:17:17Z
2013-09-13T21:39:53Z
CONTRIBUTOR
null
This is intended as a fix for #3478. ~~Sorry I do not have the time to write rigorous tests.~~
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MDU6SXNzdWUxMzc1NTM5Mw==
3,480
An apply on a DataFrame along axis=1 breaks aggregations on groupby's of that DataFrame
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2013-04-29T11:18:59Z
2013-05-01T14:27:20Z
2013-05-01T14:27:20Z
NONE
null
This seems to be a regression from 0.10.1 to 0.11.0 This works: ``` python from pandas import DataFrame df = DataFrame({'foo1' : ['one', 'two', 'two', 'three', 'one', 'two'], 'foo2' : np.random.randn(6)}) grouped = df.groupby('foo1') grouped.agg(['mean']) ``` This does not (notice the apply): ``` py...
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MDU6SXNzdWUxMzc1Nzk5Ng==
3,481
Raise more helpful exception when concat() wrongly called as concat(obj1,obj2)
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2013-04-29T12:38:49Z
2013-05-10T10:43:31Z
2013-05-10T10:43:31Z
NONE
null
concat is supposed to be called with objs = a list or dict. Not multiple objects as as separate args. RIGHT: concat([df1,df2]) WRONG: concat(df1,df2) The exception thrown in the latter case is seriously cryptic. --- df1 = pd.DataFrame(randn(5,3), columns=['a','b','c']) df2 = pd.DataFrame(randn(5,3), columns=['a','b',...
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13,763,019
MDExOlB1bGxSZXF1ZXN0NTQyNTU2OQ==
3,482
CLN: series to now inherit from NDFrame
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70
2013-04-29T14:37:35Z
2014-06-12T18:13:47Z
2013-08-16T19:27:02Z
CONTRIBUTOR
null
Major refactor primarily to make Series inherit from NDFrame affects #4080, #3862, #816, #3217, #3386, #4463, #4204, #4118 , #4555 Preserves pickle compat very few tests were changed (and only for compat on return objects) a few performance enhancements, a couple of regressions (see bottom) _obviously this is a larg...
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3,483
BUG: GH3468 Fix assigning a new index to a duplicate index in a DataFrame would fail
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15
2013-04-29T16:06:30Z
2014-06-12T15:57:23Z
2013-05-02T01:15:09Z
CONTRIBUTOR
null
partially fixes #3468 This would previously raise (same dtype assignment to a non-multi dtype frame with dup indicies) ``` In [6]: df = DataFrame([[1,2]], columns=['a','a']) In [7]: df.columns = ['a','a.1'] In [8]: df Out[8]: a a.1 0 1 2 ``` construction of a multi-dtype frame with a dup index (#2194) is...
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13,768,532
MDU6SXNzdWUxMzc2ODUzMg==
3,484
Trellis plot: wrong encoding by shape (rplot.scaleshape)
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3
2013-04-29T16:25:38Z
2015-01-26T00:57:32Z
2015-01-26T00:56:17Z
NONE
null
The trellis plot shown in the documentation (http://pandas.pydata.org/pandas-docs/stable/_images/rplot7_tips.png) that uses ScaleShape to encode the data column "size" by shape shows a bug: The same shape is used for "Sun, 5" and "Sun, 6" although they should have different shapes. Also "Thur, 4" and "Thur, 5" have th...
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13,769,557
MDU6SXNzdWUxMzc2OTU1Nw==
3,485
startswith function gives misleading results when passed a series
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2013-04-29T16:48:27Z
2020-05-03T19:48:28Z
null
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Using pandas 0.10.1. I think this is probably "working correctly as designed", but the design seems non-obvious and there's not much documentation on this. The Series object has a vectorized .str.startswith() method which works when you give it a constant string. But if you give it a series instead of a string, it...
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13,771,776
MDU6SXNzdWUxMzc3MTc3Ng==
3,486
single column DF plot, color problem
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2013-04-29T17:38:53Z
2017-05-14T10:33:54Z
2017-05-11T16:07:28Z
NONE
null
``` import pylab import pandas.util.testing as put df = put.makeTimeDataFrame() pylab.figure() df[ ['A'] ].plot(color = ['r']) pylab.savefig('C:/tmp.png') ``` will give an error ``` raise ValueError('to_rgba: Invalid rgba arg "%s"\n%s' % (str(arg), exc)) ValueError: to_rgba: Invalid rgba arg "['r']" ``` All you need...
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MDU6SXNzdWUxMzc3NDc5MA==
3,487
Can't handle duplicate column names in sql read
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2013-04-29T18:43:51Z
2013-05-10T16:38:13Z
2013-05-10T16:38:13Z
NONE
null
Possibly related to #3468 Using pandas 0.10.1. It's legal for sql (at least Sql Server) to have queries that return two columns with the same name. And it's legal for pandas to have dataframes that have two columns with the same name. But pandas gives a very misleading error message when you try it with read_frame: #...
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13,789,775
MDU6SXNzdWUxMzc4OTc3NQ==
3,488
Index get_loc() to accept list of labels
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2013-04-30T02:10:45Z
2013-05-02T19:13:51Z
2013-05-02T19:13:51Z
NONE
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Index get_loc(key_list) would be a nice enhance. Returning a list.
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3,489
version 0.11 issues with to_csv
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2013-04-30T03:01:04Z
2013-05-10T10:09:08Z
2013-05-10T10:09:08Z
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It looks like that some changes were made to the DataFrame.to_csv method, as mentioned in the what's new document. Today I found two issues with the updated to_csv: 1) I have an int column, when I use floatformat parameter, the int are changed to float 2) cols parameter simply changes the name of columns, it does no...
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xaxis limits change when plotting time series of different resolution as secondary_y
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3
2013-04-30T06:03:31Z
2014-07-01T23:59:35Z
2014-07-01T23:59:35Z
NONE
null
``` python In [1]: N = 10000 In [2]: rng = pd.date_range('1/1/2000', periods=N, freq='min') In [3]: ts = pd.Series(np.random.randn(N), index=rng) In [4]: ax = ts.plot() In [5]: ax.get_xlim() Out[5]: (15778080.0, 15788079.0) In [6]: ts.resample('D').plot(style='ro', ax=ax) Out[6]: <matplotlib.axes.AxesSubplot at 0x...
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13,796,890
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3,491
Failing Unit Test and Patch for Fixing MonthEnd DateRange Unions with Timezones
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1
2013-04-30T08:35:55Z
2014-06-25T20:51:29Z
2013-05-05T10:53:33Z
CONTRIBUTOR
null
This patch preserves the timezone information when applying an offset to `DatetimeIndex` with a timezone applied. The `MonthEnd` Offset wasn't retaining the timezone information resulting in an error even when both indexes had timezones. ``` TypeError: can't compare offset-naive and offset-aware datetimes ```
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3,492
assignment in mixed-type dataframes not working?
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2013-04-30T13:51:51Z
2013-05-27T20:34:28Z
2013-05-07T17:34:46Z
CONTRIBUTOR
null
``` from pandas import DataFrame df=DataFrame({'a':{1:'aaa',2:'bbb',3:'ccc'},'b':{1:111,2:222,3:333}}) #this works, new column is created correctly df['test']=df['a'].apply(lambda x: '_' if x=='aaa' else x) #this does not work, ie column test is not changed idx=df['test']=='_' temp=df.ix[idx,'a'].apply(lambda x: '-----...
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3,493
Cannot append DataFrames with uint dtypes to HDFStore
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2013-04-30T17:29:01Z
2013-05-01T16:31:25Z
2013-05-01T16:31:25Z
CONTRIBUTOR
null
Trying to store DataFrames with unsigned integer dtypes in HDFStore fails due to a bug in the `get_atom_data` methods of the `DataCol` and `DataIndexableCol` classes in `pandas.io.pytables`. These methods use Python's `capitalize` method to map dtypes to PyTables column types, and fail because PyTables' unsigned int c...
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BUG: GH3493 fix Cannot append DataFrames with uint dtypes to HDFStore
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3
2013-04-30T17:56:04Z
2014-07-02T10:29:10Z
2013-05-01T16:29:09Z
CONTRIBUTOR
null
Fix for self-reported uint bug in HDFStore. #3493 Travis results (pass): https://travis-ci.org/jmellen/pandas/builds/6764554
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3,495
BUG: fix to_csv to work with dup column indices
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1
2013-04-30T18:20:28Z
2013-05-02T14:54:00Z
2013-05-02T14:54:00Z
CONTRIBUTOR
null
continuation of #3095 this will work after #3483
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BUG: GH3416 properly convert np.datetime64 objects in the _possibily_convert_datetimes
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2013-04-30T19:51:34Z
2014-06-29T16:39:27Z
2013-04-30T20:22:09Z
CONTRIBUTOR
null
closes #3416
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VIS: Pandas imshow-like function
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2013-04-30T20:26:07Z
2018-02-15T08:30:11Z
2014-02-21T04:39:15Z
MEMBER
null
matplotlib's `imshow` is pretty unawesome for DataFrames. For example, to label the axes one must do all sorts of tricks with the formatting API. Pandas provides great indexing/labeling capabilities. I propose a function similar to `imshow` that uses the information in a DataFrame to correctly label the axes. The API ...
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Inconsistency between read_csv(... parse_dates) and read_csv followed by astype('datetime')
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2013-04-30T22:42:31Z
2016-07-04T12:41:34Z
2016-07-04T08:28:29Z
CONTRIBUTOR
null
Write time-zones out in csv file Datetimes are written to csv in readable UTC. Using `pd.read_csv('file.csv', parse_dates=['date'])` expects UTC. `astype('datetime64')` expects readable dates (with no timezone specified) to be local (which also makes sense). But it leads to the following: ``` python import pandas...
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3,499
Loose frequency information when storing with table=True to HDF5
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2
2013-05-01T00:33:19Z
2013-05-08T21:48:32Z
2013-05-08T21:48:32Z
NONE
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I have found what possibly is a bug. When storing data as HDF5 with `table=True` the read value of series.index.freq from HDF5 is set to None rather than its original values. Please see: http://stackoverflow.com/questions/16311045/in-pandas-why-is-frequency-information-lost-when-storing-in-hdf5-as-a-table Not sure i...
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https://api.github.com/repos/pandas-dev/pandas/issues/3500
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https://github.com/pandas-dev/pandas/pull/3500
13,837,703
MDExOlB1bGxSZXF1ZXN0NTQ2NTMwNA==
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My first PR ever. Adding documentation to Cookbook.
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{ "closed_at": "2013-07-24T23:25:44Z", "closed_issues": 410, "created_at": "2013-04-30T04:12:30Z", "creator": null, "description": "Major release (formerly 0.11.1 bugfix but has outgrown its britches)", "due_on": "2013-07-05T07:00:00Z", "html_url": "https://github.com/pandas-dev/pandas/milestone/22", "i...
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2013-05-01T04:03:03Z
2013-05-10T18:02:59Z
2013-05-10T10:38:12Z
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Just adding some more description to Cookbook documentation per J. Reback's request. If I didn't mess up anything here, I will go through the rest of the items and add some description. Please let me know if I messed anything up.
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