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https://api.github.com/repos/pandas-dev/pandas/issues/3401 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3401/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3401/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3401/events | https://github.com/pandas-dev/pandas/issues/3401 | 13,398,978 | MDU6SXNzdWUxMzM5ODk3OA== | 3,401 | FMT: allow datetime/timedelta formatting on a column to be better | {
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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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"f... | 36 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3404 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3404/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3404/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3404/events | https://github.com/pandas-dev/pandas/issues/3404 | 13,419,664 | MDU6SXNzdWUxMzQxOTY2NA== | 3,404 | Multicharacter delimiters + non-UTF8 encoding doesn't work correctly in parsers | {
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CLN: better error messages on invalid appends
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https://api.github.com/repos/pandas-dev/pandas/issues/3407 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3407/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3407/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3407/events | https://github.com/pandas-dev/pandas/issues/3407 | 13,440,125 | MDU6SXNzdWUxMzQ0MDEyNQ== | 3,407 | Infinite loop in Python when doing simple operations | {
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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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https://api.github.com/repos/pandas-dev/pandas/issues/3411 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3411/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3411/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3411/events | https://github.com/pandas-dev/pandas/issues/3411 | 13,450,035 | MDU6SXNzdWUxMzQ1MDAzNQ== | 3,411 | CLN: create io.api for io relegated read_xxx | {
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"i... | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3412 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3412/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3412/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3412/events | https://github.com/pandas-dev/pandas/issues/3412 | 13,460,164 | MDU6SXNzdWUxMzQ2MDE2NA== | 3,412 | Panel with int64 index resulting data to be NaN | {
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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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https://api.github.com/repos/pandas-dev/pandas/issues/3413 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3413/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3413/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3413/events | https://github.com/pandas-dev/pandas/issues/3413 | 13,462,103 | MDU6SXNzdWUxMzQ2MjEwMw== | 3,413 | Multiple series for FRED data | {
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"followers_url": "https://api.github.com/users/wesm... | 4 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3414 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3414/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3414/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3414/events | https://github.com/pandas-dev/pandas/issues/3414 | 13,463,118 | MDU6SXNzdWUxMzQ2MzExOA== | 3,414 | astype(object) with dtype datetime64 does wacky things when value is NaT | {
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"i... | 10 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3415 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3415/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3415/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3415/events | https://github.com/pandas-dev/pandas/issues/3415 | 13,468,466 | MDU6SXNzdWUxMzQ2ODQ2Ng== | 3,415 | Possibility to include np.inf as end point in pd.cut bins. | {
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```
pd.cut([10, 20], [1, 5, np.inf], right=False)
```
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https://api.github.com/repos/pandas-dev/pandas/issues/3416 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3416/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3416/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3416/events | https://github.com/pandas-dev/pandas/issues/3416 | 13,482,171 | MDU6SXNzdWUxMzQ4MjE3MQ== | 3,416 | BUG: conversion from np.datetime64 has odd numpy buglet | {
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"i... | 1 | 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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"followers_url": "https://api.github.com/users/wesm... | 3 | 2013-04-22T16:52:27Z | 2013-08-27T00:20:23Z | 2013-08-27T00:20:23Z | NONE | null | 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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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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https://api.github.com/repos/pandas-dev/pandas/issues/3419 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3419/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3419/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3419/events | https://github.com/pandas-dev/pandas/issues/3419 | 13,497,132 | MDU6SXNzdWUxMzQ5NzEzMg== | 3,419 | investigate travis warning in py2.6 | {
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"i... | 0 | 2013-04-22T18:06:15Z | 2013-04-30T04:15:23Z | 2013-04-24T22:39:54Z | NONE | null | ```
Exception RuntimeError: 'maximum recursion depth exceeded while calling a Python object'
in <type 'exceptions.RuntimeError'> ignored
```
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https://api.github.com/repos/pandas-dev/pandas/issues/3420 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3420/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3420/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3420/events | https://github.com/pandas-dev/pandas/pull/3420 | 13,506,553 | MDExOlB1bGxSZXF1ZXN0NTMwMjE4OQ== | 3,420 | DOC: Adding parameters to frequencies, offsets (issue #2916) | {
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``` 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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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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https://api.github.com/repos/pandas-dev/pandas/issues/3424 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3424/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3424/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3424/events | https://github.com/pandas-dev/pandas/issues/3424 | 13,513,985 | MDU6SXNzdWUxMzUxMzk4NQ== | 3,424 | Alignment for Dataframe addition operation not working for datetime index | {
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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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"i... | 1 | 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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"followers_url": "https://api.github.com/users/jorisva... | 10 | 2013-04-23T02:11:49Z | 2018-07-06T22:16:25Z | 2018-07-06T22:16:11Z | NONE | null | #### 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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https://api.github.com/repos/pandas-dev/pandas/issues/3427 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3427/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3427/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3427/events | https://github.com/pandas-dev/pandas/issues/3427 | 13,516,877 | MDU6SXNzdWUxMzUxNjg3Nw== | 3,427 | read excel support for python3 | {
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"i... | 1 | 2013-04-23T02:54:28Z | 2013-07-22T20:31:51Z | 2013-07-22T20:31:10Z | NONE | null | #3164 was merged (for diff reasons).
enable on travis, enable some tests, and kick the tires
a little bit.
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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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https://api.github.com/repos/pandas-dev/pandas/issues/3429 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3429/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3429/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3429/events | https://github.com/pandas-dev/pandas/issues/3429 | 13,527,647 | MDU6SXNzdWUxMzUyNzY0Nw== | 3,429 | df summary view should show dtype associated with column, not just overall counts. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3430 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3430/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3430/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3430/events | https://github.com/pandas-dev/pandas/issues/3430 | 13,531,339 | MDU6SXNzdWUxMzUzMTMzOQ== | 3,430 | Go through package docstrings and markup code snippets as such | {
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"labels_url": "htt... | 12 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3431 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3431/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3431/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3431/events | https://github.com/pandas-dev/pandas/issues/3431 | 13,532,807 | MDU6SXNzdWUxMzUzMjgwNw== | 3,431 | numpydoc sphinx extension disabled. was: Docstring convention | {
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"i... | 7 | 2013-04-23T12:52:18Z | 2013-04-30T04:16:24Z | 2013-04-23T13:16:37Z | NONE | null | **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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https://api.github.com/repos/pandas-dev/pandas/issues/3432 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3432/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3432/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3432/events | https://github.com/pandas-dev/pandas/issues/3432 | 13,532,946 | MDU6SXNzdWUxMzUzMjk0Ng== | 3,432 | Sphinx autodoc is too selective in what it includes, use sphinx-apidoc | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3433 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3433/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3433/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3433/events | https://github.com/pandas-dev/pandas/issues/3433 | 13,535,206 | MDU6SXNzdWUxMzUzNTIwNg== | 3,433 | BUG: groupby regression | {
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"followers_url": "https://api.github.com/users/wesm... | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3434 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3434/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3434/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3434/events | https://github.com/pandas-dev/pandas/issues/3434 | 13,536,159 | MDU6SXNzdWUxMzUzNjE1OQ== | 3,434 | WARN: possible windows x64 issue with older numpy MKL | {
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"f... | 7 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3435 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3435/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3435/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3435/events | https://github.com/pandas-dev/pandas/issues/3435 | 13,541,616 | MDU6SXNzdWUxMzU0MTYxNg== | 3,435 | fillna() does not work when value parameter is a list | {
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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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https://api.github.com/repos/pandas-dev/pandas/issues/3436 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3436/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3436/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3436/events | https://github.com/pandas-dev/pandas/issues/3436 | 13,549,178 | MDU6SXNzdWUxMzU0OTE3OA== | 3,436 | Make convert_objects less aggressive | {
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``` 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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https://api.github.com/repos/pandas-dev/pandas/issues/3437 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3437/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3437/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3437/events | https://github.com/pandas-dev/pandas/issues/3437 | 13,556,160 | MDU6SXNzdWUxMzU1NjE2MA== | 3,437 | BUG: to_csv issue when multiple datetime64[ns] columns with some NaT | {
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"i... | 23 | 2013-04-23T20:38:47Z | 2016-10-12T23:03:45Z | 2013-04-24T12:49:37Z | CONTRIBUTOR | null | http://stackoverflow.com/questions/16175761/pandas-to-csv-drops-values/16178032?noredirect=1#comment23125823_16178032
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https://api.github.com/repos/pandas-dev/pandas/issues/3438 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3438/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3438/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3438/events | https://github.com/pandas-dev/pandas/pull/3438 | 13,557,356 | MDExOlB1bGxSZXF1ZXN0NTMyNzk3Nw== | 3,438 | BUG: GH3437 to_csv issue with large number of rows and some NaT in multi datetime64[ns] cols | {
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"i... | 2 | 2013-04-23T21:05:03Z | 2014-07-02T07:30:22Z | 2013-04-24T12:49:50Z | CONTRIBUTOR | null | fixes #3437
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https://api.github.com/repos/pandas-dev/pandas/issues/3439 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3439/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3439/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3439/events | https://github.com/pandas-dev/pandas/issues/3439 | 13,557,689 | MDU6SXNzdWUxMzU1NzY4OQ== | 3,439 | Flesh out examples included in docstrings | {
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"name": "Testing",
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"followers_url": "https://api.github... | 13 | 2013-04-23T21:12:36Z | 2018-08-17T07:20:12Z | 2018-08-17T07:20:12Z | NONE | null | ```
.../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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https://api.github.com/repos/pandas-dev/pandas/issues/3440 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3440/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3440/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3440/events | https://github.com/pandas-dev/pandas/issues/3440 | 13,558,621 | MDU6SXNzdWUxMzU1ODYyMQ== | 3,440 | Panel attribute naming conflict if item is named 'a' | {
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```
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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https://api.github.com/repos/pandas-dev/pandas/issues/3441 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3441/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3441/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3441/events | https://github.com/pandas-dev/pandas/issues/3441 | 13,560,477 | MDU6SXNzdWUxMzU2MDQ3Nw== | 3,441 | Allow ExcelWriter() to add sheets to existing workbook | {
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"followers_url": "https://api.github... | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3442 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3442/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3442/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3442/events | https://github.com/pandas-dev/pandas/issues/3442 | 13,561,840 | MDU6SXNzdWUxMzU2MTg0MA== | 3,442 | Adding column to empty DataFrame doesn't work | {
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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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https://api.github.com/repos/pandas-dev/pandas/issues/3443 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3443/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3443/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3443/events | https://github.com/pandas-dev/pandas/issues/3443 | 13,587,822 | MDU6SXNzdWUxMzU4NzgyMg== | 3,443 | Support for multidimensional dtypes | {
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I understand DataFrames or Panels are usually the recommended panacea ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3444 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3444/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3444/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3444/events | https://github.com/pandas-dev/pandas/pull/3444 | 13,593,822 | MDExOlB1bGxSZXF1ZXN0NTM0NTI1Mw== | 3,444 | DOC: Adding Panel docs to API, and shortening line length in panel.py | {
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---
http://pandas.pydata.org/pandas-docs/dev/rplot.html
plot style, dimensions, grids, legend.
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https://api.github.com/repos/pandas-dev/pandas/issues/3446 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3446/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3446/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3446/events | https://github.com/pandas-dev/pandas/issues/3446 | 13,598,617 | MDU6SXNzdWUxMzU5ODYxNw== | 3,446 | Should HDFStore raise an Exception or a Warning when I remove a nonexistent object? | {
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"i... | 8 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3448 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3448/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3448/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3448/events | https://github.com/pandas-dev/pandas/issues/3448 | 13,611,161 | MDU6SXNzdWUxMzYxMTE2MQ== | 3,448 | BUG: selection from unordered time-series has incorrect / odd behavior | {
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"i... | 1 | 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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"i... | 2 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3450 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3450/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3450/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3450/events | https://github.com/pandas-dev/pandas/pull/3450 | 13,615,138 | MDExOlB1bGxSZXF1ZXN0NTM1NTQ3OA== | 3,450 | BUG: index.map fast path raises recursion warnings on index.time GH3419 | {
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"i... | 0 | 2013-04-24T22:39:37Z | 2014-07-16T08:06:17Z | 2013-04-24T22:39:44Z | NONE | null | fyi @hayd
#3419
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"i... | 0 | 2013-04-25T00:05:20Z | 2014-06-22T03:25:32Z | 2013-04-25T01:55:28Z | CONTRIBUTOR | null | closes #3449
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"i... | 0 | 2013-04-25T01:10:17Z | 2014-07-16T08:06:20Z | 2013-04-25T12:29:36Z | CONTRIBUTOR | null | closes #3448
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"i... | 4 | 2013-04-25T05:22:37Z | 2013-06-02T23:27:57Z | 2013-06-02T23:26:45Z | NONE | null | 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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"i... | 4 | 2013-04-25T06:40:46Z | 2013-12-04T00:57:21Z | 2013-04-25T16:11:11Z | NONE | null | <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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https://api.github.com/repos/pandas-dev/pandas/issues/3455 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3455/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3455/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3455/events | https://github.com/pandas-dev/pandas/issues/3455 | 13,632,598 | MDU6SXNzdWUxMzYzMjU5OA== | 3,455 | fancy indexing with dupe columns yields unexpected ordering | {
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"i... | 3 | 2013-04-25T10:49:27Z | 2013-05-03T17:15:39Z | 2013-04-25T14:38:23Z | NONE | null | ```
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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... | 5 | 2013-04-25T11:43:54Z | 2016-04-19T20:40:50Z | 2016-04-19T20:40:50Z | NONE | null | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3457 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3457/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3457/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3457/events | https://github.com/pandas-dev/pandas/issues/3457 | 13,635,705 | MDU6SXNzdWUxMzYzNTcwNQ== | 3,457 | engine='python' df.to_csv() duplicate columns doesn't work | {
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"i... | 7 | 2013-04-25T12:29:18Z | 2013-04-30T04:14:37Z | 2013-04-25T15:25:49Z | NONE | null | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3458 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3458/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3458/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3458/events | https://github.com/pandas-dev/pandas/pull/3458 | 13,636,560 | MDExOlB1bGxSZXF1ZXN0NTM2NjIwOQ== | 3,458 | BUG: to_csv handles cols= reordering,dupe cols GH3454 | {
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@jreback, comments?
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https://api.github.com/repos/pandas-dev/pandas/issues/3459 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3459/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3459/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3459/events | https://github.com/pandas-dev/pandas/pull/3459 | 13,640,626 | MDExOlB1bGxSZXF1ZXN0NTM2ODI3Mg== | 3,459 | BUG: GH3455 Duplicate indexes with getitem will return items in the correct order | {
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closes #3455, #3457
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https://api.github.com/repos/pandas-dev/pandas/issues/3460 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3460/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3460/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3460/events | https://github.com/pandas-dev/pandas/issues/3460 | 13,644,466 | MDU6SXNzdWUxMzY0NDQ2Ng== | 3,460 | tweak unicode() for PeriodIndex to yield valid python code | {
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"i... | 2 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3461 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3461/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3461/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3461/events | https://github.com/pandas-dev/pandas/issues/3461 | 13,645,472 | MDU6SXNzdWUxMzY0NTQ3Mg== | 3,461 | Sorting on Timestamp broken version 0.11 | {
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"i... | 9 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3462 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3462/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3462/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3462/events | https://github.com/pandas-dev/pandas/issues/3462 | 13,645,491 | MDU6SXNzdWUxMzY0NTQ5MQ== | 3,462 | Dataframe fancy indexing behaviour with Periodindex via strings | {
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... | 1 | 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 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3463/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3463/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3463/events | https://github.com/pandas-dev/pandas/pull/3463 | 13,655,080 | MDExOlB1bGxSZXF1ZXN0NTM3NDk5Nw== | 3,463 | CLN: series to now inherit from NDFrame | {
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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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https://api.github.com/repos/pandas-dev/pandas/issues/3464 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3464/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3464/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3464/events | https://github.com/pandas-dev/pandas/pull/3464 | 13,662,880 | MDExOlB1bGxSZXF1ZXN0NTM3OTE2OQ== | 3,464 | BUG: GH3461 Fix sorting in a frame with a list of columns which contains datetime64 | {
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"i... | 6 | 2013-04-25T21:27:25Z | 2014-07-03T18:23:38Z | 2013-04-25T21:56:33Z | CONTRIBUTOR | null | closes #3461
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"i... | 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:

This throws an exception if you try to eval it.
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https://api.github.com/repos/pandas-dev/pandas/issues/3466 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3466/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3466/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3466/events | https://github.com/pandas-dev/pandas/pull/3466 | 13,703,104 | MDExOlB1bGxSZXF1ZXN0NTM5OTA0NQ== | 3,466 | Fix pprint of index, summarizes according to display.max_seq_items | {
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makes #3391 a very good idea.
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https://api.github.com/repos/pandas-dev/pandas/issues/3467 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3467/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3467/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3467/events | https://github.com/pandas-dev/pandas/pull/3467 | 13,708,555 | MDExOlB1bGxSZXF1ZXN0NTQwMjI2OQ== | 3,467 | BUG: adjust to_latex column format when no index | {
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"i... | 1 | 2013-04-26T21:14:43Z | 2014-07-16T08:06:35Z | 2013-04-28T00:55:20Z | CONTRIBUTOR | null | `to_latex` was adding an extra alignment to `column_format` when the
`index` argument was False
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https://api.github.com/repos/pandas-dev/pandas/issues/3468 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3468/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3468/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3468/events | https://github.com/pandas-dev/pandas/issues/3468 | 13,708,937 | MDU6SXNzdWUxMzcwODkzNw== | 3,468 | Pandas inconsistenly handles identically named columns in csv export and merging | {
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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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https://api.github.com/repos/pandas-dev/pandas/issues/3469 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3469/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3469/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3469/events | https://github.com/pandas-dev/pandas/pull/3469 | 13,714,165 | MDExOlB1bGxSZXF1ZXN0NTQwNTQyNg== | 3,469 | ENH: Adding '.' as an na_value for FRED. | {
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"i... | 17 | 2013-04-27T00:53:30Z | 2014-06-14T08:26:30Z | 2013-04-27T20:14:38Z | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3470 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3470/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3470/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3470/events | https://github.com/pandas-dev/pandas/pull/3470 | 13,715,716 | MDExOlB1bGxSZXF1ZXN0NTQwNjE2MA== | 3,470 | ENH: Bring Series.dot up to par with DataFrame.dot | {
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"i... | 5 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3471 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3471/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3471/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3471/events | https://github.com/pandas-dev/pandas/issues/3471 | 13,717,884 | MDU6SXNzdWUxMzcxNzg4NA== | 3,471 | module compiled against API version 8 but this version of numpy is 7 | {
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```
In [1]: import pandas
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
RuntimeError: module compiled against API version 8 but this version ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3472 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3472/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3472/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3472/events | https://github.com/pandas-dev/pandas/issues/3472 | 13,722,485 | MDU6SXNzdWUxMzcyMjQ4NQ== | 3,472 | DOC: add note about pickle security and trusted sources. | {
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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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```
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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```
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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https://api.github.com/repos/pandas-dev/pandas/issues/3476 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3476/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3476/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3476/events | https://github.com/pandas-dev/pandas/issues/3476 | 13,735,491 | MDU6SXNzdWUxMzczNTQ5MQ== | 3,476 | Add coverage support to travis via coveralls.io | {
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"gists_url": "https://... | [] | closed | false | null | [] | null | 3 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3477 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3477/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3477/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3477/events | https://github.com/pandas-dev/pandas/pull/3477 | 13,737,936 | MDExOlB1bGxSZXF1ZXN0NTQxNDI0MA== | 3,477 | Read html tables into DataFrames | {
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"i... | 58 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3478 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3478/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3478/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3478/events | https://github.com/pandas-dev/pandas/issues/3478 | 13,746,996 | MDU6SXNzdWUxMzc0Njk5Ng== | 3,478 | DataFrame constructor raises exception with masked recarray | {
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"followers_url": "https://api.github.com/users/wesm... | 6 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3479 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3479/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3479/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3479/events | https://github.com/pandas-dev/pandas/pull/3479 | 13,747,127 | MDExOlB1bGxSZXF1ZXN0NTQxNzg5MA== | 3,479 | Support mrecarrays in DataFrame constructor | {
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"followers_url": "https://api.github.com/users/wesm... | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3480 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3480/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3480/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3480/events | https://github.com/pandas-dev/pandas/issues/3480 | 13,755,393 | MDU6SXNzdWUxMzc1NTM5Mw== | 3,480 | An apply on a DataFrame along axis=1 breaks aggregations on groupby's of that DataFrame | {
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"i... | 4 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3481 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3481/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3481/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3481/events | https://github.com/pandas-dev/pandas/issues/3481 | 13,757,996 | MDU6SXNzdWUxMzc1Nzk5Ng== | 3,481 | Raise more helpful exception when concat() wrongly called as concat(obj1,obj2) | {
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"i... | 3 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3482 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3482/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3482/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3482/events | https://github.com/pandas-dev/pandas/pull/3482 | 13,763,019 | MDExOlB1bGxSZXF1ZXN0NTQyNTU2OQ== | 3,482 | CLN: series to now inherit from NDFrame | {
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"followers_url": "https://api.github.com/users/wesm... | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3483 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3483/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3483/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3483/events | https://github.com/pandas-dev/pandas/pull/3483 | 13,767,644 | MDExOlB1bGxSZXF1ZXN0NTQyNzkwMQ== | 3,483 | BUG: GH3468 Fix assigning a new index to a duplicate index in a DataFrame would fail | {
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"i... | 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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... | closed | false | null | [] | null | 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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"f... | 11 | 2013-04-29T16:48:27Z | 2020-05-03T19:48:28Z | null | NONE | null | 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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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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https://api.github.com/repos/pandas-dev/pandas/issues/3487 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3487/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3487/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3487/events | https://github.com/pandas-dev/pandas/issues/3487 | 13,774,790 | MDU6SXNzdWUxMzc3NDc5MA== | 3,487 | Can't handle duplicate column names in sql read | {
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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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https://api.github.com/repos/pandas-dev/pandas/issues/3488 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3488/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3488/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3488/events | https://github.com/pandas-dev/pandas/issues/3488 | 13,789,775 | MDU6SXNzdWUxMzc4OTc3NQ== | 3,488 | Index get_loc() to accept list of labels | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3489 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3489/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3489/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3489/events | https://github.com/pandas-dev/pandas/issues/3489 | 13,790,554 | MDU6SXNzdWUxMzc5MDU1NA== | 3,489 | version 0.11 issues with to_csv | {
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"i... | 4 | 2013-04-30T03:01:04Z | 2013-05-10T10:09:08Z | 2013-05-10T10:09:08Z | NONE | null | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3490 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3490/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3490/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3490/events | https://github.com/pandas-dev/pandas/issues/3490 | 13,793,396 | MDU6SXNzdWUxMzc5MzM5Ng== | 3,490 | xaxis limits change when plotting time series of different resolution as secondary_y | {
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"closed_at": "2014-07-11T00:02:53Z",
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"followers_url": "https://api.github.com/users/jr... | 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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"i... | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3492 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3492/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3492/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3492/events | https://github.com/pandas-dev/pandas/issues/3492 | 13,807,222 | MDU6SXNzdWUxMzgwNzIyMg== | 3,492 | assignment in mixed-type dataframes not working? | {
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"i... | 8 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3493 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3493/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3493/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3493/events | https://github.com/pandas-dev/pandas/issues/3493 | 13,817,509 | MDU6SXNzdWUxMzgxNzUwOQ== | 3,493 | Cannot append DataFrames with uint dtypes to HDFStore | {
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"i... | 4 | 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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https://api.github.com/repos/pandas-dev/pandas/issues/3494 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3494/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3494/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3494/events | https://github.com/pandas-dev/pandas/pull/3494 | 13,818,723 | MDExOlB1bGxSZXF1ZXN0NTQ1NTA3NA== | 3,494 | BUG: GH3493 fix Cannot append DataFrames with uint dtypes to HDFStore | {
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"i... | 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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"i... | 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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"followers_url": "https://api.github.com/users/jr... | 6 | 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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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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"i... | 2 | 2013-05-01T00:33:19Z | 2013-05-08T21:48:32Z | 2013-05-08T21:48:32Z | NONE | null | 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 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3500/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3500/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3500/events | https://github.com/pandas-dev/pandas/pull/3500 | 13,837,703 | MDExOlB1bGxSZXF1ZXN0NTQ2NTMwNA== | 3,500 | My first PR ever. Adding documentation to Cookbook. | {
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"i... | 4 | 2013-05-01T04:03:03Z | 2013-05-10T18:02:59Z | 2013-05-10T10:38:12Z | NONE | null | 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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