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https://api.github.com/repos/pandas-dev/pandas/issues/5401 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5401/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5401/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5401/events | https://github.com/pandas-dev/pandas/issues/5401 | 21,926,076 | MDU6SXNzdWUyMTkyNjA3Ng== | 5,401 | ENH: cross join in merge() and join() | {
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If I haven't missed something, there's no simple way to make [cartesian product](http://pandas.pydata.org/pandas-docs/stable/merging.html#brief-primer-on-merge-methods-relational-algebra) method in pandas. For example, see http://stackoverflow.com/questions/19... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5402 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5402/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5402/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5402/events | https://github.com/pandas-dev/pandas/issues/5402 | 21,929,013 | MDU6SXNzdWUyMTkyOTAxMw== | 5,402 | BUG/Not Implemented Panel.to_frame() with MultiIndex | {
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``` python
In [39]: df = pd.DataFrame({'A': [1, 2], 'B': pd.to_datetime(['a', 'b'])},
index=pd.MultiIndex.from_tuples([(1, 'one'), (1, 'two')]))
In [40]: df
Out[40]:
A B
1 one 1 a
two 2 b
In [41]: wp = pd.Panel({'i1': df, 'i2': df})
In [42]: wp.to_frame()
----... | {
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being passed an 'engine' keyword argument + a tad bit of style cleanup.
Thanks to @jseabold and @josef-pkt for making me realize that this was
unnecessary in https://github.com/statsmodels/statsmodels/issues/1167
:)
@jmcnamara - this has comple... | {
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"followers_url": "https://api.github.com/users/... | 11 | 2013-10-31T22:22:25Z | 2014-01-01T02:43:06Z | 2014-01-01T02:43:06Z | CONTRIBUTOR | null | I was looking into expanding the pandas.io.data functionality to read options data from Google Finance. After reading
http://pandas.pydata.org/pandas-docs/stable/gotchas.html#html-gotchas
I tried various combinations for parsing
http://www.google.com/finance/option_chain?q=GOOG
without success. The page formats its... | {
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This PR fixes those issues and add some more tests.
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Can we have it for `rolling_corr_pairwise` as well?
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Python 2.7.5 (default, May 15 2013, 22:44:16) [MSC v.1500 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
Imported NumPy 1.7.1, SciPy 0.12.0, Matplotlib 1.3.0 + guidata 1.6.1, guiqwt 2.3.1
Type "scientific" for more details.
>>> from csv import QUOTE_MINIMAL, ... | {
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https://travis-ci.org/pydata/pandas/jobs/13376953
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https://api.github.com/repos/pandas-dev/pandas/issues/5410 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5410/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5410/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5410/events | https://github.com/pandas-dev/pandas/issues/5410 | 21,987,717 | MDU6SXNzdWUyMTk4NzcxNw== | 5,410 | pd.to_timedelta(single_string) returns a Series, which ruins broadcasting. | {
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```
In [10]: pd.to_timedelta(Series(['00:03:37', '00:05:05'])) - pd.to_timedelta('00:03:00')
Out[10]:
0 00:00:37
1 NaT
dtype: timedelta64[ns]
```
because
```
In [13]: pd.to_timedelta('00:03:00')
Out[13]:
0 00:03:00
dtype: timedelta64[ns]
```
More expected and consistent behavior, in my opinio... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5412 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5412/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5412/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5412/events | https://github.com/pandas-dev/pandas/issues/5412 | 21,988,342 | MDU6SXNzdWUyMTk4ODM0Mg== | 5,412 | Support numpy 1.8 | {
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"followers_url": "https://api.github.com/users/wesm... | 7 | 2013-11-01T22:26:35Z | 2013-11-02T23:54:38Z | 2013-11-02T23:54:38Z | CONTRIBUTOR | null | Numpy 1.8 was released recently - https://github.com/numpy/numpy/blob/master/doc/release/1.8.0-notes.rst
We should probably support it and add/change a Travis build for it. Additionally, might be interesting to benchmark numpy's nanmean, nanvar and nanstd against pandas versions...
numpy also notes that they are plan... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5413 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5413/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5413/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5413/events | https://github.com/pandas-dev/pandas/pull/5413 | 21,989,201 | MDExOlB1bGxSZXF1ZXN0OTYxNTM5MQ== | 5,413 | BLD: numpy 1.8 on the 3.3/2.7 builds | {
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still pretty good coverage of all numpys
build take a tad longer w/o the wheels
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Maybe write tests for this? That much is over my head currently.
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So this is a hack to get things "working".
I mainly just wanted to ask if there was a better way to get the levels and labels to the MultiIndex constructor.
Don't spend long thinking about it (this is my PR after all), but if you know of a quick way off the top of your head, I'd be interest... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5418 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5418/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5418/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5418/events | https://github.com/pandas-dev/pandas/issues/5418 | 22,011,805 | MDU6SXNzdWUyMjAxMTgwNQ== | 5,418 | parse_time_string raises key error for certain frequencies | {
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... | 1 | 2013-11-02T23:51:00Z | 2015-07-14T15:52:23Z | 2015-07-14T15:52:23Z | CONTRIBUTOR | null | I will fix as part of #5148
For example:
```
parse_time_string('2013Q1', freq="INVLD-L-DEC-SAT")
```
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Something weird with HDF where, even though it's _supposed_ to be
removing the file every time, it causes issues to use a real temp
file... Not sure why (maybe I missed something there).
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https://api.github.com/repos/pandas-dev/pandas/issues/5420 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5420/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5420/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5420/events | https://github.com/pandas-dev/pandas/issues/5420 | 22,013,025 | MDU6SXNzdWUyMjAxMzAyNQ== | 5,420 | BUG: loc should not fallback for integer indexing for multi-index | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5421 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5421/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5421/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5421/events | https://github.com/pandas-dev/pandas/issues/5421 | 22,021,360 | MDU6SXNzdWUyMjAyMTM2MA== | 5,421 | DOC/API: provide a doc matrix of all indexing accessors and behaviors | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2013-11-03T15:36:11Z | 2018-07-06T23:02:56Z | 2018-07-06T23:02:41Z | CONTRIBUTOR | null | related #5420
ML issue: https://groups.google.com/forum/#!topic/pydata/Ke8kntiPHqw
existing tests here (and tests/test_frame.py, test_multilevel.py)
https://github.com/pydata/pandas/blob/master/pandas/tests/test_indexing.py
- create new top-level advanced indexing tab (move hierarchical and sections below here)
- add... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5422 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5422/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5422/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5422/events | https://github.com/pandas-dev/pandas/pull/5422 | 22,023,178 | MDExOlB1bGxSZXF1ZXN0OTYyODgwOA== | 5,422 | TST: make pytables tests go thru a temporary dir and file | {
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related #5419
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https://api.github.com/repos/pandas-dev/pandas/issues/5423 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5423/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5423/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5423/events | https://github.com/pandas-dev/pandas/pull/5423 | 22,026,397 | MDExOlB1bGxSZXF1ZXN0OTYzMDA0Mw== | 5,423 | ENH: Better handling of MultiIndex with Excel | {
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as merged cells. closes #5254.
Some notes on this PR:
- The required xlsxwriter version was up-revved in `ci/requirements*.txt`to pick up a fix in that module that makes working with charts from pandas easier.
- Added a comment to `release.rst`.
- Modified ... | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2013-11-03T20:58:31Z | 2013-11-04T00:40:53Z | 2013-11-04T00:40:53Z | CONTRIBUTOR | null | These two codeblocks result in different dataframes:
``` python
import pandas as pd
import numpy as np
cont = ['one', 'two','three', 'four', 'five', 'six', 'seven']
dfb = pd.DataFrame({'a' : cont, "b":cont[3:]+cont[:3] ,'c' : np.arange(7)})
#print dfb.ix[0,"c"]
dfb.ix[7,'c'] = 1
print dfb
print dfb.ix[7,"c"]
print dfb... | {
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Includes @jreback's commits from #5422 and hdf_temp:
- TST: make pytables tests go thru a temporary dir and file
- TST/BUG: incorrect way of testing for r+ modes
TST: fix temporary files by using mktemp (rather than mkstemp) which opens them
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https://api.github.com/repos/pandas-dev/pandas/issues/5426 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5426/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5426/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5426/events | https://github.com/pandas-dev/pandas/pull/5426 | 22,030,212 | MDExOlB1bGxSZXF1ZXN0OTYzMTU1OA== | 5,426 | BUG: not clearing the cache when reindexing issue when partial setting (GH5424) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5427 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5427/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5427/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5427/events | https://github.com/pandas-dev/pandas/issues/5427 | 22,031,192 | MDU6SXNzdWUyMjAzMTE5Mg== | 5,427 | BUG: Excel writer doesn't handle "cols" option correctly | {
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The `cols` option in `to_excel` no longer works correctly after the fix for the above issue. For example:
``` python
import pandas as pd
df = pd.DataFrame({'A': ['a', 'a', 'a'],
'B': ['b', 'b', 'b']})
df.to_excel('frame.xlsx', sheet_name='She... | {
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Currently the to_json() method only works for Series and DataFrame, and raises NotImplementedError when called on Panel. Would be great to implement it for Panel as well.
For me it is sufficient to loop through all items and convert each item (DataFrame) to json separately and then stitch them together.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5429 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5429/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5429/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5429/events | https://github.com/pandas-dev/pandas/pull/5429 | 22,031,659 | MDExOlB1bGxSZXF1ZXN0OTYzMjA2OQ== | 5,429 | BUG: Excel writer doesn't handle "cols" option correctly | {
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Notes on this PR:
- This fix addresses an issue introduced in #5235 (Issue with Excel writers when column names are duplicated).
- Basically it needs to handle 2 different use cases:
- The user uses duplicate column names
- The user specifies a different order via the `cols` option
``` python
# Case ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5430 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5430/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5430/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5430/events | https://github.com/pandas-dev/pandas/issues/5430 | 22,032,156 | MDU6SXNzdWUyMjAzMjE1Ng== | 5,430 | Resampling a Series with a timezone using kind='period' Crashes with ~6000 Values | {
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"followers_url": "https://api.github.com/users/wesm... | 23 | 2013-11-04T02:07:13Z | 2013-11-06T01:07:39Z | 2013-11-06T00:23:40Z | CONTRIBUTOR | null | I wrote a test case that consistently crashes the entire process. It looks like it requires a Series with data localized to a timezone that has a DST and the data crosses the DST boundary. Finally, you have to use `kind='period'`for the `resample()` operation. Oddly, it's not just the actual boundary, because I can ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5431 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5431/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5431/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5431/events | https://github.com/pandas-dev/pandas/issues/5431 | 22,032,757 | MDU6SXNzdWUyMjAzMjc1Nw== | 5,431 | Can we use xlrd for all Excel file reading? | {
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https://pypi.python.org/pypi/xlrd/0.9.2
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https://api.github.com/repos/pandas-dev/pandas/issues/5432 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5432/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5432/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5432/events | https://github.com/pandas-dev/pandas/pull/5432 | 22,076,313 | MDExOlB1bGxSZXF1ZXN0OTY1NTMyMw== | 5,432 | BUG: fix Resampling a Series with a timezone using kind='period' (GH5430) | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2013-11-04T20:11:40Z | 2014-07-16T08:39:13Z | 2013-11-06T00:23:40Z | CONTRIBUTOR | null | There's a failing test case and the patch in subsequent commits.
closes #5430
closes #3609
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https://api.github.com/repos/pandas-dev/pandas/issues/5433 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5433/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5433/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5433/events | https://github.com/pandas-dev/pandas/issues/5433 | 22,077,870 | MDU6SXNzdWUyMjA3Nzg3MA== | 5,433 | Update PDF documentation to Stable version 0.12.0 | {
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If you try to download this:
http://pandas.pydata.org/pandas-docs/stable/pandas.pdf
You'll get the documentation for version 0.11.0
Check the links for the pdf documentation at the main web page here:
http://pandas.pydata.org/
The s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5435 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5435/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5435/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5435/events | https://github.com/pandas-dev/pandas/issues/5435 | 22,086,010 | MDU6SXNzdWUyMjA4NjAxMA== | 5,435 | Add ExcelFile to API docs + clarify ExcelFile isn't deprecated (just moved) | {
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"labels_url": "htt... | 1 | 2013-11-04T22:46:06Z | 2014-01-28T02:11:13Z | 2014-01-28T01:05:02Z | CONTRIBUTOR | null | ExcelFile the class isn't actually in the API anywhere. We should rectify that. Also, I realized from [this SO question on ExcelFile](http://stackoverflow.com/questions/19760741/how-do-you-read-excel-sheets-using-index-instead-of-name-with-pandas-read-excel/19778206) that the release notes aren't explicitly clear that... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5436 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5436/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5436/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5436/events | https://github.com/pandas-dev/pandas/issues/5436 | 22,089,436 | MDU6SXNzdWUyMjA4OTQzNg== | 5,436 | API: timedelta64[ns] elements operate with timedelta/offsets | {
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```
type: timedelta64[ns]
In [23]: s = pd.to_timedelta(np.arange(5),unit='d')
In [24]: s
Out[24]:
0 00:00:00
1 1 days, 00:00:00
2 2 days, 00:00:00
3 3 days, 00:00:00
4 4 days, 00:00:00
dtype: timedelta64[ns]
In [25]: s + timedelta(hours=1)
Out[25]:
0 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5437 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5437/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5437/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5437/events | https://github.com/pandas-dev/pandas/issues/5437 | 22,093,205 | MDU6SXNzdWUyMjA5MzIwNQ== | 5,437 | BUG: pd.to_timedelta raises instead of returning NaT | {
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In [1]: Series(['2011-01-01', np.nan]).apply(pd.to_datetime)
Out[1]:
0 2011-01-01 00:00:00
1 NaT
dtype: datetime64[ns]
In [2]: Series(['00:00:01', np.nan]).apply(pd.to_timedelta)
AssertionError: Invalid type for timedelta scalar: <type 'float'>
```
May not be a trivial fix. So far I have seen... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5438 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5438/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5438/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5438/events | https://github.com/pandas-dev/pandas/pull/5438 | 22,097,629 | MDExOlB1bGxSZXF1ZXN0OTY2NzAxOA== | 5,438 | BUG: pd.to_timedelta handles missing data | {
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"followers_url": "https://api.github.com/users/wesm... | 20 | 2013-11-05T03:27:15Z | 2014-06-24T21:15:32Z | 2013-11-06T23:51:20Z | CONTRIBUTOR | null | closes #5437
**Updated**: Mostly following @jreback's suggestion, but we need `np.timedelta64('NaT')`, not `pd.tslib.iNaT`, because numpy cannot cast `np.datetime64('NaT')` as `np.timedelta64` type, and throws an `AssertionError`.
```
In [1]: pd.to_timedelta(Series(['00:00:01', '00:00:02']))
Out[1]:
0 00:00:01
1 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5439 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5439/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5439/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5439/events | https://github.com/pandas-dev/pandas/pull/5439 | 22,114,568 | MDExOlB1bGxSZXF1ZXN0OTY3NTg5MQ== | 5,439 | ENH: Always do true division on Python 2.X | {
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Note: this version actually forces `a / b` to always do truediv as well. It's
less complicated to maintain if we do it that way, but it's also possible to
have this `a / b` use div and `a.div(b)` use truediv, just might be strange.
This is definitely different from numpy behavior.
We also may need to add... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5440 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5440/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5440/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5440/events | https://github.com/pandas-dev/pandas/issues/5440 | 22,116,607 | MDU6SXNzdWUyMjExNjYwNw== | 5,440 | resampling closed='left' incorrect ? | {
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... | 3 | 2013-11-05T12:31:45Z | 2021-04-11T03:49:51Z | null | NONE | null | Hi,
Coming back to issue #2665, I'm still not convinced that the closed-argument of the resampling function does what it should.
When resampling daily to monthly values with closed = 'left', the closed argument should relate to the actual time the months change, but instead it seems to refer to the time 24 hours ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5441 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5441/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5441/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5441/events | https://github.com/pandas-dev/pandas/issues/5441 | 22,124,146 | MDU6SXNzdWUyMjEyNDE0Ng== | 5,441 | HDFStore.select slowed by decode even when using columns= | {
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"followers_url": "https://api.github.com/users/wesm... | 6 | 2013-11-05T14:45:22Z | 2013-11-06T15:22:59Z | 2013-11-06T13:59:15Z | CONTRIBUTOR | null | I realized when profiling a slow select (200% more wall-time as direct pytables call and high memory usage) that most of the time is spend inside bytes.decode called by [_unconvert_strings_array](https://github.com/pydata/pandas/blob/master/pandas/io/pytables.py#L3966), even when selecting only int64 columns. It seems... | {
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"f... | 8 | 2013-11-05T16:16:29Z | 2016-05-04T13:04:00Z | 2016-05-04T13:04:00Z | NONE | null | In our project Zipline, https://github.com/quantopian/zipline/, we consume time series data one bar at a time. We provide support for calculations that are performed over a fixed length, e.g. over the last 15 days of data. The data which those calculations are performed over are updated with the most recent bar as it c... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5443 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5443/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5443/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5443/events | https://github.com/pandas-dev/pandas/issues/5443 | 22,142,844 | MDU6SXNzdWUyMjE0Mjg0NA== | 5,443 | BUG: isnull of an object array failing when NaT | {
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... | closed | false | null | [] | {
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"closed_issues": 314,
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"followers_url": "https://api.github.com/users/... | 0 | 2013-11-05T19:07:26Z | 2014-01-23T03:55:50Z | 2014-01-06T23:44:29Z | CONTRIBUTOR | null | ```
In [1]: pd.isnull(np.array([pd.NaT]))
Out[1]: array([False], dtype=bool)
```
this should be true
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https://api.github.com/repos/pandas-dev/pandas/issues/5444 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5444/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5444/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5444/events | https://github.com/pandas-dev/pandas/issues/5444 | 22,153,673 | MDU6SXNzdWUyMjE1MzY3Mw== | 5,444 | Panel4D can not be saved to hdf using the .to_hdf call | {
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import pandas as pd, numpy
print pd.__version__
with pd.get_store('test.h5') as store:
df = pd.Panel4D(data=numpy.random.randn(2,3,4,5))
store.append('test',df)
print store
df.to_hdf('test2.h5','test')
```
Output:
```
0.12.0
<class 'pandas.io.pytables.HDFStore'>
File path: test.h5
/test wide_t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5445 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5445/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5445/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5445/events | https://github.com/pandas-dev/pandas/issues/5445 | 22,158,564 | MDU6SXNzdWUyMjE1ODU2NA== | 5,445 | Use future division import in all files. | {
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... | 3 | 2013-11-05T22:57:26Z | 2017-06-01T20:13:30Z | 2017-06-01T20:13:30Z | CONTRIBUTOR | null | Now that all division on NDFrame is truediv, we should add the division future import to most/all files (alongside print) to avoid any inconsistencies. At least on the pure Python parts. Nor sure about Cython.
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https://api.github.com/repos/pandas-dev/pandas/issues/5446 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5446/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5446/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5446/events | https://github.com/pandas-dev/pandas/pull/5446 | 22,168,859 | MDExOlB1bGxSZXF1ZXN0OTcwNTUxMg== | 5,446 | PERF/ENH: Use xlsxwriter by default (and then fall back on openpyxl). | {
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reasonable to assume that if you have it installed, you want xlsxwriter.
Plus, it has better performance characteristics in general (esp. in
terms of memory usage)
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https://api.github.com/repos/pandas-dev/pandas/issues/5447 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5447/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5447/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5447/events | https://github.com/pandas-dev/pandas/pull/5447 | 22,185,165 | MDExOlB1bGxSZXF1ZXN0OTcxMzA5Mw== | 5,447 | DOC: fix build error in to_latex and release notes | {
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And in the same time, fixes a build error in the newly added docs on `truediv` in the release notes.
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https://api.github.com/repos/pandas-dev/pandas/issues/5448 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5448/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5448/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5448/events | https://github.com/pandas-dev/pandas/pull/5448 | 22,191,564 | MDExOlB1bGxSZXF1ZXN0OTcxNjQyOQ== | 5,448 | PERF: Fixed decoding perf issue on py3 (GH5441) | {
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pretty sure this is fixed with xlsxwriter...maybe need a warning with other writers?
http://stackoverflow.com/questions/19812934/pandas-dataframe-concat-and-to-excel-output
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https://api.github.com/repos/pandas-dev/pandas/issues/5450 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5450/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5450/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5450/events | https://github.com/pandas-dev/pandas/pull/5450 | 22,196,016 | MDExOlB1bGxSZXF1ZXN0OTcxODc1NA== | 5,450 | DOC: remove docstring of flags attribute during doc building process (#5331) | {
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This removes the docstring of all attributes with the name `flags` during the doc building process.
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https://api.github.com/repos/pandas-dev/pandas/issues/5451 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5451/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5451/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5451/events | https://github.com/pandas-dev/pandas/issues/5451 | 22,197,254 | MDU6SXNzdWUyMjE5NzI1NA== | 5,451 | Simple way of adding/removing column to DataFrame Not in Place | {
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I would suggest something like:
```
df_new = df.alter(new_col_name=existing_series)
```
where alter would wake one or more columns:
```
df_new = df.alter(
new_col_name1=existing_series1,
new_col_name2=existing... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5452 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5452/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5452/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5452/events | https://github.com/pandas-dev/pandas/pull/5452 | 22,197,938 | MDExOlB1bGxSZXF1ZXN0OTcxOTgzNA== | 5,452 | add optional default value to GroupBy.get_group | {
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"followers_url": "https://api.github.com/users/jr... | 59 | 2013-11-06T14:38:00Z | 2015-01-18T21:39:57Z | 2015-01-18T21:39:57Z | CONTRIBUTOR | null | I've used a try except block as opposed to and if else (below) to keep the non-default code path fast. What I didn't do:
```
if default is None :
inds = self.indices[name]
else :
inds = self.indices.get(name, default)
```
Here is an example use case:
```
def foo(df, keys) :
g = df.groupby('key')
for... | {
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"labels_url": "htt... | 4 | 2013-11-06T15:15:53Z | 2014-06-12T21:07:21Z | 2014-05-01T17:50:35Z | CONTRIBUTOR | null | After using the `asfreq` method to change the frequency of a time-series DataFrame from `None` to something e.g. `15Min` the cursor position in matplotlib graphs of that DataFrame is no longer correct (usually shows a datetime just after the unix epoch). The following demonstrates this (NB dt in df1 is not a constant)... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5455 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5455/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5455/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5455/events | https://github.com/pandas-dev/pandas/issues/5455 | 22,209,299 | MDU6SXNzdWUyMjIwOTI5OQ== | 5,455 | Allow labels argument to DataFrame.drop to be a function | {
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For example:
```
df = pd.DataFrame({'a':[1],'B':[2],'c':[3]})
df.drop(labels=lambda x:x.lower()==x, axis=1)
```
would drop columns 'a' and 'c'
This would be consistent with `DataFrame.rename... | {
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... | 5 | 2013-11-06T21:32:28Z | 2019-10-21T19:52:14Z | null | NONE | null | Add more explicit docs / work-around for dealing with groupby and NA groups
(see comments)
Changelog: 07.Nov.2013: Add line to example below to preprocess table content.
I expect the following behavior: A `DataFrame.groupby` splits the dataframe/table into subtables according to the grouping-condition. A column name... | {
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"followers_url": "https://api.github.com/users/... | 1 | 2013-11-06T22:22:46Z | 2013-11-21T13:29:16Z | 2013-11-21T13:29:16Z | CONTRIBUTOR | null | @jreback is about to introduce this with the warn on setting with copy PR. We should use it in pandas internals - will be cleaner, especially when debugging. https://github.com/pydata/pandas/commit/7aa7880f#diff-1e746a348e7db9596f3d053134d00e74R515
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https://api.github.com/repos/pandas-dev/pandas/issues/5458 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5458/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5458/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5458/events | https://github.com/pandas-dev/pandas/issues/5458 | 22,233,673 | MDU6SXNzdWUyMjIzMzY3Mw== | 5,458 | BUG: Series.apply(to_timedelta) returns object-type Series. | {
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"id": 31404521,
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{
"color": "531... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/... | 0 | 2013-11-06T23:30:00Z | 2014-02-04T15:53:19Z | 2014-01-20T23:37:17Z | CONTRIBUTOR | null | _For later (post 0.13)..._
Good:
```
In [1]: Series(['2013-01-05']).apply(pd.to_datetime)
Out[1]:
0 2013-01-05 00:00:00
dtype: datetime64[ns]
```
Bad:
```
In [2]: Series(['00:00:01']).apply(pd.to_timedelta)
Out[2]:
0 1000000000 nanoseconds
dtype: object
```
This problem turned up in #5438 , resovling #5437 . ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5459 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5459/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5459/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5459/events | https://github.com/pandas-dev/pandas/pull/5459 | 22,239,195 | MDExOlB1bGxSZXF1ZXN0OTc0MzQzNw== | 5,459 | DOC: add basic documentation to some of the GroupBy properties and methods | {
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"followers_url": "https://api.github.com/users/wesm... | 15 | 2013-11-07T01:45:06Z | 2014-06-14T22:38:30Z | 2013-11-27T20:00:21Z | CONTRIBUTOR | null | I added some simple documentation to the GroupBy and Grouper classes
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https://api.github.com/repos/pandas-dev/pandas/issues/5460 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5460/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5460/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5460/events | https://github.com/pandas-dev/pandas/issues/5460 | 22,240,096 | MDU6SXNzdWUyMjI0MDA5Ng== | 5,460 | DOC: Clarify 'public-ish' API for packages using pandas. | {
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"color": "AD... | closed | false | null | [] | {
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"f... | 6 | 2013-11-07T02:12:35Z | 2021-04-11T03:52:44Z | 2021-04-11T03:52:44Z | CONTRIBUTOR | null | I've been contributing a little bit to GeoPandas / working on some of my own custom code using pandas that I want to share with others and I realized that I wasn't sure what is and is not part of the public API for pandas.
Here's what I have in my head:
Definitely public:
- anything in pandas toplevel namespace (exce... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5461 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5461/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5461/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5461/events | https://github.com/pandas-dev/pandas/issues/5461 | 22,241,197 | MDU6SXNzdWUyMjI0MTE5Nw== | 5,461 | DatetimeIndex.normalize doesn't clear ns field | {
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... | closed | false | null | [] | null | 10 | 2013-11-07T02:48:08Z | 2013-11-08T12:46:51Z | 2013-11-08T12:46:51Z | NONE | null | ```
import pandas as pd
import numpy as np
didx = pd.DatetimeIndex(np.array([1380585623454345752, 1380585612343234312]).astype("datetime64[ns]"))
didx.normalize()
```
the output is:
```
<class 'pandas.tseries.index.DatetimeIndex'>
[2013-10-01 00:00:00.000000752, 2013-10-01 00:00:00.000000312]
Length: 2, Freq: None, T... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5462 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5462/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5462/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5462/events | https://github.com/pandas-dev/pandas/pull/5462 | 22,264,688 | MDExOlB1bGxSZXF1ZXN0OTc1NjA1Ng== | 5,462 | PERF: performance improvements on isnull/notnull for large pandas objects | {
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In [1]: df = DataFrame(np.random.randn(1000,1000))
In [2]: %timeit df.apply(pd.isnull)
10 loops, best of 3: 121 ms per loop
In [3]: %timeit pd.isnull(df)
100 loops, best of 3: 3.15 ms per loop
```
from 0.12
```
In [2]: %timeit df.apply(pd.isnull)
10 loops, best of 3: 74.3 ms per loop
In [3]: %timeit pd.isnull(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5463 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5463/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5463/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5463/events | https://github.com/pandas-dev/pandas/issues/5463 | 22,289,925 | MDU6SXNzdWUyMjI4OTkyNQ== | 5,463 | PyTables: invalid combinate of [values_axes] on appending data | {
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> File "/opt/epd/7.3-2_pandas0.11/lib/python2.7/site-packages/pandas/io/pytables.py", line 610, in append
> self._write_to_group(key, value, table=True, append=True, *_kwargs)
> File "/opt/epd/7.3-2_pandas0.11/lib/python2.7/site-packages/pandas/io/p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5464 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5464/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5464/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5464/events | https://github.com/pandas-dev/pandas/issues/5464 | 22,311,184 | MDU6SXNzdWUyMjMxMTE4NA== | 5,464 | Error setting locale in test suite | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2013-11-08T02:07:55Z | 2013-11-08T18:19:17Z | 2013-11-08T18:19:17Z | CONTRIBUTOR | null | This is on the VM running pandas windows builds.
Windows XP
Python 2.7 32-bit
```
ERROR: test suite for <class 'pandas.io.tests.test_data.TestGoogle'>
----------------------------------------------------------------------
Traceback (most recent call last):
File "c:\python27\x32\lib\site-packages\nose\suite.py", line... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5465 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5465/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5465/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5465/events | https://github.com/pandas-dev/pandas/issues/5465 | 22,311,244 | MDU6SXNzdWUyMjMxMTI0NA== | 5,465 | Error in test suite for timedelta operations | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2013-11-08T02:09:25Z | 2013-11-08T18:18:25Z | 2013-11-08T18:18:25Z | CONTRIBUTOR | null | This is on the VM running pandas windows builds.
Windows XP
Python 2.7 32-bit
numpy 1.7.1
```
======================================================================
ERROR: test_timedelta_ops_with_missing_values (pandas.tseries.tests.test_timedeltas.TestTimedeltas)
------------------------------------------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5466 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5466/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5466/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5466/events | https://github.com/pandas-dev/pandas/issues/5466 | 22,311,312 | MDU6SXNzdWUyMjMxMTMxMg== | 5,466 | Error in test suite for indexing | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2013-11-08T02:11:07Z | 2013-11-08T18:19:00Z | 2013-11-08T18:18:25Z | CONTRIBUTOR | null | This is on the VM running pandas windows builds.
Windows XP
Python 2.7 32-bit
numpy 1.7.1
```
======================================================================
ERROR: test_multiindex_assignment (pandas.tests.test_indexing.TestIndexing)
----------------------------------------------------------------------
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"id": 5... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2013-11-08T02:14:43Z | 2013-11-08T18:18:25Z | 2013-11-08T18:18:25Z | CONTRIBUTOR | null | This is on the VM running pandas windows builds.
Windows XP
Python 2.7 32-bit
numpy 1.7.1
```
======================================================================
FAIL: pandas.computation.tests.test_eval.TestAlignment.test_basic_series_frame_alignment('numexpr', 'python')
--------------------------------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5468 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5468/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5468/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5468/events | https://github.com/pandas-dev/pandas/issues/5468 | 22,311,494 | MDU6SXNzdWUyMjMxMTQ5NA== | 5,468 | Error in test suite for Series.mode | {
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Windows XP
Python 2.7 32-bit
numpy 1.7.1
```
======================================================================
FAIL: test_mode (pandas.tests.test_series.TestSeries)
----------------------------------------------------------------------
Traceback (most recent call l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5469 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5469/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5469/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5469/events | https://github.com/pandas-dev/pandas/pull/5469 | 22,315,155 | MDExOlB1bGxSZXF1ZXN0OTc4NDE1Mg== | 5,469 | TST: Fix test case to use int64 and explicit float | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5470 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5470/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5470/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5470/events | https://github.com/pandas-dev/pandas/issues/5470 | 22,321,632 | MDU6SXNzdWUyMjMyMTYzMg== | 5,470 | BUG: SparseDataFrame does not allow single value data | {
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"created_at": "2013-01-06T03:02:01Z",
"creator": {
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"f... | 3 | 2013-11-08T07:45:06Z | 2019-09-18T14:02:17Z | 2019-09-18T14:02:17Z | NONE | null | You can create a normal DataFrame with, e.g., `pandas.DataFrame(0, index=[1, 2, 3], columns=["A", "B", "C"])`. However, this fails with a SparseDataFrame:
```
>>> x = pandas.SparseDataFrame(0, index=[1, 2, 3], columns=["A", "B", "C"])
Traceback (most recent call last):
File "<pyshell#97>", line 1, in <module>
x... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5471 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5471/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5471/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5471/events | https://github.com/pandas-dev/pandas/pull/5471 | 22,324,429 | MDExOlB1bGxSZXF1ZXN0OTc4ODExNA== | 5,471 | BUG: bool(NaT) was True | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5472 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5472/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5472/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5472/events | https://github.com/pandas-dev/pandas/pull/5472 | 22,333,055 | MDExOlB1bGxSZXF1ZXN0OTc5MjcxOQ== | 5,472 | BUG: DatetimeIndex.normalize now accounts for nanoseconds (#5461). | {
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datetime64(ns) uses the dts->ps which was not being set to zero in the
normalize function.
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https://api.github.com/repos/pandas-dev/pandas/issues/5473 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5473/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5473/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5473/events | https://github.com/pandas-dev/pandas/issues/5473 | 22,344,911 | MDU6SXNzdWUyMjM0NDkxMQ== | 5,473 | Test suite throws lots of DateParseErrors | {
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I built pandas from source on [python 2.7, numpy 1.8, dateutil 2.2] using
```
python setup.py build_ext --inplace
```
When running the test suite,
```
nosetests pandas
```
I encounter lots of DateParseErrors. The error message is basically always the same, so here is an example one:
<pre>
===========... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5474 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5474/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5474/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5474/events | https://github.com/pandas-dev/pandas/pull/5474 | 22,345,656 | MDExOlB1bGxSZXF1ZXN0OTc5OTgyNQ== | 5,474 | TST: win32 fixes | {
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"followers_url": "https://api.github.com/users/wesm... | 4 | 2013-11-08T16:04:19Z | 2014-07-16T08:39:49Z | 2013-11-08T18:18:25Z | CONTRIBUTOR | null | TST: test_indexing dtype comps, closes #5466
TST don't compare invalid indices in eval operations, closes #5467
TST: invalid assignment for np.timedelta64 closes #5465
TST: skip locale checks on windows cloes #5464
TST: dtype comp issue on windows in test_indexing (GH5466)
TST: skip test_pow on windows (GH5467)
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https://api.github.com/repos/pandas-dev/pandas/issues/5475 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5475/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5475/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5475/events | https://github.com/pandas-dev/pandas/issues/5475 | 22,365,095 | MDU6SXNzdWUyMjM2NTA5NQ== | 5,475 | missing _is_copy causes strangeness | {
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"default": false,
"description": "Related to indexing on s... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2013-11-08T21:26:41Z | 2013-11-09T01:56:27Z | 2013-11-09T01:56:27Z | CONTRIBUTOR | null | Note the duplication of the assignment is not a copy/paste error-- the first one works, the second one fails, presumably because a different path is taken if the column already exists than if it doesn't.
```
>>> pd.__version__
'0.12.0-1081-ge684bdc'
>>> df = pd.DataFrame({"A": [1,2]})
>>> df._is_copy
False
>>> df.to_p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5476 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5476/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5476/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5476/events | https://github.com/pandas-dev/pandas/issues/5476 | 22,368,149 | MDU6SXNzdWUyMjM2ODE0OQ== | 5,476 | BUG: NaN in DataFame column causes select with condition to always return empty | {
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... | closed | false | null | [] | null | 6 | 2013-11-08T22:22:21Z | 2013-12-03T10:23:04Z | 2013-11-09T01:59:57Z | NONE | null | ```
import pandas as pd, numpy
r = numpy.array([
[1,2],
[2,1],
[1,2],
[2,1]],dtype=float)
r[0,1] = numpy.nan
df = pd.DataFrame(data=r,columns=['s1','s2'])
print 'Original:'
print df
print 'Selected:'
print df[df.s2==1]
# As expected
# s1 s2
#1 2 1
#3 2 1
df.to_hdf('float_bug.h5','data',table=True,data_co... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5477 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5477/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5477/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5477/events | https://github.com/pandas-dev/pandas/pull/5477 | 22,375,385 | MDExOlB1bGxSZXF1ZXN0OTgxNjk0Nw== | 5,477 | API: make sure _is_copy on NDFrame is always available (GH5475) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5478 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5478/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5478/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5478/events | https://github.com/pandas-dev/pandas/pull/5478 | 22,387,961 | MDExOlB1bGxSZXF1ZXN0OTgyMTI0OQ== | 5,478 | VIS/ENH Hexbin plot | {
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``` python
In [1]: df = pd.DataFrame(np.random.randn(1000, 2))
In [2]: df.plot(kind='hexbin', x=0, y=1)
Out[2]: <matplotlib.axes.AxesSubplot at 0x10eb76e10>
```
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"labels_url": "htt... | 6 | 2013-11-09T21:37:43Z | 2014-01-31T08:02:53Z | 2014-01-31T08:02:53Z | CONTRIBUTOR | null | I followed [this](http://pandas.pydata.org/developers.html#contributing-to-the-documentation) advice but on `python make.py html` I get
```
Running Sphinx v1.2b3
Exception occurred while building, starting debugger:
Traceback (most recent call last):
File "/usr/local/lib/python3.3/site-packages/sphinx/cmdline.py", l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5480 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5480/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5480/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5480/events | https://github.com/pandas-dev/pandas/issues/5480 | 22,399,081 | MDU6SXNzdWUyMjM5OTA4MQ== | 5,480 | BUG: value_counts / shift not in groupby dispatch whitelist (0.12-dev) | {
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"followers_url": "https://api.github.com/users/wesm... | 19 | 2013-11-10T04:00:11Z | 2013-12-28T22:18:05Z | 2013-12-07T14:16:56Z | CONTRIBUTOR | null | Copying comment from #4887 to a new issue for discussion purposes:
While testing pandas-master, hit a method not in the new groupby dispatch whitelist: `value_counts` (on a `SeriesGroupBy` object). Another possible addition: `shift`, as used in this [SO answer](http://stackoverflow.com/a/17406083/243434).
Tried to g... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5481 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5481/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5481/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5481/events | https://github.com/pandas-dev/pandas/issues/5481 | 22,411,115 | MDU6SXNzdWUyMjQxMTExNQ== | 5,481 | PERF: 6x perf hit from using numexpr | {
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"followers_url": "https://api.github.com/users/wesm... | 7 | 2013-11-10T16:18:17Z | 2013-11-10T18:47:39Z | 2013-11-10T18:47:39Z | CONTRIBUTOR | null | 1 million x 3 dataframe, using numexpr takes 142ms to do multiplication, with numexpr disabled, takes 21.6ms. I'm going to investigate, but would be helpful to know if you can reproduce this anywhere else.
```
In [10]: df = pd.DataFrame({"A": np.arange(1000000), "B": np.arange(1000000, 0, -1), "C": np.random.randn(100... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5482 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5482/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5482/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5482/events | https://github.com/pandas-dev/pandas/pull/5482 | 22,412,515 | MDExOlB1bGxSZXF1ZXN0OTgyOTQxMA== | 5,482 | PERF: perf regression with mixed-type ops using numexpr (GH5481) | {
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"followers_url": "https://api.github.com/users/wesm... | 7 | 2013-11-10T17:44:26Z | 2014-06-18T10:04:21Z | 2013-11-10T18:47:39Z | CONTRIBUTOR | null | closes #5481
BUG: non-unique ops not aligning correctly
these are bascially a trivial op in numpy, so numexpr is slightly slower (but the
the dtype inference issue is fixed). Essentially the recreation of an int64 ndarray had to check if its a datetime-like. In this case just passing in the dtype on the reconstructed... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5483 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5483/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5483/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5483/events | https://github.com/pandas-dev/pandas/issues/5483 | 22,412,912 | MDU6SXNzdWUyMjQxMjkxMg== | 5,483 | cut with np.inf gives TypeError | {
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import pandas as pd
import numpy as np
arr = np.random.randn(20)
factor = pd.cut(arr, [-np.inf, 0, np.inf])
```
gives this error:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/weitzenfeld/anaconda/lib/python2.7/site-packages/pandas/tools/tile.py", line 102, in cut
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"f... | 2 | 2013-11-10T18:07:08Z | 2018-10-25T03:22:33Z | 2018-10-25T03:22:33Z | CONTRIBUTOR | null | related #5482 / #5481
in theory an op like:
`df * df2` can be done block-based rather than column-by-column, so for large numbers of columns would see nice speedups. Though, passing to `pd.eval` is almost always faster because its passed to numexpr (at the cost of an upcasted dtype on the way back)
the 2 frames are ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5485 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5485/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5485/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5485/events | https://github.com/pandas-dev/pandas/issues/5485 | 22,413,258 | MDU6SXNzdWUyMjQxMzI1OA== | 5,485 | PERF: pd.eval when using mixed types | {
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"f... | 2 | 2013-11-10T18:10:28Z | 2021-04-11T03:53:33Z | null | CONTRIBUTOR | null | ```
In [11]: df = pd.DataFrame({"A": np.arange(1000000), "B": np.arange(1000000, 0, -1), "C": np.random.randn(1000000)})
In [13]: %timeit pd.eval('df*df')
1 loops, best of 3: 635 ms per loop
In [14]: df = df.astype(float)
In [15]: %timeit pd.eval('df*df')
100 loops, best of 3: 5.87 ms per loop
```
the time is all i... | {
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#4901
1. Path resolution was broken, so running the script outside the pandas root directory didn't work.
2. The use of `subprocess` to invoke the script from the source tree relied on system python,
ignoring the interpreter version actually used to invoke the scripts. Travis was unaffected since the system py... | {
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"followers_url": "https://api.github.com/users/jorisva... | 17 | 2013-11-10T22:20:49Z | 2015-04-30T06:40:27Z | 2015-04-29T06:05:20Z | NONE | null | I'd like to propose `read_netcdf` ([netCDF (Network Common Data Format)](http://www.unidata.ucar.edu/software/netcdf/)) a new Pandas I/O api feature with a similar top level interface as the other reader functions. This format is widely used in the scientific community. Furthermore, netCDF4 is implemented on top of ... | {
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```
end = datetime.datetime(2013, 01, 27)
```
the `01` int literal is not valid python3.
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I want to incorporate this into pandas - it would be a great improvement and a light dep for the libra... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5490 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5490/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5490/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5490/events | https://github.com/pandas-dev/pandas/issues/5490 | 22,431,953 | MDU6SXNzdWUyMjQzMTk1Mw== | 5,490 | PERF: speed up pd.to_datetime and co. by extracting dt format from data and using strptime to parse | {
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"November 1, 2013"
Series length was about 500,000
A)
running pd.to_datetime(s) takes just over a minute.
B)
running pd.to_datetime(s, format="%B %d, %Y") takes about 7 seconds!
My suggestion is a way to make case A (where user doesn't specify the format type) take abou... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5491 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5491/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5491/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5491/events | https://github.com/pandas-dev/pandas/issues/5491 | 22,447,122 | MDU6SXNzdWUyMjQ0NzEyMg== | 5,491 | Inconsistency between min and max in apply with multiindex | {
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```
>>> df = pd.DataFrame({'A': [1, -1, 2, -2]... | {
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Let me know if you want this for .13 or .14 and I'll fill in the release notes appropriately.
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This works:
import pandas as pd
import numpy as np
df = pd.DataFrame({'key1': ['a','a','n','a', 'a'],
'data1': np.random.randn(5),
'data2': np.random.randn(5)})
def x(df):
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https://api.github.com/repos/pandas-dev/pandas/issues/5494 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5494/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5494/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5494/events | https://github.com/pandas-dev/pandas/issues/5494 | 22,468,657 | MDU6SXNzdWUyMjQ2ODY1Nw== | 5,494 | ENH: make contiguous groupby easier | {
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"followers_url": "https://api.github.com/users/jorisva... | 5 | 2013-11-11T19:00:23Z | 2018-07-06T22:34:47Z | 2018-07-06T22:34:37Z | CONTRIBUTOR | null | `itertools.groupby` groups things contiguously-- great for run length encoding, not so great for partitioning. This necessitates the `groupby(sorted(items,key=keyfn), keyfn)` dance if you want to separate it. That's not always what you want either, so you wind up writing
```
def partition(seq, keyfn):
d = {}
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"followers_url": "https://api.github.com/users/... | 1 | 2013-11-12T08:25:07Z | 2014-01-07T18:59:02Z | 2013-12-30T20:55:38Z | NONE | null | When you download the current master as zip archive from github.com, assigning a version number fails (empty string). As a consequence, packages depending on pandas (e.g. statsmodels) will fail to build as well.
I assume, the reason is the following: The version number is determined using git, but since the downloaded ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5496 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5496/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5496/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5496/events | https://github.com/pandas-dev/pandas/issues/5496 | 22,512,555 | MDU6SXNzdWUyMjUxMjU1NQ== | 5,496 | DateParseError after upgrading matplotlib and others dependancies | {
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using pandas 0.12, after upgrading matplotlib from 1.2.0 to 1.3.1, which in turn have upgraded numpy python-dateutil tornado pyparsing nose six, I can't now slice a datetime based dataframe:
In [16]: pm
Out[16]:
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 1584 entries, 2013-09-01 00:00:00 to 2013-11-0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5497 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5497/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5497/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5497/events | https://github.com/pandas-dev/pandas/issues/5497 | 22,519,675 | MDU6SXNzdWUyMjUxOTY3NQ== | 5,497 | scatter_matrix: coordinate misalignment among diagonal and off-diagonal plots | {
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"followers_url": "https://api.github.com/users/... | 3 | 2013-11-12T13:56:37Z | 2014-01-21T13:30:59Z | 2014-01-21T13:30:59Z | CONTRIBUTOR | null | I make extensive use of `scatter_matrix` and I find misalignments in the coordinates of the scatter plots (off-diagonal) and the histograms (on-diagonal) which seem undesirable to me.
Consider the picture 
).
In thi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5498 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5498/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5498/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5498/events | https://github.com/pandas-dev/pandas/pull/5498 | 22,527,334 | MDExOlB1bGxSZXF1ZXN0OTg4NTQ1OQ== | 5,498 | PERF: msgpack encoding changes to use to/from string for speed boosts | {
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"followers_url": "https://api.github.com/users/wesm... | 7 | 2013-11-12T15:39:50Z | 2021-10-26T16:20:50Z | 2013-11-13T14:13:45Z | CONTRIBUTOR | null | API: disable sparse structure encodings and unicode indexes
```
-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
packers_read_pa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5499 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5499/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5499/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5499/events | https://github.com/pandas-dev/pandas/pull/5499 | 22,535,750 | MDExOlB1bGxSZXF1ZXN0OTg4OTk0Nw== | 5,499 | API/ENH: pass thru store creation arguments for HDFStore; can be used to support in-memory stores | {
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https://api.github.com/repos/pandas-dev/pandas/issues/5500 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/5500/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/5500/comments | https://api.github.com/repos/pandas-dev/pandas/issues/5500/events | https://github.com/pandas-dev/pandas/issues/5500 | 22,537,505 | MDU6SXNzdWUyMjUzNzUwNQ== | 5,500 | read_csv() & EOF character in string cause parsing issue | {
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"... | closed | false | null | [] | {
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Further, the line stated in the error messag... | {
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