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https://api.github.com/repos/pandas-dev/pandas/issues/4501 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4501/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4501/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4501/events | https://github.com/pandas-dev/pandas/issues/4501 | 17,750,835 | MDU6SXNzdWUxNzc1MDgzNQ== | 4,501 | tab complete lurking groupby methods | {
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see related issue #4500
see [this SO question](http://stackoverflow.com/questions/18104704/counting-unique-values-in-a-pandas-grouped-object) for an example (also linked to in #4500 )
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https://api.github.com/repos/pandas-dev/pandas/issues/4502 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4502/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4502/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4502/events | https://github.com/pandas-dev/pandas/pull/4502 | 17,754,969 | MDExOlB1bGxSZXF1ZXN0NzQ0OTM3NA== | 4,502 | ENH add bins argument to value_counts | {
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Also, adds arguments present in top-level function to the Series
method (sort and ascending).
Note: this only works with numeric data (it raises a TypeError if there was a TypeError problem in cut, however perhaps cut should raise a more descirptive error...)
```
In [1]: s = pd.Series(np.random.randn(100... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4503 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4503/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4503/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4503/events | https://github.com/pandas-dev/pandas/pull/4503 | 17,756,277 | MDExOlB1bGxSZXF1ZXN0NzQ1MDA3MQ== | 4,503 | TST: provide tests for memory_cycles | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2013-08-07T15:54:39Z | 2014-06-14T06:24:45Z | 2013-08-22T15:27:30Z | CONTRIBUTOR | null | related to #4491
provides an assert_memory_is_clean to test a function for leaking memory
provides a test that the current series does not leak memory
and properly cleans up
tests that an index generally populates the engine mapping (but not always
e.g. asof)
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https://api.github.com/repos/pandas-dev/pandas/issues/4504 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4504/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4504/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4504/events | https://github.com/pandas-dev/pandas/issues/4504 | 17,757,793 | MDU6SXNzdWUxNzc1Nzc5Mw== | 4,504 | read_hdf() requires write permission | {
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I have added the ability for both the C and Python CSV parsers to ignore commented lines (i.e., lines beginning with a comment character). Currently the C parser preserves commented lines as empty lines (all NaN), while the Python parser ignores them all together.
In addition, I fixed a small related pr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4506 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4506/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4506/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4506/events | https://github.com/pandas-dev/pandas/issues/4506 | 17,766,325 | MDU6SXNzdWUxNzc2NjMyNQ== | 4,506 | cumsum(skipna=True) bug if last element is NaN | {
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http://pandas.pydata.org/pandas-docs/stable/basics.html#descriptive-statistics
For the DataFrame df in the example:
```
In [39]: df
one three two
a -0.701368 NaN -0.087103
b 0.109333 -0.354359 0.637674
c -0.231617 -0.148387 -0.002666
d NaN -0.167407 0.1... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4507 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4507/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4507/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4507/events | https://github.com/pandas-dev/pandas/pull/4507 | 17,767,972 | MDExOlB1bGxSZXF1ZXN0NzQ1NjMwNw== | 4,507 | BUG/ER: various panel indexing fixes | {
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- BUG: closes #3830, panel assignment using loc with a transpose frame did not work
- BUG: closes #4016 fix panel slicing issue that was returning an object that should not have be a reduction in n... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4508 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4508/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4508/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4508/events | https://github.com/pandas-dev/pandas/issues/4508 | 17,769,602 | MDU6SXNzdWUxNzc2OTYwMg== | 4,508 | .ix[] inconsistently assigns right hand side | {
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In [1]: import pandas as pd
In [2]: df = pd.DataFrame({'a':[1,2,3],'b':[0,1,2]})
In [3]: df.ix[[0,2,],'b'] = [100,-100] # Works as intended
In [4]: print df
a b
0 1 100
1 2 1
2 3 -100
In [6]: df = pd.DataFrame({'a':range(4)})
In [7]: df['b']=pd.np.nan
In [8]: ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4510 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4510/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4510/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4510/events | https://github.com/pandas-dev/pandas/issues/4510 | 17,781,572 | MDU6SXNzdWUxNzc4MTU3Mg== | 4,510 | write percentages to excel file | {
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this is possible with `to_csv`, i think this should be possible with `to_excel` though I'm not sure
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https://api.github.com/repos/pandas-dev/pandas/issues/4511 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4511/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4511/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4511/events | https://github.com/pandas-dev/pandas/issues/4511 | 17,785,485 | MDU6SXNzdWUxNzc4NTQ4NQ== | 4,511 | ENH: Support for "52–53-week fiscal year" / "4–4–5 calendar" | {
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Certain companies, for example Green Mountain Coffee Roasters, Inc. (GMCR) use this calendar. See for example: http://files.shareholder.com/downloads/GMCR/1456137416x0x436353/9E2D04D9-79DE-4C08-A7C6-7B161E23E586/gmcr_2010_... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4512 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4512/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4512/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4512/events | https://github.com/pandas-dev/pandas/issues/4512 | 17,785,745 | MDU6SXNzdWUxNzc4NTc0NQ== | 4,512 | Provide more intelligent way of setting skipfooter in read_csv | {
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"f... | 0 | 2013-08-08T03:03:05Z | 2021-04-11T02:58:34Z | null | CONTRIBUTOR | null | See for example: http://www.datazoa.com/publish/export.asp?hash=vg6p5mBl1v&uid=dzadmin&a=exportcsv, http://www.datazoa.com/publish/export.asp?hash=yjPceG6fHL&uid=dzadmin&a=exportcsv or the http://pastebin.com/S2NqhFq0.
In all cases, it is important to set `skipfooter` in order to correctly parse the CSV.
I current se... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4513 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4513/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4513/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4513/events | https://github.com/pandas-dev/pandas/pull/4513 | 17,802,987 | MDExOlB1bGxSZXF1ZXN0NzQ3NDA4OQ== | 4,513 | BUG: read_hdf was not respecting a passed mode (GH4504) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4514 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4514/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4514/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4514/events | https://github.com/pandas-dev/pandas/issues/4514 | 17,813,944 | MDU6SXNzdWUxNzgxMzk0NA== | 4,514 | column-wise fillna with Series/dict NotImplemented | {
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... | 7 | 2013-08-08T15:48:55Z | 2019-10-21T19:34:16Z | null | CONTRIBUTOR | null | As per discussion on [this SO question](http://stackoverflow.com/questions/18127160/pandas-fillna-output-still-has-nan-values) is NotImplementedError.
Solution/workaround is to transpose do transpose? This is used elsewhere in DataFrame.fillna method. just raise if inplace?
cc @cpcloud
```
In [9]: df = pd.DataFrame... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4515 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4515/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4515/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4515/events | https://github.com/pandas-dev/pandas/pull/4515 | 17,824,191 | MDExOlB1bGxSZXF1ZXN0NzQ4NTQ1OA== | 4,515 | ENH/API: GH2578, allow ix and friends to partially set when the key is not contained in the object | {
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"followers_url": "https://api.github.com/users/wesm... | 6 | 2013-08-08T18:52:15Z | 2014-06-12T09:17:05Z | 2013-09-05T17:23:51Z | CONTRIBUTOR | null | closes #2578
On a series, this is kind of like an inplace append operation (note the dtype change - on purpose)
```
In [6]: s = Series([1,2,3])
In [7]: s[4] = 5.
In [3]: s
Out[3]:
0 1
1 2
2 3
4 5
dtype: float64
```
This is now allowed: (previously would `KeyError`), you first have to create the column ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4516 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4516/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4516/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4516/events | https://github.com/pandas-dev/pandas/issues/4516 | 17,829,521 | MDU6SXNzdWUxNzgyOTUyMQ== | 4,516 | MultiIndexes and large CSV files | {
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"followers_url": "https://api.github.com/users/wesm... | 13 | 2013-08-08T20:34:29Z | 2013-08-17T15:39:38Z | 2013-08-09T14:36:39Z | NONE | null | I've run into a data-dependent bug with MultiIndex. Attached are a test script and a data file generation script:
- sales-data.py loads CSV data from a CSV data file with read_csv and then displays a multiindexed subset.
- sales-gen.sh is an AWK script that generates CSV test files. By default, it creates a 600MB file,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4517 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4517/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4517/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4517/events | https://github.com/pandas-dev/pandas/issues/4517 | 17,845,668 | MDU6SXNzdWUxNzg0NTY2OA== | 4,517 | Add PyExcelerate as Excel Writer Engine | {
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... | 29 | 2013-08-09T03:38:15Z | 2019-02-13T08:03:13Z | 2019-02-13T08:03:13Z | CONTRIBUTOR | null | Here's an example with just 65,000 elements (it's _much_ worse with 250,000) so I can compare xls and xlsx:
from pandas import *
df = DataFrame({'col1' : [0.0] \* 65000,
'col2' : 1,
'col3' : 2})
%timeit df.to_csv('sample.csv')
10 loops, best of 3: 109 ms per loop
%timeit df.to_excel(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4518 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4518/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4518/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4518/events | https://github.com/pandas-dev/pandas/pull/4518 | 17,846,308 | MDExOlB1bGxSZXF1ZXN0NzQ5NjM1Mw== | 4,518 | DOC: added google finance as a data source to the DataReader doc | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4519 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4519/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4519/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4519/events | https://github.com/pandas-dev/pandas/issues/4519 | 17,852,291 | MDU6SXNzdWUxNzg1MjI5MQ== | 4,519 | Segfault with pd.tslib.get_period_field | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2013-08-09T08:31:41Z | 2013-08-15T17:23:58Z | 2013-08-15T17:23:58Z | CONTRIBUTOR | null | ``` python
>>> import pandas as pd
>>> pd.tslib.get_period_field(11, 1, 1)
Exception ValueError: ValueError('Unrecognized code: 11',) in 'pandas.tslib._get_accessor_func' ignored
Segmentation fault
```
I'll push a fix.
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https://api.github.com/repos/pandas-dev/pandas/issues/4520 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4520/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4520/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4520/events | https://github.com/pandas-dev/pandas/pull/4520 | 17,852,668 | MDExOlB1bGxSZXF1ZXN0NzQ5OTM4OA== | 4,520 | Segfault with pd.tslib.get_period_field FIX | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4521 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4521/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4521/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4521/events | https://github.com/pandas-dev/pandas/issues/4521 | 17,862,117 | MDU6SXNzdWUxNzg2MjExNw== | 4,521 | ENH: allow timedelta64 to be divided by integers | {
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"followers_url": "https://api.github.com/users/wesm... | 0 | 2013-08-09T13:14:10Z | 2013-10-23T23:55:58Z | 2013-08-13T22:19:43Z | CONTRIBUTOR | null | I belive numpy < 1.7 is very problematic with this, but 1.7 is ok
http://stackoverflow.com/questions/18142144/dividing-a-series-containing-datetime-by-a-series-containing-an-integer-in-panda
```
import pandas as pd
from pandas import Series
startdate = Series(pd.date_range('2013-01-01', '2013-01-03'))
enddate = Seri... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4522 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4522/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4522/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4522/events | https://github.com/pandas-dev/pandas/pull/4522 | 17,863,233 | MDExOlB1bGxSZXF1ZXN0NzUwNDcwNw== | 4,522 | BUG: GH4516 Fixed issue with sorting a duplicate multi-index that has multiple dtypes | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4523 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4523/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4523/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4523/events | https://github.com/pandas-dev/pandas/issues/4523 | 17,865,868 | MDU6SXNzdWUxNzg2NTg2OA== | 4,523 | 0.12.0 to_hdf() error on a multi-index DataFrame | {
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```
portfolio_data
```
> <class 'pandas.core.frame.DataFrame'>
> MultiIndex: 45846 entries, (2013-06-28, 000312) to (2013-07-01, Y8565N10)
> Data columns (total 12 columns):
> market_cap 45843 non-null values
> alpha 45778 non-null values
> gics_code ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4524 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4524/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4524/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4524/events | https://github.com/pandas-dev/pandas/issues/4524 | 17,868,875 | MDU6SXNzdWUxNzg2ODg3NQ== | 4,524 | DOC: need SQL -> pandas tips | {
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"followers_url": "https://api.github.com/users/... | 12 | 2013-08-09T15:33:14Z | 2013-12-10T12:51:32Z | 2013-12-10T12:51:32Z | CONTRIBUTOR | null | of course #4164 makes this syntax easier anyhow
Here's an example of the types of things we need (obviously not all apply here)
http://www.pytables.org/moin/HintsForSQLUsers
we have this in the docs for join/merge, but maybe useful for:
- groupby
- boolean indexing to replace select
e.g.
```
select * from mytables ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4525 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4525/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4525/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4525/events | https://github.com/pandas-dev/pandas/issues/4525 | 17,879,438 | MDU6SXNzdWUxNzg3OTQzOA== | 4,525 | make the align keyword work like matplotlib in bar plots | {
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"labels_url": "htt... | 0 | 2013-08-09T18:52:50Z | 2014-03-26T20:50:44Z | 2014-03-26T20:50:44Z | MEMBER | null | [SO question](http://stackoverflow.com/questions/18151775/create-yoy-graph-with-matplotlib/18153525#18153525)
if you do it with pandas like this:
```
In [60]: s.plot(kind='bar', align='center')
Out[60]: <matplotlib.axes.AxesSubplot at 0xc1f3810>
In [61]: ax = gca()
In [62]: ax2 = twinx(ax)
In [63]: s.plot(ax=ax2)
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https://api.github.com/repos/pandas-dev/pandas/issues/4526 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4526/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4526/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4526/events | https://github.com/pandas-dev/pandas/issues/4526 | 17,880,683 | MDU6SXNzdWUxNzg4MDY4Mw== | 4,526 | preserving dtype of added columns | {
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```
In [19]:
df = pd.DataFrame({'C1':range(3)})
In [20]:
df['C2'] = pd.Series(range(3), dtype='uint32')
df.dtypes
Out [20]:
C1 int... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4527 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4527/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4527/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4527/events | https://github.com/pandas-dev/pandas/issues/4527 | 17,882,404 | MDU6SXNzdWUxNzg4MjQwNA== | 4,527 | GroupBy Filter does not work for 2+ grouping columns in 0.12.0 | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2013-08-09T19:59:50Z | 2013-08-09T20:19:21Z | 2013-08-09T20:19:21Z | NONE | null | Trying to filter out groups with less than 1 row with the new groupby().filter() in 0.12.0:
``` python
df = pd.DataFrame({'A' : ['foo', 'bar', 'foo', 'bar',
....: 'foo', 'bar', 'foo', 'foo'],
....: 'B' : ['one', 'one', 'two', 'three',
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https://api.github.com/repos/pandas-dev/pandas/issues/4528 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4528/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4528/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4528/events | https://github.com/pandas-dev/pandas/issues/4528 | 17,885,281 | MDU6SXNzdWUxNzg4NTI4MQ== | 4,528 | BUG/API: can't pass parameters to csv module via df.to_csv | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4529 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4529/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4529/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4529/events | https://github.com/pandas-dev/pandas/pull/4529 | 17,892,764 | MDExOlB1bGxSZXF1ZXN0NzUyMDY3OQ== | 4,529 | ENH: avoid unnecessary ga mgmt calls if given profile_id upfront | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4530 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4530/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4530/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4530/events | https://github.com/pandas-dev/pandas/pull/4530 | 17,892,929 | MDExOlB1bGxSZXF1ZXN0NzUyMDczNQ== | 4,530 | DOC/BLD: Update version support in docs and setup.py. | {
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Changes install.rst to explicitly reference that pandas supports 2.6,
2.7, and 3.2+. (and removes line that Python 3 support is less
well-tested). Also adds 2.6, 2.7, 3.2, and 3.3 in classifiers in
setup.py
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https://api.github.com/repos/pandas-dev/pandas/issues/4531 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4531/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4531/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4531/events | https://github.com/pandas-dev/pandas/issues/4531 | 17,893,223 | MDU6SXNzdWUxNzg5MzIyMw== | 4,531 | Bug: Bizarre DataFrame printing inconsistency (REPL only) | {
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] | closed | false | null | [] | null | 7 | 2013-08-10T02:33:36Z | 2013-08-13T02:52:02Z | 2013-08-10T12:08:46Z | NONE | null | Pandas 0.12.0 fails to print a column change in this specific example:
``` python
Python 2.7.3 (default, Apr 10 2013, 05:13:16)
[GCC 4.7.2] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> import pandas
>>> length = 5
>>> xx = pandas.DataFrame({'a':np.random.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4532 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4532/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4532/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4532/events | https://github.com/pandas-dev/pandas/issues/4532 | 17,898,561 | MDU6SXNzdWUxNzg5ODU2MQ== | 4,532 | BUG/API: timedelta64 series should operate directly with np.timedelta64/pd.offsets | {
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http://stackoverflow.com/questions/18159675/python-pandas-change-duplicate-timestamp-to-unique/18162121#18162121
```
In [81]: df = DataFrame(dict(time = [Timestamp('20130101 9:01'),Timestamp('20130101 9:02')]))
```
This is buggy
```
In [82]: df.time + np.timedelta64(1,'ms')
Out[82]:
0 2013-01-... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4533 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4533/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4533/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4533/events | https://github.com/pandas-dev/pandas/issues/4533 | 17,899,015 | MDU6SXNzdWUxNzg5OTAxNQ== | 4,533 | BUG: diff on a DataFrame with a datelike broken | {
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In [10]: df = DataFrame(dict(time = [Timestamp('20130101 9:01'),Timestamp('20130101 9:02')],value=[1.0,2.0]))
In [11]: df
Out[11]:
time value
0 2013-01-01 09:01:00 1
1 2013-01-01 09:02:00 2
```
works on series
```
In [12]: df.time.diff()
Out[12]:
0 NaT
1 00:01:00
Name: time... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4534 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4534/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4534/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4534/events | https://github.com/pandas-dev/pandas/pull/4534 | 17,899,456 | MDExOlB1bGxSZXF1ZXN0NzUyMzE3Nw== | 4,534 | BUG/API: Fix operating with timedelta64/pd.offsets on rhs of a datelike series/index | {
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closes #4134
closes #4135
closes #4521
Timedeltas can be converted to other ‘frequencies’ by dividing by another timedelta.
```
In [210]: td = Series(date_range('20130101',periods=4))-Series(date_range('20121201',periods=4))
In [211]: td[2] += np.timedelta64(timedelta(minutes=5,seconds=3))
In [212]: t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4535 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4535/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4535/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4535/events | https://github.com/pandas-dev/pandas/issues/4535 | 17,900,794 | MDU6SXNzdWUxNzkwMDc5NA== | 4,535 | Remove deprecated setters for MultiIndex levels and labels | {
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... | 0 | 2013-08-10T16:28:42Z | 2018-07-06T22:36:12Z | 2018-07-06T22:36:12Z | CONTRIBUTOR | null | For 0.14 or later, after #4039 is merged this becomes a todo item for the future.
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https://api.github.com/repos/pandas-dev/pandas/issues/4536 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4536/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4536/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4536/events | https://github.com/pandas-dev/pandas/issues/4536 | 17,901,531 | MDU6SXNzdWUxNzkwMTUzMQ== | 4,536 | DataFrame produces NaNs | {
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``` python
In [1]: import urllib2
In [2]: open("N_06_area.txt", "w").write(urllib2.urlopen("ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/Jun/N_06_area.txt").read())
In [3]: from pandas import read_table, DataFrame
In [4]: data = read_table("data/N_06_area.txt", skipfooter=16, sep="\s+... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4537 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4537/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4537/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4537/events | https://github.com/pandas-dev/pandas/issues/4537 | 17,907,039 | MDU6SXNzdWUxNzkwNzAzOQ== | 4,537 | BUG: Comparisons with non-comparable objects in DataFrame return True | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4538 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4538/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4538/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4538/events | https://github.com/pandas-dev/pandas/issues/4538 | 17,913,258 | MDU6SXNzdWUxNzkxMzI1OA== | 4,538 | fill_between doesn't work with Series objects | {
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if instead you don't use `.values` then a `KeyError` is thrown
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http://pandas.pydata.org/pandas-docs/stable/generated/pandas.io.parsers.read_table.html#pandas.io.parsers.read_table
shows it as `pandas.io.parsers.read_table` but it should be used as `pandas.read_table` and that's how it should appear
this could be a simple sphinx ref... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4540 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4540/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4540/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4540/events | https://github.com/pandas-dev/pandas/issues/4540 | 17,919,979 | MDU6SXNzdWUxNzkxOTk3OQ== | 4,540 | HDF4 -Earth Observing System (EOS) | {
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Is it possible include any easy access to HDF4 files?
They are still in use specially for those data distributed by NASA satellite MODIS.
Cheers,
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Please, make it freuqency aware. Currently, it just works with daily data.
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Hi,
I am the author of the [XlsxWriter](https://github.com/jmcnamara/XlsxWriter) module, a Python module for writing Excel XLSX files.
I am interested in submitting a PR to add this as a option when writing Excel xlsx files via `to_excel()`.
It has a similar interface to the xlwt module but cre... | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2013-08-12T17:23:32Z | 2016-07-20T07:44:57Z | 2016-07-19T21:06:38Z | NONE | null | It would work similar to drop_duplicates (same interface), but would only remove consecutive duplicates (like Unix's uniq does). So to in order to remove all duplicates with this function, the DataFrame would need to be sorted by the same criteria. This function can be useful when order is important and non-consecuti... | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2013-08-12T20:16:47Z | 2013-10-24T12:57:37Z | 2013-10-01T01:21:47Z | CONTRIBUTOR | null | I'm really sorry if this is a duplicate issue of #2997, but it seems to me that this is a little bit different. Here the `.ix` when getting a value interprets the integer as label, and when setting a value it interprets it as a positional index.
``` python
>>> import numpy as np
>>> import pandas as pd
>>> df = pd.Dat... | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2013-08-12T22:44:50Z | 2013-09-26T21:27:34Z | 2013-09-26T21:27:34Z | MEMBER | null | maybe would be nice to have `df.plot(kind='candle')` or `df.plot(kind='ohlc')`? kind of a pain to do all the date/time stuff manually
see [this SO question](http://stackoverflow.com/q/18195231/564538) for an example
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https://api.github.com/repos/pandas-dev/pandas/issues/4546 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4546/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4546/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4546/events | https://github.com/pandas-dev/pandas/issues/4546 | 17,976,905 | MDU6SXNzdWUxNzk3NjkwNQ== | 4,546 | Issue Using Chained Accessors with Multiple dtypes & Performance Tips | {
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```
import pandas
df = pandas.DataFrame({'a':[7.3,5.1,3.0,5.5,6.4],'b':[5,4,5,1,6]})
df['a'] = df.apply(lambda x: 1... | {
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import pandas as pd
ts1=pd.date_range('1/1/2000',periods=1,freq='Q')[0]
ts1-1-1
Error:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "tslib.pyx", line 566, in pandas.tslib._Timestamp.__sub__ ... | {
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``` python
>>> import pandas as pd
>>> pd.__version__
'0.12.0'
>>> s1 = pd.Series(range(3))
>>> s2 = pd.Series(range(3))
>>> comb = pd.concat([s1,s2])
>>> comb
0 0
1 1
2 2
0 0
1 1
2 2
dtype: int64
```
Assign value by boolean mask:
``` python
>>> comb[comb<1] =... | {
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original stacktrace (containing the code path that raised the original
exception). This makes debugging difficult since all we know is that an error
occured when `frame._apply_standard` attempted to call the provided function.
Preserve the origin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4550 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4550/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4550/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4550/events | https://github.com/pandas-dev/pandas/issues/4550 | 17,994,747 | MDU6SXNzdWUxNzk5NDc0Nw== | 4,550 | 'ValueError: Cannot assign nan to integer series" when calling `where` on Series with non-unique index. | {
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"followers_url": "https://api.github.com/users/wesm... | 4 | 2013-08-13T12:55:03Z | 2013-09-09T02:03:14Z | 2013-09-09T02:03:14Z | CONTRIBUTOR | null | Create a Series with non-unique index:
``` python
>>> import pandas as pd
>>> pd.__version__
'0.12.0'
>>> s1 = pd.Series(range(3))
>>> s2 = pd.Series(range(3))
>>> comb = pd.concat([s1,s2])
>>> comb
0 0
1 1
2 2
0 0
1 1
2 2
dtype: int64
```
As of https://github.com/pydata/pandas/issues/4548 I cannot ... | {
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I have a DataFrame of length 390,080, with int64 indices.
`df.index.size` gives the correct answer of 390,080, but `df.index.max` results in a huge traceback that ends with:
```
/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pandas/cor... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4552 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4552/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4552/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4552/events | https://github.com/pandas-dev/pandas/issues/4552 | 17,997,017 | MDU6SXNzdWUxNzk5NzAxNw== | 4,552 | docs: use randint where possible | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2013-08-13T13:44:42Z | 2013-09-27T20:13:44Z | 2013-09-27T20:13:44Z | CONTRIBUTOR | null | Hello,
I suggest to use np.random.randin where possible in the docstrings / examples.
With values imited like:
```
np.random.randint(1, 10, 4000)
```
...the reader would have it easy to re-calculate results (sum, max, min, mean, etc.) while reading the examples.
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"labels_url": "htt... | 20 | 2013-08-13T15:22:38Z | 2014-03-10T20:01:30Z | 2014-03-10T20:01:30Z | CONTRIBUTOR | null | ```
In [6]: Timestamp('20130101',offset='D')
Out[6]: Timestamp('2013-01-01 00:00:00', tz=None)
In [7]: Timestamp('20130101',offset='D').freq
Out[7]: 'D'
```
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"followers_url": "https://api.github.com/users/wesm... | 5 | 2013-08-13T15:54:09Z | 2013-10-24T11:52:14Z | 2013-09-29T22:07:31Z | CONTRIBUTOR | null | This may be seen like a weird function call but it is actually triggered when plotting with development versions of matplotlib and the case is explicitly (and wrongly as it seems) by pandas:
```
>>> import pandas as pd
>>> x = pd.Series(range(5))
>>> x.reshape(x.shape)
Traceback (most recent call last):
File "<stdin... | {
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It's hard to think of why a DataFrame would allow a `regex=True` replace method, and a Series wouldn't. This must just be an oversight, right?
```
>>> test = pd.DataFrame(['hello','goodbye','thankyou'],columns=['to_replace'])
>>> test
to_replace
0 hello
1 goodbye
2 thankyou
>>> test.re... | {
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"labels_url": "htt... | 4 | 2013-08-13T18:14:00Z | 2014-01-24T15:14:48Z | 2014-01-24T15:12:14Z | CONTRIBUTOR | null | related #3281
Create a read_pdf method in IO tools for reading tables from PDF documents. Many data sets are released in PDF form.
For example:
- Walmart's Historical Unit Count and Square Footage: http://az204679.vo.msecnd.net/media/documents/unit-counts-q1-fy14_130131488115936836.pdf
- Las Vegas Visitor Statistics:... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4557 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4557/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4557/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4557/events | https://github.com/pandas-dev/pandas/issues/4557 | 18,021,171 | MDU6SXNzdWUxODAyMTE3MQ== | 4,557 | No way to access correlation significance value (Spearman, Kendall) | {
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"followers_url": "https://api.github.com/users/jorisva... | 11 | 2013-08-13T21:04:02Z | 2017-11-24T10:30:13Z | 2017-11-24T10:30:05Z | NONE | null | The corr() method attached to DataFrames is a great way to get a matrix of correlation coefficients. But for the Kendall and Spearman options, the p-value is discarded:
https://github.com/pydata/pandas/blob/8ac0e11b59b65f0ac898dca2beebde5f87836649/pandas/core/nanops.py#L510-L517
For a function called corr() this wou... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4558 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4558/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4558/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4558/events | https://github.com/pandas-dev/pandas/issues/4558 | 18,022,597 | MDU6SXNzdWUxODAyMjU5Nw== | 4,558 | API/ENH: stata export should better support np.datetime64 based times | {
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"followers_url": "https://api.github.com/users/jr... | 9 | 2013-08-13T21:31:57Z | 2014-03-13T22:19:16Z | 2014-03-13T22:19:16Z | CONTRIBUTOR | null | The following code exporting a dataframe with a timeseries index with np.datetime64 type
``` python
import numpy as np
import pandas as pd
timestamps = pd.date_range(np.datetime64('2013-01-01 11:00:00.123456'), periods=5, freq='123U')
dataframe = pd.DataFrame(np.random.randn(len(timestamps)), index=timestamps)
datafr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4559 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4559/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4559/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4559/events | https://github.com/pandas-dev/pandas/issues/4559 | 18,028,474 | MDU6SXNzdWUxODAyODQ3NA== | 4,559 | add a doc example of SQL's ON statement | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4560 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4560/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4560/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4560/events | https://github.com/pandas-dev/pandas/pull/4560 | 18,030,445 | MDExOlB1bGxSZXF1ZXN0NzU4OTM3Ng== | 4,560 | CLN/ENH: Provide full suite of arithmetic (and flex) methods to all NDFrame objects. | {
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This goes on top of @jreback's Series refactoring (#3482). If you want to review, I suggest looking [at the PR on top of jreback/series2](https://github.com/jreback/pandas/pull/6), so you only see the diffs specific to this PR.
This does a few things:
1. Normalizes the arithmetic ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4561 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4561/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4561/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4561/events | https://github.com/pandas-dev/pandas/issues/4561 | 18,039,205 | MDU6SXNzdWUxODAzOTIwNQ== | 4,561 | BUG: read_clipboard fails on Windows since pandas 0.12 | {
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```
import pandas as pd
df = pd.read_clipboard()
```
Results in:
```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-2-6de... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4562 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4562/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4562/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4562/events | https://github.com/pandas-dev/pandas/pull/4562 | 18,046,493 | MDExOlB1bGxSZXF1ZXN0NzU5Nzg4MA== | 4,562 | BUG: Fix Segfault with pd.tslib.get_period_field (GH4519, GH4520) | {
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"followers_url": "https://api.github.com/users/wesm... | 4 | 2013-08-14T11:09:00Z | 2014-07-02T22:36:41Z | 2013-08-15T17:23:31Z | CONTRIBUTOR | null | Fixes the following problem (issues #4519, #4520):
``` python
>>> import pandas as pd
>>> pd.tslib.get_period_field(11, 1, 1)
Exception ValueError: ValueError('Unrecognized code: 11',) in 'pandas.tslib._get_accessor_func' ignored
Segmentation fault
```
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https://api.github.com/repos/pandas-dev/pandas/issues/4563 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4563/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4563/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4563/events | https://github.com/pandas-dev/pandas/issues/4563 | 18,051,991 | MDU6SXNzdWUxODA1MTk5MQ== | 4,563 | pandas.io.excel.read_excel kind parameter | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2013-08-14T13:29:10Z | 2013-09-22T20:14:55Z | 2013-09-22T20:14:55Z | CONTRIBUTOR | null | The `kind` parameter on `pandas.io.excel.read_excel` is totally undocumented:
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.io.excel.read_excel.html#pandas.io.excel.read_excel
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https://api.github.com/repos/pandas-dev/pandas/issues/4564 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4564/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4564/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4564/events | https://github.com/pandas-dev/pandas/pull/4564 | 18,052,634 | MDExOlB1bGxSZXF1ZXN0NzYyNTMwNA== | 4,564 | BUG: DatetimeIndex uses the wrong union if the operands overlap | {
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"followers_url": "https://api.github.com/users/wesm... | 5 | 2013-08-14T13:42:16Z | 2015-01-06T14:43:46Z | 2013-09-26T00:49:44Z | CONTRIBUTOR | null | This pretty much boils down to this line: https://github.com/pydata/pandas/blob/master/pandas/tseries/index.py#L987
You can easily reproduce the error using the following code:
```
r = pd.date_range("2013-01-01", "2013-02-01")
r2 = r + pd.DateOffset(minutes=15)
r | r2 # Results in the index r having "2013-01-31 00:15... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4565 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4565/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4565/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4565/events | https://github.com/pandas-dev/pandas/issues/4565 | 18,054,382 | MDU6SXNzdWUxODA1NDM4Mg== | 4,565 | API: add is_beg_month/year, is_end_month/year accessors for a DateTimeIndex/Timestamp | {
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"creator": null,
"description": "2014-02-3: previous version released",
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"labels_url": "htt... | 0 | 2013-08-14T14:14:11Z | 2014-04-29T23:41:57Z | 2014-04-29T23:41:57Z | CONTRIBUTOR | null | ```
In [110]: x = Timestamp('20130101')
```
Last day of month
```
In [111]: pd.tslib.monthrange(x.year,x.month)[1]==x.day
Out[111]: False
```
First day of month
```
In [112]: x.day==1
Out[112]: True
```
First day of year
```
In [113]: x.day==1 & x.month==1
Out[113]: True
```
http://stackoverflow.com/questions/18... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4566 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4566/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4566/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4566/events | https://github.com/pandas-dev/pandas/pull/4566 | 18,054,665 | MDExOlB1bGxSZXF1ZXN0NzYwMjU2Mg== | 4,566 | Fixes check in _can_fast_union. | {
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"f... | 11 | 2013-08-14T14:27:59Z | 2021-07-14T01:41:40Z | 2020-09-19T20:49:31Z | CONTRIBUTOR | null | I think an implementation of a general recurrent relation might be interesting. These
are not able to evaluated in numpy/numexpr directly
see here:
http://stackoverflow.com/questions/9984373/calculate-two-coupled-equation-with-numpy
http://stackoverflow.com/questions/21336794/python-recursive-vectorization-with-timese... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4568 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4568/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4568/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4568/events | https://github.com/pandas-dev/pandas/issues/4568 | 18,057,390 | MDU6SXNzdWUxODA1NzM5MA== | 4,568 | ENH/API: cross_apply | {
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"f... | 2 | 2013-08-14T15:07:39Z | 2021-04-11T03:00:47Z | 2021-04-11T03:00:46Z | CONTRIBUTOR | null | Would prob need to be done in cython for perf
```
def cross_apply(func, is_symmetric=True, **kwargs):
l = len(df.columns)
results = np.zeros((l,l))
if is_symmetric:
for i in range(l):
for j in range(i + 1):
results[i,j] = results[j,i] = func(ac,bc, **kwargs)
else:
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https://api.github.com/repos/pandas-dev/pandas/issues/4569 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4569/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4569/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4569/events | https://github.com/pandas-dev/pandas/issues/4569 | 18,058,047 | MDU6SXNzdWUxODA1ODA0Nw== | 4,569 | One assignment method in mixed type dataframe not working | {
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"f... | 3 | 2013-08-14T15:19:07Z | 2014-06-08T01:07:51Z | 2014-06-08T01:07:51Z | NONE | null | I tried several ways of assigning values in a mixed type dataframe and it seems that one of them is not working. I am not sure if it is supposed to do so:
from pandas import DataFrame
df = DataFrame({'A':[:'aaa','bbb','ccc'],'B':[1,2,3]})
# this works, value is changed
df.ix[0,'A'] = 11
# this works, value is changed... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4570 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4570/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4570/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4570/events | https://github.com/pandas-dev/pandas/issues/4570 | 18,058,561 | MDU6SXNzdWUxODA1ODU2MQ== | 4,570 | DOC: even bigger badder warning on doing chained assignments | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2013-08-14T15:27:16Z | 2013-08-14T16:03:04Z | 2013-08-14T16:03:04Z | CONTRIBUTOR | null | BAD
`df.ix[0]['A'] = 5`
GOOD
`df.ix[0,'A'] = 5`
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https://api.github.com/repos/pandas-dev/pandas/issues/4571 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4571/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4571/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4571/events | https://github.com/pandas-dev/pandas/pull/4571 | 18,074,174 | MDExOlB1bGxSZXF1ZXN0NzYxMzczMg== | 4,571 | BUG: Fix bug in pd.read_clipboard on windows with PY3 (GH4561); not decoding properly | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4572 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4572/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4572/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4572/events | https://github.com/pandas-dev/pandas/issues/4572 | 18,080,926 | MDU6SXNzdWUxODA4MDkyNg== | 4,572 | implementation of a general recurrent relation | {
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http://permalink.gmane.org/gmane.comp.python.pydata/2164
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https://api.github.com/repos/pandas-dev/pandas/issues/4573 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4573/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4573/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4573/events | https://github.com/pandas-dev/pandas/pull/4573 | 18,081,693 | MDExOlB1bGxSZXF1ZXN0NzYxODE5OA== | 4,573 | BUG: Fix incorrect urlparse in _is_s3_url | {
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changed - urlparse is no longer imported in io/common (in favor of py2/3
compatible methods).
I added a dumb test case so it at least gets called going forward.
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skipping test via: b5ff81d34d74efdf88b8151ff58ed16ff7c02c67
fails about 1/3 times (and only seems on py3)
https://travis-ci.org/pydata/pandas/jobs/10223886
don't use now, pick a known value (that you can then compare too exactly)
```
def test_datetime_units(self):
from pandas.lib import... | {
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"followers_url": "https://api.github.com/users/wesm... | 16 | 2013-08-15T06:27:50Z | 2016-07-16T22:41:18Z | 2013-08-26T12:45:17Z | CONTRIBUTOR | null | It seems that when comparing DataFrame to list or tuple of values (lenght of DataFrame columns), the resulting boolean DataFrame is incorrect.
`````` python
>>> import pandas
>>> print pandas.__version__
0.12.0
>>> import numpy as np
>>> print np.__version__
1.6.1
>>> df=pandas.DataFrame([ [-1, 0], [1, 2] ])
>>> df > ... | {
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```
/usr/local/lib/python2.7/dist-packages/numpy/core/scalarmath.so
/usr/local/lib/python2.7/dist-packages/numpy/linalg/lapack_lite.so
/usr/local/lib/python2.7/dist-packages/pan... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4578 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4578/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4578/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4578/events | https://github.com/pandas-dev/pandas/pull/4578 | 18,149,492 | MDExOlB1bGxSZXF1ZXN0NzY1NTIyMg== | 4,578 | ENH: Remove the hardcoded border=1 in the to_html dataframe export. | {
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border gives the user the possibility to style the table, using CSS Classes.
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https://api.github.com/repos/pandas-dev/pandas/issues/4579 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4579/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4579/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4579/events | https://github.com/pandas-dev/pandas/pull/4579 | 18,151,718 | MDExOlB1bGxSZXF1ZXN0ODgxODAyMQ== | 4,579 | date_range should (at least optionally) deal with right-open intervals | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4580 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4580/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4580/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4580/events | https://github.com/pandas-dev/pandas/pull/4580 | 18,153,993 | MDExOlB1bGxSZXF1ZXN0NzY1NzY5OA== | 4,580 | TST: win32 paths cannot be turned into URLs by prefixing them with "file://" | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4581 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4581/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4581/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4581/events | https://github.com/pandas-dev/pandas/issues/4581 | 18,154,193 | MDU6SXNzdWUxODE1NDE5Mw== | 4,581 | BUG: (iloc) Comparisons of Series have different indexing semantics from DataFrame comparisons | {
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``` python
In [3]: df = pd.DataFrame(np.arange(5), columns=["foo"])
In [4]: df["foo"].iloc[:-1] != df["foo"].iloc[1:]
Out[4]:
0 True
1 True
2 True
3 True
dtype: bool
In [5]: df["foo"].iloc[1:] != df["foo"].iloc[:-1]
Out[5]:
1 True
2 True
3 True
4 True
dtype: bool
```
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4582 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4582/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4582/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4582/events | https://github.com/pandas-dev/pandas/issues/4582 | 18,158,059 | MDU6SXNzdWUxODE1ODA1OQ== | 4,582 | ER: raise on invalid compression options in HDFStore | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4583 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4583/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4583/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4583/events | https://github.com/pandas-dev/pandas/issues/4583 | 18,164,426 | MDU6SXNzdWUxODE2NDQyNg== | 4,583 | 0.12.0 concat() error | {
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```
columns = None
for portfolio_data in portfolio_data_list:
print(portfolio_data.shape)
if columns is None:
columns = portfolio_data.columns
else:
print(all(portfolio_data.columns == columns))
portfolio_data = pd.concat(portfolio_data_list)... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4584 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4584/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4584/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4584/events | https://github.com/pandas-dev/pandas/issues/4584 | 18,166,985 | MDU6SXNzdWUxODE2Njk4NQ== | 4,584 | BUG: 0.12.0 using DataFrame.to_hdf() with mode='a' does not append the data | {
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Is there a way to use DataFrame.to_hdf() so that data can be appened the data? Somehow to_hdf(filename, table_name, mode='a', table=True) overwrites the data while to_hdf(filename, table_name, table=True, append=True) gives the following error:
> Tra... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4585 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4585/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4585/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4585/events | https://github.com/pandas-dev/pandas/pull/4585 | 18,178,540 | MDExOlB1bGxSZXF1ZXN0NzY3MDgwMA== | 4,585 | BUG: Fix boolean comparison with a DataFrame on the lhs, and a list/tuple on the rhs GH4576 | {
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```
In [1]: df = DataFrame(np.arange(6).reshape((3,2)))
In [2]: b = np.array([2, 2])
In [3]: b_r = np.atleast_2d([2,2])
In [4]: b_c = b_r.T
In [5]: df>b
Out[5]:
0 1
0 False False
1 False True
2 True True
In [6]: df.values>b
Out[6]:
array([[False, False],
[False, True... | {
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This sort is undocumented and unwanted. Certainly the default behavior should be no-sort. EDIT: the standard order as in SQL would be: col... | {
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closes #4589
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https://api.github.com/repos/pandas-dev/pandas/issues/4591 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4591/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4591/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4591/events | https://github.com/pandas-dev/pandas/issues/4591 | 18,184,889 | MDU6SXNzdWUxODE4NDg4OQ== | 4,591 | DOC: Unclear documentation for Period Construction | {
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"f... | 6 | 2013-08-17T00:11:47Z | 2021-10-17T18:27:06Z | null | CONTRIBUTOR | null | The documentation is unclear as to what the date passed to a `Period` means: whether it is the start date or the end date of the period. Convention is that fiscal quarters are usually stated by the date the quarter ends, whereas weeks are many times stated by the day week starts. This is especially unclear given that t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4592 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4592/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4592/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4592/events | https://github.com/pandas-dev/pandas/pull/4592 | 18,192,830 | MDExOlB1bGxSZXF1ZXN0NzY3NzA4Mw== | 4,592 | TST: fix ujson's intermittently failing date unit test | {
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As you surmised @jreback it looks like unnecessary float arithmetic was causing the test failure. I fixed this up and in the interest of consistency removed the dependence on `datetime.now()`
Example
``` python
In [8]: val = 1376774232215504000
In [9]: val / 1000
Out[9]: 1376774232215504
In [10]: val ... | {
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``` python
In [16]: df = DataFrame([['a', 'b'], ['c', 'd']], index=['index " 1', 'index / 2'], columns=['a \\ b', 'y / z'])
In [17]: df
Out[17]:
a \ b y / z
index " 1 a b
in... | {
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"labels_url": "htt... | 12 | 2013-08-17T19:18:50Z | 2014-01-24T19:42:23Z | 2014-01-24T14:48:49Z | CONTRIBUTOR | null | Currently the `flavor` argument to `read_html` must either be `None` or a string or a container of strings. This make is difficult for the user to write his own instance of `_HtmlFrameParser` and to use that when parsing. I suggest also allowing the user to pass in a subclass of `_HtmlFrameParser` in place of a string.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4595 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4595/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4595/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4595/events | https://github.com/pandas-dev/pandas/issues/4595 | 18,201,161 | MDU6SXNzdWUxODIwMTE2MQ== | 4,595 | DataFrame.to_csv/read_csv inconsistency | {
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When I download data from Yahoo, mimicking the code on p. 139 of the book (python for data analysis) it creates a data frame. The index for this data frame is a time series index - timestamps provided by Yahoo.
If I save this DataFrame to disk using to_... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4596 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4596/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4596/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4596/events | https://github.com/pandas-dev/pandas/issues/4596 | 18,201,612 | MDU6SXNzdWUxODIwMTYxMg== | 4,596 | PythonParser::_check_thousands appears broken | {
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```
def _check_thousands(self, lines):
if self.thousands is None:
return lines
nonnum = re.compile('[^-^0-9^%s^.]+' % self.thousands)
ret = []
for l in lines:
rl = []
for x in l:
if (not isinstance(x, comp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4597 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4597/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4597/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4597/events | https://github.com/pandas-dev/pandas/issues/4597 | 18,203,942 | MDU6SXNzdWUxODIwMzk0Mg== | 4,597 | Add example git workflows to the wiki | {
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FYI, I'm trying to highlight `git` usage here, so if... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4598 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4598/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4598/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4598/events | https://github.com/pandas-dev/pandas/pull/4598 | 18,208,767 | MDExOlB1bGxSZXF1ZXN0NzY4Mjg2OQ== | 4,598 | csv_import: Thousands separator works in floating point numbers | {
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Adds support for the thousands character in csv parser for floats.
Previously, the thousands separator character did not pass into the core floating point number parsing algorithm:
https://github.com/pydata/pandas/blob/master/pandas/src/parser/tokenizer.c#L1861
I added an argument to this function... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4599 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4599/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4599/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4599/events | https://github.com/pandas-dev/pandas/issues/4599 | 18,209,374 | MDU6SXNzdWUxODIwOTM3NA== | 4,599 | Give the merge copy parameter better documentation | {
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"f... | 6 | 2013-08-18T15:59:22Z | 2020-05-27T17:14:56Z | null | MEMBER | null | See [this SO question](http://stackoverflow.com/q/18295630/564538)
The docstring should indicate _what_ is not being copied unnecessarily (`Index`es, `ndarray`s, etc.)
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https://api.github.com/repos/pandas-dev/pandas/issues/4600 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4600/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4600/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4600/events | https://github.com/pandas-dev/pandas/issues/4600 | 18,209,632 | MDU6SXNzdWUxODIwOTYzMg== | 4,600 | Adding a column to a DataFrame always creates a copy of a Series | {
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"followers_url": "https://api.github.com/users/wesm... | 15 | 2013-08-18T16:19:17Z | 2018-11-01T14:29:32Z | 2013-08-19T14:23:31Z | CONTRIBUTOR | null | I don't know if this is a valid behaviour, but it seems to me like a bug?
``` python
>>> s = pd.Series([1,2,3])
>>> df = pd.DataFrame(s)
>>> df.index is s.index
True
>>> df.iloc[0, 0] = 33
>>> df
0
0 33
1 2
2 3
>>> s
0 33
1 2
2 3
dtype: int64
```
So far so good.
But if I do:
``` python
>>> s = p... | {
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