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https://api.github.com/repos/pandas-dev/pandas/issues/10403 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10403/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10403/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10403/events | https://github.com/pandas-dev/pandas/issues/10403 | 89,953,832 | MDU6SXNzdWU4OTk1MzgzMg== | 10,403 | Assign SparseDataFrame row-by-row error | {
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"descript... | closed | false | null | [] | null | 1 | 2015-06-21T20:01:44Z | 2015-06-22T08:20:09Z | 2015-06-22T08:19:56Z | NONE | null | Hi,
I am trying to initialize a sparseDataFrame into block of memory and assign the value row-by-row, which ends up with:
```
a = np.random.rand(4,5)
b = pd.DataFrame(a)
c = sparse.csr_matrix(a)
d = pd.SparseDataFrame(index=b.index, columns=b.columns)
elem = pd.SparseSeries(c[2].toarray().ravel())
d.loc[[2]] = [ elem... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10404 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10404/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10404/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10404/events | https://github.com/pandas-dev/pandas/issues/10404 | 90,043,624 | MDU6SXNzdWU5MDA0MzYyNA== | 10,404 | PERF: implement timedelta string parsing to c | {
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... | 3 | 2015-06-22T08:38:48Z | 2018-08-29T01:24:52Z | 2018-08-29T01:24:52Z | CONTRIBUTOR | null | follows #6755 / #10396
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https://api.github.com/repos/pandas-dev/pandas/issues/10405 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10405/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10405/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10405/events | https://github.com/pandas-dev/pandas/pull/10405 | 90,096,400 | MDExOlB1bGxSZXF1ZXN0MzgyMzA2NzI= | 10,405 | TST: Use unicode literals in string test | {
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- Remove `compat.u()` completely, because the escaped literal is different from normal unicode literals internally.
- Remove `compat.callable` brought back in v3.2 ([some code](https://github.com/pydata/pandas/blob/master/pandas/core/frame.p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10406 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10406/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10406/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10406/events | https://github.com/pandas-dev/pandas/issues/10406 | 90,153,186 | MDU6SXNzdWU5MDE1MzE4Ng== | 10,406 | slicing dataframe with date index is not working properly | {
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"followers_url": "https://api.github.com/users/jorisva... | 5 | 2015-06-22T16:56:39Z | 2019-03-26T09:56:16Z | 2019-03-26T06:26:21Z | NONE | null | When slicing data time - indexed dataframe with date in string format, it works:
```
df.ix['2014-11-12'].head()
Out[55]:
calories gsr heart-rate skin-temp steps
date
2014-11-12 00:00:00 2.1 7.04640 NaN 85.77... | {
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in older versions pandas was able to plot onto inset-axis of matplotlib. In new versions this support seems to be broken. I was able to execute the following code without any exceptions using an old pandas version. However, the current pandas version (0.16.2) throws an exception. Since the last update of matplotli... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10408 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10408/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10408/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10408/events | https://github.com/pandas-dev/pandas/issues/10408 | 90,221,776 | MDU6SXNzdWU5MDIyMTc3Ng== | 10,408 | vectorised setting of timestamp columns fails with python datetime and numpy datetime64 | {
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import pandas as pd
import numpy as np
import datetime as dt
z=dt.date(2010,11,1)
zs=[z+dt.timedelta(days=r) for r in range(5)]
df=pd.DataFrame({'obj':zs, 'b':pd.Timestamp('2010-10-01'),'c':pd.Timestamp('2010-10-01')})
df.dtypes
#df.loc[0:2,'c']=dt.date(2010,10,12) # causes error: long() argument must be a string ... | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2015-06-23T00:18:46Z | 2017-03-10T23:06:03Z | 2017-03-10T23:06:03Z | CONTRIBUTOR | null | xref #14351
None of the following merge operations retain the `category` types. Is this expected? How can I keep them?
#### Merging on a `category` type:
Consider the following:
```
A = pd.DataFrame({'X': np.random.choice(['foo', 'bar'],size=(10,)),
'Y': np.random.choice(['one', 'two', 'three'], s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10410 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10410/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10410/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10410/events | https://github.com/pandas-dev/pandas/issues/10410 | 90,287,393 | MDU6SXNzdWU5MDI4NzM5Mw== | 10,410 | Writing as Excel with a MultiIndex is not yet implemented. | {
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when running the example below(as described in your site):
"Generating Excel Reports from a Pandas Pivot Table. "
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This does not entirely solve the floating point precision issues, but gets us part of the way there -- we can explicitly lookup data with a fixed tolerance for nearest neighbor matches.
It is also is useful in its own right, mostly as a simple sanity check to verify that labels are not entirely misaligned.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10412 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10412/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10412/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10412/events | https://github.com/pandas-dev/pandas/issues/10412 | 90,363,980 | MDU6SXNzdWU5MDM2Mzk4MA== | 10,412 | BUG: setting a slice with datetime64 ignores datetime64 resolution | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-06-23T11:40:02Z | 2015-07-24T13:50:18Z | 2015-07-24T13:50:18Z | MEMBER | null | Resulting in 1970 datetimes when using eg `datetime64[D]` resolution (splitted from #10408):
```
In [46]: df=pd.DataFrame({'c':pd.Timestamp('2010-10-01')}, index=range(5))
In [47]: df
Out[47]:
c
0 2010-10-01
1 2010-10-01
2 2010-10-01
3 2010-10-01
4 2010-10-01
In [48]: df.loc[0:2,'c'] = np.datetime64('2010... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10413 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10413/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10413/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10413/events | https://github.com/pandas-dev/pandas/issues/10413 | 90,411,171 | MDU6SXNzdWU5MDQxMTE3MQ== | 10,413 | BUG: csv w only header and no index_col failing | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-06-23T14:55:38Z | 2015-09-17T10:43:12Z | 2015-07-07T09:30:45Z | CONTRIBUTOR | null | after this fix https://github.com/pydata/pandas/pull/10302
The following is failing (as `index_col` is `None`)
```
In [9]: data
Out[9]: 'header1,header2\n'
In [10]: read_csv(StringIO(data),iterator=True,index_col=False).read()
TypeError: object of type 'bool' has no len()
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10414 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10414/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10414/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10414/events | https://github.com/pandas-dev/pandas/issues/10414 | 90,424,289 | MDU6SXNzdWU5MDQyNDI4OQ== | 10,414 | Documentation: Example missing in NA values by GroupBy | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-06-23T15:48:02Z | 2015-07-01T10:58:05Z | 2015-07-01T10:58:05Z | CONTRIBUTOR | null | http://pandas.pydata.org/pandas-docs/stable/missing_data.html#na-values-in-groupby
```
NA groups in GroupBy are automatically excluded. This behavior is consistent with R, for example.
```
I can take this up.
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https://api.github.com/repos/pandas-dev/pandas/issues/10415 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10415/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10415/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10415/events | https://github.com/pandas-dev/pandas/issues/10415 | 90,443,040 | MDU6SXNzdWU5MDQ0MzA0MA== | 10,415 | Add to_fwf support | {
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"f... | 1 | 2015-06-23T17:23:30Z | 2021-04-18T07:02:59Z | null | CONTRIBUTOR | null | Right now pandas can read fwf but there is no `to_fwf`.
From [SO](http://stackoverflow.com/questions/16490261/python-pandas-write-dataframe-to-fixed-width-file-to-fwf).
This output format seems similar to what [`numpy.savetxt`](http://docs.scipy.org/doc/numpy/reference/generated/numpy.savetxt.html) handles.
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https://api.github.com/repos/pandas-dev/pandas/issues/10416 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10416/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10416/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10416/events | https://github.com/pandas-dev/pandas/issues/10416 | 90,444,353 | MDU6SXNzdWU5MDQ0NDM1Mw== | 10,416 | Unstack MultiIndex vs consecutive unstack | {
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"de... | closed | false | null | [] | null | 2 | 2015-06-23T17:29:11Z | 2015-06-24T14:26:13Z | 2015-06-23T21:17:38Z | NONE | null | Hello,
If I try to unstack using multiIndex I got some groups divided. However, if I tried to do it by successive unstacking they are correctly grouped. Please see image below
I believe this is due to the f... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10417 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10417/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10417/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10417/events | https://github.com/pandas-dev/pandas/issues/10417 | 90,467,700 | MDU6SXNzdWU5MDQ2NzcwMA== | 10,417 | BUG: groupby with levels on duplicated multi-index | {
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x = pd.DataFrame({'x':[1,1,3,3],'y':[3,3,5,5]},index=[11,11,12,12])
y = x.stack()
print(y)
print(y.groupby(level=[0,1]).sum())
```
Ouput
```
11 x 1
y 3
x 1
y 3
12 x 3
y 5
x 3
y 5
dtype: int64
11 x 1
y 3
x 1
y 3
12 x 3
y 5
x ... | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-06-23T20:33:59Z | 2015-08-07T10:54:08Z | 2015-08-07T10:54:07Z | CONTRIBUTOR | null | Close #10362 . Specify information on the use of index in pandas.Series.interpolate documentation.
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https://api.github.com/repos/pandas-dev/pandas/issues/10419 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10419/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10419/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10419/events | https://github.com/pandas-dev/pandas/pull/10419 | 90,494,564 | MDExOlB1bGxSZXF1ZXN0MzgzODQ5ODY= | 10,419 | BUG: Fix value_counts name handling | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-06-23T21:27:25Z | 2015-07-04T12:52:08Z | 2015-06-27T03:51:56Z | MEMBER | null | Closes #10150. Also, made `test_base` have name attributes.
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https://api.github.com/repos/pandas-dev/pandas/issues/10420 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10420/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10420/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10420/events | https://github.com/pandas-dev/pandas/issues/10420 | 90,510,737 | MDU6SXNzdWU5MDUxMDczNw== | 10,420 | Pandas Interpolate Does not Handle Empty Values at Front of Series | {
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See for example [`UnivariateSpline... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10423 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10423/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10423/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10423/events | https://github.com/pandas-dev/pandas/pull/10423 | 90,582,262 | MDExOlB1bGxSZXF1ZXN0Mzg0MTE2MjQ= | 10,423 | Removed scikit-timeseries migration docs from FAQ | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10424 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10424/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10424/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10424/events | https://github.com/pandas-dev/pandas/issues/10424 | 90,588,756 | MDU6SXNzdWU5MDU4ODc1Ng== | 10,424 | csv_read() fails on properly decoding latin-1(i.e. non utf8) encoded file from URL | {
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Here is a problem that we had with a colleague, working on data available on a ftp (or http) server (internal network, we're sorry we can't have a proper example file to point to).
Reading a csv file (with csv_read) encoded with non utf8 (like latin-1), with special character in header, fails to properly ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10425 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10425/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10425/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10425/events | https://github.com/pandas-dev/pandas/issues/10425 | 90,613,827 | MDU6SXNzdWU5MDYxMzgyNw== | 10,425 | Pandas failing on Debian big-endian builds | {
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Package pandas is failing to build from source on Debian big-endian builds with following message:
<pre>
======================================================================
FAIL: test_to_records (pandas.tests.test_categorical.TestCategoricalAsBlock)
----------------------------------------------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10426 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10426/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10426/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10426/events | https://github.com/pandas-dev/pandas/issues/10426 | 90,664,213 | MDU6SXNzdWU5MDY2NDIxMw== | 10,426 | ERR: Timedelta('3.1415') should raise | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10427 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10427/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10427/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10427/events | https://github.com/pandas-dev/pandas/issues/10427 | 90,665,273 | MDU6SXNzdWU5MDY2NTI3Mw== | 10,427 | TST: Allow assert_numpy_array_equal to compare nan | {
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```
import numpy as np
import pandas as pd
import pandas.util.testing as pdt
import numpy.testing.utils as npt
npt.assert_array_equal(np.array([1, np.nan, 3]), np.array([1, np.nan, 3]))
# no AssertionError
pdt... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10430 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10430/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10430/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10430/events | https://github.com/pandas-dev/pandas/issues/10430 | 90,778,819 | MDU6SXNzdWU5MDc3ODgxOQ== | 10,430 | BUILD: 2.7 with numpy_dev currently broken | {
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I think might be a bug on numpy's part.
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https://api.github.com/repos/pandas-dev/pandas/issues/10431 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10431/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10431/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10431/events | https://github.com/pandas-dev/pandas/pull/10431 | 90,811,750 | MDExOlB1bGxSZXF1ZXN0Mzg1MDA5NjM= | 10,431 | BUG: provide categorical concat always on axis 0, #10430 | {
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closes #10430
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https://api.github.com/repos/pandas-dev/pandas/issues/10432 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10432/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10432/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10432/events | https://github.com/pandas-dev/pandas/issues/10432 | 90,814,954 | MDU6SXNzdWU5MDgxNDk1NA== | 10,432 | SciPy sprints | {
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"followers_url": "https://api.github.com/users/jorisva... | 0 | 2015-06-25T00:37:03Z | 2015-08-21T08:27:34Z | 2015-08-21T08:27:34Z | CONTRIBUTOR | null | @jreback, @shoyer, and @cpcloud will be at SciPy this year, and are going to host a sprint on July 11 (saturday).
SciPy sprint pages is [here](http://scipy2015.scipy.org/ehome/115969/292867/?&)
This issue will be the landing page for contributors.
[pandas](http://pandas.pydata.org) is an open source, BSD-licensed li... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10433 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10433/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10433/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10433/events | https://github.com/pandas-dev/pandas/pull/10433 | 90,828,851 | MDExOlB1bGxSZXF1ZXN0Mzg1MDYwMDM= | 10,433 | BUG: closes bug in stack when index is not unique | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10434 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10434/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10434/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10434/events | https://github.com/pandas-dev/pandas/issues/10434 | 90,832,429 | MDU6SXNzdWU5MDgzMjQyOQ== | 10,434 | Unclear UnicodeDecodeError exception. | {
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'ascii' codec can't decode byte 0xd7 in position 0: ordinal not in range(128)`
This is hard to understand. I finally figured out the issue, and it was that strings and floats are being compared. I suppose now the error message makes sense. This is an issue related to ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10435 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10435/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10435/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10435/events | https://github.com/pandas-dev/pandas/pull/10435 | 90,866,611 | MDExOlB1bGxSZXF1ZXN0Mzg1MTUwNjk= | 10,435 | BUG: GH10365 in interpolate_1d when method is piecewise_polynomial | {
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... | 5 | 2015-06-25T06:14:43Z | 2015-08-21T01:37:30Z | 2015-08-21T01:37:30Z | CONTRIBUTOR | null | Starting point for closing #10365.
I only have the trivial case. I think this method (and perhaps other methods as well) needs #10383 for it to be useful.
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type(not_empty)
empty_dim_1 = pd.DataFrame(columns=['a', 'b']).squeeze()
type(empty_dim_1)
empty_dim_0 = pd.DataFrame(index=['c', 'd']).squeeze()
type(empty_dim_0)
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https://api.github.com/repos/pandas-dev/pandas/issues/10437 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10437/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10437/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10437/events | https://github.com/pandas-dev/pandas/issues/10437 | 90,897,861 | MDU6SXNzdWU5MDg5Nzg2MQ== | 10,437 | unexpected behaviour when reindexing a Panel with MultiIndex | {
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```
wp.loc[(1,slice(None)),:,:] #Access the panel fixing the first index of the multiIndex
```
But whenever I try to reindex, like in this example I got this strange behaviour.
```
wp = pd.Panel(pd.randn(4, 5... | {
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closes #10425
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https://api.github.com/repos/pandas-dev/pandas/issues/10439 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10439/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10439/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10439/events | https://github.com/pandas-dev/pandas/issues/10439 | 90,963,221 | MDU6SXNzdWU5MDk2MzIyMQ== | 10,439 | BUG: read_pickle and period data | {
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<pre><code>
import pandas as pd
df = pd.DataFrame({'period': [pd.Period('2014Q4')] * 5})
msk = df['period'] == pd.Period('2014Q4')
print msk
d... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10440 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10440/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10440/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10440/events | https://github.com/pandas-dev/pandas/issues/10440 | 91,022,070 | MDU6SXNzdWU5MTAyMjA3MA== | 10,440 | Setting values on slice of multi-index gives NaNs | {
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... | 8 | 2015-06-25T17:11:59Z | 2021-08-31T14:14:07Z | null | NONE | null | Best shown with an example.
``` python
import numpy as np, pandas as pd
timestamps = map(pd.Timestamp, ['2014-01-01', '2014-02-01'])
categories = ['A', 'B', 'C', 'D']
df = pd.DataFrame(index=pd.MultiIndex.from_product([timestamps, categories], names=['ts', 'cat']),
columns=['Col1', 'Col2'])
>>> df
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https://api.github.com/repos/pandas-dev/pandas/issues/10441 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10441/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10441/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10441/events | https://github.com/pandas-dev/pandas/pull/10441 | 91,033,287 | MDExOlB1bGxSZXF1ZXN0Mzg1NzQ4MTU= | 10,441 | BUG: Bug fix implement __reduce__/__setstate__ for Period pickle support | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10442 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10442/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10442/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10442/events | https://github.com/pandas-dev/pandas/issues/10442 | 91,047,613 | MDU6SXNzdWU5MTA0NzYxMw== | 10,442 | ENH: Convert datetimelike index to strings with astype(str) | {
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- [x] Fix `.astype(str)` on `DatetimeIndex` to use call `.format()` (Index method)
~~\- [ ] Add `Series.dt.format()` accessor to call `.format()`~~ (#10110 does this with `.strftime`)
- [x] Change `Series.astype(str)` to call equiv of `Series.dt.format()` for `datetime64[ns]` dtype
Recently the ability t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10443 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10443/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10443/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10443/events | https://github.com/pandas-dev/pandas/pull/10443 | 91,059,366 | MDExOlB1bGxSZXF1ZXN0Mzg1ODYxOTQ= | 10,443 | ENH: Simplify using read_hdf for HDF files with one dataset | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-06-25T19:53:00Z | 2015-07-13T13:22:12Z | 2015-07-13T10:56:10Z | CONTRIBUTOR | null | Allow read_hdf to be used without a key when a single pandas object
is stored in a HDF file. Raises if multiple pandas objects found.
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https://api.github.com/repos/pandas-dev/pandas/issues/10444 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10444/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10444/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10444/events | https://github.com/pandas-dev/pandas/issues/10444 | 91,099,700 | MDU6SXNzdWU5MTA5OTcwMA== | 10,444 | Better error message when using DataFrame.hist() without numerical columns | {
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matplotlib version 1.4.3 (and produced different error message on older version)
``` python
import numpy as np
import pandas as pd
df = pd.DataFrame(np.random.rand(10,2))
df_o = df.astype(np.object)
df_o.hist()
```
```
ValueError Traceback (most recent call last)... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10445 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10445/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10445/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10445/events | https://github.com/pandas-dev/pandas/issues/10445 | 91,223,026 | MDU6SXNzdWU5MTIyMzAyNg== | 10,445 | Cannot fill in empty Panel with DataFrame | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2015-06-26T10:52:48Z | 2018-07-06T20:21:07Z | 2017-07-10T21:07:10Z | NONE | null | I'm not sure this is a bug, but it bit me recently.
I can fill-in an empty `DataFrame` with a `Series`:
```
In [1]: import pandas as pd
In [2]: d = pd.DataFrame()
In [3]: d[0] = pd.Series([1,2,3])
In [4]: d
Out[4]:
0
0 1
1 2
2 3
```
However, I cannot do the same for a `Panel`, even though it fails silently:
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... | 1 | 2015-06-26T12:55:57Z | 2019-10-21T20:06:20Z | null | MEMBER | null | The documentation on the extensive pandas IO tools is currently one big page: http://pandas.pydata.org/pandas-docs/stable/io.html.
I propose to split this in several files: a page with a general introduction to the IO tools, and then one page per format (writer/reader combo).
(this could be seen as a first start for... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-06-26T14:33:41Z | 2015-07-13T12:42:41Z | 2015-07-13T12:42:41Z | CONTRIBUTOR | null | Attempting to store a Panel4D of complext128 results in an error. This is true if I use table or fixed formats (different errors) [I am showing the last call from pandas as well as the actual error]
``` python
pd.Panel4D(np.tile(np.array([1+1j,2+2j]),[2,2,2,1])).to_hdf('complex.h5','complex',format='t')
Traceback (mo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10448 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10448/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10448/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10448/events | https://github.com/pandas-dev/pandas/issues/10448 | 91,289,783 | MDU6SXNzdWU5MTI4OTc4Mw== | 10,448 | Cython function group_var_float64 may return small negative values | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-06-26T16:14:25Z | 2015-07-08T14:19:57Z | 2015-06-26T18:07:27Z | CONTRIBUTOR | null | For certain well-chosen inputs, `group_var_float64` may return small negative values due to roundoff error. This then interferes with e.g. computing aggregate standard deviations:
``` python
>>> import pandas as pd
>>> import numpy as np
>>> df = pd.DataFrame({'a': (0, 0, 0), 'b': 0.832845131556193 * np.ones(3)})
>>> ... | {
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... | 10 | 2015-06-26T18:21:09Z | 2020-05-11T02:05:55Z | null | CONTRIBUTOR | null | Consider the following:
```
index = pd.date_range("2015-01-01", "2015-01-01 02:00", freq="1H", closed="left")
s = pd.Series(1, index=index)
s.resample("15T", fill_method="ffill", closed="left")
```
The result looks like this
<pre>2015-01-01 00:00:00 1
2015-01-01 00:15:00 1
2015-01-01 00:30:00 1
2015-01-01 0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10450 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10450/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10450/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10450/events | https://github.com/pandas-dev/pandas/pull/10450 | 91,349,078 | MDExOlB1bGxSZXF1ZXN0Mzg2ODQyODQ= | 10,450 | DOC: GH10414 Missing example in NA values in GroupBy | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2015-06-26T20:04:35Z | 2015-07-01T10:58:05Z | 2015-07-01T10:58:05Z | CONTRIBUTOR | null | closes #10414
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https://api.github.com/repos/pandas-dev/pandas/issues/10451 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10451/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10451/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10451/events | https://github.com/pandas-dev/pandas/issues/10451 | 91,459,326 | MDU6SXNzdWU5MTQ1OTMyNg== | 10,451 | BUG: display.precision option seems off-by-one | {
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"followers_url": "https://api.github.com/users/jr... | 9 | 2015-06-27T12:39:39Z | 2015-08-02T21:26:30Z | 2015-08-02T21:26:30Z | CONTRIBUTOR | null | I may very well be wrong on this, given how common an option it seems, but I am surprised that the "display.precision" option seems to limit the digits after the decimal to one less than specified.
``` python
In [1]: x = pd.Series(np.random.randn(5))
In [2]: x
Out[2]:
0 -0.163960
1 1.016273
2 0.861317
3 -... | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-06-27T13:43:35Z | 2016-03-30T12:39:02Z | 2016-03-30T12:39:02Z | MEMBER | null | `SparseSeries.shape` seems to return incorrect result ignoring shapes filled by `fill_value`.
```
s = pd.SparseSeries([0, 0, 1, 0], fill_value=0)
s
#0 0
#1 0
#2 1
#3 0
# dtype: int64
# BlockIndex
# Block locations: array([2], dtype=int32)
# Block lengths: array([1], dtype=int32)
len(s)
#4
# must be (4, )... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-06-27T14:36:26Z | 2015-06-27T14:40:08Z | 2015-06-27T14:39:07Z | CONTRIBUTOR | null | Very minor fix but `str.ljust()` and `str.rjust()` have broken links in the docstrings.
You can see in http://pandas.pydata.org/pandas-docs/version/0.16.2/generated/pandas.Series.str.ljust.html#pandas.Series.str.ljust that it should be linking to `str.ljust()` instead of `str.right()` (which doesn't exist)
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https://api.github.com/repos/pandas-dev/pandas/issues/10454 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10454/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10454/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10454/events | https://github.com/pandas-dev/pandas/pull/10454 | 91,478,138 | MDExOlB1bGxSZXF1ZXN0Mzg3MTA1NTg= | 10,454 | Attempt to fix issue #10366 encoding and categoricals hdf serialization. | {
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Probably not quite the right approach but want to run travis. Tests are a bit weak at this point (just testing for non-exceptions). Encoding issues might be relevant to other types besides categoricals (but categoricals raise exceptions when strings to mangled to non-uniqueness).
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https://api.github.com/repos/pandas-dev/pandas/issues/10456 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10456/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10456/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10456/events | https://github.com/pandas-dev/pandas/pull/10456 | 91,523,220 | MDExOlB1bGxSZXF1ZXN0Mzg3MTY0MTk= | 10,456 | DOC: Add warning for newbs not to edit auto-generated file | {
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You said "and more importantly prob a note in `internals.rst` about how/what to change", but I didn't understand that. `inter... | {
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pd.read_csv('Department_of_Recreation_and_Parks_Facility_and_Park_Information.csv')
and get this back:
-bash: syntax error near unexpected token `'Department_of_Recreation_and_Parks__Facility_and_Park_Information.csv''
The file exists in the folder
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Changed to use `assertIsInstance` in all cases, and make `assert_isinstance` show warning.
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https://api.github.com/repos/pandas-dev/pandas/issues/10459 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10459/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10459/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10459/events | https://github.com/pandas-dev/pandas/issues/10459 | 91,534,047 | MDU6SXNzdWU5MTUzNDA0Nw== | 10,459 | Timestamp.to_datetime() crashes with win32timezone.TimeZoneInfo objects | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2015-06-28T00:32:29Z | 2020-01-01T16:02:30Z | 2020-01-01T15:57:28Z | NONE | null | Thanks to the wonders of duck typing, `pandas.Timestamp` happily accepts `pywintypes.TimeType` objects (otherwise known as `pywintypes.datetime`), including those that employ the `win32timezone.TimeZoneInfo` object. And most methods work.
For some reason, `to_datetime` does not, and indeed it crashes:
```
import pan... | {
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import pandas as pd
import numpy as np
levels = ['foo', 'bar', 'baz', 'qux']
codes = np.random.randint(0, 4, size=100)
cats = pd.Categorical.from_codes(codes, levels, name='myfactor', ordered=True)
data = pd.DataFrame(np.random.randn(100, 4))
grouped = data.groupby(cats)
desc_result = grouped.describe()
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... | 9 | 2015-06-28T01:04:10Z | 2021-04-18T07:09:14Z | null | MEMBER | null | Currently, `MultiIndex.get_level_values` handles both names and levels, it return different levels depending on its name (like `.ix`). Adding an option (or separate method) like `.loc` and `.iloc` to avoid any unexpected results?
```
idx = pd.MultiIndex.from_tuples([(1, 'A'), (2, 'B')])
idx.get_level_values(0)
# Int64... | {
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... | 10 | 2015-06-28T06:11:29Z | 2015-10-12T01:32:14Z | 2015-10-11T16:00:58Z | CONTRIBUTOR | null | closes #10445
I based this bugfix off how DataFrame handles the analogous situation ‒ being intialized to empty and then having a series added (cf. [DataFrame._ensure_valid_index](https://github.com/pydata/pandas/blob/master/pandas/core/frame.py#L2167))
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I'm currently writing code that opera... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10464 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10464/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10464/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10464/events | https://github.com/pandas-dev/pandas/pull/10464 | 91,586,068 | MDExOlB1bGxSZXF1ZXN0Mzg3MjM2NTQ= | 10,464 | BUG: Series.map using categorical Series raises AttributeError | {
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Based on #9848, using `.get_values` should be avoided?
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https://api.github.com/repos/pandas-dev/pandas/issues/10465 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10465/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10465/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10465/events | https://github.com/pandas-dev/pandas/pull/10465 | 91,588,454 | MDExOlB1bGxSZXF1ZXN0Mzg3MjM4NjI= | 10,465 | BUG: MultiIndex.get_level_values created from Categorical raises AttributeError | {
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xref: #10464.
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https://api.github.com/repos/pandas-dev/pandas/issues/10466 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10466/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10466/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10466/events | https://github.com/pandas-dev/pandas/pull/10466 | 91,631,913 | MDExOlB1bGxSZXF1ZXN0Mzg3MzA4MTc= | 10,466 | ENH: Add pipe method to GroupBy (fixes #10353) | {
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... | 21 | 2015-06-28T19:51:19Z | 2015-12-06T19:09:55Z | 2015-12-06T19:09:55Z | NONE | null | closes #10353, extends the "pipe" method to a GroupBy object to allow one to chain it with NDFrame.pipe calls
- Moves the functionality of "pipe" from NDFrame into generics._pipe to avoid code duplication
- Leverages this in GroupBy object
- Adds unit test
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https://api.github.com/repos/pandas-dev/pandas/issues/10467 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10467/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10467/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10467/events | https://github.com/pandas-dev/pandas/issues/10467 | 91,767,392 | MDU6SXNzdWU5MTc2NzM5Mg== | 10,467 | BUG: read_csv: invalid index from header-only input file with multiindex. | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-06-29T10:28:49Z | 2015-07-07T09:30:45Z | 2015-07-07T09:30:45Z | CONTRIBUTOR | null | ``` Python
import pandas as pd
import cStringIO as stringio
df = pd.read_csv(stringio.StringIO("x,y,z"), index_col=["x", "y"])
print df.columns
print df.index.names
```
Output:
```
$ python x.py
Index([u'y'], dtype='object')
[u'x', u'y']
```
Expected column name is "z".
## INSTALLED VERSIONS
commit: 01995b2c2c759c... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10468 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10468/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10468/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10468/events | https://github.com/pandas-dev/pandas/issues/10468 | 91,768,396 | MDU6SXNzdWU5MTc2ODM5Ng== | 10,468 | Iterating over groups skips groups with nan in the name | {
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"id": ... | closed | false | null | [] | null | 8 | 2015-06-29T10:35:38Z | 2017-12-19T20:06:47Z | 2015-06-29T11:07:26Z | CONTRIBUTOR | null | Today I discovered a strange behaviour when iterating over groups where the group name contains a nan. Take the following data frame and group it. As expected there are two groups:
``` python
In [1]: df = pd.DataFrame([['a', 1, 1], ['b', sp.nan, 2]], columns = ['a', 'b', 'c'])
In [2]: grouped = df.groupby(['a', 'b'])... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10469 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10469/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10469/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10469/events | https://github.com/pandas-dev/pandas/pull/10469 | 91,806,906 | MDExOlB1bGxSZXF1ZXN0Mzg3NzQ3NTU= | 10,469 | BUG: Fix csv_read bugs when using empty input. GH10467 & GH10413 | {
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closes #10467
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https://api.github.com/repos/pandas-dev/pandas/issues/10470 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10470/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10470/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10470/events | https://github.com/pandas-dev/pandas/issues/10470 | 91,828,422 | MDU6SXNzdWU5MTgyODQyMg== | 10,470 | CLN: StringIO from io instead of from StringIO | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10471 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10471/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10471/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10471/events | https://github.com/pandas-dev/pandas/issues/10471 | 91,860,776 | MDU6SXNzdWU5MTg2MDc3Ng== | 10,471 | test_set_locale fails if LC_ALL is set outside | {
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"d... | closed | false | null | [] | null | 1 | 2015-06-29T17:19:03Z | 2021-04-18T07:13:19Z | 2021-04-18T07:13:19Z | CONTRIBUTOR | null | ```
~/pandas-0.16.2+git58-g01995b2# LC_ALL=C.UTF-8 nosetests3 -s -v /tmp/buildd/pandas-0.16.2+git58-g01995b2/debian/tmp/usr/lib/python3/dist-packages/pandas/tools/tests/test_util.py
test_datetimeindex (pandas.tools.tests.test_util.TestCartesianProduct) ... ok
test_simple (pandas.tools.tests.test_util.TestCartesianProdu... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10472 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10472/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10472/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10472/events | https://github.com/pandas-dev/pandas/pull/10472 | 91,861,641 | MDExOlB1bGxSZXF1ZXN0Mzg3OTY3MzI= | 10,472 | ENH: Make group_var_ use Welford's algorithm. | {
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This PR reimplements the Cython functions `group_var_float64` and `group_var_float32` to use Welford's algorithm, rather than the sum-of-squares method, which is numerically unstable. This came up in #10448; see also #10242 for more discussion.
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https://api.github.com/repos/pandas-dev/pandas/issues/10473 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10473/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10473/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10473/events | https://github.com/pandas-dev/pandas/pull/10473 | 91,887,694 | MDExOlB1bGxSZXF1ZXN0Mzg4MDgzMjE= | 10,473 | BUG: Enable complex values to be written to HDF | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2015-06-29T19:27:56Z | 2015-07-13T13:22:09Z | 2015-07-13T12:42:41Z | CONTRIBUTOR | null | Enable table format to be used to store complex values
in DataFrames, Panels and Panel4Ds.
Add tests for both fixed and panel.
Add exception when attempting to write Series with complex values.
closes #10447
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https://api.github.com/repos/pandas-dev/pandas/issues/10474 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10474/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10474/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10474/events | https://github.com/pandas-dev/pandas/issues/10474 | 91,917,441 | MDU6SXNzdWU5MTkxNzQ0MQ== | 10,474 | Feature Request: Add support for 'Allow Large Results' to BigQuery connector | {
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"followers_url": "https://api.github.com/users/jorisva... | 5 | 2015-06-29T21:44:36Z | 2017-02-26T20:22:29Z | 2017-02-26T20:11:08Z | NONE | null | gbq.py currently returns an error if the result of a query is what Google considers to be 'Large'. The google api allows jobs to be sent with a flag to allow large results. It would be very beneficial to provide this as an option in the BigQuery connector.
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https://api.github.com/repos/pandas-dev/pandas/issues/10475 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10475/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10475/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10475/events | https://github.com/pandas-dev/pandas/issues/10475 | 92,090,515 | MDU6SXNzdWU5MjA5MDUxNQ== | 10,475 | Series.shift speed up | {
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... | 3 | 2015-06-30T13:14:38Z | 2020-03-31T04:55:31Z | 2020-03-31T04:55:31Z | NONE | null | Series.shift() is slow when freq parameter is supplied
```
ts = pd.util.testing.makeTimeSeries(10000)
ts.shift(5, 'D') # takes 0.5 sec
ts.shift(5, np.timedelta64(1, 'D')) # takes 0.16 sec
ts2 = ts.copy()
ts2.index = ts.index + np.timedelta64(5, 'D') # takes < 0.001 sec
```
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-06-30T15:40:42Z | 2016-05-25T12:09:25Z | 2016-05-25T12:09:25Z | CONTRIBUTOR | null | Only thing I changed from my usually working reduction pipeline is to try `engine="python"` (because I wanted to use `nrows` for a smaller test-read, but that fails as well, and I thought maybe the python engine is buggy currently):
``` python
$ python reduction.py ~/data/planet4/2015-06-21_planet_four_classifications... | {
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closes #10763
ToDos:
- [x] doc updates
- [x] test with `Series.dt.*`
- [x] test with csv/HDF5
- [x] nat setting borked ATM
- [x] HDF5 example from 0.16.2
~~\- [ ] get_values/values - make consistent~~
~~\- [ ] maybe move `DatetimeTZBlock.shift` mostly to `DatetimeIndex.shift`~~
Also
- This cleans up t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10478 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10478/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10478/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10478/events | https://github.com/pandas-dev/pandas/issues/10478 | 92,184,629 | MDU6SXNzdWU5MjE4NDYyOQ== | 10,478 | test_concat_categorical fails on 32bit | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-06-30T19:55:38Z | 2015-06-30T21:21:14Z | 2015-06-30T21:21:01Z | CONTRIBUTOR | null | ``` ======================================================================
FAIL: test_concat_categorical (pandas.tests.test_categorical.TestCategoricalAsBlock)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/tmp/buildd/pandas-0.16.2+git58-g01995b2/debia... | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-07-01T04:52:03Z | 2015-07-02T04:17:15Z | 2015-07-01T10:53:21Z | CONTRIBUTOR | null | I discovered entirely by accident that the `na_values` in `pd.read_*` can be a string. According to the docstring, it can only be a sequence or a dict. This PR fixes that.
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https://api.github.com/repos/pandas-dev/pandas/issues/10480 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10480/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10480/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10480/events | https://github.com/pandas-dev/pandas/issues/10480 | 92,328,222 | MDU6SXNzdWU5MjMyODIyMg== | 10,480 | numeric_only inconsistency with pandas Series | {
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In [1]: import pandas as pd
In [2]: pd.Series([1,2,3]).sum(numeric_only=False)
Out[2]: 6
In [3]: pd.Series([1,2,3]).sum(numeric_only=True)
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
<ipython-input-3-2c46bd... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10481 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10481/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10481/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10481/events | https://github.com/pandas-dev/pandas/issues/10481 | 92,350,424 | MDU6SXNzdWU5MjM1MDQyNA== | 10,481 | DOC: na_fvalues argument for read_csv not documented in docstring | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10482 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10482/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10482/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10482/events | https://github.com/pandas-dev/pandas/issues/10482 | 92,400,857 | MDU6SXNzdWU5MjQwMDg1Nw== | 10,482 | BUG: Index doesn't take over the Categorical name | {
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```
import pandas as pd
c = pd.Categorical([1, 2, 3], name='xxx')
pd.Series(c)
#0 1
#1 2
#2 3
# Name: xxx, dtype: category
# Categories (3, int64): [1, 2, 3]
```
But `Index` doesn't.
```
pd.Index(c)
# CategoricalIndex([1, 2, 3], categories=[1, 2, 3], ordered=Fa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10483 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10483/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10483/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10483/events | https://github.com/pandas-dev/pandas/pull/10483 | 92,470,164 | MDExOlB1bGxSZXF1ZXN0MzkwMTgxNjA= | 10,483 | Series.from_csv not loading header names | {
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"... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-07-01T19:47:21Z | 2015-07-07T15:52:31Z | 2015-07-07T15:52:31Z | CONTRIBUTOR | null | Series.from_csv at the moment does not load the series.name and series.index.name when the header keyword argument is stated.
This was introduced in 6078fba9410918baa486ca008cc9e3ba066c03ec. The issue was that `Series.from_csv` uses `DataFrame.from_csv`, which automatically indexes columns (in practice, the index col... | {
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... | 1 | 2015-07-01T23:15:31Z | 2019-10-21T20:07:56Z | null | CONTRIBUTOR | null | from #10468
```
In [40]: df = DataFrame({'A' : [1,2,3]},index=pd.MultiIndex.from_tuples([(1,np.nan),(1,1),(2,1)],names=['first','second']))
In [41]: df
Out[41]:
A
first second
1 NaN 1
1 2
2 1 3
In [42]: df.groupby(level='second').sum()
Out[42]:
A
second
1 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10485 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10485/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10485/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10485/events | https://github.com/pandas-dev/pandas/issues/10485 | 92,505,488 | MDU6SXNzdWU5MjUwNTQ4OA== | 10,485 | More descriptive ylabel for Series.hist() | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2015-07-01T23:19:02Z | 2015-07-15T11:13:35Z | 2015-07-15T11:13:35Z | CONTRIBUTOR | null | ```
s = pd.Series(np.random.randn(100))
s.plot(kind='hist')
s.hist()
```
Running `s.plot(kind='hist')` labels the y axis with the word 'Degree'. A more informative label might be 'count', 'frequency', or 'density'.
Also, it seems strange that `s.plot(kind='hist')` and `s.hist()` produce plots with different labels / ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10486 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10486/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10486/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10486/events | https://github.com/pandas-dev/pandas/issues/10486 | 92,510,433 | MDU6SXNzdWU5MjUxMDQzMw== | 10,486 | BUG: query with invalid dtypes should fallback to python engine | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-07-01T23:50:49Z | 2016-05-07T17:12:30Z | 2016-05-07T17:12:30Z | NONE | null | The following call of `df.query()` produces an error:
```
...
File "/Applications/anaconda/lib/python3.4/site-packages/numexpr/necompiler.py", line 629, in getType
raise ValueError("unkown type %s" % a.dtype.name)
ValueError: unkown type str128
```
in pandas 0.15.2
```
# -*- coding: utf-8 -*-
import re
import panda... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10488 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10488/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10488/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10488/events | https://github.com/pandas-dev/pandas/pull/10488 | 92,543,643 | MDExOlB1bGxSZXF1ZXN0MzkwNDcxMzc= | 10,488 | DOC: Better explain the behaviour of na_values | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-07-02T04:17:02Z | 2015-07-02T07:42:55Z | 2015-07-02T07:42:55Z | CONTRIBUTOR | null | According to the suggestion of @jorisvandenbossche from https://github.com/pydata/pandas/pull/10479, changing some wording in the docs.
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https://api.github.com/repos/pandas-dev/pandas/issues/10489 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10489/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10489/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10489/events | https://github.com/pandas-dev/pandas/issues/10489 | 92,560,196 | MDU6SXNzdWU5MjU2MDE5Ng== | 10,489 | Pandas: why pandas.Series.std() is quite different from numpy.std() | {
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> > numpy.std([766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346])
> >
> > 0
> >
> > pd.Series([766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346]).std(ddof=0)
> >... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10490 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10490/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10490/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10490/events | https://github.com/pandas-dev/pandas/pull/10490 | 92,627,947 | MDExOlB1bGxSZXF1ZXN0MzkwNzgzMzY= | 10,490 | TST/ERR: GH10369 read_msgpack checks argument type | {
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... | 5 | 2015-07-02T16:25:38Z | 2018-11-28T21:03:51Z | null | NONE | null | When writing a DataFrame to hdf format ('to_hdf' method) you cannot pass a file handle instead of a string. i.e. you can't:
``` python
with open('test.hdf') as f:
df.to_hdf(f, "df")
```
This raises an error:
```
Traceback (most recent call last):
File "<stdin>", line 2, in <module>
File "C:\Anaconda\lib\site... | {
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"followers_url": "https://api.github.com/users/j... | 4 | 2015-07-02T17:00:45Z | 2020-10-08T01:23:14Z | 2020-10-08T01:23:14Z | CONTRIBUTOR | null | It's not clear from the docs that indexing with a boolean `ndarray` isn't the same as indexing with a boolean `Series`. It took me a while to realise that:
``` python
import pandas as pd
df = pd.DataFrame([[1, 2], [3, 4], [5, 6]], list('abc'), ['one', 'two'])
sr = (df['one'] > 2)
df.loc[sr, 'two'] # This is ok
df... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10493 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10493/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10493/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10493/events | https://github.com/pandas-dev/pandas/pull/10493 | 92,691,938 | MDExOlB1bGxSZXF1ZXN0MzkxMDczMzg= | 10,493 | ENH: GH10485 'Frequency' label for Series.plot | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2015-07-02T17:36:05Z | 2015-07-11T06:45:10Z | 2015-07-11T06:45:10Z | CONTRIBUTOR | null | More informative label for histogram.
Conversation in #10485
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https://api.github.com/repos/pandas-dev/pandas/issues/10494 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10494/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10494/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10494/events | https://github.com/pandas-dev/pandas/issues/10494 | 92,827,760 | MDU6SXNzdWU5MjgyNzc2MA== | 10,494 | BUG: convert_objects(convert_dates='coerce') fails on single-valued series | {
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"color": "009... | closed | false | null | [] | null | 1 | 2015-07-03T09:02:39Z | 2015-07-03T11:57:42Z | 2015-07-03T11:57:26Z | NONE | null | With an unconvertible value (like e.g. "2014-12-32"), `convert_objects(convert_dates='coerce')` is supposed to return `NaT`. When run on a series with a single unconvertible value it gives back the original string instead.
``` python
>>> from pandas import Series
>>> Series(['2014-12-32']).convert_objects(convert_date... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10495 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10495/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10495/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10495/events | https://github.com/pandas-dev/pandas/issues/10495 | 92,871,047 | MDU6SXNzdWU5Mjg3MTA0Nw== | 10,495 | .shift() on Categorical raises "'Categorical' object has no attribute 'flags'" | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-07-03T13:01:56Z | 2015-07-06T12:44:38Z | 2015-07-06T12:44:38Z | CONTRIBUTOR | null | Not sure if this is related to #10324 .
Running master with python 3.4.3.
``` python
import pandas
values = ['a', 'b', 'c', 'd']
a = pandas.Series(values)
b = pandas.Series(values, dtype='category')
print(a.shift()) # ok
print(b.shift()) # error
```
Error looks like this:
```
$ python f.py
0 NaN
1 a
2 ... | {
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... | 8 | 2015-07-03T13:35:55Z | 2015-07-17T16:15:56Z | 2015-07-17T16:15:55Z | NONE | null | When reading a table while specifying duplicate column names - let's say two different names - pandas 0.16.1 will copy the last two columns of the data over and over again.
I opened a thread on this here:
http://stackoverflow.com/questions/31207560/pandas-read-table-with-duplicate-names
Is this a bug or an intended b... | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-07-03T13:42:01Z | 2015-07-18T00:03:30Z | 2015-07-18T00:03:27Z | CONTRIBUTOR | null | Should resolve #9416.
CategoricalBlocks always seem to have ndim=1, even if multiple
categoricals are in a frame with the same categories. This simplifies
the axis shift logic somewhat.
Note that dataframe shift with axis=1 still doesn't work with multiple
categorical columns, since they are each a different block.
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Waiting for Travis and will review further.
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https://api.github.com/repos/pandas-dev/pandas/issues/10499 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10499/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10499/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10499/events | https://github.com/pandas-dev/pandas/pull/10499 | 92,880,365 | MDExOlB1bGxSZXF1ZXN0MzkxNzY4MzQ= | 10,499 | Updated to_hdf doc string | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-07-03T15:04:30Z | 2015-07-04T12:49:42Z | 2015-07-04T11:29:41Z | MEMBER | null | The result of `DataFrame.quantile` should have `Float64Index` as below, but current test case doesn't check it.
```
import pandas as pd
pd.DataFrame([1, 2, 3, 4]).quantile([0.5, 0.75]).index
# Float64Index([0.5, 0.75], dtype='float64')
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10501 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10501/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10501/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10501/events | https://github.com/pandas-dev/pandas/pull/10501 | 92,894,021 | MDExOlB1bGxSZXF1ZXN0MzkxODI4MTU= | 10,501 | TST: Fix test for datetime categorical | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-07-03T15:15:40Z | 2015-07-06T12:59:19Z | 2015-07-06T12:54:05Z | MEMBER | null | Related to #10465, but different part.
Current `test_groupby_datetime_categorical` in `test_groupby.py` is incorrect, the actual result returns `CategoricalIndex` as level 0, otherwise expected result uses `DatetimeIndex` as level 0. Changed to use the same dtype and added explicit comparison.
### Actual Result (curre... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10502 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10502/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10502/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10502/events | https://github.com/pandas-dev/pandas/pull/10502 | 92,898,558 | MDExOlB1bGxSZXF1ZXN0MzkxODQ1MDE= | 10,502 | CLN: remove na_fvalues from TextFileReader (read_csv et al) signature (GH10481) | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-07-03T15:41:16Z | 2015-07-13T13:14:25Z | 2015-07-13T13:14:25Z | MEMBER | null | Closes #10481
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