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https://api.github.com/repos/pandas-dev/pandas/issues/6401 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6401/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6401/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6401/events | https://github.com/pandas-dev/pandas/pull/6401 | 27,834,612 | MDExOlB1bGxSZXF1ZXN0MTI2NzQ5MTU= | 6,401 | BUG: Float64Index with nans not comparing correctly | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6402 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6402/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6402/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6402/events | https://github.com/pandas-dev/pandas/issues/6402 | 27,838,616 | MDU6SXNzdWUyNzgzODYxNg== | 6,402 | using DataFrame.interpolate with inplace=True causes error | {
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```
/Library/Python/2.7/site-packages/pandas/core/generic.pyc in interpolate(self, method, axis, limit, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6403 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6403/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6403/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6403/events | https://github.com/pandas-dev/pandas/issues/6403 | 27,843,453 | MDU6SXNzdWUyNzg0MzQ1Mw== | 6,403 | ExcelFile parse of empty sheet fails with "IndexError: list index out of range" | {
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``` python
import pandas as pd
xl_file ... | {
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In [3]: dates = pd.date_range('01-Jan-2015', '01-Jan-2016', freq='MS')
...: s = pd.TimeSeries(1, dates)
...: pd.infer_freq(s)
...:
Traceback (most recent call last):
File "<ipython-input-3-a7de7a7e9245>", line 3, in <module>
pd.infer_freq(s)
File "C:\dev\bin\Anaconda\lib\site-packages\pan... | {
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API: pd.infer_freq() will now raise a TypeError if given an invalid Series/Index type (GH6407)
closes #6407
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... | 0 | 2014-02-19T13:40:36Z | 2020-03-31T04:20:56Z | null | CONTRIBUTOR | null | http://stackoverflow.com/questions/21878599/pandas-drops-timestamp-columns-in-resample
```
init_time=pd.date_range(start='2010-01-01 00:00', end='2010-01-05 00:00', freq='12H')
valid_time=pd.date_range(start='2010-01-01 00:00', end='2010-01-05 00:00', freq='12H')
data = np.random.random(len(valid_time))
frame = pd.Dat... | {
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fails on 32-bit
```
In [1]: df = pd.DataFrame({"A": range(2), "B": [pd.Timestamp('2000-01-1')]*2})
In [2]: df
Out[2]:
A B
0 0 2000-01-01
1 1 2000-01-01
[2 rows x 2 columns]
In [3]: df.groupby("A")["B"].transform(min)
Out[3]:
0 2000-01-01
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https://api.github.com/repos/pandas-dev/pandas/issues/6415 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6415/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6415/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6415/events | https://github.com/pandas-dev/pandas/issues/6415 | 27,946,062 | MDU6SXNzdWUyNzk0NjA2Mg== | 6,415 | BUG: to_datetime ignores utc=True when arg is Series | {
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... | 10 | 2014-02-20T09:06:33Z | 2017-09-01T12:19:31Z | 2017-09-01T12:19:31Z | CONTRIBUTOR | null | Is this a bug or a feature that I don't understand:
``` python
data = ['20100102 121314', '20100102 121315']
print (pd.to_datetime(data, format='%Y%m%d %H%M%S',
utc=True)[0]).__repr__()
print (pd.to_datetime(pd.Series(data), format='%Y%m%d %H%M%S',
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https://api.github.com/repos/pandas-dev/pandas/issues/6416 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6416/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6416/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6416/events | https://github.com/pandas-dev/pandas/issues/6416 | 27,961,923 | MDU6SXNzdWUyNzk2MTkyMw== | 6,416 | ENH: SQL through SQLAlchemy - performance | {
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... | 8 | 2014-02-20T13:40:31Z | 2018-07-06T21:57:26Z | 2018-07-06T21:57:26Z | CONTRIBUTOR | null | This issue is to track performance measurement and improvements to the SQLalchemy-based SQL io support in pandas.
TODO
- [ ] Get perfromance measurements working
- [ ] Determine bottlenecks
- [ ] Address bottleneck
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https://api.github.com/repos/pandas-dev/pandas/issues/6417 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6417/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6417/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6417/events | https://github.com/pandas-dev/pandas/pull/6417 | 27,962,136 | MDExOlB1bGxSZXF1ZXN0MTI3NDU5MTQ= | 6,417 | ENH #6416 improve performance on SQL insert | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6420 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6420/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6420/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6420/events | https://github.com/pandas-dev/pandas/pull/6420 | 27,964,846 | MDExOlB1bGxSZXF1ZXN0MTI3NDc0MzU= | 6,420 | ENH #6416: performance improvements on write | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6421 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6421/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6421/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6421/events | https://github.com/pandas-dev/pandas/pull/6421 | 27,975,073 | MDExOlB1bGxSZXF1ZXN0MTI3NTM0Mjc= | 6,421 | REGR: Bug in Series.reindex when specifying a method with some nan values was inconsistent (GH6418) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6422 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6422/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6422/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6422/events | https://github.com/pandas-dev/pandas/pull/6422 | 28,000,601 | MDExOlB1bGxSZXF1ZXN0MTI3Njg4MDE= | 6,422 | ENH: Add functions for creating dataframes with NaNs | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6423 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6423/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6423/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6423/events | https://github.com/pandas-dev/pandas/issues/6423 | 28,003,336 | MDU6SXNzdWUyODAwMzMzNg== | 6,423 | Passing invalid unit to to_timedelta is silently ignored | {
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```
In [25]: pd.to_timedelta([2,10], unit="days")
Out[25]:
0 00:00:00.000000
1 00:00:00.000000
dtype: timedelta64[ns]
```
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https://api.github.com/repos/pandas-dev/pandas/issues/6424 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6424/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6424/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6424/events | https://github.com/pandas-dev/pandas/issues/6424 | 28,005,450 | MDU6SXNzdWUyODAwNTQ1MA== | 6,424 | interpolate w/ method=time does not work with timedeltas | {
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"followers_url": "https://api.github.com/users/jr... | 14 | 2014-02-20T23:17:25Z | 2016-12-10T11:20:10Z | 2016-12-10T11:19:49Z | CONTRIBUTOR | null | ```
In [98]: pd.DataFrame({'v':[1,2,3]},index=pd.to_timedelta([1,2,3], unit="d")).interpolate(method="time")
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-98-9c399944f329> in <module>()
----> 1 pd.D... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6425 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6425/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6425/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6425/events | https://github.com/pandas-dev/pandas/issues/6425 | 28,005,771 | MDU6SXNzdWUyODAwNTc3MQ== | 6,425 | groupby w/ levels on MultiIndex and then interpolate | {
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```
In [111]:
df_1 = pd.DataFrame({'v':[1,np.nan,3]},index=pd.to_datetime([1,2,3], unit="d"))
pd.concat({'a':df_1, 'b':df_1}).groupby(level=0).apply(lambda x:x.interpolate(method="time"))
---------------------------------------------------------------------------
ValueErro... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6426 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6426/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6426/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6426/events | https://github.com/pandas-dev/pandas/issues/6426 | 28,008,183 | MDU6SXNzdWUyODAwODE4Mw== | 6,426 | indexing using iterator (Frame.ix[#]) changed - .ix does not work, .iloc does | {
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Not sure if this is known or not - couldn't find anything like it in the list of problems. I use data frames that basically have a column of serial numbers, and then two columns after that that contain multidimensional arrays representing data for each serial number (say md1 and md2). On both pandas 0.13.0 an... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6427 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6427/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6427/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6427/events | https://github.com/pandas-dev/pandas/issues/6427 | 28,014,757 | MDU6SXNzdWUyODAxNDc1Nw== | 6,427 | SparseDataFrame.shift does not respond to axis | {
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"f... | 4 | 2014-02-21T02:33:14Z | 2019-09-18T14:02:17Z | 2019-09-18T14:02:17Z | CONTRIBUTOR | null | The shift method in SparseDataFrame does not respond to axis correctly.
```
>>> import pandas as pd
>>> import numpy as np
>>> df = pd.SparseDataFrame(np.random.rand(10,5))
>>> df.shift(1)
0 1 2 3 4
0 NaN NaN NaN NaN NaN
1 0.015673 0.456047 0.4... | {
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In [265]: s = pd.Series(['10/18/2006', '10/18/2008', ' '])
In [266]: pd.to_datetime(s)
Out[266]:
0 2006-10-18
1 2008-10-18
2 2014-02-20
dtype: datetime64[ns]
In [268]: pd.to_datetime(s, errors='raise')
Out[268]:
0 2006-10-18
1 2008-10-18
2 2014-02-20
dtype: datetime64[ns]
```
_Note: Can use `pd.to_da... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6429 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6429/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6429/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6429/events | https://github.com/pandas-dev/pandas/pull/6429 | 28,018,515 | MDExOlB1bGxSZXF1ZXN0MTI3Nzk1MzI= | 6,429 | BUG: punt to user when passing overlapping replacement values in a nested dict | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6430 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6430/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6430/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6430/events | https://github.com/pandas-dev/pandas/pull/6430 | 28,019,059 | MDExOlB1bGxSZXF1ZXN0MTI3Nzk4MTc= | 6,430 | BUG: correctly tokenize local variable references | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6431 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6431/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6431/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6431/events | https://github.com/pandas-dev/pandas/issues/6431 | 28,038,275 | MDU6SXNzdWUyODAzODI3NQ== | 6,431 | apply function to groupby-ed dataframe, can't take args | {
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File "d:\Scripts\new model parameters\genNewParametersFromDb.py", line 99, in <module>
df.groupby(['pooltype1','CollType','ltv_buc', 'ltv']).apply(getTrans12,args=(6,)),
File "C:\Anaconda\Lib\site-packages\pandas\core\groupby.py", line 331, in apply
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https://api.github.com/repos/pandas-dev/pandas/issues/6432 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6432/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6432/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6432/events | https://github.com/pandas-dev/pandas/pull/6432 | 28,040,290 | MDExOlB1bGxSZXF1ZXN0MTI3OTEwMzk= | 6,432 | CLN: minimize tokenizer passes | {
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"labels_url": "htt... | 1 | 2014-02-21T17:24:20Z | 2014-03-22T21:13:10Z | 2014-03-22T21:12:26Z | CONTRIBUTOR | null | I have a standard DataFrame indexed by
``` python
<class 'pandas.tseries.index.DatetimeIndex'>
[2009-07-08 07:00:00.134000, ..., 2009-07-08 10:00:01.297000]
Length: 84384, Freq: None, Timezone: None
```
and 189 columns named like this:
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https://api.github.com/repos/pandas-dev/pandas/issues/6435 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6435/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6435/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6435/events | https://github.com/pandas-dev/pandas/pull/6435 | 28,061,655 | MDExOlB1bGxSZXF1ZXN0MTI4MDM0NTI= | 6,435 | DOC: link to pandas-cookbook instructions | {
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see: https://github.com/jvns/pandas-cookbook/issues/7
this SO question: https://stackoverflow.com/questions/21868105/problems-with-pandas-tutorial-missing-file-bikes-csv-and-special-characters-in
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https://travis-ci.org/pydata/pandas/jobs/19331373
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```
df = pd.util.testing.makeDataFrame() # yes!
df["group"] = 0
df.ix[range... | {
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API: concat will now concatenate mixed Series and DataFrames, closes #2385
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"labels_url": "htt... | 5 | 2014-02-22T01:09:16Z | 2014-07-01T07:16:44Z | 2014-02-23T21:59:25Z | MEMBER | null | This breaks the new `pandas.MultiIndex.from_product` function when one of the product arrays is DatetimeIndex. Observe:
```
>>> import pandas as pd
>>> from pandas.tools.util import cartesian_product
>>> x, y = cartesian_product([[1, 2], pd.date_range('2000-01-01', periods=2)])
>>> print x
[1 1 2 2]
>>> print y.values... | {
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There's an API change though: no type inference will now happen upon resulting index, e.g. here's what it would look like on current master:
``` python
In [1]: pd.Index([1,2,3, 'a', 'b', 'c'])
Out[1]: Index([1, 2, 3, u'a', u'b', u'c'], dtype='object')... | {
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BUG/TST: iloc will now raise IndexError on out-of-bounds list indexers promotoing consistency with python/numpy syntax. The out-of-bounds for slice indexers will continue to work (again for consistency) (#6296 / #6299)
DOC: makes tz attribute default to `None` to r... | {
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```
>>> from pandas import Index
>>> import numpy as np
>>> idx1 = Index([1, 2, np.nan])
>>> idx2 = Index([0, 1, np.nan])
>>> result = idx1.sy... | {
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closes #6445
This a very specific bug fix. Only using `lxml` exposes this bug, whereas using
`bs4` raises an exception. `lxml` drops data which allows it to parse the multiindex
header differently and succeed.
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https://api.github.com/repos/pandas-dev/pandas/issues/6449 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6449/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6449/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6449/events | https://github.com/pandas-dev/pandas/issues/6449 | 28,114,637 | MDU6SXNzdWUyODExNDYzNw== | 6,449 | min() and max() on df.index cause maximum recursion depth exceeded Error | {
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import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.random((4, 3)), columns=['A', 'B', 'C'])
df.index.max() # This will cause RuntimeError: maximum recursion depth exceeded
```
Happens on pandas v0.13.1
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https://api.github.com/repos/pandas-dev/pandas/issues/6450 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6450/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6450/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6450/events | https://github.com/pandas-dev/pandas/pull/6450 | 28,116,394 | MDExOlB1bGxSZXF1ZXN0MTI4MzExNjY= | 6,450 | BLD: add benchmarks for all single-axis indexers | {
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"closed_at": "2015-03-23T10:50:37Z",
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It is currently in WIP state, but the ideas and comments are welcome. Multi-axis indexers are left for future to avoid overcomplicating things from the beginning.
Part of functionality implemented in this PR is c... | {
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```
df = pd.util.testing.makeDataFrame()
df.index.name = 'name'
df.set_index(df.index)
df.set_index(df.index).index.names
```
MultiIndex
```
from statsmodels.datasets import grunfeld
data = sm.datasets.grunfeld.load_pandas().data
data = data.set_index(['firm', 'year'])
data.set_index(data.index).index.names
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https://api.github.com/repos/pandas-dev/pandas/issues/6453 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6453/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6453/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6453/events | https://github.com/pandas-dev/pandas/pull/6453 | 28,127,356 | MDExOlB1bGxSZXF1ZXN0MTI4MzU1OTM= | 6,453 | BUG/TST: sorting of NaNs on sym_diff | {
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"gi... | [] | closed | false | null | [] | null | 7 | 2014-02-23T21:09:43Z | 2017-05-15T21:15:51Z | 2014-02-23T21:51:05Z | CONTRIBUTOR | null | Closes https://github.com/pydata/pandas/issues/6444, which was failing on Python 3.4
I don't actually have python 3.4 running yet, virtualenv is complaining about my 3.4 executable. These test _should_ pass on 2.6+.
I put the release note under the bug section, but I can move it to the API section if you think that'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6454 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6454/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6454/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6454/events | https://github.com/pandas-dev/pandas/issues/6454 | 28,128,416 | MDU6SXNzdWUyODEyODQxNg== | 6,454 | travis failure | {
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https://travis-ci.org/pydata/pandas/jobs/19460011
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https://api.github.com/repos/pandas-dev/pandas/issues/6455 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6455/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6455/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6455/events | https://github.com/pandas-dev/pandas/pull/6455 | 28,128,599 | MDExOlB1bGxSZXF1ZXN0MTI4MzYxMzc= | 6,455 | str_extract should work for timeseries, bug 6348 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6456 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6456/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6456/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6456/events | https://github.com/pandas-dev/pandas/issues/6456 | 28,129,107 | MDU6SXNzdWUyODEyOTEwNw== | 6,456 | read_html and read_json should provide a cache | {
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"f... | 7 | 2014-02-23T22:24:04Z | 2014-12-11T18:26:15Z | 2014-02-24T20:24:02Z | NONE | null | Hello,
`pandas.io.html.read_html` should provide a cache such as what requests_cache provides
https://requests-cache.readthedocs.org/en/latest/
persistence into sqlite, mongodb, redis... is very convenient.
Maybe some other pandas functions could also use this cache mechanism.
`pandas.io.json.read_json` for example
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https://api.github.com/repos/pandas-dev/pandas/issues/6457 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6457/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6457/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6457/events | https://github.com/pandas-dev/pandas/issues/6457 | 28,129,362 | MDU6SXNzdWUyODEyOTM2Mg== | 6,457 | isnull() and notnull() - documentation | {
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"labels_url": "htt... | 3 | 2014-02-23T22:34:42Z | 2014-02-24T04:40:53Z | 2014-02-24T04:40:53Z | NONE | null | Hi,
It will be nice if someone can add that
`isnull()` function have a contrary which is called `notnull()`
and
`notnull()` function have a contrary which is called `isnull()`
into documentation
http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.notnull.html
http://pandas.pydata.org/pandas-docs/stabl... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6459 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6459/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6459/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6459/events | https://github.com/pandas-dev/pandas/pull/6459 | 28,137,929 | MDExOlB1bGxSZXF1ZXN0MTI4NDA2MDk= | 6,459 | ENH: Preserve .names in df.set_index(df.index) | {
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"labels_url": "htt... | 10 | 2014-02-24T04:28:11Z | 2014-06-14T22:09:22Z | 2014-03-04T11:13:16Z | CONTRIBUTOR | null | closes #6452.
This causes a slight change in behavior in @jseabold's second example. Previously, `df.set_index(df.index)` would convert a `MultiIndex` into an `Index` of tuples:
```
In [7]: from statsmodels.datasets import grunfeld
In [8]: data = sm.datasets.grunfeld.load_pandas().data
In [9]: data = data.set_index... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6460 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6460/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6460/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6460/events | https://github.com/pandas-dev/pandas/issues/6460 | 28,141,425 | MDU6SXNzdWUyODE0MTQyNQ== | 6,460 | famafrench, pandas.io.data.DataReader error for 'F-F_Momentum_Factor' data | {
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"labels_url": "htt... | 5 | 2014-02-24T06:48:21Z | 2014-04-02T14:16:49Z | 2014-02-25T18:56:13Z | CONTRIBUTOR | null | I think there is a very minor issue in `pandas.io.data.DataReader` for pandas 0.13.1 caused by an inconsistent extension in Ken French's data library. The DataReader can't process the 'F-F_Momentum_Factor' data from Ken French's website:
``` python
import pandas as pd
import pandas.io.data as web
mom = web.DataReader... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6461 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6461/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6461/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6461/events | https://github.com/pandas-dev/pandas/pull/6461 | 28,151,580 | MDExOlB1bGxSZXF1ZXN0MTI4NDc4NzQ= | 6,461 | DOC: Added entries into ecosystem.rst | {
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"labels_url": "htt... | 0 | 2014-02-24T12:12:04Z | 2014-02-25T20:43:00Z | 2014-02-25T20:43:00Z | CONTRIBUTOR | null | ```
In [1]: s = pd.to_timedelta(range(4),unit='d')
In [2]: s
Out[2]:
0 0 days
1 1 days
2 2 days
3 3 days
dtype: timedelta64[ns]
In [3]: s.mean()
Out[3]:
0 1 days, 12:00:00
dtype: timedelta64[ns]
In [4]: s.sum()
Out[4]: 518400000000000
```
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https://api.github.com/repos/pandas-dev/pandas/issues/6463 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6463/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6463/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6463/events | https://github.com/pandas-dev/pandas/issues/6463 | 28,176,933 | MDU6SXNzdWUyODE3NjkzMw== | 6,463 | infer_freq fails on Index | {
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"labels_url": "htt... | 3 | 2014-02-24T16:54:02Z | 2014-02-24T21:34:44Z | 2014-02-24T21:32:47Z | CONTRIBUTOR | null | Continuing with the my projects are the pandas test suite theme of issue reports. This broke for me on a recent upgrade.
Ok.
```
pd.infer_freq(['2004-01', '2004-02', '2004-03', '2004-04'])
```
No longer works.
```
pd.infer_freq(pd.Index(['2004-01', '2004-02', '2004-03', '2004-04']))
```
Seems like this should sti... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6464 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6464/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6464/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6464/events | https://github.com/pandas-dev/pandas/issues/6464 | 28,193,619 | MDU6SXNzdWUyODE5MzYxOQ== | 6,464 | xs on Series with MultiIndex gives KeyError | {
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In [3]: df
Out[3]:
A B C D
first second third
bar one 1 4 1 8 9
two 1 7 5 5 0
baz one 1 6 6 8 0
three 2 5 3 5 3
[4 rows x 4 columns]
In [4]: df.xs('one', level=1)
Out[4]:
A B C D
first third
bar 1 4 1 8 9
ba... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6465 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6465/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6465/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6465/events | https://github.com/pandas-dev/pandas/pull/6465 | 28,194,408 | MDExOlB1bGxSZXF1ZXN0MTI4NzI4OTQ= | 6,465 | COMPAT: infer_freq compat on passing an Index of strings (GH6463) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6466 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6466/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6466/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6466/events | https://github.com/pandas-dev/pandas/issues/6466 | 28,197,745 | MDU6SXNzdWUyODE5Nzc0NQ== | 6,466 | str.split ignores n if pat is None | {
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`str.split` ignores `n` if `pat` is `None`
relevant source code:
```
# pandas/core/strings.py
def str_split(arr, pat=None, n=None):
if pat is None:
if n is None or n == 0:
n = -1
f = lambda x: x.split()
....
```
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```
In [10]: pd.Timestamp.now()
Out[10]:
Timestamp('2014-02-24 17:54:18.370128', tz=None)
In [11]: pd.Timestamp("now")
Out[11]:
Timestamp('2014-02-24 22:54:18', tz=None)
```
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... | 9 | 2014-02-25T00:20:48Z | 2019-07-23T15:27:41Z | 2019-07-23T15:27:40Z | CONTRIBUTOR | null | related #6779
- [x] `asobject` (#7544)
- [x] `__unicode__` (#7602)
- [x] `min/max` (#7609)
- [x] `summary` (#9116)
- [x] `equals` (#13986)
- [x] `isin`
- [x] `unique` (#7540, #7843)
- [x] `value_counts` (#7735)
- [x] `resolution` (#7708)
- [x] `__iter__` (#7702, #7709, #7720)
- [x] `__add__`, `__iadd__`, `_... | {
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closes #6460
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Currently `Float64Index` uses the `Object` back-end for ease of implementation.
See Here: https://github.com/pydata/pandas/blob/master/pandas/core/index.py#L1881
- change the backend to use `Float64Engine` - the cythob code needs fixin in order to make it w... | {
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"labels_url": "htt... | 5 | 2014-02-25T17:18:36Z | 2014-06-27T12:10:32Z | 2014-02-25T17:56:39Z | CONTRIBUTOR | null | Allows custom frequencies other than business day in testing utilities. Keeps the old default.
closes #4541
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s = pd.Series([1,2,3],name='seriesName')
df = pd.DataFrame(s,columns=['columnName'])
In v 0.12, df is the expected DataFrame w/ values [1,2,3] and df.columns = ['columnName']
In v 0.13.1, df is an empty DataFrame.
This seems to be an error, unless there's a reason for the change.
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"description": "__repr__ of pandas objec... | closed | false | null | [] | null | 1 | 2014-02-25T21:12:43Z | 2015-10-20T22:24:57Z | 2015-10-20T22:24:57Z | CONTRIBUTOR | null | I was doing maintenance on an old box, and I just noticed that `clipboard_set` didn't seem to work for me when I only had `xsel` installed and not `xclip`. Installing `xclip` things work fine. Possible that this was a local issue, but just wanted to park this here in case anyone comes across it.
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https://api.github.com/repos/pandas-dev/pandas/issues/6479 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6479/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6479/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6479/events | https://github.com/pandas-dev/pandas/issues/6479 | 28,287,198 | MDU6SXNzdWUyODI4NzE5OA== | 6,479 | Serious performance regression in DataFrame construction with monthly DatetimeIndex | {
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"labels_url": "htt... | 15 | 2014-02-25T21:42:54Z | 2014-03-05T21:55:05Z | 2014-02-27T01:19:04Z | CONTRIBUTOR | null | Hi,
After upgrading from v0.12.0 to v0.13.1, I noticed about a 100% slowdown on a pandas-heavy project. I've just started looking, but I've come up with a test case that shows a time-complexity change from O(1) to O(n) (~240x slowdown for my inputs).
Here's the comparison for v0.12.0 (y-axis is milliseconds):
![perf... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6480 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6480/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6480/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6480/events | https://github.com/pandas-dev/pandas/pull/6480 | 28,293,247 | MDExOlB1bGxSZXF1ZXN0MTI5MjkxNjY= | 6,480 | CLN: remove vestigial count code | {
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maybe related #5734
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``` python
import pandas as pd
import numpy as np
from pandas import Timestamp
timestamps = pd.Series(data=[Timestamp('2014-07-01... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6484 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6484/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6484/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6484/events | https://github.com/pandas-dev/pandas/issues/6484 | 28,335,734 | MDU6SXNzdWUyODMzNTczNA== | 6,484 | PERF: non-info axes slicing on Panels is slow | {
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```
>>> pn1.shape
(13, 5412, 162)
>>> pn2.shape
(12, 5412, 162)
```
12 fields are float64 while one field in `pn1` is `datetime64[ns]`. This slows pretty much all operations (slicing, querying, anything) down by a huge factor:
```
>>> %timeit pn2.values
100000 loops, best of 3: 4.06 µs per... | {
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... | 5 | 2014-02-26T14:54:47Z | 2019-12-24T22:17:32Z | null | CONTRIBUTOR | null | http://stackoverflow.com/questions/22044766/adding-row-to-pandas-dataframe-changes-dtype/22045011#22045011
A bit non-trival (maybe coerce back after) if possible?
maybe just change this to an actual append?
```
In [1]: df = DataFrame({'a' : range(10)}, dtype='i4')
In [2]: df
Out[2]:
a
0 0
1 1
2 2
3 3
4 4
5... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6486 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6486/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6486/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6486/events | https://github.com/pandas-dev/pandas/pull/6486 | 28,352,211 | MDExOlB1bGxSZXF1ZXN0MTI5NjI2MDM= | 6,486 | PERF: perf improvements in single-dtyped indexing (GH6484) | {
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seems on a full vbench to somewhat speedup some reindexing operations.. but this particular is not vbenched
```
In [13]: pn = pd.Panel(np.random.random((12, 5412, 162)))
In [14]: ix = np.ones(pn.shape[1], dtype=bool)
In [15]: ix[np.random.random(ix.size) > 0.5] = 0
In [16]: %timeit pn.loc[0, ix] # on... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6487 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6487/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6487/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6487/events | https://github.com/pandas-dev/pandas/issues/6487 | 28,357,266 | MDU6SXNzdWUyODM1NzI2Ng== | 6,487 | HDFStore.append() throws ValueError for DataFrame created with combine_first() | {
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The df created using combine_first() has same axis as the df originally appended.
This appears to be IFF the index is updated.
Steps:
1. Create df.
2. Append it to hdf store (newly created).
3. df2 = df.copy() + alter index
4. Append df2 to hdf store.
The follo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6488 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6488/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6488/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6488/events | https://github.com/pandas-dev/pandas/issues/6488 | 28,361,934 | MDU6SXNzdWUyODM2MTkzNA== | 6,488 | ENH: Html table export: Add of other attributes | {
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"f... | 7 | 2014-02-26T19:31:53Z | 2021-02-20T20:46:58Z | 2021-02-20T20:46:58Z | NONE | null | The to_html method allows to specify a set of classes for table rendering
However, I would like to specify other attribute to the table markup
Typically I want to use the DataTables (table plug-in for jQuery) library, that requires another attribute for rendering table
Here is an example
https://datatables.net/relea... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6489 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6489/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6489/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6489/events | https://github.com/pandas-dev/pandas/pull/6489 | 28,372,009 | MDExOlB1bGxSZXF1ZXN0MTI5NzQ0NDM= | 6,489 | DOC: Expand on freq in shift usage. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6490 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6490/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6490/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6490/events | https://github.com/pandas-dev/pandas/issues/6490 | 28,384,375 | MDU6SXNzdWUyODM4NDM3NQ== | 6,490 | pivot_table on non existent column | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-02-27T00:42:22Z | 2014-05-16T17:47:22Z | 2014-05-16T17:47:10Z | CONTRIBUTOR | null | If you try to access a column which doesn't exist you get an error
```
In [11]: df = pd.DataFrame([[1, 2, 3]], columns=list('ABC'))
In [12]: df.pivot_table('no', 'A', 'B')
DataError: No numeric types to aggregate
```
Should probably say that the column isn't there.
vaguely related #4733 ?
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https://api.github.com/repos/pandas-dev/pandas/issues/6491 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6491/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6491/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6491/events | https://github.com/pandas-dev/pandas/issues/6491 | 28,389,152 | MDU6SXNzdWUyODM4OTE1Mg== | 6,491 | to_latex truncates string names | {
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"id": ... | closed | false | null | [] | {
"closed_at": "2021-07-02T07:59:17Z",
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"followers_url": "https://api.github.com/users/j... | 2 | 2014-02-27T02:29:59Z | 2021-05-24T13:44:07Z | 2021-05-24T13:44:06Z | CONTRIBUTOR | null | Tried to use `to_latex` to make a table containing long string names. It truncated them and inserted `...`. Drive-by bug issue report. Will update with MWE later.
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https://api.github.com/repos/pandas-dev/pandas/issues/6492 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6492/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6492/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6492/events | https://github.com/pandas-dev/pandas/issues/6492 | 28,391,488 | MDU6SXNzdWUyODM5MTQ4OA== | 6,492 | DataFrame.get_value() doesn't work with no unique monotonic MultiIndex | {
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```
import pandas as pd
from numpy.random import randint
midx = pd.MultiIndex.from_arrays([randint(0, 3, 20), randint(10, 13, 20)]).order()
df = pd.DataFrame({"x":randint(0, 100, 20)}, index=midx)
df.get_value((1, 10), "x")
```
It seems that the `values.searchsorted()` failed in `_get_loc_du... | {
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import pandas as pd
s = pd.Series(range(5), index=[1,1,2,2,3])
s.iat[2]
```
which returns `array([2, 3], dtype=int64)`, I think the result should be `2`.
`s.iloc[2]` works, but `s.iloc[[2, 3]]` raise error.
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"f... | 1 | 2014-02-27T08:53:26Z | 2018-07-06T21:45:36Z | 2018-07-06T21:45:36Z | CONTRIBUTOR | null | This is very much a work in progress, but I've hacked together a copy of vbench that can produce benchmark coverage reports using nosetests and coverage.
The following results are _very_ preliminary, as many benchmarks are failing in the current setup (especially PyTables) and I have to manually intervene to get this ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6495 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6495/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6495/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6495/events | https://github.com/pandas-dev/pandas/pull/6495 | 28,420,434 | MDExOlB1bGxSZXF1ZXN0MTMwMDMyNzk= | 6,495 | BUG: Bug in iat/iloc with duplicate indices on a Series (6493) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6496 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6496/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6496/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6496/events | https://github.com/pandas-dev/pandas/issues/6496 | 28,429,368 | MDU6SXNzdWUyODQyOTM2OA== | 6,496 | PERF: transform speedup | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2014-02-27T15:50:39Z | 2014-08-10T01:24:50Z | 2014-06-11T14:06:07Z | CONTRIBUTOR | null | http://stackoverflow.com/questions/22072943/faster-way-to-transform-group-with-mean-value-in-pandas/22073449#22073449
I think this actually will work in a general case. but prob only really makes sense when you have a cythonized work function (or a ufunc) that is much faster than iteratively calling the groups.
```
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https://api.github.com/repos/pandas-dev/pandas/issues/6497 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6497/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6497/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6497/events | https://github.com/pandas-dev/pandas/issues/6497 | 28,433,564 | MDU6SXNzdWUyODQzMzU2NA== | 6,497 | Possible regression in df.copy() in 0.13 | {
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pd.DataFrame(index=[0])["a"] = 1 # this works
pd.DataFrame(index=[0]).copy()["a"] = 1 # this doesn't
```
The latter command raises:
```
pandas/core/internals.pyc in _add_new_block(self, item, value, loc)
3040 new_block = make_block(value, self.items[loc:loc + 1].copy(),
3041 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6498 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6498/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6498/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6498/events | https://github.com/pandas-dev/pandas/issues/6498 | 28,441,096 | MDU6SXNzdWUyODQ0MTA5Ng== | 6,498 | str.extract fails when non-default index is present | {
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```
import pandas as pd
values = ['11', '23', '45', '98']
noindex = pd.Series(data=values, index=None)
yesindex = pd.Series(data=values, index=list('abcd'))
extractno = noindex.str.extract('(\d)')
print extractno
extractyes = yesindex.str.extract('(\d)')
print extractyes
```
Output:
```
0 1
1 2
2 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6499 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6499/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6499/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6499/events | https://github.com/pandas-dev/pandas/pull/6499 | 28,442,202 | MDExOlB1bGxSZXF1ZXN0MTMwMTYwOTY= | 6,499 | DOC: show users how to emulate R c function with iloc slicing and r_ | {
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https://api.github.com/repos/pandas-dev/pandas/issues/6500 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/6500/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/6500/comments | https://api.github.com/repos/pandas-dev/pandas/issues/6500/events | https://github.com/pandas-dev/pandas/pull/6500 | 28,443,954 | MDExOlB1bGxSZXF1ZXN0MTMwMTcxMjI= | 6,500 | DOC: Clarify that methods taking a MultiIndex level index also accept the name | {
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