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https://api.github.com/repos/pandas-dev/pandas/issues/13104 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13104/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13104/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13104/events | https://github.com/pandas-dev/pandas/issues/13104 | 153,509,175 | MDU6SXNzdWUxNTM1MDkxNzU= | 13,104 | pd.DataFrame.describe percentile string precision | {
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```
In [1]: s = Series(np.random.randn(10))
In [2]: s.describe()
Out[2]:
count 10.000000
mean 0.2... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13105 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13105/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13105/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13105/events | https://github.com/pandas-dev/pandas/issues/13105 | 153,553,067 | MDU6SXNzdWUxNTM1NTMwNjc= | 13,105 | [feature req] List tables function for sql | {
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"description": "to_sql, ... | open | false | null | [] | null | 2 | 2016-05-06T22:45:07Z | 2016-05-11T21:38:12Z | null | NONE | null | Suggestion: introduce a function, something like `pandas.sql_list_tables(conn)` to look up available tables (shortcut for
`pd.read_sql("SELECT * FROM sqlite_master WHERE type='table'", conn, index_col=["name"])` or
`pd.read_sql("SELECT name FROM sqlite_master WHERE type='table'", conn)`).
Like in [this `R` module](... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13106 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13106/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13106/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13106/events | https://github.com/pandas-dev/pandas/issues/13106 | 153,556,971 | MDU6SXNzdWUxNTM1NTY5NzE= | 13,106 | BUG: loc fails on PeriodIndex within MultiIndex | {
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Came across this while searching to see if this had an existing issue, my guess is that this would dramatically help with these Period issues: https://github.com/pydata/pandas/issues/7651
``` python
In [2]: df... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13107 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13107/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13107/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13107/events | https://github.com/pandas-dev/pandas/issues/13107 | 153,557,328 | MDU6SXNzdWUxNTM1NTczMjg= | 13,107 | BUG/API: Index.equals should check input class? | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-05-06T23:26:33Z | 2016-09-03T15:31:03Z | 2016-09-03T15:31:03Z | MEMBER | null | #### Code Sample, a copy-pastable example if possible
Decide the behavior if non `Index` with same values is passed. Currently, there is incompatibility between dtypes.
```
pd.Index([1], dtype=object).equals(pd.Series([1], dtype=object))
# False
pd.Index([1]).equals(pd.Series([1]))
# True
```
#### output of `pd.sho... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13108 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13108/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13108/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13108/events | https://github.com/pandas-dev/pandas/issues/13108 | 153,564,779 | MDU6SXNzdWUxNTM1NjQ3Nzk= | 13,108 | DOC: MultiIndex sort docs | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2016-05-07T01:13:25Z | 2016-05-08T15:17:16Z | 2016-05-08T15:17:16Z | CONTRIBUTOR | null | I found this confusing, despite being a moderately competent pandas user:
from http://pandas.pydata.org/pandas-docs/stable/advanced.html#the-need-for-sortedness-with-multiindex
> Caveat emptor: the present implementation of MultiIndex requires that the labels be sorted for some of the slicing / indexing routines to w... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13109 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13109/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13109/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13109/events | https://github.com/pandas-dev/pandas/issues/13109 | 153,578,628 | MDU6SXNzdWUxNTM1Nzg2Mjg= | 13,109 | "import pandas" changes NumPy error-handling settings | {
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This is a problem when using Pandas as a library, particularly during testing: a test (completely unrelated to Pandas) that should h... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13110 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13110/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13110/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13110/events | https://github.com/pandas-dev/pandas/issues/13110 | 153,595,193 | MDU6SXNzdWUxNTM1OTUxOTM= | 13,110 | BUG: SparseSeries/DataFrame non-float dtypes repr | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2016-05-07T13:48:30Z | 2016-08-31T07:57:34Z | 2016-08-31T07:57:34Z | MEMBER | null | Currently sparse don't actually support dtype other than `float`. These must be fixed with #667
#### Code Sample, a copy-pastable example if possible
##### 1. bool dtype with `fill_value` raises `IndexError`
```
pd.SparseSeries([True, False, True, False, True], fill_value=False)
# IndexError: index out of bounds
```
#... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13111 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13111/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13111/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13111/events | https://github.com/pandas-dev/pandas/issues/13111 | 153,597,263 | MDU6SXNzdWUxNTM1OTcyNjM= | 13,111 | ENH: parallel support in .apply | {
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[questions from SO](http://stackoverflow.com/questions/37078880/status-of-parallelization-of-pandas-apply?noredirect=1#comment61713215_37078880).
[mrocklins nice example of using .apply](http://stackoverflow.com/questions/31361721/python-dask-dataframe-support-for-trivially-parallelizable-row-apply)
So her... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13112 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13112/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13112/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13112/events | https://github.com/pandas-dev/pandas/pull/13112 | 153,618,207 | MDExOlB1bGxSZXF1ZXN0NjkyNTMyOTc= | 13,112 | DOC: Multiindex sort docs | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-05-07T21:14:27Z | 2016-05-08T15:18:00Z | 2016-05-08T15:17:15Z | CONTRIBUTOR | null | closes https://github.com/pydata/pandas/issues/13108
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https://api.github.com/repos/pandas-dev/pandas/issues/13113 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13113/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13113/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13113/events | https://github.com/pandas-dev/pandas/issues/13113 | 153,626,538 | MDU6SXNzdWUxNTM2MjY1Mzg= | 13,113 | BUG: Large MultiIndex-ed series fails on slicing | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2016-05-08T00:33:31Z | 2016-05-08T00:37:47Z | 2016-05-08T00:37:14Z | CONTRIBUTOR | null | With a large MultiIndex-ed series, slicing doesn't fully slice on a 2nd-level.
I've been struggling with this for a while, any ideas greatly appreciated...
``` python
In [135]: ints = (pd.np.random.rand(150000)*1e7).round().astype('int')
In [136]: index=pd.MultiIndex.from_arrays([list('a'*50000 + 'b'*50000+'c'*50000... | {
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Fixed reading and writing of Multiindex.
In a situation where Multiindex looked like this:
| One | Two |
| --- | --- |
| X | |
it was changed to:
| One | Two |
| --- | --- |
| X | X |
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Is this the right way to do this?
cc @MaximilianR
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des_table = df_final_S1415.describe(percentiles=[.05, .25, .5, .75, .95 ]).T
#### Expected Output
In version 18.0 describe function will return percentiles when columns contain nan.
#### output of `pd.show_versions()`
But in version 18.1 describe function will n... | {
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```
In [7]: import datetime as dt
In [8]: df = pd.DataFrame([[dt.datetime(2016,1,31,15)], [dt.datetime(2016,2,7,17)]], index=[dt.datetime(2016,1,31,15), dt.datetime(2016,2,7,17)], columns=['ti... | {
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First noted in discussion here: https://github.com/quantopian/zipline/pull/1190/files/fe5a2a888a498d838c3cc43de2c33ac08b20d2a7#r62506342. This most often matters when passing a value typed in Cython as something like `int64_t[:]`.
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```
df = pd.DataFrame({'a':['foo', 'foo', 'bar'], 'b':[1,1,1]}).set_index('a')
def f(df):
print '============'
print df
print
print(pd.DataFrame(df.groupby(level='a').apply(lambda df: df['b'].cumsum())))
f(df)
f(df[df.index == 'foo'])
```
### Actua... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13122 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13122/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13122/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13122/events | https://github.com/pandas-dev/pandas/pull/13122 | 153,880,233 | MDExOlB1bGxSZXF1ZXN0Njk0MTg0Mzg= | 13,122 | PERF: quantile now operates per block boosting perf / fix quantile with nan | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2016-05-09T22:02:04Z | 2016-05-12T13:12:58Z | 2016-05-12T13:12:58Z | CONTRIBUTOR | null | closes #11623
closes #13098
There is a slight API change in that the returned Series are now named by the quantile.
this PR
```
In [1]: df = DataFrame(np.random.randn(1000, 3), columns=list('ABC'))
In [2]: %timeit df.quantile([0.1, 0.5], axis=1)
1000 loops, best of 3: 830 µs per loop
```
0.18.1
```
In [3]: df.quan... | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2016-05-09T22:16:56Z | 2016-07-20T20:21:05Z | 2016-07-19T10:48:25Z | CONTRIBUTOR | null | I think we are sufficiently on asv now.
Ideally would check if anything in `bench` that we should add to asv. Make sure the asv runs after removing `vb_suite`.
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"followers_url": "https://api.github.com/users/jr... | 10 | 2016-05-10T04:37:39Z | 2016-05-11T23:24:40Z | 2016-05-11T22:18:27Z | CONTRIBUTOR | null | - [x] closes #11981
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Closes #11981
Updated the v0.18.2 document
In the function `__call__` of EngFormatter check if decimal input is NaN.
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https://api.github.com/repos/pandas-dev/pandas/issues/13125 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13125/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13125/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13125/events | https://github.com/pandas-dev/pandas/pull/13125 | 153,949,340 | MDExOlB1bGxSZXF1ZXN0Njk0NjYwNDY= | 13,125 | Make os.linesep default line_terminator in to_clipboard | {
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"description": "p... | closed | false | null | [] | null | 9 | 2016-05-10T08:22:54Z | 2016-12-26T21:46:14Z | 2016-12-26T21:46:14Z | CONTRIBUTOR | null | closes #11720
- Make os.linesep default line_terminator in to_clipboard
- Add line_terminator kw to Series.to_csv
- Refactor to_clipboard
Observed/fixed problems in to_clipboard:
- try..except: pass
- excel=None, though it defaults to True
- several code paths with return
- sep argument could be passed via kwargs
- "o... | {
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"descript... | closed | false | null | [] | null | 5 | 2016-05-10T14:15:02Z | 2016-05-11T14:12:11Z | 2016-05-10T14:41:29Z | NONE | null | #### Additional option for the `date_format` parameter
'isomongo'
#### Expected Output
{ "$date": "YYYY-MM-DDTHH:mm:ss.mmm<+/-Offset>" }
See https://docs.mongodb.com/manual/reference/mongodb-extended-json/#date
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"descri... | closed | false | null | [] | null | 14 | 2016-05-10T16:07:09Z | 2016-05-10T18:35:42Z | 2016-05-10T18:35:42Z | NONE | null | ### Error
Started to get this error recently.
```
tables.exceptions.HDF5ExtError: HDF5 error back trace
File "H5A.c", line 634, in H5Awrite
not an attribute
End of HDF5 error back trace
Can't set attribute 'levels' in node:
/tensor (Group) ''.
Closing remaining open files:tensor.h5...done
```
#### Code Samp... | {
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"followers_url": "https://api.github... | 2 | 2016-05-10T19:28:40Z | 2018-08-14T10:49:11Z | 2018-08-14T10:49:11Z | CONTRIBUTOR | null | Comparing a dataframes where some series have a datatype and others a datetime type, yields the following error:
```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-6-991045b5f90e> in <module>()
... | {
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"color": "005... | closed | false | null | [] | null | 2 | 2016-05-10T19:48:11Z | 2019-10-27T18:23:17Z | 2019-10-27T18:23:17Z | CONTRIBUTOR | null | master issue for some comparisons
- [x] #13128, datetime with string on frame
- [x] #7830, datetimeindex vs other
- [x] #8932, timestamps with frame
- [x] #12601, tz comparisons
- [x] #9369, numeric and Series
- [ ] #11565, strings and numbers
- [x] #13200 Period and Series/Index
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2016-05-10T23:15:50Z | 2018-07-06T20:21:10Z | 2017-07-10T21:08:31Z | CONTRIBUTOR | null | It seems that the `count` method no longer works on `PanelGroupBy` objects, instead raising `NotImplementedError`?
```
dr = pd.date_range("20160505", "20160507 23:00", freq="H")
test_panel = pd.Panel(data=np.random.random((2,72,2)), major_axis=dr)
gb = test_panel.groupby(pd.TimeGrouper('D', axis=1))
# works under al... | {
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https://github.com/pydata/pandas/pull/11770
Closes:
https://github.com/matplotlib/matplotlib/issues/6365
The mistake in #11770 was missing that pandas had a 1/us not 1/s
scaled bucket.
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https://api.github.com/repos/pandas-dev/pandas/issues/13132 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13132/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13132/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13132/events | https://github.com/pandas-dev/pandas/pull/13132 | 154,138,676 | MDExOlB1bGxSZXF1ZXN0Njk2MDA4Mjk= | 13,132 | pd.DataFrame.describe percentile string precision | {
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- [ ] tests added / passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew pretty format returns based on decimalization of input and not just fixed to a single decimal precision
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https://api.github.com/repos/pandas-dev/pandas/issues/13133 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13133/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13133/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13133/events | https://github.com/pandas-dev/pandas/issues/13133 | 154,147,159 | MDU6SXNzdWUxNTQxNDcxNTk= | 13,133 | API: port the magic X from pandas_ply/dplython to pandas proper? | {
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... | 9 | 2016-05-11T02:29:26Z | 2021-04-30T05:03:13Z | null | MEMBER | null | Many DataFrame methods ([now including `__getitem__`](https://github.com/pydata/pandas/issues/11485)) accept callables that take the DataFrame as input, e..g, `df[lambda x: x.sepal_length > 3]`.
However, this is annoyingly verbose. I recently suggested (https://github.com/pydata/pandas/issues/13040) enabling argument-... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13134 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13134/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13134/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13134/events | https://github.com/pandas-dev/pandas/issues/13134 | 154,148,013 | MDU6SXNzdWUxNTQxNDgwMTM= | 13,134 | pd.to_datetime raises expection when converting date object with unit param | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2016-05-11T02:37:59Z | 2016-05-11T02:52:30Z | 2016-05-11T02:41:50Z | NONE | null | Hello, since pandas 0.18.1, converting to datetime a date defined as object, using the unit parameter, raises a ValueError exception.
#### Code Sample, a copy-pastable example if possible
```
import pandas as pd
import datetime
df = pd.DataFrame([[datetime.date(2016, 5, 10)]], index=[0], columns=['date'])
pd.to_date... | {
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RuntimeWarning: divide by zero encountered in log10
C:\Users\Nick\Anaconda3\lib\site-packages\pandas\computation\align.py:98:
ordm = np.log10(abs(reindexer_size - term_axis_size))
while running query().
dtypes:
CGI int64
SITEID int32
LONGITUDE float64
LATITUDE ... | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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... | 7 | 2016-05-11T14:14:12Z | 2019-06-28T16:20:24Z | 2019-06-28T16:20:24Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```
mi = pandas.MultiIndex.from_tuples([('c', 'd'), ('e', 'd'), ('f', 'g')])
df = DataFrame({'a': [1,2,3], 'b': [1,5,6]}, index=mi)
p = Panel(data={'one': df}).transpose(1,2,0)
p.loc[:, :, 'one'] = p.loc[:, :, 'one']
```
I get:
```
TypeError: Expected tuple, got ... | {
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``` python
import pandas as pd
import numpy as np
df = pd.DataFrame({'A': 'foo bar foo bar foo bar foo foo'.split(),
'B': 'one one two three two two one three'.split(),
'C': np.arange(8), 'D': np.arange(8) * 2})
```
#### Expected output
If I run query with an emp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13140 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13140/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13140/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13140/events | https://github.com/pandas-dev/pandas/issues/13140 | 154,278,489 | MDU6SXNzdWUxNTQyNzg0ODk= | 13,140 | df.style des not render pivot tables in the same fashion as to_html | {
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"color": "006b7... | closed | false | null | [] | null | 2 | 2016-05-11T15:53:16Z | 2016-05-17T02:18:43Z | 2016-05-17T02:18:43Z | NONE | null | Please see
http://stackoverflow.com/questions/37166730/how-do-i-preserve-hierarchical-tables-with-pandas-pivot-table-and-dataframe-styl
#### Code Sample, a copy-pastable example if possible
```
import pandas as pd
import numpy as np
np.random.seed(0)
a = np.random.randint(1, 4, 10)
b = np.random.randint(1, 4, 10)
c ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13141 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13141/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13141/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13141/events | https://github.com/pandas-dev/pandas/issues/13141 | 154,279,271 | MDU6SXNzdWUxNTQyNzkyNzE= | 13,141 | [ENH] pandas.read_html argument to interpret hyperlinks as links (not merely text) | {
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"description": "read_htm... | open | false | null | [] | null | 5 | 2016-05-11T15:56:37Z | 2021-02-13T13:11:51Z | null | NONE | null | For starters I'd just like to share that pandas is AWESOME! Thank you to all who contribute and make this lean, mean number crunching machine available to others like me.
pandas.read_html is super convenient for making dataframes from the web! The power of the web is that it's just that... a web of many highly interco... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13142 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13142/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13142/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13142/events | https://github.com/pandas-dev/pandas/pull/13142 | 154,283,856 | MDExOlB1bGxSZXF1ZXN0Njk3MDA0NjU= | 13,142 | Implement is_array_like | {
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- [ ] tests added / passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
Is it worth using this PR to consolidate how the common package is imported across modules? Some files use `from pandas.core.common import *` style whereas others use `import pandas.core.common ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13143 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13143/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13143/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13143/events | https://github.com/pandas-dev/pandas/issues/13143 | 154,296,905 | MDU6SXNzdWUxNTQyOTY5MDU= | 13,143 | sample not using numpy's random state | {
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Expected behavior of `numpy.random.choice` but found something different. Here is pandas:
``` python
In [1]: import pandas as pd
In [2]: import numpy as np
In [3]: df = pd.DataFrame(np.arange(1000))
In [12]: np.random.... | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2016-05-11T19:53:31Z | 2016-05-13T13:21:47Z | 2016-05-13T13:21:47Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```
import scipy.sparse as sps
import pandas as pd
A = sps.rand(350, 18)
ss = pd.SparseSeries.from_coo(A)
print(ss)
A = sps.rand(350, 17)
ss = pd.SparseSeries.from_coo(A)
print(ss)
```
#### Expected Output
The expected output is that both cases print the SparseSe... | {
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"followers_url": "https://api.github.com/users/jr... | 14 | 2016-05-11T20:55:37Z | 2016-08-21T13:54:47Z | 2016-08-21T13:37:54Z | CONTRIBUTOR | null | - [x] closes #13109
- [x] closes #13135
- [x] tests passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
The precise strategy to be taken here is open for discussion. I tried to be reasonably fine-grained rather than slap a generic decorator over everything because it's easier to go tha... | {
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#### Code Sample, a copy-pastable example if possible
``` python
import numpy as np
import pandas as pd
df = pd.DataFrame({'task_complete':['success','success','... | {
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So this is the big boy. destroyed `core/common.py` and split up. Now have no more import issues and a nice private API. Nothing is exported by default. You have to explicity import things.
There is now a `pandas.api`, so:
```
In [1]: from pandas import api
In [2]: dir(api)
Out[2]:
['__builtins__',
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13148 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13148/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13148/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13148/events | https://github.com/pandas-dev/pandas/pull/13148 | 154,380,475 | MDExOlB1bGxSZXF1ZXN0Njk3NjkwNDE= | 13,148 | COMPAT: Further Expand Compatibility with fromnumeric.py | {
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"followers_url": "https://api.github.com/users/jr... | 9 | 2016-05-12T01:55:13Z | 2016-05-20T23:53:31Z | 2016-05-20T13:19:33Z | MEMBER | null | Follow-on to #12810 by expanding compatibility with `fromnumeric.py` in the following modules:
1) `tslib.pyx`
2) `window.py`
3) `groupby.py` and `resample.py` (shared classes)
Closes #12811.
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https://api.github.com/repos/pandas-dev/pandas/issues/13149 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13149/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13149/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13149/events | https://github.com/pandas-dev/pandas/issues/13149 | 154,385,124 | MDU6SXNzdWUxNTQzODUxMjQ= | 13,149 | NaNs in Float64Index are converted to silly integers using index.astype('int') | {
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... | 6 | 2016-05-12T02:42:59Z | 2016-05-23T20:45:45Z | 2016-05-23T20:45:45Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```
>>> df = pd.DataFrame({'a': [1, 2], 'b': [3, 4]})
>>> df.index = [None, 1]
>>> df
a b
NaN 1 3
1.0 2 4
>>> df.index = df.index.astype('int')
>>> df
a b
-9223372036854775808 1 3
1 2 4
```
#### output of `... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13150 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13150/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13150/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13150/events | https://github.com/pandas-dev/pandas/issues/13150 | 154,387,870 | MDU6SXNzdWUxNTQzODc4NzA= | 13,150 | read_excel: fails for Python 3.5.1/Pandas 0.18.0 | {
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"name": "IO Excel",
"node_id": "MDU6TGFiZWw0OTI1NDI3Mw==",
"url": "https://api.github.com/repos/pandas-dev/pandas/labels/IO%20Excel"
}
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"followers_url": "https://api.github.com/users/jorisva... | 5 | 2016-05-12T03:12:58Z | 2016-05-12T15:16:12Z | 2016-05-12T13:03:17Z | NONE | null | I'm running Anaconda 64-bit, Python 3.51 (pandas: 0.18.0) and 2.7 (pandas: 0.17.1.)
When I'm in the 2.7 environment, read_excel works properly
``` python
import pandas as pd
d=pd.read_excel(XLS1)
*** No CODEPAGE record, no encoding_override: will use 'ascii'
```
In the 3.5 environment, I get the following error:
``... | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2016-05-12T04:07:14Z | 2016-05-12T10:30:57Z | 2016-05-12T10:30:57Z | CONTRIBUTOR | null | #### Code Sample, a copy-pastable example if possible
I use resample with group by method to run following code:
```
import pandas as pd
data = [{'buyer_id': 1, 'pay_time': '2016-01-01', 'tid': '11'}, {'buyer_id': 1, 'pay_time': '2016-01-03', 'tid': '12'}, {'buyer_id': 1, 'pay_time': '2016-01-05', 'tid': '13'}, {'buy... | {
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... | 1 | 2016-05-12T05:47:10Z | 2021-04-30T05:05:43Z | null | MEMBER | null | They provide scalars are the values rather all the corresponding labels:
```
In [81]: index = pd.date_range('2000-01-01', periods=5)
In [82]: s = pd.Series(np.arange(index.size), index)
In [83]: s
Out[83]:
2000-01-01 0
2000-01-02 1
2000-01-03 2
2000-01-04 3
2000-01-05 4
Freq: D, dtype: i... | {
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"id": 13098779,
"name": "Reshaping",
"node_id": "MDU6TGFiZWwxMzA5ODc3OQ==",
"url": "https://api.github.com/repos/pandas-dev/pandas/labels/Reshaping"
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"de... | closed | false | null | [] | {
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"f... | 4 | 2016-05-12T08:47:27Z | 2021-04-30T05:06:58Z | 2021-04-30T05:06:58Z | NONE | null | ```
def get_desc(x):
return "Intermission" if x["ID"] == "0*" else x.workTitle.string + " by " + x.composerName.string
works["nice"] = works[0].apply(get_desc)
```
on this https://github.com/nyphilarchive/PerformanceHistory dataset
I would like pandas to tell me which line the function fails on, rather than somet... | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2016-05-12T09:25:48Z | 2016-05-12T09:55:36Z | 2016-05-12T09:55:36Z | NONE | null | #### Code Sample, a copy-pastable example if possible
``` python
import pandas as pd
s_empty = pd.Series()
s_filled = pd.Series([1, 2, 3, 4, 5])
pd.concat([s_empty, s_filled], 1)
```
#### Expected Output
Expect to be consistent between versions: previously would not add any columns for the empty `Series`, now a col... | {
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] | closed | false | null | [] | null | 4 | 2016-05-12T10:03:19Z | 2016-05-12T12:32:49Z | 2016-05-12T12:32:48Z | CONTRIBUTOR | null | #### Code Sample, a copy-pastable example if possible
``` python
python -c "import pandas as pd; print(pd.__version__); pd.tslib._Timestamp(42, 7, 13)"
```
Crashes python.exe on Windows 7, 10. Tested with Python 3.3, 3.4, 3.5, pandas 0.16.2, 0.17.1, 0.18.0. ipython.exe crashes on exit when this code is executed.
##... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13156 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13156/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13156/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13156/events | https://github.com/pandas-dev/pandas/pull/13156 | 154,485,834 | MDExOlB1bGxSZXF1ZXN0Njk4Mzg1NTE= | 13,156 | ENH/BUG: str.extractall doesn't support index | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-05-12T13:44:25Z | 2016-05-13T13:25:05Z | 2016-05-13T13:24:58Z | MEMBER | null | - [x] closes #10008
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
```
# same output as pd.Series(["a1a2", "b1", "c1"]).str.extractall("[ab](?P<digit>\d)")
idx = pd.Index(["a1a2", "b1", "c1"])
idx.str.extractall("[ab](?P<digit>\d)")
# digit
# match ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13157 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13157/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13157/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13157/events | https://github.com/pandas-dev/pandas/issues/13157 | 154,505,526 | MDU6SXNzdWUxNTQ1MDU1MjY= | 13,157 | quantile() does not work with columns of type Decimal | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2016-05-12T15:02:49Z | 2016-05-12T15:21:23Z | 2016-05-12T15:19:49Z | NONE | null | #### Code Sample, a copy-pastable example if possible
This snippet does not work (returns an empty DataFrame)
```
pd.DataFrame([
Decimal(162.7646939720129171), Decimal(162.5470404198062433),
Decimal(162.9334883683360258), Decimal(161.7975872981700753),
Decimal(160.9450499461786868), Decimal(163.1648865446... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13158 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13158/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13158/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13158/events | https://github.com/pandas-dev/pandas/issues/13158 | 154,525,742 | MDU6SXNzdWUxNTQ1MjU3NDI= | 13,158 | ambiguous ValueError message | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2016-05-12T16:28:10Z | 2016-05-13T00:19:01Z | 2016-05-13T00:19:01Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```
df=pd.DataFrame([(i+j,i-j,i*j) for i in range(0,4) for j in (2,6)])
df.columns=['a','b','c']
df.loc[:,['a','c']].div(df['b'],axis=0)
```
Output:
"ValueError: putmask: mask and data must be the same size"
This message is too ambiguous: what size is it referrin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13159 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13159/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13159/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13159/events | https://github.com/pandas-dev/pandas/issues/13159 | 154,551,623 | MDU6SXNzdWUxNTQ1NTE2MjM= | 13,159 | DOC: floating point precision on writing/reading to csv | {
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... | 4 | 2016-05-12T18:35:50Z | 2019-10-21T19:52:16Z | null | NONE | null | #### Code Sample
```
x0 = 18292498239.824
df1 = pd.DataFrame({'One': x0},index=["bignum"])
df1.to_csv('repr_test.csv')
df2 = pd.DataFrame.from_csv('repr_test.csv')
df3 = pd.read_csv('repr_test.csv')
x1 = df1['One'][0]
x2 = df2['One'][0]
x3 = df3['One'][0]
fh = open('repr_test.csv','rb')
ll = fh.readlines()
x4 = float(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13160 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13160/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13160/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13160/events | https://github.com/pandas-dev/pandas/issues/13160 | 154,557,647 | MDU6SXNzdWUxNTQ1NTc2NDc= | 13,160 | The documentation around frequency strings is unclear | {
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"followers_url": "https://api.github.com/users/jr... | 11 | 2016-05-12T19:05:12Z | 2016-07-21T14:31:18Z | 2016-07-21T14:31:18Z | CONTRIBUTOR | null | http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.rolling.html?highlight=rolling#pandas.DataFrame.rolling and various other places in the documentation talk about something called "frequency strings", however, there doesn't seem to be any explanation of what this term means anywhere. http://pandas.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13161 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13161/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13161/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13161/events | https://github.com/pandas-dev/pandas/pull/13161 | 154,557,687 | MDExOlB1bGxSZXF1ZXN0Njk4ODk4NDk= | 13,161 | Use np.random's RandomState when seed is None | {
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"followers_url": "https://api.github.com/users/jr... | 19 | 2016-05-12T19:05:29Z | 2017-02-18T16:53:26Z | 2016-05-21T14:37:56Z | NONE | null | - [x] closes #13143
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
The handle for numpy's current random state is
`np.random.mtrand._rand`.
Compare https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/utils/validation.py#L573
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https://api.github.com/repos/pandas-dev/pandas/issues/13162 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13162/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13162/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13162/events | https://github.com/pandas-dev/pandas/issues/13162 | 154,569,652 | MDU6SXNzdWUxNTQ1Njk2NTI= | 13,162 | pandas TypeError: Series.name must be a hashable type | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2016-05-12T20:07:43Z | 2016-05-12T22:46:32Z | 2016-05-12T22:46:32Z | NONE | null | #### Code Sample, a copy-pastable example if possible
This is the following SO issue: http://stackoverflow.com/questions/37195658/pandas-typeerror-series-name-must-be-a-hashable-type
Call to Func_df(df):
pattern_tmp1 = grouped[['sprd1','cost1']].apply(Func_df)[0]
Input df to Func_df(df):
sprd1 cost1
date
2016-... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13163 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13163/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13163/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13163/events | https://github.com/pandas-dev/pandas/pull/13163 | 154,601,105 | MDExOlB1bGxSZXF1ZXN0Njk5MjExOTk= | 13,163 | BUG: Misc fixes for SparseSeries indexing with MI | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-05-12T23:08:36Z | 2016-05-13T13:21:58Z | 2016-05-13T13:21:47Z | MEMBER | null | - [x] closes #13144
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Fixed following bugs. These makes `MultiIndex` repr work.
```
orig = pd.Series([1, np.nan, np.nan, 3, np.nan], index=idx)
sparse = orig.to_sparse()
sparse['A']
# IndexError: Out of bounds ac... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13164 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13164/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13164/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13164/events | https://github.com/pandas-dev/pandas/pull/13164 | 154,605,614 | MDExOlB1bGxSZXF1ZXN0Njk5MjQ0MDQ= | 13,164 | TST: Test resampling with NaT | {
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"followers_url": "https://api.github.com/users/jr... | 7 | 2016-05-12T23:45:48Z | 2016-05-18T22:11:12Z | 2016-05-18T22:10:30Z | CONTRIBUTOR | null | - Closes #13020
- Adds `test_generic.py:TestDataFrame.test_resample_with_nat`
- Passes tests and flake8
- No documentation needed
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https://api.github.com/repos/pandas-dev/pandas/issues/13165 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13165/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13165/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13165/events | https://github.com/pandas-dev/pandas/pull/13165 | 154,612,622 | MDExOlB1bGxSZXF1ZXN0Njk5Mjk0MTA= | 13,165 | DOC: Fix delim_whitespace regex typo. | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-05-13T00:56:20Z | 2016-05-13T08:48:08Z | 2016-05-13T08:48:02Z | CONTRIBUTOR | null | Minor typo in the explanation of delim_whitespace which tripped up a user on SO (although the user should probably have been using `delim_whitespace=True` directly anyhow.)
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https://api.github.com/repos/pandas-dev/pandas/issues/13166 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13166/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13166/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13166/events | https://github.com/pandas-dev/pandas/issues/13166 | 154,621,734 | MDU6SXNzdWUxNTQ2MjE3MzQ= | 13,166 | Float64Index is very slow in some condition. | {
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"color": "a1... | closed | false | null | [] | {
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```
import pandas as pd
import numpy as np
dt = 4.8000000418824129e-08
data = np.random.rand(1000000, 4)
df = pd.DataFrame(data, columns=list("ABCD"))
df.index *= dt
print(df.loc[0:0.001].shape)
```
after debug it, I found `Float64Engine.get_loc()` is slow. Here is a demo:
```
impor... | {
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- [ ] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] remove unused parameters `out` and `dtype` from `cumulated` functions (`cummin`, `cumsum`, `cumprod`, `cummax`)
This also affects the documentation. Check for example: http://pandas.pydata.org/pandas-docs/stable... | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2016-05-13T10:11:02Z | 2016-07-11T07:43:58Z | 2016-07-11T07:43:57Z | CONTRIBUTOR | null | I was trying to process a massive table in chunks and therefore wanted to read the table in chunks and
process it.
When i tried reading the table using the pandas.read_sql_table i ran out of memory even though i
had passed in the chunksize parameter.
I'm using the mysqlclient for python3.
#### Code Sample, a copy-pas... | {
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... | 0 | 2016-05-13T13:57:38Z | 2021-04-30T05:25:06Z | null | CONTRIBUTOR | null | ```
In [5]: df = DataFrame({'A' : [1,2]})
In [6]: df['B'] = Index([True,False])
In [7]: df['C'] = Index([True,False]).values
In [8]: df
Out[8]:
A B C
0 1 True True
1 2 False False
In [9]: df.dtypes
Out[9]:
A int64
B object
C object
dtype: object
In [10]: df = DataFrame({'A' : [1,2]... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-05-13T14:07:22Z | 2016-05-27T12:41:32Z | 2016-05-27T12:41:32Z | CONTRIBUTOR | null | - closes #8596, preserve join keys dtype
- adds `Index.where` method for all Index types (like `np.where/Series.where`), but preserves dtypes
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-05-13T16:24:49Z | 2016-05-17T13:40:50Z | 2016-05-17T13:40:50Z | CONTRIBUTOR | null | #### Code Sample, a copy-pastable example if possible
```
from __future__ import unicode_literals
import pandas as pd
pd.DataFrame([{'id': '10', 'title': 'hello'}]).set_index('id').to_records()
```
the code above will report following error:
```
TypeError Traceback (most recent call l... | {
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the performance significantly deteriorates. A small example:
```
import pandas as pa
obs = 1000
start_date = '1/1/1900'
df = pa.DataFrame(list(range(1, obs + 1)))
df['dateindex'] = pa.date_range('1/1/1900', periods=obs, freq='M')
df['periodindex'] ... | {
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```
import pandas as pd
data = [{'id': 1, 'buyer': 'A'}, {'id': 2, 'buyer': 'B'}]
df = pd.DataFrame(data, index=pd.date_range('2016-01-01', periods=2))
resampler = df.groupby('id').resample('1D')
```
If I then run `resampler['buyer'].count()` first time, it will o... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13175 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13175/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13175/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13175/events | https://github.com/pandas-dev/pandas/pull/13175 | 154,827,883 | MDExOlB1bGxSZXF1ZXN0NzAwNzgzNzQ= | 13,175 | BUG: Bug in .groupby(..).resample(..) when the same object is called multiple times | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/13177 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13177/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13177/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13177/events | https://github.com/pandas-dev/pandas/pull/13177 | 154,829,289 | MDExOlB1bGxSZXF1ZXN0NzAwNzkyMTU= | 13,177 | DOC: Clarify Categorical Crosstab Behaviour | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13178 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13178/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13178/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13178/events | https://github.com/pandas-dev/pandas/pull/13178 | 154,851,243 | MDExOlB1bGxSZXF1ZXN0NzAwOTA5Mzk= | 13,178 | BUG: fix to_records confict with unicode_literals #13172 | {
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- [ ] tests added / passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/13179 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13179/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13179/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13179/events | https://github.com/pandas-dev/pandas/issues/13179 | 154,868,682 | MDU6SXNzdWUxNTQ4Njg2ODI= | 13,179 | BUG: groupby upon categorical and sort=False triggers ValueError | {
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... | closed | false | null | [] | {
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**The combination of `sort=False` and a missing category in the data causes the bug - see below**
First off, see this notebook which showcases the bug nicely: [github.com/mpschr/pandas_missing_cat_bug](https://github.com/mpschr/pandas_missing_cat_bug/blob/master/Pandas_categorical_b... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13180 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13180/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13180/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13180/events | https://github.com/pandas-dev/pandas/issues/13180 | 154,884,950 | MDU6SXNzdWUxNTQ4ODQ5NTA= | 13,180 | Converting float64 values to datetime64[ns] format using pd.to_datetime results in NaT if errors='coerce' | {
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A Pandas dataframe contains a date variable that is formatted as float64 as follows:
```
tempDF = pd.DataFrame({'group': ['a','b'],
'date': [1.434692e+18,1.432766e+18]})
print(tempDF)
```
Which appears as:
```
date group
0 1.4... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13181 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13181/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13181/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13181/events | https://github.com/pandas-dev/pandas/issues/13181 | 154,892,658 | MDU6SXNzdWUxNTQ4OTI2NTg= | 13,181 | The behavior of `DataFrame.ix` slicing with a negative index | {
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``` python
>>> df = pd.DataFrame(np.arange(16).reshape(8, 2))
>>> df
0 1
0 0 1
1 2 3
2 4 5
3 6 7
4 8 9
5 10 11
6 12 13
7 14 15
>>> df[-4:]
0 1
4 8 9
5 10 11
6 12 13
7 14 15
```
But, `df.ix[-4:]` returns:
``` python
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https://api.github.com/repos/pandas-dev/pandas/issues/13182 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13182/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13182/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13182/events | https://github.com/pandas-dev/pandas/issues/13182 | 154,895,652 | MDU6SXNzdWUxNTQ4OTU2NTI= | 13,182 | x_compat has no effect | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13183 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13183/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13183/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13183/events | https://github.com/pandas-dev/pandas/pull/13183 | 154,909,839 | MDExOlB1bGxSZXF1ZXN0NzAxMjE4OTQ= | 13,183 | BUG: Bug in .to_datetime() when passing integers or floats, no unit and errors=coerce | {
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[foo1.csv](https://www.dropbox.com/s/peojg2ugn6m4dtt/foo1.csv?dl=0)
#### Code Sample, a copy-pastable example if possible
import pandas as pd
df = pd.read_csv('foo1.csv', sep='\t', encoding='utf-16le', engine='python')
df.to_csv("out.csv", mode='wb', sep='\t', encoding='utf-16le', engine='python')
###... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13185 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13185/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13185/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13185/events | https://github.com/pandas-dev/pandas/issues/13185 | 154,913,179 | MDU6SXNzdWUxNTQ5MTMxNzk= | 13,185 | FAIL: test_scatter_matrix_axis (pandas.tests.test_graphics_others.TestDataFramePlots) in 0.18.1 with py27 | {
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I cannot test with py34 because matplotlib is not available on FreeBSD under py3k.
#### Code Sample, a copy-pastable example if possible
```
% nosetests-2.7 pandas.tests.test_graphics_others:TestDataF... | {
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#### Code Sample, a copy-pastable example if possible
```
% nosetests-2.7 pandas.tests.series.test_timeseries:TestSeriesTimeSeries.test_getitem_setitem_datetime_tz_dateutil
F
======================================================================
FAIL: test_getitem_setitem_datetime_... | {
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- [ ] tests passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew:
As per issue 13084, made it clearer for the user to understand why a concat failed. No additional code was needed. This is because the _verify_integrity method inside the BlockManager class of pandas/core/in... | {
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- [x] passes `git diff upstream/master | flake8 --diff`
Also a MatplotlibDeprecationWarning for use of `.get_axes()` vs. `.axes` in some tests.
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/13190 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13190/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13190/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13190/events | https://github.com/pandas-dev/pandas/pull/13190 | 154,927,723 | MDExOlB1bGxSZXF1ZXN0NzAxMzE3MzI= | 13,190 | TST: Use compatible time zones (#13186) | {
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The test failures in Travis are all unrelated to the code affected by this change.
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#### Code Sample, a copy-pastable example if possible
``` python
In [20]: df = pd.DataFrame({'grouping':[np.nan,1,1,3],
'v':[1.1, 2.1, 3.1, 4.5],
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https://api.github.com/repos/pandas-dev/pandas/issues/13192 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13192/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13192/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13192/events | https://github.com/pandas-dev/pandas/pull/13192 | 154,937,827 | MDExOlB1bGxSZXF1ZXN0NzAxMzY5NjM= | 13,192 | PERF: DataFrame transform | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-05-15T23:23:09Z | 2016-05-18T13:19:53Z | 2016-05-18T13:19:39Z | CONTRIBUTOR | null | - [x] closes #12737,
closes #13191
- [ ] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
```
before after ratio
[2de2884 ] [4b352d9 ]
- 164.84ms 1.73ms 0.01 groupby.groupby_transform_dataframe.time_groupby_transform_dataframe
4.44ms ... | {
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... | 16 | 2016-05-16T00:21:09Z | 2019-12-01T17:54:37Z | null | NONE | null | Hello everyone,
I am trying to merge a ridiculously large dataframe with another ridiculously smaller one and I get
`df=df.merge(slave,left_on='buyer',right_on='NAME',how='left')`
`OverflowError: Python int too large to convert to C long`
Ram is filled at 56% prior to the merge. Am I hitting some limitations here?
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... | 3 | 2016-05-16T14:10:14Z | 2019-10-21T19:52:16Z | null | CONTRIBUTOR | null | Pandas version 0.18.1:
``` python
In[1]: import pandas as pd
In[2]: df = pd.DataFrame(np.array([[1., 2.], [3., 4.]]), columns=list('AB'))
In[3]: ts = pd.Series([5., 6., 7.])
In[4]: df.align(ts, join='outer', axis=0, broadcast_axis=1)
Out[4]:
( A B
0 1.0 2.0
1 3.0 4.0, A B
0 5.0 5.0
1 6.0 6.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13196 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13196/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13196/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13196/events | https://github.com/pandas-dev/pandas/issues/13196 | 155,130,757 | MDU6SXNzdWUxNTUxMzA3NTc= | 13,196 | Series accessed with timezoned timestamps inexplicably returns NaN | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2016-05-16T21:52:04Z | 2016-05-19T17:19:20Z | 2016-05-17T13:38:21Z | NONE | null | Somewhere between version 0.16.1 and 0.18.1 the behavior of Series[] called with an array of timestamps with timezones stopped working.
Is this expected behavior?
Here's our failing test case.
#### Code Sample, a copy-pastable example if possible
```
import pytz
import pandas as pp
MTV_TZ = pytz.timezone... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-05-17T04:28:29Z | 2016-05-17T14:47:57Z | 2016-05-17T13:22:39Z | CONTRIBUTOR | null | `__init__` shouldn't return anything
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- Implemented the _easy fix_
- Future work : To implement broadcast axis remaining functionality.
- All tests in test_generic.py passed.
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https://blog.rstudio.org/2016/03/29/feather/
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https://api.github.com/repos/pandas-dev/pandas/issues/13200 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13200/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13200/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13200/events | https://github.com/pandas-dev/pandas/pull/13200 | 155,249,792 | MDExOlB1bGxSZXF1ZXN0NzAzNDk4ODA= | 13,200 | BUG: Period and Series/Index comparison raises TypeError | {
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- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
`Period` and `Series/Index` comparison raises `TypeError` if `Period` is on left hand side.
```
# OK
pd.Series([pd.Period('2011-01-01', freq='D')]) > pd.Period('2011-01-01', freq='D')
#0 False
# dtype: bool
# ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13201 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13201/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13201/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13201/events | https://github.com/pandas-dev/pandas/pull/13201 | 155,250,913 | MDExOlB1bGxSZXF1ZXN0NzAzNTA2NzY= | 13,201 | BUG: Sparse creation with object dtype may raise TypeError | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-05-17T12:48:40Z | 2016-05-18T13:23:14Z | 2016-05-18T13:22:36Z | MEMBER | null | closes #11633
closes #11856
Added basic tests for `groupby` and `pivot_table`.
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https://api.github.com/repos/pandas-dev/pandas/issues/13202 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13202/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13202/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13202/events | https://github.com/pandas-dev/pandas/issues/13202 | 155,263,189 | MDU6SXNzdWUxNTUyNjMxODk= | 13,202 | DOC: pandas cheat sheet | {
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"followers_url": "https://api.github.com/users/jr... | 25 | 2016-05-17T13:44:35Z | 2016-12-21T17:23:05Z | 2016-12-21T17:23:05Z | CONTRIBUTOR | null | https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf
I think we could pretty much rip this off exactly as is and just substitute pandas functions directly.
Further could update `comparison with R` a bit.
anyone up for this?
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https://api.github.com/repos/pandas-dev/pandas/issues/13203 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13203/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13203/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13203/events | https://github.com/pandas-dev/pandas/issues/13203 | 155,272,686 | MDU6SXNzdWUxNTUyNzI2ODY= | 13,203 | enhancement: add optional row/col paramater to to_latex formatter | {
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"followers_url": "https://api.github.com/users/j... | 6 | 2016-05-17T14:23:30Z | 2021-05-24T13:44:06Z | 2021-05-24T13:44:06Z | NONE | null | I need to have to_latex formatter function know the row/col of the item being formatted, so it can modify the formatting of certain items, e.g., set some items in color of bold based on the values in the table.
To do this in a backward compatible way, I propose adding a keyword to to_latex - which would then cause the... | {
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