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https://api.github.com/repos/pandas-dev/pandas/issues/13004 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13004/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13004/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13004/events | https://github.com/pandas-dev/pandas/pull/13004 | 151,260,358 | MDExOlB1bGxSZXF1ZXN0Njc5NzI3NzM= | 13,004 | DOC: more pd.to_datetime examples | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13005 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13005/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13005/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13005/events | https://github.com/pandas-dev/pandas/pull/13005 | 151,264,353 | MDExOlB1bGxSZXF1ZXN0Njc5NzU0NDc= | 13,005 | PERF: don't create the skiprows set if using the c-parser | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-04-26T23:38:06Z | 2016-04-27T12:29:55Z | 2016-04-27T12:29:55Z | CONTRIBUTOR | null | ```
In [4]: DataFrame(np.random.randn(1000000,1)).to_csv('test.csv',index=False)
```
branch
```
In [1]: %memit pd.read_csv('test.csv',skiprows=999999)
peak memory: 65.74 MiB, increment: 1.59 MiB
In [2]: %memit pd.read_csv('test.csv',skiprows=999999)
peak memory: 65.89 MiB, increment: 0.22 MiB
In [3]: %memit pd.rea... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13006 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13006/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13006/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13006/events | https://github.com/pandas-dev/pandas/issues/13006 | 151,268,829 | MDU6SXNzdWUxNTEyNjg4Mjk= | 13,006 | BUG: Type error when comparing numpy scalar to pandas series | {
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I'm getting strange results when comparing a numpy float to a pandas series. It seems to think that the numpy float is some sort of array...
``` python
import numpy as np
import pandas as pd
np.float64(0) < pd.Series([1,2,3],dtype=np.float64)
```
#### Expected Output
```
0 True
1 True
2 True
dtype: bool... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13007 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13007/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13007/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13007/events | https://github.com/pandas-dev/pandas/pull/13007 | 151,297,598 | MDExOlB1bGxSZXF1ZXN0Njc5OTU5ODU= | 13,007 | BUG: COMPAT:0.18 added scipy version check GH12887 | {
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- [X] tests passed (Tests specific to this issue now pass with scipy dev and numpy dev versions that I was using when I opened the issue)
- [X] passes `git diff upstream/master | flake8 --diff`
- [X] whatsnew entry
@jreback @TomAugspurger
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https://api.github.com/repos/pandas-dev/pandas/issues/13008 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13008/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13008/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13008/events | https://github.com/pandas-dev/pandas/pull/13008 | 151,367,027 | MDExOlB1bGxSZXF1ZXN0NjgwNDA1Mzg= | 13,008 | PERF: Improved performance for .str.encode/decode | {
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Optimize string encoding-decoding, leave default implementation for CPython optimized encodings,
(see https://docs.pyth... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13012 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13012/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13012/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13012/events | https://github.com/pandas-dev/pandas/pull/13012 | 151,417,985 | MDExOlB1bGxSZXF1ZXN0NjgwNzU0ODQ= | 13,012 | API, DEPR: Raise and Deprecate Reshape for Pandas Objects | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13013 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13013/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13013/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13013/events | https://github.com/pandas-dev/pandas/issues/13013 | 151,501,494 | MDU6SXNzdWUxNTE1MDE0OTQ= | 13,013 | cannot truncate a timeseries without sorting it first | {
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... | closed | false | null | [] | null | 2 | 2016-04-27T22:00:26Z | 2016-04-27T22:55:02Z | 2016-04-27T22:54:52Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```
pd.Series(index=pd.to_datetime(['2016-04-15 21:18:04.683115', '2016-04-15 21:18:05.384231',
'2016-04-15 21:18:05.504638', '2016-04-15 21:18:05.510117',
'2016-04-15 21:18:05.370865', '2016-04-15 21:18:05.577177',
'201... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13014 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13014/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13014/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13014/events | https://github.com/pandas-dev/pandas/pull/13014 | 151,555,281 | MDExOlB1bGxSZXF1ZXN0NjgxNjc0ODE= | 13,014 | BUG: .isin(...) now coerces sets to lists | {
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- [ ] tests added, passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [ ] `comp.isin(values)` now coerces `values` from a set into a list. This was failing when `comp` is a datetime dtype and `values` is a set, where `.isin` will try to run `to_datetime(values)` on the unordered set an... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13015 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13015/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13015/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13015/events | https://github.com/pandas-dev/pandas/issues/13015 | 151,564,999 | MDU6SXNzdWUxNTE1NjQ5OTk= | 13,015 | TST: Can't Seem to Run Individual Test Suites in pandas/io | {
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$ python /home/user/Repositories/pandas/pandas/io/tests/test_data.py
Traceback (most recent call last):
File "/home/user/Repositories/pandas/pandas/io/tests/test_data.py", line 4, in <module>
from pandas import compat
File "/home/user/miniconda2/envs/pandas-dev/lib/python2.7/site-packages/pandas/__init__.py... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13016 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13016/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13016/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13016/events | https://github.com/pandas-dev/pandas/issues/13016 | 151,646,081 | MDU6SXNzdWUxNTE2NDYwODE= | 13,016 | Pandas pytables interface doesn't create empty table datasets | {
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... | 27 | 2016-04-28T13:49:01Z | 2021-04-23T05:11:04Z | null | NONE | null | Pandas used to allow the writing of empty HDF5 datasets through its pytables interface code. However, after upgrading to 0.17 (from 0.11), we've discovered that this behaviour is intentionally
short circuited. The library behaves as though the dataset is being written, but simply ignores the request and the resulting H... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13017 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13017/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13017/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13017/events | https://github.com/pandas-dev/pandas/issues/13017 | 151,649,448 | MDU6SXNzdWUxNTE2NDk0NDg= | 13,017 | Three or more unnamed fields block loc assignment | {
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... | 10 | 2016-04-28T14:03:33Z | 2021-04-24T03:50:22Z | 2021-04-24T03:50:21Z | NONE | null | Writing a dataframe to csv using `df.to_csv("/path/to/file.csv")` causes the creation of an "unnamed" field containing the indexes of the rows. Continually writing/reading to/from this file will result in many "unnamed" fields. Once there are three unnamed fields you can no longer use loc to replace values, what's more... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13018 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13018/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13018/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13018/events | https://github.com/pandas-dev/pandas/issues/13018 | 151,674,728 | MDU6SXNzdWUxNTE2NzQ3Mjg= | 13,018 | Failed ri2py conversion of Vectors.ListVector object to Python dictionary | {
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"followers_url": "https://api.github.com/users/jorisva... | 10 | 2016-04-28T15:36:02Z | 2017-01-16T16:22:36Z | 2016-04-28T15:46:22Z | CONTRIBUTOR | null | Current conversion of R objects into Python usng `pandas2ri.ri2py` does not work for the `<class 'rpy2.robjects.vectors.ListVector'>` object. As noted [here](http://pandas.pydata.org/pandas-docs/stable/r_interface.html), `pandas2ri.py2ri()` and `pandas2ri.ri2py()` are current methods to handle conversion. However, prev... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13019 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13019/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13019/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13019/events | https://github.com/pandas-dev/pandas/issues/13019 | 151,691,376 | MDU6SXNzdWUxNTE2OTEzNzY= | 13,019 | Categorical dtypes cause error when attempting stacked bar plot | {
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``` python
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
# running this code in terminal/ipython
%matplotlib qt
import matplotlib.pylab
import matplotlib.pyplot as plt
geographies = ['north america', 'central/south america', 'europe', 'africa', 'asia', 'o... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13020 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13020/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13020/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13020/events | https://github.com/pandas-dev/pandas/issues/13020 | 151,717,849 | MDU6SXNzdWUxNTE3MTc4NDk= | 13,020 | Unclear error produced by resampling with NaT in Index | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-04-28T18:58:36Z | 2016-05-18T22:10:30Z | 2016-05-18T22:10:30Z | CONTRIBUTOR | null | Similar to #4746, trying to `resample` with an index containing `NaT` produces rather ambiguous error messages of the form:
> ValueError: Shape of passed values is (2, 5), indices imply (2, 4)
Something like `cannot resample from index containing Not-a-Time (NaT)` would be more helpful to users.
#### MWE
``` pytho... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13021 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13021/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13021/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13021/events | https://github.com/pandas-dev/pandas/issues/13021 | 151,738,115 | MDU6SXNzdWUxNTE3MzgxMTU= | 13,021 | to_html formatter not called for float values in a mixed-type column | {
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... | 8 | 2016-04-28T20:40:37Z | 2021-04-24T03:52:09Z | null | NONE | null | #### When column x has float64 type, the custom formatter is applied to every value
```
t = pd.DataFrame([[0], [10.4], [3]], columns=['x'])
display(HTML(t.to_html(formatters=dict(x='xxx'.format))))
x
------
0 xxx
1 xxx
2 xxx
```
#### But when column x is mixed type, the formatter isn't called for (only) floatin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13022 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13022/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13022/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13022/events | https://github.com/pandas-dev/pandas/issues/13022 | 151,738,166 | MDU6SXNzdWUxNTE3MzgxNjY= | 13,022 | BUG: resample with TimedeltaIndex, fenceposts are off | {
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"followers_url": "https://api.github... | 3 | 2016-04-28T20:40:50Z | 2018-09-05T11:31:04Z | 2018-09-05T11:31:04Z | CONTRIBUTOR | null | brought up in #12925
some examples in #15167
Resampling fence posts are off when upsampling < 1 Day.
```
In [5]: df = DataFrame(data=[[1, 3], [-5, 10], [0, 0]],index=pd.timedelta_range('00:00:00','00:10:00',freq='5T'))
In [6]: df.resample('1T').asfreq()
Out[6]:
0 1
00:00:00 1.0 3.0
0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13023 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13023/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13023/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13023/events | https://github.com/pandas-dev/pandas/issues/13023 | 151,769,755 | MDU6SXNzdWUxNTE3Njk3NTU= | 13,023 | equals method of dataframe doesn't return the same as (df1 == df2).all().all() | {
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"color": "005... | closed | false | null | [] | null | 2 | 2016-04-29T00:04:47Z | 2016-04-29T13:57:01Z | 2016-04-29T13:56:53Z | NONE | null | I have created two dataframes with earthquake data that I am trying to compare. The elements in the dataframes should be equal. The files are attached below.
[broken_df.zip](https://github.com/pydata/pandas/files/241604/broken_df.zip)
#### Code Sample, a copy-pastable example if possible
``` python
import pandas as p... | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
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- [x] tests added / passed
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Enabled true division. It also prevents differences between py2 / py3.
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https://api.github.com/repos/pandas-dev/pandas/issues/13026 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13026/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13026/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13026/events | https://github.com/pandas-dev/pandas/pull/13026 | 151,783,543 | MDExOlB1bGxSZXF1ZXN0NjgzMTg5Nzc= | 13,026 | BUG/TST: Calling shift on a DatetimeIndex of length 0 returns an Index in… | {
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No what's new as the fixed timing is unclear.
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xref: https://github.com/pydata/pandas/issues/12398, #12402 (not merged)
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https://api.github.com/repos/pandas-dev/pandas/issues/13028 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13028/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13028/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13028/events | https://github.com/pandas-dev/pandas/pull/13028 | 151,787,089 | MDExOlB1bGxSZXF1ZXN0NjgzMjExNzk= | 13,028 | BUG/TST: TimeGrouper has erroneous groups if key length is too short | {
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- [x] tests added / passed
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No what's new as the fixed timing is unclear.
**NOTE** Different from `TimeGrouper` with single key, it doesn't interpolate missing datetimes between existing keys (same as current behavior of ke... | {
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Tutorial at [pandas.pydata.org/pandas-docs/stable/10min.html](http://pandas.pydata.org/pandas-docs/stable/10min.html) has the following code, where the obvious mistake is having only 1 key "foo" instead of 2 keys: "foo" and "bar" throughout the whole example
---
# Join
## SQL style merges. See the Database style... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13030 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13030/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13030/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13030/events | https://github.com/pandas-dev/pandas/issues/13030 | 151,946,735 | MDU6SXNzdWUxNTE5NDY3MzU= | 13,030 | pd.to_datetime giving invalid output | {
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```
>>> pd.to_datetime(1, unit='D')
Timestamp('1970-01-02 00:00:00')
```
However, the following gives incorrect output:
```
>>> pd.to_datetime(1, unit='D', errors='coerce')
NaT
```
#### Details of Configuration:
python: 2.7.11.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13031 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13031/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13031/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13031/events | https://github.com/pandas-dev/pandas/issues/13031 | 151,961,832 | MDU6SXNzdWUxNTE5NjE4MzI= | 13,031 | Feature request: pandas.DataFrame.to_sas | {
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] | closed | false | null | [] | null | 1 | 2016-04-29T20:28:29Z | 2016-04-29T20:40:35Z | 2016-04-29T20:40:31Z | NONE | null | Hello,
I find very usefull `pandas.read_sas` but, as I'm collaborating a lot with SAS users, I'm wondering if there are some plans to implement `pandas.DataFrame.to_sas`?
Up to now, the only possibility I see is to pass through common file formats like `pandas.DataFrame.to_csv`.
Thanks a lot for your help.
Best reg... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13032 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13032/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13032/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13032/events | https://github.com/pandas-dev/pandas/issues/13032 | 151,973,347 | MDU6SXNzdWUxNTE5NzMzNDc= | 13,032 | Justification is broken with to_string(index=False) | {
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"followers_url": "https://api.github... | 7 | 2016-04-29T21:33:36Z | 2018-09-25T12:55:05Z | 2018-09-25T12:55:05Z | CONTRIBUTOR | null | With 0.17.1, justification is handled correctly:
```
In [3]: df = pd.DataFrame(np.random.randn(3, 3), columns=['one', 'two', 'three'])
In [4]: print df.to_string(index=False)
one two three
0.096065 -0.529437 -2.058535
0.588013 0.221911 -2.400129
0.848234 -0.093931 1.221708
```
But in 0.18.0, it'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13033 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13033/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13033/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13033/events | https://github.com/pandas-dev/pandas/pull/13033 | 151,985,171 | MDExOlB1bGxSZXF1ZXN0Njg0NDU1MDU= | 13,033 | BUG: to_datetime when called with a unit and coerce is buggy | {
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```
In [2]: import pandas as pd
In [3]: a = pd.Series([True,False,True])
In [4]: a
Out[4]:
0 True
1 False
2 True
dtype: bool
In [6]: a[0] = pd.np.nan
In [7]: a
Out[7]:
0 NaN
1 0.0
2 1.0
dtype: float64
```
#### Expected Output
based on typ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13035 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13035/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13035/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13035/events | https://github.com/pandas-dev/pandas/issues/13035 | 151,991,584 | MDU6SXNzdWUxNTE5OTE1ODQ= | 13,035 | index.set_levels produces weird results when index is repetative | {
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... | 2 | 2016-04-30T00:07:56Z | 2019-09-05T16:13:39Z | 2019-09-05T16:13:38Z | NONE | null | My understanding of how multiindexes work is fuzzy, but as far as I can tell set_levels isn't updating the labels properly. The example probably explains better than I can:
#### Code
``` python
df = pd.DataFrame(data = ["foo","bar"])
df2 = pd.concat([df,df,df],keys = ["a","b","c"])
print df2
newIndex = df2.index.get_l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13036 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13036/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13036/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13036/events | https://github.com/pandas-dev/pandas/pull/13036 | 151,997,635 | MDExOlB1bGxSZXF1ZXN0Njg0NTMwNjg= | 13,036 | PERF: Sparse IntIndex.make_union / Numeric ops | {
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- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Replace repeated `list.append` with `np.union1d` in `IntIndex.make_union`. `make_union` is used in numeric ops.
**NOTE:** It is also possible to fix `IntIndex.intersect` to use `np.intersect1d`, but it doesn't inc... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13037 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13037/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13037/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13037/events | https://github.com/pandas-dev/pandas/pull/13037 | 152,009,942 | MDExOlB1bGxSZXF1ZXN0Njg0NTg0Mzk= | 13,037 | BUG: subclassed .align returns normal DataFrame | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-04-30T04:59:59Z | 2016-04-30T14:56:46Z | 2016-04-30T14:56:43Z | MEMBER | null | - [x] closes #12983
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
Also fixed a bug which `Series.align(DataFrame)` raises `AttributeError`.
```
pd.Series([1, 2], index=['a', 'b']).align(pd.DataFrame([1, 2], index=['a', 'c']))
# AttributeError: 'Series' object ... | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
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https://api.github.com/repos/pandas-dev/pandas/issues/13039 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13039/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13039/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13039/events | https://github.com/pandas-dev/pandas/pull/13039 | 152,012,350 | MDExOlB1bGxSZXF1ZXN0Njg0NTk0MTU= | 13,039 | TST/BUG: DataFrame truncated repr with DatetimeTz and NaT column | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
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https://api.github.com/repos/pandas-dev/pandas/issues/13040 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13040/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13040/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13040/events | https://github.com/pandas-dev/pandas/issues/13040 | 152,013,181 | MDU6SXNzdWUxNTIwMTMxODE= | 13,040 | API: use argument-free lambdas for injecting DataFrames columns as variables? | {
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``` python
(df[lambda: sepal_length > 3]
.groupby(lambda: pd.cut(sepal_width, 5))
.apply(lambda: petal_width.mean()))
```
Syntax like `df[lambda: sepal_length >... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13041 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13041/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13041/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13041/events | https://github.com/pandas-dev/pandas/issues/13041 | 152,028,552 | MDU6SXNzdWUxNTIwMjg1NTI= | 13,041 | secondary_y sequence doesn't work | {
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... | open | false | null | [] | null | 4 | 2016-04-30T12:42:50Z | 2020-04-30T05:52:56Z | null | NONE | null | #### Code Sample, a copy-pastable example if possible
```
import pandas
df = pandas.DataFrame({'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [7, 8, 9], 'd': [10, 11, 12]})
df.plot(y=['a', 'b'], secondary_y=['c', 'd'])
```
I only get the primary axis results:
![figure_1](https://cloud.githubusercontent.com/assets/2196196/14935... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13042 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13042/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13042/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13042/events | https://github.com/pandas-dev/pandas/pull/13042 | 152,030,043 | MDExOlB1bGxSZXF1ZXN0Njg0Njc4Njc= | 13,042 | BUG: Convert non-dates in xls date cells to number | {
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"followers_url": "https://api.github.com/users/jr... | 11 | 2016-04-30T13:22:19Z | 2016-05-06T12:11:02Z | 2016-05-06T12:10:40Z | CONTRIBUTOR | null | - [x ] closes #10001
- [x ] tests added / passed
- [x ] passes `git diff upstream/master | flake8 --diff`
- [x ] whatsnew entry
closes GH10001
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https://api.github.com/repos/pandas-dev/pandas/issues/13043 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13043/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13043/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13043/events | https://github.com/pandas-dev/pandas/issues/13043 | 152,031,752 | MDU6SXNzdWUxNTIwMzE3NTI= | 13,043 | BUG: Series with datetime-like object ops raises TypeError | {
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```
pd.Series([pd.Timestamp('2015-01-01', tz='US/Eastern'),
pd.Timestamp('2015-01-01', tz='Asia/Tokyo')]) + pd.Timedelta('1 days')
# TypeError: unsupported operand type(s) for +: 'numpy.ndarray' and 'Timedelta'
pd.Series([pd.Period('2015-01-01', freq='D... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13044 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13044/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13044/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13044/events | https://github.com/pandas-dev/pandas/issues/13044 | 152,042,577 | MDU6SXNzdWUxNTIwNDI1Nzc= | 13,044 | COMPAT: should an empty string match a format (or just be NaT) | {
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"followers_url": "https://api.github.com/users/j... | 3 | 2016-04-30T17:29:37Z | 2020-11-19T18:58:15Z | 2020-11-19T18:58:15Z | CONTRIBUTOR | null | after #13033
I left this alone, but should an empty string just be a `NaT` (like we do elsewhere), even when a `format`is present?
```
In [1]: td = pd.Series(['May 04', 'Jun 02', ''], index=[1, 2, 3])
In [2]: td
Out[2]:
1 May 04
2 Jun 02
3
dtype: object
In [3]: pd.to_datetime(td, format='%b %y', ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13045 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13045/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13045/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13045/events | https://github.com/pandas-dev/pandas/pull/13045 | 152,048,471 | MDExOlB1bGxSZXF1ZXN0Njg0NzcwMzI= | 13,045 | DOC: Add tutorial link | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-04-30T19:43:36Z | 2016-05-01T13:50:06Z | 2016-05-01T13:49:58Z | CONTRIBUTOR | null | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13046 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13046/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13046/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13046/events | https://github.com/pandas-dev/pandas/issues/13046 | 152,055,507 | MDU6SXNzdWUxNTIwNTU1MDc= | 13,046 | BUG: SeriesGroupBy.transform() tries to do dtype downcasting, NDFrameGroupBy.transform() - doesn't do this | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-04-30T22:07:32Z | 2017-02-27T21:39:11Z | 2016-04-30T23:10:59Z | CONTRIBUTOR | null | #### Code Sample, a copy-pastable example if possible
original: http://stackoverflow.com/questions/36960086/groupby-how-to-extract-seconds-from-datetime-with-diff
```
data = """
idx A ID3 DATETIME
0 B-028 b76cd912ff "2014-10-08 13:43:27"
1 B-054 4a57ed0b02 "2014-10-08 14:26:19"
2 B-07... | {
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TST: use 32bit_repr when printing formatting of sparse
COMPAT: ensure consensus name when Indexes are union/intersected if possible
COMPAT: skip some coercion tests on 32-bit
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```
In [1]: sp = pd.SparseDataFrame([1, 2, 3])
In [2]: np.cumsum(sp)
ValueError: No axis named None for object type <class 'pandas.sparse.frame.SparseDataFrame'>
In [3]: np.cumsum(sp, axis=0)
Out[3]:
0
0 1.0
1 3.0
2 6.0
In [4]: np.cumsum(sp, axis=1)
Out[4]:
0
0 1.0
1 2.0
2 3.0
```
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In _pd.read_sql_ and _pd.read_sql_table_ when the _chunksize_ parameter is set, Pandas builds a DataFrame with dtypes inferred from the data **in the chunk**. This can be a problem if an INTEGER colum contains null values in some chunks but not in others, leading the same column to be int64 in some cases a... | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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"followers_url": "https://api.github... | 4 | 2016-05-01T21:40:16Z | 2018-06-28T10:23:02Z | 2018-06-28T10:23:02Z | CONTRIBUTOR | null | I ran into an issue where the behavior of `.apply()` changed from 0.16 to 0.17, causing different results on tz aware data. Extracting the hour of day from datetimes is different for `Series(x).apply(func)` vs `func(x)`. Below is a minimal example of the issue in 0.17, it seems the behavior is the same in 0.18 but diff... | {
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#### Code Sample, a copy-pastable example if possible
In IPython:
``` python
import pandas as pd
pd.D... | {
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... | 13 | 2016-05-02T06:33:38Z | 2021-10-07T11:04:13Z | null | NONE | null | If I use MultiIndex columns and if a level happens to have empty values for all columns, the saved CSV file cannot be read. I expected to recover the dataframe from the saved CSV perfectly.
I believe #6618 might be related, because this is somehow related to how Pandas uses an empty data row to separate column names a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13056 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13056/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13056/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13056/events | https://github.com/pandas-dev/pandas/issues/13056 | 152,567,645 | MDU6SXNzdWUxNTI1Njc2NDU= | 13,056 | API: inconsistent return format of groupby apply | {
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... | open | false | null | [] | null | 14 | 2016-05-02T14:42:09Z | 2021-06-11T13:08:21Z | null | NONE | null | related issues:
- [x] #13121
- [x] #5839
- [x] #9867
- [x] #13255
- [x] #20066
- [ ] #14927 (about detecting mutating functions)
_Thank you very much for provide us pandas which is really a good packages I have used!_
### There were several times when I use pandas but get inconsistent return format which f... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13057 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13057/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13057/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13057/events | https://github.com/pandas-dev/pandas/issues/13057 | 152,584,127 | MDU6SXNzdWUxNTI1ODQxMjc= | 13,057 | ENH: add option to tz_localize to return NaT instead of raising a NonExistentTimeError | {
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"followers_url": "https://api.github.com/users/jr... | 7 | 2016-05-02T16:00:24Z | 2016-05-07T14:59:43Z | 2016-05-07T14:59:43Z | CONTRIBUTOR | null | It would be nice if the `tz_localize` function of a `DatetimeIndex` had an optional flag for silently returning `NaT` instead of throwing a `NonExistentTimeError`, if the timestamp is not valid in the given timezone (for example due to DST changes).
I ran into this problem while trying to `tz_localize` a large index, a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13058 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13058/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13058/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13058/events | https://github.com/pandas-dev/pandas/pull/13058 | 152,640,376 | MDExOlB1bGxSZXF1ZXN0Njg2MTgxMzk= | 13,058 | ENH: Add an errors flag to tz_localize | {
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Author: dancsi szilagyi.d@gmail.com
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https://api.github.com/repos/pandas-dev/pandas/issues/13059 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13059/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13059/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13059/events | https://github.com/pandas-dev/pandas/pull/13059 | 152,678,840 | MDExOlB1bGxSZXF1ZXN0Njg2NDUzNDM= | 13,059 | BUG: More followups on to_datetime exceptions, xref #13033 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13060 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13060/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13060/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13060/events | https://github.com/pandas-dev/pandas/pull/13060 | 152,688,611 | MDExOlB1bGxSZXF1ZXN0Njg2NTA5OTk= | 13,060 | DOC: add warning section in indexing docs. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13061 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13061/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13061/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13061/events | https://github.com/pandas-dev/pandas/issues/13061 | 152,697,610 | MDU6SXNzdWUxNTI2OTc2MTA= | 13,061 | DOC: DataFrame.to_hdf() docstring does not mention data_columns | {
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To be able to do on-disk filtering per column, one needs to store not only in `table` format, but also create an index in the HDF file for the columns required to be indexed, or setting it to `True`, for all columns to be indexed.
This needs to be done by using the... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13062 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13062/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13062/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13062/events | https://github.com/pandas-dev/pandas/issues/13062 | 152,699,471 | MDU6SXNzdWUxNTI2OTk0NzE= | 13,062 | HDF query with long literal string fails | {
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``` python
c_ids = ['50ef419195e6e40eac000001', '50ef419195e6e40eac000002', '50ef419195e6e40eac000003']
df = pd.DataFrame({'class_id':c_ids, 'a':range(3)})
df.to_hdf('teststore.hdf', 'df',format='t', data_columns=True)
print('with variable')
c_id = '50ef419195e6... | {
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To keep it sim... | {
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``` python
import pandas as pd
def test():
names = ['openid', 'clientid', 'roleid', 'rolename', 'school', 'IP', 'snid', 'rolelogin_time', 'amount', 'val', 'consume_sum', 'own_after', 'first_payment_time', 'last_payment_time', 'last_l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13065 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13065/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13065/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13065/events | https://github.com/pandas-dev/pandas/pull/13065 | 152,749,001 | MDExOlB1bGxSZXF1ZXN0Njg2ODk3MDQ= | 13,065 | add data_columns to doc string | {
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- [ ] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
How about this for #13061 ?
I don't think pandas has tests for each documented field, correct?
Do you want a whatsnew entry for this? If yes, how does that work? The guidelines don't talk about ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13066 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13066/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13066/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13066/events | https://github.com/pandas-dev/pandas/pull/13066 | 152,807,437 | MDExOlB1bGxSZXF1ZXN0Njg3Mjc4MjA= | 13,066 | BUG: Default to stat axis for SparseDataFrame when axis=None | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13067 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13067/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13067/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13067/events | https://github.com/pandas-dev/pandas/pull/13067 | 152,826,611 | MDExOlB1bGxSZXF1ZXN0Njg3NDA5Njc= | 13,067 | BUG: Period resample with length=0 doesn't set freq | {
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- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
given freq is not applied if data is empty.
```
s = pd.Series(index=pd.PeriodIndex([], freq='D'))
s.resample('M').mean()
# Series([], Freq: D, dtype: float64)
```
#### Expected
```
s.resample('M').mean()
# Series(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13068 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13068/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13068/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13068/events | https://github.com/pandas-dev/pandas/issues/13068 | 152,827,225 | MDU6SXNzdWUxNTI4MjcyMjU= | 13,068 | Python 3 writing to_csv file ignores encoding argument. | {
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"default": false,
"description": "Unicode strings",
"i... | closed | false | null | [] | {
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"created_at": "2020-05-29T23:47:32Z",
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"followers_url": "https://api.github.com/users/j... | 32 | 2016-05-03T17:13:57Z | 2020-08-07T11:53:10Z | 2020-08-07T11:53:10Z | CONTRIBUTOR | null | ``` python
# is missing the UTF8 BOM (encoded with default encoding UTF8)
with open('path_to_f', 'w') as f:
df.to_csv(f, encoding='utf-8-sig')
# is not missing the UTF8 BOM (encoded with passed encoding utf-8-sig)
df.to_csv('path_to_f', encoding='utf-8-sig')
```
I expect:
``` python
with open('path_to_f', 'w') a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13069 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13069/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13069/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13069/events | https://github.com/pandas-dev/pandas/pull/13069 | 152,828,048 | MDExOlB1bGxSZXF1ZXN0Njg3NDE3NjQ= | 13,069 | BUG: Addition raises TypeError if Period is on rhs | {
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- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
`Period` addition raises `TypeError` if `Period` is on right hand side.
```
1 + pd.Period('2011-01', freq='M')
# TypeError: unsupported operand type(s) for +: 'int' and 'pandas._period.Period'
```
#### Expected
``... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13070 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13070/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13070/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13070/events | https://github.com/pandas-dev/pandas/pull/13070 | 152,834,554 | MDExOlB1bGxSZXF1ZXN0Njg3NDYzMjI= | 13,070 | DOC: add warning section in indexing docs | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13071 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13071/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13071/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13071/events | https://github.com/pandas-dev/pandas/pull/13071 | 152,835,127 | MDExOlB1bGxSZXF1ZXN0Njg3NDY3Mzg= | 13,071 | BUG: PeriodIndex and Period subtraction error | {
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- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Similar to #5202. `PeriodIndex` subtraction raises `AttributeError` either side is `Period` (scalar).
```
pd.PeriodIndex(['2011-01', '2011-02'], freq='M') - pd.Period('2011-01', freq='M')
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https://api.github.com/repos/pandas-dev/pandas/issues/13072 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13072/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13072/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13072/events | https://github.com/pandas-dev/pandas/pull/13072 | 152,838,584 | MDExOlB1bGxSZXF1ZXN0Njg3NDkyNzg= | 13,072 | BUG: Series ops with object dtype may incorrectly fail | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
This must be after #13069.
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https://api.github.com/repos/pandas-dev/pandas/issues/13073 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13073/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13073/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13073/events | https://github.com/pandas-dev/pandas/pull/13073 | 152,858,260 | MDExOlB1bGxSZXF1ZXN0Njg3NjMxODU= | 13,073 | BUG: Respect Filtered Categorical in Crosstab | {
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"followers_url": "https://api.github.com/users/jorisva... | 15 | 2016-05-03T19:44:07Z | 2016-05-13T00:43:14Z | 2016-05-13T00:20:25Z | MEMBER | null | Closes #12298 by stripping the `Categorical` elements of their original categories so that only their included values are considered during the counting / aggregation.
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https://api.github.com/repos/pandas-dev/pandas/issues/13074 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13074/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13074/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13074/events | https://github.com/pandas-dev/pandas/issues/13074 | 152,881,094 | MDU6SXNzdWUxNTI4ODEwOTQ= | 13,074 | Add .tobytes() method to categorical type | {
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"descript... | closed | false | null | [] | null | 8 | 2016-05-03T21:40:49Z | 2016-05-03T21:57:04Z | 2016-05-03T21:54:31Z | NONE | null | It would be nice to have this implemented so that a parallel apply using `dask` could be used on dataframes with `Categorical` type columns.
Right now if I try to use `Dask` for a parallelized apply like so:
``` python
import dask.dataframe as dd
df_test = pd.DataFrame({'id': ['a', 'a', 'a', 'b', 'b'],
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https://api.github.com/repos/pandas-dev/pandas/issues/13075 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13075/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13075/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13075/events | https://github.com/pandas-dev/pandas/issues/13075 | 152,888,735 | MDU6SXNzdWUxNTI4ODg3MzU= | 13,075 | More comprehensive testing for interp methods 'piecewise_polynomial' / 'from_derivatives' | {
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... | 2 | 2016-05-03T22:26:58Z | 2021-04-24T03:59:34Z | null | NONE | null | @jreback Just opening this up as the next step after pydata/pandas#12887.
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https://api.github.com/repos/pandas-dev/pandas/issues/13076 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13076/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13076/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13076/events | https://github.com/pandas-dev/pandas/issues/13076 | 152,897,251 | MDU6SXNzdWUxNTI4OTcyNTE= | 13,076 | TST: assert_series/frame not comparing for categoricals | {
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```
In [1]: df1 = DataFrame({'A' : Series(list('aba')).astype('category', categories=list('ab'), ordered=True)})
In [2]: df2 = DataFrame({'A' : Series(list('aba')).astype('category', categories=list('ba'), ordered=True)})
In [3]: tm.assert_frame_equal(df1, df2)
In [11]: df2... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13077 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13077/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13077/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13077/events | https://github.com/pandas-dev/pandas/issues/13077 | 152,912,518 | MDU6SXNzdWUxNTI5MTI1MTg= | 13,077 | ENH/API: Decide what to return Period - Period subtraction | {
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"followers_url": "https://api.github... | 6 | 2016-05-04T01:49:30Z | 2018-06-29T00:45:49Z | 2018-06-29T00:45:49Z | MEMBER | null | #### Code Sample, a copy-pastable example if possible
Split from #13071. Currently it returns int and loses freq info.
```
pd.Period('2011-03', freq='M') - pd.Period('2011-01', freq='M')
#2
```
#### Expected Output
Current ideas are:
1. Return `Timedelta` adding support of `Monthly` freq.
2. Return `Perioddelta` ne... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13078 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13078/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13078/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13078/events | https://github.com/pandas-dev/pandas/issues/13078 | 152,912,833 | MDU6SXNzdWUxNTI5MTI4MzM= | 13,078 | BUG/ERR: DatetimeIndex - Period shows ununderstandable error | {
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Split from #13071. `DatetimeIndex` - `Period` is not supported ATM, but errors are not understandable.
```
pd.DatetimeIndex(['2011-01-01', '2011-02-01']) - pd.Period('2011-01-01', freq='D')
# ValueError: Cannot do arithmetic with non-conforming periods
pd.Dateti... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13079 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13079/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13079/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13079/events | https://github.com/pandas-dev/pandas/pull/13079 | 152,919,578 | MDExOlB1bGxSZXF1ZXN0Njg4MDQ4Nzk= | 13,079 | BUG: Empty PeriodIndex issues | {
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- [x] tests added / passed
- [X] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
closes #13067
closes #13212
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https://api.github.com/repos/pandas-dev/pandas/issues/13080 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13080/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13080/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13080/events | https://github.com/pandas-dev/pandas/pull/13080 | 152,928,065 | MDExOlB1bGxSZXF1ZXN0Njg4MTAzMTM= | 13,080 | TST: fix assert_categorical_equal message | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] no whatsnew as it is internal test method
```
a = pd.Categorical([1, 2, 3, 4])
b = pd.Categorical([1, 2, 3, 5])
tm.assert_categorical_equal(a, b)
# Categorical.categories are different
# ...
a = pd.Categor... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13081 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13081/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13081/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13081/events | https://github.com/pandas-dev/pandas/pull/13081 | 152,998,566 | MDExOlB1bGxSZXF1ZXN0Njg4NTMxNzA= | 13,081 | TST/CLN: Cleanup test_pickle | {
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- [x] passes `git diff upstream/master | flake8 --diff`
Merging comparison dispatch logic.
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https://api.github.com/repos/pandas-dev/pandas/issues/13082 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13082/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13082/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13082/events | https://github.com/pandas-dev/pandas/pull/13082 | 152,999,808 | MDExOlB1bGxSZXF1ZXN0Njg4NTQwMzA= | 13,082 | PERF: Sparse ops speedup | {
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- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Follow-up for #13036. Perf improvements are not significant because the number of previous `list.append` call is not so large.
```
import numpy as np
import pandas as pd
np.random.seed(1)
N = 1000000
a = np.array(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13083 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13083/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13083/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13083/events | https://github.com/pandas-dev/pandas/issues/13083 | 153,005,819 | MDU6SXNzdWUxNTMwMDU4MTk= | 13,083 | ohlc resampling returns a different type depending on upsampling vs downsampling | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-05-04T13:01:38Z | 2017-10-01T14:55:33Z | 2017-10-01T14:55:33Z | CONTRIBUTOR | null | Upsampling returns a Series, Downsampling returns a DataFrame. Is this valid?
``` python
In [80]: series=pd.Series(range(10), index=pd.PeriodIndex(start='2000', freq='D', periods=10))
In [81]: series
Out[81]:
2000-01-01 0
2000-01-02 1
2000-01-03 2
2000-01-04 3
2000-01-05 4
2000-01-06 5
2000-01-07 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13084 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13084/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13084/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13084/events | https://github.com/pandas-dev/pandas/issues/13084 | 153,031,868 | MDU6SXNzdWUxNTMwMzE4Njg= | 13,084 | ERR: concat of non-unique join axes should have better error | {
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... | 6 | 2016-05-04T14:52:24Z | 2020-01-07T11:49:58Z | 2020-01-07T11:49:58Z | NONE | null | You get a confusing error message when trying to concat on non-unique (but also non-exactly-equal) indices. Small example:
```
In [57]: df1 = pd.DataFrame({'col1': [1, 2, 3]}, index=[0, 0, 1])
...: df2 = pd.DataFrame({'col2': [1, 2, 3]}, index=[0, 1, 2])
In [59]: pd.concat([df1, df2], axis=1)
-------------... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-05-04T23:27:19Z | 2016-05-05T00:35:19Z | 2016-05-04T23:28:30Z | NONE | null | I was on PyPI just now, and the [only versions](https://pypi.python.org/pypi/pandas) of pandas available are 0.17.1 and 0.18.0. Trying https://pypi.python.org/pypi/pandas/0.18.1 leads to a 404 page. I tried installing via `pip`, and it can't find 0.18.1 either. Is there an issue communicating with PyPI, or is something... | {
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```
def get_user_account_credentials(): # https://github.com/pydata/pandas/blob/master/pandas/io/gbq.py#L160
from oauth2client.client import OAuth2WebServerFlow
from oauth2client.file import Storage
from oauth2client.tools import run_flow, argparser
reauth = False
flow = OAuth2W... | {
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... | closed | false | null | [] | null | 28 | 2016-05-05T01:37:38Z | 2017-01-21T23:14:36Z | 2017-01-21T23:14:36Z | NONE | null | - [x] closes #13086
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
Also did little cleanup of `testing.pyx` and `testing.py`.
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... | 9 | 2016-05-05T11:17:10Z | 2021-04-24T04:02:47Z | null | CONTRIBUTOR | null | #### Code Sample, a copy-pastable example if possible
Unfortunately can't reproduce it with other examples. Only this which I load from csv.
`txn.loc[pd.Timestamp('2014-06-04 00:00:00'):]`
``` --------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13091 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13091/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13091/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13091/events | https://github.com/pandas-dev/pandas/pull/13091 | 153,222,910 | MDExOlB1bGxSZXF1ZXN0NjkwMDA3OTk= | 13,091 | TST: Fix assertNotIsInstance msg | {
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- [x] passes `git diff upstream/master | flake8 --diff`
The current error message below is confusing.
```
tm.assertNotIsInstance(pd.Series([1]), pd.Series)
# AssertionError: Expected object to be of type <class 'pandas.core.series.Series'>, found <class 'pandas.core.series.Series'> instead
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https://api.github.com/repos/pandas-dev/pandas/issues/13092 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13092/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13092/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13092/events | https://github.com/pandas-dev/pandas/issues/13092 | 153,227,403 | MDU6SXNzdWUxNTMyMjc0MDM= | 13,092 | ENH: pd.read_feather/to_feather | {
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so this should be straightforward. a couple of things to note.
- should support the `LocalPath/PathLib` objects (easy as we do this in other `read_*`)
- non-supported on windows ATM. need to skip for testing. `feather-format` will just... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13093 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13093/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13093/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13093/events | https://github.com/pandas-dev/pandas/pull/13093 | 153,263,329 | MDExOlB1bGxSZXF1ZXN0NjkwMjc3ODk= | 13,093 | Improve error message for category dtype in HDF5, format="fixed" store. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13094 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13094/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13094/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13094/events | https://github.com/pandas-dev/pandas/issues/13094 | 153,267,853 | MDU6SXNzdWUxNTMyNjc4NTM= | 13,094 | ERR: warning on merging on unequal levels for an Index | {
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... | 6 | 2016-05-05T16:20:59Z | 2021-04-24T04:04:25Z | null | CONTRIBUTOR | null | I found what seems to me a behavior that might be wrong when joining a simple index df with a multiindex df.
I'm admittedly not an SQL expert and I'm not sure this is really a bug.
Consider the case:
``` python
X = pd.DataFrame([[2, 3], [5, 7]], columns=['a','p']).set_index('a')
Y = pd.DataFrame([[1, 2, 3], [3, 4, 8],... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13095 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13095/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13095/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13095/events | https://github.com/pandas-dev/pandas/issues/13095 | 153,279,348 | MDU6SXNzdWUxNTMyNzkzNDg= | 13,095 | Problems installing pandas using pip | {
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I installed pandas via pip git
`pip install git+git://github.com/pydata/pandas.git`
and during the installation it says:
`Running setup.py install for pandas ... done
Successfully installed pandas-0.18.0+207.gc6110e2`
But when I want to import it, it gives an error
`C extension: hashtable not built.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13096 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13096/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13096/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13096/events | https://github.com/pandas-dev/pandas/pull/13096 | 153,281,660 | MDExOlB1bGxSZXF1ZXN0NjkwNDAyMzc= | 13,096 | add --force to pandas build error message | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-05-05T17:31:59Z | 2016-05-05T17:36:14Z | 2016-05-05T17:36:14Z | CONTRIBUTOR | null | - [x] closes #13095
- [ ] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/13097 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13097/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13097/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13097/events | https://github.com/pandas-dev/pandas/issues/13097 | 153,295,585 | MDU6SXNzdWUxNTMyOTU1ODU= | 13,097 | TST: Start using py.test | {
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Currently _most_ of the tests pass with pytest, but there are 69 that don't. Most of these look like they're pickle or SQL / external resources issues.
pytest output here: https://gist.github.com/MaximilianR/225a071337e335ebdcc1d17637126126
So this does need a champio... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13098 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13098/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13098/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13098/events | https://github.com/pandas-dev/pandas/issues/13098 | 153,298,994 | MDU6SXNzdWUxNTMyOTg5OTQ= | 13,098 | REGRP: Series.quantile returns NaN | {
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``` python
import pandas as pd
import numpy
s = pd.Series([1, 2, 3, 4, numpy.nan])
s.quantile(0.5)
nan
```
#### Expected Output
I would expect 2.5 as output (as with version 0.17.1).
#### output of `pd.show_versions()`
commit: None
python: 2.7.6.final.0
python-bi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13099 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13099/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13099/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13099/events | https://github.com/pandas-dev/pandas/pull/13099 | 153,324,625 | MDExOlB1bGxSZXF1ZXN0NjkwNjkzOTc= | 13,099 | COMPAT: add 0.17.0 pickle/msgpacks | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13100 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13100/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13100/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13100/events | https://github.com/pandas-dev/pandas/issues/13100 | 153,340,524 | MDU6SXNzdWUxNTMzNDA1MjQ= | 13,100 | AttributeError when trying to freeze pandas.io.sql.read_sql() with cx_freeze | {
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When freezing an application that uses `pandas.io.sql.read_sql()` (alias: `pd.read_sql()`) via cx_freeze, the build succeeds but the execution fails with `AttributeError: 'str' object has no attribute 'cursor'`.
#### Code
Below are the minimum requirements to recreate the issue. Put both files in an empt... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13101 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13101/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13101/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13101/events | https://github.com/pandas-dev/pandas/issues/13101 | 153,396,150 | MDU6SXNzdWUxNTMzOTYxNTA= | 13,101 | BUG: .filter with unicode labels when can't encode | {
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"description": "Unicode strings",
"i... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-05-06T07:41:01Z | 2017-11-22T02:03:52Z | 2017-11-22T02:03:52Z | NONE | null | Edit #10506 breaks if the DataFrame contains unicode column names with non-ASCII characters.
```
import pandas as pd
df = pd.DataFrame({u'a': [1, 2, 3], u'ä': [4, 5, 6]})
df.filter(regex=u'a')
```
throws me a
```
---------------------------------------------------------------------------
UnicodeEncodeError ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13102 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13102/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13102/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13102/events | https://github.com/pandas-dev/pandas/issues/13102 | 153,398,493 | MDU6SXNzdWUxNTMzOTg0OTM= | 13,102 | BUG: plot(kind='kde') no longer works | {
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] | closed | false | null | [] | null | 4 | 2016-05-06T07:58:45Z | 2016-05-06T14:34:38Z | 2016-05-06T14:32:54Z | NONE | null | #### Code Sample, a copy-pastable example if possible
``` python
import pandas as pd
import numpy as np
df=pd.DataFrame({'a':np.random.normal(5,1,1000)})
df.a.plot(kind='kde')
```
#### Expected Output
In previous versions, a kde plot was shown. Now I get a "Kernel died unexpectedly" error.
#### output of `pd.show_ver... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13103 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13103/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13103/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13103/events | https://github.com/pandas-dev/pandas/issues/13103 | 153,470,582 | MDU6SXNzdWUxNTM0NzA1ODI= | 13,103 | .transform not respecting axis=1 in combine stage of group-apply-combine | {
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... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2016-05-06T15:00:40Z | 2016-05-06T15:07:33Z | 2016-05-06T15:07:09Z | CONTRIBUTOR | null | `.transform` does not appear to be respecting the axis argument of the groupby in the combine stage. The code below yields:
`ValueError: Length mismatch: Expected axis has 4 elements, new values have 5 elements`
```
#### Code Sample, a copy-pastable example if possible
import pandas as pd
df = pd.DataFrame(pd.np.aran... | {
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