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https://api.github.com/repos/pandas-dev/pandas/issues/13404 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13404/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13404/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13404/events | https://github.com/pandas-dev/pandas/issues/13404 | 159,258,163 | MDU6SXNzdWUxNTkyNTgxNjM= | 13,404 | Merging on columns results in loss of categorical dtypes (cast to "object") | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2016-06-08T20:03:40Z | 2017-02-06T00:10:54Z | 2016-06-08T20:32:54Z | NONE | null | #### Code Sample, a copy-pastable example if possible
```
import pandas as pd
import numpy as np
a = pd.DataFrame({'numbers': np.arange(10), 'categories': list('abcabcabcd')})
a['categories'] = a['categories'].astype('category')
b = pd.DataFrame({'numbers': np.arange(10)})
print a.dtypes
print a.categories.cat.catego... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13405 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13405/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13405/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13405/events | https://github.com/pandas-dev/pandas/pull/13405 | 159,292,401 | MDExOlB1bGxSZXF1ZXN0NzMxMzI1Njc= | 13,405 | ENH: implement 'reverse' for grouping | {
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for example a multiindex dataframe
```
df.mean(level=['year', 'month', 'day', 'hour', 'min', 'trial'])
```
can be replaced with
```
df.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13406 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13406/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13406/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13406/events | https://github.com/pandas-dev/pandas/pull/13406 | 159,299,518 | MDExOlB1bGxSZXF1ZXN0NzMxMzc1OTA= | 13,406 | ENH: parse categoricals in read_csv | {
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"followers_url": "https://api.github.com/users/jr... | 12 | 2016-06-08T23:31:14Z | 2016-08-06T22:54:20Z | 2016-08-06T22:53:22Z | CONTRIBUTOR | null | Closes #10153 (at least partly)
Adds the ability to directly parse a `Categorical` through the `dtype` parameter to `read_csv`. Currently just uses whatever is there as the categories, a possible enhancement would be to allow and enforce user-specified categories, through not quite sure what the api would be.
This o... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13407 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13407/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13407/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13407/events | https://github.com/pandas-dev/pandas/issues/13407 | 159,303,277 | MDU6SXNzdWUxNTkzMDMyNzc= | 13,407 | DataFrame.values not a 2D-array when constructed from timezone-aware datetimes | {
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#### Code Sample, a copy-pastable example if possible
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13408 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13408/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13408/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13408/events | https://github.com/pandas-dev/pandas/issues/13408 | 159,313,816 | MDU6SXNzdWUxNTkzMTM4MTY= | 13,408 | fillna() is incomplete after performing resample() | {
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Make data
```
>>> dates = pd.date_range('01-01-2015','01-07-2015', freq='B')
>>> df = pd.DataFrame({'a':[1,2,np.nan,4,5],'b':[6,7,8,9,np.nan]}, dates)
>>> print(df)
a b
2015-01-01 1.0 6.0
2015-01-02 2.0 7.0
2015-01-05 NaN 8.0
2015-01-06 4.0 9.0
2015-01-07 5.0 NaN
```
Then ... | {
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In this example, one level of a multiindex is dropped and data is copied based on ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13410 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13410/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13410/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13410/events | https://github.com/pandas-dev/pandas/issues/13410 | 159,399,596 | MDU6SXNzdWUxNTkzOTk1OTY= | 13,410 | ENH: Categorical.from_union | {
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... | 10 | 2016-06-09T12:49:14Z | 2021-05-01T22:10:01Z | null | CONTRIBUTOR | null | xref #13361
- [x] support union w `Series/CategoricalIndex` as well as `Categorical` #14199
- [x] add `ignore_order` to ignore the raising on an ordered Categorical (and just have it work) #15219
- [ ] do we want to put this in the `pd` namespace (or change its name). Consider `Categorical.from_union(...)`
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2) Fix bug in C engine in which a NULL `quotechar` would raise even though `quoting=csv.QUOTE_NONE`.
3) Fix bug in C engine in which `quoting=csv.QUOTE_NONNUMERIC` wouldn't cause non-quoted fields to be cast to `float`. Relevant definitions can be found in the Pyth... | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2016-06-09T14:18:36Z | 2017-03-13T13:16:45Z | 2016-12-06T11:35:03Z | CONTRIBUTOR | null | The function below has been incorrectly implemented. If the frame has an index with duplicated values, you will get a result with more than `n` rows and not properly sorted. So `nsmallest` and `nlargest` for DataFrame doesn't return a correct frame in this particular case.
```
def _nsorted(self, columns, n, method, ke... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13413 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13413/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13413/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13413/events | https://github.com/pandas-dev/pandas/pull/13413 | 159,473,774 | MDExOlB1bGxSZXF1ZXN0NzMyNjA3NTE= | 13,413 | DOC- typo fix and adding correct command for environment deactivation… | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-06-09T18:15:56Z | 2016-06-09T19:43:58Z | 2016-06-09T19:16:27Z | CONTRIBUTOR | null | - [ ] closes #xxxx
- [ ] tests added / passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
… for windows and linux
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https://api.github.com/repos/pandas-dev/pandas/issues/13414 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13414/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13414/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13414/events | https://github.com/pandas-dev/pandas/issues/13414 | 159,495,169 | MDU6SXNzdWUxNTk0OTUxNjk= | 13,414 | is there pandas.filter for values (not row or column labels)? | {
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``` python
ix=None
for ixi in [res[col].str.contains('string') for col in res.columns]:
if ix is not None:
ix = ix | ixi
else:
ix = ixi
res[ix]
```
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https://api.github.com/repos/pandas-dev/pandas/issues/13415 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13415/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13415/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13415/events | https://github.com/pandas-dev/pandas/issues/13415 | 159,519,350 | MDU6SXNzdWUxNTk1MTkzNTA= | 13,415 | DataFrame(recarray, columns=MultiIndex) disregards input data, gives empty DataFrame | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2016-06-09T22:06:00Z | 2016-06-10T09:48:37Z | 2016-06-10T09:48:32Z | CONTRIBUTOR | null | I previously posted this as a question (not knowing it was a bug) here: http://stackoverflow.com/questions/37732403/pandas-dataframe-from-multiindex-and-numpy-structured-array-recarray
First I create a two-level MultiIndex:
```
import numpy as np
import pandas as pd
ind = pd.MultiIndex.from_product([('X','Y'), ('a',... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13416 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13416/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13416/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13416/events | https://github.com/pandas-dev/pandas/issues/13416 | 159,520,528 | MDU6SXNzdWUxNTk1MjA1Mjg= | 13,416 | Inconsistencies in groupby aggregation with non-numeric types | {
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... | 5 | 2016-06-09T22:13:27Z | 2021-05-01T22:12:08Z | null | CONTRIBUTOR | null | xref #13992
Some of the issues and inconsistencies I noticed.
(Apologies for a bit lengthy input.)
##### Settings:
``` python
df = pd.DataFrame({"A": [2, 1, 2, 2],
"B": [3, 3, 4, 4],
"C1": pd.Categorical([5, 6, 6, 6], [5, 6, 7]),
"C2": pd.Categorical(list("aa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13417 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13417/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13417/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13417/events | https://github.com/pandas-dev/pandas/issues/13417 | 159,525,995 | MDU6SXNzdWUxNTk1MjU5OTU= | 13,417 | helper function - detect index columns in dataframe | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13418 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13418/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13418/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13418/events | https://github.com/pandas-dev/pandas/pull/13418 | 159,560,768 | MDExOlB1bGxSZXF1ZXN0NzMzMjMwNDg= | 13,418 | BUG: Fix csv.QUOTE_NONNUMERIC quoting in to_csv | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2016-06-10T05:22:02Z | 2016-06-16T12:32:47Z | 2016-06-16T12:32:24Z | MEMBER | null | Closes #12922: "bug" traced to #12194 via bisection, where the float formatting was unconditionally casting everything to string.
I say "bug" (with quotations) because the changes to `get_result_as_array` did **correctly** cast everything to string as per the documentation (i.e. it had inadvertently patched a bug itse... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13419 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13419/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13419/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13419/events | https://github.com/pandas-dev/pandas/pull/13419 | 159,564,967 | MDExOlB1bGxSZXF1ZXN0NzMzMjU1Mjk= | 13,419 | CLN: Remove the engine parameter in CSVFormatter and to_csv | {
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Internal code and #6581 indicate that this was long overdue.
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https://api.github.com/repos/pandas-dev/pandas/issues/13420 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13420/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13420/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13420/events | https://github.com/pandas-dev/pandas/issues/13420 | 159,603,874 | MDU6SXNzdWUxNTk2MDM4NzQ= | 13,420 | DataFrame.groupby(grp, axis=1) with categorical grp breaks | {
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"followers_url": "https://api.github.com/users/wesm... | 4 | 2016-06-10T10:17:09Z | 2019-08-07T13:57:33Z | 2019-08-07T13:57:33Z | NONE | null | While attempting to use `pd.qcut` (which returned a Categorical) to bin some data in groups for plotting, I encountered the following error. The idea is to group a DataFrame by columns (`axis=1`) using a Categorical.
#### Minimal breaking example
```
>>> import pandas
>>> df = pandas.DataFrame({'a':[1,2,3,4], 'b':[-1,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13421 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13421/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13421/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13421/events | https://github.com/pandas-dev/pandas/issues/13421 | 159,637,275 | MDU6SXNzdWUxNTk2MzcyNzU= | 13,421 | DataFrame from hierarchical NumPy recarray with hierarchical MultiIndex results in all NaN values | {
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"followers_url": "https://api.github.com/users/jorisva... | 17 | 2016-06-10T13:39:38Z | 2016-06-10T20:13:30Z | 2016-06-10T18:10:02Z | CONTRIBUTOR | null | I filed #13415 in which it was said that `DataFrame(recarray, columns=MultiIndex)` does reindexing and so only selects matching columns to be in the resultant frame. I can see how this might be a backward compatibility constraint. However, I have discovered a similar but different case which still seems broken:
```
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https://api.github.com/repos/pandas-dev/pandas/issues/13422 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13422/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13422/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13422/events | https://github.com/pandas-dev/pandas/issues/13422 | 159,651,118 | MDU6SXNzdWUxNTk2NTExMTg= | 13,422 | Ggplot theme does not work correctly | {
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```
seasonname Core-no season Fall/Winter Spring/Summer Summery Core True Summer
date_utc
2015-06-01 199.7825 111.1363 180.3559 166.6217 66.3297
2015-06-02 201.9999 111.9228 15... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13423 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13423/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13423/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13423/events | https://github.com/pandas-dev/pandas/issues/13423 | 159,704,443 | MDU6SXNzdWUxNTk3MDQ0NDM= | 13,423 | Setting NaN values on DataFrame with non-unique column names | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2016-06-10T19:22:40Z | 2016-06-11T12:14:21Z | 2016-06-11T12:14:01Z | NONE | null | #### Code Sample, a copy-pastable example if possible
Something goes wrong when I try to set a NaN value using the iloc syntax. Instead of just the entry being set, the entire row gets set.
``` python
import pandas as pd
import numpy as np
df = pd.DataFrame(np.arange(1,5).reshape(2,2), columns=["A"]*2)
# this works l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13424 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13424/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13424/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13424/events | https://github.com/pandas-dev/pandas/issues/13424 | 159,714,240 | MDU6SXNzdWUxNTk3MTQyNDA= | 13,424 | bug in pandas.read_fwf | {
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``` python
self.delimiter = b'\r\n' + bytes(delimiter, 'utf8') if delimiter else b'\n\r\t '
```
instead of
``` python
self.delimiter = '\r\n' + delimiter if delimiter else '\n\r\t '
```
otherwise an exception is going to be raised on line 2605 of the same module, as it expects `de... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13425 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13425/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13425/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13425/events | https://github.com/pandas-dev/pandas/pull/13425 | 159,743,599 | MDExOlB1bGxSZXF1ZXN0NzM0NTA4NTE= | 13,425 | ENH: add downcast to pd.to_numeric | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13426 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13426/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13426/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13426/events | https://github.com/pandas-dev/pandas/pull/13426 | 159,766,218 | MDExOlB1bGxSZXF1ZXN0NzM0NjQzNTU= | 13,426 | BUG: categorical unpickle to use _coerce_indexer_dtype | {
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- [x] whatsnew entry
follow up for #13080 to use `_coerce_indexer_dtype`.
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https://api.github.com/repos/pandas-dev/pandas/issues/13427 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13427/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13427/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13427/events | https://github.com/pandas-dev/pandas/issues/13427 | 159,788,897 | MDU6SXNzdWUxNTk3ODg4OTc= | 13,427 | BUG: duplicate indexing on non-integer index with positional indexers failing in py3 | {
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> > > df = pd.DataFrame({"a" : [0,1,2], "b" : [1,2,3]})
> > > df[["a", "a"]].apply(lambda x: x[0] + x[1], axis = 1)
> > > #### Expected Output
> > >
> > > 0 0
> > > 1 2
> > > 2 4
> > > dtype: int64
> > > #### output of `pd.show_versions()`
> > >
> > > Tr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13428 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13428/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13428/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13428/events | https://github.com/pandas-dev/pandas/pull/13428 | 159,806,832 | MDExOlB1bGxSZXF1ZXN0NzM0ODU3OTk= | 13,428 | BUG: in _nsorted for frame with duplicated values index | {
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] | closed | false | null | [] | null | 10 | 2016-06-12T04:11:50Z | 2016-10-28T15:59:24Z | 2016-10-28T15:59:24Z | CONTRIBUTOR | null | - [x] closes #13412
- [ ] 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/13429 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13429/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13429/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13429/events | https://github.com/pandas-dev/pandas/issues/13429 | 159,823,238 | MDU6SXNzdWUxNTk4MjMyMzg= | 13,429 | BUG/API: PeriodIndex doesn't support loc using partial string | {
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... | 7 | 2016-06-12T11:42:51Z | 2021-05-15T03:56:33Z | 2021-05-15T03:56:33Z | MEMBER | null | #### Code Sample, a copy-pastable example if possible
`DataFrame.loc` supports partial string selection when it has `DatetimeIndex`. But it can't work if index is `PeriodIndex`.
```
ddf = pd.DataFrame(np.random.randn(10, 3),
index=pd.date_range('2011-01-01', freq='H', periods=10))
ddf.loc['2011-01-... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13430 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13430/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13430/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13430/events | https://github.com/pandas-dev/pandas/pull/13430 | 159,824,473 | MDExOlB1bGxSZXF1ZXN0NzM0OTUwNjg= | 13,430 | ENH: PeriodIndex now accepts pd.NaT | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-06-12T12:18:24Z | 2016-06-14T21:26:17Z | 2016-06-14T21:26:02Z | MEMBER | null | - [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Related to #12759. `PeirodIndex` can be created from list/array which contains `pd.NaT`.
currently it raises:
```
pd.PeriodIndex([pd.NaT])
# ValueError: freq not specified and cannot be inferred from first element... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13431 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13431/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13431/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13431/events | https://github.com/pandas-dev/pandas/issues/13431 | 159,829,532 | MDU6SXNzdWUxNTk4Mjk1MzI= | 13,431 | BUG: different behaviors of sort_index() and sort_index(level=0) | {
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"followers_url": "https://api.github.com/users/jr... | 12 | 2016-06-12T14:13:48Z | 2017-04-07T15:18:25Z | 2017-04-07T15:18:25Z | CONTRIBUTOR | null | Inspired by some bug reports around multiindex sortedness (http://stackoverflow.com/questions/31427466/ensuring-lexicographical-sort-in-pandas-multiindex, #10651, #9212), I found that `sort_index()` sometimes can't make a multiindex ready for slicing, but `sort_index(level=0)` (so does `sortlevel()`) can.
``` python
I... | {
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"followers_url": "https://api.github.com/users/j... | 17 | 2016-06-13T00:09:39Z | 2021-05-17T15:17:29Z | 2021-05-17T15:17:29Z | CONTRIBUTOR | null | Issues:
- [x] `Index.difference` and `symmetric_difference` raise for mixed types (solved by #13514)
- [x] `Index._get_consensus_name` incorrectly returns an empty index (solved by #13514)
- [ ] bug in `Index.union` for non-unique indexes (see [comment](#issuecomment-226665776))
- [ ] bug in `Index.intersection` for n... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13433 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13433/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13433/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13433/events | https://github.com/pandas-dev/pandas/issues/13433 | 159,934,133 | MDU6SXNzdWUxNTk5MzQxMzM= | 13,433 | Assignment of multiple columns (hierarchical index) changes dtypes | {
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"f... | 7 | 2016-06-13T12:02:06Z | 2021-05-01T22:17:05Z | null | NONE | null | #### Code Sample, a copy-pastable example if possible
[data.zip](https://github.com/pydata/pandas/files/311709/data.zip)
With the attached data (0.18.1 msgpack format), read the contained data frame and inspect the dtypes:
```
df = pd.read_msgpack('path/to/test.msg')
print df.dtypes
phases end date... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13434 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13434/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13434/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13434/events | https://github.com/pandas-dev/pandas/issues/13434 | 159,949,163 | MDU6SXNzdWUxNTk5NDkxNjM= | 13,434 | read_html() doesn't handle tables with multiple header rows | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-06-13T13:24:04Z | 2017-03-29T23:28:23Z | 2017-03-29T23:28:23Z | NONE | null | The `read_html()` function seems to treat every `<th>` in a table as a column, even if they occur in separate `<tr>`s. This means that it breaks even on simple tables generated by pandas' `to_html()` function.
#### Code Sample, a copy-pastable example if possible
```
df = pd.DataFrame(
columns=["Name", "Age", "Par... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13435 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13435/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13435/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13435/events | https://github.com/pandas-dev/pandas/pull/13435 | 160,066,853 | MDExOlB1bGxSZXF1ZXN0NzM2NTkyNjc= | 13,435 | BUG: df.pivot_table: margins_name ignored when aggfunc is a list | {
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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/13436 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13436/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13436/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13436/events | https://github.com/pandas-dev/pandas/pull/13436 | 160,090,373 | MDExOlB1bGxSZXF1ZXN0NzM2NzU0OTM= | 13,436 | PERF: float hash slow in py3 | {
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Using exactly the approach suggested by @ruoyu0088
significant changes in asv below
```
before after ratio
- 8.88s 78.12ms 0.01 indexing.float_loc.time_float_loc
- 13.11s 78.12ms 0.01 groupby.groupby_float32.time_groupby_sum
```
Factor of 10 small... | {
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file "setup,py" , line 33 , in <module>
ver =Cython. **version**
atrribute error: 'module' object has no attribute ' **version** '
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```
In [2]: s = pd.Series(['a', 'b', None])
In [3]: s
Out[3]:
0 a
1 b
2 None
dtype: object
In [4]: s.str.replace('a', None)
Out[4]:
0 NaN
1 NaN
2 NaN
dtype: float64
```
cc @kwsmith
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https://api.github.com/repos/pandas-dev/pandas/issues/13439 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13439/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13439/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13439/events | https://github.com/pandas-dev/pandas/issues/13439 | 160,180,982 | MDU6SXNzdWUxNjAxODA5ODI= | 13,439 | Feature request: read_excel to support hyperlinks split into label and hyperlink | {
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.xlsx file having a column with label and hyperlinks (see screenshot collage)
In Excel, label: Python (that has a hyperlink to i.e.: www.python.org)
#### Code Sample, a copy-pastable example if possible
data = pd.read_excel('Book1.xlsx')
column has just "Python" as content. Hyperlink information is lost.
(s... | {
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"color": "e1... | closed | false | null | [] | null | 14 | 2016-06-14T14:45:52Z | 2016-07-09T14:23:15Z | 2016-07-09T12:55:28Z | MEMBER | null | - [x] closes #13365
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
@jreback take this just as a wild guess of how to fix #13365 . If the approach makes sense, I will add tests, whatsnew and some more docs.
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https://api.github.com/repos/pandas-dev/pandas/issues/13441 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13441/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13441/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13441/events | https://github.com/pandas-dev/pandas/pull/13441 | 160,219,903 | MDExOlB1bGxSZXF1ZXN0NzM3Njc3NDQ= | 13,441 | BUG: Rolling negative window issue fix #13383 | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-06-14T16:02:36Z | 2016-06-21T10:09:36Z | 2016-06-21T10:09:29Z | CONTRIBUTOR | null | - [x] closes #13383
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Added functionality in validate function of Rolling to ensure that window size is non-negative.
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] | closed | false | null | [] | null | 4 | 2016-06-14T16:13:17Z | 2019-04-10T00:44:30Z | 2019-04-10T00:44:30Z | CONTRIBUTOR | null | Based on a sqlite database [my_database.zip](https://github.com/pydata/pandas/files/314395/my_database.zip) created from the file [source.zip](https://github.com/pydata/pandas/files/314358/source.zip) in a table `my_table`. I get different results when parsing the dates in the method `read_sql_query` between version 0.... | {
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I semi-frequently get the `.levels` and `.labels` of a `MultiIndex` backwards. Maybe it's just me, but I think `labels` is the culprit, because in other pandas contexts, "labels" refer to the actual value of the thing. E.g.
- `.loc` indexes by "label... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-06-14T21:40:00Z | 2016-06-17T00:37:55Z | 2016-06-17T00:37:39Z | CONTRIBUTOR | null | https://github.com/pydata/pandas/commit/8f3229227856af4feedb5894da9ccd4168a4e2a0
https://github.com/pydata/pandas/commit/eefe71e27131bc4848e549e3688ef6700b57b73a (partial revert)
fixing to 4.0.8
seems 4.1 breaks things.
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https://api.github.com/repos/pandas-dev/pandas/issues/13445 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13445/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13445/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13445/events | https://github.com/pandas-dev/pandas/issues/13445 | 160,357,053 | MDU6SXNzdWUxNjAzNTcwNTM= | 13,445 | Pandas series.rank(ascending=False) get rise to SIGSEGV error | {
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"description": "Non-arithmetic algos: va... | closed | false | null | [] | {
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Maybe it's a numpy or table bug..
#### Code Sample, a copy-pastable example if possible
import pandas as pd
def test_df_ranks(f):
df = pd.read_hdf(f, key="t")
print (df.shape)
print (type(df))
print (df)
s=df.non_current_asse... | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2016-06-15T09:05:42Z | 2016-06-16T08:09:38Z | 2016-06-15T11:56:45Z | CONTRIBUTOR | null | Using `sum()` on a Series of Decimal datatypes returns a Decimal. However, using `sum()` on a DataFrame of Decimal datatypes returns floats.
I think it would be more consistent for the DataFrame `sum()` to return Decimals.
#### Code Sample
``` python
import pandas as pd
from decimal import Decimal
df = pd.DataFrame... | {
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"color": "005... | closed | false | null | [] | null | 3 | 2016-06-15T10:24:04Z | 2016-06-15T15:34:34Z | 2016-06-15T11:26:06Z | CONTRIBUTOR | null | Trying to print anything containing a V\* (void) type throws in `isnull`:
``` python
>>> import numpy as np
>>> import pandas as pd
>>> arr = np.array([b'foo'], dtype='V')
>>> arr
array([[102 111 111]],
dtype='|V3')
>>> s = pd.Series(arr)
>>> s[0]
[102 111 111]
>>> s
TypeError: ufunc 'isnan' not supported for th... | {
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so this is failing on windows py2.7 (3.5 works fine).
```
pandas\algos.c(113380) : warning C4244: '=' : conversion from 'int' to '__pyx_t_5numpy_float32_t', possible loss of data
pandas\algos.c(114441) : warning C4244: '=' : conversion from '__pyx_t_5numpy_int64_t' to '__pyx_t_5numpy_float64_t', possible... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13449 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13449/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13449/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13449/events | https://github.com/pandas-dev/pandas/pull/13449 | 160,419,048 | MDExOlB1bGxSZXF1ZXN0NzM5MDkwNDY= | 13,449 | DOC: Corrected Series.str.extract documentation error | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-06-15T13:15:00Z | 2016-06-15T13:25:16Z | 2016-06-15T13:25:13Z | CONTRIBUTOR | null | Really small documentation fix, that rather confused me as I was first reading it (given the documentation contradicts itself). I believe this is the correct resolution.
Let me know if I need to actually compile/test anything.
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https://api.github.com/repos/pandas-dev/pandas/issues/13450 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13450/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13450/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13450/events | https://github.com/pandas-dev/pandas/pull/13450 | 160,429,036 | MDExOlB1bGxSZXF1ZXN0NzM5MTYyOTE= | 13,450 | ERR: fix error message for to_datetime | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-06-15T13:58:27Z | 2016-06-16T12:18:44Z | 2016-06-16T12:18:43Z | CONTRIBUTOR | null | - [x] ~~closes #xxxx~~ There is no issue for this.
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Fixes the error message when the argument to `to_datetime` doesn't match the format specified.
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https://api.github.com/repos/pandas-dev/pandas/issues/13451 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13451/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13451/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13451/events | https://github.com/pandas-dev/pandas/issues/13451 | 160,438,398 | MDU6SXNzdWUxNjA0MzgzOTg= | 13,451 | to_datetime can't handle int16 or int8 | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-06-15T14:36:41Z | 2016-06-17T22:04:34Z | 2016-06-17T22:04:34Z | CONTRIBUTOR | null | #### Code sample
```
df = pd.DataFrame({'year': [2015, 2016],
'month': [2, 3],
'day': [4, 5]})
pd.to_datetime(df.astype('int16'))
```
#### Expected Output
```
0 2015-02-04
1 2016-03-05
dtype: datetime64[ns]
```
#### output of `pd.show_versions()`
``````
INSTALLED VER... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13452 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13452/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13452/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13452/events | https://github.com/pandas-dev/pandas/issues/13452 | 160,458,616 | MDU6SXNzdWUxNjA0NTg2MTY= | 13,452 | index disappears on groupby.rank() | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2016-06-15T15:55:35Z | 2016-06-16T07:51:48Z | 2016-06-16T07:51:44Z | NONE | null | df = pd.DataFrame({'A' : [1, 1, 3, 4], 'B': [7, 7, 7, 8], 'C': [5, 6, 7, 8], 'D': [5, 6, 7, 8]})
print(df)
print("")
print(df.groupby(["A", "B"]).rank())
print("")
print(df.groupby(["A", "B"]).sum())
print("")
print(df.groupby(["A", "B"]).count())
print("")
#### Expected Output
Would expect all three functions to show... | {
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Pandas `Resampler.nunique` appears to be putting the same data in multiple bins:
``` python
import pandas as pd
# Create a series with a datetime index
index = pd.date_range('1-1-2000', '2-15-2000', freq='h')
index2 = pd.date_range('4-15-2000', '5-15-2000', freq='h')
index3 = index.appe... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13454 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13454/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13454/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13454/events | https://github.com/pandas-dev/pandas/issues/13454 | 160,518,194 | MDU6SXNzdWUxNjA1MTgxOTQ= | 13,454 | Exception when calling read_gbq : No module named discovery | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-06-15T20:38:26Z | 2016-07-07T07:26:12Z | 2016-07-07T07:26:12Z | CONTRIBUTOR | null | I ran into the following exception when using the pandas `read_gbq()` function.
```
1 import pandas as pd
----> 2 pd.read_gbq('select * from SampleDataset.SampleTable', project_id='xxxxxxx')
/usr/local/lib/python2.7/dist-packages/pandas/io/gbq.pyc in read_gbq(query, project_id, index_col, col_order, reauth, ver... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13455 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13455/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13455/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13455/events | https://github.com/pandas-dev/pandas/issues/13455 | 160,525,643 | MDU6SXNzdWUxNjA1MjU2NDM= | 13,455 | Feature Request: groupby retaining indexes | {
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I imagine it as a simple parameter for the `groupby` function.
The feature is: the ability to group a level (of a MultiIndex data... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13456 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13456/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13456/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13456/events | https://github.com/pandas-dev/pandas/pull/13456 | 160,540,232 | MDExOlB1bGxSZXF1ZXN0NzM5OTYyOTg= | 13,456 | BLD: use inline macro | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-06-15T22:39:24Z | 2016-06-16T12:13:47Z | 2016-06-16T12:13:47Z | CONTRIBUTOR | null | closes #13448
This built locally (on Windows) for py27 and py35.
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... | 1 | 2016-06-15T23:21:50Z | 2019-10-21T20:03:53Z | null | CONTRIBUTOR | null | from [SO](http://stackoverflow.com/questions/37845884/pandas-setting-column-subset-slow)
I'm guessing there's a lot of inference / checks along this path, but this is slower than I'd expect.
``` python
In [66]: df = pd.DataFrame(np.random.randint(0,1000, size=(10000, 1026)))
...: f = list(range(1024))
...:
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"followers_url": "https://api.github.com/users/jr... | 9 | 2016-06-16T02:16:25Z | 2016-07-07T07:26:19Z | 2016-07-07T07:26:12Z | CONTRIBUTOR | null | - [ x ] closes #13454
- [ x ] tests added / passed
- [ x ] passes `git diff upstream/master | flake8 --diff`
- [ x ] whatsnew entry
All gbq tests pass locally
```
tony@tonypc:~/parthea-pandas/pandas/io/tests$ nosetests test_gbq.py -v
test_read_gbq_with_corrupted_private_key_json_should_fail (pandas.io.tests.test_gbq.... | {
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```
nosetests pandas/tseries/tests/test_timezones.py:TestTimeZones.test_normalize_tz
F
======================================================================
FAIL: test_normalize_tz (pandas.tseries.tests.test_timezones.TestTimeZones)
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-06-16T09:26:20Z | 2016-06-16T21:02:28Z | 2016-06-16T21:02:21Z | CONTRIBUTOR | null | - [x] closes #13438
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- [x] passes `git diff upstream/master | flake8 --diff`
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.str.replace now raises TypeError when replacement is invalid
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Is there a reason why more parsing/all parsing options aren't exposed to `TextParser` at https://github.com/pydata/pandas/blob/master... | {
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- [x] closes #11879
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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#### ISSUE
```
import pandas as pd
pd.DataFrame({'C': pd.period_range('2015-01-01', periods=3)}).to_msgpack()
---------------------------------------------------------------------------
TypeError Traceback (most recent... | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
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Fixes #13451
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... | 3 | 2016-06-16T18:24:04Z | 2020-05-11T00:54:29Z | null | NONE | null | This was an issue that was fixed in 0.14.0, but has re-appeared in 0.18.1. The series s should have a mulit-level index, but in 18.1 it has a single-level index with a tuple for each value in the index.
#### Code Sample, a copy-pastable example if possible
```
import pandas as pd
from numpy.random import randn
a = [[... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13466 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13466/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13466/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13466/events | https://github.com/pandas-dev/pandas/issues/13466 | 160,744,909 | MDU6SXNzdWUxNjA3NDQ5MDk= | 13,466 | BUG, dot product with empty dataframe | {
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I thought the expected ones would be empty or NaN?
In [3]: df = pd.DataFrame(index = ['a','b'])
In [4]: srs = pd.Series()
In [5]: df
Out[5]:
Empty DataFrame
Columns: []
Index: [a, b]
In [6]: srs
Out[6]: Series([], dtype: float64)
In [7]: df.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13467 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13467/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13467/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13467/events | https://github.com/pandas-dev/pandas/issues/13467 | 160,764,474 | MDU6SXNzdWUxNjA3NjQ0NzQ= | 13,467 | API: NaT/nan mixed input coerces to timedelta64 | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2016-06-16T21:24:07Z | 2016-07-11T07:31:10Z | 2016-07-11T07:31:10Z | MEMBER | null | #### Code Sample, a copy-pastable example if possible
`Index`/`Series` results in `datetime64` dtype if all inputs are `pd.NaT`.
```
pd.Index([pd.NaT, pd.NaT])
# DatetimeIndex(['NaT', 'NaT'], dtype='datetime64[ns]', freq=None)
pd.Series([pd.NaT, pd.NaT])
#0 NaT
#1 NaT
# dtype: datetime64[ns]
```
However, it coe... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13468 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13468/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13468/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13468/events | https://github.com/pandas-dev/pandas/issues/13468 | 160,777,950 | MDU6SXNzdWUxNjA3Nzc5NTA= | 13,468 | iterrows: when upcasting to object, values are converted to python types | {
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... | 10 | 2016-06-16T22:46:45Z | 2021-05-01T22:22:40Z | null | MEMBER | null | I know `iterrows` is not the most recommended function, but I noticed a strange behaviour (triggered by a problem of a geopandas user: https://github.com/geopandas/geopandas/issues/348). When using `iterrows` on a df with mixed dtypes (so the resulting series is of object dtype), the numeric values are converted to pyt... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13469 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13469/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13469/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13469/events | https://github.com/pandas-dev/pandas/issues/13469 | 160,788,264 | MDU6SXNzdWUxNjA3ODgyNjQ= | 13,469 | Followup to #13358 asof-join | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-06-17T00:12:31Z | 2016-06-17T13:19:04Z | 2016-06-17T13:03:59Z | CONTRIBUTOR | null | xref #13358
- [ ] need full signature on deprecated `ordered_merge`
- [ ] `pd.merge_asof()` for asof-style time-series joining, see :ref:`here <whatsnew_0182.enhancements.asof_merge>` for highlites
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https://api.github.com/repos/pandas-dev/pandas/issues/13470 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13470/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13470/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13470/events | https://github.com/pandas-dev/pandas/issues/13470 | 160,792,174 | MDU6SXNzdWUxNjA3OTIxNzQ= | 13,470 | feature request : lead/lag values based on timedeltas | {
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It's me again ;-)
Consider the following:
```
rng = pd.date_range('1/1/2011', periods=5, freq='T')
ts = pd.DataFrame({'A' : np.random.randn(len(rng))}, index=rng)
ts.drop(ts.index[[2,3]],inplace=True)
# note how I delete some rows so that the index contains holes
ts
Out[37]:
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https://api.github.com/repos/pandas-dev/pandas/issues/13471 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13471/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13471/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13471/events | https://github.com/pandas-dev/pandas/issues/13471 | 160,793,011 | MDU6SXNzdWUxNjA3OTMwMTE= | 13,471 | Is it possible for `rolling()` to set labels at any position within the window? | {
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"de... | closed | false | null | [] | null | 4 | 2016-06-17T01:04:36Z | 2021-06-23T15:41:07Z | 2016-06-17T01:08:33Z | NONE | null | By default `rolling()` sets labels (resulting values) at the "right edge" of the window. The right edge is where the window has the greatest index (biggest number, most recent date, etc.). `rolling()` does have an argument to center labels, but there doesn't seem to be a way to set the label at the left edge or anywh... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13472 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13472/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13472/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13472/events | https://github.com/pandas-dev/pandas/issues/13472 | 160,793,652 | MDU6SXNzdWUxNjA3OTM2NTI= | 13,472 | BLD: fix appveyor to work with latest conda/conda-build | {
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Current are
- `conda==4.1.1` is good
- `conda-build==1.21.0` seems buggy
a working version is:
- `conda=4.0.8`
- `conda-build=1.20.3`
may need to fix the version if conda-build not fixed soon
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https://api.github.com/repos/pandas-dev/pandas/issues/13473 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13473/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13473/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13473/events | https://github.com/pandas-dev/pandas/issues/13473 | 160,936,687 | MDU6SXNzdWUxNjA5MzY2ODc= | 13,473 | ENH: add errors='raise' option to rename | {
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... | 10 | 2016-06-17T17:26:19Z | 2020-06-17T01:29:17Z | 2019-03-05T22:15:20Z | CONTRIBUTOR | null | Is there a reason that `.rename` doesn't raise if keys are supplied that don't exist? This caught me out a couple of times:
``` python
In [14]: import pandas as pd
In [15]: df=pd.DataFrame({'a': [1,2], 'b': [3,4]})
In [16]: df
Out[16]:
a b
0 1 3
1 2 4
In [17]: df.rename(columns={'a': 'c'})
Out[17]:
c ... | {
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... | 2 | 2016-06-17T17:53:54Z | 2021-05-01T22:23:42Z | null | MEMBER | null | #### Code Sample, a copy-pastable example if possible
```
In [2]: df = pd.DataFrame(0, index=range(2), columns=pd.MultiIndex.from_product([[1], [2]]))
In [3]: df['oth'] = 1
In [4]: df.loc[0, 'oth']
Out[4]:
1
Name: 0, dtype: int64
In [5]: df.loc[0, 'oth'] += 1
In [6]: df.loc[0, 'oth']
Out[6]:
NaN
Name: 0, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13475 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13475/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13475/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13475/events | https://github.com/pandas-dev/pandas/issues/13475 | 160,946,165 | MDU6SXNzdWUxNjA5NDYxNjU= | 13,475 | BUG: index.name not preserved in concat in case of unequal object index | {
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```
In [23]: df1 = pd.DataFrame({'a':[1,2]}, index=pd.Index(['a', 'b'], name='idx'))
In [24]: df2 = pd.DataFrame({'b':[2,3]}, index=pd.Index(['b', 'c'], name='idx'))
In [26]: pd.concat([df1, df2], axis=1)
Out[26]:
a b
a 1.0 NaN
b 2.0 2.0
c NaN 3.0
In [27]: print pd.concat([... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13476 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13476/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13476/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13476/events | https://github.com/pandas-dev/pandas/issues/13476 | 160,959,742 | MDU6SXNzdWUxNjA5NTk3NDI= | 13,476 | DataFrame.describe() no longer excludes NaN. | {
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In 0.18.1, a single NaN in a column will cause the reported percentiles to all be NaN. In 0.18.0 and according to the documentation, NaNs are excluded.
```
import pandas as pd
import numpy as np
df = pd.DataFrame(data={'blah': range(10) + [np.nan]})
df.describe(pe... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13477 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13477/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13477/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13477/events | https://github.com/pandas-dev/pandas/pull/13477 | 161,005,760 | MDExOlB1bGxSZXF1ZXN0NzQzMjcxMTI= | 13,477 | BUG: Series/Index results in datetime/timedelta incorrectly if inputs are all nan/nat like | {
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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/13478 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13478/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13478/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13478/events | https://github.com/pandas-dev/pandas/issues/13478 | 161,009,349 | MDU6SXNzdWUxNjEwMDkzNDk= | 13,478 | Pythonic chained comparisons | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2016-06-18T06:11:42Z | 2016-06-19T12:46:58Z | 2016-06-18T10:51:52Z | NONE | null | #### Code Sample, a copy-pastable example if possible
dtw[(x <= dtw.id < y)]
#### Expected Output
same as dtw[(x <= dtw.id) & (dtw.id < y)] or dtw.query('{}<=id<{}'.format(x, y)), but these solutions are less Pythonic
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https://api.github.com/repos/pandas-dev/pandas/issues/13479 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13479/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13479/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13479/events | https://github.com/pandas-dev/pandas/issues/13479 | 161,014,797 | MDU6SXNzdWUxNjEwMTQ3OTc= | 13,479 | Enhancement request for .get_values() | {
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"color": "005... | closed | false | null | [] | null | 1 | 2016-06-18T08:56:17Z | 2016-06-18T14:46:08Z | 2016-06-18T14:45:59Z | CONTRIBUTOR | null | #### Code Sample, a copy-pastable example if possible
Hello,
At the moment I have to call two methods, if I want to extract a numpy array from a
DataFrame with a specific type.
Let's assume for this example that `example_frame` contains only integers.
If I want to force `int64` numbers, I have to write:
```
exampl... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13480 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13480/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13480/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13480/events | https://github.com/pandas-dev/pandas/issues/13480 | 161,016,520 | MDU6SXNzdWUxNjEwMTY1MjA= | 13,480 | Change MultiIndex repr ? | {
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The current MultiIndex representation looks like this:
```
In [15]: mi = pd.MultiIndex.from_tuples([('A', 1), ('A', 2),
...: ('B', 3), ('B', 4)])
In [16]: mi
Out[16]:
MultiIndex(levels=[[u'A', u'B'], [1, 2, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13481 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13481/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13481/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13481/events | https://github.com/pandas-dev/pandas/pull/13481 | 161,031,300 | MDExOlB1bGxSZXF1ZXN0NzQzNDA4MDc= | 13,481 | BUG: windows with TemporaryFile an read_csv #13398 | {
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"followers_url": "https://api.github.com/users/jr... | 22 | 2016-06-18T16:09:28Z | 2016-06-22T10:21:40Z | 2016-06-22T10:21:28Z | CONTRIBUTOR | null | - [ x] closes #13398
- [ x] no tests added -> could not find location for IO tests?
- [ x] passes `git diff upstream/master | flake8 --diff`
Change the way of reading back to readline (consistent with the test before entering the function)
One failure on Windows 10 (Python 3.5), but expected to fail actually (should... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13482 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13482/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13482/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13482/events | https://github.com/pandas-dev/pandas/issues/13482 | 161,035,870 | MDU6SXNzdWUxNjEwMzU4NzA= | 13,482 | Incorrect use of super() in pandas core module | {
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In the pandas core module `base.py`, the `__sizeof__` member of the `PandasObject` class uses the following line:
```
return super(self, PandasObject).__sizeof__()
```
#### Expected Code
This is an incorrect use of `super`, which is supposed to have the type argument before the object argument ([r... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13483 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13483/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13483/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13483/events | https://github.com/pandas-dev/pandas/issues/13483 | 161,037,615 | MDU6SXNzdWUxNjEwMzc2MTU= | 13,483 | Dataframe pivot_table() returning a multi-index for a single value, empty dataframe | {
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```
In [1]: import pandas as pd
In [2]: df = pd.DataFrame({'a': ['a1', 'a2', 'a3'], 'b': [1,2,3], 'c':['c1', 'c2', 'c3']})
In [3]: x = df[df['c'] == 'c1']
In [4]: y = x.pivot_table(index='a', columns='c', values='b')
In [5]: y.columns
Out[5]: Index([u'c1'], dty... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13484 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13484/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13484/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13484/events | https://github.com/pandas-dev/pandas/pull/13484 | 161,053,962 | MDExOlB1bGxSZXF1ZXN0NzQzNTMyODE= | 13,484 | BUG: is_normalized returned False for local tz | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2016-06-19T03:02:19Z | 2016-06-21T12:43:08Z | 2016-06-21T12:43:02Z | CONTRIBUTOR | null | - [x] closes #13459
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
is_normalized returned False for normalized date_range
in case of local timezone 'Asia/Kolkata'
Fixes: #13459
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https://api.github.com/repos/pandas-dev/pandas/issues/13485 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13485/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13485/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13485/events | https://github.com/pandas-dev/pandas/pull/13485 | 161,058,067 | MDExOlB1bGxSZXF1ZXN0NzQzNTU1OTI= | 13,485 | ENH:read_html() handles tables with multiple header rows #13434 | {
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- [ ] read_html() handles tables with multiple header rows
Now it produces the following output for the issue
Unnamed: 0 Age Party
0 Hillary 68 D
1 Bernie 74 D
2 Donald 69 R
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https://api.github.com/repos/pandas-dev/pandas/issues/13486 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13486/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13486/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13486/events | https://github.com/pandas-dev/pandas/issues/13486 | 161,060,422 | MDU6SXNzdWUxNjEwNjA0MjI= | 13,486 | ENH: bad directive in to_datetime format - this uses std. strptime zone offset | {
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"followers_url": "https://api.github... | 4 | 2016-06-19T07:16:05Z | 2018-05-29T00:28:41Z | 2018-05-29T00:28:41Z | NONE | null | this is really bad for me since almost all linux logfiles contain zone offset.
As far as I can see there is not workaround without parsing the timestamp twice.
#### Code Sample, a copy-pastable example if possible
_parse common Apache access log timestamp_
```
pd.to_datetime(['28/Jul/2006:10:22:04 -0300'], format='%... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13487 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13487/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13487/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13487/events | https://github.com/pandas-dev/pandas/pull/13487 | 161,072,789 | MDExOlB1bGxSZXF1ZXN0NzQzNjMzMjE= | 13,487 | DOC: add nbformat for notebook conversion | {
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] | closed | false | null | [] | null | 3 | 2016-06-19T13:23:43Z | 2017-04-05T02:06:51Z | 2016-06-19T14:31:41Z | CONTRIBUTOR | null | The build [here](https://travis-ci.org/pydata/pandas/jobs/138633677#L1866) didn't succeed. Had `nbconvert` in the debs, but not `nbformat`.
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https://api.github.com/repos/pandas-dev/pandas/issues/13488 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13488/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13488/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13488/events | https://github.com/pandas-dev/pandas/issues/13488 | 161,083,895 | MDU6SXNzdWUxNjEwODM4OTU= | 13,488 | ENH: df.add fill_value NotImplementedError | {
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... | 3 | 2016-06-19T17:52:18Z | 2021-05-01T22:26:22Z | null | NONE | null | It appears that `fill_value` option for the `df.add()` method is not actually implemented in the source code. This was brought up in a[ StackOverflow question](http://stackoverflow.com/questions/37887796/pandas-dataframe-add-fill-value-notimplementederror).
[piRSquared](http://stackoverflow.com/users/2336654/pirsquare... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13489 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13489/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13489/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13489/events | https://github.com/pandas-dev/pandas/issues/13489 | 161,099,231 | MDU6SXNzdWUxNjEwOTkyMzE= | 13,489 | 'sharex' keyword doesn't work for df.plot(kind='hist') | {
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... | open | false | null | [] | null | 5 | 2016-06-20T00:10:52Z | 2021-05-01T22:27:27Z | null | NONE | null | #### Code Sample:
Dataframe:
```
gre gpa prestige
0 380.0 3.61 3.0
1 660.0 3.67 3.0
2 800.0 4.00 1.0
3 640.0 3.19 4.0
4 0520.0 2.93 4.0
```
`df.plot.hist(figsize=(20, 10), layout=(2,3), subplots=True, sharex=False, bins=10);`
Result:
, datetime.date(2000, 1, 2)]), name='cols')
idx1 = pd.Index(pd.to_datetime([datetime.date(2010, 1, 1), datetime.date(2010, 1, 2)]), name='rows')
s = pd.DataFrame(np.arange(4).reshape(2,2), columns=idx, index=idx1)
print type(s.index.name)
# T... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13495 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13495/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13495/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13495/events | https://github.com/pandas-dev/pandas/issues/13495 | 161,428,709 | MDU6SXNzdWUxNjE0Mjg3MDk= | 13,495 | ValueError on eval after 'from pandas import *' | {
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] | closed | false | null | [] | null | 1 | 2016-06-21T12:52:03Z | 2016-06-21T12:56:30Z | 2016-06-21T12:56:30Z | NONE | null | #### Test code
[20160621 eval problem.txt](https://github.com/pydata/pandas/files/325599/20160621.eval.problem.txt)
#### Expected Output
Raises Value Error when using 'from pandas import *'. Executes as expected using 'import pandas'.
Issue was raised originally at bugs.Python.org - Issue: 27361 but from there point... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13496 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13496/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13496/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13496/events | https://github.com/pandas-dev/pandas/pull/13496 | 161,609,737 | MDExOlB1bGxSZXF1ZXN0NzQ3MzQ1NzM= | 13,496 | TST: Clean up tests of DataFrame.sort_{index,values} | {
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This commit fixes:
- Some expected results were obtained by running code identical to what's being tested. (i.e. test could never fail)
- Removed duplicate assertions testing the same functionality both in `test_sort_... | {
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... | closed | false | null | [] | null | 6 | 2016-06-22T20:42:58Z | 2016-06-23T08:17:44Z | 2016-06-22T23:49:39Z | CONTRIBUTOR | null | Consider the following script:
import pandas as PD
df = PD.read_csv('sample.csv',
encoding='utf8')
print(df.columns[:5])
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https://api.github.com/repos/pandas-dev/pandas/issues/13498 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13498/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13498/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13498/events | https://github.com/pandas-dev/pandas/issues/13498 | 161,903,654 | MDU6SXNzdWUxNjE5MDM2NTQ= | 13,498 | Adding 'String search filter' functionality | {
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] | closed | false | null | [] | null | 4 | 2016-06-23T11:49:47Z | 2016-06-23T21:09:03Z | 2016-06-23T21:09:03Z | NONE | null | Hey everyone,
I was working on a project that involves working with data acquired via the world bank pandas api (i.e. `pandas.io.wb`). This library has a function called `pandas.io.wb.search(str)` which is very useful. In data transformation terms, it's basically does this- given a string 's', filter the dataframe by ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13499 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13499/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13499/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13499/events | https://github.com/pandas-dev/pandas/pull/13499 | 161,912,477 | MDExOlB1bGxSZXF1ZXN0NzQ5NDcyNzA= | 13,499 | DOC: fix accessor docs for sphinx > 1.3 (GH12161) | {
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With this change, the links in the api summary to the accessor methods should work again.
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https://api.github.com/repos/pandas-dev/pandas/issues/13500 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13500/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13500/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13500/events | https://github.com/pandas-dev/pandas/issues/13500 | 161,925,954 | MDU6SXNzdWUxNjE5MjU5NTQ= | 13,500 | API: Expanded resample | {
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... | 1 | 2016-06-23T13:42:17Z | 2016-08-31T13:13:55Z | 2016-08-31T13:13:55Z | CONTRIBUTOR | null | Idea after seeing the gitter between @ssanderson and @jorisvandenbossche
Consider this data:
```
In [13]: df = pd.DataFrame({'date': pd.date_range('2015-01-01', freq='W', periods=5),
'a': np.arange(5)},
index=pd.MultiIndex.from_arrays([
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https://api.github.com/repos/pandas-dev/pandas/issues/13501 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13501/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13501/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13501/events | https://github.com/pandas-dev/pandas/issues/13501 | 161,930,304 | MDU6SXNzdWUxNjE5MzAzMDQ= | 13,501 | Partial indexing with a list and hierarchical index | {
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"followers_url": "https://api.github.com/users/j... | 4 | 2016-06-23T14:00:53Z | 2021-05-17T15:17:29Z | 2021-05-17T15:17:29Z | CONTRIBUTOR | null | #### Code Sample, a copy-pastable example if possible
Teaching a pandas course. Attendee just came across this. Note that we index with a list instead of a tuple at the bottom.
``` python
frame = pd.DataFrame(np.arange(12).reshape(( 4, 3)),
index =[['a', 'a', 'b', 'b'], [1, 2, 1, 2]],
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https://api.github.com/repos/pandas-dev/pandas/issues/13502 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13502/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13502/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13502/events | https://github.com/pandas-dev/pandas/pull/13502 | 161,952,633 | MDExOlB1bGxSZXF1ZXN0NzQ5NzU4NDQ= | 13,502 | DOC: various doc build fixes | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13503 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13503/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13503/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13503/events | https://github.com/pandas-dev/pandas/issues/13503 | 161,963,499 | MDU6SXNzdWUxNjE5NjM0OTk= | 13,503 | Rolling(axis='columns').count() ignores axis= keyword | {
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#### Code Sample, a copy-pastable example if possible
``` python
In [1]: import pandas as pd
In [2]: df = pd.DataFrame({'x': range(5), 'y': range(5)})
In [3]: df
Out[3]:
x y
0 0 0
1 1 1
2 2 2
3 3 3
4 4 4
In [4]: df.rolling(2, axis='columns').sum() # meets expectations
Out[4]... | {
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