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https://api.github.com/repos/pandas-dev/pandas/issues/14408 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14408/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14408/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14408/events | https://github.com/pandas-dev/pandas/issues/14408 | 182,653,997 | MDU6SXNzdWUxODI2NTM5OTc= | 14,408 | PERF: to_json very slow with lines=True | {
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``` python
N = 100000
C = 5
In [6]: df = DataFrame(dict([('float{0}'.format(i), np.random.randn(N)) for i in range(C)]))
In [7]: df.to_json('foo.json',orient='records',lines=True)
In [8]: %timeit df.to_json('foo.json',orient='records',lines=True)
1 loop, best of 3: 3.66 s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14409 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14409/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14409/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14409/events | https://github.com/pandas-dev/pandas/pull/14409 | 182,661,622 | MDExOlB1bGxSZXF1ZXN0ODkxMTQ1NDU= | 14,409 | DOC: pydata/pandas -> pandas-dev/pandas | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14410 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14410/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14410/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14410/events | https://github.com/pandas-dev/pandas/issues/14410 | 182,661,883 | MDU6SXNzdWUxODI2NjE4ODM= | 14,410 | ENH: Do not exclude Boolean columns from DataFrame.describe() | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2016-10-12T23:48:42Z | 2016-10-12T23:57:48Z | 2016-10-12T23:57:12Z | NONE | null | Sometimes, it is desired to know the percentage of true values in a Boolean column. Like when a DataFrame is composed of results from fitting many models, knowing up front the distribution of number of successful fits is helpful.
```
In [1]: df = pd.DataFrame({'c1' : list('abcdef'),
'c2' : [... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14411 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14411/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14411/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14411/events | https://github.com/pandas-dev/pandas/issues/14411 | 182,692,768 | MDU6SXNzdWUxODI2OTI3Njg= | 14,411 | Behavior change in Index.equals from 0.18.0 to 0.19.0 -- intentional? | {
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"followers_url": "https://api.github.com/users/j... | 2 | 2016-10-13T04:22:42Z | 2019-06-28T19:54:50Z | 2019-06-28T19:54:50Z | NONE | null | Traditionally, we have:
``` python
In [3]: pandas.__version__
Out[3]: '0.18.0'
In [4]: pandas.Index([1, 2]).equals([1, 2])
Out[4]: True
```
But this changed
``` python
In [4]: pandas.__version__
Out[4]: '0.19.0'
In [5]: pandas.Index([1, 2]).equals([1, 2])
Out[5]: False
```
Looks like it might not be intentional s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14412 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14412/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14412/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14412/events | https://github.com/pandas-dev/pandas/pull/14412 | 182,693,040 | MDExOlB1bGxSZXF1ZXN0ODkxMzQ4OTE= | 14,412 | Bug: Made it so that 0 was included in uint8 | {
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"followers_url": "https://api.github.com/users/jre... | 3 | 2016-10-13T04:25:29Z | 2016-10-22T08:49:42Z | 2016-10-21T23:55:53Z | NONE | null | - [ ] closes #14401
- [ ] tests added / passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
Decided to restart. Sorry for the inconvenience. -> #14472
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``` python
# Your code here
```
#### Expected Output
#### Output of `pd.show_versions()`
<details>
# Paste the output here
</details>
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https://api.github.com/repos/pandas-dev/pandas/issues/14414 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14414/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14414/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14414/events | https://github.com/pandas-dev/pandas/issues/14414 | 182,780,727 | MDU6SXNzdWUxODI3ODA3Mjc= | 14,414 | Cannot initialize a data frame with None | {
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just figured out that the following code
```
pd.DataFrame({'x':None}, index=[0])
```
works in 0.18.1 but not 0.19.0, is that the expected behavior? Thanks!
Best,
Jie
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``` python
# Your code here
In [1]: import numpy as np; import pandas as pd
In [3]: pd.Timestamp(np.iinfo(np.int64).min + 80000000000000)
Out[3]: Timestamp('2262-04-11 22:26:03.145224192')
In [4]: pd.Timestamp(np.iinfo(np.int64).min + 90000000000000)
Out[4]: Timestamp('1677... | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
I closed #14389 and opened with one in hopes of the new commits showing up.
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https://api.github.com/repos/pandas-dev/pandas/issues/14417 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14417/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14417/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14417/events | https://github.com/pandas-dev/pandas/issues/14417 | 182,862,538 | MDU6SXNzdWUxODI4NjI1Mzg= | 14,417 | BUG: index.max() not matching index.levels[0].max() for multiindex on sliced dataframe | {
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``` python
df = pd.DataFrame(index=pd.MultiIndex.from_product([['A','B','C'],['a','b']])
```
Then:
``` python
df.loc[:'B'].index.max()
```
gives `('B', 'b')` as expected.
But:
``` python
df.loc[:'B'].index.levels[0].max()
```
gives `'C'` in conflict with the previous result.
#### Expected Functiona... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14418 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14418/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14418/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14418/events | https://github.com/pandas-dev/pandas/issues/14418 | 182,874,273 | MDU6SXNzdWUxODI4NzQyNzM= | 14,418 | read_csv and others derived from _read close user-provided filehandles | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14419 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14419/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14419/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14419/events | https://github.com/pandas-dev/pandas/pull/14419 | 182,889,591 | MDExOlB1bGxSZXF1ZXN0ODkyNzQyNDI= | 14,419 | Period factorization | {
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"followers_url": "https://api.github.com/users/jre... | 2 | 2016-10-13T20:17:07Z | 2016-10-15T19:27:19Z | 2016-10-15T19:27:11Z | CONTRIBUTOR | null | - [x] closes #14338
- [x] tests not needed / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
asv
```
before after ratio
[c41c6511] [96b364a4]
- 2.44s 46.28ms 0.02 groupby.groupby_period.time_groupby_sum
```
Continuation of #14348
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https://api.github.com/repos/pandas-dev/pandas/issues/14420 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14420/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14420/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14420/events | https://github.com/pandas-dev/pandas/issues/14420 | 182,899,198 | MDU6SXNzdWUxODI4OTkxOTg= | 14,420 | DataFrame.groupby(level=...).rolling(n).mean() | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2016-10-13T20:58:07Z | 2016-10-13T21:12:13Z | 2016-10-13T21:11:55Z | NONE | null | Using the groupby().rolling() object seems to duplicate a level of the index.
```
In [9]: d.groupby(level='ticker').rolling(30).mean()
Out[9]:
ticker ticker date
BMO BMO 2006-01-02 NaN
2006-01-03 NaN
TD TD 2016-09-22 57.139340
2016-09-23 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14421 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14421/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14421/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14421/events | https://github.com/pandas-dev/pandas/issues/14421 | 182,928,675 | MDU6SXNzdWUxODI5Mjg2NzU= | 14,421 | cryptic DataFrame.agg error when using dictionaries | {
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"followers_url": "https://api.github.com/users/jorisva... | 18 | 2016-10-13T23:23:18Z | 2016-10-14T19:33:06Z | 2016-10-13T23:30:19Z | NONE | null | Not sure if this is a bug. This works:
``` python
(
pd.DataFrame({"u": [2,1,4,2,5], "a": ["a", "a", "b", "a", "b"]})
.groupby("a")
.agg(lambda x: np.mean(x)/np.std(x))
)
```
while this returns an error:
``` python
(
pd.DataFrame({"u": [2,1,4,2,5], "a": ["a", "a", "b", "a", "b"]})
.groupby("a")
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14422 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14422/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14422/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14422/events | https://github.com/pandas-dev/pandas/issues/14422 | 182,947,993 | MDU6SXNzdWUxODI5NDc5OTM= | 14,422 | BUG: to_numeric doesn't work uint64 numbers | {
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``` python
In [10]: pd.to_numeric(pd.Series([0, 9223372036854775808]), downcast = 'unsigned')
---------------------------------------------------------------------------
OverflowError Traceback (most recent call last)
<ip... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14423 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14423/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14423/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14423/events | https://github.com/pandas-dev/pandas/issues/14423 | 182,959,741 | MDU6SXNzdWUxODI5NTk3NDE= | 14,423 | BUG: unwanted numeric coercion after groupby-apply | {
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xref #14849 (datetime)
#### A small, complete example of the issue
``` python
import pandas as pd
def predictions(tool):
out = pd.Series(index=['p1', 'p2', 'useTime'], dtype=object)
if 'step1' in list(tool.State):
out['p1'] = str(tool[tool.State == 'step1'].Mach... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14424 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14424/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14424/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14424/events | https://github.com/pandas-dev/pandas/pull/14424 | 183,026,019 | MDExOlB1bGxSZXF1ZXN0ODkzNjc2Njk= | 14,424 | BUG: String indexing against object dtype may raise AttributeError | {
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"followers_url": "https://api.github.com/users/jre... | 3 | 2016-10-14T11:21:48Z | 2016-10-22T09:54:41Z | 2016-10-22T09:54:33Z | MEMBER | null | - [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
String indexing may raise `AttributeError`, rather than `KeyError`.
```
df = pd.DataFrame([1], pd.Index([pd.Timestamp('2011-01-01')], dtype=object))
df.index.is_all_dates
# True
df['2011']
# AttributeError: 'Index'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14425 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14425/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14425/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14425/events | https://github.com/pandas-dev/pandas/issues/14425 | 183,028,910 | MDU6SXNzdWUxODMwMjg5MTA= | 14,425 | incorrect calculation of centered moving averages for even length series | {
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- [x] tests added / passed
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#### A small, complete example of the issue
``` python
import pandas as pd
df1 = pd.DataFrame({'a': [1, 2, 3]})
df2 = pd.DataFrame({'b': [2,3,4]})
df = pd.concat([df1, df1, df2], axis=1).to_sparse()
df.index = [1, 2, 3]
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- [x] tests added / passed
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- [x] whatsnew entry
This PR is a continuation of #14333. See discussion there for explanation of why this new PR was needed.
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master
```
In [1]: np.random.seed(1234)
In [2]: N = 100000
...: C = 5
...: df = DataFrame(dict([('float{0}'.format(i), np.random.randn(N)) for i in range(C)]))
In [3]: %timeit df.to_json('foo.json',orient='records',lines=True)
1 loop, best of 3: 3.67 s per loop
```
PR (with proper encoding/deco... | {
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Resubmitting PR (@jorisvandenbossche)
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/14434 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14434/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14434/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14434/events | https://github.com/pandas-dev/pandas/pull/14434 | 183,279,933 | MDExOlB1bGxSZXF1ZXN0ODk1MzI5NTk= | 14,434 | Checks for left_index and right_index merge parameters | {
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I just committed an error when I was doing an analysis using pandas and this motivated me to implement two checks which in my opinion are necessary.
I was trying to perform a merge and I confused the parameters "left_on" and "right_on" for "left_index" and "right_index". I ran the code and it did not raised me a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14435 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14435/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14435/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14435/events | https://github.com/pandas-dev/pandas/issues/14435 | 183,292,725 | MDU6SXNzdWUxODMyOTI3MjU= | 14,435 | HDF Store with multi-index problems when using data_columns=True | {
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Not sure if this is supposed to be like this. When I store a multi-index along with the option `data_column=True`, I cannot query along the dataframe indexes only the columns are valid references. However, it works when I store them with the option `data_columns=[...]`.
``` python
import pandas as pd
import nu... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14436 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14436/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14436/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14436/events | https://github.com/pandas-dev/pandas/pull/14436 | 183,307,716 | MDExOlB1bGxSZXF1ZXN0ODk1NDkzMDQ= | 14,436 | WIP: Rework IndexEngine to better support hashtable-free algorithms. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14437 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14437/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14437/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14437/events | https://github.com/pandas-dev/pandas/issues/14437 | 183,343,675 | MDU6SXNzdWUxODMzNDM2NzU= | 14,437 | .unique() inconsistency between Series and Index objects | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2016-10-17T07:26:02Z | 2016-10-17T10:51:20Z | 2016-10-17T10:18:36Z | CONTRIBUTOR | null | #### A small, complete example of the issue
``` python
ix = pd.Index([0,0,1,2])
sr = pd.Series([0,0,1,2])
ix.unique()
Int64Index([0, 1, 2], dtype='int64')
sr.unique()
array([0, 1, 2], dtype=int64)
```
#### Expected Output
I'd expect that unique returns the original datatype or always an array.
I'd prefer the origi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14438 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14438/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14438/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14438/events | https://github.com/pandas-dev/pandas/issues/14438 | 183,404,422 | MDU6SXNzdWUxODM0MDQ0MjI= | 14,438 | BUG: concat with dataframes heterogeneous in length and tuple keys | {
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"followers_url": "https://api.github.com/users/jre... | 1 | 2016-10-17T12:36:37Z | 2016-10-20T10:28:27Z | 2016-10-20T10:25:35Z | CONTRIBUTOR | null | #### A small, complete example of the issue
``` python
import numpy as np
import pandas as pd
df1 = pd.DataFrame(np.random.rand(4).reshape((2, 2)), columns=list('AB'))
df2 = pd.DataFrame(np.random.rand(6).reshape((3, 2)), columns=list('AB'))
print(pd.concat([df1, df2], keys=[('bee', 'bah'), ('bee', 'bouh')], names=['z... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14439 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14439/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14439/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14439/events | https://github.com/pandas-dev/pandas/issues/14439 | 183,412,719 | MDU6SXNzdWUxODM0MTI3MTk= | 14,439 | DEV: Update merge-pr.py script given repo rename | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14440 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14440/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14440/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14440/events | https://github.com/pandas-dev/pandas/issues/14440 | 183,419,690 | MDU6SXNzdWUxODM0MTk2OTA= | 14,440 | Floating point accuracy problems in `DatetimeIndex.round` | {
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There is a slight problem when using the rounding methods of `DatetimeIndex` (`round, floor, ceil`) to high frequencies as illustrated by this example:
``` python
pd.DatetimeIndex(['2016-10-17 12:00:00.0015']).round('ms')
DatetimeIndex(['2016-10-17 12:00:00.001999872'], dty... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14441 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14441/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14441/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14441/events | https://github.com/pandas-dev/pandas/pull/14441 | 183,443,939 | MDExOlB1bGxSZXF1ZXN0ODk2NDMxODU= | 14,441 | Update unpack_template.h | {
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"followers_url": "https://api.github.com/users/jre... | 4 | 2016-10-17T15:12:36Z | 2016-10-20T22:44:57Z | 2016-10-20T22:44:39Z | CONTRIBUTOR | null | - [x ] closes #14373
- [ ] tests added / passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
USE_CASE_RANGE is a GNU C feature. This change will activate
USE_CASE_RANGE on any platform when using GNU C and not on any platform
when a different compiler is being used.
closes #14373
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https://api.github.com/repos/pandas-dev/pandas/issues/14442 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14442/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14442/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14442/events | https://github.com/pandas-dev/pandas/pull/14442 | 183,474,682 | MDExOlB1bGxSZXF1ZXN0ODk2NjUxMDQ= | 14,442 | DOC: Expand on reference docs for read_json | {
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"followers_url": "https://api.github.com/users/jre... | 3 | 2016-10-17T17:15:12Z | 2016-10-27T13:51:10Z | 2016-10-27T13:51:10Z | CONTRIBUTOR | null | - [ ] closes #xxxx
- [ ] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [] whatsnew entry
Continuation of closed PR #14284
Documentation update for `read_json()`.
expanded reference document for pandas.read_json(), especially concentrating on the orient parameter. Also added some exampl... | {
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This is sample... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14444 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14444/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14444/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14444/events | https://github.com/pandas-dev/pandas/issues/14444 | 183,543,183 | MDU6SXNzdWUxODM1NDMxODM= | 14,444 | Series `sort_index` missing `kind` keyword | {
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``` python
>>> import pandas as pd
>>> pd.Series(index=[3,2,1,4,3]).sort_index(kind='mergesort')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: sort_index() got an unexpected keyword argument 'kind'
```
#### Expected Output
A `Series` s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14445 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14445/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14445/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14445/events | https://github.com/pandas-dev/pandas/pull/14445 | 183,553,468 | MDExOlB1bGxSZXF1ZXN0ODk3MjE1MzY= | 14,445 | ENH: support kind and na_position kwargs in Series.sort_index | {
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closes #13729
I'm waiting on adding the whatsnew entry. I'm not sure if this is a BUG (the [documentation](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.sort_index.html) says these parameters exist) or an ENH (we're adding support for these parameters). It depends on how you look ... | {
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"followers_url": "https://api.github.com/users/jr... | 15 | 2016-10-18T12:38:41Z | 2017-03-03T10:07:39Z | 2017-03-02T13:44:58Z | CONTRIBUTOR | null | - [x] closes #13937
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] 0.20.0
Fix index for datetime64 conversion
This PR fixes index for datetime64 conversion. Also,
update tests - pandas/pandas/tests/tests_convert_to.py
Fixes https://github.com/pydata/pandas/issues/1... | {
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referring too http://pandas.pydata.org/pandas-docs/stable/generated/pandas.to_datetime.html
The example provides different results.
``` python
# Your code here
import pandas as pd
pd.to_datetime('13000101', format='%Y%m%d')
```
raises...
```
Traceback (most recent call... | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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``` python
df = pd.DataFrame({"data": np.arange(0, 10, 0.1)})
v = pd.cut(df.data, [0, 1, 2, 5, 10], include_lowest=True).rename("cuts")
df.join(pd.get_dummies(v))
```
#### Expected Output
A data frame similar to the input dataframe with 4 additional variables for the cut ca... | {
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I'm writing a text mining toolkit, and decided to try pandas because it offered convenience row-and-column labelled access. Numpy doesn't, and structured numpy arrays only have named columns.
#### Performance Problem
Indexing text, and manipulating dataframes of word co-occurrence/relevance appeared to ... | {
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- [ ] tests added / passed
- [ ] passes git diff upstream/master | flake8 --diff
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``` python
# A dataframe with a category variable
df = pd.DataFrame({ 'day' : [1,2,3], 'month' : ['a','b','c'], 'dow' : ['mon','mon','thur' ]})
df = df.set_index(['day','month'])
df.dow = df.dow.astype('category')
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- [ ] tests added / passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
Add option to drop non-unique bins.
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- [x] closes #14448
- [ ] tests added / passed
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http://stackoverflow.com/q/40141881/2336654
``` python
import pandas as pd
import numpy as np
df = pd.DataFrame(dict(A=['a', 'a'], B=[0, 1]))
print(df.groupby('A').transform(np.mean))
# is no the same as
print(df.groupby('A').transform(lambda x: np.mean(x)))
```
#### Output of `pd.show_versions()`
<det... | {
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- [x] tests added / passed
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Alternative to #14340
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https://api.github.com/repos/pandas-dev/pandas/issues/14459 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14459/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14459/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14459/events | https://github.com/pandas-dev/pandas/issues/14459 | 184,212,730 | MDU6SXNzdWUxODQyMTI3MzA= | 14,459 | Conflict b/w skiprows and default quotechar kwargs to pandas.read_table | {
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"description": "Functionality that used ... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jre... | 14 | 2016-10-20T12:13:41Z | 2016-10-31T20:39:59Z | 2016-10-31T20:39:59Z | NONE | null | #### A small, complete example of the issue
while trying to open a data file similar to
```
a
b"
c
d
e"
a,b,c
1,2,3
4,5,6
7,8,9
```
i expect the following code
```
python -c "import pandas; df = pandas.read_table('quoted_data.csv', skiprows=5, sep=','); print df"
```
#### Expected Output
```
a b c
0 1 2 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14460 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14460/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14460/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14460/events | https://github.com/pandas-dev/pandas/issues/14460 | 184,213,943 | MDU6SXNzdWUxODQyMTM5NDM= | 14,460 | Strip columns/column names in data frame of white spaces | {
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"... | open | false | null | [] | null | 9 | 2016-10-20T12:19:37Z | 2021-05-02T00:33:43Z | null | NONE | null | This is more of a question than a bug.
#### A small, complete example of the issue
while opening a data file similar to
```
a , b , c , d
1 , 2 , 3 , 4
5 , 6 , 7 , 8
```
using
``` python
python -c "import pandas; df = pandas.read_table('unstripped_data.csv', sep=','); print df.columns"
```
#### Observed Outpu... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14461 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14461/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14461/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14461/events | https://github.com/pandas-dev/pandas/issues/14461 | 184,272,494 | MDU6SXNzdWUxODQyNzI0OTQ= | 14,461 | pd.Series.asof performance regression: 14x slower | {
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"followers_url": "https://api.github.com/users/jre... | 9 | 2016-10-20T16:05:57Z | 2016-10-26T08:16:57Z | 2016-10-26T08:16:57Z | CONTRIBUTOR | null | #### pd.Series.asof takes 14x longer in 0.19.0 than 0.18.1
``` python
In[14]: pd.__version__
Out[14]: '0.18.1'
In[15]: s = pd.Series([1, 1, 1, np.nan, np.nan])
In[16]: %timeit s.asof(4)
The slowest run took 8.25 times longer than the fastest. This could mean that an intermediate result is being cached.
100000 loops, b... | {
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... | 4 | 2016-10-20T19:27:26Z | 2020-09-22T10:22:28Z | null | CONTRIBUTOR | null | Pandas DataFrames containing text columns are expensive to serialize. This affects dask.dataframe performance in multiprocessing or distributed settings.
### Pickle is expensive
In particular the current solution of using `pickle.dumps` for object dtype columns can be needlessly expensive when all of the values in th... | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2016-10-20T20:46:27Z | 2016-10-21T10:41:59Z | 2016-10-21T10:41:43Z | NONE | null | ``` python
s = pd.DataFrame(["I love you", "Pandas", "<3"], index=["A", "B", "C"],columns=['a'])
io=r"\b(Pandas)\b"
s['a'].str.extractall(io)
```
#### Expected Output
```
0
```
match
B 0 Pandas
#### Output of `pd.show_versions()`
## INSTALLED VERSIONS
commit: None
python: 3.5.2.final.0
pyt... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14464 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14464/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14464/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14464/events | https://github.com/pandas-dev/pandas/issues/14464 | 184,377,161 | MDU6SXNzdWUxODQzNzcxNjE= | 14,464 | Allow DataFrame.apply() to accept dict of funcs | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-10-21T01:08:01Z | 2017-10-27T19:06:18Z | 2017-04-14T15:37:04Z | CONTRIBUTOR | null | When using DataFrame.apply(), it would be helpful to be able to apply different functions to different columns. There's a nice workaround on [StackOverflow](http://stackoverflow.com/questions/26434123/pandas-apply-different-functions-to-different-columns):
``` python
import numpy as np
import pandas as pd
def multi_f... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14465 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14465/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14465/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14465/events | https://github.com/pandas-dev/pandas/pull/14465 | 184,407,772 | MDExOlB1bGxSZXF1ZXN0OTAzMjgzNTA= | 14,465 | MAINT: Use check_output when merging. | {
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"followers_url": "https://api.github.com/users/jre... | 2 | 2016-10-21T06:18:41Z | 2016-10-24T22:10:15Z | 2016-10-24T22:10:14Z | MEMBER | null | Since we don't support Python 2.6 anymore, the `check_output` method from `subprocess` is
at our disposal.
Follow-up to #14447.
xref <a href="https://github.com/pandas-dev/pandas/issues/14439#issuecomment-254522055"> #14439 (comment)</a>
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#### A small, complete example of the issue
``` python
df = pd.DataFrame([[1, 2, 3], [4, 5, 6]],
index=[['gibberish']*2, [0, 1]],
columns=[['baldersash']*3, [10, 20, 30]])
```
The result is
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might be interesting if someone is looking for a project :>
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https://api.github.com/repos/pandas-dev/pandas/issues/14469 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14469/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14469/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14469/events | https://github.com/pandas-dev/pandas/issues/14469 | 184,569,362 | MDU6SXNzdWUxODQ1NjkzNjI= | 14,469 | pd.read_html() not working showing error in _html5lib.py | {
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pd.read_html() not working showing error in _html5lib.py,line 70 class TreeBuilderForHtml5lib
``` python
import pandas as pd
import html5lib
import lxml
data = pd.read_html('https://blockchain.info/blocks')
```
gives
```
File "C:\Anaconda2\lib\site-packages\bs4\builder... | {
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The code came directly from a w... | {
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- [ ] closes #14401
- [ ] tests added / passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
Once again I had some very bizarre issues with git. Hope this does it this time.
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Added test case to check for invalid input(empy string) on pd.eval('') and df.query('').
Used existing helper function(_check_expression)
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Open issues/PRs: https://github.com/pandas-dev/pandas/milestones/0.19.1
Some issues still that would be nice to ... | {
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"followers_url": "https://api.github.com/users/jre... | 3 | 2016-10-22T11:49:26Z | 2016-10-24T22:24:19Z | 2016-10-24T22:24:18Z | CONTRIBUTOR | null | - [x] closes #14204
- [x] tests not needed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
We could just make a cython a build-time requirement, but given we already create a sdists with `.c` files, probably makes sense to continue to support it.
I tested this locally, applying this patch... | {
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- [x] closes #14461
- [x] add asv benchmark
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https://api.github.com/repos/pandas-dev/pandas/issues/14477 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14477/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14477/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14477/events | https://github.com/pandas-dev/pandas/issues/14477 | 184,665,418 | MDU6SXNzdWUxODQ2NjU0MTg= | 14,477 | read_csv incompatible with newstr and future | {
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#### A small, complete example of the issue
``` python
import pandas... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14478 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14478/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14478/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14478/events | https://github.com/pandas-dev/pandas/issues/14478 | 184,704,997 | MDU6SXNzdWUxODQ3MDQ5OTc= | 14,478 | df.to_hdf() blocks some supported pytables compression types ‘blosc:lz4’, ‘blosc:lz4hc’, ‘blosc:snappy’, ‘blosc:zlib’ and ‘blosc:zstd’ | {
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I would like to try blosc:lz4 compression for some of the bigger data I have to compare size and speed to LZO.
``` python
df.to_hdf(path, 'df', complib='blos... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14480 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14480/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14480/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14480/events | https://github.com/pandas-dev/pandas/issues/14480 | 184,786,633 | MDU6SXNzdWUxODQ3ODY2MzM= | 14,480 | Strip whitespace from column names when usecols in read_csv | {
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when loading a file of the type, where headers have a trailing whitespace,
```
a ,b ,c
1,2,3
4,5,6
```
I would expect the following code to work and give the result
``` python
pandas.read_table('test_data.csv', sep=',', usecols=['a', 'b'])
```
#### Expected Output
```
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I read a CSV file that has a string column with some missing values, and pandas loads those missing string values as NaN. Pandas won't let me group on that string value, so I'm trying to fillna() with the value "<blank>". But that doesn't work either, pandas overwrites the good values th... | {
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#### Code Snippet
``` python
import pandas as pd
outliers_lst = [(23240, 0)... | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2016-10-24T19:56:35Z | 2016-10-24T22:05:54Z | 2016-10-24T22:05:53Z | NONE | null | Assume we have a simple DF like this
```
x = pd.DataFrame({'a':[1,1,2,2],'b':['a','a','a','b'],'c':[[1,2],[3,4],[5,6],[7,8]]})
a b c
0 1 a [1, 2]
1 1 a [3, 4]
2 2 a [5, 6]
3 2 b [7, 8]
```
and we want to do a groupby operation that concatenates the lists in column `c` together. This works fine... | {
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... | 0 | 2016-10-24T22:00:16Z | 2021-05-02T00:39:15Z | null | NONE | null | #### A small, complete example of the issue
I am not sure I understand how label generation work in pandas and I've had several problems in the past. I tried to find some documentation without success so here is my pb. I open a ticket here since I was told on gitter it might be a bug but it might just be me misunderst... | {
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... | 5 | 2016-10-24T22:56:44Z | 2021-05-02T00:39:44Z | null | MEMBER | null | Copying from https://github.com/pandas-dev/pandas/issues/14448#issuecomment-255068330 (as the issue is closed now):
```
In [1]: pd.to_datetime('13000101', errors='ignore')
Out[1]: '13000101'
In [2]: pd.to_datetime('13000101', errors='ignore', format='%Y%m%d')
Out[2]: datetime.datetime(1300, 1, 1, 0, 0)
```
The above... | {
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It can be done with the following little changes:
In file `/pandas/io/pickle.py`:
```
def to_pickle(obj, path, protocol=pkl.HIGHEST_PROTOCOL):
"""
Pi... | {
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IIRC some issues w.r.t. int *\* int. unrelated to this PR.
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2016-10-25T14:32:05Z | 2016-10-26T10:21:26Z | 2016-10-26T10:21:03Z | CONTRIBUTOR | null | I am getting "time out" errors when trying to read from a large CSV (2GB) in S3:
``` python
df = pd.read_csv('path_to_2GB_file.csv')
```
The file is hosted privately so unfortunately can't make it accessible. I'll be happy to try reading from an open/public S3 repository if anyone knows where to get CSVs of a similar... | {
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Using a boolean index in a `pandas.Series` on a data frame with an string index fails with `Unalignable boolean Series key provided`:
``` python
import pandas as pd
# DF without string index
df = pd.DataFrame({"A": [0, 1, 2]})
df.loc[[True, True, True], :] # ... | {
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``` python
# Your code here
sparse_df = df.pivot(index='a', columns='b', values='c', aggfunc=lambda x: len(x), sparse=True)
```
#### Expected Output
#### Output of `pd.show_versions()`
<details>
# Paste the output here
</details>
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
I was thinking about code paths that give away borrowed references to strings and realized that interned strings can be accessed even when their refcount is 1. This is because the intern table hol... | {
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https://pypi.python.org/pypi/Bottleneck
its not up on conda-forge (or defaults ATM). so need to watch for that and test.
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The distutils extension Cython.Distutils.build_ext has now been updated to use cythonize which properly handles dependencies. The old extension can still be found in Cython.Distutils.old_build_ext and is now deprecated.
seems to have broken the include of auto-generated algos_common_helper.... | {
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Numpy starts to error on those cases from 1.12 https://github.com/numpy/numpy/pull/8127
This just fixes the test for now, but other option is to coerce to floats (but that is certainly not for 0.19.1)
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closes #14489
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... | 7 | 2016-10-26T11:01:38Z | 2017-01-20T12:16:29Z | 2017-01-20T12:16:29Z | CONTRIBUTOR | null | #### A small, complete example of the issue
``` python
a = pd.Panel({'a':np.arange(15).reshape((5,3)), 'b':np.arange(15,30).reshape((5,3))})
a['a'].loc[1,1] = np.nan
a['a']
Out[36]:
0 1 2
0 0 1.0 2
1 3 NaN 5
2 6 7.0 8
3 9 10.0 11
4 12 13.0 14
a.ffill(axis=2)['a']
Out[38]:
0 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14500 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14500/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14500/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14500/events | https://github.com/pandas-dev/pandas/issues/14500 | 185,366,384 | MDU6SXNzdWUxODUzNjYzODQ= | 14,500 | BUG: index.map() deletes index.name | {
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Possibly a duplicate.
#### A small, complete example of the issue
```
DD = pd.DataFrame({'A':[1,2,3,4,5]})
DD.index.name = 'Test'
print DD.index.name
DD.index = DD.index.map(unicode)
print DD.index.name
```
#### Expected Output
The mapping operation... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14501 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14501/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14501/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14501/events | https://github.com/pandas-dev/pandas/pull/14501 | 185,379,186 | MDExOlB1bGxSZXF1ZXN0OTA5OTM5MjY= | 14,501 | BUG: fix DatetimeIndex._maybe_cast_slice_bound for empty index (GH14354) | {
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... | 2 | 2016-10-26T16:47:34Z | 2021-05-02T00:40:16Z | null | CONTRIBUTOR | null | In https://github.com/pandas-dev/pandas/pull/13406 Chris added support for `read_csv(..., dtype={'col': 'category'})` (thanks!). This issue is for expanding that syntax to allow a more complete specification of the resulting categorical.
``` python
# Your code here
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"followers_url": "https://api.github.com/users/jr... | 8 | 2016-10-26T17:42:43Z | 2017-02-24T01:36:34Z | 2016-11-17T13:10:59Z | NONE | null | - [ ] closes #14401
- [ ] tests added / passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
Have to figure out whats going wrong with the build still. Will let you know as soon as I do.
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---
When using pandas.io.json.json_normalize to parse a nested json and convert it to a dataframe, the meta parameter can be used to use fields as metadata for each record in resulting table. In some cases, not all items may contain all of the specified... | {
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- [x] closes #12798
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
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This is a follow on to #12798.
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- [ ] whatsnew entry (This is a bugfix for https://github.com/pandas-dev/pandas/pull/14429 and https://github.com/pandas-dev/pandas/pull/14391)
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