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https://api.github.com/repos/pandas-dev/pandas/issues/8001 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8001/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8001/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8001/events | https://github.com/pandas-dev/pandas/issues/8001 | 40,057,868 | MDU6SXNzdWU0MDA1Nzg2OA== | 8,001 | Inconsistent indexing of mixed type indexed Series | {
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"color": "00... | closed | false | null | [] | null | 1 | 2014-08-12T14:04:51Z | 2014-08-13T12:25:36Z | 2014-08-12T14:07:22Z | NONE | null | Consider the following code:
``` python
import pandas as pd
sr = pd.Series(data=[1,2,3,4], index=[1,2, '3', '4'])
print sr[1]
print sr[[1,2]]
```
Note that the rows of the Series are both indexed with integers and strings.
This generates the following output:
1
2 2
3 3
The first print statement selects... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8002 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8002/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8002/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8002/events | https://github.com/pandas-dev/pandas/issues/8002 | 40,065,647 | MDU6SXNzdWU0MDA2NTY0Nw== | 8,002 | BUG: float conversion in read_csv is inaccurate for precise input | {
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"followers_url": "https://api.github.com/users/jr... | 7 | 2014-08-12T15:17:32Z | 2014-09-19T16:07:47Z | 2014-09-19T16:07:47Z | CONTRIBUTOR | null | This is coming from #2566, which noted that the `xstrtod()` method used by `read_csv` doesn't agree with standard numpy float conversion. I see that the priority is speed of parsing over complete accuracy (within 0.5 units in the last place, or ULP), but there are two issues here that (at least to me) actually appear t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8003 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8003/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8003/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8003/events | https://github.com/pandas-dev/pandas/pull/8003 | 40,066,202 | MDExOlB1bGxSZXF1ZXN0MTk2Njg1NDA= | 8,003 | API: consistency in .loc indexing when no values are found in a list-like indexer GH7999) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8004 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8004/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8004/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8004/events | https://github.com/pandas-dev/pandas/issues/8004 | 40,066,882 | MDU6SXNzdWU0MDA2Njg4Mg== | 8,004 | Pandas doesn't accept dtype=np.datetime64 | {
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... | 15 | 2014-08-12T15:29:05Z | 2019-12-18T23:26:00Z | 2019-12-18T23:26:00Z | CONTRIBUTOR | null | ```
In [1]: from pandas import Series
In [3]: import numpy as np
In [4]: Series([], dtype=np.datetime64)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-4-139e5646d234> in <module>()
----> 1 Series... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8005 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8005/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8005/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8005/events | https://github.com/pandas-dev/pandas/issues/8005 | 40,067,961 | MDU6SXNzdWU0MDA2Nzk2MQ== | 8,005 | Inconsistent behavior using 'in' operator | {
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] | closed | false | null | [] | null | 1 | 2014-08-12T15:39:18Z | 2014-08-12T15:43:09Z | 2014-08-12T15:43:04Z | NONE | null | Operator **in** works differently with str and int in series; please see short snippet below.
`import pandas as pd`
`df1 = pd.DataFrame({'a':['a','b','c'], 'b':['d','e','f']})`
`df2 = pd.DataFrame({'a':[1,2,3], 'b':[3,2,1]})`
`df1.a[0] in df1.a`
False
`df2.a[0] in df2.a`
True
## INSTALLED VERSIONS
commit: None
python... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8006 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8006/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8006/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8006/events | https://github.com/pandas-dev/pandas/pull/8006 | 40,072,094 | MDExOlB1bGxSZXF1ZXN0MTk2NzIzNzQ= | 8,006 | CLN/DOC/TST: categorical fixups (GH7768) | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-08-12T16:18:20Z | 2014-08-12T18:15:28Z | 2014-08-12T18:14:25Z | CONTRIBUTOR | null | replaces #7768
closes #3678
Categorical([1, np.nan]) would end up with a single `1.` float level.
This commit ensures that if `values` is a list of ints and contains np.nan,
the float conversation does not take place.
Categorical: fix describe with np.nan
Categorical: ensure that one can assign np.nan
Categorical... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8007 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8007/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8007/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8007/events | https://github.com/pandas-dev/pandas/pull/8007 | 40,082,909 | MDExOlB1bGxSZXF1ZXN0MTk2NzkzMTA= | 8,007 | CLN/DOC/TST: Categorical fixups (GH7768) | {
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closes #3678
Categorical: preserve ints when NaN are present
`Categorical([1, np.nan])` would end up with a single `1.` float level.
This commit ensures that if `values` is a list of ints and contains np.nan,
the float conversation does not take place.
Categorical: fix describe with np.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8008 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8008/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8008/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8008/events | https://github.com/pandas-dev/pandas/pull/8008 | 40,103,789 | MDExOlB1bGxSZXF1ZXN0MTk2OTI4ODc= | 8,008 | Add sharex and sharey to grouped boxplot | {
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... | 5 | 2014-08-12T21:59:27Z | 2015-05-09T21:24:25Z | 2015-05-09T16:20:05Z | CONTRIBUTOR | null | sharex and sharey should be settable and by default False in a grouped boxplot. E.g.
```
n [97]: df = DataFrame(np.random.rand(10,2), columns=['Col1', 'Col2'] )
In [98]: df['X'] =['A','A','A','A','A','B','B','B','B','B']
In [99]: df.iloc[0:5, :2] += 10000
In [100]: df.groupby('X').boxplot() # this is unreadable
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] | closed | false | null | [] | null | 12 | 2014-08-12T22:30:21Z | 2014-08-13T20:26:01Z | 2014-08-13T12:43:39Z | NONE | null | I posted this on StackOverflow as a [question](http://stackoverflow.com/questions/25275009/pandas-series-filter-values-returning-different-type-than-numpy-array), but I think it may be a bug in Pandas.
These two expressions return something slightly different:
```
df.filter(regex='other').iloc[0].values
df.iloc[0].f... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8010 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8010/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8010/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8010/events | https://github.com/pandas-dev/pandas/pull/8010 | 40,109,965 | MDExOlB1bGxSZXF1ZXN0MTk2OTY5ODQ= | 8,010 | fix issue #8000 | {
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... | [] | closed | false | null | [] | null | 1 | 2014-08-12T23:31:03Z | 2014-08-13T13:57:02Z | 2014-08-13T02:04:55Z | CONTRIBUTOR | null | This pull request is in response to [issue #8000](https://github.com/pydata/pandas/issues/8000).
Changes to core/common.py add np.nan as the default value for missing values to the left and right non-missing values during interpolation. This prevents DataFrame.interpolate() from extrapolating the last non-missing val... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8011 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8011/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8011/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8011/events | https://github.com/pandas-dev/pandas/issues/8011 | 40,111,563 | MDU6SXNzdWU0MDExMTU2Mw== | 8,011 | ExcelFile.parse() does not return TextFileReader object, but rather a DataFrame | {
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... | 3 | 2014-08-12T23:59:27Z | 2020-05-07T22:11:35Z | 2020-05-07T22:11:34Z | NONE | null | When specifying a chunksize during the ExcelFile.parse() method, I should be back an iterable object, but instead a DataFrame is returned.
If you return just the TextParser (change parser.read() to just parser) in the code block below, then iterating over the parsed ExcelFile works and returns the specified number of... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8012 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8012/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8012/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8012/events | https://github.com/pandas-dev/pandas/pull/8012 | 40,114,612 | MDExOlB1bGxSZXF1ZXN0MTk2OTk4OTI= | 8,012 | WIP: generalize categorical to N-dimensions | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8013 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8013/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8013/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8013/events | https://github.com/pandas-dev/pandas/pull/8013 | 40,117,239 | MDExOlB1bGxSZXF1ZXN0MTk3MDE0NDI= | 8,013 | fix issue #8000 - interpolation extrapolates over trailing missing values | {
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... | 9 | 2014-08-13T02:04:24Z | 2016-04-04T23:57:50Z | 2015-07-28T21:56:26Z | CONTRIBUTOR | null | This pull request is in response to [issue #8000](https://github.com/pydata/pandas/issues/8000).
Changes to core/common.py add np.nan as the default value for missing values to the left and right non-missing values during interpolation. This prevents DataFrame.interpolate() from extrapolating the last non-missing valu... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8014 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8014/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8014/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8014/events | https://github.com/pandas-dev/pandas/issues/8014 | 40,121,564 | MDU6SXNzdWU0MDEyMTU2NA== | 8,014 | Iterating through TableIterator with where clause can incorrectly ignore data | {
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The attached code generates appendable ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8015 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8015/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8015/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8015/events | https://github.com/pandas-dev/pandas/issues/8015 | 40,138,305 | MDU6SXNzdWU0MDEzODMwNQ== | 8,015 | pd.Series.groupby is said to have only optional parameters | {
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s = pd.Series(x)
m = s.groupby().count() # does not work
m = s.groupby(s.values).count() # works
```
In `https://github.com/pydata/pandas/blob/master/pandas/core/generic.py`, `by=None` should be corrected to just `by` as `None` always leads to an error.
```
def groupby(self, by=None, axis=0, level=None, as_ind... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8016 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8016/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8016/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8016/events | https://github.com/pandas-dev/pandas/issues/8016 | 40,148,476 | MDU6SXNzdWU0MDE0ODQ3Ng== | 8,016 | Inconsistent assingment when indexing with mixed type | {
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] | closed | false | null | [] | null | 3 | 2014-08-13T12:15:38Z | 2014-08-13T12:25:52Z | 2014-08-13T12:25:36Z | NONE | null | When I run the following code:
``` python
import pandas as pd
import numpy as np
dfe=pd.Series(np.array([ 0, 0, 0]),index=[1,2, '3'])
df=pd.Series([2],index=[1])
print dfe.loc[df.index]
print dfe.loc[df.index] + df.loc[df.index]
dfe.loc[df.index] = dfe.loc[df.index] + df.loc[df.index]
print dfe
```
I get the followi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8017 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8017/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8017/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8017/events | https://github.com/pandas-dev/pandas/issues/8017 | 40,155,400 | MDU6SXNzdWU0MDE1NTQwMA== | 8,017 | BUG: sort_index/sortlevel fails MultiIndex after columns are added. | {
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- [x] fix `FIXME`s
- [x] Split to `plot_seriesgroupby` and `plot_dataramegroupby` specifying defa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8019 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8019/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8019/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8019/events | https://github.com/pandas-dev/pandas/issues/8019 | 40,170,576 | MDU6SXNzdWU0MDE3MDU3Ng== | 8,019 | Can't shift an empty dataframe with pandas 0.14.1 and numpy 1.7.1 | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-08-13T16:08:29Z | 2017-02-06T18:23:52Z | 2014-08-18T15:38:09Z | CONTRIBUTOR | null | We have some code which filters a dataframe, then shifts the result. However, this dataframe may end up being empty. In pandas 0.13, this works without problem:
```
In [61]: df = DataFrame(columns=['foo'])
In [62]: df.shift(-1)
Out[62]:
Empty DataFrame
Columns: [foo]
Index: []
[0 rows x 1 columns]
```
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https://api.github.com/repos/pandas-dev/pandas/issues/8020 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8020/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8020/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8020/events | https://github.com/pandas-dev/pandas/issues/8020 | 40,170,784 | MDU6SXNzdWU0MDE3MDc4NA== | 8,020 | Make empty data construction error message less dev-y | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-08-13T16:10:22Z | 2016-02-27T14:46:28Z | 2016-02-27T14:46:28Z | MEMBER | null | When one tries to construct a `DataFrame` where the data column count and the passed in column count differ the error message is completely unintuitive unless you know something about the internal representation of the data inside of `NDFrame`s.
I think we should at the very least make the dimensions in the error mess... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8021 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8021/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8021/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8021/events | https://github.com/pandas-dev/pandas/issues/8021 | 40,187,931 | MDU6SXNzdWU0MDE4NzkzMQ== | 8,021 | Bug in generate CREATE TABLE SQL for DataFrame with MultiIndex with different types | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-08-13T19:06:19Z | 2014-08-15T22:40:58Z | 2014-08-15T22:40:58Z | CONTRIBUTOR | null | When using SQLAlchemy to create a table from a dataframe, Pandas messes up the types of the index columns. For example:
``` python
import sqlalchemy
engine = sqlalchemy.create_engine('sqlite:///:memory:')
import pandas as pd
from pandas.io.sql import PandasSQLTable, PandasSQLAlchemy
df = pd.DataFrame.from_records([{... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8022 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8022/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8022/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8022/events | https://github.com/pandas-dev/pandas/pull/8022 | 40,233,201 | MDExOlB1bGxSZXF1ZXN0MTk3NzQxNjQ= | 8,022 | Fixed incorrect datatype conversion on multi-indexes | {
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"followers_url": "https://api.github.com/users/jr... | 12 | 2014-08-14T08:32:13Z | 2014-08-20T20:23:36Z | 2014-08-15T22:40:58Z | CONTRIBUTOR | null | When creating a new table from a `pandas` dataframe with a multi-index, the code would iterate over the index columns backwards but use their types as if counting forwards. This meant that the created table had incorrect indexes for multi-indexes.
This code factors out a function to pull column names and column types... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8023 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8023/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8023/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8023/events | https://github.com/pandas-dev/pandas/issues/8023 | 40,234,806 | MDU6SXNzdWU0MDIzNDgwNg== | 8,023 | harmonize the testing namespace with tm.TestCase | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2014-08-14T08:55:53Z | 2014-12-01T00:08:05Z | 2014-12-01T00:08:05Z | CONTRIBUTOR | null | Currently these two have different places to look for the relevant equality tests: `TestCase` has `assert_numpy_array_equivalent` and `assert_numpy_array_equal` but the testing module has `assert_frame_equal` and `assert_series_equal`.
It would be nice if all substantial code is available form the testing module and `... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8024 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8024/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8024/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8024/events | https://github.com/pandas-dev/pandas/issues/8024 | 40,241,998 | MDU6SXNzdWU0MDI0MTk5OA== | 8,024 | Regression in series.map? | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2014-08-14T10:34:40Z | 2014-08-14T19:43:06Z | 2014-08-14T13:08:19Z | CONTRIBUTOR | null | ```
import pandas
from statsmodels import datasets
# load the data and clean it a bit
affairs = datasets.fair.load_pandas()
datas = affairs.exog
# any time greater than 0 is cheating
datas['cheated'] = affairs.endog > 0
# sort by the marriage quality and give meaningful name
# [rate_marriage, age, yrs_married, childr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8025 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8025/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8025/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8025/events | https://github.com/pandas-dev/pandas/issues/8025 | 40,245,510 | MDU6SXNzdWU0MDI0NTUxMA== | 8,025 | API: Timestamp.tz_convert/tz_localize raises Exception, should be TypeError | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-08-14T11:30:26Z | 2014-08-16T16:56:02Z | 2014-08-16T16:56:02Z | MEMBER | null | `Timestamp` raises normal `Exception` in case of error, and we have to catch `Exception` for error handling.
Expect `TypeError` in consistent with `DatetimeIndex`.
```
pd.Timestamp('2011-01-01').tz_convert('US/Eastern')
# Exception: Cannot convert tz-naive Timestamp, use tz_localize to localize
pd.DatetimeIndex(['20... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8026 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8026/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8026/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8026/events | https://github.com/pandas-dev/pandas/pull/8026 | 40,246,684 | MDExOlB1bGxSZXF1ZXN0MTk3ODI1MjI= | 8,026 | BUG: related to GH5080, get_indexer choking on boolean type promotion (GH8024) | {
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#### NG: Each areas are drawn with `alpha=1.0`, but legend has `alpha=0.5`
#### After fix
```
df = pd.DataFrame(n... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8028 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8028/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8028/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8028/events | https://github.com/pandas-dev/pandas/issues/8028 | 40,247,707 | MDU6SXNzdWU0MDI0NzcwNw== | 8,028 | ENH/API: Allow get_dummies to specify return value | {
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... | 2 | 2014-08-14T12:07:32Z | 2016-05-07T09:57:38Z | 2016-05-07T09:57:38Z | MEMBER | null | Currently `get_dummies` always returns dummy values with `0` or `1`. When we want others, have to use `replace`, `apply...` etc (and it is not easy in some cases because column name can differs depending on target value).
```
s = pd.Series(['A', 'A', 'B', 'C'])
pd.get_dummies(s)
# A B C
#0 1 0 0
#1 1 0 0
#... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8029 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8029/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8029/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8029/events | https://github.com/pandas-dev/pandas/pull/8029 | 40,259,809 | MDExOlB1bGxSZXF1ZXN0MTk3OTA5Nzg= | 8,029 | BUG: fix HDFStore iterator to handle a where properly (GH8014) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8030 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8030/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8030/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8030/events | https://github.com/pandas-dev/pandas/pull/8030 | 40,279,796 | MDExOlB1bGxSZXF1ZXN0MTk4MDMwNDE= | 8,030 | BUG: fix py3 read_html bytes input | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8031 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8031/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8031/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8031/events | https://github.com/pandas-dev/pandas/issues/8031 | 40,316,011 | MDU6SXNzdWU0MDMxNjAxMQ== | 8,031 | read_msgpack compress kwarg not getting passed | {
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"gists... | [] | closed | false | null | [] | null | 1 | 2014-08-15T01:24:05Z | 2014-08-15T11:45:50Z | 2014-08-15T11:45:45Z | NONE | null | The compress kwarg isn't getting passed down the chain when using pd.read_msgpack(buffer).
```
def read_msgpack(path_or_buf, iterator=False, **kwargs):
...
def read(fh):
l = list(unpack(fh)) (which then goes to decode() and unconvert() )
```
Replication:
```
df = pd.DataFrame([{'foo','bar'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8032 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8032/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8032/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8032/events | https://github.com/pandas-dev/pandas/issues/8032 | 40,318,571 | MDU6SXNzdWU0MDMxODU3MQ== | 8,032 | test_fred fails in latest release | {
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``` python
FAIL: test_fred (pandas.io.tests.test_data.TestFred)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/mnt/gen2/TmpDir/portage/dev-python/pandas-0.14.1/work/pandas-0.14.1-python2_7/lib/pandas/util/testing.py", line 1346, in w... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8033 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8033/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8033/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8033/events | https://github.com/pandas-dev/pandas/issues/8033 | 40,318,676 | MDU6SXNzdWU0MDMxODY3Ng== | 8,033 | build issues re -Wimplicit-function-declaration | {
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] | closed | false | null | [] | null | 2 | 2014-08-15T02:37:54Z | 2014-08-15T12:24:28Z | 2014-08-15T11:46:32Z | NONE | null | portage repeats and lists warnings for convenience at the end of an install
``` python
>>> Completed installing pandas-0.14.1 into /mnt/gen2/TmpDir/portage/dev-python/pandas-0.14.1/image/
strip: x86_64-pc-linux-gnu-strip --strip-unneeded -R .comment -R .GCC.command.line -R .note.gnu.gold-version
usr/lib64/python2.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8034 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8034/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8034/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8034/events | https://github.com/pandas-dev/pandas/pull/8034 | 40,332,420 | MDExOlB1bGxSZXF1ZXN0MTk4MzQ1NTk= | 8,034 | DOC: suppress warning + fix reshape example | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8035 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8035/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8035/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8035/events | https://github.com/pandas-dev/pandas/pull/8035 | 40,346,962 | MDExOlB1bGxSZXF1ZXN0MTk4NDM0NDQ= | 8,035 | DOC: Fixing 'chunksize' parameter name typo io.rst | {
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... | closed | false | null | [] | null | 1 | 2014-08-15T13:19:00Z | 2014-08-15T13:20:50Z | 2014-08-15T13:20:18Z | CONTRIBUTOR | null | Fixing an error in the 'chunksize' parameter name for the io doc. With the typo (parameter called 'chunsize'), the sample code from the documentation fails silently / confusingly - returns an iterator over individual dataframe elements rather than dataframe chunks.
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https://api.github.com/repos/pandas-dev/pandas/issues/8036 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8036/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8036/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8036/events | https://github.com/pandas-dev/pandas/pull/8036 | 40,349,101 | MDExOlB1bGxSZXF1ZXN0MTk4NDQ3Njc= | 8,036 | API: Timetamp.tz_localize and tz_convert raises TypeError rathar | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8037 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8037/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8037/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8037/events | https://github.com/pandas-dev/pandas/pull/8037 | 40,349,489 | MDExOlB1bGxSZXF1ZXN0MTk4NDQ5OTY= | 8,037 | DOC/CLN: Cleanups plotting.py | {
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- Made `DataFrame.plot` and `Series.plot` should have consistent docstring except differences.
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https://api.github.com/repos/pandas-dev/pandas/issues/8038 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8038/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8038/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8038/events | https://github.com/pandas-dev/pandas/issues/8038 | 40,354,001 | MDU6SXNzdWU0MDM1NDAwMQ== | 8,038 | ERR: Index.shift() gives confusing error message when no DatetimeIndex | {
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"closed_at": "2015-11-21T13:47:07Z",
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In [1]: idx = pd.Index(range(5))
In [2]: idx
Out[2]: Int64Index([0, 1, 2, 3, 4], dtype='int64')
In [3]: idx.shift(1)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-3-d8362983dbf7> in <module>()
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https://api.github.com/repos/pandas-dev/pandas/issues/8039 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8039/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8039/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8039/events | https://github.com/pandas-dev/pandas/issues/8039 | 40,361,024 | MDU6SXNzdWU0MDM2MTAyNA== | 8,039 | Stacking MultiIndex DataFrame columns with Timestamps levels fails | {
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```
import pandas as pd
import datetime as dt
key = pd.MultiIndex.from_tuples([(
dt.datetime(2014,8,1,0,0,0),
'SomeColumnName',
'AnotherOne')])
data = {
'1' : 34204,
'2' : 43580,
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https://api.github.com/repos/pandas-dev/pandas/issues/8040 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8040/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8040/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8040/events | https://github.com/pandas-dev/pandas/issues/8040 | 40,363,018 | MDU6SXNzdWU0MDM2MzAxOA== | 8,040 | Pandas 0.14.1 StataReader seems to read .dta files 10x slower than Pandas 0.13.1 | {
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I would really like to use the newer version of... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8041 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8041/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8041/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8041/events | https://github.com/pandas-dev/pandas/pull/8041 | 40,366,198 | MDExOlB1bGxSZXF1ZXN0MTk4NTU2MTk= | 8,041 | BUG: Don't call np.roll on empty arrays. | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2014-08-15T17:16:33Z | 2014-08-18T18:20:52Z | 2014-08-18T15:38:09Z | CONTRIBUTOR | null | On some versions of numpy (such as 1.7, but not 1.8), this throws a
ZeroDivisionError.
Fixes #8019.
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https://api.github.com/repos/pandas-dev/pandas/issues/8043 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8043/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8043/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8043/events | https://github.com/pandas-dev/pandas/pull/8043 | 40,390,582 | MDExOlB1bGxSZXF1ZXN0MTk4NzA2OTA= | 8,043 | BUG: stack with datetimes | {
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The only change I made was to select from the MultiIndex itself, rather than the underlying `.values` attribute. The test set passed but I want to look at this a bit more closely to make sure everything is ok.
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This was fixed in a previous PR, but these checks had previously been
implemented on a value-by-value basis. This has now been changed to a
vectorized version that is orders of magnitude faster.
Additionally, a benchmark was added to monitor... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8046 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8046/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8046/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8046/events | https://github.com/pandas-dev/pandas/issues/8046 | 40,425,369 | MDU6SXNzdWU0MDQyNTM2OQ== | 8,046 | GroupBy.transform bug/API change | {
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A _Python for Data Analysis_ reader noted the following issue with recent versions of pandas (as of 1 year ago):
```
import pandas as pd
from pandas import DataFrame
import numpy as np
def demean(arr):
return arr - arr.mean()
people = DataFrame(np.random.randn(5, 5),
columns=['a', 'b', 'c', 'd', 'e'],... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8047 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8047/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8047/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8047/events | https://github.com/pandas-dev/pandas/pull/8047 | 40,429,978 | MDExOlB1bGxSZXF1ZXN0MTk4ODc3NjM= | 8,047 | Update README to use pydata instead of pystatsmodels google group | {
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http://pandas.pydata.org/community.html
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https://api.github.com/repos/pandas-dev/pandas/issues/8048 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8048/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8048/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8048/events | https://github.com/pandas-dev/pandas/issues/8048 | 40,431,266 | MDU6SXNzdWU0MDQzMTI2Ng== | 8,048 | pandas MultiIndex series "unstack" to scipy sparse array functionality | {
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I have found myself on occasion writing code to convert from a pandas Series (with n-level MultiIndex) to a scipy sparse n-dim array (plus dimension labels) and back. I am not terribly familiar with the newer sparse data structure features but my impression is that it provides a totally different kind of... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8049 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8049/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8049/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8049/events | https://github.com/pandas-dev/pandas/pull/8049 | 40,444,716 | MDExOlB1bGxSZXF1ZXN0MTk4OTM5NTE= | 8,049 | BUG: Bug in DataFrameGroupby.transform when transforming with a passed non-sorted key (GH8046) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8050 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8050/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8050/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8050/events | https://github.com/pandas-dev/pandas/issues/8050 | 40,452,861 | MDU6SXNzdWU0MDQ1Mjg2MQ== | 8,050 | Error with reading/writing a lot of large hdf5 files | {
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] | closed | false | null | [] | null | 4 | 2014-08-18T03:36:29Z | 2015-03-08T17:00:51Z | 2015-03-08T17:00:51Z | NONE | null | I am using pandas to read/write a lot of relatively large hdf5 files (hundreds MB each), hundreds of them, using HDFStore. My app acts as a service and I am facing seg faults after it runs for some time. It seems that it seg fault after some random HDF error occurs. I am able to cause some HDF errors by repeatedly read... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8051 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8051/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8051/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8051/events | https://github.com/pandas-dev/pandas/issues/8051 | 40,458,377 | MDU6SXNzdWU0MDQ1ODM3Nw== | 8,051 | C files in source distribution | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8052 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8052/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8052/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8052/events | https://github.com/pandas-dev/pandas/issues/8052 | 40,484,017 | MDU6SXNzdWU0MDQ4NDAxNw== | 8,052 | TST: Invalid table option table parsing | {
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cc @dstephens99
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Other tests have no problem with MPL1.4.dev:
- tests\test_graphics.py
- tseries\tests\test_plotting.py
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https://api.github.com/repos/pandas-dev/pandas/issues/8055 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8055/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8055/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8055/events | https://github.com/pandas-dev/pandas/issues/8055 | 40,502,857 | MDU6SXNzdWU0MDUwMjg1Nw== | 8,055 | read_csv segfault with file open in LibreOffice | {
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"descriptio... | closed | false | null | [] | null | 9 | 2014-08-18T15:53:43Z | 2020-04-04T03:34:10Z | 2020-04-04T03:34:10Z | CONTRIBUTOR | null | I'm trying to read a simple file which works fine when I don't have the file open. However, when I have the file open in LibreOffice it reliably segfaults (memory steadily increases and network traffic is at 70MB/s for a good 30 seconds). When open in the TextEditor it works fine.
csv data:
ID,Start Date,End Date
1... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8056 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8056/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8056/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8056/events | https://github.com/pandas-dev/pandas/issues/8056 | 40,503,476 | MDU6SXNzdWU0MDUwMzQ3Ng== | 8,056 | BUG: rolling_count() and expanding_*() return error for empty Series | {
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```
In [1]: from pandas import Series, rolling_count, expanding_count, expanding_mean
In [2]: expanding_count(Series([]))
---------------------------------------------------------------------------
ValueError ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8057 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8057/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8057/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8057/events | https://github.com/pandas-dev/pandas/issues/8057 | 40,504,532 | MDU6SXNzdWU0MDUwNDUzMg== | 8,057 | broken 0.14.1 download link | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8058 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8058/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8058/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8058/events | https://github.com/pandas-dev/pandas/issues/8058 | 40,509,260 | MDU6SXNzdWU0MDUwOTI2MA== | 8,058 | Timestamp cannot be compared to np.int64: impact on series binary operations | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2014-08-18T17:01:11Z | 2014-08-19T15:12:53Z | 2014-08-19T15:12:53Z | CONTRIBUTOR | null | Binary operations between two series fail if the .name attribute of the first is a Timestamp and the .name of the second is a numpy.int64.
It seems a corner case, but it's pretty common when the series are slices of dataframes.
It happens independently if, say, + or .add() is used.
It doesn't happen if the order is rev... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8059 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8059/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8059/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8059/events | https://github.com/pandas-dev/pandas/pull/8059 | 40,509,453 | MDExOlB1bGxSZXF1ZXN0MTk5MzA2NjE= | 8,059 | BUG: rolling_count() and expanding_*() with zero-length args; rolling/expanding_apply with min_periods=0 | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2014-08-18T17:03:26Z | 2014-09-10T00:11:40Z | 2014-08-28T17:34:49Z | CONTRIBUTOR | null | Closes https://github.com/pydata/pandas/issues/8056
Closes https://github.com/pydata/pandas/issues/8080
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https://api.github.com/repos/pandas-dev/pandas/issues/8060 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8060/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8060/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8060/events | https://github.com/pandas-dev/pandas/issues/8060 | 40,514,286 | MDU6SXNzdWU0MDUxNDI4Ng== | 8,060 | Is the storage cost of fixed-format vs. tabular HDF documented? | {
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"color": "005... | closed | false | null | [] | null | 3 | 2014-08-18T17:58:26Z | 2014-10-02T12:26:12Z | 2014-10-02T12:26:12Z | CONTRIBUTOR | null | I discovered that `store.put('key', df)` takes a whopping 40X more storage than `store('key', df, format='table')` for my DataFrames of floats. (See soft-matter/trackpy#144 for one demonstration.)
1. Am I doing it wrong? Is cost difference really that high?
2. I see that the read/write speed differences (which favor fi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8061 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8061/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8061/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8061/events | https://github.com/pandas-dev/pandas/pull/8061 | 40,517,494 | MDExOlB1bGxSZXF1ZXN0MTk5MzU3MjQ= | 8,061 | ENH: improve datetime string parsing with CustomBusinessDay | {
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] | closed | false | null | [] | null | 6 | 2014-08-18T18:32:43Z | 2015-04-08T17:19:04Z | 2015-04-08T15:21:33Z | CONTRIBUTOR | null | Currently CustomBusinessDay requires a strict format for holiday definition
```
CustomBusinessDay(holidays=['2014-05-12'])
```
but the following would raise a ValueError:
```
CustomBusinessDay(holidays=['5/12/2014'])
```
this PR makes the date parsing easier and adds a unit test
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https://api.github.com/repos/pandas-dev/pandas/issues/8062 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8062/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8062/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8062/events | https://github.com/pandas-dev/pandas/pull/8062 | 40,529,316 | MDExOlB1bGxSZXF1ZXN0MTk5NDMwNjA= | 8,062 | Added chunksize argument to to_sql | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2014-08-18T20:37:40Z | 2014-09-15T21:49:48Z | 2014-08-22T07:32:12Z | CONTRIBUTOR | null | Large dataframes may fail to write to a database in one go due to packet size errors . This add a `chunksize` parameter which will write the dataframe to the database in batches. See https://github.com/pydata/pandas/issues/7347 .
Notice that there is quite a bit of code duplication between the SQLAlchemy and legacy ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8063 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8063/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8063/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8063/events | https://github.com/pandas-dev/pandas/pull/8063 | 40,532,357 | MDExOlB1bGxSZXF1ZXN0MTk5NDQ5ODI= | 8,063 | Adding a warning when dropping NA values for panel.to_frame #7879 | {
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I've added a warning when the <code>NaN</code> values are dropped when calling <code>pd.Panel(dict).to_frame()</code> with the param <code>filter_observations</code> true
I've supplied a test case to be used against the example provided in the issue tracker
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https://api.github.com/repos/pandas-dev/pandas/issues/8064 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8064/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8064/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8064/events | https://github.com/pandas-dev/pandas/issues/8064 | 40,538,742 | MDU6SXNzdWU0MDUzODc0Mg== | 8,064 | API: expanding/rolling_std/var/cov and ddof | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-08-18T22:17:28Z | 2014-09-17T18:03:54Z | 2014-09-17T18:03:54Z | CONTRIBUTOR | null | Though it's not mentioned in the doc strings, `expanding/rolling_std/var` support a `ddof` parameter, while `expanding/rolling_cov` do not (they effectively assume `ddof=1`).
I think it would be best if all these functions supported an explicit (i.e. documented) `ddof` parameter that defaults to `1`.
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https://api.github.com/repos/pandas-dev/pandas/issues/8065 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8065/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8065/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8065/events | https://github.com/pandas-dev/pandas/issues/8065 | 40,541,423 | MDU6SXNzdWU0MDU0MTQyMw== | 8,065 | BUG/ENH: categorical returned during a transform | {
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"followers_url": "https://api.github.com/users/jorisva... | 10 | 2014-08-18T22:55:38Z | 2018-07-06T22:58:28Z | 2018-07-06T22:58:12Z | CONTRIBUTOR | null | http://stackoverflow.com/questions/25372877/python-pandas-groupby-and-qcut-doesnt-work-in-0-14-1
```
df = pd.DataFrame({'x': np.random.rand(20), 'grp': ['a'] * 10 + ['b'] * 10})
```
worked in 0.13 (but returns a 2 element series with a list)
```
df.groupby('grp')['x'].transform(pd.qcut, 3)
```
much cleaner.
```
df... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8066 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8066/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8066/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8066/events | https://github.com/pandas-dev/pandas/pull/8066 | 40,570,366 | MDExOlB1bGxSZXF1ZXN0MTk5Njc1Njk= | 8,066 | Fix bdist_wheel. Add Tag information to WHEEL dist info. | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-08-19T08:55:56Z | 2014-09-14T15:19:01Z | 2014-09-14T14:13:25Z | CONTRIBUTOR | null | The wheel build with https://github.com/MacPython/pandas-wheels
```
# file: pandas-0.14.1.dist-info/WHEEL
Wheel-Version: 1.0
Generator: bdist_wheel (0.24.0)
Root-Is-Purelib: false
Tag: cp27-none-macosx_10_6_intel
```
Although it was renamed to `macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64`, the real
tag did... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8067 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8067/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8067/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8067/events | https://github.com/pandas-dev/pandas/pull/8067 | 40,588,868 | MDExOlB1bGxSZXF1ZXN0MTk5Nzg4MTM= | 8,067 | typo: "cubhelix" -> "cubehelix" | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8068 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8068/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8068/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8068/events | https://github.com/pandas-dev/pandas/pull/8068 | 40,591,080 | MDExOlB1bGxSZXF1ZXN0MTk5ODAyMTY= | 8,068 | DOC: Fix Release note 8019, 8039 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8069 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8069/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8069/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8069/events | https://github.com/pandas-dev/pandas/pull/8069 | 40,595,101 | MDExOlB1bGxSZXF1ZXN0MTk5ODI1MTM= | 8,069 | DOC: Add scatter to visualization.rst | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8070 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8070/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8070/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8070/events | https://github.com/pandas-dev/pandas/pull/8070 | 40,595,743 | MDExOlB1bGxSZXF1ZXN0MTk5ODI5NTI= | 8,070 | BUG: Bug in Timestamp comparisons with == and dtype of int64 (GH8058) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8071 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8071/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8071/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8071/events | https://github.com/pandas-dev/pandas/issues/8071 | 40,599,089 | MDU6SXNzdWU0MDU5OTA4OQ== | 8,071 | API: Accept negative value for layout keyword in plot | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-08-19T14:47:28Z | 2014-09-18T17:16:32Z | 2014-09-18T17:16:32Z | CONTRIBUTOR | null | Once https://github.com/pydata/pandas/pull/7736 is merged, we can add this option
```
df.plot(subplots=True, layout=(4, -1)
```
This will behave similar to numpy's `reshape` method, except that we won't require the number of subplots generated by layout to exactly match the number of subplots in `df`. We'll just fill... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8072 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8072/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8072/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8072/events | https://github.com/pandas-dev/pandas/issues/8072 | 40,599,346 | MDU6SXNzdWU0MDU5OTM0Ng== | 8,072 | BUG: improve error message for negative window argument to rolling_*() | {
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... | 3 | 2014-08-19T14:50:00Z | 2017-06-10T21:59:33Z | 2017-06-10T21:59:33Z | CONTRIBUTOR | null | Currently (in v0.14.1) `rolling_mean(s, window=-1)` produces (the somewhat inelegant) error message `ValueError: min_periods must be >= 0`. It would be better to test explicitly for negative (non-positive?) `window`, and produce a more direct error message.
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https://api.github.com/repos/pandas-dev/pandas/issues/8073 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8073/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8073/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8073/events | https://github.com/pandas-dev/pandas/pull/8073 | 40,605,756 | MDExOlB1bGxSZXF1ZXN0MTk5ODkzODI= | 8,073 | PERF: StataReader is slow | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2014-08-19T15:49:29Z | 2014-08-22T15:42:25Z | 2014-08-20T10:52:34Z | CONTRIBUTOR | null | StataReader does not make use of vectorized operations.
To improve performance, the following changes have been made:
- Use numpy.frombuffer to real the stored data in a single operation
- Vectorize date conversion
- Removal of unreachable private functions
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https://api.github.com/repos/pandas-dev/pandas/issues/8074 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8074/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8074/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8074/events | https://github.com/pandas-dev/pandas/issues/8074 | 40,647,912 | MDU6SXNzdWU0MDY0NzkxMg== | 8,074 | Discussion: feedback on the Categorical integration | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8075 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8075/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8075/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8075/events | https://github.com/pandas-dev/pandas/pull/8075 | 40,651,587 | MDExOlB1bGxSZXF1ZXN0MjAwMTgxNzQ= | 8,075 | ENH: add support dtype='category' in Series constructor | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2014-08-20T00:13:51Z | 2014-08-21T21:33:10Z | 2014-08-21T21:33:10Z | CONTRIBUTOR | null | xref #8074
closes #8076
```
In [1]: Series([1,1,2,2,3,4,5],dtype='category')
Out[1]:
0 1
1 1
2 2
3 2
4 3
5 4
6 5
dtype: category
Levels (5, int64): [1 < 2 < 3 < 4 < 5]
```
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https://api.github.com/repos/pandas-dev/pandas/issues/8076 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8076/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8076/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8076/events | https://github.com/pandas-dev/pandas/issues/8076 | 40,670,549 | MDU6SXNzdWU0MDY3MDU0OQ== | 8,076 | BUG: Putting a Categorical series in a DataFrame with a different index raises IndexError | {
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... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-08-20T07:35:05Z | 2014-08-21T21:33:10Z | 2014-08-21T21:33:10Z | MEMBER | null | ```
>>> import pandas as pd
>>> pd.DataFrame({'x': pd.Series(['a', 'b', 'c'])}, index=pd.date_range('20000101', periods=3))
x
2000-01-01 NaN
2000-01-02 NaN
2000-01-03 NaN
>>> df = pd.DataFrame({'x': pd.Series(pd.Categorical(['a', 'b', 'c']))}, index=pd.date_range('20000101', periods=3))
>>> df
<repr(<p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8077 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8077/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8077/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8077/events | https://github.com/pandas-dev/pandas/issues/8077 | 40,671,317 | MDU6SXNzdWU0MDY3MTMxNw== | 8,077 | API: update pd.cut with the new categorical integration | {
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"followers_url": "https://api.github.com/users/jr... | 19 | 2014-08-20T07:47:55Z | 2014-09-29T13:04:23Z | 2014-09-25T22:16:08Z | MEMBER | null | xref #8074. Some issues about `pd.cut/qcut` (http://pandas.pydata.org/pandas-docs/stable/generated/pandas.cut.html#pandas.cut):
- If the input is a Series, also return a Series?
- The produced categorical is not ordered, while the `Categorical` constructor is by default. Also in the case of `cut` it seems logical that... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8078 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8078/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8078/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8078/events | https://github.com/pandas-dev/pandas/issues/8078 | 40,700,501 | MDU6SXNzdWU0MDcwMDUwMQ== | 8,078 | Second Categorical fixups | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-08-20T13:54:44Z | 2014-09-28T11:10:48Z | 2014-09-25T22:17:05Z | CONTRIBUTOR | null | Docs:
- [x] `np.asarray(s2.cat)` -> `np.asarray(s2)`
- [x] `Series(.....dtype='categorical')` example, #8075
- [x] Add docstring about internal useage to to_dense and from_array
- [x] go through the docs and change levels -> categories
- [x] clarify docs on usage of `Categorical` (public API restricted to creation (t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8079 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8079/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8079/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8079/events | https://github.com/pandas-dev/pandas/pull/8079 | 40,710,457 | MDExOlB1bGxSZXF1ZXN0MjAwNTIzOTU= | 8,079 | PERF: StataWriter is slow | {
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"followers_url": "https://api.github.com/users/jr... | 12 | 2014-08-20T15:27:40Z | 2014-08-22T15:42:17Z | 2014-08-21T14:26:34Z | CONTRIBUTOR | null | StataWriter wrote data using scalar operations. This has been replaced using
numpy's internal binary writer (tofile).
Changes needed to improve performance include:
- Vectorized pandas date to Stata date conversion
- Vectorized null padding
- Conversion to record array
When data contain strings, the old writing path... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8080 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8080/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8080/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8080/events | https://github.com/pandas-dev/pandas/issues/8080 | 40,722,297 | MDU6SXNzdWU0MDcyMjI5Nw== | 8,080 | BUG: expanding/rolling_apply() interpret min_periods=0 as min_periods=1 | {
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For example, I think that in the following calls, the results should be `1, 2, 2` ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8081 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8081/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8081/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8081/events | https://github.com/pandas-dev/pandas/issues/8081 | 40,723,326 | MDU6SXNzdWU0MDcyMzMyNg== | 8,081 | BUG: scatter plot with error bars broken on master | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-08-20T17:33:54Z | 2014-09-05T16:16:34Z | 2014-09-05T16:16:34Z | MEMBER | null | This example works on 0.14.1 but not master:
```
%matplotlib inline
import numpy as np
import pandas as pd
np.random.seed(12345)
df = pd.DataFrame(np.random.rand(10, 5), columns=['a', 'b', 'c', 'd', 'e'])
df.plot(x='a', y='b', xerr='c', yerr='d', kind='scatter')
```
I get:
```
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https://api.github.com/repos/pandas-dev/pandas/issues/8082 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8082/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8082/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8082/events | https://github.com/pandas-dev/pandas/issues/8082 | 40,737,171 | MDU6SXNzdWU0MDczNzE3MQ== | 8,082 | 'labels' as a DataFrame column name in version 0.14.1 | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-08-20T19:46:36Z | 2014-09-13T22:47:12Z | 2014-09-13T22:47:12Z | CONTRIBUTOR | null | I'm not sure if this qualifies as a bug, but it is a change that occurred between 0.13.1 and 0.14.1. In 0.14.1, if I have a DataFrame with a column named 'labels', I get the following error when trying to access it as an attribute of the DataFrame:
```
>>> df = pandas.DataFrame(columns=['labels'])
>>> df['labels']
Ser... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8083 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8083/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8083/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8083/events | https://github.com/pandas-dev/pandas/pull/8083 | 40,740,531 | MDExOlB1bGxSZXF1ZXN0MjAwNzExOTk= | 8,083 | BUG: When creating table, db indexes should be created from DataFrame indexes | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8084 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8084/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8084/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8084/events | https://github.com/pandas-dev/pandas/issues/8084 | 40,757,269 | MDU6SXNzdWU0MDc1NzI2OQ== | 8,084 | BUG: expanding/rolling_quantile() inconsistent with Series.quantile() | {
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... | 4 | 2014-08-20T23:36:45Z | 2017-05-03T10:11:25Z | 2017-05-03T10:11:18Z | CONTRIBUTOR | null | It appears that `Series.quantile()` interpolates between the two bracketing values, whereas `expanding/rolling_quantile()` don't.
```
In [496]: x = Series([0,1])
In [497]: x.quantile(0.3)
Out[497]: 0.29999999999999999
In [498]: expanding_quantile(x, 0.3)
Out[498]:
0 0
1 0
dtype: float64
In [499]: rolling_quan... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8085 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8085/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8085/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8085/events | https://github.com/pandas-dev/pandas/pull/8085 | 40,760,514 | MDExOlB1bGxSZXF1ZXN0MjAwODM0NzM= | 8,085 | CLN: PEP8 cleanup of holiday.py | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8086 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8086/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8086/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8086/events | https://github.com/pandas-dev/pandas/issues/8086 | 40,763,951 | MDU6SXNzdWU0MDc2Mzk1MQ== | 8,086 | BUG: expanding/rolling_skew/kurt() inconsistent with Series.skew/kurt() | {
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```
In [532]: s = Series([1]*4)
In [533]: s.skew()
Out[533]: 0
In [534]: expanding_skew(s)
Out[534]:
0 NaN
1 NaN
2 NaN
3 NaN
dtype: float64
In [535]: rolling_skew(s, 4)
Out[535]:
0 NaN
1 NaN
2 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8087 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8087/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8087/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8087/events | https://github.com/pandas-dev/pandas/issues/8087 | 40,774,390 | MDU6SXNzdWU0MDc3NDM5MA== | 8,087 | Problem writing to SQL db with DataFrame column names as numbers | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2014-08-21T05:42:51Z | 2014-08-21T08:08:31Z | 2014-08-21T08:07:28Z | CONTRIBUTOR | null | Example:
``` python
import numpy as np
import pandas as pd
from sqlalchemy import create_engine
engine = create_engine('mssql+pyodbc://localhost\\sqlexpress/test')
x1 = pd.DataFrame(np.random.rand(5,3))
x2 = pd.DataFrame(np.random.rand(5,3), columns=['0', '1', '2'])
x1.to_sql('x1', con=engine)
x2.to_sql('x2', con=e... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8088 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8088/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8088/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8088/events | https://github.com/pandas-dev/pandas/issues/8088 | 40,782,513 | MDU6SXNzdWU0MDc4MjUxMw== | 8,088 | Write Null values to mssql table | {
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Referencing https://github.com/pydata/pandas/issues/4199
Example:
``` python
import numpy as np
import pandas as pd
from sqlalchemy import create_engine
pg_engine = create_engine('postgresql://postgres:*pass*@localhost:5432/t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8089 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8089/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8089/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8089/events | https://github.com/pandas-dev/pandas/issues/8089 | 40,809,534 | MDU6SXNzdWU0MDgwOTUzNA== | 8,089 | TST: yahoo test fails | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8090 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8090/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8090/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8090/events | https://github.com/pandas-dev/pandas/pull/8090 | 40,893,577 | MDExOlB1bGxSZXF1ZXN0MjAxNjE3MjQ= | 8,090 | ENH: add support for datetime.date/time in to_sql (GH6932) | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2014-08-22T09:41:46Z | 2014-08-28T07:06:21Z | 2014-08-28T07:03:43Z | MEMBER | null | Closes #6932
Support for writing `datetime.date` and `datetime.time` object columns with `to_sql`.
Works nicely for the sqlalchemy mode, for sqlite fallback it writes OK for `datetime.date`, but comes back as object strings (this is also the case for datetime)
Remaining question:
- when reading the data back in `TIM... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8091 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8091/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8091/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8091/events | https://github.com/pandas-dev/pandas/issues/8091 | 40,902,779 | MDU6SXNzdWU0MDkwMjc3OQ== | 8,091 | TST: failing box plot tests on windows | {
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```
======================================================================
ERROR: test_boxplot (pandas.tests.test_graphics.TestDataFrameGroupByPlots)
----------------------------------------------------------------------
Traceback (most recent call last):
File "c:\Users\Jeff Reba... | {
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``` python
In [0]: import pandas as pd
In [1]: s = pd.Series([1,2,3], index = [0.1,0.2,0.3])
In [2]: s.at[0.1]
---------------------------------------------------------------------------
AttributeError Traceback (most recent... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8093 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8093/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8093/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8093/events | https://github.com/pandas-dev/pandas/issues/8093 | 40,908,429 | MDU6SXNzdWU0MDkwODQyOQ== | 8,093 | BUG: Group-by on an empty data object dtype loses the index name (cython aggregation is ok) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8095 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8095/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8095/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8095/events | https://github.com/pandas-dev/pandas/issues/8095 | 40,912,321 | MDU6SXNzdWU0MDkxMjMyMQ== | 8,095 | pandas 0.14.1 Excel Writer with 'excelwriter' engine cannot create a 2nd sheet | {
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Python 2.7, Windows 7
``` python
>>> import pandas as pd
>>> print(pd.__version__)
0.14.1
>>> df=pd.DataFrame({'a': [1,2,3], 'b':[4,5,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8096 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8096/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8096/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8096/events | https://github.com/pandas-dev/pandas/issues/8096 | 40,938,337 | MDU6SXNzdWU0MDkzODMzNw== | 8,096 | pandas.io.data doesn't work with hyphenated ticker names | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2014-08-22T18:47:30Z | 2015-03-08T17:01:20Z | 2015-03-08T17:01:11Z | NONE | null | Noticed that the pandas.io.data doesn't return the Data Frame on tickers having a '-' in the ticker name , for example: HINDUNILVR-EQ.NS, TATA-MOTORS.NS .
Any ideas ?
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https://api.github.com/repos/pandas-dev/pandas/issues/8097 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8097/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8097/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8097/events | https://github.com/pandas-dev/pandas/issues/8097 | 40,944,013 | MDU6SXNzdWU0MDk0NDAxMw== | 8,097 | SQL: issues with get_schema | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-08-22T19:50:23Z | 2014-09-15T21:43:01Z | 2014-09-15T21:43:01Z | MEMBER | null | - using `get_schema` in sqlalchemy mode (providing an engine) does also create the table, while just getting the create table string should not have any effects.
- the `get_schema` implementation for fallback duplicates a lot of code of `PandasSQLTableLegacy._create_table_statement`
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https://api.github.com/repos/pandas-dev/pandas/issues/8098 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8098/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8098/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8098/events | https://github.com/pandas-dev/pandas/pull/8098 | 40,965,371 | MDExOlB1bGxSZXF1ZXN0MjAyMDU2NDQ= | 8,098 | TST: Fix boxplot test for python3 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8099 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8099/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8099/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8099/events | https://github.com/pandas-dev/pandas/pull/8099 | 40,965,422 | MDExOlB1bGxSZXF1ZXN0MjAyMDU2NjQ= | 8,099 | TST: Fix timezone test to avoit dateutil issue | {
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