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https://api.github.com/repos/pandas-dev/pandas/issues/9903 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9903/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9903/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9903/events | https://github.com/pandas-dev/pandas/issues/9903 | 68,553,237 | MDU6SXNzdWU2ODU1MzIzNw== | 9,903 | Calling shift on a DatetimeIndex of length 0 returns an Index instead of a DatetimeIndex | {
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```
In [5]: pandas.__version__
Out[5]: '0.16.0-151-gcef3c85'
In [7]: DatetimeIndex([]).shift(3, 'H')
Out[7]: Index([], dtype='object')
```
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https://api.github.com/repos/pandas-dev/pandas/issues/9904 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9904/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9904/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9904/events | https://github.com/pandas-dev/pandas/pull/9904 | 68,566,892 | MDExOlB1bGxSZXF1ZXN0MzMzMjEwNDI= | 9,904 | DatetimeIndex 0 length shift (GH9903) | {
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Fixes a bug where calling shift on an empty DatetimeIndex would result in the returned value being an Index rather than a DatetimeIndex.
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https://api.github.com/repos/pandas-dev/pandas/issues/9905 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9905/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9905/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9905/events | https://github.com/pandas-dev/pandas/issues/9905 | 68,672,112 | MDU6SXNzdWU2ODY3MjExMg== | 9,905 | BUG: barplot with log=True not working for values smaller than 1 | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-15T12:44:27Z | 2015-04-16T18:55:42Z | 2015-04-16T18:55:42Z | MEMBER | null | ```
s = pd.Series([0.1, 0.01, 0.001], index=['a', 'b', 'c'])
s.plot(kind='bar', log=True)
```
gives:
```
TypeError Traceback (most recent call last)
<ipython-input-13-75b989d29042> in <module>()
1 s = pd.Series([0.1, 0.01, 0.001], index=['a', 'b', 'c'])
----> 2 s.plot(kind='bar',... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9906 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9906/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9906/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9906/events | https://github.com/pandas-dev/pandas/pull/9906 | 68,714,153 | MDExOlB1bGxSZXF1ZXN0MzMzNjY3Mzg= | 9,906 | Fix of the docs for tz_conver and tz_localize (fix for #9865) | {
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Docs for `tz_convert` and `tz_localize` were updated and "Raises" section were added.
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https://api.github.com/repos/pandas-dev/pandas/issues/9907 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9907/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9907/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9907/events | https://github.com/pandas-dev/pandas/issues/9907 | 68,733,491 | MDU6SXNzdWU2ODczMzQ5MQ== | 9,907 | DatetimeIndex behaves inconsistently when start and end have different precisions | {
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``` python
>>>pd.__version__
0.15.2-318-g549b72f
>>>pd.DatetimeIndex(start='2015-04-15 00:00:03', end='2016-04-22 00:00:04', freq='Q')
2015-06-30 00:00:03
2015-09-30... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9908 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9908/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9908/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9908/events | https://github.com/pandas-dev/pandas/pull/9908 | 68,759,434 | MDExOlB1bGxSZXF1ZXN0MzMzODQxNzQ= | 9,908 | Fixed latex output for multi-indexed dataframes - GH9778 | {
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"followers_url": "https://api.github.com/users/jr... | 10 | 2015-04-15T18:44:18Z | 2015-07-23T11:02:22Z | 2015-04-16T06:14:38Z | CONTRIBUTOR | null | Proposed fix for https://github.com/pydata/pandas/issues/9778
The formatting issue was caused by an incorrect number of elements in the (first) index columns of `strcols`. The length of reinserted columns was based on the number of elements per index level, but should have relied on the number of rows/occurrences of s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9909 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9909/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9909/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9909/events | https://github.com/pandas-dev/pandas/issues/9909 | 68,774,618 | MDU6SXNzdWU2ODc3NDYxOA== | 9,909 | pandas scatter plot: Secondary axis overrides primary | {
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... | 3 | 2015-04-15T20:03:12Z | 2021-04-18T06:25:30Z | null | NONE | null | When a second scatter plot is added as ''secondary_y'', the outcome is that the primary is overridden.
``` python
import matplotlib.pyplot as plt
import pandas as pd,numpy as np
# secondary axis does not work on scatter plot
x=pd.Series(np.linspace(-10,10,201))
y,z=np.sin(x),np.cos(x)
df=pd.concat([x,np.sin(x),np.cos... | {
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"followers_url": "https://api.github.com/users/jr... | 12 | 2015-04-15T20:57:31Z | 2015-04-21T21:45:58Z | 2015-04-21T00:58:16Z | CONTRIBUTOR | null | @jreback this PR makes it easier to add/delete items from `__dir__`. The `.str/.dt/.cat` are now only present in `__dir__` when they are appropriate types.
However, the IPython tab completion does not seem to only source the list from `__dir__`, and therefore even if an item is removed from `__dir__` it is still showi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9911 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9911/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9911/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9911/events | https://github.com/pandas-dev/pandas/pull/9911 | 68,786,245 | MDExOlB1bGxSZXF1ZXN0MzMzOTYxMTM= | 9,911 | DOC: add redirects to ensure old links instead of building the docstring page | {
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(The reason I care about this is that googling eg `read_csv` still oft... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9912 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9912/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9912/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9912/events | https://github.com/pandas-dev/pandas/issues/9912 | 68,821,168 | MDU6SXNzdWU2ODgyMTE2OA== | 9,912 | Column name 'class' causes access and query issues | {
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"color": "00... | closed | false | null | [] | null | 3 | 2015-04-16T01:12:52Z | 2015-04-16T01:20:25Z | 2015-04-16T01:20:25Z | NONE | null | For some reason pandas isn't liking when I create a column named class and attempt to access with .{columnname} method
I also cannot run a query on the dataframe.
Code:
``` python
>>> a = pandas.DataFrame({'class':[0], 'clas1': [1]})
>>> a.clas1
0 1
Name: clas1, dtype: int64
>>> a.class
File "<stdin>", line 1
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9913 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9913/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9913/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9913/events | https://github.com/pandas-dev/pandas/issues/9913 | 68,934,259 | MDU6SXNzdWU2ODkzNDI1OQ== | 9,913 | Passing a list to level param of unstack() unexpectedly changes dtype from numeric to object | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2015-04-16T14:19:31Z | 2017-07-31T15:12:21Z | 2017-07-31T15:12:10Z | NONE | null | I experience these strange behavior of `unstack()` when its `level` parameter gets a list instead of string.
This changes `dtype` of some columns from numeric to object, which is obviously a worrying change.
I am wondering if this a bug or there is something I am missing about dealing with this.
I am on pandas 0.16.0, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9914 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9914/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9914/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9914/events | https://github.com/pandas-dev/pandas/pull/9914 | 68,941,732 | MDExOlB1bGxSZXF1ZXN0MzM0NTkwMTQ= | 9,914 | BUG: barplot with log=True not working for values smaller than 1 | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-16T14:55:15Z | 2015-04-18T10:43:50Z | 2015-04-16T18:55:42Z | MEMBER | null | Closes #9905. Also include a fix that `log` kw is ignored in horizontal bar plot. Test cases are based on standard mpl result:
```
plt.bar([0, 1, 2], [0.1, 0.01, 0.001], log=True)
plt.gca().get_ylim()
# (0.001, 0.10000000000000001)
plt.gca().yaxis.get_ticklocs()
# [ 1.00000000e-04 1.00000000e-03 1.00000000e-02 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9915 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9915/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9915/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9915/events | https://github.com/pandas-dev/pandas/issues/9915 | 68,972,930 | MDU6SXNzdWU2ODk3MjkzMA== | 9,915 | Resampling produces all NaN values for a particular dataset | {
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``` python
>>> import pandas; from pandas import Timestamp
>>> data1 = pandas.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9916 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9916/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9916/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9916/events | https://github.com/pandas-dev/pandas/pull/9916 | 68,985,177 | MDExOlB1bGxSZXF1ZXN0MzM0ODAxOTQ= | 9,916 | ENH: Remove Unnecessary Conditional | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9917 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9917/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9917/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9917/events | https://github.com/pandas-dev/pandas/pull/9917 | 69,023,311 | MDExOlB1bGxSZXF1ZXN0MzM0OTk1NTU= | 9,917 | Add time_format argument to ExcelWriter. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9918 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9918/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9918/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9918/events | https://github.com/pandas-dev/pandas/issues/9918 | 69,024,608 | MDU6SXNzdWU2OTAyNDYwOA== | 9,918 | uint64 multicolumn sort | {
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``` python
>>> import pandas as pd
>>> import numpy as np
>>> df = pd.DataFrame({'a': pd.Series([18446637057563306014, 1162265347240853609]), 'b': pd.Series([1, 2])})
>>> df['a'] = df['a'].astype(np.uint64)
>>> df.sort(['a', 'b'])['a']
0 18446637... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9919 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9919/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9919/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9919/events | https://github.com/pandas-dev/pandas/issues/9919 | 69,033,150 | MDU6SXNzdWU2OTAzMzE1MA== | 9,919 | Series don't plot in nbagg while dataframe.plot() call works | {
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http://nbviewer.ipython.org/gist/michaelaye/4af80037146dfb65b105
Not sure if I should have submitted it here or with matplotlib. Just let me know, then I can open one there.
Output of pd.show_versions():
## INSTALLED VERSIONS
commit: None
python: 3.4.3.final.0
python-bits: 64
OS: Linux
OS-release... | {
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... | open | false | null | [] | null | 1 | 2015-04-17T00:00:15Z | 2015-04-17T17:25:41Z | null | CONTRIBUTOR | null | Bug shown at the end of this:
http://nbviewer.ipython.org/gist/michaelaye/4af80037146dfb65b105
Output of pd.show__versions():
## INSTALLED VERSIONS
commit: None
python: 3.4.3.final.0
python-bits: 64
OS: Linux
OS-release: 2.6.32-431.11.2.el6.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG:... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9921 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9921/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9921/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9921/events | https://github.com/pandas-dev/pandas/issues/9921 | 69,160,002 | MDU6SXNzdWU2OTE2MDAwMg== | 9,921 | groupby transform misbehaving with categoricals | {
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```
>>> df = pd.DataFrame({"a": [5,15,25]})
>>> c = pd.cut(df.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9922 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9922/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9922/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9922/events | https://github.com/pandas-dev/pandas/pull/9922 | 69,181,424 | MDExOlB1bGxSZXF1ZXN0MzM1NjUwNDY= | 9,922 | TST: adding sdist and install tests to the 2.6 regression - closes #9878 | {
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This PR adds a test for packaging and installing pandas from a tarball, inside of the 2.6 regression.
After regular nosetests complete, cython is removed from the venv, pandas is packaged with cdist command, and the package is installed via pip. Limited nosetests run once installed.
The travis log outp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9923 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9923/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9923/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9923/events | https://github.com/pandas-dev/pandas/pull/9923 | 69,196,926 | MDExOlB1bGxSZXF1ZXN0MzM1NzIyMTI= | 9,923 | Added grouby apply notebook | {
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Its meant to help document the behavior in issue 9867: It's difficult to predict what DataFrame.groupby().apply() will return
https://github.com/pydata/pandas/issues/9867
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https://api.github.com/repos/pandas-dev/pandas/issues/9924 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9924/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9924/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9924/events | https://github.com/pandas-dev/pandas/pull/9924 | 69,214,467 | MDExOlB1bGxSZXF1ZXN0MzM1ODA3NjQ= | 9,924 | BUG: need better inference for path in Series construction (GH9456) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9925 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9925/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9925/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9925/events | https://github.com/pandas-dev/pandas/issues/9925 | 69,246,724 | MDU6SXNzdWU2OTI0NjcyNA== | 9,925 | BUG: GroupBy.size doesn't attach index name properly if grouped by TimeGrouper | {
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import numpy as np
import pandas as pd
import datetime
df = pd.DataFrame({'A': [1, 1, 1, 2, 2, 2], 'B': [1, 2, 3, 4, 5, 6]})
grouped = df.groupby('A')
n = 20
data = np.random.randn(n, 4)
dt_df = pd.DataFrame(data, columns=['A', 'B', 'C', 'D'])
dt_df['key'] = [datetime.datetime(2013, 1, 1), datetime.datetime(2013,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9926 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9926/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9926/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9926/events | https://github.com/pandas-dev/pandas/issues/9926 | 69,247,223 | MDU6SXNzdWU2OTI0NzIyMw== | 9,926 | BUG: index name lost with timedelta ops | {
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"followers_url": "https://api.github.... | 4 | 2015-04-18T00:36:11Z | 2015-06-02T19:25:19Z | 2015-05-18T11:59:45Z | MEMBER | null | ```
import pandas as pd
dtidx = pd.DatetimeIndex(['2011-01-01'], freq='D', name='dtidx')
(dtidx + 1).name
# dtidx
# NG
(dtidx + pd.Timedelta('1 day')).name
# None
tdidx = pd.TimedeltaIndex(['1 day'], freq='D', name='tdidx')
(tdidx + 1).name
# tdidx
# NG
(tdidx + pd.Timedelta('1 day')).name
# None
```
ref: #9862
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https://api.github.com/repos/pandas-dev/pandas/issues/9927 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9927/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9927/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9927/events | https://github.com/pandas-dev/pandas/issues/9927 | 69,258,884 | MDU6SXNzdWU2OTI1ODg4NA== | 9,927 | API/BUG: awkward syntax to add categories to a Categorical | {
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- the `.add_categories` should be able to take an `Index`/ndarray, ATM it must be converted to a list
- should be a keyword for something like: add any additional categories that I am passing to you (even if the cur... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9928 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9928/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9928/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9928/events | https://github.com/pandas-dev/pandas/issues/9928 | 69,262,465 | MDU6SXNzdWU2OTI2MjQ2NQ== | 9,928 | Pandas gives 600 line long ValueError while runing sklearn GridSearchCV | {
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```
rfc = RandomForestClassifier(random_state=1)
tuned_parameters = [{'max_features': ['sqrt', 'log2'],
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https://api.github.com/repos/pandas-dev/pandas/issues/9929 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9929/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9929/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9929/events | https://github.com/pandas-dev/pandas/pull/9929 | 69,278,048 | MDExOlB1bGxSZXF1ZXN0MzM1OTc5MjE= | 9,929 | Allow add_categories() to accept Series/np.array and make raising on dup... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9930 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9930/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9930/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9930/events | https://github.com/pandas-dev/pandas/issues/9930 | 69,318,583 | MDU6SXNzdWU2OTMxODU4Mw== | 9,930 | read_excel with sheetname=None or sheetname=[0,1,”Sheet5”] should preserve sheets order | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-04-18T15:23:16Z | 2016-11-11T13:02:04Z | 2016-11-11T10:00:32Z | CONTRIBUTOR | null | Hello,
I noticed in http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_excel.html#pandas.read_excel
that `read_excel` can have a parameter `sheetname`set to `None` or a to a `list`
In such a case a dictionary of `DataFrame` is returned.
Maybe it should output an `OrderedDict` of `DataFrame` to preserv... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9931 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9931/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9931/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9931/events | https://github.com/pandas-dev/pandas/pull/9931 | 69,319,831 | MDExOlB1bGxSZXF1ZXN0MzM2MDM3OTI= | 9,931 | Update README.md | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9932 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9932/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9932/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9932/events | https://github.com/pandas-dev/pandas/issues/9932 | 69,319,900 | MDU6SXNzdWU2OTMxOTkwMA== | 9,932 | Travis build status badge is not clickable in README.md | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9933 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9933/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9933/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9933/events | https://github.com/pandas-dev/pandas/pull/9933 | 69,320,629 | MDExOlB1bGxSZXF1ZXN0MzM2MDM4OTM= | 9,933 | Update excel.py to output OrderedDict instead of dict | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9934 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9934/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9934/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9934/events | https://github.com/pandas-dev/pandas/pull/9934 | 69,329,157 | MDExOlB1bGxSZXF1ZXN0MzM2MDU0OTM= | 9,934 | BUG: Exception when setting an empty range using DataFrame.loc | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9935 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9935/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9935/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9935/events | https://github.com/pandas-dev/pandas/pull/9935 | 69,342,476 | MDExOlB1bGxSZXF1ZXN0MzM2MDc4MDY= | 9,935 | add support for quandl historical financial data | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-18T19:57:34Z | 2015-04-19T18:52:22Z | 2015-04-19T18:51:08Z | NONE | null | | Q | A |
| --- | --- |
| Bug fix? | no |
| New feature? | yes |
| BC breaks? | no |
| Deprecations? | no |
| Tests pass? | yes |
| Fixed tickets | - |
| License | BSD |
| Doc PR | - |
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https://api.github.com/repos/pandas-dev/pandas/issues/9936 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9936/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9936/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9936/events | https://github.com/pandas-dev/pandas/pull/9936 | 69,347,002 | MDExOlB1bGxSZXF1ZXN0MzM2MDg2NzQ= | 9,936 | BUG: GroupBy.size doesnt attach index name properly if grouped by TimeGr... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-18T20:56:54Z | 2015-04-22T13:55:10Z | 2015-04-20T11:08:51Z | MEMBER | null | Closes #9925
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https://api.github.com/repos/pandas-dev/pandas/issues/9937 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9937/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9937/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9937/events | https://github.com/pandas-dev/pandas/issues/9937 | 69,370,427 | MDU6SXNzdWU2OTM3MDQyNw== | 9,937 | pd.merge for outer with empty dataframe on the left side results in merged dataframe with the key column not being first | {
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I am new to Pandas and like it a lot. I noticed that while doing an outer merge if the dataframe on the left side is empty, then the key column in the merged dataframe is not the first.
First the summary and then my code, print output, and pd.show_versions is included below. Consider 2 dataframes left and right.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9938 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9938/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9938/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9938/events | https://github.com/pandas-dev/pandas/pull/9938 | 69,410,633 | MDExOlB1bGxSZXF1ZXN0MzM2MTY3ODk= | 9,938 | DOC: Link to recipe for SafeHDF5Store | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9939 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9939/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9939/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9939/events | https://github.com/pandas-dev/pandas/pull/9939 | 69,451,293 | MDExOlB1bGxSZXF1ZXN0MzM2MjMzMTM= | 9,939 | BUG: DataFrame constructor fails when columns is set and data=[] | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-04-19T18:27:44Z | 2015-04-28T23:16:52Z | 2015-04-28T12:16:00Z | CONTRIBUTOR | null | From this StackOverflow question: http://stackoverflow.com/questions/29730488/setting-columns-for-an-empty-pandas-dataframe
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https://api.github.com/repos/pandas-dev/pandas/issues/9940 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9940/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9940/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9940/events | https://github.com/pandas-dev/pandas/pull/9940 | 69,451,664 | MDExOlB1bGxSZXF1ZXN0MzM2MjMzNTY= | 9,940 | PERF: improve perf of writing csv's with datetimes | {
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-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
frame_to_csv_mixed | 107.7774 | 668.5090 | 0.16... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9941 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9941/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9941/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9941/events | https://github.com/pandas-dev/pandas/issues/9941 | 69,466,373 | MDU6SXNzdWU2OTQ2NjM3Mw== | 9,941 | groupby/transform with NaNs in grouped column | {
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... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-19T21:24:18Z | 2016-12-18T20:24:12Z | 2016-12-18T20:24:12Z | CONTRIBUTOR | null | What's the expected behavior when grouping on a column containing `NaN` and then applying `transform`? For a `Series`, the current result is to throw an exception:
```
>>> df = pd.DataFrame({
... 'a' : range(10),
... 'b' : [1, 1, 2, 3, np.nan, 4, 4, 5, 5, 5]})
>>>
>>> df.groupby(df.b)['a'].transform(max)
Trac... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9942 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9942/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9942/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9942/events | https://github.com/pandas-dev/pandas/pull/9942 | 69,469,683 | MDExOlB1bGxSZXF1ZXN0MzM2MjcwMDk= | 9,942 | various windows test / dtype fixes | {
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xref #9845
xref #9804
xref #9802
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https://api.github.com/repos/pandas-dev/pandas/issues/9943 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9943/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9943/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9943/events | https://github.com/pandas-dev/pandas/issues/9943 | 69,496,397 | MDU6SXNzdWU2OTQ5NjM5Nw== | 9,943 | BUG: index name lost when indexing with another index | {
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... | 8 | 2015-04-20T03:15:12Z | 2021-04-18T06:31:58Z | 2021-04-18T06:31:58Z | NONE | null | Very subtle. Index name stays when using .ix [ list ], but gets lost when using .ix[ Int64Index ].
```
import pandas as pd
from pandas.util.testing import assert_frame_equal
import numpy as np
assert pd.__version__ == '0.16.0'
df = pd.DataFrame([np.nan, np.nan], columns = ['tags'], index=pd.Int64Index([4815961, 48159... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9944 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9944/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9944/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9944/events | https://github.com/pandas-dev/pandas/pull/9944 | 69,502,971 | MDExOlB1bGxSZXF1ZXN0MzM2MzQ3MjE= | 9,944 | ENH: return an OrderedDict from read_excel with sheetname=None/list #9930 | {
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... | 13 | 2015-04-20T04:20:38Z | 2015-05-10T14:20:54Z | 2015-05-10T14:20:54Z | CONTRIBUTOR | null | Fix https://github.com/pydata/pandas/issues/9930
read_excel with sheetname=None or sheetname=[0,1,”Sheet5”] returns an OrderedDict instead of a dict
Follow-up of #9933
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https://api.github.com/repos/pandas-dev/pandas/issues/9945 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9945/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9945/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9945/events | https://github.com/pandas-dev/pandas/issues/9945 | 69,513,676 | MDU6SXNzdWU2OTUxMzY3Ng== | 9,945 | groupby().transform(f) is very slow if there are assignment statements to the argument of f() | {
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... | 3 | 2015-04-20T05:54:25Z | 2021-04-16T04:35:38Z | 2021-04-16T04:35:29Z | NONE | null | Here is the test code:
```
import pandas as pd
from numpy.random import randint, rand, seed
seed(10)
N_Group = 20
N_Rows = 1000
df = pd.DataFrame({"g":randint(0, N_Group, N_Rows), "a":rand(N_Rows), "b":rand(N_Rows)})
def f(df):
df["a"] -= df["b"].mean()
return df
%time df1 = df.groupby("g").apply(f)
%time d... | {
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... | closed | false | null | [] | null | 5 | 2015-04-20T06:46:32Z | 2018-07-07T20:15:35Z | 2018-07-07T20:15:27Z | NONE | null | ```
df = pd.DataFrame({"g":[1, 2, 2, 2], "a":[1, 2, 3, 4], "b":[5, 6, 7, 8]})
df.groupby("g").apply(lambda x:x.copy())
```
raise
```
ValueError: Shape of passed values is (3, 4), indices imply (3, 2)
```
but `lambda x:x` or `lambda x:x[:]` works.
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"followers_url": "https://api.github.com/users/jr... | 26 | 2015-04-20T07:55:40Z | 2015-07-17T14:02:03Z | 2015-07-16T08:32:48Z | CONTRIBUTOR | null | currently on `master` (after the PR https://github.com/pydata/pandas/issues/9785), we have the following behavior when comparing two Indexes with `==`:
```
In [3]: index_a = Index(['a', 'b', 'c'])
In [4]: index_b = Index(['a', 'b', 'c', 'd'])
In [5]: index_a == index_b
Out[5]: False
```
Firstly, `==` should be elemen... | {
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"de... | closed | false | null | [] | null | 4 | 2015-04-20T08:34:32Z | 2015-04-20T10:58:44Z | 2015-04-20T10:58:38Z | CONTRIBUTOR | null | The following fails:
```
pd.DataFrame([], columns="a b".split())
```
I'd expect this to be equivalent to
```
pd.DataFrame(None, columns="a b".split())
```
Is there any reason not to do it like this?
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https://api.github.com/repos/pandas-dev/pandas/issues/9949 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9949/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9949/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9949/events | https://github.com/pandas-dev/pandas/issues/9949 | 69,548,241 | MDU6SXNzdWU2OTU0ODI0MQ== | 9,949 | Avoidable memory error when dealing with large column assignments | {
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] | closed | false | null | [] | null | 2 | 2015-04-20T09:37:31Z | 2019-10-02T07:34:03Z | 2015-04-20T10:38:42Z | NONE | null | When dealing with data sizes at the limit of the machine, pandas produces a memory error when one tries to assign a numpy array to a equally typed and sized pandas column. `__setitem__()` seems to force an unnecessary copy since assigning directly to the array backing the block is possible:
```
In [1]: import numpy as... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9950 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9950/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9950/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9950/events | https://github.com/pandas-dev/pandas/issues/9950 | 69,551,304 | MDU6SXNzdWU2OTU1MTMwNA== | 9,950 | pandas give a warning when working with np.NaN values | {
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"color": "006b7... | closed | false | null | [] | {
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Example:
```
>>> import pandas as pd, numpy as np
>>> pd.Series([np.nan,np.nan,np.nan],index=[1,2,3])
1 NaN
2 NaN
3 NaN
dtype: float64
C:\Users\domen\Anaconda\lib\site-packages\pandas\core\format.py:1995: Runtim... | {
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"de... | closed | false | null | [] | null | 1 | 2015-04-20T10:17:49Z | 2015-04-20T10:45:54Z | 2015-04-20T10:45:34Z | NONE | null | Whilst answering this [SO question](http://stackoverflow.com/questions/29706825/pandas-version-0-16-0-after-changing-dataframe-index-all-values-become-nan) I discovered that the DataFrame constructor is ignoring the fact that I'm passing an index explicitly resulting in a df with all NaNs:
```
In [6]:
df = pd.DataFram... | {
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This is not very informative in this case.
```
In [11]: df = pd.DataFrame({'a':np... | {
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"gi... | [] | closed | false | null | [] | null | 0 | 2015-04-20T12:26:18Z | 2017-04-05T02:06:24Z | 2015-04-20T18:41:21Z | CONTRIBUTOR | null | Closes https://github.com/pydata/pandas/issues/9158
Fixes up a git mistake in https://github.com/pydata/pandas/pull/9164
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https://api.github.com/repos/pandas-dev/pandas/issues/9954 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9954/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9954/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9954/events | https://github.com/pandas-dev/pandas/pull/9954 | 69,615,432 | MDExOlB1bGxSZXF1ZXN0MzM2Nzc1MTY= | 9,954 | Spelling typo | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9956 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9956/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9956/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9956/events | https://github.com/pandas-dev/pandas/pull/9956 | 69,658,580 | MDExOlB1bGxSZXF1ZXN0MzM2OTYxMjI= | 9,956 | TST: adding sdist and install tests to the 2.6 regression - closes #9878 | {
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Adds a test for packaging and installing pandas from a tarball, inside of the 2.6 regression.
After regular nosetests complete, cython is removed from the venv, pandas is packaged with cdist command, and the package is installed via pip. Limited nosetests run once installed.
The output of this test in t... | {
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... | closed | false | null | [] | null | 2 | 2015-04-20T21:01:00Z | 2015-04-20T21:09:50Z | 2015-04-20T21:09:27Z | CONTRIBUTOR | null | I have an installation of Pandas of 0.16.0 that fails TestSeries.test_sum when using Numpy 1.9.2 compiled against MKL 11.2. Here is a minimal test:
```
import numpy as np
import pandas as pd
s = np.nan*pd.util.testing.makeStringSeries()
print s.sum()
```
For Pandas 0.15.2, Numpy 1.9.1 compiled against MKL 10.3, this... | {
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... | 11 | 2015-04-20T22:05:38Z | 2020-03-28T22:30:48Z | 2016-06-12T21:04:40Z | NONE | null | When I left-join two data frames on an int64 column, this column is cast to a float if it is the index of one of the two data frames:
``` python
>>> id = [1, 143349558619761320]
>>> a = pd.DataFrame({'a': [1, 2]}, index=pd.Int64Index(id, name='id'))
>>> b = pd.DataFrame({'id': id[1], 'b': [2]})
>>> merge_index = pd.me... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9959 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9959/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9959/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9959/events | https://github.com/pandas-dev/pandas/issues/9959 | 69,714,194 | MDU6SXNzdWU2OTcxNDE5NA== | 9,959 | columns selection after groupby reset group_keys to True | {
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... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/j... | 3 | 2015-04-21T00:56:18Z | 2020-08-31T22:31:08Z | 2020-08-31T22:31:08Z | NONE | null | ```
df = pd.DataFrame({"g":[1, 2, 1, 2, 1], "a":range(5), "b":range(1, 6), "c":range(2, 7)})
g = df.groupby("g", group_keys=False)
print g.group_keys #False
print g[["a", "b", "c"]].group_keys #True
```
So the `apply()` results are different for these two case:
```
print g.apply(lambda x:x[:2])
```
ouput:
```
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https://api.github.com/repos/pandas-dev/pandas/issues/9960 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9960/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9960/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9960/events | https://github.com/pandas-dev/pandas/issues/9960 | 69,772,211 | MDU6SXNzdWU2OTc3MjIxMQ== | 9,960 | Status of io.sql.get_schema as public function? | {
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... | 19 | 2015-04-21T07:51:09Z | 2021-04-18T06:37:56Z | null | MEMBER | null | At this moment, `pd.io.sql.get_schema` is not documented (not in the API docs, and not in the io docs). But, it is a potential useful function, so I think it would be good to be more explicit about its status (by mentioning it in the docs).
However, there are some quirks about the function:
- The signature: `pd.io.sql... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9961 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9961/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9961/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9961/events | https://github.com/pandas-dev/pandas/pull/9961 | 69,854,904 | MDExOlB1bGxSZXF1ZXN0MzM3NjQzMTM= | 9,961 | Introduction of RangeIndex | {
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This re-implementation is compatible with the current `Index()` api and is a drop-in replacement for `Int64Index()`. It automatically converts to Int64Index() when required by operations.
At present only for a minimum num... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9962 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9962/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9962/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9962/events | https://github.com/pandas-dev/pandas/issues/9962 | 69,872,461 | MDU6SXNzdWU2OTg3MjQ2MQ== | 9,962 | Docs: Add reference to pandaSDMX to the pandas Ecosystem page in the API section | {
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] | closed | false | null | [] | null | 6 | 2015-04-21T15:11:24Z | 2015-04-28T19:32:57Z | 2015-04-28T19:32:57Z | CONTRIBUTOR | null | I would be pleased if pandaSDMx (http://pandasdmx.readthedocs.org) could be added to the pandas Ecosystem directory. The following text is just a proposal, feel free to change it as you see fit:
"pandaSDMX is a libraryaimed at becoming the most intuitive and versatile tool to retrieve and acquire statistical data and ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9963 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9963/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9963/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9963/events | https://github.com/pandas-dev/pandas/issues/9963 | 69,883,834 | MDU6SXNzdWU2OTg4MzgzNA== | 9,963 | asfreq() issue with 'method' parameter | {
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"closed_at": "2016-10-03T08:52:13Z",
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-04-21T15:56:08Z | 2016-07-12T07:07:41Z | 2016-07-12T07:07:41Z | NONE | null | Hi all,
I've noticed the following behaviour in .asfreq method when dealing with frames/series containing original NaN values. When calling for instance asfreq('W-FRI',method='ffill') only NaN generated by DateOffset are forward filled, while the already present NaN values are not treated. I'm trying to figure out whe... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9964 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9964/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9964/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9964/events | https://github.com/pandas-dev/pandas/issues/9964 | 69,985,755 | MDU6SXNzdWU2OTk4NTc1NQ== | 9,964 | .loc and .iloc returns different dtypes on empty dataframe | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-04-22T00:23:43Z | 2015-04-30T10:04:04Z | 2015-04-30T10:04:04Z | CONTRIBUTOR | null | `.iloc` returns `object` dtype for a non-object empty series:
```
In [1]: import pandas as pd
In [2]: df = pd.DataFrame({'a':[1,2,3],'b':['b','b2','b3']})
In [3]: df.ix[[],:].loc[:,'a']
Out[3]: Series([], name: a, dtype: int64)
In [4]: df.ix[[],:].iloc[:,0]
Out[4]: Series([], name: a, dtype: object)
```
(came acros... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9965 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9965/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9965/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9965/events | https://github.com/pandas-dev/pandas/pull/9965 | 69,987,139 | MDExOlB1bGxSZXF1ZXN0MzM4MTY2ODU= | 9,965 | FIX: interesction and union changed index names. fixes #9943 partly #9862 | {
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"followers_url": "https://api.github.com/users/jr... | 16 | 2015-04-22T00:32:36Z | 2015-08-06T01:21:48Z | 2015-08-05T21:39:50Z | CONTRIBUTOR | null | had some time this morning and started working
closes #9943
for now I just uncommented the explicit setting to None of the index names.
let me know if I should remove it completely.
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https://api.github.com/repos/pandas-dev/pandas/issues/9966 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9966/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9966/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9966/events | https://github.com/pandas-dev/pandas/issues/9966 | 70,097,553 | MDU6SXNzdWU3MDA5NzU1Mw== | 9,966 | Int64Index with dtype=float and slicing issues | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-04-22T11:12:43Z | 2015-09-06T16:31:07Z | 2015-09-06T16:31:07Z | NONE | null | I have stumbled onto problems with slicing a pandas DataFrame when an index that originally contained integers has been manipulated such that it contains floats. Consider the following example (somewhat contrived to make it stand on its own; in practice, data are loaded from file):
```
df = pd.DataFrame({'i': np.linsp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9967 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9967/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9967/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9967/events | https://github.com/pandas-dev/pandas/issues/9967 | 70,127,113 | MDU6SXNzdWU3MDEyNzExMw== | 9,967 | MultiIndex copies don't have _id field set. | {
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"closed_at": "2017-05-06T10:20:19Z",
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-04-22T13:33:11Z | 2016-12-22T11:25:52Z | 2016-12-22T11:25:52Z | NONE | null | I have stumbled across a curious issue when working with `pandas.concat`.
Let's consider a simple example:
``` python
import pandas as pd
from copy import deepcopy
example_multiindex1 = pd.MultiIndex.from_product([['a'], ['b']])
example_dataframe1 = pd.DataFrame([0], index=example_multiindex1)
example_multiindex2 =... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9969 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9969/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9969/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9969/events | https://github.com/pandas-dev/pandas/issues/9969 | 70,182,826 | MDU6SXNzdWU3MDE4MjgyNg== | 9,969 | Poor read_csv performance on file with many columns | {
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... | 2 | 2015-04-22T17:11:48Z | 2015-04-24T00:43:43Z | null | NONE | null | A student came to me for help using PyData tools for processing data in many-column CSV files. The files have 2740 rows; the longer file has 50k columns of floats, the smaller has 2740 columns of 0/1 binary data (defining a graph).
She currently is using numpy.loadtxt to read the files; the float file takes ~10 - 15 m... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9970 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9970/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9970/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9970/events | https://github.com/pandas-dev/pandas/issues/9970 | 70,218,207 | MDU6SXNzdWU3MDIxODIwNw== | 9,970 | Value error on groupby bfill() | {
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s = pd.Series([1,1,0], index=[1,2,2])
s.groupby(s).fillna(method='bfill')
```
I have a dataframe with a column containing some strings and NaNs. I can do do `df.col.bfill()` but when I try to do `df.groupby('col2').col1.bfill()` I get a `ValueError`.
I can do `first` and `apply(lambda x: x is str)` without error.
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https://api.github.com/repos/pandas-dev/pandas/issues/9971 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9971/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9971/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9971/events | https://github.com/pandas-dev/pandas/issues/9971 | 70,248,336 | MDU6SXNzdWU3MDI0ODMzNg== | 9,971 | UnboundLocalError in pandas.io.data.get_data_yahoo | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2015-04-22T22:11:27Z | 2015-04-22T23:55:18Z | 2015-04-22T23:46:26Z | CONTRIBUTOR | null | ``` python
In [1]: %paste
import pandas.io.data as web
all_data = {}
for ticker in ['AAPL', 'GOOG', 'IBM', 'YHOO', 'MSFT']:
all_data[ticker] = web.get_data_yahoo(ticker, '1/1/2010', '1/1/2013')
price = pd.DataFrame({tic: data['Adj Close']
for tic, data in all_data.iteritems()})
## -- End past... | {
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- `assert_index_equal` (default=True).
- `assert_series_equal` (default=True). Maybe the same option can be used to check `Series.name` in the future, otherwise it may better to choose separate name such as `check_index_name`.
- `assert_paneln... | {
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Out[1]:
0 -inf
1 inf
dtype: float64
This appears to be resolved in 0.15, and 0.16 - so not sure that this is worth reporting
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https://api.github.com/repos/pandas-dev/pandas/issues/9975 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9975/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9975/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9975/events | https://github.com/pandas-dev/pandas/pull/9975 | 70,521,451 | MDExOlB1bGxSZXF1ZXN0MzQwMDAxMTc= | 9,975 | Series string operators | {
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``` python
In [1]: a = pd.Series(['%s', '%s'])
In [2]: a.str % 2
Out[2]: array(['2', '2'], dtype=object)
In [3]: a = pd.Series(['a', 'b'])
In [4]: a.str * 2
Out[4]: array(['aa', 'bb'], dtype=object)
In [5]: a.str + 'test'
Out[5]: array(['atest', 'btes... | {
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```
import pandas as pd
class MyDataFrame(pd.DataFrame):
@property
def my_attribute(self):
self.a_wrong_attribute
return 'Hello, World'
```
Applying it yield... | {
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... | 18 | 2015-04-24T11:21:15Z | 2015-12-30T15:39:31Z | 2015-12-30T15:39:31Z | NONE | null | closes #939
`RangeIndex(1, 10, 2)` is a memory saving alternative to `Index(np.arange(1, 10,2))`: c.f. #939.
This re-implementation is compatible with the current `Index()` api and is a drop-in replacement for `Int64Index()`. It automatically converts to Int64Index() when required by operations.
At present only for ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9978 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9978/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9978/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9978/events | https://github.com/pandas-dev/pandas/pull/9978 | 70,719,422 | MDExOlB1bGxSZXF1ZXN0MzQwNTg4Nzk= | 9,978 | Add override_header_style option to data_frame.to_excel() | {
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The Excel export (`data_frame.to_excel`) currently hard codes cell styles for all header frames. This pull request allows this style to be overridden by the user.
Don't override the default header style (Default)
`data_frame.to_excel(..... "override_header_style":None)`
Don't style the header at al... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9979 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9979/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9979/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9979/events | https://github.com/pandas-dev/pandas/issues/9979 | 70,732,257 | MDU6SXNzdWU3MDczMjI1Nw== | 9,979 | AttributeError: Cannot use pandas from a script file | {
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I am able to use the Pandas module from within the python console, but am unable to use it from within a script file. i.e. when I run a script that imports the pandas module, then I get an attribute error.
For example, this:
```
import pandas as pd
df = pd.Dat... | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-04-24T21:06:42Z | 2015-05-08T00:16:51Z | 2015-05-08T00:16:51Z | MEMBER | null | Follow-ups for #9667. Noticed 2 methods which can return `DataFrame`.
### 1. `Index.str.extract`
As shown in docstring, it returns `DataFrame` when the expression has 2 or more groups.
```
pd.Series(['a1', 'b2', 'c3']).str.extract('[ab](\d)')
#0 1
#1 2
#2 NaN
# dtype: object
pd.Series(['a1', 'b2', 'c3']... | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-04-24T21:23:21Z | 2015-04-25T07:38:35Z | 2015-04-25T07:34:47Z | CONTRIBUTOR | null | I noticed some of the HTML links are broken in `text.rst`
@sinhrks @jorisvandenbossche this is related to https://github.com/pydata/pandas/pull/9843 but can be independently merged
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... | 0 | 2015-04-24T21:47:13Z | 2015-04-24T21:47:26Z | null | MEMBER | null | It may be nice to have a doc like "Comparison with R / SQL"?
- https://databricks.com/blog/2015/02/17/introducing-dataframes-in-spark-for-large-scale-data-science.html
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Notice that `assert_frame_equal` now fails for empty dataframes with different dtypes (as, I think, it should). However, this means some tests need to be patched now.
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Also, fixed broken section name for subclass document.
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-04-25T18:55:33Z | 2015-04-25T23:31:42Z | 2015-04-25T21:44:41Z | CONTRIBUTOR | null | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9987 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9987/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9987/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9987/events | https://github.com/pandas-dev/pandas/pull/9987 | 70,964,986 | MDExOlB1bGxSZXF1ZXN0MzQxMTI3MzQ= | 9,987 | DOC: clean up / consistent imports (GH9886) | {
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] | closed | false | null | [] | null | 3 | 2015-04-25T20:41:47Z | 2015-05-05T10:37:24Z | 2015-05-05T10:37:24Z | MEMBER | null | Start for #9886
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https://api.github.com/repos/pandas-dev/pandas/issues/9988 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9988/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9988/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9988/events | https://github.com/pandas-dev/pandas/pull/9988 | 70,965,415 | MDExOlB1bGxSZXF1ZXN0MzQxMTI3ODc= | 9,988 | DOC: provide more links to API documentation where possible (GH3705) | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2015-04-25T20:45:37Z | 2015-05-02T19:08:45Z | 2015-05-02T19:08:45Z | MEMBER | null | Part 1: 10min and basics.rst
Addresses #3705 (for two files). I mainly replaced most ```method_name``` occurences with `:meth:`name``
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https://api.github.com/repos/pandas-dev/pandas/issues/9989 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9989/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9989/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9989/events | https://github.com/pandas-dev/pandas/issues/9989 | 70,976,302 | MDU6SXNzdWU3MDk3NjMwMg== | 9,989 | "Big-endian buffer not supported on little-endian compiler" when accessing multiple columns | {
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"c... | closed | false | null | [] | null | 1 | 2015-04-25T22:27:15Z | 2015-04-25T22:40:01Z | 2015-04-25T22:39:32Z | NONE | null | If I create a dataframe with two arrays that have different endianness, it works fine if I access the whole DataFrame or individual arrays:
``` python
In [1]: import pandas
In [2]: d = pandas.DataFrame()
In [3]: import numpy as np
In [4]: d['a'] = np.array([1,2,3], dtype='>f4')
In [5]: d['b'] = np.array([1,2,3], d... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9990 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9990/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9990/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9990/events | https://github.com/pandas-dev/pandas/issues/9990 | 71,010,987 | MDU6SXNzdWU3MTAxMDk4Nw== | 9,990 | The DataReader got stuck when fetched data from yahoo. | {
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] | closed | false | null | [] | null | 1 | 2015-04-26T04:57:35Z | 2015-04-28T00:26:40Z | 2015-04-28T00:26:34Z | NONE | null | I have script fetched the data from yahoo in multithread, the script always got stuck.
It looks like we need add a timeout parameter somewhere when we call the urlopen.
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https://api.github.com/repos/pandas-dev/pandas/issues/9991 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9991/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9991/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9991/events | https://github.com/pandas-dev/pandas/issues/9991 | 71,023,585 | MDU6SXNzdWU3MTAyMzU4NQ== | 9,991 | local variable 'rs' referenced before assignment error | {
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] | closed | false | null | [] | null | 5 | 2015-04-26T07:07:50Z | 2015-04-28T00:24:00Z | 2015-04-28T00:23:53Z | NONE | null | Hope you can help with the following error (thanks):
(with any financial data source, after I upgraded to v0.16 because yahoo finance was not working 0.14)
$goog=web.DataReader('GOOG', data_source='google', start='3/14/2009', end = '4/14/2014')
anaconda/lib/python2.7/site-packages/pandas/io/data.pyc in _retry_read_u... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9992 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9992/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9992/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9992/events | https://github.com/pandas-dev/pandas/issues/9992 | 71,038,827 | MDU6SXNzdWU3MTAzODgyNw== | 9,992 | nosetest failed for pandas 0.16.0 | {
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I recently upgraded pandas from 0.15.1 to 0.16.0. after running the nosetest i got the following error msgs. wondering if anything series (i tested HDF5 writing/reading. everything looks normal).
#
## ERROR: test_conv_read_write (pandas.io.tests.test_pytables.TestHDFStore)
Traceback (most recent call la... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9993 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9993/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9993/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9993/events | https://github.com/pandas-dev/pandas/issues/9993 | 71,064,890 | MDU6SXNzdWU3MTA2NDg5MA== | 9,993 | Plot matrix (and more specifically confusion matrix) | {
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I don't find any method to plot a matrix (such as confusion matrix) using "pure" Pandas.
Having a more convenient approach than
http://scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html
http://matplotlib.org/examples/pylab_examples/matshow.html
will be great.
```
import pandas as... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9994 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9994/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9994/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9994/events | https://github.com/pandas-dev/pandas/pull/9994 | 71,106,296 | MDExOlB1bGxSZXF1ZXN0MzQxMjc5Nzc= | 9,994 | BUG: transform and filter misbehave when grouping on categorical data | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-04-26T19:04:19Z | 2015-09-19T00:38:08Z | 2015-04-29T10:31:53Z | CONTRIBUTOR | null | Fixes GH #9921
closes #9700
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https://api.github.com/repos/pandas-dev/pandas/issues/9995 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9995/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9995/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9995/events | https://github.com/pandas-dev/pandas/issues/9995 | 71,134,450 | MDU6SXNzdWU3MTEzNDQ1MA== | 9,995 | BUG: length_of_indexer() can return incorrect values that break slice assignments. | {
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length_of_indexer() (defined in pandas/core/indexing.py) returns incorrect result
if (stop-start) is not divisible by step. As a consequence some slice assignments
throw exceptions. Affected panda versions: 0.16.x, 0.15.x, current git master.
HOW TO REPRODUCE:
import pandas as pd
sr= pd.Series([-1]*... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9996 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9996/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9996/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9996/events | https://github.com/pandas-dev/pandas/pull/9996 | 71,135,023 | MDExOlB1bGxSZXF1ZXN0MzQxMzIxMTI= | 9,996 | BUGFIX: length_of_indexer() can return incorrect values that break slice assignments | {
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BUG DESCRIPTION:
length_of_indexer() (defined in pandas/core/indexing.py) returns incorrect result
if (stop-start) is not divisible by step. As a consequence some slice assignments
throw exceptions. Affected panda versions: 0.16.x, 0.15.x, current git master.
HOW TO REPRODUCE:
import pandas as pd
sr... | {
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... | 41 | 2015-04-27T12:05:35Z | 2020-04-03T03:51:45Z | 2020-04-03T03:51:44Z | MEMBER | null | Here's our roadmap document: https://docs.google.com/document/d/151ct8jcZWwh7XStptjbLsda6h2b3C0IuiH_hfZnUA58/edit#
Just because it is a nice round number :-)
Or maybe we can use it to discuss how we imagine a possible pandas 1.0 ..
---
Some clarification (from @shoyer): This is not the place to make new feature re... | {
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OverflowError: normalized days too large to fit in a C int
But I have "parse_dates=False" so I thought pandas.ExcelFile would not try to parse... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10002 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10002/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10002/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10002/events | https://github.com/pandas-dev/pandas/issues/10002 | 71,416,618 | MDU6SXNzdWU3MTQxNjYxOA== | 10,002 | Usage of 'limit' keyword when filling with a value | {
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When doing `df.fillna(10, limit=2)` what is `limit=2` doing?
The [docstring](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.fillna.htm... | {
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