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https://api.github.com/repos/pandas-dev/pandas/issues/301
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301
Alternate constructor for dict of DataFrame -> Panel that doesn't nuke type information
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2011-10-27T04:20:59Z
2011-11-14T01:15:06Z
2011-11-14T01:15:06Z
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null
``` Panel({k : df}) ``` will cast everything to object if `df` is a mixed-type DataFrame
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302
Add DataFrame "type inference" function for casting object arrays to a more appropriate type
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2011-10-27T04:36:26Z
2011-12-12T04:48:23Z
2011-12-12T04:48:23Z
MEMBER
null
Could be called to recover types after `df.T.T`
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2,068,379
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303
Add back proper rolling WLS / panel WLS
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2011-11-08T04:33:05Z
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2,068,646
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304
Cannot fill inserted column of NaNs
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2
2011-10-27T14:45:53Z
2011-10-28T18:08:43Z
2011-10-28T15:13:43Z
CONTRIBUTOR
null
After inserting a column of NaNs into a preexisting DataFrame its contents cannot be filled using advanced indexing. See test case below. This only appears to happen if the existing DataFrame is filled with floats, i.e. it works fine for ints. Tested with pandas 0.5 and latest github snapshot. ``` python from pandas...
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2,071,809
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305
Print hierarchical index names in Series.__repr__
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2011-10-27T19:36:55Z
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306
Document DataFrame.set_index
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2011-10-28T16:45:30Z
2011-11-05T01:32:57Z
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307
ENH: Add .topK(col, k) to DataFrame
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3
2011-10-29T07:26:37Z
2011-11-02T05:26:22Z
2011-11-02T05:26:22Z
NONE
null
When exploring new datasets in pandas, I often find myself writing `````` df.groupby(col)[col].agg(len).order(ascending=False).head()```. I added a convenience method to frame.py so that I could write ```df.topK(col)``` instead: ```python def topK(self, col, k=5): """Returns top k most frequently occurring value...
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https://api.github.com/repos/pandas-dev/pandas/issues/308
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308
Should return DataFrame in Series.groupby when as_index=False
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2011-10-30T22:22:34Z
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309
Implement fast Cython Series iterator, for speeding up DataFrame.apply
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2011-10-31T01:26:56Z
2011-11-14T23:04:21Z
2011-11-13T23:17:03Z
MEMBER
null
Having tons of calls to `Series.__new__` seriously degrades performance because most of the logic isn't necessary. Could play tricks in Cython with the data pointers to avoid this.
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310
Deprecation warning in __init__.py
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1
2011-10-31T02:34:05Z
2011-11-16T20:21:19Z
2011-11-02T19:11:23Z
CONTRIBUTOR
null
... pandas/pandas/**init**.py:12: DeprecationWarning: BaseException.message has been deprecated as of Python 2.6 Shows up when I edit the code base with omnicompletion in vim.
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311
aggregate_item_by_item does not handle as_index=False in GroupBy
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2011-11-04T22:19:15Z
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312
Enable passing vector to on argument in DataFrame.join
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313
ENH: Added the level arguments to the series and frame math operations
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2011-11-01T18:17:20Z
2014-06-13T04:48:31Z
2011-11-02T05:03:50Z
CONTRIBUTOR
null
such as sum, etc.
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2,113,737
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314
Series.apply() does not always return a Series
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2011-11-01T18:56:52Z
2011-11-03T21:31:38Z
2011-11-03T21:31:38Z
NONE
null
Example below of it returning a NumPy array. This seems unexpected, given the documentation in the function. Thanks! Example: Code: import pandas as ps import numpy as np test = ps.Series(np.linspace(start=0, stop=1, num=20)) print test print test.apply(lambda x: np.round(x, 1)) Note : this is equivalent to np.roun...
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https://api.github.com/repos/pandas-dev/pandas/issues/315
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2,114,312
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315
Support boolean data in Cythonized groupby
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3
2011-11-01T19:56:01Z
2011-11-03T21:19:25Z
2011-11-03T21:19:25Z
MEMBER
null
reported by @bburan on the mailing list ``` In [146]: frame = DataFrame({'a': np.random.randint(0, 5, 10), 'b': np.random.ra ndint(0, 2, 10).astype('bool')}) In [147]: print frame a b 0 1 False 1 2 True 2 2 True 3 1 True 4 3 True 5 3 True 6 3 True 7 1 True 8 2 True 9 1 False In [150]: frame.g...
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2,115,148
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316
Raise warning or exception when calling Series.sort when do not own data
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2011-11-01T21:10:07Z
2011-12-24T21:37:14Z
2011-12-24T21:37:14Z
MEMBER
null
For example, when part of a DataFrame, can result in the source array being modified in place
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2,115,231
MDU6SXNzdWUyMTE1MjMx
317
Don't show Series.name if it's None
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2011-11-01T21:19:23Z
2011-11-03T21:39:18Z
2011-11-03T21:39:18Z
MEMBER
null
More aesthetically pleasing to me anyway
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318
Fix DataFrame.join docs to note that a Series with a name can be passed
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319
Add new function to remove duplicate rows from a DataFrame
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3
2011-11-01T23:20:43Z
2011-11-07T02:43:57Z
2011-11-07T02:43:57Z
MEMBER
null
Should be reasonably performant, probably just use sets + `np.apply_along_axis`
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320
read_csv fails to import data
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2011-11-02T02:15:02Z
2011-11-02T03:02:31Z
2011-11-02T03:02:31Z
CONTRIBUTOR
null
I'm using pandas 0.5.0 with python 2.7 on archlinux. This example file seems pretty standard and it opens well in Libreoffice: http://dl.dropbox.com/u/40028/countrycode.csv ``` python import pandas cc = pandas.read_csv('countrycode.csv', index_col=1) cc ERROR: An unexpected error occurred while tokenizing input The f...
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321
Added a QuarterEnd class to datetools module.
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1
2011-11-02T16:50:06Z
2014-06-13T11:06:15Z
2011-11-03T21:41:40Z
NONE
null
Wes, Hoping to get this in to the public version so we don't have to keep a separate local copy. If its, a no go, just let me know and we'll work around. Thanks, Nathan Pinger YCharts.com
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2,124,458
MDU6SXNzdWUyMTI0NDU4
322
Round trip from CSV to CSV should leave data types unaltered
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2011-11-02T18:05:41Z
2012-04-10T05:07:43Z
2012-04-10T05:07:38Z
CONTRIBUTOR
null
I love where pandas is going. A use-case for which R's csv capabilities still win, though, is in editing a large csv file that's used as a poor-mans database. R will keep a column of integers as integers, pandas changes some of them to floats, some to strings! I'm not sure why there's inconsistency there, but I figure...
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323
[BUG] DataFrame.describe fails if no numeric columns
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3
2011-11-02T18:34:47Z
2011-11-05T00:00:46Z
2011-11-05T00:00:46Z
NONE
null
DataFrame.describe function fails with the following when called on a Data Frame with no numeric columns: /usr/lib64/python2.7/site-packages/pandas/core/ frame.py(2324)describe() 2322 '25%', '50%', '75%', 'max'] 2323 -> 2324 data = [tmp.count(), tmp.mean(), tmp.std(), tmp.m...
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2,126,080
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324
add legend to DataFrame.plot()
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2011-11-02T20:30:48Z
2011-11-03T21:04:46Z
2011-11-03T21:04:37Z
CONTRIBUTOR
null
It would be very helpful if DataFrame.plot() function would also provide a legend with column names
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2,126,661
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325
to_string on DataFrame may print column labels in the wrong order
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2011-11-02T21:17:27Z
2011-11-05T00:32:56Z
2011-11-05T00:32:56Z
NONE
null
d = {'a': [1,2,3], 'b':[4,5,6]} from pandas import DataFrame df = DataFrame(d) df.to_string() Returns: a b 0 1 4 1 2 5 2 3 6 df.to_string(columns=['b','a']) Returns: a b 0 4 1 1 5 2 2 6 3
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326
DataFrame.plot with legend fails when the columns are integers
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2011-11-02T21:57:40Z
2011-11-03T21:03:07Z
2011-11-03T21:03:07Z
MEMBER
null
Fails at least with matplotlib 1.1. Should always stringify the columns
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327
Investigate why numpy.unique is so slow on Series input
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1
2011-11-02T21:58:12Z
2011-11-03T21:45:22Z
2011-11-03T21:45:22Z
MEMBER
null
Only true anecdotally (I've witnessed `np.unique(s.values)` being a lot faster but didn't have time to profile)
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328
Fundamental issue with ix
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3
2011-11-03T12:44:21Z
2012-01-07T01:29:06Z
2012-01-07T01:29:06Z
NONE
null
Using square bracket indexing [x] on a Series where x is an integer seems to return: - the item at the index x if such index is present - the x-th item if the index does not exist To be precise: In [190]: ss = pandas.Series(range(10), index = range(0, 20, 2)) ...: print ss ...: 0 0 2 1 ...
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329
[Bug] pandas.io.data.DataReader Yahoo dates bug
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4
2011-11-03T21:25:02Z
2011-11-05T01:08:44Z
2011-11-05T01:08:44Z
NONE
null
Yahoo finance seems to set its historical data URLs with the month variables set back minus one, and DataReader doesn't seem to accommodate this. For example, running: ticker = '^GSPC' start_dt = datetime(2008, 6, 30) end_dt = datetime(2010, 12, 31) data = DataReader(ticker, 'yahoo', start=start_dt, end=end_dt) Then:...
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330
ENH: small corrections to Series repr
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1
2011-11-03T21:27:35Z
2014-06-26T22:25:05Z
2011-11-03T21:38:50Z
CONTRIBUTOR
null
Issue #317
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331
DataFrame.join fails with unconsolidated inputs
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0
2011-11-04T16:36:19Z
2011-11-04T16:43:36Z
2011-11-04T16:43:36Z
MEMBER
null
An oversight in the join refactoring recently ``` create two objects: a=DataFrame(randn(30,2),columns=['a','b']) c=Series(randn(30)) now add c as column of a: a['c']=c create a third object: d=DataFrame(randn(30,1),columns=['d']) try to join with a: a.join(d) ```
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332
New attribute error associated with tseries
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2011-11-04T16:51:37Z
2011-11-05T03:45:27Z
2011-11-05T03:45:27Z
NONE
null
Hi Wes, After having gotten pandas to build and run on 10.7 previously, an updated build based on the current Github source yields the following AttributeError, also related to _tseries (which appears to be "lib" in this case): ``` In [1]: from pandas import * ---------------------------------------------------------...
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333
Add float_format option to Series.to_string
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2011-11-04T22:56:24Z
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334
ENH: Print hierarchical index names in Series.__repr__
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2011-11-04T19:43:08Z
2014-06-17T07:23:41Z
2011-11-04T22:22:59Z
CONTRIBUTOR
null
Issue 305
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335
Issue with _set_item not consolidating
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2011-11-04T21:15:22Z
2011-11-05T00:04:21Z
2011-11-05T00:04:21Z
NONE
null
The following code breaks (though it worked in previous versions of pandas): import pandas as ps x = ps.DataFrame(index=[1,2,3], columns=None, data=None) s = ps.Series(index=[1,2,3], data=[10,20,30]) x['a']=s x['b']=s_2 y = ps.DataFrame(index=[1,2,3], columns=None, data=None) y['c']=s y['d']=s_2 z = x.join(y, how='ou...
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336
make it easier to join TS to DF
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2011-11-04T21:25:35Z
2011-11-04T21:39:28Z
2011-11-04T21:39:28Z
CONTRIBUTOR
null
Normally I work with DataFrames consisting of OHLC columns. To create a new DF with only 'close' column of multiple DFs one can do something like this: DataFrame({'VIX':vix['close'],'VXV':vxv['close']}) However, it would be more convenient to use .join method, but to do this I have to hack around with a rename functio...
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337
DataFrame.min/max do not support mixed-type frames currently
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338
Implement label-based fancy indexing analogue for DataFrame
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2011-11-05T22:46:20Z
2012-01-12T19:53:28Z
2012-01-12T19:53:28Z
MEMBER
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List of rows + list of columns -> 1D vector of values
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339
Add function to infer better dtypes for DataFrame columns of object dtype
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2011-11-05T22:59:05Z
2011-11-13T23:45:32Z
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MEMBER
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For example when doing a transpose roundtrip-- right now type information is lost
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340
See if it's possible to have somewhat sensible unicode handling
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2011-11-06T01:42:04Z
2012-01-25T23:21:18Z
2012-01-25T23:21:18Z
MEMBER
null
`__repr__` will keep failing in Python 2.x, but should be possible to get to_string to return unicode so at least the thing can be printed.
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341
Use faster count_level_1d function in DataFrame too
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2011-11-06T21:23:48Z
2011-11-07T01:15:13Z
2011-11-07T01:15:13Z
MEMBER
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Currently only being used in Series
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342
Enable easier transformations of multiple columns in DataFrame
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2011-11-07T00:40:35Z
2018-12-13T18:11:45Z
2011-12-19T05:21:30Z
MEMBER
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things like ``` df[cols] = transform(df[cols]) ``` should be possible in a mixed-type DataFrmae, per the mailing list discussion
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343
Add converters argument to read_csv a la np.loadtxt
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344
library not found for -lbundle1.o
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2011-11-07T07:15:04Z
2011-11-07T16:42:38Z
2011-11-07T16:42:38Z
CONTRIBUTOR
null
I'll begin by saying that I believe the problem with this could be unique to my machine. I'm running OSX Lion on a MacBookPro. Attempting to easy_install pandas I get: ``` gcc: pandas/src/tseries.c gcc -bundle -undefined dynamic_lookup -g -arch i386 build/temp.macosx-10.5-i386-2.7/pandas/src/tseries.o -o build/lib....
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345
Quarterend
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2011-11-07T16:26:06Z
2011-11-07T16:31:03Z
2011-11-07T20:12:02Z
NONE
null
Wes, Thanks for taking the QuarterEnd class as-is. Here are the accompanying unit tests you wanted, along with the original commit. Best, Nathan
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346
Raise more helpful ImportError if dateutil 2.0 installed on Python 2.x
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2011-11-07T16:37:40Z
2011-11-08T04:46:30Z
2011-11-08T04:46:30Z
MEMBER
null
per conversation with @mforthmann
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347
Implement logical operators on DataFrame, &, |, ^, ~
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2011-11-07T16:41:38Z
2011-11-08T04:30:37Z
2011-11-08T04:30:37Z
MEMBER
null
code example from ML ``` from pandas import * df1 = {'a': {'a': True, 'b': False, 'c': False, 'd': True, 'e': True}, 'b': {'a': False, 'b': True, 'c': False, 'd': False, 'e': False}, 'c': {'a': False, 'b': False, 'c': True, 'd': False, 'e': False}, 'd': {'a': True, 'b': False, 'c': False, 'd': True, 'e': True}, 'e...
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348
Add kind='line' or 'bar' argument to DataFrame.plot
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2011-11-08T01:59:02Z
2014-06-14T08:07:19Z
2011-11-14T00:57:16Z
CONTRIBUTOR
null
This is just a first stab at it, comments are very welcome, plus feel free to say you'd rather not add it at all.
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349
index_col argument in read_csv may not respect order given
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MEMBER
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User reported on mailing list
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350
Conversion of DataFrame to R's data.frame
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2011-11-08T09:56:11Z
2012-05-14T15:06:42Z
2012-05-14T15:05:24Z
CONTRIBUTOR
null
Although I have already produced code for this (see below) I'm posting this as an issue rather than a pull request to discuss the design, because there are some issues open in my code: - Series of dtype object need an explicit cast or rpy2's numpy conversion will treat them improperly - The performance has not been pro...
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351
.join works incorrectly with MultiIndex (data is not actually alligned)
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2
2011-11-08T21:34:02Z
2011-11-10T03:19:38Z
2011-11-10T03:17:05Z
NONE
null
- When you use .join with a MultiIndex, it combines the DataFrames improperly. - When you use .join(how='outer'), the index is destroyed (turned into integers). Example below. Thanks, Ryan index1=MultiIndex.from_arrays([['a','a','a','b','b','b'], [1,2,3,1,2,3]]) index2=MultiIndex.from_arrays([['b','b','b','c','c',...
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352
Badly-formatted hashbang in setup.py
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2011-11-09T10:48:44Z
2011-11-10T01:50:25Z
2011-11-10T01:50:25Z
NONE
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The first line of the file setup.py is as follows: ``` #/usr/bin/env python ``` (ie. missing a ! symbol) Attempting to eecute the file with the command `./setup.py` results in some strange errors. A work-around is to execute the file using `python setup.py` instead.
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353
str + Series does not yield expected result
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2011-11-09T21:49:54Z
2011-11-10T02:09:06Z
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dispatch order is wrong
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354
pivot_table should fail if duplicate entries exist
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2011-11-10T16:14:03Z
2011-11-10T20:06:57Z
2011-11-10T20:06:57Z
NONE
null
This looks like #147, but I don't have permission to re-open that. Consider the following situation: ``` In [3]: dt Out[3]: foo bar baz 0 1 2 3 1 4 5 6 2 1 2 4 In [4]: pandas.pivot_table(dt, values="baz", rows=["foo"], cols=["bar"]) Out[4]: bar 2 5 foo 1 3.5...
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355
Vectorize pandas.Series.apply
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4
2011-11-10T16:33:30Z
2014-06-14T16:19:02Z
2011-11-11T21:05:56Z
CONTRIBUTOR
null
When profiling my code I noticed that numpy.vectorize was a bit faster than pandas.Series.apply. Execution Times: numpy.vectorize: 3.3 seconds pandas.Series.apply: 4.4 seconds.
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356
read_csv error
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2011-11-10T17:54:40Z
2011-11-10T18:04:55Z
2011-11-10T18:04:55Z
CONTRIBUTOR
null
I get the following traceback when trying to read a csv_file: Traceback (most recent call last): File "C:\src\OSR\OSR\run.py", line 127, in <module> pheno_data = read_data(base_dir+'pheno_data_num_id.csv') File "C:\src\OSR\OSR\run.py", line 41, in read_data pheno_data = pandas.read_csv(filename,index_col=0...
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357
Add Fast DataFrame constructor from records (list of tuples)
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2011-11-10T21:23:56Z
2011-11-11T20:50:49Z
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358
Single column groupby does not set name
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2011-11-10T21:50:56Z
2011-11-11T18:37:45Z
2011-11-11T18:37:45Z
MEMBER
null
``` In [2]: paste df = DataFrame({'A' : ['foo', 'bar', 'foo', 'bar', 'foo', 'bar', 'foo', 'foo'], 'B' : ['one', 'one', 'two', 'three', 'two', 'two', 'one', 'three'], 'C' : np.random.randn(8)...
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359
creating Panel from dict of DataFrames loses dtypes
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1
2011-11-11T14:13:36Z
2011-11-11T18:37:54Z
2011-11-11T17:23:27Z
CONTRIBUTOR
null
in the example below, "a" is a mixed type dataframe. Once included in the Panel, all columns become of type object: In [249]: a=DataFrame(randn(30,3),columns=('a','b','c')) In [250]: b=DataFrame(randn(30,3),columns=('a','b','c')) In [251]: a['b']=a['b'].astype(object) In [252]: a.dtypes Out[252]: a float64 b ...
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360
Add fast methods for getting and putting single elements in DataFrame, Panel
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2011-11-13T01:15:27Z
2011-11-13T04:28:35Z
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MEMBER
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361
Move caching decorators to Cython for speed
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2011-11-13T02:00:31Z
2011-11-13T04:25:39Z
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362
Issues #194 (cov function) and #92 (multi-column sort)
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2011-11-13T15:45:22Z
2014-06-12T09:19:59Z
2011-11-13T17:51:58Z
CONTRIBUTOR
null
Added: 1. Series.cov 2. DataFrame.cov 3. test_cov in test_series.py 4. test_cov in test_frame.py Modified: 1. DataFrame.sort 2. DataFrame.sort_index 3. test_sort in test_frame.py
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363
GroupBy Series with name field set, should pass on name
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2011-11-22T16:50:33Z
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MEMBER
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364
Support separators with > 1 character and regular expressions in read_table
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2011-11-14T18:59:02Z
2011-11-17T18:26:12Z
2011-11-17T18:26:12Z
MEMBER
null
Major source of difficulty are quoted strings-- not doing this for now, will need to have a state machine-type parser (Cython?) later
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365
rolling_* with min_periods=0
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2011-11-15T00:58:46Z
2011-11-16T20:02:10Z
2011-11-16T20:02:10Z
CONTRIBUTOR
null
I ran into a minor gotcha with the rolling_\* methods, below is some ipython output to illustrate. I set min_periods to 0, which in retrospect i realize is not a reasonable value, but i would either expect the same behavior as min_periods=1 or maybe an error. For rolling_max, the issue is with line 421 in moments.pyx...
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366
Traceback when calling df.as_matrix()
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2011-11-15T11:09:50Z
2011-11-16T08:35:13Z
2011-11-16T08:35:13Z
NONE
null
I have a DataFrame object that was created by importing some data in list form, pivoting it, then adding totals columns using `df.append(pandas.DataFrame(some_matrix, columns=df.columns, index=[some_tuple])` and `df[some_other_tuple] = some_array` respectively. The resulting DataFrame object looks like this: ``` >>> d...
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Exception Joining DataFrames and Series
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2011-11-15T15:53:22Z
2011-11-16T08:50:45Z
2011-11-16T08:50:45Z
CONTRIBUTOR
null
In [23]: a=DataFrame(randn(5,2),index=[1,2,3,6,7],columns=['a','b']) In [24]: b=Series([6,7,8,9],index=[0,1,2,3],name='c') In [25]: c=Series([6,7,8,9],name='c') In [26]: a Out[26]: a b 1 -0.268 -0.1305 2 0.2243 0.4644 3 0.4767 -0.5677 6 0.1806 0.6276 7 0.9767 0.3687 In [27]: b Out[27]: 0 6 1...
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368
DataFrame.boxplot fixes
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1
2011-11-15T21:56:19Z
2013-09-29T00:03:46Z
2011-11-23T17:41:20Z
MEMBER
null
per mailing list discussion @lodagro - Return ax or axes - Handling of [col] and multiple columns - Plot when only single column passed not correct
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369
Fix graphics tests under Python 3
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2011-11-16T01:28:01Z
2014-07-02T22:17:37Z
2011-11-18T17:39:18Z
CONTRIBUTOR
null
A simple switch from `string.letters` to `string.ascii_letters`. The latter is present on Python 2 as well, so nothing clever is needed.
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370
Add ability to stack/unstack multiple levels at once
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2011-11-16T06:10:39Z
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MEMBER
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371
Wildcard for indexing with MultiIndex
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7
2011-11-16T10:54:19Z
2012-01-17T07:49:03Z
2012-01-16T22:00:56Z
CONTRIBUTOR
null
based on [mailing list discussion](https://groups.google.com/forum/#!searchin/pystatsmodels/wildcard/pystatsmodels/vxUE3NXWpVM/sYnBKkYZOLgJ), adding here for better traceability. Is there a way to use wild cards when using MultiIndex? As an example, let`s work with the following DataFrame: ``` python In [10]: df Out...
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372
Unable to build from HEAD
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2011-11-16T15:04:33Z
2011-11-16T19:18:51Z
2011-11-16T19:18:40Z
NONE
null
I've just tried to build the latest version of pandas from HEAD, and I get the following error: ``` error: pandas/src/cppsandbox.pyx: No such file or directory ``` Did you forget to add this file to the repository?
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373
DataFrame constructor when passed a Series
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3
2011-11-16T17:15:52Z
2011-11-17T09:00:26Z
2011-11-16T19:28:29Z
CONTRIBUTOR
null
If I do: a=Series([1,2,3],index=['a','b','c'],name='x') b=DataFrame(a) I would expect b to have a single column 'x' with indices a,b,c; instead only a.values is retained.
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374
Better skiplist data structure implementation in Cython
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2011-11-16T19:36:08Z
2011-12-28T22:16:48Z
2011-12-28T22:16:48Z
MEMBER
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Rolling median is slow as a result of too much Python
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375
Pivoting on multiple columns causes data loss
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2011-11-17T12:21:36Z
2011-11-18T06:08:34Z
2011-11-18T06:08:34Z
NONE
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Seen on HEAD. This problem is new since 0.5.0. ``` In [3]: data Out[3]: foo bar baz spam data 0 foo1 bar1 baz1 spam2 20 1 foo1 bar2 baz1 spam3 30 2 foo2 bar2 baz1 spam2 40 3 foo1 bar1 baz2 spam1 50 4 foo3 bar1 baz2 spam1 60 In [4]: pandas.pivot_table(data, values="data",...
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376
Enable pass through *args, **kwargs to function in DataFrame.apply
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377
mixed type dataframe loses type info
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2011-11-17T17:34:22Z
2011-11-17T17:57:48Z
2011-11-17T17:57:48Z
CONTRIBUTOR
null
I have a situation where joining objects of different types creates object where info() and dtypes disagree, and generally all datatypes revert to object: In [630]: a=DataFrame(['aa','bb','cc','dd','ee'],index=[1,2,3,4,5],columns=['a']) In [631]: b=DataFrame(randn(5,1),index=[1,2,3,4,5],columns=['b']) In [632]: a.dt...
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2,272,263
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378
Exception Upon Pivoting an Empty DataFrame
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2011-11-17T18:52:42Z
2011-11-18T06:48:05Z
2011-11-18T06:48:05Z
NONE
null
from pandas import DataFrame df = DataFrame({},columns=['time','item','value']) df.pivot('time','item','value') pandas\core\frame.pyc in pivot(self, index, columns, values) 1953 """ 1954 from pandas.core.reshape import pivot -> 1955 return pivot(self, index=index, columns=columns, values=...
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379
Allow user to pass level names to swaplevel
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2011-11-17T22:03:21Z
2011-11-22T05:38:32Z
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2,274,447
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380
Exception With np.frompyfunc
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2011-11-17T22:16:02Z
2012-01-20T20:48:22Z
2011-11-18T15:30:05Z
NONE
null
from aqr.core.frame import DataFrame import numpy as np def func(a, b): return a + b df = DataFrame({'US':[1,2,3]}) f = np.frompyfunc(func, 2, 1) print f.accumulate(df) In pre-0.4.0 pandas, this printed: US 0 1 1 3 2 6 Now, this: ValueError: could not find a matching type for func (vectorized).accumulate, r...
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381
Pass list to values argument in pivot_table
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2011-11-17T23:39:43Z
2011-11-18T06:23:17Z
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382
DataFrame should be more aggressive about trying to aggregate numeric data stored in dtype object
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2011-11-18T00:07:02Z
2011-11-23T03:41:21Z
2011-11-23T03:41:21Z
MEMBER
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``` data = dict() data['a'] = [-0.00049987540199591344, -0.0016467257772919831, 0.00067695870775883013] data['b'] = [-0, -0, 0.0] data['c'] = [0.00031111847529610595, 0.0014902627951905339, -0.00094099200035979691] AA = DataFrame( data , index = ['20110801', '20110802', '20110803'] , dtype = ‘object’ ) ```
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383
Pass multiple columns to DataFrameGroupBy.__getitem__
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2011-11-18T06:17:18Z
2012-05-14T20:01:58Z
2012-05-14T20:01:58Z
MEMBER
null
(preferably without copying data)
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384
Test all NA case in min/max functions
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2011-11-18T07:33:01Z
2011-11-23T03:40:33Z
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385
resolve issue 368
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2011-11-18T09:21:29Z
2014-07-04T00:18:53Z
2011-11-18T17:35:29Z
CONTRIBUTOR
null
two commits to resolve [issue#368](https://github.com/wesm/pandas/issues/368)
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https://api.github.com/repos/pandas-dev/pandas/issues/386
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386
DataFrame.dtypes reports all object dtypes even if items aren't object dtype
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2011-11-18T09:38:17Z
2011-11-19T19:18:47Z
2011-11-19T19:18:47Z
CONTRIBUTOR
null
I'm not sure if this is just an error on my part, but I have ``` python >>> dataset <class 'pandas.core.frame.DataFrame'> Index: 17788 entries, 10000 to AFFX-r2-P1-cre-5 Data columns: ID 17788 non-null values Sample 1 17788 non-null values Sample 2 17788 non-null values Sample 3 17788 non-null v...
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387
DataFrame.to_html()
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2011-11-18T09:53:38Z
2014-06-17T21:46:53Z
2011-11-18T17:44:30Z
CONTRIBUTOR
null
DataFrame.to_html() -- Render a DataFrame to a html table.
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388
Even more agile reshaping
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2011-11-18T17:34:38Z
2014-03-09T15:19:04Z
2014-03-09T15:19:04Z
MEMBER
null
Similar to STATA reshape-- may just want to hold some columns fixed, reshape and munge column names
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https://api.github.com/repos/pandas-dev/pandas/issues/389
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389
DataFrame.apply returns Series
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2011-11-18T18:59:34Z
2011-11-22T18:38:03Z
2011-11-22T18:38:03Z
NONE
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from pandas import DataFrame, DateRange dr = DateRange('2011-11-01','2011-11-15') df = DataFrame(index=dr) df_or_so_youd_think = df.apply(lambda x:x) print df_or_so_youd_think This returns an empty Series.
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390
Result of asfreq should have DateRange index
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2011-11-18T19:38:38Z
2011-11-22T05:14:27Z
2011-11-22T05:14:27Z
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fyi @craustin
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391
Add more robust frequency inference function
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392
Do converters work for index columns in read_csv?
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2011-11-20T02:27:03Z
2011-11-22T05:07:22Z
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per @aman-thakral e-mail on mailing list
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Make delevel work with non-MultiIndex with a name
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.ix[val] discards index names
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Tweak DataFrame formatting to always use same # of digits
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Handle masked arrays in DataFrame constructor
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2011-11-22T03:55:50Z
2014-06-15T04:55:39Z
2011-11-23T17:20:01Z
CONTRIBUTOR
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If passing a masked array to DataFrame constructor, my expectation was that the masked entries would end up as NAN's in the DataFrame. This does not appear to be the case. The commits in the pull request try toe address that. as always, comments welcome. thanks
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Partial setting (with more than 1 level specified) with .ix raises exception
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