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https://api.github.com/repos/pandas-dev/pandas/issues/401 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/401/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/401/comments | https://api.github.com/repos/pandas-dev/pandas/issues/401/events | https://github.com/pandas-dev/pandas/issues/401 | 2,319,602 | MDU6SXNzdWUyMzE5NjAy | 401 | Panel property specifying orientation | {
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"f... | 3 | 2011-11-22T16:20:05Z | 2014-05-28T23:12:49Z | 2014-05-28T23:12:49Z | CONTRIBUTOR | null | I have on occasion used the from_dict(orientation) method that you created. It would be useful to have a property of the panel object telling me with which orientation the Panel was created, so that I can handle it differently.
Thanks
Christian
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http://www.pastie.org/2904328
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```
Well, it's only the ones that are the same that I want to ignore. I'd
say that's up to the user to do this right. No checking, just take the
first value or something, but that's up to you.
df = df.unstack('agefrom', ignore='ccode')
df = df.unstack('agefrom', keep='ccode')
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"followers_url": "https://api.github.com/users/wesm/f... | 1 | 2011-11-24T11:27:35Z | 2011-11-25T05:50:26Z | 2011-11-25T05:50:26Z | CONTRIBUTOR | null | In [11]: Panel(items=arange(3),major_axis=arange(3),minor_axis=arange(3),dtype=np.object).ix[1].dtypes
Out[11]:
0 float64
1 float64
2 float64
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https://api.github.com/repos/pandas-dev/pandas/issues/412 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/412/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/412/comments | https://api.github.com/repos/pandas-dev/pandas/issues/412/events | https://github.com/pandas-dev/pandas/issues/412 | 2,343,842 | MDU6SXNzdWUyMzQzODQy | 412 | Override Index.astype to prevent bad things from happening | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2011-11-24T17:58:54Z | 2011-12-03T17:51:16Z | 2011-12-03T17:51:12Z | MEMBER | null | For example, this should be possible: `index.astype('i8')`
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https://api.github.com/repos/pandas-dev/pandas/issues/413 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/413/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/413/comments | https://api.github.com/repos/pandas-dev/pandas/issues/413/events | https://github.com/pandas-dev/pandas/issues/413 | 2,344,354 | MDU6SXNzdWUyMzQ0MzU0 | 413 | API: Making plot methods more uniform in their options | {
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"f... | 9 | 2011-11-24T19:21:01Z | 2018-07-06T19:31:40Z | 2018-07-06T19:31:39Z | MEMBER | null | from @lodagro:
Been thinking a bit on uniformering signatures for plot, hist, boxplot and what they do/return.
For reference, below an overview what pandas and matplotlib.pyplot have.
some things that come to mind
- +1 for what you did with boxplot, _by_ and _column_ are handy, this could also be used for other kind ... | {
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"f... | 1 | 2011-11-24T20:14:15Z | 2014-06-07T16:57:58Z | 2013-11-22T09:52:45Z | MEMBER | null | per Andreas Hilboll question on mailing list
```
Hi,
I have a DataFrame ``DF`` where in one column there's the time (in
hours, as float). I'm looking for an easy way of iterating over
subsets of ``DF`` which are defined by looking for time gaps of 45
minutes or more and using these gaps as seperator between the
diffe... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/417 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/417/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/417/comments | https://api.github.com/repos/pandas-dev/pandas/issues/417/events | https://github.com/pandas-dev/pandas/issues/417 | 2,355,564 | MDU6SXNzdWUyMzU1NTY0 | 417 | test failures with v0.6.0 | {
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python: Enthought Python Distribution, Python 2.7.2 |EPD 7.1-1 (32-bit)
pandas: v0.6.0 , git commit 010a620da89e5babc137b924dd1f632b4f6e6fee
Running 'nosetests pandas' yields the following errors:
#
## ERROR: testFilterWithDataFrameRHS (pandas.stats.tests.test_ols_filter.TestOLSFilter)
Traceback (most ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/418 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/418/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/418/comments | https://api.github.com/repos/pandas-dev/pandas/issues/418/events | https://github.com/pandas-dev/pandas/issues/418 | 2,360,857 | MDU6SXNzdWUyMzYwODU3 | 418 | strange behavior with int in DF | {
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When I create a dataframe as a class property and append rows as shown in the code below,
the 'int' type of 'id' field is being returned as float when accessed with .ix or .xs method:
``` python
from pandas import Dat... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/419 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/419/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/419/comments | https://api.github.com/repos/pandas-dev/pandas/issues/419/events | https://github.com/pandas-dev/pandas/issues/419 | 2,362,969 | MDU6SXNzdWUyMzYyOTY5 | 419 | DataReader - request to truncate retrieved data to specified dates | {
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from pandas.io.data import DataReader
import datetime
import matplotlib.pyplot as plt
sp500 = DataReader("SPY", "yahoo", start=datetime.datetime(2005, 1,1))
sp500.info()
sp500["Adj Close"].plot()
plt.show()
<class 'pandas.core.frame.DataFrame'>
Index: 4744 entries, 1993-01-29 00:00:00 to 2011-11... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/420 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/420/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/420/comments | https://api.github.com/repos/pandas-dev/pandas/issues/420/events | https://github.com/pandas-dev/pandas/pull/420 | 2,364,814 | MDExOlB1bGxSZXF1ZXN0NTMyNTM3 | 420 | Change Series default float formatter. | {
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_pandas.core.common._float_format()_ is also default float formatter for DataFrame.
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import numpy as np
import pandas
def webuse(data, baseurl='http://www.stata-press.com/data/r11/'):
"""
Parameters
----------
data : str
Name of dataset to fetch.
Examples
--------
>>> dta = webuse('auto')
Notes
-----
Make sure baseurl has trailing forward slash. Do... | {
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`DataMatrix(index=range(10)).count(1)`
returning zeros should not be very harmful.
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https://api.github.com/repos/pandas-dev/pandas/issues/425 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/425/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/425/comments | https://api.github.com/repos/pandas-dev/pandas/issues/425/events | https://github.com/pandas-dev/pandas/pull/425 | 2,406,858 | MDExOlB1bGxSZXF1ZXN0NTQ0NDUw | 425 | more momery efficient describe() for DataFrame | {
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https://api.github.com/repos/pandas-dev/pandas/issues/426 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/426/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/426/comments | https://api.github.com/repos/pandas-dev/pandas/issues/426/events | https://github.com/pandas-dev/pandas/issues/426 | 2,408,182 | MDU6SXNzdWUyNDA4MTgy | 426 | Build errors using llvm-gcc | {
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```
building 'pandas._cppsandbox' extension
llvm-gcc-4.2 -DNDEBUG -g -fwrapv -Os -Wall -Wstrict-proto... | {
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compareOp = lambda s1, s2 : map(lambda x, y: x if y is None else (y if x is None else min(x, y)), s1, s2)
print m2.apply(lambda x : compareOp(x, s))
```
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https://api.github.com/repos/pandas-dev/pandas/issues/434 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/434/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/434/comments | https://api.github.com/repos/pandas-dev/pandas/issues/434/events | https://github.com/pandas-dev/pandas/issues/434 | 2,432,464 | MDU6SXNzdWUyNDMyNDY0 | 434 | Empty series corner case arith bug | {
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```
import numpy as np
from pandas import Series
s1 = Series([], [], dtype=np.int32)
s2 = Series({'x' : 0.})
print s1 * s2
```
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https://api.github.com/repos/pandas-dev/pandas/issues/435 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/435/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/435/comments | https://api.github.com/repos/pandas-dev/pandas/issues/435/events | https://github.com/pandas-dev/pandas/pull/435 | 2,433,164 | MDExOlB1bGxSZXF1ZXN0NTUzNTg0 | 435 | Using pandas with PyQt | {
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https://api.github.com/repos/pandas-dev/pandas/issues/440 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/440/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/440/comments | https://api.github.com/repos/pandas-dev/pandas/issues/440/events | https://github.com/pandas-dev/pandas/issues/440 | 2,433,751 | MDU6SXNzdWUyNDMzNzUx | 440 | DataFrame.delevel infer dtypes better | {
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```
MultiIndex seems to store the level data always as dtype('object').
When using DataFrame.delevel() the added columns from the index also have dtype('object').
This prevents from using DataFrame.delevel.corr() to have a look at the correlation between the original DataFrame columns and the index level ... | {
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<pre>
File "zipextimporter.pyo", line 82, in load_module
File "pandas\core\panel.pyo", line 145, in <module>
File "pandas\core\panel.pyo", line 690, in Panel
File "pandas\core\panel.pyo", line 114, in _panel_ar... | {
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... | 1 | 2011-12-05T02:28:39Z | 2019-11-18T17:09:34Z | 2019-11-18T17:09:33Z | MEMBER | null | Currently all NA groups are excluded though perhaps this should be a flag passed to groupby
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@y-p
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``` python
>>> df
RP/Rsum P.value
ID
A_23_P42353 17.8 0
A_23_P369994 15.91 0
A_33_P3262440 436.7 0.0005
A_32_P199429 18.97 0
A_23_P256724 22.24 0
A_33_P3394689 24.24 0
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``` python
In [170]: import pandas
In [171]: import numpy as np
In [172]: import itertools
In [173]: index = pandas.MultiIndex.from_tuples([t for t in itertools.product(['foo', 'bar'], [0, 1] , ['a', 'b'])])
In [174]: df = pandas.DataFrame(np.random.randn(8,2), columns=['A', 'B'], i... | {
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the following code produces a UnboundLocalError when executed with pandas 0.6.0 / Python 2.7:
```
import datetime
import pandas
timeidx = pandas.DateRange(start=datetime.datetime(2009,1,1),
end=datetime.datetime(2009,12,31),
offset=pandas.datetools.MonthEnd())
lons_co... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/453 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/453/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/453/comments | https://api.github.com/repos/pandas-dev/pandas/issues/453/events | https://github.com/pandas-dev/pandas/pull/453 | 2,463,652 | MDExOlB1bGxSZXF1ZXN0NTYzMzgx | 453 | Series/DataFrame, make decision between full and short __repr__ configurable | {
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These two numbers impact `pandas.Series.__repr__()` and `pandas.DataFrame.__repr__()`.
Decision between a short representation or a full one is now configurable. Default values are set to the current ones, so the change is trans... | {
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the following code produces a `ValueError: unrecognized index type <type 'float'>`:
```
import datetime
import pandas
timeidx = pandas.DateRange(start=datetime.datetime(2009,1,1),
end=datetime.datetime(2009,12,31),
offset=pandas.datetools.MonthEnd())
lons_coarse = np.linspace... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/456 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/456/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/456/comments | https://api.github.com/repos/pandas-dev/pandas/issues/456/events | https://github.com/pandas-dev/pandas/issues/456 | 2,466,718 | MDU6SXNzdWUyNDY2NzE4 | 456 | DateRange union bug caused by bad DateOffset comparison | {
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```
In [35]: rng1 = DateRange('12/5/2011', '12/5/2011')
In [36]: rng2 = DateRange('12/2/2011', '12/5/2011')
In [37]: rng1.union(rng2)
Out[37]:
<class 'pandas.core.daterange.DateRange'>
offset: <1 BusinessDay>, tzinfo: None
[2011-12-02 00:00:00, ..., 2011-12-05 00:00:00]
length: 2
In [38]: rng2.off... | {
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```
running build
running build_py
copying pandas\version.py -> build\lib.win32-2.6\pandas
running build_ext
skipping 'pandas\src\tseries.c' Cython extension (up-to-date)
building 'pandas._tseries' extension
C:\Program Files\Microsoft Visual Studio 9.0\VC\BIN\cl.e... | {
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"labels_url": "htt... | 7 | 2011-12-07T15:29:54Z | 2019-10-18T15:39:08Z | 2014-03-11T01:33:18Z | CONTRIBUTOR | null | Been working a bit on the idea of DataFrame rendering stylists. Would like some feedback on the idea / API.
Idea is that on top of the _formatters_ used in `DataFrame.to_string()` and `DataFrame.to_html()`, i would like to add _stylists_. A _stylist_ takes as input a string and returns a string, allowing to alter the ... | {
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There are two issues there:
1. MSVC does not support "inline" in C (see http://msdn.microsoft.com/en-us/library/z8y1yy88.aspx)
It does support _inline in C however, which has the intended meaning as fa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/463 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/463/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/463/comments | https://api.github.com/repos/pandas-dev/pandas/issues/463/events | https://github.com/pandas-dev/pandas/pull/463 | 2,481,740 | MDExOlB1bGxSZXF1ZXN0NTcwMzc4 | 463 | Yahoo quote | {
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https://api.github.com/repos/pandas-dev/pandas/issues/464 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/464/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/464/comments | https://api.github.com/repos/pandas-dev/pandas/issues/464/events | https://github.com/pandas-dev/pandas/issues/464 | 2,495,888 | MDU6SXNzdWUyNDk1ODg4 | 464 | Insert DataFrame rows with dict / other interface | {
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https://api.github.com/repos/pandas-dev/pandas/issues/465 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/465/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/465/comments | https://api.github.com/repos/pandas-dev/pandas/issues/465/events | https://github.com/pandas-dev/pandas/issues/465 | 2,500,548 | MDU6SXNzdWUyNTAwNTQ4 | 465 | DataFrame.applymap(func) issue when func returns tuple | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2011-12-09T11:13:43Z | 2013-12-04T00:48:07Z | 2011-12-12T02:58:34Z | CONTRIBUTOR | null | ``` python
In [82]: def func_tuple(x):
....: return (x,x)
....:
In [83]: series = pandas.Series(['a', 'b', 'c', 'd'])
In [84]: df = pandas.DataFrame({'A': series})
In [85]: df
Out[85]:
A
0 a
1 b
2 c
3 d
In [86]: df.applymap(func_tuple)
Out[86]:
A
0 None
1 None
2 None
3 None
```
This works f... | {
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```
df = DataFrame(index=np.arange(175))
for i in range(8000):
df[i] = 5
```
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https://api.github.com/repos/pandas-dev/pandas/issues/469 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/469/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/469/comments | https://api.github.com/repos/pandas-dev/pandas/issues/469/events | https://github.com/pandas-dev/pandas/issues/469 | 2,518,357 | MDU6SXNzdWUyNTE4MzU3 | 469 | Need to exclude NA values with dtype=object in stat methods | {
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import pandas
lis = [1, 3, 5, None, 7]
index = [1, 2, 3, 4, 5]
ser = pandas.core.series.Series(data=lis, index=index)
ser.mean()
Gives this error:
Traceback (most recent call last):
File "<console>", line 1, in <module>
File ".../pandas/core/series.py", line 65... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/471 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/471/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/471/comments | https://api.github.com/repos/pandas-dev/pandas/issues/471/events | https://github.com/pandas-dev/pandas/issues/471 | 2,520,213 | MDU6SXNzdWUyNTIwMjEz | 471 | ImportError: No module named sparse.api | {
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"followers_url": "https://api.github.com/users/wesm/f... | 2 | 2011-12-12T07:46:39Z | 2011-12-12T15:58:03Z | 2011-12-12T15:30:09Z | CONTRIBUTOR | null | Pulled from github master and did install (removed previous version and build dir), but get ImportError.
``` python
In [1]: import pandas
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
...
----> 1 import pandas
<.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/472 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/472/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/472/comments | https://api.github.com/repos/pandas-dev/pandas/issues/472/events | https://github.com/pandas-dev/pandas/issues/472 | 2,520,963 | MDU6SXNzdWUyNTIwOTYz | 472 | pandas: python remote engine crashes at object introspection of DataFrame instance Optionen | {
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When i try the following pandas example code from
http://pandas.sourceforge.net/dsintro.html
in the Python interpreter of PyScripter 2.4.3.0 with python 2.6.7 on
win32bit and the remote python engine (using rpyc Version 3.2.0) and
pandas 0.6.0
from pandas import *
d = {'one' : Series([1., 2., 3.], index=['a'... | {
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```
import pandas
pandas
import numpy as np
from pandas import DataMatrix
Y = DataMatrix( np.random.random( (4,4) ) , index = ('a','b','c','d') , columns = ('e','f','g','h' ))
Y
Y['e'] = Y['e'].astype('object')
Y['g']['c'] = np.NaN
Y
Y.sum()
Y['g'].sum()
```
Appears to be caused by a stale reference ... | {
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```
In [7]: DataFrame(Series(np.arange(10)), index=range(5))
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
/home/wesm/code/pandas/<ipython-input-7-0a85de6b44f0> in <module>()
----> 1 DataFrame(... | {
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```
Concerning the method name, DataFrame.delevel() is maybe too close to a MultiIndex.
DataFrame.deindex() is more general, both are fine for me. And i have no problem to change either.
One little remark, for a MultiIndex default column names are inserted when needed, whereas if no MultiIndex is used,... | {
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```
from pandas import read_csv
import matplotlib.pyplot as plt
junk = read_csv('bar.csv')
fig = plt.figure()... | {
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```
append_many(cls, frames):
df = None
for f in frames:
df = f if df is None else df.append(f)
return df
```
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https://api.github.com/repos/pandas-dev/pandas/issues/483 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/483/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/483/comments | https://api.github.com/repos/pandas-dev/pandas/issues/483/events | https://github.com/pandas-dev/pandas/issues/483 | 2,536,571 | MDU6SXNzdWUyNTM2NTcx | 483 | should asfreq return future dates as well? | {
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"followers_url": "https://api.github.com/users/wesm/... | 3 | 2011-12-13T13:41:10Z | 2012-04-23T16:06:47Z | 2012-04-23T16:06:47Z | CONTRIBUTOR | null | Suppose I have a daily series ts ending on dec 12th, and that I want to make a monthly series out of it, with ts.asfreq(MonthEnd()).
The last date I will obtain is 2011-11-30, but if I want to use this data to calculate returns I do not want to lose data for December and get a MTD return as last datapoint.
So I was wo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/484 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/484/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/484/comments | https://api.github.com/repos/pandas-dev/pandas/issues/484/events | https://github.com/pandas-dev/pandas/issues/484 | 2,540,806 | MDU6SXNzdWUyNTQwODA2 | 484 | Type inference with list of lists in DataFrame constructor | {
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```
In [1216]: l = [[1, 'a'], [2, 'b']]
...: df = DataFrame(data = l, columns = ["num", "str"])
...:
In [1217]: df.dtypes
Out[1217]: num object
str object
```
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https://api.github.com/repos/pandas-dev/pandas/issues/485 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/485/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/485/comments | https://api.github.com/repos/pandas-dev/pandas/issues/485/events | https://github.com/pandas-dev/pandas/issues/485 | 2,541,338 | MDU6SXNzdWUyNTQxMzM4 | 485 | Cython required on install | {
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```
Traceback (most recent call last):
File "test.py", line 2, in <module>
from pandas import DataFrame, Series, read_csv
File "/home/mhar... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/486 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/486/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/486/comments | https://api.github.com/repos/pandas-dev/pandas/issues/486/events | https://github.com/pandas-dev/pandas/issues/486 | 2,549,380 | MDU6SXNzdWUyNTQ5Mzgw | 486 | exception joining dataframes with different datatypes | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2011-12-14T09:48:57Z | 2011-12-15T17:22:57Z | 2011-12-15T17:22:57Z | CONTRIBUTOR | null | In [71]: a=DataFrame(randn(10,2),columns=['a','b'])
In [72]: b=DataFrame(randn(10,1),columns=['c']).astype(np.float32)
## In [73]: a.join(b)
TypeError Traceback (most recent call last)
/Users/c.prinoth/<ipython-input-73-3163f462d6f9> in <module>()
----> 1 a.join(b)
/usr/local/Cellar/p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/487 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/487/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/487/comments | https://api.github.com/repos/pandas-dev/pandas/issues/487/events | https://github.com/pandas-dev/pandas/issues/487 | 2,554,685 | MDU6SXNzdWUyNTU0Njg1 | 487 | nanops on datetime objects failing | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2011-12-14T16:48:19Z | 2011-12-15T04:23:28Z | 2011-12-15T04:23:28Z | NONE | null | Hi,
It looks like apply_along_axis does not play well with objects that have no length? If I go comment out the numpy 1.6.1 workaround in Python 3.x portion, this goes back to working fine.
Thanks!
For example:
> > > import pandas as ps
> > > x = ps.Series([ps.datetime(2011,4,3)])
> > > x.min()
Traceback (most rec... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/488 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/488/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/488/comments | https://api.github.com/repos/pandas-dev/pandas/issues/488/events | https://github.com/pandas-dev/pandas/issues/488 | 2,556,375 | MDU6SXNzdWUyNTU2Mzc1 | 488 | Exception calling to_string on empty Series | {
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"followers_url": "https://api.github.com/users/wesm/... | 3 | 2011-12-14T18:56:00Z | 2013-12-04T00:43:45Z | 2011-12-15T17:38:22Z | NONE | null | from pandas import Series
s = Series({})
s.to_string()
pandas\core\series.pyc in to_string(self, buf,
na_rep, float_format, nanRep)
460 na_rep = nanRep
461
--> 462 the_repr = self._get_repr(float_format=float_format, na_rep=na_rep)
463 if buf is None:
464 return ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/489 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/489/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/489/comments | https://api.github.com/repos/pandas-dev/pandas/issues/489/events | https://github.com/pandas-dev/pandas/issues/489 | 2,556,418 | MDU6SXNzdWUyNTU2NDE4 | 489 | Series.to_string Always Prints Length | {
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"followers_url": "https://api.github.com/users/wesm/... | 3 | 2011-12-14T18:59:52Z | 2011-12-15T14:03:33Z | 2011-12-15T04:40:17Z | NONE | null | We like to use to_string to print the contents of a Series to a buffer. As of 0.6.1, this has started including "\nLength:..." at the end. Could this be an option? It leaves us with no option but to rewrite to_string if we don't want this included.
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https://api.github.com/repos/pandas-dev/pandas/issues/490 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/490/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/490/comments | https://api.github.com/repos/pandas-dev/pandas/issues/490/events | https://github.com/pandas-dev/pandas/issues/490 | 2,557,160 | MDU6SXNzdWUyNTU3MTYw | 490 | can't print embedded ndarray | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2011-12-14T19:49:16Z | 2011-12-15T20:13:46Z | 2011-12-15T20:13:46Z | NONE | null | Just playing with pandas. I was using structured array. I tried converting my structured array to pandas. It was OK, until I tried with a field that was itself a (variable length) ndarray.
arr = np.empty ((len(results),), dtype=[(... various fields ommitted,
```
('err', object),
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https://api.github.com/repos/pandas-dev/pandas/issues/491 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/491/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/491/comments | https://api.github.com/repos/pandas-dev/pandas/issues/491/events | https://github.com/pandas-dev/pandas/issues/491 | 2,560,859 | MDU6SXNzdWUyNTYwODU5 | 491 | Cannot instantiate DataFrame with | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2011-12-14T23:13:22Z | 2013-12-04T00:43:45Z | 2011-12-15T04:05:07Z | NONE | null | from pandas import DataFrame
DataFrame([],[]) # DataFrame([]) does the same thing
pandas\core\frame.pyc in **init**(self, data, index, columns, dtype, copy)
208 copy=copy)
209 elif isinstance(data, list):
--> 210 if isinstance(data[0], (list, tuple))... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/492 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/492/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/492/comments | https://api.github.com/repos/pandas-dev/pandas/issues/492/events | https://github.com/pandas-dev/pandas/issues/492 | 2,564,334 | MDU6SXNzdWUyNTY0MzM0 | 492 | Saving DataFrame with tuple index to HDFStore fails | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2011-12-15T08:52:27Z | 2011-12-15T17:53:24Z | 2011-12-15T17:53:24Z | CONTRIBUTOR | null | The following code fails on pandas 0.6.1
```
import numpy as np
import pandas
col = np.arange(10)
idx = [(0.,1.), (2., 3.), (4., 5.)]
data = np.random.randn(30).reshape((3, 10))
DF = pandas.DataFrame(data, index=idx, columns=col)
H = pandas.HDFStore("test.h5", "w")
H['data'] = DF
H.close()
```
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In [2]: df = DataFrame([1,2,3,4], index=['a','b','c','d'])
In [3]: df
Out[3]:
0
a 1
b 2
c 3
d 4
In [4]: df.dtypes
Out[4]: 0 int64
In [5]: df.dtypes[0]
Out[5]: dtype('int64')
In [6]: df.dtypes[1]
**\* glibc detected **\* /home/adam/.virtualenvs/py27/bin/python: free(): corrup... | {
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pprint(_fields)
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'timescited',
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