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```
from pandas import DataFrame
import matplotlib.pyplot as plt
df = DataFrame({'a': [0, 1], 'b': [1, 0]})
fig = plt.figure()
ax = fig.add_subplot(111)
df.plot(ax=ax, kind='bar')
plt.show()
UnboundLocalError: local variable 'axes' referenced before assignment
```
If the 'ax' parameter is removed, no... | {
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When writing HDF files, pandas tries to convert datetime index values to an ordinal using time.mktime. mktime does not support any dates before 1969.
error output shows the offending line to be:
> File "C:\Python27\lib\site-packages\pandas\io\p... | {
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In [1]: from pandas import DataFrame
In [2]: df = DataFrame({u'c/\u03c3':[1,2,3]})
In [3]: df.to_csv('test')
---------------------------------------------------------------------------
UnicodeEncodeError Traceback (most recent call last)
.../<ipython-input-3-9b2e5ea53beb> in <module>()
----> ... | {
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However, the getting and setting with .ix is not consistent
from pandas imp... | {
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In [11]: t1
Out[11]:
value
id
a 1
b 2
c 3
In [12]: t2
Out[12]:
value
id
a 7
b 8
In [13]: concat([t1, t2], axis=1, keys=['t1', 't2'])
---------------------------------------------------------------------------
Exception Tracebac... | {
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```
In [20]: df
Out[20]:
value
id
t1 a 1
b 2
c 3
t2 a 7
b 8
In [21]: df.ix[:, 'value']
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
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"followers_url": "https://api.github.com/users/wesm/... | 3 | 2012-01-29T13:47:52Z | 2012-02-01T19:51:06Z | 2012-02-01T19:30:57Z | CONTRIBUTOR | null | This is a prototype for functions to work with series of strings. There's a lot more to be done if we like the approach, but I wanted to check in before I spent too much time on it.
You can easily map a function onto a series:
```
In [4]: s = Series(["hi","hoot", "far"])
In [5]: strings.startswith(s, "h")
Out[5]:
0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/712 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/712/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/712/comments | https://api.github.com/repos/pandas-dev/pandas/issues/712/events | https://github.com/pandas-dev/pandas/issues/712 | 3,017,405 | MDU6SXNzdWUzMDE3NDA1 | 712 | Empty DataFrame breaks .pivot_table() | {
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```
df = DataFrame({}, columns=['a', 'b'])
df.pivot_table(rows='a')
```
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```
df = DataFrame({
'x':('a', 'b'),
'y':('A', 'B'),
'i':(1, 2),
})
pivot_table(df, rows='x', cols='y')
y A B
x
a 1.0 NaN
b NaN 2.0
```
Love pandas!
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```
import time
def test_unique(obj):
for n in range(6):
objs = Series([obj] * 10 ** n)
start = time.time()
objs.unique()
stop = time.time()
print('%6.0f %s' % (len(objs), stop - start))
test_unique('a')
1 4.98294830322e-05
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I'm running pandas 0.6.0. (I also checked the latest build on GitHub just in case!)
File "C:/Work/PyCharm/EPD-7.2.1/python/bin/heatmap.py", line 166, in zscore
logger.debug('b:{}'.format(series.mean()))
File "C:\Pytho... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/723 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/723/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/723/comments | https://api.github.com/repos/pandas-dev/pandas/issues/723/events | https://github.com/pandas-dev/pandas/pull/723 | 3,039,158 | MDExOlB1bGxSZXF1ZXN0NzYxNjcz | 723 | BUG: closes #719, check for sortedness of multiindex in to_panel | {
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https://api.github.com/repos/pandas-dev/pandas/issues/724 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/724/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/724/comments | https://api.github.com/repos/pandas-dev/pandas/issues/724/events | https://github.com/pandas-dev/pandas/issues/724 | 3,042,191 | MDU6SXNzdWUzMDQyMTkx | 724 | Integrate numexpr VM to implement fast "where" expressions (as strings) on DataFrame | {
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``` python
In [1]: import pandas
In [2]: pandas.__version__
Out[2]: '0.7.0.dev-e3df4e2'
In [3]: df = pandas.DataFrame({'A': [746.03, 0.00, 5620.00, 1592.36]})
In [4]: df
Out[4]:
A
0 746.
1 0.00
2 5620
3 1592
In [5]:
```
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There's also an accidental end of line whitespace fix from my editor.
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https://api.github.com/repos/pandas-dev/pandas/issues/728 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/728/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/728/comments | https://api.github.com/repos/pandas-dev/pandas/issues/728/events | https://github.com/pandas-dev/pandas/issues/728 | 3,054,576 | MDU6SXNzdWUzMDU0NTc2 | 728 | GCC compiler warnings | {
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```
python setup.py build_ext --inplace
running build_ext
cythoning pandas/src/tseries.pyx to pandas/src/tseries.c
warning: /home/wmckinney/pandas/pandas/src/moments.pyx:486:53: local variable 'ret' referenced before assignment
warning: /home/wmckin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/729 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/729/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/729/comments | https://api.github.com/repos/pandas-dev/pandas/issues/729/events | https://github.com/pandas-dev/pandas/pull/729 | 3,056,200 | MDExOlB1bGxSZXF1ZXN0NzY4MjU0 | 729 | BLD: #728 everything but sandbox builds cleanly | {
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If I run SparseSeries.to_dense().dropna() I get the expected output ie. non-NaN indexes and their values.
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https://api.github.com/repos/pandas-dev/pandas/issues/731 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/731/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/731/comments | https://api.github.com/repos/pandas-dev/pandas/issues/731/events | https://github.com/pandas-dev/pandas/issues/731 | 3,058,293 | MDU6SXNzdWUzMDU4Mjkz | 731 | Add sort option to DataFrame.join | {
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https://api.github.com/repos/pandas-dev/pandas/issues/733 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/733/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/733/comments | https://api.github.com/repos/pandas-dev/pandas/issues/733/events | https://github.com/pandas-dev/pandas/issues/733 | 3,061,194 | MDU6SXNzdWUzMDYxMTk0 | 733 | Improper handling of join keys in MergeOperation | {
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https://api.github.com/repos/pandas-dev/pandas/issues/734 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/734/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/734/comments | https://api.github.com/repos/pandas-dev/pandas/issues/734/events | https://github.com/pandas-dev/pandas/issues/734 | 3,068,075 | MDU6SXNzdWUzMDY4MDc1 | 734 | Change argument name in DataFrame.drop_duplicates | {
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The keyword argument for specifying which columns to consider in drop_duplicates is called col_or_columns. Maybe change the name to col or to columns? Or the strangely long name is intended to make it clear that you can either pass in a label or a sequence of labels?
Thanks,
Marius
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https://api.github.com/repos/pandas-dev/pandas/issues/735 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/735/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/735/comments | https://api.github.com/repos/pandas-dev/pandas/issues/735/events | https://github.com/pandas-dev/pandas/pull/735 | 3,069,740 | MDExOlB1bGxSZXF1ZXN0NzczMzgy | 735 | Excel writing | {
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Added a to_excel method to DataFrame and refactored to_csv to use a helper method that also serves to_excel.
I still need to add some tests, but wanted to get feedback before spending any more time.
There are still some issues, like xlwt throws exceptions when writing np.i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/736 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/736/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/736/comments | https://api.github.com/repos/pandas-dev/pandas/issues/736/events | https://github.com/pandas-dev/pandas/issues/736 | 3,071,249 | MDU6SXNzdWUzMDcxMjQ5 | 736 | Create a generic version of convert_to_annual function in scikits.timeseries | {
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https://api.github.com/repos/pandas-dev/pandas/issues/737 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/737/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/737/comments | https://api.github.com/repos/pandas-dev/pandas/issues/737/events | https://github.com/pandas-dev/pandas/issues/737 | 3,071,338 | MDU6SXNzdWUzMDcxMzM4 | 737 | More NA handling in binary ops with object Series | {
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>>> y = [Decimal('1.3'), Decimal('2.3')]
>>> y2 = [datetime.date(2012,1,1), datetime.date(2012,1,2)]
>>> y3 = Series(y, index=y2)
In [21]: y3 + y3.shift(1)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/home/... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/738 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/738/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/738/comments | https://api.github.com/repos/pandas-dev/pandas/issues/738/events | https://github.com/pandas-dev/pandas/issues/738 | 3,072,538 | MDU6SXNzdWUzMDcyNTM4 | 738 | test_to_csv_unicode fails on python 3.1, 3.2 windows | {
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## ERROR: test_to_csv_unicode (pandas.tests.test_frame.TestDataFrame)
Traceback (most recent call last):
File "c:\python32\lib\site-packages\pandas-0.7.0.dev-py3.2-win-amd64.egg\panda
s\tests\test_frame.py", line 2488, in test_to_csv_unicode
df.to_csv(path, encoding='UTF-8')
File "c:\python32\lib\site-packa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/739 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/739/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/739/comments | https://api.github.com/repos/pandas-dev/pandas/issues/739/events | https://github.com/pandas-dev/pandas/issues/739 | 3,072,615 | MDU6SXNzdWUzMDcyNjE1 | 739 | Add method to sort *within* a single MultiIndex level | {
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https://api.github.com/repos/pandas-dev/pandas/issues/740 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/740/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/740/comments | https://api.github.com/repos/pandas-dev/pandas/issues/740/events | https://github.com/pandas-dev/pandas/issues/740 | 3,073,753 | MDU6SXNzdWUzMDczNzUz | 740 | Maybe add an abs instance method to pandas objects | {
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"gists_... | null | 2 | 2012-02-03T15:18:06Z | 2012-03-01T19:40:11Z | 2012-03-01T19:40:10Z | CONTRIBUTOR | null | Plotting functions work fine if the index holds numeric or date data.
But error is generated when Index holds e.g strings, or when MultiIndex is used.
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df = DataFrame([['b','c','a'],['a','c','b']])
ranked = df..rank(1)
Currently:
ranked = Empty DataFrame
Desired
ranked = a ranked DataFrame (by row) as in the case of DataFrame.rank(1) of dtype = float/int/etc
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https://api.github.com/repos/pandas-dev/pandas/issues/743 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/743/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/743/comments | https://api.github.com/repos/pandas-dev/pandas/issues/743/events | https://github.com/pandas-dev/pandas/issues/743 | 3,092,813 | MDU6SXNzdWUzMDkyODEz | 743 | Empty DataFrame returned when grouping on datetime column | {
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import numpy
import pandas
def simple_test(use_date=True):
data = [
[1, '2012-01-01', 1.0],
[2, '2012-01-02', 2.0],
[3, None, 3.0]
]
if use_date:
data = [[row[0], datetime.datetime.strptime(row[1], '%Y-%m-
%d').date() if row[1] else None, ro... | {
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"f... | 2 | 2012-02-04T17:35:51Z | 2016-03-13T21:30:05Z | 2016-03-13T21:26:33Z | NONE | null | Following up on Wes's email from the pandas group: I was having a problem trying to use converters in "read_table". I have a file that looks like this:
```
id value
a a=0,b=... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/746 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/746/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/746/comments | https://api.github.com/repos/pandas-dev/pandas/issues/746/events | https://github.com/pandas-dev/pandas/issues/746 | 3,096,003 | MDU6SXNzdWUzMDk2MDAz | 746 | Improve docs about filtering | {
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```
Yes. Suppose that function f returns a boolean value given a column
value. To filter you would do:
df[df[column_to_filter_by].map(f)]
oftentimes filtering is using NumPy vector operations like
df[df[column] == val]
but sometimes you have ... | {
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```
dtypes: float64(18), object(1), object(6)
```
In reality first block is `<O8` (unpickled pickle from 32-bit platform) and second block is `|O8` (originated from 64-bit platform)
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https://api.github.com/repos/pandas-dev/pandas/issues/750 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/750/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/750/comments | https://api.github.com/repos/pandas-dev/pandas/issues/750/events | https://github.com/pandas-dev/pandas/pull/750 | 3,096,401 | MDExOlB1bGxSZXF1ZXN0NzgzMjg1 | 750 | BUG: code to address #742, DataFrame.rank | {
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https://api.github.com/repos/pandas-dev/pandas/issues/751 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/751/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/751/comments | https://api.github.com/repos/pandas-dev/pandas/issues/751/events | https://github.com/pandas-dev/pandas/issues/751 | 3,096,439 | MDU6SXNzdWUzMDk2NDM5 | 751 | Speed up DataFrame._get_numeric_data | {
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https://api.github.com/repos/pandas-dev/pandas/issues/752 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/752/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/752/comments | https://api.github.com/repos/pandas-dev/pandas/issues/752/events | https://github.com/pandas-dev/pandas/issues/752 | 3,100,261 | MDU6SXNzdWUzMTAwMjYx | 752 | Preserve dtype of integer join keys | {
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https://api.github.com/repos/pandas-dev/pandas/issues/753 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/753/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/753/comments | https://api.github.com/repos/pandas-dev/pandas/issues/753/events | https://github.com/pandas-dev/pandas/issues/753 | 3,101,194 | MDU6SXNzdWUzMTAxMTk0 | 753 | np.vectorize can cause failures in TextParser if converter returns ints and floats | {
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import StringIO
import numpy as np
import pandas
csv = """\
id,score,days
1,2,12
2,2-5,
3,,14+
4,6-12,2
"""
def convert_days(x):
x = x.strip()
if not x: return np.nan
is_plus = x.endswith('+')
if is_plus:
x = int(x[:-1]) + 1
else:
x = int(x)
return x
def convert_score(x):
x ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/755 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/755/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/755/comments | https://api.github.com/repos/pandas-dev/pandas/issues/755/events | https://github.com/pandas-dev/pandas/issues/755 | 3,109,896 | MDU6SXNzdWUzMTA5ODk2 | 755 | Current git master does not import cleanly if bottleneck is not installed | {
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``` python
try:
import bottleneck as bn
_USE_BOTTLENECK = True
except ImportError: # pragma: no cover
_USE_BOTTLENECK = False
def _bottleneck_switch(bn_name, alt, **kwargs):
try:
bn_func = getattr(bn, bn_name)
```
`b... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/756 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/756/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/756/comments | https://api.github.com/repos/pandas-dev/pandas/issues/756/events | https://github.com/pandas-dev/pandas/issues/756 | 3,117,632 | MDU6SXNzdWUzMTE3NjMy | 756 | DataFrame crashes system | {
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The following:
df = DataFrame(randn(10, 4), columns=['A', 'B', 'C', 'D'])
print df #df.to_string fails also
crashes my system, no error given, simply asked to shut down application.
However:
print df.values
does not. Any help apprecitated.
running:
pandas-0.7.0rc1.win32-py2.6
ActivePython-2.6.7.20-win... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/757 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/757/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/757/comments | https://api.github.com/repos/pandas-dev/pandas/issues/757/events | https://github.com/pandas-dev/pandas/pull/757 | 3,118,073 | MDExOlB1bGxSZXF1ZXN0NzkwNTIy | 757 | Handle subclasses of dicts in DataFrame constructor, with tests | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-02-07T02:09:23Z | 2014-07-24T05:29:24Z | 2012-02-07T23:52:31Z | CONTRIBUTOR | null | Minor change to allow passing subclasses of dict into DataFrame constructor. I assume there is no way to pass these directly to cython, we have to make a copy first?
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https://api.github.com/repos/pandas-dev/pandas/issues/758 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/758/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/758/comments | https://api.github.com/repos/pandas-dev/pandas/issues/758/events | https://github.com/pandas-dev/pandas/issues/758 | 3,121,128 | MDU6SXNzdWUzMTIxMTI4 | 758 | Strange behavior of Series/TimeSeries with datetime index | {
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In [1]: from pandas import *
In [2]: t = [datetime(2012, 2, 7, 0, 0, 0), datetime(2012, 2, 7, 23, 0, 0)]
In [3]: s = Series([0, 1], index=t)
In [4]: print s
2012-02-07 0
2012-02-07 00:00:00 1
The first index value s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/759 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/759/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/759/comments | https://api.github.com/repos/pandas-dev/pandas/issues/759/events | https://github.com/pandas-dev/pandas/issues/759 | 3,126,439 | MDU6SXNzdWUzMTI2NDM5 | 759 | ols summary fails with dtype=object arrays | {
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https://api.github.com/repos/pandas-dev/pandas/issues/760 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/760/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/760/comments | https://api.github.com/repos/pandas-dev/pandas/issues/760/events | https://github.com/pandas-dev/pandas/issues/760 | 3,126,756 | MDU6SXNzdWUzMTI2NzU2 | 760 | Non-matching join operation | {
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"description": "2014-02-3: previous version released",
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"html_url": "https://github.com/pandas-dev/pandas/milestone/24",
"id": 526062,
"labels_url": "htt... | 1 | 2012-02-07T16:37:15Z | 2014-03-09T15:19:59Z | 2014-03-09T15:19:59Z | MEMBER | null | from @yarden on the mailing list
```
Hi,
I have a very common use case which pandas which involve a JOIN
operation related to coordinate arithmetic on two dataframes,
with queries like: for each entry in dataframe A, return all the
entries from dataframe B that have coordinates overlapping with
this entry. This join ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/761 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/761/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/761/comments | https://api.github.com/repos/pandas-dev/pandas/issues/761/events | https://github.com/pandas-dev/pandas/issues/761 | 3,138,025 | MDU6SXNzdWUzMTM4MDI1 | 761 | pandas/tests installed as executables (linux) | {
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"f... | 6 | 2012-02-08T09:22:29Z | 2014-06-03T01:18:06Z | 2014-06-03T01:18:06Z | CONTRIBUTOR | null | Pandas installs its tests now with executable flag. Result is that nosetests skips them and no tests are find.
Running nosetests in the repository itself works fine.
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```
Extracting pandas-0.7.0.dev_6253b07-py2.7-linux-x86_64.egg to /usr/lib64/python2.7/site-packages
SyntaxError: ('invalid syntax', ('/usr/lib64/python2.7/site-packag... | {
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In [116]: ra.ix[:5,:5]
Out[116]:
005665 023740 028758 040828 045449
2011-05-09 NaN NaN NaN NaN NaN
2011-05-10 -0.00284467268624 0.0 0.0 -0.002844627571 0.0003532... | {
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```
In [8]: df
Out[8]:
a b c routine1 routine2 top
result1 result2 result1 OD
wx wy
0 -0.914239... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/768 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/768/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/768/comments | https://api.github.com/repos/pandas-dev/pandas/issues/768/events | https://github.com/pandas-dev/pandas/pull/768 | 3,151,068 | MDExOlB1bGxSZXF1ZXN0ODAyOTg3 | 768 | 'Mixed depth' hierarchical column labels | {
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If column label tuples contain only empty strings at the lower levels, allows the DataFrame to be indexed with only the higher levels. So for example if a column has the hierarchical label ('a'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/769 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/769/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/769/comments | https://api.github.com/repos/pandas-dev/pandas/issues/769/events | https://github.com/pandas-dev/pandas/pull/769 | 3,159,037 | MDExOlB1bGxSZXF1ZXN0ODA1ODAx | 769 | Minor excel stuff | {
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- Put the ExcelWriter in the pandas namespace
- Add sheet_names property to ExcelFile
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```
DateRange("2011-1-1","2012-1-31",offset=DateOffset(months=3))
```
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> > > a = pandas.DateRange('11/30/2011','12/31/2011')
> > > a
> > > <class 'pandas.core.daterange.DateRange'>
> > > offset: <1 BusinessDay>, tzinfo: None
> > > [2011-11-30 00:00:00, ..., 2011-12-30 00:00:00]... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/772 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/772/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/772/comments | https://api.github.com/repos/pandas-dev/pandas/issues/772/events | https://github.com/pandas-dev/pandas/pull/772 | 3,167,966 | MDExOlB1bGxSZXF1ZXN0ODA5NjEw | 772 | Add _repr_html method to make DataFrames nice in IPython notebook. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/773 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/773/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/773/comments | https://api.github.com/repos/pandas-dev/pandas/issues/773/events | https://github.com/pandas-dev/pandas/pull/773 | 3,177,460 | MDExOlB1bGxSZXF1ZXN0ODEyODE0 | 773 | unify API in regards to column-vs-columns | {
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```
$> git grep 'def.*column='
pandas/core/frame.py: def boxplot(self, column=None, by=None, ax=None, fontsize=None,
pandas/stats/misc.py:def percentileRank(frame, column=None, kind='mean'):
pandas/tools/plotting.py:def boxplot(data, column=None, by=None... | {
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In pandas 0.6.1:
In [13]: pandas.version.version
Out[13]: '0.6.1'
In [14]: pandas.DataFrame(['\xc2'])
Out[14]:
0
0 ┬
In pandas 0.7.0:
In [2]: pandas.version.version
Out[2]: '0.7.0'
In [3]: pandas.DataFrame(['\xc2'])
.....
C:\Python26\lib\site-packages\pa... | {
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```
import datetime
import numpy
import pandas
def simple_test2():
data = [
[1, 'string1', 1.0],
[2, 'string2', 2.0],
[3, None, 3.0]
]
df = pandas.DataFrame({'key': [x[0] for x ... | {
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```
ticker date pnl mv
0 aapl 01/01/12 100 1000
1 aapl 01/02/12 -50 950
2 aapl 01/03/12 200 1150
3 goog 01/01/12 100 2000
4 goog 01/02/12 100 2100
5 goog 01/03/12 -50 2050
6 goog 01/04/12 -50 200
```
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In [2]: index = [52195.504153, 52196.303147, 52198.369883]
In [3]: a = pandas.DataFrame(randn(3, 2), index)
In [4]: a
Out[4]:
0 1
52195.504153 1.367681 0.243237
52196.303147 -0.745796 -1.054106
52198.369883 -1.462461 -0.683286
In [5]: a.ix[52195.:52196.]
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```
df = DataFrame(index=[0], columns=['A', 'B', 'C'])
df3 = DataFrame(index=[1, 2], columns=['A', 'B'])
df5 = df.append(df3)
expected = DataFrame({'A': [nan, nan, nan],
'B': [nan, nan, nan],
'C': [nan, nan, nan]})
```
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```
df = DataFrame(index=np.arange(100))
for i in range(5000):
df[i] = 5
```
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In [9]: df = read_clipboard(header=None, sep='\s+')
In [10]: df
Out[10]: ---------------------------------------------------------------------------
UnicodeDecodeError Traceback (most recent call last)
/Users/wesm/<ipython-input-10-7ed0097d7e9e> in <module>()
----> 1 df
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https://api.github.com/repos/pandas-dev/pandas/issues/797 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/797/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/797/comments | https://api.github.com/repos/pandas-dev/pandas/issues/797/events | https://github.com/pandas-dev/pandas/issues/797 | 3,265,018 | MDU6SXNzdWUzMjY1MDE4 | 797 | Panel constructor ignores dtype | {
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In [27]: a=Panel(items=range(2),major_axis=range(10),minor_axis=range(5),dtype=np.float32)
In [28]: a[0].dtypes
Out[28]:
0 float64
1 float64
2 float64
3 float64
4 float64
A quick debug shows that the routine form_blocks ju... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/799 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/799/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/799/comments | https://api.github.com/repos/pandas-dev/pandas/issues/799/events | https://github.com/pandas-dev/pandas/issues/799 | 3,277,225 | MDU6SXNzdWUzMjc3MjI1 | 799 | read_csv delimiter auto-detection no longer works | {
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