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https://api.github.com/repos/pandas-dev/pandas/issues/1501 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1501/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1501/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1501/events | https://github.com/pandas-dev/pandas/pull/1501 | 5,169,333 | MDExOlB1bGxSZXF1ZXN0MTYwNzY3MQ== | 1,501 | Probability plot | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1502 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1502/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1502/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1502/events | https://github.com/pandas-dev/pandas/issues/1502 | 5,174,312 | MDU6SXNzdWU1MTc0MzEy | 1,502 | Performance of adding columns to DataFrame | {
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``` python
import numpy as np
import pandas
import time
values = np.random.randn(100)
t0 = time.time()
columns = [valu... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1503 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1503/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1503/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1503/events | https://github.com/pandas-dev/pandas/issues/1503 | 5,178,757 | MDU6SXNzdWU1MTc4NzU3 | 1,503 | Improve repr for weekly Periods | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-06-20T19:39:56Z | 2012-07-13T01:35:24Z | 2012-07-13T01:35:24Z | NONE | null | It's totally possible I don't understand how to_timestamp should be used with a Period. But, I have a hunch there is a bug here.
```
In : p = Period('01-Jan-2012', 'W')
In : p.to_timestamp(how='E')
Out: <Timestamp: 2012-01-01 00:00:00>
In : p.to_timestamp('H', how='E')
Out: <Timestamp: 2012-01-01 23:00:00>
```
(foun... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1504 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1504/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1504/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1504/events | https://github.com/pandas-dev/pandas/issues/1504 | 5,181,091 | MDU6SXNzdWU1MTgxMDkx | 1,504 | Faster rolling_min/rolling_max | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-06-20T21:29:22Z | 2012-07-12T16:50:50Z | 2012-07-12T16:50:35Z | NONE | null | See #50
Using a `min-heap` and `max-heap` to implement the `rolling_min` and `rolling_max` functions seems to be about 30% faster than the current implementation.
Something sort of like this:
``` python
from heapq import heappush, heapify
from numpy import empty, nan
cimport numpy as np
cdef extern from "math.h":... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1505 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1505/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1505/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1505/events | https://github.com/pandas-dev/pandas/issues/1505 | 5,190,505 | MDU6SXNzdWU1MTkwNTA1 | 1,505 | itertuples converts int to float for all numeric rows. | {
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from pandas import *
x = DataFrame([(1,3,4.5,6.5), (1,3,4.5,6.5)])
print x
print x.dtypes
for row in x.itertuples():
print row
0 1 2 3
0 1 3 4.5 6.5
1 1 3 4.5 6.5
0 int64
1 int64
2 float64
3 float64
(0, 1.0, 3.0, 4.5, 6.5)
(1, 1.0, 3.0, 4.5, 6.5)
```
mixed dtype row leaves in... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1506 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1506/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1506/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1506/events | https://github.com/pandas-dev/pandas/issues/1506 | 5,191,592 | MDU6SXNzdWU1MTkxNTky | 1,506 | DataFrame.boxplot() NaN handling | {
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"followers_url": "https://api.github.com/users/wesm/... | 0 | 2012-06-21T12:25:26Z | 2012-06-22T14:29:11Z | 2012-06-22T14:29:11Z | CONTRIBUTOR | null | In case of NaN, `DataFrame.boxplot()` produces unexpected plot (see below df2, column A boxplot).
It is matplotlib related (using version 1.1.0).
``` python
In [248]: df = pandas.DataFrame(np.random.randn(1000,2), columns=['A', 'B'])
In [249]: df.describe()
Out[249]:
A B
count 1000.000000... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1507 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1507/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1507/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1507/events | https://github.com/pandas-dev/pandas/issues/1507 | 5,191,974 | MDU6SXNzdWU1MTkxOTc0 | 1,507 | DataFrameGroupBy.boxplot() should not relay to DataFrame.boxplot() | {
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Since `DataFrameGroupby.boxplot()` relays boxplot to `DataFrame.boxplot()`, one ends up with one messy plot.
See [screenshot](https://lh6.googleusercontent.com/-Ax6O9Be-VLQ/T-MYeSyB7VI/AAAAAAAAANs/fGzupMhexw8/s583/issue1507_screenshot1.p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1508 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1508/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1508/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1508/events | https://github.com/pandas-dev/pandas/issues/1508 | 5,196,696 | MDU6SXNzdWU1MTk2Njk2 | 1,508 | na_option is not used in DataFrame.rank() | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1509 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1509/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1509/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1509/events | https://github.com/pandas-dev/pandas/issues/1509 | 5,207,904 | MDU6SXNzdWU1MjA3OTA0 | 1,509 | legend for plots with secondary axis | {
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"followers_url": "https://api.github.com/users/wesm/... | 4 | 2012-06-22T03:40:12Z | 2012-07-19T19:35:43Z | 2012-07-19T19:35:43Z | CONTRIBUTOR | null | need to get all the lines and labels and pass to the same axes
maybe need to have ax and twinx keep references to each other
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https://api.github.com/repos/pandas-dev/pandas/issues/1510 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1510/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1510/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1510/events | https://github.com/pandas-dev/pandas/issues/1510 | 5,217,005 | MDU6SXNzdWU1MjE3MDA1 | 1,510 | Gap freq inference for ts plotting | {
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"f... | 1 | 2012-06-22T15:03:54Z | 2020-05-03T21:04:04Z | 2020-05-03T21:04:03Z | CONTRIBUTOR | null | 1. explicit: user supplies timedelta defining the maximum distance between points that should be interpolated.
2. implicit: computes GCF for all unique timedeltas in the index and use that to get the regularized frequency.
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https://api.github.com/repos/pandas-dev/pandas/issues/1511 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1511/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1511/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1511/events | https://github.com/pandas-dev/pandas/issues/1511 | 5,219,838 | MDU6SXNzdWU1MjE5ODM4 | 1,511 | Inconsistent Behavior of cut when labels=False | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-06-22T17:22:40Z | 2012-06-28T22:40:21Z | 2012-06-28T22:40:21Z | CONTRIBUTOR | null | ``` python
s = Series([0, -1, 0, 1, -3])
ind, label = cut(s, [-4, 0, 1], retbins=True, labels=False)
# label [-4 0 1]
# ind array([0, 0, 0, 1, 0])
s = Series([0, -1, 0, 1, -3])
ind, label = cut(s, [0, 1], retbins=True, labels=False)
# label [0 1]
# ind array([ nan, nan, nan, 1., nan])
# Should the 1 be a 0?
``... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1512 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1512/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1512/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1512/events | https://github.com/pandas-dev/pandas/issues/1512 | 5,220,131 | MDU6SXNzdWU1MjIwMTMx | 1,512 | add ability to read Stata files | {
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"html_url": "https://github.com/pandas-dev/pandas/milestone/22",
"i... | 2 | 2012-06-22T17:38:58Z | 2013-05-18T00:51:49Z | 2013-05-18T00:45:46Z | CONTRIBUTOR | null | Note to self. I think it makes sense to move or copy the Stata file handling from statsmodels to pandas rather than having a return_pandas option in statsmodels. DataFrame.from_dta would be helpful.
https://github.com/statsmodels/statsmodels/blob/master/statsmodels/iolib/foreign.py
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https://api.github.com/repos/pandas-dev/pandas/issues/1513 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1513/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1513/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1513/events | https://github.com/pandas-dev/pandas/issues/1513 | 5,220,633 | MDU6SXNzdWU1MjIwNjMz | 1,513 | DataFrame.drop loses MultiIndex | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-06-22T18:06:09Z | 2012-06-22T19:27:26Z | 2012-06-22T19:26:59Z | NONE | null | ```
In [2]: df = DataFrame({'a': [1,2,3], 'b': [1,2,3], 'c': [4,5,6]})
In [3]: df.set_index(['a','b'], inplace=True)
Out[3]:
c
a b
1 1 4
2 2 5
3 3 6
In [5]: dropped = df.drop((1,1))
In [6]: dropped
Out[6]:
c
2 2 5
3 3 6
```
MultiIndex is gone! (2,2) and (3,3) are now plain tuples
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https://api.github.com/repos/pandas-dev/pandas/issues/1514 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1514/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1514/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1514/events | https://github.com/pandas-dev/pandas/issues/1514 | 5,221,508 | MDU6SXNzdWU1MjIxNTA4 | 1,514 | Signal Processing in pandas | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1515 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1515/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1515/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1515/events | https://github.com/pandas-dev/pandas/issues/1515 | 5,226,215 | MDU6SXNzdWU1MjI2MjE1 | 1,515 | pandas take or .ix[] breaks iterrows indexing | {
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In [20]: df = pandas.DataFrame(np.random.rand(5,2))
In [21]: df
Out[21]:
0 1
0 0.854891 0.303209
1 0.460207 0.661508
2 0.534319 0.626693
3 0.504076 0.693567
4 0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1517 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1517/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1517/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1517/events | https://github.com/pandas-dev/pandas/issues/1517 | 5,232,691 | MDU6SXNzdWU1MjMyNjkx | 1,517 | Plotting both fixed frequency and irregular time series on same subplot fails | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1518 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1518/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1518/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1518/events | https://github.com/pandas-dev/pandas/issues/1518 | 5,235,948 | MDU6SXNzdWU1MjM1OTQ4 | 1,518 | Time zone handling / strftime issues | {
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http://stackoverflow.com/questions/11175213/pandas-read-csv-input-local-datetime-strings-tz-convert-to-utc
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#1517
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https://api.github.com/repos/pandas-dev/pandas/issues/1520 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1520/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1520/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1520/events | https://github.com/pandas-dev/pandas/issues/1520 | 5,239,012 | MDU6SXNzdWU1MjM5MDEy | 1,520 | HDFStore casting all numeric columns to datetime | {
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```
print df.dtypes
0 int64
1 int64
2 object
3 object
4 object
5 object
6 datetime64[ns]
7 float64
8 int64
9 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1521 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1521/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1521/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1521/events | https://github.com/pandas-dev/pandas/pull/1521 | 5,239,104 | MDExOlB1bGxSZXF1ZXN0MTYzNzU5OA== | 1,521 | BUG: HDFStore converting all to datetime64 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1526 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1526/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1526/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1526/events | https://github.com/pandas-dev/pandas/pull/1526 | 5,249,273 | MDExOlB1bGxSZXF1ZXN0MTY0MTU2OA== | 1,526 | ENH: Add raise on conflict keyword to update | {
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Could this be possible?
I saw that xlrd had `fi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1530 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1530/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1530/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1530/events | https://github.com/pandas-dev/pandas/issues/1530 | 5,263,776 | MDU6SXNzdWU1MjYzNzc2 | 1,530 | build issues on osx 10.6.8 | {
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] | closed | false | null | [] | null | 2 | 2012-06-26T02:33:46Z | 2012-06-26T19:05:42Z | 2012-06-26T19:05:42Z | NONE | null | I have python 2.6, and i'm on osx 10.6.8
when I try installing with pip or building from source (latest from git and latest stable release), i get error messages to the tune of:
```
python setup.py build
...
building 'pandas._algos' extension
creating build/temp.macosx-10.6-universal-2.6
creating build/temp.macosx-10... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1531 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1531/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1531/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1531/events | https://github.com/pandas-dev/pandas/issues/1531 | 5,273,836 | MDU6SXNzdWU1MjczODM2 | 1,531 | arrays of datetime.time() objects don't convert into TimeSeries | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1532 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1532/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1532/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1532/events | https://github.com/pandas-dev/pandas/issues/1532 | 5,276,302 | MDU6SXNzdWU1Mjc2MzAy | 1,532 | Segmentation fault with MultiIndex join() | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-06-26T15:31:03Z | 2012-06-28T18:21:47Z | 2012-06-28T18:21:47Z | NONE | null | With pandas from the current master branch and python-3.2.2, I'm getting a seg fault with the following minimal example:
```
df1 = pandas.DataFrame({'a': [1, 1], 'b': [1, 2], 'x': [1, 2]})
df2 = pandas.DataFrame({'a': [2, 2], 'b': [1, 2], 'y': [1, 2]})
df1 = df1.set_index(['a', 'b'])
df2 = df2.set_index(['a', 'b'])
df... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1533 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1533/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1533/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1533/events | https://github.com/pandas-dev/pandas/issues/1533 | 5,277,114 | MDU6SXNzdWU1Mjc3MTE0 | 1,533 | Assigning to a sliced a Panel | {
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"followers_url": "https://api.github.com/users/wesm/... | 4 | 2012-06-26T16:06:41Z | 2013-10-04T15:28:52Z | 2012-06-29T14:39:49Z | CONTRIBUTOR | null | Suppose I have:
a=Panel(items=[1,2,3],major_axis=[11,22,33],minor_axis=[111,222,333])
b=DataFrame(randn(2,3),index=[111,333],columns=[1,2,3])
I get an error when trying to assign b to a slice of a:
## a.ix[:,22,[111,333]]=b
ValueError Traceback (most recent call last)
<ipython-input-34... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1534 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1534/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1534/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1534/events | https://github.com/pandas-dev/pandas/issues/1534 | 5,281,155 | MDU6SXNzdWU1MjgxMTU1 | 1,534 | MultiIndex.from_tuples issue | {
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```
import pandas
mix = pandas.MultiIndex.from_tuples([('1a', '2a'), ('1a', '2b'), ('1a', '2c'), ('1b', '2d')])
df = pandas.DataFrame([[1,2,3,4],[5,6,7,8]], columns=mix)
#... manipulate columns here ... but not required to raise error here
df.columns = pandas.MultiIndex.from_tuples(df.colu... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1535 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1535/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1535/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1535/events | https://github.com/pandas-dev/pandas/pull/1535 | 5,281,633 | MDExOlB1bGxSZXF1ZXN0MTY1NTg5NA== | 1,535 | ENH: implement DataFrameGroupBy.boxplot(), close #1507 | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-06-26T19:28:48Z | 2014-07-15T10:14:51Z | 2012-06-29T00:16:09Z | CONTRIBUTOR | null | I noticed this was marked for milestone 0.9.0, so a pull request iso push myself.
I know plenty of goodies are on it`s way for plotting, so this might be a temporary solution (it is not my intention to run in the way of @orbitfold).
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https://api.github.com/repos/pandas-dev/pandas/issues/1536 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1536/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1536/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1536/events | https://github.com/pandas-dev/pandas/issues/1536 | 5,285,782 | MDU6SXNzdWU1Mjg1Nzgy | 1,536 | index_col parser bug | {
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In [10]: !cat book_scripts/io/ex2.csv
1,2,3,4,hello
5,6,7,8,world
9,10,11,12,foo
In [11]: names
Out[11]: ['a', 'b', 'c', 'd', 'message']
In [12]: read_csv('book_scripts/io/ex2.csv', names=names, index_col=['message'])
Out[12]:
a b c d
message
hello 1 2 3 4
world 5 6 7... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1537 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1537/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1537/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1537/events | https://github.com/pandas-dev/pandas/issues/1537 | 5,294,266 | MDU6SXNzdWU1Mjk0MjY2 | 1,537 | Problem when setting values based on MultiIndex subset | {
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from pandas import *
test = read_csv('/home/arthur/transform_issue.csv')
x =test.groupby(['A','B','C'])['revenues'].first().index
test.set_index(['A','B','C'], inplace=True)
test.ix[x]['revenues']= 999.99
print test.ix[x].shape
print test[test.revenues==999.99]
(127, 5)
Empty DataFrame
Columns: array([D, E, week,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1538 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1538/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1538/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1538/events | https://github.com/pandas-dev/pandas/issues/1538 | 5,298,532 | MDU6SXNzdWU1Mjk4NTMy | 1,538 | Add print option to not sparsify hierarchical levels | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1540 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1540/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1540/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1540/events | https://github.com/pandas-dev/pandas/issues/1540 | 5,299,600 | MDU6SXNzdWU1Mjk5NjAw | 1,540 | DataFrame.plot doesn't use kwarg color properly | {
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A quick workaround, in plotting.py, line 716, replace
if 'color' not in kwds:
kwds['color']... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1541 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1541/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1541/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1541/events | https://github.com/pandas-dev/pandas/pull/1541 | 5,302,296 | MDExOlB1bGxSZXF1ZXN0MTY2NTMwMA== | 1,541 | ENH: datetime.time converters for plotting | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1542 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1542/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1542/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1542/events | https://github.com/pandas-dev/pandas/issues/1542 | 5,303,780 | MDU6SXNzdWU1MzAzNzgw | 1,542 | Docs from 0.7.3 are pointing to 0.8.0rc2 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1543 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1543/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1543/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1543/events | https://github.com/pandas-dev/pandas/issues/1543 | 5,306,216 | MDU6SXNzdWU1MzA2MjE2 | 1,543 | Support for bimonthly/weekly timerules | {
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I could probably do this.
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https://api.github.com/repos/pandas-dev/pandas/issues/1545 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1545/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1545/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1545/events | https://github.com/pandas-dev/pandas/issues/1545 | 5,328,065 | MDU6SXNzdWU1MzI4MDY1 | 1,545 | Can not pip install git+: generated.c: No such file or directory | {
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<snip>
gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fPIC -I/local/lib/python2.7/site-packages/numpy/core/include -I/usr/include/python2.7 -c pandas/src/generated.c -o build/temp.linux-i686-2.7/pandas/src/generated.o
gcc: ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1546 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1546/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1546/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1546/events | https://github.com/pandas-dev/pandas/issues/1546 | 5,329,985 | MDU6SXNzdWU1MzI5OTg1 | 1,546 | nosetests: algorithms.py:125: RuntimeWarning: tp_compare didn't return -1 or -2 for exception | {
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C:\Python27\lib\site-packages\pandas\core\algorithms.py:125: RuntimeWarning: tp_compare didn't return -1 or -2 for exception
sorter = uniques.argsort()
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https://api.github.com/repos/pandas-dev/pandas/issues/1547 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1547/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1547/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1547/events | https://github.com/pandas-dev/pandas/issues/1547 | 5,347,238 | MDU6SXNzdWU1MzQ3MjM4 | 1,547 | cannot use trace routines with Pandas | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-06-29T09:17:25Z | 2012-06-29T14:54:50Z | 2012-06-29T14:54:50Z | NONE | null | Because of the way local variables are used in read_cvs, setting a tracing routine will fail at that point. Here is a test case with an arbitrarily simple tracing routine:
```
def trace_memory_usage(frame, event, arg):
return trace_memory_usage
import sys
sys.settrace(trace_memory_usage)
if __name__ == '__main__... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1548 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1548/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1548/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1548/events | https://github.com/pandas-dev/pandas/issues/1548 | 5,347,433 | MDU6SXNzdWU1MzQ3NDMz | 1,548 | matplotlib.pyplot called on import pandas on trunk | {
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"followers_url": "https://api.github.com/users/wesm/... | 3 | 2012-06-29T09:30:33Z | 2012-06-29T14:40:29Z | 2012-06-29T14:40:29Z | CONTRIBUTOR | null | the call added in https://github.com/pydata/pandas/commit/61aac3d0a98f748fd9fd4df9df0ef4bd8849f9b5
added an import of tseries.converter from tools\plotting.py
which in turn loads matplotlib:
from matplotlib import pylab
in rc2, the following worked:
import pandas
import matplotlib
matplotlib.use('qt4agg')
in trunk:
W... | {
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Test environment: http://www.lfd.uci.edu/~gohlke/pythonlibs/tests/20120629-win-amd64-py3.2/versions.txt
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```
read_csv(StringIO('1,2'), names=['a', 'b'], sep=None))
Traceback (most recent call last):
...
StopIteration
```
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Please strike items through after a release has implemented a feature stated.
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to
http://docs.python.org/library/csv.html#csv.Dialect
using intersphinx
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http://pandas.pydata.org/pandas-docs/dev/whatsnew.html
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$ python3 setup.py build
$ python3 setup.py install
Everything appears to run normally, but when I run
import pandas
in IDLE, it tells me there is no pandas module. What could be the problem... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1560 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1560/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1560/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1560/events | https://github.com/pandas-dev/pandas/issues/1560 | 5,390,299 | MDU6SXNzdWU1MzkwMjk5 | 1,560 | MultiIndex fails when passed a numpy.int64 index element instead of an int | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-07-02T16:51:51Z | 2012-07-11T23:45:32Z | 2012-07-11T23:45:32Z | NONE | null | MultiIndex does not behave as expected anymore on 0.8.0 (I'm on Python 3.2.3). In particular, I get a strange error when I pass in an np.int64 object (i.e. the same type as the first level of the index). I hope the following testcase is clear, tried to stick close to the MultiIndex example in the docs.
Code:
```
fro... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1561 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1561/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1561/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1561/events | https://github.com/pandas-dev/pandas/issues/1561 | 5,398,581 | MDU6SXNzdWU1Mzk4NTgx | 1,561 | datetime64 bug arising in Series.set_value | {
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```
Hi guys,
I am using the new release 0.8.0. Below is what I observed. My numpy
version if 1.6.2. Please help. thx.
In [3]: from pandas import Series
In [4]: from datetime import datetime
In [5]: s = Series().set_value(datetime(2001,1,1),
1.).set_value(datetime(2001,1,2),float('nan'))
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https://api.github.com/repos/pandas-dev/pandas/issues/1562 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1562/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1562/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1562/events | https://github.com/pandas-dev/pandas/issues/1562 | 5,407,697 | MDU6SXNzdWU1NDA3Njk3 | 1,562 | Date slicing bug | {
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http://stackoverflow.com/questions/11306167/pandas-slicing-on-a-timeseries-seems-inconsistent-with-list-slicing
```
import pandas as pd
import datetime
times = [datetime.datetime(2000, 1, 1) + datetime.timedelta(minutes=i) for i in range(1000000)]
df = pd.TimeSeries(range(1000000), times)
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https://api.github.com/repos/pandas-dev/pandas/issues/1563 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1563/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1563/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1563/events | https://github.com/pandas-dev/pandas/issues/1563 | 5,408,315 | MDU6SXNzdWU1NDA4MzE1 | 1,563 | Convenience function for timeseries | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-07-03T14:37:18Z | 2012-07-13T01:30:12Z | 2012-07-13T01:30:12Z | CONTRIBUTOR | null | from pydata mailing list:
just wondering if there is a more convenient way to convert the new Period /
PeriodIndex classes to datetime objects. As well as converting into lists of
tuples to insert into sql databases.
For example:
import pandas as pd
prng = pd.period_range('2012-01', periods = 12, freq = 'M')
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https://api.github.com/repos/pandas-dev/pandas/issues/1564 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1564/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1564/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1564/events | https://github.com/pandas-dev/pandas/pull/1564 | 5,413,628 | MDExOlB1bGxSZXF1ZXN0MTcwODc5OQ== | 1,564 | ENH: per column styles to plot | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1565 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1565/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1565/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1565/events | https://github.com/pandas-dev/pandas/pull/1565 | 5,414,362 | MDExOlB1bGxSZXF1ZXN0MTcwOTE3NA== | 1,565 | BUG: no longer ignore given axes in boxplot | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1566 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1566/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1566/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1566/events | https://github.com/pandas-dev/pandas/pull/1566 | 5,416,470 | MDExOlB1bGxSZXF1ZXN0MTcxMDIxMw== | 1,566 | Radviz | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1567 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1567/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1567/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1567/events | https://github.com/pandas-dev/pandas/issues/1567 | 5,419,513 | MDU6SXNzdWU1NDE5NTEz | 1,567 | read_csv: na_values=dict and index_col don't play nice together | {
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```
In [1]: import pandas
In [3]: import StringIO
In [4]: pandas.read_csv(StringIO.StringIO("a,b\n0,NA\n"), na_values={}, index_col=0)
---------------------------------------------------------------------------
TypeError ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1568 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1568/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1568/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1568/events | https://github.com/pandas-dev/pandas/issues/1568 | 5,430,668 | MDU6SXNzdWU1NDMwNjY4 | 1,568 | sum with level=0 of MultiIndex with Series length 1 failing | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-07-04T16:08:40Z | 2012-07-11T23:08:45Z | 2012-07-11T23:08:29Z | CONTRIBUTOR | null | pandas.Series([10.0], index=pandas.MultiIndex.from_tuples([(2, 3)])).sum(level=0) #level=None works, series length > 1 works
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https://api.github.com/repos/pandas-dev/pandas/issues/1569 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1569/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1569/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1569/events | https://github.com/pandas-dev/pandas/issues/1569 | 5,431,290 | MDU6SXNzdWU1NDMxMjkw | 1,569 | Allow dropping (without losing) and adding levels to MultiIndex | {
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similar to reset_index I want to be able to drop a level from a MultiIndex that then enters the columns again. similarly I want to be able to move a column to the MultiIndex.
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https://api.github.com/repos/pandas-dev/pandas/issues/1570 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1570/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1570/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1570/events | https://github.com/pandas-dev/pandas/issues/1570 | 5,431,637 | MDU6SXNzdWU1NDMxNjM3 | 1,570 | monthly periods prior to dec-1969 off by one year | {
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# version 0.8.0 of pandas
# version 1.6.1 of numpy
# windows XP 32-bit
>>> import pandas as pd
>>> pd.Period('1969-12', 'M')
Period('Dec-1969', 'M')
>>> pd.Period('1969-11', 'M')
Period('Nov-1970', 'M')
</pre>
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https://api.github.com/repos/pandas-dev/pandas/issues/1571 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1571/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1571/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1571/events | https://github.com/pandas-dev/pandas/issues/1571 | 5,460,694 | MDU6SXNzdWU1NDYwNjk0 | 1,571 | to_datetime poor performance parsing string datetimes | {
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I want to convert to datetime64 a Series that contains datetimes as strings. The format is '%Y-%m-%d %H:%M:%S' ('2012-07-06 10:05:58', for instance).
Casting the strings array into a datetime64 array in numpy (or using Series.astype("datetime64")) is fast, but it transforms the datetimes according to the local ti... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1572 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1572/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1572/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1572/events | https://github.com/pandas-dev/pandas/issues/1572 | 5,464,224 | MDU6SXNzdWU1NDY0MjI0 | 1,572 | DataFrame.__init__(..., dtype=dt) makes unnecessary copies | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-07-06T12:39:44Z | 2012-07-11T23:55:40Z | 2012-07-11T23:55:08Z | NONE | null | If I have a DataFrame `df` with homogenous type, then `DataFrame(df)` returns a view on the original dataframe. `DataFrame(df, dtype=current_type)` should be identical; but, instead, it makes an unnecessary copy.
```
>>> import pandas
>>> pandas.__version__
'0.8.0'
>>> df = pandas.DataFrame([[1, 2]])
>>> df
0 1
0 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1573 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1573/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1573/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1573/events | https://github.com/pandas-dev/pandas/issues/1573 | 5,465,176 | MDU6SXNzdWU1NDY1MTc2 | 1,573 | Inconsistent date range behaviour | {
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"closed_at": "2018-05-16T03:09:58Z",
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works, but not
pandas.DatetimeIndex(start=datetime.datetime(2012, 2, 20), freq=pandas.offsets.MonthEnd(day=20), periods=10)
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https://api.github.com/repos/pandas-dev/pandas/issues/1574 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1574/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1574/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1574/events | https://github.com/pandas-dev/pandas/issues/1574 | 5,469,225 | MDU6SXNzdWU1NDY5MjI1 | 1,574 | Negative indexing into Series in 0.8.0 | {
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In [3]: ser = pandas.Series( ['A','B','C'] )
```
In [4]: ser
Out[4]:
0 A
1 B
2 C
In [5]: ser[1]
Out[5]: 'B'
In [6]: ser[-1]
-------------------------------------------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1575 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1575/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1575/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1575/events | https://github.com/pandas-dev/pandas/issues/1575 | 5,469,227 | MDU6SXNzdWU1NDY5MjI3 | 1,575 | Negative indexing into Series in 0.8.0 | {
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In [3]: ser = pandas.Series( ['A','B','C'] )
```
In [4]: ser
Out[4]:
0 A
1 B
2 C
In [5]: ser[1]
Out[5]: 'B'
In [6]: ser[-1]
-------------------------------------------------------... | {
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Out[18]:
MultiIndex
[(0.12609189981717644, 1.103678121647419)
(0.34279706720294867, -0.7021022763765951)
(1.4611933034915323, -0.9892166873678242)
(-1.8708717491582252, 1.0296013286162102)
In [19]: len(idx.tolist())
Out[19]: 0
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https://api.github.com/repos/pandas-dev/pandas/issues/1577 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1577/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1577/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1577/events | https://github.com/pandas-dev/pandas/pull/1577 | 5,475,320 | MDExOlB1bGxSZXF1ZXN0MTczNjk5Mw== | 1,577 | Reset level | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1578 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1578/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1578/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1578/events | https://github.com/pandas-dev/pandas/issues/1578 | 5,476,452 | MDU6SXNzdWU1NDc2NDUy | 1,578 | Series(series) discards name attribute | {
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```
>>> import pandas
>>> pandas.__version__
'0.8.0'
>>> s = pandas.Series([1, 2, 3], index=[4, 5, 6], name="NAME")
>>> s
4 1
5 2
6 3
Name: NAME
>>> pandas.Series(s)
4 1
5 2
6 3
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1579 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1579/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1579/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1579/events | https://github.com/pandas-dev/pandas/issues/1579 | 5,481,307 | MDU6SXNzdWU1NDgxMzA3 | 1,579 | Improve time series plotting performance | {
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I am trying to use the plot method of series in pandas 8.0 to graph minutely data that is several years long. This can take 30 seconds to display because of the processing of the datetime index. I was thinking instead of using matplotlibs plot_date function for large series which seems... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1580 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1580/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1580/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1580/events | https://github.com/pandas-dev/pandas/issues/1580 | 5,482,746 | MDU6SXNzdWU1NDgyNzQ2 | 1,580 | Weird results grouping data by day | {
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amounts from following csv file are grouped by date, but the sums for some days
are wrong:
2011-02-02 resulting: 0 correct: 40
2011-08-21 resulting: 3 correct: 133
2012-10-22 resulting: 157 correct: 27
This is the script I am running:
``` p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1581 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1581/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1581/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1581/events | https://github.com/pandas-dev/pandas/issues/1581 | 5,487,595 | MDU6SXNzdWU1NDg3NTk1 | 1,581 | No datetime64 DataFrame column conversion of datetime.datetime with tzinfo | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1582 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1582/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1582/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1582/events | https://github.com/pandas-dev/pandas/issues/1582 | 5,487,627 | MDU6SXNzdWU1NDg3NjI3 | 1,582 | to_panel issues with integers | {
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http://stackoverflow.com/questions/11329611/python-pandas-to-panel-from-dataframe-returns-weird-numbers-for-binary-variab
pm10 = pds.read_csv('pm10.csv', index_col = [0,1], parse_dates=True)
panel_exog = pm10.to_panel()['pass_ind']
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https://api.github.com/repos/pandas-dev/pandas/issues/1583 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1583/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1583/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1583/events | https://github.com/pandas-dev/pandas/issues/1583 | 5,488,292 | MDU6SXNzdWU1NDg4Mjky | 1,583 | DataFrame.to_csv with no "leading comma" option | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1584 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1584/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1584/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1584/events | https://github.com/pandas-dev/pandas/issues/1584 | 5,488,501 | MDU6SXNzdWU1NDg4NTAx | 1,584 | Add option to disable adjustment factor in EWMA | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1585 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1585/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1585/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1585/events | https://github.com/pandas-dev/pandas/issues/1585 | 5,489,719 | MDU6SXNzdWU1NDg5NzE5 | 1,585 | Cannot slice a SparseDataFrame's columns. | {
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``` python
sdf = pandas.SparseDataFrame(index=[0, 1, 2], columns=['a', 'b','c'])
sdf[['a', 'b']]
/usr/lib64/python2.7/site-packages/pandas/sparse/frame.pyc in __getitem__(self, item)
321 try:
322 # unsure about how kludgy this is
--> 323 s = self._series[item]
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https://api.github.com/repos/pandas-dev/pandas/issues/1586 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1586/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1586/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1586/events | https://github.com/pandas-dev/pandas/issues/1586 | 5,490,062 | MDU6SXNzdWU1NDkwMDYy | 1,586 | Unordered duplicate index doesn't yield scalar value | {
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In [13]: obj = Series(range(5), index=['c', 'a', 'a', 'b', 'b'])
In [14]: obj['c']
Out[14]: c 0
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1587 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1587/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1587/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1587/events | https://github.com/pandas-dev/pandas/issues/1587 | 5,499,714 | MDU6SXNzdWU1NDk5NzE0 | 1,587 | slicing with multiple timestamps | {
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This is the data file:
06/01/04 10:11:46 1.2735 1.2737
06/01/04 10:11:47 1.2735 1.2737
06/01/04 10:11:48 1.2736 1.2738
06/01/04 10:11:50 1.2736 1.2738
06/01/04 10:11:50 1.2735 1.2737
raw_data = read_csv('bug_data',header=None, parse_dates=[[0,1]], sep=' ', in... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1588 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1588/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1588/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1588/events | https://github.com/pandas-dev/pandas/issues/1588 | 5,506,904 | MDU6SXNzdWU1NTA2OTA0 | 1,588 | Resampling bug | {
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```
dates = date_range('4/16/2012 20:00', periods=5000000, freq='s')
ts = Series(randn(len(dates)), index=dates)
ts.resample('d')
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1589 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1589/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1589/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1589/events | https://github.com/pandas-dev/pandas/issues/1589 | 5,508,912 | MDU6SXNzdWU1NTA4OTEy | 1,589 | Series/DataFrame.rank broken on all integer data | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1590 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1590/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1590/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1590/events | https://github.com/pandas-dev/pandas/issues/1590 | 5,509,831 | MDU6SXNzdWU1NTA5ODMx | 1,590 | set_index doesn't like non zero-starting initial indeces | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2012-07-09T22:09:39Z | 2013-12-04T00:43:09Z | 2012-07-11T17:09:52Z | NONE | null | It seems unless a DataFrame is completely fresh and it's index hasn't been manipulated in anyway ( such as being a result of a group by ) then set_index() doesn't quite work.
```
In [1]: import pandas
In [2]: pandas.__version__
Out[2]: '0.8.0'
In [3]: df = pandas.DataFrame([ {'val':0,'key':'a'},{'val':1,'key':'b'},{... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1591 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1591/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1591/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1591/events | https://github.com/pandas-dev/pandas/issues/1591 | 5,512,106 | MDU6SXNzdWU1NTEyMTA2 | 1,591 | Cannot resample with 'D' and tz aware timeseries | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-07-09T23:29:55Z | 2012-07-11T21:12:50Z | 2012-07-11T21:12:40Z | NONE | null | ``` python
from pandas import *
dr = date_range(start='2012-5-1', end='2012-6-1')
ts = Series(range(len(dr)), dr)
ts_utc = ts.tz_localize('UTC')
ts_local = ts_utc.tz_convert('America/Los_Angeles')
ts_local.resample('D')
```
yields..
``` traceback
/env/lib/python2.7/site-packages/pandas/tseries/resample.pyc in _get_ti... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1592 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1592/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1592/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1592/events | https://github.com/pandas-dev/pandas/pull/1592 | 5,514,465 | MDExOlB1bGxSZXF1ZXN0MTc1MjY3NQ== | 1,592 | BUG: DataFrame.set_index bug | {
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#1590
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https://api.github.com/repos/pandas-dev/pandas/issues/1593 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1593/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1593/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1593/events | https://github.com/pandas-dev/pandas/issues/1593 | 5,514,623 | MDU6SXNzdWU1NTE0NjIz | 1,593 | drop() issue with MultiIndex after append() | {
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```
In [10]: df1 = pandas.DataFrame({'x': ['a', 'b'], 'y': ['A', 'A'], 'z': [1,1]}).set_index(['x', 'y'])
In [11]: df2 = pandas.DataFrame({'x': ['a'], 'y': ['B'], 'z': [1]}).set_index(['x', 'y'])
In [12]: df3 = df1.append(df2)
In [13]: df3
Out[13]:
z
x y
a A 1
b A 1
a B 1
In [14]: df3.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1594 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1594/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1594/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1594/events | https://github.com/pandas-dev/pandas/issues/1594 | 5,521,377 | MDU6SXNzdWU1NTIxMzc3 | 1,594 | period_range fails on python 2.7 (works on python 3.2) - 'str' object has no attribute 'read' | {
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rng = pandas.period_range('1/1/2011', periods=500, freq='M')
---
DateParseError Traceback (most recent call last)
/home/users/pawel/AGH/mgr/dane/gazowe/<ipython-input-4-a54f4f8b58b5> in <module>()
----> ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1595 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1595/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1595/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1595/events | https://github.com/pandas-dev/pandas/issues/1595 | 5,526,647 | MDU6SXNzdWU1NTI2NjQ3 | 1,595 | Pandas DataFrame.corr() raises exception if two columns have no common values | {
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A B
0 1 NaN
1 1 NaN
2 1 NaN
3 NaN 1
4 NaN 1
5 NaN 1
In DataFrame.corr() it only checks for valid.all(). It needs to check for valid.any() also.
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https://api.github.com/repos/pandas-dev/pandas/issues/1596 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1596/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1596/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1596/events | https://github.com/pandas-dev/pandas/issues/1596 | 5,527,139 | MDU6SXNzdWU1NTI3MTM5 | 1,596 | Resampling with how=list_of_funcs not returning dataframe | {
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I would like to get a dataframe back where each column corresponds to applying each function to each time interval.
If you insert a value into the series, for example at 2012-06-12 01:01:00, you get tha... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1597 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1597/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1597/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1597/events | https://github.com/pandas-dev/pandas/pull/1597 | 5,527,932 | MDExOlB1bGxSZXF1ZXN0MTc1ODUwNw== | 1,597 | Frame corr | {
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if empty arrays are passed in, kendalltau leads to max recursion depth exceeded in mergesort, so must check valid.any before valid.all case.
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https://api.github.com/repos/pandas-dev/pandas/issues/1598 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1598/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1598/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1598/events | https://github.com/pandas-dev/pandas/pull/1598 | 5,528,481 | MDExOlB1bGxSZXF1ZXN0MTc1ODc4NA== | 1,598 | BUG: DataFrame.corr bug | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1599 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1599/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1599/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1599/events | https://github.com/pandas-dev/pandas/issues/1599 | 5,530,114 | MDU6SXNzdWU1NTMwMTE0 | 1,599 | Plotting of millisecond frequency broken | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-07-10T18:21:26Z | 2015-02-18T15:41:44Z | 2012-07-13T03:11:47Z | CONTRIBUTOR | null | from stackoverflow:
I am trying to create a plot waith an x range of e.g. 500 milliseconds.
rng = date_range(s,periods=500,freq="U")
df = DataFrame(randn(500),index=rng,columns=["A"])
to plot column A:
df["A"].plot()
The whole plot will be squeezed into a single spike because the x range is defined from Jan-2011 un... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1600 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1600/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1600/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1600/events | https://github.com/pandas-dev/pandas/issues/1600 | 5,530,307 | MDU6SXNzdWU1NTMwMzA3 | 1,600 | period alias lookup error | {
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Out[18]:
<class 'pandas.tseries.period.PeriodIndex'>
freq: D
[01-Jan-2012, ..., 14-May-2013]
length: 500
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