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https://api.github.com/repos/pandas-dev/pandas/issues/3301 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3301/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3301/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3301/events | https://github.com/pandas-dev/pandas/issues/3301 | 12,989,005 | MDU6SXNzdWUxMjk4OTAwNQ== | 3,301 | #3300 fixed bar log plots (mpl 1.2.1 regressions), check for similar problems in other plot types | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3302 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3302/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3302/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3302/events | https://github.com/pandas-dev/pandas/issues/3302 | 12,990,231 | MDU6SXNzdWUxMjk5MDIzMQ== | 3,302 | adopt spiffy knownfailureif decorator for tests from mpl | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3303 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3303/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3303/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3303/events | https://github.com/pandas-dev/pandas/issues/3303 | 12,995,125 | MDU6SXNzdWUxMjk5NTEyNQ== | 3,303 | Panel and Panel.from_dict() don't honor ordering when passed OrderedDict | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3304 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3304/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3304/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3304/events | https://github.com/pandas-dev/pandas/pull/3304 | 12,995,245 | MDExOlB1bGxSZXF1ZXN0NTA3MDE4Mw== | 3,304 | PR: Panel and Panel.from_dict() don't honor ordering when passed OrderedDict | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3305 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3305/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3305/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3305/events | https://github.com/pandas-dev/pandas/issues/3305 | 12,995,513 | MDU6SXNzdWUxMjk5NTUxMw== | 3,305 | Panel4D ctor probably doesn't respect OrderedDict. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3306 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3306/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3306/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3306/events | https://github.com/pandas-dev/pandas/issues/3306 | 12,996,864 | MDU6SXNzdWUxMjk5Njg2NA== | 3,306 | Incorrect datetime indexing using Panels, potentially DataFrame too? | {
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``` python
from pandas import Panel, DataFrame
import numpy as np
import datetime
import pandas as pn
import p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3307 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3307/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3307/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3307/events | https://github.com/pandas-dev/pandas/issues/3307 | 13,001,418 | MDU6SXNzdWUxMzAwMTQxOA== | 3,307 | Add exception when passing invalid column name to select_as_multiple | {
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... | 7 | 2013-04-10T02:21:27Z | 2018-07-06T22:37:15Z | 2018-07-06T22:37:15Z | NONE | null | No exception is raised when requesting a column that doesn't exist in any of the key tables.
I think the desired behavior in this situation would be to check if the requested columns exist before performing retrieving the data. If any of the columns do not exist, raising an exception that lists the invalid columns ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3308 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3308/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3308/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3308/events | https://github.com/pandas-dev/pandas/issues/3308 | 13,002,034 | MDU6SXNzdWUxMzAwMjAzNA== | 3,308 | segfault on set_index | {
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``` python
import pandas as pd
pd.__version__ # '0.11.0.dev-809b238'
d = {'t1': [2, 2.5, 3], 't2': [4, 5, 6]}
df = pd.DataFrame(d)
tuples = [(0, 1), (0, 2), (1, 2)]
df['tuples'] = tuples
df.set_index(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3309 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3309/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3309/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3309/events | https://github.com/pandas-dev/pandas/issues/3309 | 13,006,328 | MDU6SXNzdWUxMzAwNjMyOA== | 3,309 | test_bar_log failure | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2013-04-10T07:00:41Z | 2013-04-10T08:00:48Z | 2013-04-10T08:00:48Z | MEMBER | null | matplotlib v 1.1.1. maybe i should upgrade?
```
23:57 ~/code/pandas (master)$ nosetests pandas/tests/test_graphics.py
........F...............................
======================================================================
FAIL: test_bar_log (pandas.tests.test_graphics.TestDataFramePlots)
---------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3310 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3310/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3310/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3310/events | https://github.com/pandas-dev/pandas/pull/3310 | 13,020,000 | MDExOlB1bGxSZXF1ZXN0NTA4Mjc3Ng== | 3,310 | TST/CLN: legacy pickle testing | {
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- standardized testing data to live under tests/data (for that set of tests),
- added method `util/testing.get_data_path` to give you this path
TST:
- added `io/tests/test_pickle.py` and `io/tests/generate_legacy_pickles.py`
to generate legacy pickle files and provide comparsions
just run `python path_to_gene... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3311 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3311/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3311/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3311/events | https://github.com/pandas-dev/pandas/issues/3311 | 13,020,867 | MDU6SXNzdWUxMzAyMDg2Nw== | 3,311 | BUG: datetime selection in a DataFrame should work in the where | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2013-04-10T14:16:26Z | 2013-08-11T02:11:03Z | 2013-04-10T18:25:46Z | CONTRIBUTOR | null | I think something broke:
see: http://stackoverflow.com/questions/15927451/filter-on-pandas-dataframe-with-datetime-columns-raises-error/15927797?noredirect=1#comment22689922_15927797
This is wrong (should give rows > 0)
```
In [3]: df = pd.DataFrame(dict(A = pd.date_range('20130102',periods=5), B = pd.date_range('20... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3312 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3312/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3312/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3312/events | https://github.com/pandas-dev/pandas/pull/3312 | 13,023,192 | MDExOlB1bGxSZXF1ZXN0NTA4NDUwMw== | 3,312 | BUG: GH3311 Dataframe where with a datetimelike was not correctly selecting | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3313 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3313/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3313/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3313/events | https://github.com/pandas-dev/pandas/pull/3313 | 13,023,506 | MDExOlB1bGxSZXF1ZXN0NTA4NDY2Mw== | 3,313 | TST: test fix on GH3235 (failing because of system dtype on different sy... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3314 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3314/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3314/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3314/events | https://github.com/pandas-dev/pandas/pull/3314 | 13,046,451 | MDExOlB1bGxSZXF1ZXN0NTA5NjY4NA== | 3,314 | DOC add dayfirst to to_datetime | {
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~~Also a cheeky enhancement to use pr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3315 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3315/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3315/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3315/events | https://github.com/pandas-dev/pandas/issues/3315 | 13,047,707 | MDU6SXNzdWUxMzA0NzcwNw== | 3,315 | Data Frame division | {
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Is the former the intended behavior?
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https://api.github.com/repos/pandas-dev/pandas/issues/3316 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3316/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3316/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3316/events | https://github.com/pandas-dev/pandas/pull/3316 | 13,048,551 | MDExOlB1bGxSZXF1ZXN0NTA5NzgzNg== | 3,316 | SCR: add a script for tracking down all commits touching a named method | {
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code base.
Initially, I hope this well help define "golden" commits for the various
adhoc versions of pickled pandas objects, so we can finish off #3310
, get robust back-compat testing and feel easier about touching
the serialization code (which always sc... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3317 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3317/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3317/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3317/events | https://github.com/pandas-dev/pandas/issues/3317 | 13,050,129 | MDU6SXNzdWUxMzA1MDEyOQ== | 3,317 | BUG: reindex by both index and columns loses DatetimeIndex frequency | {
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```
from numpy import ones
from pandas import DataFrame, __version__
df = DataFrame(ones((3, 3)), index=[datetime(2012, 1, 1), datetime(2012, 1, 2), datetime(2012, 1, 3)], columns=['a', 'b', 'c'])
time_freq = date_range('2012-01-01', '2012-01-03', freq='d')
some_cols = ['a', 'b']
```
We get:
```
__version__
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https://api.github.com/repos/pandas-dev/pandas/issues/3318 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3318/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3318/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3318/events | https://github.com/pandas-dev/pandas/issues/3318 | 13,052,010 | MDU6SXNzdWUxMzA1MjAxMA== | 3,318 | np.nan rows being dropped from HDFStore frame_tables using append | {
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``` python
test = pd.Series(range(401125), dtype=np.float64)
idx = np.random.permutation(test.index)[:50000]
test[idx] = np.nan
# check that there are indeed np.nan in the series
test.isnull().value_counts()
False 351125
T... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3319 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3319/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3319/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3319/events | https://github.com/pandas-dev/pandas/issues/3319 | 13,066,705 | MDU6SXNzdWUxMzA2NjcwNQ== | 3,319 | Selection Issues | {
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TypeError: unsupported operand type(s) for |: 'bool' and 'NotImplementedType'
Code:
``` sql
df.columns
```
Index([KeyNum, ServiceAddrID, ActionStatus, LDCServiceLocationSystemID, LDCCustomerSystemID, TurnOnDate, TurnOffDate, ...etc , dtype=object)
If... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3320 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3320/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3320/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3320/events | https://github.com/pandas-dev/pandas/issues/3320 | 13,067,659 | MDU6SXNzdWUxMzA2NzY1OQ== | 3,320 | inconsistent behavior between DataFrame and Series when underlying objects are datetime | {
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the test below is a comparison on 0.10.0 and 0.10.1 under windows 32 bit python 2.7.2
``` python
import numpy
print numpy.__version__
import pandas
from panda... | {
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ix = pd.date_range('1/1/2013', periods=12, freq='M')
ts = Series(np.arange(12), index=ix)
ts
2013-01-31 0
2013-02-28 1
2013-03-31 2
2013-04-30 3
2013-05-31 4
2013-06-30 5
2013-07-31 6
2013-08-31 7
2013-09-30 8
2013-10-31 9
2013-11-30 10
2013-12-31 11
Freq: M, dty... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3322 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3322/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3322/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3322/events | https://github.com/pandas-dev/pandas/pull/3322 | 13,091,514 | MDExOlB1bGxSZXF1ZXN0NTExODgzNg== | 3,322 | BUG: ensure index casting works even in Int64Index | {
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df = DataFrame({'A' : [1.1,2.2,3.3], 'B' : [5.0,6.1,7.2]}, index = [2010, 2011, 2012])
df.index = df.index.astype(int)
df.ix[2010]
```
was failing - fixed up
from the mailing list
https://groups.google.com/forum/?fromgroups#!topic/pydata/ClJA5ldNQNQ
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https://api.github.com/repos/pandas-dev/pandas/issues/3323 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3323/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3323/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3323/events | https://github.com/pandas-dev/pandas/issues/3323 | 13,094,868 | MDU6SXNzdWUxMzA5NDg2OA== | 3,323 | ENH/API: Allow dicts with tuple keys in DataFrame constructor | {
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"labels_url": "htt... | 15 | 2013-04-11T23:20:57Z | 2014-07-01T11:30:28Z | 2014-04-09T23:32:24Z | MEMBER | null | related #4805
It would be nice to allow automatic conversion to a MultiIndex when a `dict` with tuple keys is passed into the `DataFrame` constructor. Here's what currently happens:
``` python
from pandas import Index, DataFrame
from numpy.random import rand
import itertools as itools
d = {(i, j): rand(10) for i, j i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3324 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3324/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3324/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3324/events | https://github.com/pandas-dev/pandas/issues/3324 | 13,100,162 | MDU6SXNzdWUxMzEwMDE2Mg== | 3,324 | DOC: in docstrings point users to valid offset aliases | {
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"id... | closed | false | null | [] | null | 9 | 2013-04-12T02:39:06Z | 2017-03-14T13:45:01Z | 2017-03-14T13:45:01Z | CONTRIBUTOR | null | Many timeseries-related functions have a `freq` argument that accepts strings representing some offset value. The specific valid options are apparently known as "offset aliases." Not exactly intuitive search terms but I did eventually find https://github.com/pydata/pandas/blob/master/doc/source/timeseries.rst which lis... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3325 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3325/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3325/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3325/events | https://github.com/pandas-dev/pandas/issues/3325 | 13,114,051 | MDU6SXNzdWUxMzExNDA1MQ== | 3,325 | TST: create more test pickles | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2013-04-12T11:00:29Z | 2013-09-22T00:06:13Z | 2013-09-22T00:06:13Z | CONTRIBUTOR | null | need to run io/tests/generate_legacy_pickles.py on various systems/py/pandas versions to generate more legacy pickles
user contrib welcome
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https://api.github.com/repos/pandas-dev/pandas/issues/3326 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3326/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3326/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3326/events | https://github.com/pandas-dev/pandas/issues/3326 | 13,117,584 | MDU6SXNzdWUxMzExNzU4NA== | 3,326 | Perf check on upcoming v0.11.0 vs 0.10.1 | {
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best of 5.
I hope to have this automated and realtime by the time the
next release comes around, along with bisection.
1st run
```
λ cat r1/report.txt
Worse
getattr_dataframe_index 2.000000
frame_multi_and_no_ne 1.319728
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https://api.github.com/repos/pandas-dev/pandas/issues/3327 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3327/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3327/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3327/events | https://github.com/pandas-dev/pandas/pull/3327 | 13,119,434 | MDExOlB1bGxSZXF1ZXN0NTEzMDY1OA== | 3,327 | PERF: fixed int64 indexing perf issue when conversion to int64 | {
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```
-------------------------------------------------------------------------------
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https://api.github.com/repos/pandas-dev/pandas/issues/3328 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3328/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3328/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3328/events | https://github.com/pandas-dev/pandas/issues/3328 | 13,121,803 | MDU6SXNzdWUxMzEyMTgwMw== | 3,328 | Wierd issue with series and dataframe creation (clean_index_list error) | {
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I have the following (new) problem:
obj2 = pd.Series([4,7,-5,3], index = ['d','b','a','c'])
or
df2 = pd.DataFrame([4,7,-5,3], index = ['d','b','a','c'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3329 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3329/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3329/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3329/events | https://github.com/pandas-dev/pandas/pull/3329 | 13,122,755 | MDExOlB1bGxSZXF1ZXN0NTEzMjEwOQ== | 3,329 | PERF/CLN: infer Period in infer_dtype, later index inference is faster | {
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see #3326
not sure if this is that stable of a perf fix
```
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https://api.github.com/repos/pandas-dev/pandas/issues/3330 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3330/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3330/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3330/events | https://github.com/pandas-dev/pandas/issues/3330 | 13,126,366 | MDU6SXNzdWUxMzEyNjM2Ng== | 3,330 | Consider moving date parsing behaviour out of options.display.xFirst | {
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"labels_url": "htt... | 1 | 2013-04-12T15:50:17Z | 2014-01-10T12:14:17Z | 2014-01-10T12:14:17Z | NONE | null | https://github.com/pydata/pandas/pull/3314#issuecomment-16300121, `options.display.dayfirst` modifies parsing behaviour in `parse_time_string`, which controls "smart slicing" for timeseries.
Consider seperating the display and parsing behaviour. the parsing
behaviour belongs in `options.mode`. with a warning in 0.12 an... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3331 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3331/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3331/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3331/events | https://github.com/pandas-dev/pandas/pull/3331 | 13,127,284 | MDExOlB1bGxSZXF1ZXN0NTEzNDQzMg== | 3,331 | PERF: fixed int64 indexing perf issue when conversion to int64 | {
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```
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https://api.github.com/repos/pandas-dev/pandas/issues/3332 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3332/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3332/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3332/events | https://github.com/pandas-dev/pandas/pull/3332 | 13,127,691 | MDExOlB1bGxSZXF1ZXN0NTEzNDYyNg== | 3,332 | PERF/CLN: infer Period in infer_dtype, later index inference is faster | {
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see #3326
not sure if this is that stable of a perf fix
```
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https://api.github.com/repos/pandas-dev/pandas/issues/3333 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3333/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3333/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3333/events | https://github.com/pandas-dev/pandas/pull/3333 | 13,134,136 | MDExOlB1bGxSZXF1ZXN0NTEzNzkyNQ== | 3,333 | PERF: series construction perf enhancements, use a fast path based on dt... | {
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(I measure the existing one at 9us, this puts it at 10, before
this change was about 11)
difference is 3 function calls, so not much more we can do I think
(as this is handling more cases)
```
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https://api.github.com/repos/pandas-dev/pandas/issues/3334 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3334/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3334/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3334/events | https://github.com/pandas-dev/pandas/issues/3334 | 13,145,528 | MDU6SXNzdWUxMzE0NTUyOA== | 3,334 | Pivot table margins brittleness | {
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>
> ```
> df = DataFrame({'Response' : ['Y', 'N' ,'N', 'Y', 'Y', 'N'],
> 'Type' : ['A', 'A', 'B', 'B', 'B', 'C']})
> ```
>
> I want to count the number of responses of each value (Y or N... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3335 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3335/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3335/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3335/events | https://github.com/pandas-dev/pandas/issues/3335 | 13,145,555 | MDU6SXNzdWUxMzE0NTU1NQ== | 3,335 | Test/fix case where use of "All" causes problems in pivot_table with margins=True | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3336 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3336/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3336/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3336/events | https://github.com/pandas-dev/pandas/pull/3336 | 13,145,950 | MDExOlB1bGxSZXF1ZXN0NTE0NDIyNA== | 3,336 | TST: properly raise the quoted exception when trying to unpickle on py2 | {
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as the try: except: is mainly to catch a decoding error
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https://api.github.com/repos/pandas-dev/pandas/issues/3337 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3337/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3337/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3337/events | https://github.com/pandas-dev/pandas/issues/3337 | 13,151,379 | MDU6SXNzdWUxMzE1MTM3OQ== | 3,337 | FIX? df.__repr__ takes for ever with big data | {
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after having updated my local branch with the current dev master ( pd.**version** == '0.11.0rc1' -- compiling under Mac OS 10.8 went smoothly) some of my scripts in which I handle large data frames (2.6 million rows, 10 columns) stopped working.
It turned out that accessing the df's repr method but also look... | {
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"followers_url": "https://api.github.com/users/... | 10 | 2013-04-13T11:40:49Z | 2013-10-04T23:17:53Z | 2013-10-04T23:17:53Z | NONE | null | continuing #3112 , get rid of all the shocking blue in [visualization.rst](http://pandas.pydata.org/pandas-docs/dev/visualization.html)
scatter_plot still uses the evil blue, for one.
Also, grid defaults.
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```
In [8]: df = pd.DataFrame({'A': ['foo', 'bar'] * 3,
'B': np.random.randn(6),
'C': np.random.randint(0, 20, 6)})
# this gets you a new grouper
In [22]: df.groupby(['A'])['B']
Out[22]... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3340 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3340/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3340/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3340/events | https://github.com/pandas-dev/pandas/issues/3340 | 13,157,000 | MDU6SXNzdWUxMzE1NzAwMA== | 3,340 | BUG? Indexing + assignment does not work if member selected after indexing | {
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this is one that has puzzled me for quite some time, but somehow it never asked about it. It seems whether an conditional assignment to a df column is performed or not depends on the order of indexing / member getting inside the left-hand expression of the assignment statement. See this snippet:
``` Python
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"followers_url": "https://api.github.com/users/jorisva... | 15 | 2013-04-13T14:34:45Z | 2018-07-09T17:28:37Z | 2018-07-06T22:19:40Z | CONTRIBUTOR | null | xref #12585
I think this ought to raise a ValueErrror:
```
In [1]: pd.to_datetime('01-13-2012', dayfirst=True)
Out[1]: datetime.datetime(2012, 1, 13, 0, 0)
```
_This means if my data is bad (i.e. somehow I have a mixture of american and british string-dates), I won't be told there was an issue when parsing! I can't ... | {
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This PR moves the doc string from **init** to the more common class location.
(cf.. numpy, rest of pandas classes that have a doc string)
Besides STY / consistency this would allow for more directly accessing the doc string in a debugging (pdb) session:
``` Python
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... | 6 | 2013-04-13T23:20:06Z | 2016-08-01T15:35:58Z | 2016-07-31T18:39:04Z | NONE | null | Pandas does not handle Series in CSV format very well.
First problem: read_csv(squeeze=True) does not work, see:
http://stackoverflow.com/questions/15760856/how-to-read-a-pandas-series-from-a-csv-file/15767171
Secondly: both read_csv() and pandas.Series.from_csv() can't handle row-oriented CSV files. As an example, t... | {
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Current workarounds include using numpy.outer() (which is still not really a real matrix multiplication, because it will al... | {
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concurrent we gain little by having some jobs take less time (except
a headstart on the next build)
Specifically:
- roll LOCALE_OVERRIDE into an extra step on one of the other jobs
- do "not slow" followed by full_deps install followed by "slow an... | {
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In [42]: labels = [('foo', 1),
...: ('foo', 2),
...: ('bar', 3),
...: ('bar', 4)]
...: pd.MultiIndex.from_tuples(labels)
Out[42]:
MultiIndex
[foo 1, 2, bar 3, 4]
```
hiding the repeated `foo` and `bar` is nice for small multindices, but
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``` python
In [55]: pd.MultiIndex.from_tuples(zip(*[range(200),range(200)]))
Out[55]:
MultiIndex
[0 0 , 1 1 , 2 2 , 3 3 , 4 4 , 5 5 , 6 6 , 7 7 , 8 8 , 9 9 , 10 10, 11 11, 12 12, 13 13, 14 14, 15 15, 16 16, 17 17, 18 18, 19 19, 20 20, 21 21, 22 22, 23 23... | {
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disabled the gc when doing multiple runs on the same vb (just in case).
Though usage, this appears to cause memory exhaustion for large N, which is
an indication that cyclic refs are being created somewhere. invoking gc.collect()
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Probably not serious enough to block release, @wesm?
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https://api.github.com/repos/pandas-dev/pandas/issues/3358 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3358/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3358/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3358/events | https://github.com/pandas-dev/pandas/pull/3358 | 13,173,295 | MDExOlB1bGxSZXF1ZXN0NTE1MTM5MQ== | 3,358 | BLD: Add 2to3 caching, move the build cache logic into use_build_cache.py | {
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to shove into setup.py, I'm glad to pull it back out.
a "goto_ver.sh" script is now really easy to do, and very useful for benchmarking
and bisecting regressions.
.bashrc:
``` bash
# Use the pandas build cache
export BUILD_CACHE_... | {
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```
(which wasn't using the block level take)
```
This is not a big diff on get_numeric_data, about 5us on avg when I test it,
but its non-zero! (and there is some other code cleanups)
The other tests might be noise, not sure.
```
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https://api.github.com/repos/pandas-dev/pandas/issues/3360 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3360/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3360/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3360/events | https://github.com/pandas-dev/pandas/issues/3360 | 13,175,608 | MDU6SXNzdWUxMzE3NTYwOA== | 3,360 | Test failures on FreeBSD 9.1 | {
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% uname -a
FreeBSD XXXX.saltant.net 9.1-STABLE FreeBSD 9.1-STABLE #0 r248078: Fri Mar 8 20:36:00 EST 2013 root@XXXX.saltant.net:/usr/obj/usr/src/sys/NIPPL amd64
% pkg_info -xE pandas
py27-pandas-0.11.0.r1
% pkg_info -xE ^python
python27-2.7.3_6
% pkg_info -xE numpy
py27-numpy-1.6.2_1,1
% nosetests pandas.test... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3361 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3361/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3361/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3361/events | https://github.com/pandas-dev/pandas/issues/3361 | 13,176,303 | MDU6SXNzdWUxMzE3NjMwMw== | 3,361 | DataFrame.pivot_table bug when rows is unspecified | {
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"followers_url": "https://api.github.com/users/wesm... | 1 | 2013-04-14T17:55:03Z | 2013-04-14T18:47:50Z | 2013-04-14T18:47:50Z | CONTRIBUTOR | null | ```
In [6]: df
Out[6]:
cols rows values
0 x a 1
1 y b 2
2 z c 3
In [7]: df.pivot_table(rows='rows', aggfunc={'values': ['mean']})
Out[7]:
values
mean
rows
a 1
b 2
c 3
In [8]: df.pivot_table(cols='cols', aggfunc={'values': ['mean... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3362 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3362/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3362/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3362/events | https://github.com/pandas-dev/pandas/issues/3362 | 13,183,704 | MDU6SXNzdWUxMzE4MzcwNA== | 3,362 | import pandas fails with cannot import name Timestamp / hashtable | {
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"followers_url": "https://api.github.com/users/wesm/... | 10 | 2013-04-15T03:21:07Z | 2014-08-06T22:35:24Z | 2013-04-18T05:52:58Z | NONE | null | I installed version pandas-0.11.0.dev-cddde22.win32-py2.7.exe but I always got the errors while importing pandas.Then I tried to install pandas-0.10.1.win32-py2.7.exe (without uninstalling the previous, I didn't know how to do, it didn't change anything. I have vista.
The error is 'cannot import name hashtable' if I us... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3363 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3363/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3363/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3363/events | https://github.com/pandas-dev/pandas/issues/3363 | 13,185,783 | MDU6SXNzdWUxMzE4NTc4Mw== | 3,363 | test failures and errors with v0.11rc1 | {
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This is the traceback of the error:
``` ======================================================================
FAIL: testWLS (pandas.stats.tests.test_ols.TestOLS)
----------------------------------------------------------------------
Traceback (mos... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3364 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3364/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3364/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3364/events | https://github.com/pandas-dev/pandas/pull/3364 | 13,204,772 | MDExOlB1bGxSZXF1ZXN0NTE2NTExNA== | 3,364 | CLN: remove some unicode hair from pre-pprint_thing days GH3360 | {
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"i... | 0 | 2013-04-15T15:20:36Z | 2014-07-16T08:05:55Z | 2013-04-23T02:09:41Z | NONE | null | breaks no tests, and the code it removes resolved an issue
which now works even without it. even so, no sudden moves
a couple of days before a major release, so 0.12.
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https://api.github.com/repos/pandas-dev/pandas/issues/3365 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3365/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3365/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3365/events | https://github.com/pandas-dev/pandas/pull/3365 | 13,205,190 | MDExOlB1bGxSZXF1ZXN0NTE2NTMzMA== | 3,365 | DOC: Moved note about cursor position in TS plots out of changes to pd.data.io.Options in v0.11.0 | {
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Note about cursor position in time series plots should not have been a part of changes to Options class in data.io.
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https://api.github.com/repos/pandas-dev/pandas/issues/3366 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3366/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3366/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3366/events | https://github.com/pandas-dev/pandas/issues/3366 | 13,206,071 | MDU6SXNzdWUxMzIwNjA3MQ== | 3,366 | group.apply(...) changes dtype to object -> Regression? | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2013-04-15T15:47:55Z | 2013-09-22T13:39:19Z | 2013-09-22T00:12:59Z | CONTRIBUTOR | null | ``` python
import pandas
df = pandas.DataFrame({"a":["a","b","a","b"], "b":[1,2,3,4], "c":[1.,2.,3.,4.], "d":["a","b","a","b"]})
print df.dtypes
print df
print df[["b","c"]].corr()
groups = df.groupby("a")
highest = groups.apply(lambda group: group.ix[group['b'].idxmax()])
print highest.dtypes
print highest
print highe... | {
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``` python
from pandas import Series, PeriodIndex, Period
pi = PeriodIndex(start=Period('1950-1'), freq='M', end=Period('1950-7'))
a = Series([1,nan,nan,4,5,nan,7], pi)
b = Series([9,9,9,9,9,9,9], pi)
display(a, b, a.combine_first(b))
```
Then the output is:
```
1950-01 1
1950-02 NaN
1950-03 NaN
1... | {
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User provides HTML string for whatever source he likes, or url.
optionally specify table id, or regex to match against contained cell
content to quickly single out `.+` tables, when multiple exist on the page.
Pseudo:
```
DataFrame.fro... | {
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```
ValueError: Length of replacements must equal series length
```
However, looking at the lengths of the original values and the replacements, there does not seem to be a problem:
```
In [151]: len(children.wfa[not_n... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3371 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3371/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3371/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3371/events | https://github.com/pandas-dev/pandas/issues/3371 | 13,217,410 | MDU6SXNzdWUxMzIxNzQxMA== | 3,371 | BUG/ENH: timedelta fillna should work intuitively | {
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setup
```
txt = '''ID,DATE
002691c9cec109e64558848f1358ac16,2003-08-13 00:00:00
002691c9cec109e64558848f1358ac16,2003-08-13 00:00:00
0088f218a1f00e0fe1b94919dc68ec33,2006-05-07 00:00:00
0088f218a1f00e0fe1b94919dc68ec33,2006-06-03 00:... | {
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"f... | 11 | 2013-04-15T20:53:25Z | 2015-05-04T12:29:19Z | 2013-11-10T11:24:26Z | NONE | null | Let me start by saying that I apologize if this is already on your radar. I looked, but could not find a similar issue. When I try to write out numpy.timedelta64 to excel I get the following error:
```
pandas.__version__
Out[22]: '0.11.0.dev-6cda5dc'
run tester
------------------------------------------------------... | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2013-04-16T13:30:56Z | 2013-04-18T20:37:48Z | 2013-04-16T13:35:25Z | CONTRIBUTOR | null | With 0.10.1:
``` python
In [1]: pd.__version__
Out[1]: '0.10.1'
In [2]: dates = pd.date_range('01-Jan-2013','01-Jan-2014', freq='H')
...: df = pd.DataFrame(randn(dates.size,5), index=dates)
In [3]: %time print(df)
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 8761 entries, 2013-01-01 00:00:00 to 2014-01-01... | {
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match_price = get_info[match_time]['Bid Price']
The actual index value:
<Timestamp: 2013-04-10 10:22:01.696815975-0500 CDT, tz=US/Central>
The error returned:
KeyError: u'no item named 2013-04-10 10:22:01.696815-05:00'
It seems to me that it is cutting off the last digits... | {
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That's the bundled version on precise. Perhaps just headless travis issues.
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2013-04-17T00:13:10Z | 2014-06-30T05:21:11Z | 2013-04-17T22:40:58Z | MEMBER | null | #2903 solves the case for the first level but using the same variables from that issue, the following code raises a `TypeError` for the second level:
``` python
import pandas as pd
from numpy.random import rand
columns = pd.MultiIndex.from_tuples([('a', 'foo'), ('a', 'bar'), ('b', 'hello'), ('b', 'world')], names=['lv... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3379 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3379/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3379/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3379/events | https://github.com/pandas-dev/pandas/pull/3379 | 13,275,950 | MDExOlB1bGxSZXF1ZXN0NTIwMTU2Ng== | 3,379 | ENH/CLN: make Timestamp repr valid python code, like datetime does. | {
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"closed_at": "2013-07-24T23:25:44Z",
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"created_at": "2013-04-30T04:12:30Z",
"creator": null,
"description": "Major release (formerly 0.11.1 bugfix but has outgrown its britches)",
"due_on": "2013-07-05T07:00:00Z",
"html_url": "https://github.com/pandas-dev/pandas/milestone/22",
"i... | 2 | 2013-04-17T01:02:05Z | 2014-06-19T05:28:32Z | 2013-04-23T02:13:36Z | NONE | null | In the same vein as #3038 , make `repr()` output valid python code where feasible. I find this not
being the case inconvenient for example when issues contain code examples,
and the data needs to be recreated by hand rather then merely copy pasted.
```
In [2]: zs=[Timestamp('99-04-17 00:00:00',tz='UTC'),
...: Time... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3380 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3380/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3380/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3380/events | https://github.com/pandas-dev/pandas/issues/3380 | 13,296,945 | MDU6SXNzdWUxMzI5Njk0NQ== | 3,380 | Assignment in groupby fails with error (AssertionError: Index length did not match values) | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2013-04-17T13:57:37Z | 2013-04-20T14:33:09Z | 2013-04-20T14:33:09Z | NONE | null | I have a dataset that is inherently hierarchical (from some experiments). For each large category 1, there are several category 2 entries, and in turn for each cat2 entry there are several cat3 entries. For each (cat1, cat2, cat3) tuple I have a measurement value, val below.
The analysis I am doing is per category 1. ... | {
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The first dataframe has three columns: Timestamp, float, Timestamp:
df1 = pd.DataFrame({'time':[pd.Timestamp('2013-01-01'),pd.Timesta... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3382 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3382/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3382/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3382/events | https://github.com/pandas-dev/pandas/issues/3382 | 13,299,050 | MDU6SXNzdWUxMzI5OTA1MA== | 3,382 | Int64Index.max() raises a TypeError exception | {
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] | closed | false | null | [] | null | 10 | 2013-04-17T14:38:22Z | 2013-04-20T20:35:48Z | 2013-04-19T23:22:36Z | NONE | null | On my computer, the following code raises a `TypeError: len() of unsized object` on line 171 of `core\index.py`:
```
pd.Int64Index(range(10)).max()
```
Similarly for `min()`, but `mean()` works.
Pandas version: 0.10.0
System: Windows 8 64 bits
Python 2.7.3 64 bits
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https://api.github.com/repos/pandas-dev/pandas/issues/3384 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3384/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3384/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3384/events | https://github.com/pandas-dev/pandas/pull/3384 | 13,299,866 | MDExOlB1bGxSZXF1ZXN0NTIxMzI5OA== | 3,384 | BUG: GH3380 groupby will handle mutation on a DataFrame group's columns | {
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"followers_url": "https://api.github.com/users/wesm/... | 2 | 2013-04-17T14:54:52Z | 2014-06-24T18:14:36Z | 2013-04-20T14:32:53Z | CONTRIBUTOR | null | and fallback to non-fast apply
fixes #3380
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https://api.github.com/repos/pandas-dev/pandas/issues/3385 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3385/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3385/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3385/events | https://github.com/pandas-dev/pandas/issues/3385 | 13,307,019 | MDU6SXNzdWUxMzMwNzAxOQ== | 3,385 | read_csv documentation: iterator=True returns TextFileReader and not TextParser | {
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http://stackoverflow.com/questions/16067144/in-pandas-how-to-use-fillna-to-fill-the-whole-columns-with-string-if-the-column/16067653#16067653
```
In [2]: csv=u"""a,a,,a
b,b,,b
c,c,,c
"""
In [3]: df = pd.read_csv(StringIO(csv), header=None)
In [4]: df
Out[4]:
0 1 2 3
... | {
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Is there any way to compute the length of the column `repr` w... | {
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y build --compiler=mingw32
<snip>
In file included from c:\WinPython-32bit-3.3.0.0beta2\python-3.3.0\lib\site-pack
ages\numpy\core\include/numpy/ndarraytypes.h:1728:0,
from pandas/src/period.h:11,
from pa... | {
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https://groups.google.com/forum/?fromgroups=#!topic/pydata/fzPGjVrj9lU
```
df = pd.DataFrame.from_items([('a', [1,2]), ('b', ([3,4]))])
df.index = pd.MultiIndex.from_tuples([('A', 'B'),('C', 'D')],
names=['k1', 'k2'])
# A dataframe, with a multiindex:
>>> df
a b
k1 k2
A B 1 3
C D 2 4
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`pd.options.display.max_seq_items` should not be None by default.
It's easy to hang the terminal by repr()ing with some mal-chosen data.
#3426
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"f... | 2 | 2013-04-18T17:10:14Z | 2013-12-20T02:20:55Z | 2013-12-20T02:20:55Z | CONTRIBUTOR | null | run through file and find the positions that are blank on every line
use the first position if there is a block
useful for small files and/or copy-pasting small DataFrame console output and then reconstructing via read_fwf
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`pd.eval(function_or_string,method=None, **kwargs)`
to support things like:
1) out-of-core computation (locally) (see #3202)
2) string evaluation which does not use python lazy evaluation
(so pandas can process effiiently)
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obviously these also offer persistence as well
but this is a another dependence
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This PR should make my wrong, right again. In non-interactive mode i re-enabled concise formats and made sure that auto-terminal-size detectio... | {
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The data is in a table with a major index of event timestamp. I can assume the new batch has complete data for the first day so all I need to do is to remove all rows with a timestamp >= min_new_date.
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https://api.github.com/repos/pandas-dev/pandas/issues/3397 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3397/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3397/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3397/events | https://github.com/pandas-dev/pandas/pull/3397 | 13,380,836 | MDExOlB1bGxSZXF1ZXN0NTI1MDY1Mg== | 3,397 | ENH: speed up testing when --processes arg is given to test_fast.sh | {
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"followers_url": "https://api.github.com/users/wesm/... | 4 | 2013-04-19T07:25:20Z | 2013-04-23T00:17:26Z | 2013-04-22T23:58:21Z | CONTRIBUTOR | null | ``` python
In [69]: data = """\
....: A,B,C
....: foo,,
....: ,bar,
....: ,,baz
....: """
In [70]: pd.read_csv(StringIO(data))
---------------------------------------------------------------------------
CParserError Traceback (most recent call last)
...
CParserError: Error t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3399 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3399/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3399/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3399/events | https://github.com/pandas-dev/pandas/pull/3399 | 13,393,772 | MDExOlB1bGxSZXF1ZXN0NTI1NjA5Mg== | 3,399 | DOC: ref / val caveat, point at pandas methods | {
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"followers_url": "https://api.github.com/users/wesm/... | 9 | 2013-04-19T09:32:59Z | 2014-06-14T17:35:39Z | 2013-04-20T14:32:40Z | NONE | null | This in part addresses #3340.
I added a few comments in the doc that point users ad using the pandas
at, iat, loc, iloc, etc. methods and included an example similar to
the one exposed in #3340 that addresses some of the reference / value
intricaies encountered with pandas and numpy objects.
To make things clear I se... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/3400 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/3400/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/3400/comments | https://api.github.com/repos/pandas-dev/pandas/issues/3400/events | https://github.com/pandas-dev/pandas/issues/3400 | 13,398,358 | MDU6SXNzdWUxMzM5ODM1OA== | 3,400 | strange `read_table` error message | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2013-04-19T12:10:48Z | 2013-09-30T13:15:22Z | 2013-09-30T13:15:15Z | CONTRIBUTOR | null | Hi, I have a ASCII file I want to read with `read_table`. I put the file here: https://gist.github.com/andreas-h/5419916.
I want to read this file like this:
```
read_table("gistfile1.txt", sep="\s*")
```
However I get this error:
```
ValueError: Expected 6 fields in line 38, saw 7
```
Okay, line 38 looks differen... | {
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