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https://api.github.com/repos/pandas-dev/pandas/issues/7801 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7801/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7801/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7801/events | https://github.com/pandas-dev/pandas/pull/7801 | 38,229,614 | MDExOlB1bGxSZXF1ZXN0MTg2MTkxMjI= | 7,801 | BUG: timeseries subplots may display unnecessary minor ticklabels | {
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(And another problem is `rot` default is not applied to minor ticks. I'll check this separatelly)
```
df = pd.DataFrame(np.random.randn(10, 4), index=pd.date_range(s... | {
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Sorry, caused by #7533. The `ValueError` is being raised when `PeriodIndex` or `DatetimeIndex` with tz 's unique values are less than `MultiIndex` length.
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> index : array-like or Index (1d)
> Values must be unique and hashable, same length as data.
A little bit earlier the same page says:
> Labels need not be unique but must be any hashable type.
Other pages also mention non-uniq... | {
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Maybe `scatter` and `hist` can be deprecated in 0.15 if `MPLPlot` can offer better `GroupBy` plot (plan to do in separate PR).
### Example
This allow... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7810 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7810/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7810/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7810/events | https://github.com/pandas-dev/pandas/pull/7810 | 38,259,328 | MDExOlB1bGxSZXF1ZXN0MTg2MzAzMjQ= | 7,810 | TST: add tests for GH 6572 | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-07-20T14:52:20Z | 2014-07-23T11:08:16Z | 2014-07-21T11:43:55Z | MEMBER | null | Closes #6572. It seems to be fixed by #7465 as a side effect.
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https://api.github.com/repos/pandas-dev/pandas/issues/7811 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7811/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7811/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7811/events | https://github.com/pandas-dev/pandas/issues/7811 | 38,268,882 | MDU6SXNzdWUzODI2ODg4Mg== | 7,811 | ENH: Allow period_range to accept freq with mult != 1 | {
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"description": "DateOffs... | closed | false | null | [] | {
"closed_at": "2015-10-09T18:34:35Z",
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-07-20T23:10:28Z | 2015-09-03T14:04:18Z | 2015-09-03T14:04:18Z | MEMBER | null | `date_range` can accept freq with mult != 1 and output `DatetimeIndex`, otherwise `period_range` raises `ValueError`.
```
pd.date_range('2014-01-01 09:00', '2014-01-01 20:00', freq='4H')
# <class 'pandas.tseries.index.DatetimeIndex'>
# [2014-01-01 09:00:00, ..., 2014-01-01 21:00:00]
# Length: 4, Freq: 4H, Timezone: No... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7812 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7812/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7812/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7812/events | https://github.com/pandas-dev/pandas/issues/7812 | 38,268,935 | MDU6SXNzdWUzODI2ODkzNQ== | 7,812 | ENH: Allow to reset tz from DatetimeIndex holding time representation | {
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"followers_url": "https://api.github.com/users/jr... | 20 | 2014-07-20T23:13:15Z | 2014-08-05T14:49:29Z | 2014-08-05T14:49:29Z | MEMBER | null | There looks no easy way to remove tz from tz-aware `DatetimeIndex` holding the timestamp represented. What required is inverse operation of `tz_localize`.
```
idx = pd.date_range('2014-01-01 09:00', '2014-01-01 20:00', freq='H', tz='Asia/Tokyo')
idx
# <class 'pandas.tseries.index.DatetimeIndex'>
# [2014-01-01 09:00:00... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7813 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7813/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7813/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7813/events | https://github.com/pandas-dev/pandas/issues/7813 | 38,298,121 | MDU6SXNzdWUzODI5ODEyMQ== | 7,813 | TST: add tests for Series/Panel with non-unique index in to_hdf with fixed format | {
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"followers_url": "https://api.github.com/users/jorisva... | 10 | 2014-07-21T12:28:28Z | 2018-07-06T21:41:21Z | 2018-07-06T21:41:13Z | CONTRIBUTOR | null | xref #7788
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https://api.github.com/repos/pandas-dev/pandas/issues/7814 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7814/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7814/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7814/events | https://github.com/pandas-dev/pandas/issues/7814 | 38,313,328 | MDU6SXNzdWUzODMxMzMyOA== | 7,814 | BUG: at allowing fallback type indexing (which is not correct, its a restricted version of loc) | {
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```
In [19]: s = pd.Series([1,2,3], index=list('abc'))
In [20]: s.at['a']
Out[20]: 1
In [23]: s.at[0]
Out[23]: 1
```
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https://api.github.com/repos/pandas-dev/pandas/issues/7815 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7815/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7815/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7815/events | https://github.com/pandas-dev/pandas/issues/7815 | 38,356,160 | MDU6SXNzdWUzODM1NjE2MA== | 7,815 | BUG/ENH: to_sql fails to detect tables via if_exists on mysql with capitalised table names | {
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"followers_url": "https://api.github.com/users/jr... | 9 | 2014-07-21T23:41:26Z | 2014-09-10T06:26:28Z | 2014-09-09T07:55:57Z | CONTRIBUTOR | null | Demonstration code, running on windows (so case insensitive) with pandas 0.14.0
``` python
engine=create_engine('mysql://{username}:{password}@{host}/{database}?charset=utf8'.format(**db))
metadata=MetaData(bind=engine)
table=Table('foo', metadata, Column('id', Integer, primary_key=True), Column('language', Unicode(25... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7816 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7816/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7816/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7816/events | https://github.com/pandas-dev/pandas/issues/7816 | 38,364,949 | MDU6SXNzdWUzODM2NDk0OQ== | 7,816 | StataReader.variable_labels() does not read variable label correctly for stata datasets saved under Stata 13 using 'save' (but it can read datasets saved using 'saveold') | {
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"followers_url": "https://api.github.com/users/jr... | 14 | 2014-07-22T02:59:39Z | 2014-07-23T13:40:44Z | 2014-07-23T13:40:44Z | NONE | null | If I use SataReader to read a Stata dataset saved in Stata 13 using the `save` command, I can get the data but not the variable labels.
If, however, I use the `saveold` command in Stata 13, I am able to get the variable labels in Python3 using `StataReader.variable_labels()`.
Can anyone suggest how to accommodate St... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7817 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7817/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7817/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7817/events | https://github.com/pandas-dev/pandas/issues/7817 | 38,383,495 | MDU6SXNzdWUzODM4MzQ5NQ== | 7,817 | period_range() bug? | {
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``` python
63 In : df = P.DataFrame(index=P.period_range('2000-1-1 10:20', '2005-1-1 12:00'))
64 In : df.index[0]
64 Out: Period('2000-01-01', 'D')
65 In : df.index[0].hour
65 Out: 0
```
it should have been 10, right?
why does period_range() loses time information?
I was recommended to use periods and peri... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7818 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7818/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7818/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7818/events | https://github.com/pandas-dev/pandas/pull/7818 | 38,422,925 | MDExOlB1bGxSZXF1ZXN0MTg3MjgyNjM= | 7,818 | BUG: Fixed failure in StataReader when reading variable labels in 117 | {
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"followers_url": "https://api.github.com/users/jr... | 10 | 2014-07-22T17:24:49Z | 2014-08-20T15:32:51Z | 2014-07-23T13:40:44Z | CONTRIBUTOR | null | Stata's implementation does not match the online dta file format description.
The solution used here is to directly compute the offset rather than reading
it from the dta file. If Stata fixes their implementation, the original code
can be restored.
closes #7816
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https://api.github.com/repos/pandas-dev/pandas/issues/7819 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7819/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7819/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7819/events | https://github.com/pandas-dev/pandas/issues/7819 | 38,433,451 | MDU6SXNzdWUzODQzMzQ1MQ== | 7,819 | df.reset_index fails with tz-aware column (similar to #7533) | {
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```
imp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7820 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7820/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7820/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7820/events | https://github.com/pandas-dev/pandas/issues/7820 | 38,538,476 | MDU6SXNzdWUzODUzODQ3Ng== | 7,820 | Index([1,2,.np.nan]).get_indexer([np.nan]) returns wrong value? | {
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"closed_at": "2020-01-30T12:18:05Z",
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"followers_url": "https://api.github.com/users/wesm... | 21 | 2014-07-23T15:10:08Z | 2019-12-31T15:04:45Z | 2019-12-31T15:04:45Z | CONTRIBUTOR | null | **When this is merged, make the below change in Categorical as well!**
Having `np.nan` in an `Index` is not returning the position of NaN but `-1`:
```
In[5]: from pandas.core.index import _ensure_index
In[6]: import numpy as np
In[7]: idx = _ensure_index([1,2,3,4, np.nan])
In[8]: np.nan in idx
Out[8]: True
In[9]: id... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7821 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7821/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7821/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7821/events | https://github.com/pandas-dev/pandas/issues/7821 | 38,539,115 | MDU6SXNzdWUzODUzOTExNQ== | 7,821 | DOC: api references not working | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-07-23T15:15:57Z | 2014-07-28T20:25:49Z | 2014-07-28T20:25:49Z | CONTRIBUTOR | null | http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0150-cat
references to the `api` section for some reason are not showing up correctly (while other, similar references work ok).
@jorisvandenbossche
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https://api.github.com/repos/pandas-dev/pandas/issues/7822 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7822/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7822/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7822/events | https://github.com/pandas-dev/pandas/issues/7822 | 38,539,653 | MDU6SXNzdWUzODUzOTY1Mw== | 7,822 | API: preserver tz on created series from Index when possible | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-07-23T15:21:19Z | 2014-07-23T17:01:23Z | 2014-07-23T17:01:23Z | CONTRIBUTOR | null | I think this could be done w/o breaking anything else.
xref: #3950
```
In [16]: ts = pd.date_range('1/1/2011', periods=5, freq='10s', tz = 'US/Eastern')
In [17]: ts
Out[17]:
<class 'pandas.tseries.index.DatetimeIndex'>
[2011-01-01 00:00:00-05:00, ..., 2011-01-01 00:00:40-05:00]
Length: 5, Freq: 10S, Timezone: US/Ea... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7823 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7823/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7823/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7823/events | https://github.com/pandas-dev/pandas/pull/7823 | 38,542,186 | MDExOlB1bGxSZXF1ZXN0MTg3ODM4MTQ= | 7,823 | BUG: Bug in passing a DatetimeIndex with a timezone that was not being retained in Frame construction (GH7822) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7824 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7824/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7824/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7824/events | https://github.com/pandas-dev/pandas/issues/7824 | 38,543,937 | MDU6SXNzdWUzODU0MzkzNw== | 7,824 | API: Panel.groupby has an older interface | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2014-07-23T16:02:41Z | 2018-07-06T20:21:04Z | 2017-07-11T09:53:51Z | CONTRIBUTOR | null | This seems to not conform to the `DataFrame.groupby/Series.groupby`
should be straightforward to fix this I think, just simply removing it in favor of `core/generic/NDFrame.groupby`, but would need to fix tests, maybe. The `mapper` argument is the `by` argument.
http://stackoverflow.com/questions/24914748/why-does-pa... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7825 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7825/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7825/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7825/events | https://github.com/pandas-dev/pandas/issues/7825 | 38,560,221 | MDU6SXNzdWUzODU2MDIyMQ== | 7,825 | BUG: Timestamp.replace() behaves naively at DST boundaries (plus bonus segfault!) | {
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... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jre... | 19 | 2014-07-23T18:59:44Z | 2018-06-18T22:34:30Z | 2018-06-18T22:34:30Z | CONTRIBUTOR | null | ``` python
In [1]: import pandas as pd
In [2]: t = pd.Timestamp('2013-11-3', tz='America/Chicago')
In [3]: t
Out[3]: Timestamp('2013-11-03 00:00:00-0500', tz='America/Chicago')
In [4]: t.replace(hour=3)
Out[4]: Timestamp('2013-11-03 03:00:00-0500', tz='America/Chicago')
# This time doesn't exist.
In [5]: pd.Timest... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7826 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7826/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7826/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7826/events | https://github.com/pandas-dev/pandas/issues/7826 | 38,574,724 | MDU6SXNzdWUzODU3NDcyNA== | 7,826 | read_sql chokes on mysql when using labels with queries due to unnecessary quoting | {
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``` python
engine=create_engine('mysql://{username}:{password}@{host}/{database}?charset=utf8'.format(**db))
pandas.io.sql.read_sql('SELECT onlinetransactions.id FROM onlinetransactions L... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7827 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7827/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7827/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7827/events | https://github.com/pandas-dev/pandas/issues/7827 | 38,588,868 | MDU6SXNzdWUzODU4ODg2OA== | 7,827 | BUG: non-monotonic DatetimeIndex does not raise KeyError for missing labels | {
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... | 7 | 2014-07-24T01:02:01Z | 2021-04-11T04:57:47Z | null | MEMBER | null | ``` python
import pandas as pd
index = pd.to_datetime(['2000-01-02', '2000-01-01'])
index.get_loc('1900-01-01')
```
```
array([], dtype=int64)
```
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https://api.github.com/repos/pandas-dev/pandas/issues/7828 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7828/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7828/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7828/events | https://github.com/pandas-dev/pandas/issues/7828 | 38,597,390 | MDU6SXNzdWUzODU5NzM5MA== | 7,828 | Docs: json_normalize appears in docs, but not in the API page. | {
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Not here.
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https://api.github.com/repos/pandas-dev/pandas/issues/7829 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7829/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7829/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7829/events | https://github.com/pandas-dev/pandas/issues/7829 | 38,611,410 | MDU6SXNzdWUzODYxMTQxMA== | 7,829 | Pandas read_csv parsing error if lines contains variable fields | {
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"descript... | closed | false | null | [] | null | 1 | 2014-07-24T09:24:40Z | 2014-07-24T11:39:52Z | 2014-07-24T11:39:42Z | NONE | null | I am using pandas version 0.14.0 and try to parse a csv file which variable number of tokens (fields) using read_csv(). While parsing, I got the below error.
File "parser.pyx", line 727, in pandas.parser.TextReader.read (pandas\parser.c:7146)
File "parser.pyx", line 749, in pandas.parser.TextReader._read_low_memo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7830 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7830/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7830/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7830/events | https://github.com/pandas-dev/pandas/issues/7830 | 38,616,654 | MDU6SXNzdWUzODYxNjY1NA== | 7,830 | Equality comparison raises exception | {
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"followers_url": "https://api.github... | 8 | 2014-07-24T10:40:23Z | 2018-08-01T09:19:44Z | 2018-08-01T09:19:44Z | CONTRIBUTOR | null | Test case:
``` python
def test_datetimeindex__eq__():
"""Equality comparisons should never raise an exception"""
pd.DatetimeIndex(['01-Jan-2015']) == ()
```
``` python
In [115]: test_datetimeindex__eq__()
Traceback (most recent call last):
File "<ipython-input-115-9b7967ca9de2>", line 1, in <module>
te... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7831 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7831/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7831/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7831/events | https://github.com/pandas-dev/pandas/pull/7831 | 38,631,329 | MDExOlB1bGxSZXF1ZXN0MTg4MzY4ODY= | 7,831 | CI: fix typos in readme | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7832 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7832/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7832/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7832/events | https://github.com/pandas-dev/pandas/pull/7832 | 38,632,570 | MDExOlB1bGxSZXF1ZXN0MTg4Mzc2NzQ= | 7,832 | ENH: PeriodIndex can accept freq with mult | {
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- [x] Change `Period.freq` and `PeriodIndex.freq` to store offsets.
- [x] Add `freqstr` to `Period`, `PeriodIndex` can use `DatetimeIndexOpsMixin`'s logic
- [x] Logic and tests for pickles taken in prev versions
- [x] Perform shift/arithmetic considering freq's mult.
- [x] Test all offsets has acc... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7833 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7833/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7833/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7833/events | https://github.com/pandas-dev/pandas/issues/7833 | 38,645,935 | MDU6SXNzdWUzODY0NTkzNQ== | 7,833 | BUG: Constructing Timestamp from local time + offset + time zone yields wrong offset | {
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``` python
In [1]: import pandas as pd
In [2]: pd.Timestamp('2013-11-01 00:00:00-0500', tz='America/Chicago')
Out[2]: Timestamp('2013-10-31 23:09:00-0551', tz='America/Chicago')
```
This bug is inherited from `datetime`, which is using local mean time (the first entry for `America/Chicago` in tzinfo).
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https://api.github.com/repos/pandas-dev/pandas/issues/7834 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7834/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7834/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7834/events | https://github.com/pandas-dev/pandas/pull/7834 | 38,664,556 | MDExOlB1bGxSZXF1ZXN0MTg4NTc3NjA= | 7,834 | ENH: allow MultiIndex column selection from HDFStore | {
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... | 8 | 2014-07-24T19:16:04Z | 2015-04-08T15:04:33Z | 2015-04-08T15:04:33Z | MEMBER | null | Needs some more testing
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https://api.github.com/repos/pandas-dev/pandas/issues/7835 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7835/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7835/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7835/events | https://github.com/pandas-dev/pandas/issues/7835 | 38,665,146 | MDU6SXNzdWUzODY2NTE0Ng== | 7,835 | BUG: date_range(str, tz=str) and date_range(Timestamp) handle tz discontinuity differently | {
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xref (addtl test cases) #7901
I believe `Out[2]` is correct and `Out[3]` is a bug, and that others will agree with me.
I believe `Out[4]` is a bug, `Out[7]` is correct and `Out[10]` is a bug, but that I will have to do some work to convince others to agree with me.
``` python
In [1]: import pandas as pd
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https://api.github.com/repos/pandas-dev/pandas/issues/7837 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7837/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7837/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7837/events | https://github.com/pandas-dev/pandas/issues/7837 | 38,688,250 | MDU6SXNzdWUzODY4ODI1MA== | 7,837 | pivot_table / groupby with miss value in Index | {
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When I try to use multi-index which has some miss value, to build a pivot table, I find pandas take a strange behavior.
Pandas will autofill nan value with the value just above this index value, and this may give a wrong result , which make the value of second last index equal to its value plus nan value.
萧玮 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7838 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7838/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7838/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7838/events | https://github.com/pandas-dev/pandas/issues/7838 | 38,693,480 | MDU6SXNzdWUzODY5MzQ4MA== | 7,838 | Rapid Concurrent Access Breaks HDFStore | {
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"description": "read_hdf, HDFStore",
... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jorisva... | 14 | 2014-07-25T02:56:31Z | 2018-07-06T22:02:57Z | 2018-07-06T21:24:41Z | NONE | null | There are several errors associated with this. One of them is that the HDFStore fails to load some tables inside the store file, but fails silently. Another error is a loud HDF5 error that gives a full traceback. Both should be visible in the following code.
```
import pandas as pd
import multiprocessing as mp
def f(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7839 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7839/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7839/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7839/events | https://github.com/pandas-dev/pandas/issues/7839 | 38,716,619 | MDU6SXNzdWUzODcxNjYxOQ== | 7,839 | itertuples does not work with categorical column in dataframe | {
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... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-07-25T10:22:30Z | 2014-07-25T23:30:04Z | 2014-07-25T23:30:04Z | CONTRIBUTOR | null | Code Snippet
``` python
df = pd.DataFrame({"id":[1,2,3,4,5,6], "raw_grade":['a', 'b', 'b', 'a', 'a', 'e']})
df['grade'] = pd.Categorical(df['raw_grade'])
for t in df.itertuples(index=False):
print(t)
```
Error
```
---------------------------------------------------------------------------
TypeError ... | {
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it will be nice if `to_dict` method could provide same `orient` parameter as `to_json`.
For example when `outtype='split'` we get same results as `outtype='series'`.
I also noticed that `df.to_dict(outtype='split1234')` is understood as `df.to_dict(outtype='series')` which is quite strange but `df.to_dict(outt... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7841 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7841/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7841/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7841/events | https://github.com/pandas-dev/pandas/issues/7841 | 38,743,703 | MDU6SXNzdWUzODc0MzcwMw== | 7,841 | MultiIndex.tostring() produces empty string for non-empty index | {
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... | 7 | 2014-07-25T15:44:41Z | 2017-06-10T22:00:39Z | 2017-06-10T22:00:39Z | NONE | null | With pandas 0.14.1, the following code produces an empty string:
```
import pandas
idx = pandas.MultiIndex(levels=[['a'],[0,1,2,3,4,4]],
labels=[[0,0,0,0,0],[0,1,2,3,4]],
names=[0,1])
print idx.tostring()
```
Is this behavior correct? `Index.tostring()` appears to prod... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7844 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7844/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7844/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7844/events | https://github.com/pandas-dev/pandas/pull/7844 | 38,779,512 | MDExOlB1bGxSZXF1ZXN0MTg5MjQ4ODA= | 7,844 | BUG/VIS: rot and fontsize are not applied to timeseries plots | {
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- timeseries line / area plot: `rot` is not applied to minor ticklabels, and `fontsize` is completely ignored. (Fixed to apply to xticklabels)
- kde plot: `rot` and `fontsize` are completely ignored. (Fixed to apply to xticklabels)
- scatter and he... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7846 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7846/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7846/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7846/events | https://github.com/pandas-dev/pandas/issues/7846 | 38,801,688 | MDU6SXNzdWUzODgwMTY4OA== | 7,846 | tz_localize() and tz_convert() doesn't work on MultiIndex | {
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```
In [1]: import pandas as pd
In [2]: pd.__version__
Out[2]: '0.14.1'
In [3]: cohort_date = pd.date_range('20140701', periods=5, freq='D')
In [4]: event_date = pd.date_range('20140701', periods=5, freq='D')
In [5]: multi_index = pd.MultiIndex.from_pr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7847 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7847/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7847/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7847/events | https://github.com/pandas-dev/pandas/issues/7847 | 38,813,075 | MDU6SXNzdWUzODgxMzA3NQ== | 7,847 | pandas.json.dumps gives incorrect results with numpy 1.6.1 | {
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] | closed | false | null | [] | null | 6 | 2014-07-26T08:23:53Z | 2014-07-28T18:07:17Z | 2014-07-28T12:50:03Z | CONTRIBUTOR | null | I ran into this nasty error when building / testing OSX wheels.
```
======================================================================
ERROR: test_timedelta (pandas.io.tests.test_json.test_pandas.TestPandasContainer)
----------------------------------------------------------------------
Traceback (most recent call... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7848 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7848/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7848/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7848/events | https://github.com/pandas-dev/pandas/issues/7848 | 38,814,676 | MDU6SXNzdWUzODgxNDY3Ng== | 7,848 | Categorical in dataframe is sorted lexically. | {
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``` python
df = pd.DataFrame({"id":[6,5,4,3,2,1], "raw_grade":['a', 'b', 'b', 'a', 'a', 'e']})
df["grade"] = pd.Categorical(df["raw_grade"])
df['grade'].cat.reorder_levels(['b', 'e', 'a'])
# sorts 'grade' according to the order of the levels
df.sort(columns=['grade'])
```
correct output
```
id raw_grade... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7849 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7849/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7849/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7849/events | https://github.com/pandas-dev/pandas/pull/7849 | 38,814,866 | MDExOlB1bGxSZXF1ZXN0MTg5MzA1NTY= | 7,849 | Docs: improve installation instructions, recommend Anaconda. | {
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"followers_url": "https://api.github.com/users/jr... | 22 | 2014-07-26T10:18:17Z | 2014-07-31T02:22:40Z | 2014-07-29T09:58:55Z | CONTRIBUTOR | null | I believe installing pandas via Anaconda should definitely be the recommended installation method for most users.
It is cross platform, doesn't require a compiler, and will install all requirements for the user also (including NumPy).
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https://api.github.com/repos/pandas-dev/pandas/issues/7850 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7850/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7850/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7850/events | https://github.com/pandas-dev/pandas/pull/7850 | 38,817,830 | MDExOlB1bGxSZXF1ZXN0MTg5MzE5MTY= | 7,850 | BUG: fix multi-column sort that includes Categoricals / concat (GH7848/GH7864) | {
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closes #7848
closes #7864
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https://api.github.com/repos/pandas-dev/pandas/issues/7851 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7851/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7851/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7851/events | https://github.com/pandas-dev/pandas/pull/7851 | 38,818,758 | MDExOlB1bGxSZXF1ZXN0MTg5MzIzMDU= | 7,851 | BUG: fix greedy date parsing in read_html | {
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closes #7762
closes #7032
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https://api.github.com/repos/pandas-dev/pandas/issues/7852 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7852/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7852/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7852/events | https://github.com/pandas-dev/pandas/pull/7852 | 38,818,828 | MDExOlB1bGxSZXF1ZXN0MTg5MzIzMzc= | 7,852 | ENH: tz_localize(None) allows to reset tz | {
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CC @rockg, @nehalecky
```
t = pd.Timestamp('2014-01-01 09:00', tz='Asia/Tokyo')
# tz_localize resets tz holding current tz representation
t.tz_localize(None)
#2014-01-01 09:00:00
# tz_convert reset tz using UTC represe... | {
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```
>>> ### left join with multiple matches - single index case
>>> left = DataFrame([
... ['X', 'Y', 'C', 'a'],
... ['W', 'Y', 'C', 'e'],
... ['V', 'Q', 'A', 'h'],
... ['V', 'R', 'D', 'i'],
... ['X', 'Y', 'D', 'b'],
... ['X', 'Y', 'A', 'c'],
... ['W', 'Q', 'B', 'f'],
... ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7854 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7854/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7854/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7854/events | https://github.com/pandas-dev/pandas/pull/7854 | 38,838,765 | MDExOlB1bGxSZXF1ZXN0MTg5NDA3MDQ= | 7,854 | CLN: Clean tslib, frequencies import | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-07-27T13:22:43Z | 2014-08-04T13:18:06Z | 2014-07-28T14:57:03Z | MEMBER | null | Fixed:
- Some modules are imported different aliases
- Merge duplicated functions (`maybe_get_tz` and `ensure_int64`)
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https://api.github.com/repos/pandas-dev/pandas/issues/7855 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7855/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7855/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7855/events | https://github.com/pandas-dev/pandas/pull/7855 | 38,845,205 | MDExOlB1bGxSZXF1ZXN0MTg5NDIxMTY= | 7,855 | BUG/API: allow get_indexer to work with nans | {
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... | 10 | 2014-07-27T16:23:32Z | 2015-04-08T15:03:14Z | 2015-04-08T15:03:14Z | MEMBER | null | - [ ] clear the FIXME in Categorical in #7820 (comment)
closes #7820
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https://api.github.com/repos/pandas-dev/pandas/issues/7856 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7856/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7856/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7856/events | https://github.com/pandas-dev/pandas/issues/7856 | 38,851,887 | MDU6SXNzdWUzODg1MTg4Nw== | 7,856 | set_option('max_colwidth', N) not working on groupby output | {
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Might be pilot error (or the incorrect expectations), but I was expecting the max_colwidth option to work on groupby terminal output. Replication here:
```
$ python
> import pandas as pd
> df = pd.DataFrame([{'a':'foo','b':'bar','c':'uncomfortably long line with lots of stuff','d':1}, \
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df = DataFrame(index=MultiIndex.from_product([[2011, 2012], [1,2,3]],
names=['year', 'month']))
df = df.reset_index()
str_year = df.year.astype('str')
str_month = df.month.astype('str')
str_both = str_year.str.cat(str_month, sep=' ')
```
... so far, everything is fine... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7858 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7858/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7858/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7858/events | https://github.com/pandas-dev/pandas/issues/7858 | 38,896,274 | MDU6SXNzdWUzODg5NjI3NA== | 7,858 | to_stata results in unnecessarily long strings | {
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In Stata, I then have trouble with it due to its length. codebook shows that my variable as been encoded as a string of length 244:
of type "string (str244), but longest is str5"
If tthe longest string is length 5, so should be the output var... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7859 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7859/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7859/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7859/events | https://github.com/pandas-dev/pandas/pull/7859 | 38,900,089 | MDExOlB1bGxSZXF1ZXN0MTg5NzMxNTA= | 7,859 | BUG: Check the first element of "others.values" rather than "others". | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-07-28T15:14:58Z | 2014-08-02T13:04:33Z | 2014-08-02T07:23:53Z | MEMBER | null | Closes #7857
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https://api.github.com/repos/pandas-dev/pandas/issues/7860 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7860/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7860/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7860/events | https://github.com/pandas-dev/pandas/issues/7860 | 38,923,397 | MDU6SXNzdWUzODkyMzM5Nw== | 7,860 | ENH: indexing support for reversed is_monotonic | {
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"followers_url": "https://api.github.com/users/jre... | 17 | 2014-07-28T19:23:34Z | 2014-11-02T22:41:28Z | 2014-11-02T22:41:28Z | NONE | null | conceptually not hard (and you can look at a the slices to figure this out, e.g. if start >= end or start>last_endpoint, you can just do a reversed is_monotonic), to avoid a perf hit I think, then just reverse the searching operations for slices would need to do `is_monotonic_decreasing` here : https://github.com/pydat... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7861 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7861/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7861/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7861/events | https://github.com/pandas-dev/pandas/issues/7861 | 38,948,873 | MDU6SXNzdWUzODk0ODg3Mw== | 7,861 | Series.view fails when series has a dtype of `object` (behavior change from 0.12) | {
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... | 13 | 2014-07-29T00:48:01Z | 2018-03-07T09:50:25Z | 2018-03-07T09:50:25Z | CONTRIBUTOR | null | As per the title, `Series.view(…)` fails when the `dtype` is `"object"`:
```
In [1]: import pandas as pd
In [2]: s = pd.Series([u'a', u'b', u'c'])
In [3]: s.view(pd.Series)
---------------------------------------------------------------------------
TypeError Traceback (most recent cal... | {
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"followers_url": "https://api.github.com/users/jr... | 17 | 2014-07-29T06:19:15Z | 2014-08-20T15:32:49Z | 2014-08-01T13:30:09Z | CONTRIBUTOR | null | Strings were incorrectly written using 244 character irrespective of the actual
length of the underlying due to changes in pandas where the underlying NumPy
datatype of strings is always np.object_, and never np.string_. Closes #7858
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https://api.github.com/repos/pandas-dev/pandas/issues/7863 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7863/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7863/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7863/events | https://github.com/pandas-dev/pandas/issues/7863 | 38,962,459 | MDU6SXNzdWUzODk2MjQ1OQ== | 7,863 | DataFrame to_json Column -> [values] orientation and scientifc notation? | {
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"descript... | closed | false | null | [] | null | 4 | 2014-07-29T06:45:43Z | 2014-08-05T16:21:47Z | 2014-08-05T16:21:47Z | NONE | null | Hi,
I'm exporting a data frame from pandas and importing it in a C++ program using rapidjson. I believe I have tested all available orientations and I am wondering if it was possible to obtain the following:
``` python
c1 c2
r1 1 2
r2 3 4
```
converted to
``` python
{ c1: [1, 3], c2: [2,4], index: [r1... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7864 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7864/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7864/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7864/events | https://github.com/pandas-dev/pandas/issues/7864 | 38,973,804 | MDU6SXNzdWUzODk3MzgwNA== | 7,864 | pd.concat reordering categorical levels lexically | {
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``` python
In [1]: import pandas as pd
In [2]: df = pd.DataFrame({"id":[1,2,3,4,5,6], "raw_grade":['a', 'b', 'b', 'a', 'a', 'e']})
...: df["grade"] = pd.Categorical(df["raw_grade"])
...: df['grade'].cat.reorder_levels(['e', 'a', 'b'])
...:
In [3]: df1 = df[0:3]
...: df2 = df[3:]
...:
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2014-07-29T09:59:48Z | 2018-07-06T22:03:12Z | 2018-07-06T21:22:13Z | CONTRIBUTOR | null | xref #7849
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https://api.github.com/repos/pandas-dev/pandas/issues/7866 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7866/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7866/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7866/events | https://github.com/pandas-dev/pandas/issues/7866 | 38,980,484 | MDU6SXNzdWUzODk4MDQ4NA== | 7,866 | BUG/API: bug in multi-index slicing with missing indexers | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-07-29T11:39:45Z | 2014-07-31T15:49:45Z | 2014-07-30T23:48:47Z | CONTRIBUTOR | null | I think the following _could_ work and not raise `KeyError` because of a missing indexer. This would follow the API of loc which will be effectively a reindex as long as you have at least 1 found value.
```
s = pd.Series(np.arange(9),index=pd.MultiIndex.from_product([['A','B','C'],['foo','bar','baz']],names=['one','tw... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7867 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7867/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7867/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7867/events | https://github.com/pandas-dev/pandas/pull/7867 | 38,981,460 | MDExOlB1bGxSZXF1ZXN0MTkwMjIwOTQ= | 7,867 | BUG: Bug in multi-index slicing with missing indexers (GH7866) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7868 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7868/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7868/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7868/events | https://github.com/pandas-dev/pandas/issues/7868 | 38,985,652 | MDU6SXNzdWUzODk4NTY1Mg== | 7,868 | Extending Dataframe | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2014-07-29T12:59:59Z | 2015-03-08T16:57:52Z | 2015-03-08T16:57:49Z | CONTRIBUTOR | null | I'm interested if there are recommended best practices for extending DataFrames.
I work on a project where we have an API for querying a database that returns DataFrames. I basically want a way to associate extra metadata with each column in the DataFrame. At a minimum this would allow me to run commands like `df.... | {
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In [1]: import pandas as pd
In [2]: pd.Series(dtype='m8[ns]').sum()
Out[2]: 0
In [3]: pd.Series(dtype='m8[ns]').mean()
Out[3]:
0 NaT
dtype: timedelta64[ns]
In [4]: pd.Series(dtype='m8[ns]').median()
Out[4]: nan
In [5]: pd.Series(dtype=float).sum()
Out[5]: 0
In [6]: pd.Series([0], dtype=float).sum()
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https://api.github.com/repos/pandas-dev/pandas/issues/7870 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7870/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7870/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7870/events | https://github.com/pandas-dev/pandas/issues/7870 | 39,005,576 | MDU6SXNzdWUzOTAwNTU3Ng== | 7,870 | groupby filtering is missing some groups | {
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```
In [20]: df = pd.DataFrame([
['best', 'a', 'x'],
['worst', 'b', 'y'],
['best', 'c', 'x'],
['best','d', 'y'],
['worst','d', 'y'],
['worst','d', 'y'],
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https://api.github.com/repos/pandas-dev/pandas/issues/7872 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7872/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7872/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7872/events | https://github.com/pandas-dev/pandas/issues/7872 | 39,026,626 | MDU6SXNzdWUzOTAyNjYyNg== | 7,872 | Give all NotImplementedErrors a description | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2014-07-29T19:36:57Z | 2015-04-14T14:21:22Z | 2015-04-14T14:19:43Z | CONTRIBUTOR | null | Currently some NotImplementedErrors don't have a description (most do!) .
```
raise NotImplemented
# should be
raise NotImplemented("short description of thing which isn't implemented")
```
I think this would be pretty useful, and makes it less confusing for users, and at least they would be pointed in the right dire... | {
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`df1 = df.at_time(time(15, 0), asof=True)`
asof is very useful. If implemented it would allow us to use the at_time functionality and work with data that might not be complete, or don't have homogeneous time stamps. It would enable us to get... | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-07-29T21:07:09Z | 2014-07-30T22:38:48Z | 2014-07-30T22:13:57Z | CONTRIBUTOR | null | Closes #7792
New `level` argument:
```
set_names(self, names, level=None, inplace=False)
set_levels(self, levels, level=None, inplace=False, verify_integrity=True)
set_labels(self, labels, level=None, inplace=False, verify_integrity=True)
```
e.g.
set_names('foo',level=1)
set_names(['foo','bar'],level=[1,2])... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7875 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7875/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7875/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7875/events | https://github.com/pandas-dev/pandas/issues/7875 | 39,072,440 | MDU6SXNzdWUzOTA3MjQ0MA== | 7,875 | ValueError Exception during reset_index of timezone-aware data | {
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import pandas as pd
import numpy as np
from datetime import datetime
import pytz
print "This is working:"
data = {23:np.nan, 24:-1949, 25:-1848, 26: np.nan}
date_without_timezone = datetime.now()
df = pd.DataFrame(data, index=[date_without_timezone,])
print df
print
print df.index
print
print df.stack()
pr... | {
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```
BARC:LON HSBA:LON LLOY:LON STAN:LON
timestamp
2014-07-03 08:02:00 217.551 601.938 76.2100 1223.36
2014-07-03 08:04:00 217.200 602.100 75.8520 1220.00
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7877 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7877/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7877/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7877/events | https://github.com/pandas-dev/pandas/issues/7877 | 39,086,490 | MDU6SXNzdWUzOTA4NjQ5MA== | 7,877 | ENH: support both SQLAlchemy engines and connections | {
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Also reported in #8533, #10104
---
My use case - I often add a week's worth of data (stored in a pandas dataframe) to an existing table. Before I add the data, I want to be able to delete any existing data for this week from the table, ... | {
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I'm on pandas 0.14.1. Timestamp seems to lose nanoseconds when converting to string and back. Wonder if this is bug.
``` python
In [18]: pd.Timestamp('20010101 00:00:00')+pd.tseries.offsets.Nano()
Out[18]: Timestamp('2001-01-01 00:00:00.000000001')
In [19]: pd.Timestamp('2001-01-01 00:00:00.000000001')
Out[19]:... | {
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"followers_url": "https://api.github.com/users/jorisva... | 17 | 2014-07-30T13:54:09Z | 2018-07-06T20:21:04Z | 2017-07-11T09:58:47Z | NONE | null | As already described in issue #3690, panel.to_frame discards all minor entries with nan in the data, which can be very confusing. I believe there should be a warning, first time data is dropped or the opposite should be the default behavior.
The warning could be treated similar to a ZeroDivisionWarning in numpy only o... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7880 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7880/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7880/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7880/events | https://github.com/pandas-dev/pandas/issues/7880 | 39,110,192 | MDU6SXNzdWUzOTExMDE5Mg== | 7,880 | Intersection of non-overlapping DatetimeIndexes with tz set fails | {
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``` python
import pandas as pd
a = pd.date_range('2014-07-07 12', freq='3min', periods=20,)
b = pd.date... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7881 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7881/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7881/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7881/events | https://github.com/pandas-dev/pandas/pull/7881 | 39,113,245 | MDExOlB1bGxSZXF1ZXN0MTkxMDIwNjU= | 7,881 | PERF: groupby / frame apply optimization | {
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-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
groupby_frame_apply_overhead | 9.1400 | 70.3743 | 0.129... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7882 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7882/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7882/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7882/events | https://github.com/pandas-dev/pandas/issues/7882 | 39,124,565 | MDU6SXNzdWUzOTEyNDU2NQ== | 7,882 | Comparison with R should discuss dcast as well as aggregate | {
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"f... | 4 | 2014-07-30T18:52:32Z | 2021-02-07T19:00:26Z | null | NONE | null | The [Comparison with R](http://pandas.pydata.org/pandas-docs/stable/comparison_with_r.html) docs have a great section on how to go from R's `aggregate` function to Pandas's `groupby`, but as [this StackOverflow](http://stackoverflow.com/questions/25043927/dcast-replicate-in-python) question shows, there are similar but... | {
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"followers_url": "https://api.github.com/users/wesm... | 29 | 2014-07-30T20:41:51Z | 2019-12-31T15:04:44Z | 2019-12-31T15:04:44Z | CONTRIBUTOR | null | The original thread is [here](http://stackoverflow.com/questions/25046252/filling-in-with-the-last-entry-of-the-group?noredirect=1#comment38958154_25046252).
``` python
> df
C D E
A B
bar one -1.350006 0.260339 2
three -0.236451 -0.056614 0
flux six... | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-07-31T02:13:35Z | 2014-08-20T01:51:33Z | 2014-08-02T13:46:41Z | CONTRIBUTOR | null | In the examples below with `min_periods=2`, `expanding_mean/std` start to give values once there are two values, but `ewma/std` only once there are three values. Is this intentional? It looks like a bug to me.
```
In [1]: from pandas import Series, expanding_mean, expanding_std, ewma, ewmstd, show_versions
In [2]: s ... | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-07-31T02:50:57Z | 2014-09-07T14:30:53Z | 2014-09-07T14:30:53Z | CONTRIBUTOR | null | http://stackoverflow.com/questions/25050015/resampling-over-dates-in-both-levels-of-a-multiindex-pandas-dataframe/25050074#25050074
```
from datetime import date
d0 = date.today() - timedelta(days=14)
dates = pd.date_range(d0, date.today())
date_index = pd.MultiIndex.from_product([dates, dates], names=['cohort_date', ... | {
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related #7867
I think this should raise as this is not clear how this should work (e.g. should you get all the other levels set to `nan`?)
or see my comment below, maybe just document?
```
In [11]: s = pd.Series(np.arange(9),index=pd.MultiIndex.from_product([['A','B','C'],['foo','bar','baz']],names=['... | {
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... | 8 | 2014-07-31T11:36:43Z | 2021-04-11T04:59:23Z | 2021-04-11T04:59:23Z | CONTRIBUTOR | null | from #7867
```
In [1]: s = pd.Series([1,2,3])
In [2]: s
Out[2]:
0 1
1 2
2 3
dtype: int64
# this is de-facto: s.reindex([[1,2,3]])
In [3]: s.loc[[1,2,3]]
Out[3]:
1 2
2 3
3 NaN
dtype: float64
```
should this work?
```
In [4]: s.loc[[1,2,3]] = 4
KeyError: '[3] not in index'
```
(Doing this with... | {
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```
In [3]: date1 = datetime.date.today()
In [4]: date2 = datetime.date.today().replace(month=1)
In [5]: date_cols=['date1', 'date2']
In [6]: index = pd.MultiIndex.from_product([[date1],[da... | {
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In [1]: import pandas as pd
In [2]: pd.Series().product()
Out[2]: nan
```
I excepted:
```
Out[2]: 1
```
http://en.wikipedia.org/wiki/Empty_product
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It would be nice to be able to write:
``` python
s[s.index.isin(['a', 'b', 'c'], level='foo')]
```
instead of
``` python
s[s.index.get_level_values('foo').isin(['a', 'b', 'c'])]
```
The former variant is not only shorter but is also potentially more performant: one only has to look up levels in given co... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7891 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7891/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7891/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7891/events | https://github.com/pandas-dev/pandas/pull/7891 | 39,216,397 | MDExOlB1bGxSZXF1ZXN0MTkxNjUxMDE= | 7,891 | CLN/INT: remove Index as a sub-class of NDArray | {
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should allow much easier new Index classes (e.g. #7640)
This doesn't change the public API at all, and provides compat
closes #5080
back compat for pickles is now way simpler
ToDo:
- docs
- [x] release note
- [x] warnings in io.rst abou... | {
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This PR adds `level` kwarg for `Index` objects as discussed (briefly in #7890):
``` python
Index.isin(iterable, level=None)
```
### Summary
- for non-`MultiIndex` classes:
- no functional changes in the actual membership test
- valid `level` values are `None`, `0`, `-1` and `self.name`
- if `level... | {
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Hi,
I encountered an edge case in DataFrame initialization with something like the following:
``` python
In [1]: from pandas import *
In [2]: s = Series(1, name='foo')
In [3]: df = DataFrame(s, columns=['bar'])
In [4]: df
Empty DataFrame
Columns: [bar]
Index: []
```
T... | {
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] | closed | false | null | [] | null | 31 | 2014-07-31T21:52:23Z | 2014-08-02T13:47:56Z | 2014-08-02T13:47:56Z | NONE | null | I have a large dataset (4 million rows, 50 columns) stored via pandas store.append. When I use either store.select or read_hdf with a query for 2 columns being greater than a certain value (i.e. "(a > 10) & (b > 1)" I get 15,000 or so rows returned.
When I read in the entire table, as say df, and do df[(df.a > 10) & ... | {
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... | 6 | 2014-08-01T00:51:23Z | 2021-04-11T05:01:19Z | null | CONTRIBUTOR | null | xref #10347
I'm having trouble understand how exactly reindex is supposed to work in the case of MultiIndex. What I would like is the exact behavior in the Index case where values can be filled or padded according to some level of the MultiIndex. I can't understand what reindex is doing in the MultiIndex case. The... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7896 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7896/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7896/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7896/events | https://github.com/pandas-dev/pandas/pull/7896 | 39,306,398 | MDExOlB1bGxSZXF1ZXN0MTkyMjAzMTQ= | 7,896 | BUG: fixing ewma() for adjust=False and ignore_na=False | {
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"followers_url": "https://api.github.com/users/jr... | 10 | 2014-08-01T16:37:34Z | 2014-09-10T00:12:18Z | 2014-08-01T18:30:44Z | CONTRIBUTOR | null | The previous code in https://github.com/pydata/pandas/pull/7603 wasn't quite right for the case that both `adjust=False` and `ignore_na=False`. This PR fixes the handling of that case. Note that `ignore_na=False` behavior is new in v0.15.0, so this bug and its fix don't affect any prior behavior.
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"followers_url": "https://api.github.com/users/jr... | 6 | 2014-08-01T17:19:09Z | 2014-08-07T14:27:08Z | 2014-08-07T14:27:08Z | NONE | null | This means that patterns such as:
``` python
if my_frame.index:
# do something
```
with `my_frame` having a `MultiIndex` will never enter the `if` block. One can check that `bool(my_frame.index)` returns False. A single index (`pandas.Index`) will (correctly IMO) raise a `ValueError` warning that the truth valu... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7898 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7898/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7898/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7898/events | https://github.com/pandas-dev/pandas/pull/7898 | 39,318,072 | MDExOlB1bGxSZXF1ZXN0MTkyMjc2OTM= | 7,898 | BUG: ewm*() interpretation of min_periods is off by one | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2014-08-01T19:00:22Z | 2014-09-10T00:12:07Z | 2014-08-02T13:46:41Z | CONTRIBUTOR | null | Closes https://github.com/pydata/pandas/issues/7884.
This addresses only the `ewm*()` functions' off-by-one interpretation of `min_periods`.
It doesn't address the inconsistency between the `ewm*()` functions and the `rolling_*()` functions in the meaning of `min_periods`.
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https://api.github.com/repos/pandas-dev/pandas/issues/7899 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7899/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7899/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7899/events | https://github.com/pandas-dev/pandas/pull/7899 | 39,318,919 | MDExOlB1bGxSZXF1ZXN0MTkyMjgyNTk= | 7,899 | NotImplementedError messages doc update #7872 | {
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"closed_at": "2015-05-11T15:46:03Z",
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I have updated the NonImplementedError messages #7872 in all places applicable.
It includes changes to statements of type
- raise NotImplementedError
- raise NotImplementedError()
Comment on the changes.
The one place I have doubt and not sure whether to add one or not would be https://github.com/pyda... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7900 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7900/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7900/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7900/events | https://github.com/pandas-dev/pandas/issues/7900 | 39,333,057 | MDU6SXNzdWUzOTMzMzA1Nw== | 7,900 | BUG: Inconsistencies in calculating second moments of a single value | {
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"description": "Arithmetic, Comparison, ... | closed | false | null | [] | {
"closed_at": "2014-10-23T11:43:09Z",
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"followers_url": "https://api.github.com/users/jr... | 15 | 2014-08-01T22:29:59Z | 2014-09-15T06:23:09Z | 2014-09-10T00:02:26Z | CONTRIBUTOR | null | I noticed (in https://github.com/pydata/pandas/issues/7884) that `ewmvar`, `ewmstd`, `ewmvol`, `ewmcov`, `rolling_var`, and `rolling_std` return `0.0` for a single value (assuming `min_periods=0`); whereas `Series.std`, `Series.var`, `ewmcorr`, `expanding_cov`, `expanding_corr`, `rolling_cov`, and `rolling_corr` all re... | {
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