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https://api.github.com/repos/pandas-dev/pandas/issues/7901 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7901/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7901/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7901/events | https://github.com/pandas-dev/pandas/issues/7901 | 39,338,980 | MDU6SXNzdWUzOTMzODk4MA== | 7,901 | date_range does not capture right timezone from input dates | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7902 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7902/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7902/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7902/events | https://github.com/pandas-dev/pandas/pull/7902 | 39,344,208 | MDExOlB1bGxSZXF1ZXN0MTkyNDM4NTY= | 7,902 | BUG: do not assume 0 is in index of potential Series | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7903 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7903/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7903/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7903/events | https://github.com/pandas-dev/pandas/pull/7903 | 39,345,794 | MDExOlB1bGxSZXF1ZXN0MTkyNDQ2MTY= | 7,903 | TST/BUG: Rename html encoding test files. | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2014-08-02T09:27:50Z | 2014-08-02T22:13:59Z | 2014-08-02T12:59:20Z | CONTRIBUTOR | null | html test_encode fails on OSX 10.9.4 due to missing dash in `utf32` encoding
string.
The test encoding string is derived from a split of the test file name.
Only utf32 is affected but this commit changes the utf8 and utf16 containing filenames as well for the sake of consistency.
``` ================================... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7904 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7904/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7904/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7904/events | https://github.com/pandas-dev/pandas/issues/7904 | 39,349,111 | MDU6SXNzdWUzOTM0OTExMQ== | 7,904 | INT: followup to Index not a sub-class of ndarray | {
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- [x] tests for `argmin/argmax`, #7951
- [x] doc-strings for properties / functions that are ndarray compat, #7891, #7951
- [x] `any/all` doc-strings (series/index) (unbox already does this)
- [ ] `searchsorted`, #7447
- [x] `Index.__nonzero__` should raise ? #7897, fixed in #7951
- [x] see if ca... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7905 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7905/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7905/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7905/events | https://github.com/pandas-dev/pandas/pull/7905 | 39,350,413 | MDExOlB1bGxSZXF1ZXN0MTkyNDY2NTc= | 7,905 | ENH: Add BusinessHour offset | {
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"closed_at": "2015-05-11T15:46:03Z",
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"followers_url": "https://api.github.com/users/jr... | 10 | 2014-08-02T14:56:55Z | 2015-05-06T17:38:09Z | 2015-05-05T22:27:56Z | MEMBER | null | Closes #2469. Create `BusinessHour` offset to specify business hours on `BusinessDay`. Appreciated if any feedbacks regarding bahaviours, keywords, etc.
### Basic
By default, use 9:00 - 17:00 as business hours. Adding `BusinessHour` will increment timestamp by hourly on the days belong to `BusinessDay` offset.
```
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https://api.github.com/repos/pandas-dev/pandas/issues/7906 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7906/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7906/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7906/events | https://github.com/pandas-dev/pandas/pull/7906 | 39,357,279 | MDExOlB1bGxSZXF1ZXN0MTkyNDk3NjU= | 7,906 | DOC: grammar fixes in docs | {
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- `Timestamp` parsing results incorrect if input contains offset string (Closes #7833).
NOTE: Also modified `Timestamp.__repr__` to display fixed timezone info, because this can be either `pytz` or `dateutil`.
```
# Result after the fix
# If string contain... | {
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tar tf /sw/src/pandas-0.14.1.tar.gz | grep '~' | head
pandas-0.14.1/doc/sphinxext/numpydoc.py~
pandas-0.14.1/doc/sphinxext/**init**.py~
pandas-0.14.1/doc/sphinxext/docscrape_sphinx.py~
pandas-0.14.1/doc/source/gotchas.rst~
pandas-0.14.1/doc/source/ecosystem.... | {
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Fixes #7901
Fixes #7835.
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https://api.github.com/repos/pandas-dev/pandas/issues/7910 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7910/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7910/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7910/events | https://github.com/pandas-dev/pandas/pull/7910 | 39,379,689 | MDExOlB1bGxSZXF1ZXN0MTkyNTk0Njk= | 7,910 | added support for selecting multiple nth values | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2014-08-03T21:20:30Z | 2015-04-29T15:33:46Z | 2014-09-04T00:42:46Z | CONTRIBUTOR | null | I'm not 100% sure this is the best way to implement this, but I think it'd be nice for GroupBy.nth() to support selecting multiple values. For instance if we have
```
df = DataFrame(1, index=pd.date_range(start='1/1/2013', end='6/30/2014', freq='B'), columns=['a', 'b'])
```
and currently we can easily get the nth ent... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7911 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7911/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7911/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7911/events | https://github.com/pandas-dev/pandas/issues/7911 | 39,383,948 | MDU6SXNzdWUzOTM4Mzk0OA== | 7,911 | ENH: add "adjust" parameter to ewmvar(), ewmstd(), ewmvol(), ewmcov(), and ewmcorr() | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-08-04T00:48:56Z | 2014-09-10T00:02:26Z | 2014-09-10T00:02:26Z | CONTRIBUTOR | null | Currently `ewma()` has an `adjust` parameter (affecting how the weights are calculated) whereas all the other `ewm*()` functions do not. When they call `ewma()`, `adjust` is implicitly set to its default value, `True`. This is probably fine in most cases, but if `ewma()` is going to expose the `adjust` parameter, the o... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7912 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7912/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7912/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7912/events | https://github.com/pandas-dev/pandas/issues/7912 | 39,384,794 | MDU6SXNzdWUzOTM4NDc5NA== | 7,912 | BUG: ewmvar/std/cov() de-biasing formula incorrect | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2014-08-04T01:27:58Z | 2014-09-10T00:02:26Z | 2014-09-10T00:02:26Z | CONTRIBUTOR | null | `ewmvar()` and `ewmcov()` contain the following code:
```
if not bias:
result *= (1.0 + 2.0 * com) / (2.0 * com)
```
Where does this scaling formula come from? Does the number of observations not enter in to the bias of the (sample) variance estimation? I would imagine that perhaps the formula above is fo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7913 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7913/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7913/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7913/events | https://github.com/pandas-dev/pandas/pull/7913 | 39,387,562 | MDExOlB1bGxSZXF1ZXN0MTkyNjM0MTA= | 7,913 | update to holiday to help with GH#7070 | {
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"followers_url": "https://api.github.com/users/jr... | 14 | 2014-08-04T03:09:11Z | 2014-08-19T19:33:03Z | 2014-08-11T12:57:15Z | CONTRIBUTOR | null | I am working on a financial calendar and wanted to add the following functions to pandas.tseries.holiday in order to properly handle half days.
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https://api.github.com/repos/pandas-dev/pandas/issues/7914 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7914/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7914/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7914/events | https://github.com/pandas-dev/pandas/issues/7914 | 39,390,513 | MDU6SXNzdWUzOTM5MDUxMw== | 7,914 | DataFrame with MultiIndex columns implicitly assumes that stored data has an ndim attribute | {
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```
df = DataFrame([[np.mean, np.median],['mean','median']],
columns=MultiIndex.from_tuples([('functs','mean'),
('functs','median')]),
index=['function', 'name']... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7915 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7915/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7915/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7915/events | https://github.com/pandas-dev/pandas/pull/7915 | 39,391,827 | MDExOlB1bGxSZXF1ZXN0MTkyNjU3MTA= | 7,915 | ENH: New `level` argument for DataFrame.tz_localize and DataFrame.tz_convert (GH7846) | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2014-08-04T05:34:58Z | 2014-08-07T20:47:42Z | 2014-08-07T20:47:32Z | CONTRIBUTOR | null | Closes #7846
New `level` argument for `DataFrame.tz_localize()` and `DataFrame.tz_convert()`, needed for a DataFrame with MultiIndex:
```
tz_convert(self, tz, axis=0, level=None, copy=True)
tz_localize(self, tz, axis=0, level=None, copy=True, infer_dst=False)
```
@jreback Not sure if `test_generic.py` is the right p... | {
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values are identical.
Need to assess both correctness and performance impact.
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https://api.github.com/repos/pandas-dev/pandas/issues/7917 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7917/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7917/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7917/events | https://github.com/pandas-dev/pandas/pull/7917 | 39,397,815 | MDExOlB1bGxSZXF1ZXN0MTkyNjkwNTk= | 7,917 | DOC: small fixes categorical docs | {
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There were also some other failures, but I will open an issue for those (don't directly see the solution for them).
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https://api.github.com/repos/pandas-dev/pandas/issues/7918 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7918/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7918/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7918/events | https://github.com/pandas-dev/pandas/issues/7918 | 39,398,284 | MDU6SXNzdWUzOTM5ODI4NA== | 7,918 | DOC/BUG: errors in the categorical docs | {
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- Docs say "Writing data to a HDF store works", but `df.to_hdf(hdf_file, "frame")` gives a `TypeError: objects of type ``Categorical`` are not supported in this context, sorry` (http://pandas-docs.github.io/pandas-docs-travis/categorical.html#getting-data-in-out). ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7919 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7919/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7919/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7919/events | https://github.com/pandas-dev/pandas/issues/7919 | 39,411,628 | MDU6SXNzdWUzOTQxMTYyOA== | 7,919 | Api: shared axis of plot | {
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Example:
```
fig, axes = plt.subplots(3,2)
seriesA.plot(ax=axes[1][0])
seriesB.plot(ax= axes[2][1], sharey=axes[1][0])
```
even ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7920 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7920/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7920/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7920/events | https://github.com/pandas-dev/pandas/pull/7920 | 39,419,214 | MDExOlB1bGxSZXF1ZXN0MTkyODEyMjY= | 7,920 | DOC: Fix release note for GH7798 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7921 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7921/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7921/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7921/events | https://github.com/pandas-dev/pandas/pull/7921 | 39,421,237 | MDExOlB1bGxSZXF1ZXN0MTkyODI0Mzc= | 7,921 | REGR: Regression in multi-index indexing with a non-scalar type object (GH7914) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7922 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7922/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7922/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7922/events | https://github.com/pandas-dev/pandas/issues/7922 | 39,421,331 | MDU6SXNzdWUzOTQyMTMzMQ== | 7,922 | statsmodels frequency inference problems on 0.14.0 | {
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] | closed | false | null | [] | null | 7 | 2014-08-04T13:41:31Z | 2014-12-04T09:52:18Z | 2014-08-06T21:17:17Z | CONTRIBUTOR | null | Reports are starting to trickle in of failing statsmodels tests on pandas 0.14.0. I haven't had a chance to see what the problem is yet.
https://github.com/statsmodels/statsmodels/issues/1822
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https://api.github.com/repos/pandas-dev/pandas/issues/7923 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7923/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7923/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7923/events | https://github.com/pandas-dev/pandas/pull/7923 | 39,428,661 | MDExOlB1bGxSZXF1ZXN0MTkyODcxMDY= | 7,923 | BUG: Fix Grouper with multi-level index and frequency (GH7885) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7924 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7924/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7924/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7924/events | https://github.com/pandas-dev/pandas/pull/7924 | 39,428,821 | MDExOlB1bGxSZXF1ZXN0MTkyODcyMDI= | 7,924 | BUG/DOC: Categorical fixes (GH7918) | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-08-04T15:01:57Z | 2014-08-04T20:29:34Z | 2014-08-04T20:29:34Z | CONTRIBUTOR | null | Categoricals now raise NotImplementedError when writing to HDFStore with a Fixed type store
Slicing bug with a single-dtyped category and a possible view
closes #7918
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https://api.github.com/repos/pandas-dev/pandas/issues/7925 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7925/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7925/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7925/events | https://github.com/pandas-dev/pandas/issues/7925 | 39,437,224 | MDU6SXNzdWUzOTQzNzIyNA== | 7,925 | Bug in rolling_* functions when combining center and min_periods arguments | {
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I have found some incorrect behavior in the pd.rolling_\* functions regarding the combination of 'center' and 'min_periods' arguments. I believe this is an issue for all rolling_\* functions. Here is an example using rolling_mean:
When using only the 'center' argument, the behavior works as expected:
``` pyt... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7926 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7926/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7926/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7926/events | https://github.com/pandas-dev/pandas/pull/7926 | 39,437,621 | MDExOlB1bGxSZXF1ZXN0MTkyOTI1ODk= | 7,926 | API/BUG/ENH: ewmvar/cov debiasing factors; add 'adjust' to ewmvar/std/vol/cov/corr; ewm*() min_periods | {
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"followers_url": "https://api.github.com/users/jr... | 42 | 2014-08-04T16:34:07Z | 2014-09-10T00:11:00Z | 2014-09-10T00:02:26Z | CONTRIBUTOR | null | Closes https://github.com/pydata/pandas/issues/7911.
Closes https://github.com/pydata/pandas/issues/7912.
Closes https://github.com/pydata/pandas/issues/7977.
Closes https://github.com/pydata/pandas/issues/7900.
These are all fixed simultaneously in order to enable consistency testing across the various functions.
En... | {
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I was testing the index sub-class on 3.4 (may have appeared on travis too)
`/mnt/home/jreback/venv/py3.4/index/pandas/io/tests/data/html_encoding/chinese_utf-16.html'`
```
======================================================================
ERROR: test_en... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7928 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7928/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7928/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7928/events | https://github.com/pandas-dev/pandas/pull/7928 | 39,444,962 | MDExOlB1bGxSZXF1ZXN0MTkyOTcyMzM= | 7,928 | BUG: define empty product on Series and DataFrame to be 1 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7929 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7929/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7929/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7929/events | https://github.com/pandas-dev/pandas/issues/7929 | 39,456,357 | MDU6SXNzdWUzOTQ1NjM1Nw== | 7,929 | BUG: resample unexpectedly branching on type of `how` callable | {
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"followers_url": "https://api.github.com/users/jr... | 11 | 2014-08-04T20:13:40Z | 2014-08-12T19:24:44Z | 2014-08-10T03:47:08Z | CONTRIBUTOR | null | I was about to answer an SO question giving the standard "use `lambda` or `functools.partial`" to create a new function with bound arguments when to my surprise my example didn't work with the OP's code. After some experimentation, it turns out to be because we don't always get the same return type. For example:
```... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7930 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7930/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7930/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7930/events | https://github.com/pandas-dev/pandas/issues/7930 | 39,462,433 | MDU6SXNzdWUzOTQ2MjQzMw== | 7,930 | to_datetime %Y%m%d does not coerce correctly | {
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see this example:
```
# imagine a dataframe with a from/to
x_df = DataFrame([[20120101, 20121231], [20130101, 20131231], [20140101, 20141231], [20150101, 99991231]])
x_df.columns = ['date_from', 'date_to']
date_def = '%Y%m%d'
# so everything is ok & peachy for the from dates
x_df['date_from_2'] = pd.to_datetime(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7931 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7931/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7931/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7931/events | https://github.com/pandas-dev/pandas/pull/7931 | 39,464,905 | MDExOlB1bGxSZXF1ZXN0MTkzMTAxNzM= | 7,931 | BUG: Bug in to_datetime when format='%Y%m%d and coerce=True are specified (GH7930) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7932 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7932/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7932/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7932/events | https://github.com/pandas-dev/pandas/issues/7932 | 39,470,901 | MDU6SXNzdWUzOTQ3MDkwMQ== | 7,932 | BUG: periodindex converted to Series incorrectly getting coerce to int64 | {
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"... | closed | false | null | [] | {
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In [47]: span
Out[47]:
<class 'pandas.tseries.period.PeriodIndex'>
[2012-12-31, ..., 9999-12-31]
Length: 3, Freq: D
In [48]: Series(span)
Out[48]:
0 15705
1 16404
2 2932896
dtype: int64
In [49]: Series(span.asobject)
Out[49]:
0 2012-12-31
1 2014-11-30
2 9999-12-31
dtype: object
```
I bel... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7933 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7933/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7933/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7933/events | https://github.com/pandas-dev/pandas/pull/7933 | 39,471,180 | MDExOlB1bGxSZXF1ZXN0MTkzMTQyMjM= | 7,933 | DOC: update docs to show construction of periodindex when needing out-of bounds spans | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7934 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7934/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7934/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7934/events | https://github.com/pandas-dev/pandas/pull/7934 | 39,471,622 | MDExOlB1bGxSZXF1ZXN0MTkzMTQ1MDk= | 7,934 | BUG: rolling/expanding_* treatment of center | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7935 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7935/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7935/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7935/events | https://github.com/pandas-dev/pandas/issues/7935 | 39,472,848 | MDU6SXNzdWUzOTQ3Mjg0OA== | 7,935 | [pandas/io/stata.py] Importing option for importing specified columns from stata .dta files | {
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"followers_url": "https://api.github.com/users/jre... | 6 | 2014-08-04T23:54:07Z | 2014-10-30T11:19:43Z | 2014-10-20T11:03:40Z | NONE | null | It would be great if a `columns` option could be added to the Stata Reader. Some `dta` files can be large and I would like to import a few specified columns. Current I am importing the entire file and returning a selection such as:
``` python
data = pd.read_stata(fn)[['year', 'exports']]
```
I would propose `pd.read_... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7936 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7936/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7936/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7936/events | https://github.com/pandas-dev/pandas/issues/7936 | 39,496,872 | MDU6SXNzdWUzOTQ5Njg3Mg== | 7,936 | 'MySQLConverter' object has no attribute '_timestamp_to_mysql' error with datetime64[ns], MySQL and MySQL-connector | {
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This code
```
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import pandas as pd
import numpy as np
import sqlalchemy
def main():
N = 5
df = pd.DataFrame({'Date':pd.date_range('2000-12-29', freq='D', periods=N), 'Open': range(N)})
scheme = 'mysql+mysqlconnector'
config = {
'host' :... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7937 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7937/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7937/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7937/events | https://github.com/pandas-dev/pandas/pull/7937 | 39,500,711 | MDExOlB1bGxSZXF1ZXN0MTkzMzA5MjU= | 7,937 | DOC: mention that stack/unstack implicicly sort | {
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(Yes, I know there is a note somewhere warning users that some operations depend on the index being sorted, but maybe this is a sligthly different case, since the operations do work after all, the problem is t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7938 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7938/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7938/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7938/events | https://github.com/pandas-dev/pandas/issues/7938 | 39,512,314 | MDU6SXNzdWUzOTUxMjMxNA== | 7,938 | Timestamp sub second resolution not supported with MySQL | {
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Timestamp sub second resolution doesn't seem to be supported with mysqldb.
See:
```python
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import pandas as pd
import numpy as np
import sqlalchemy
def main():
N = 5
df = pd.DataFrame({'Date':pd.date_range('2000-12-29', freq='D', periods=N... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7939 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7939/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7939/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7939/events | https://github.com/pandas-dev/pandas/issues/7939 | 39,513,466 | MDU6SXNzdWUzOTUxMzQ2Ng== | 7,939 | Inconsistent treatment of None with .where() and inplace | {
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"followers_url": "https://api.github.com/users/jr... | 20 | 2014-08-05T12:24:10Z | 2014-08-19T16:42:50Z | 2014-08-19T16:42:50Z | CONTRIBUTOR | null | Calling `.where()` treats `None` differently depending on the value of `inplace`.
```
In [1]: import pandas
In [2]: s1 = pandas.Series(['a', 'b', 'c'])
In [3]: s1.where(s1 != 'a', None)
Out[3]:
0 None
1 b
2 c
dtype: object
In [4]: s2 = pandas.Series(['a', 'b', 'c'])
In [5]: s2.where(s1 != 'a', None... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7940 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7940/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7940/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7940/events | https://github.com/pandas-dev/pandas/pull/7940 | 39,515,382 | MDExOlB1bGxSZXF1ZXN0MTkzMzk2MjM= | 7,940 | BUG/API: Consistency in .where() when setting with None for both inplace in a Series (GH7939) | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-08-05T12:51:27Z | 2014-08-06T15:44:30Z | 2014-08-05T13:18:00Z | CONTRIBUTOR | null | closes #7939
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https://api.github.com/repos/pandas-dev/pandas/issues/7941 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7941/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7941/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7941/events | https://github.com/pandas-dev/pandas/pull/7941 | 39,515,952 | MDExOlB1bGxSZXF1ZXN0MTkzMzk5NzQ= | 7,941 | API: Coerce None according to the dtype of the container | {
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"followers_url": "https://api.github.com/users/jr... | 17 | 2014-08-05T12:59:05Z | 2014-09-04T00:23:14Z | 2014-08-19T16:42:50Z | CONTRIBUTOR | null | This pull request fixes #7939 by ensuring that None coercion always obeys the following rules:
1. If the container is numeric, None should be coerced to NaN
2. If the container is for time data, None should be coerced to NaT
3. If the container contains heterogenous data (i.e. objects), None should be preserved.
## Old... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7942 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7942/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7942/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7942/events | https://github.com/pandas-dev/pandas/issues/7942 | 39,533,488 | MDU6SXNzdWUzOTUzMzQ4OA== | 7,942 | BUG: DataFrame bdate_range index being changed under concat()? | {
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] | closed | false | null | [] | null | 14 | 2014-08-05T15:53:40Z | 2014-08-29T21:53:05Z | 2014-08-29T20:11:28Z | CONTRIBUTOR | null | It looks like `concat()` changes the bdate_range index of a DataFrame:
```
In [1]: from pandas.util.testing import assert_series_equal, assert_frame_equal
In [2]: from pandas import Series, DataFrame, concat, bdate_range
In [3]: import numpy as np
In [4]: from datetime import datetime
In [5]: df = DataFrame(np.nan... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7943 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7943/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7943/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7943/events | https://github.com/pandas-dev/pandas/issues/7943 | 39,536,367 | MDU6SXNzdWUzOTUzNjM2Nw== | 7,943 | tz_localize should support is_dst input array | {
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"followers_url": "https://api.github.com/users/jr... | 14 | 2014-08-05T16:23:25Z | 2014-09-13T19:27:34Z | 2014-09-13T19:27:34Z | CONTRIBUTOR | null | When storing datetimes with timezone information in mysql I split out the is_dst flag into a separate column. Then when reconstructing the Timestamps I am either forced to iterate through each row and call pytz.timezone.localize on every Timestamp which is very slow or do some magic with localizing what I can and then... | {
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``` python
try:
do_smth()
except MyError:
do_smth_otherwise()
```
as opposed to
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if i_can_do_smth():
do_smth()
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xref #6812
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FYI technically there are 2 situations where the same error is raised: 1) setting on a copy, 2) chained assignment on a view. Both are really similar and result in usually the same issue. An assignment that doesn't appear to assign anything... | {
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DOC: release notes corrections
API: raise on `__nonzero__` for Indexes, closes #7897
partial close of #7904
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Add support to read/write data from/to a specific database schema through a `schema` keyword. If this is `None`, use the default schema as before.
- [x] support via a `schema` arg in the `read_sql_table` and `to_sql` functions
- [x] not for `read_sql_query` -> is this needed? (t... | {
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```
In [1]: s = Series(date_range('20130101',periods=3))
In [2]: s.dt.
s.dt.date s.dt.dayofweek s.dt.hour s.dt.is_month_start s.dt.is_quarter_start s.dt.is_year_start s.dt.minute s.dt.nanosecond s.dt.second s.dt.week s.dt... | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2014-08-07T18:03:20Z | 2014-08-07T19:06:59Z | 2014-08-07T19:00:31Z | MEMBER | null | because i live dangerously and run master pretty much all the time i found this in some code of mine that saves indices to matlab files, the solution is to call `.values`, but it would be nice if we could not break this.
Here's a simple test:
``` python
import pandas as pd
import numpy as np
from scipy.io import save... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7956 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7956/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7956/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7956/events | https://github.com/pandas-dev/pandas/issues/7956 | 39,756,334 | MDU6SXNzdWUzOTc1NjMzNA== | 7,956 | csv writer engine 'fast' has a bug | {
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rdr2.to_csv('jdate_test_out.csv', index=False)
csvtest = pd.read_csv('jdate_test_out.csv')
print csvtest.jdate.ptp()
rdr2.to_csv('jdate_test_out.csv', index=False, engine='fast')
csvtest = pd.read_csv('jdate_test_out.csv')
print csvtest.jdate.ptp()
```
0.0416644699872
0.0
Disclaimer: the 'fast' engine came... | {
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... | 11 | 2014-08-07T21:52:44Z | 2020-05-16T03:33:27Z | null | NONE | null | In `_sqlalchemy_type` function, pandas import Text type from sqlalchemy as the default type when generating text field in SQL table, which is transformed into "text" type in microsoft sql. This type could not be used by "group by" in SQL query.
SQL query with a group by clause with the field generate an error msg like... | {
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... | 18 | 2014-08-08T00:50:03Z | 2021-01-24T18:00:40Z | 2021-01-24T18:00:39Z | NONE | null | I'm building a simulation tool that essentially requires iterating through some fairly large DataFrames with iterrows (ie. the tool cannot be vectorized). I've looked into converting it to Cython but I'm just not that skilled with Cython to make it work. Also, I don't quite get why it's such a no-no to iterate on row... | {
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... | 16 | 2014-08-08T09:19:08Z | 2021-04-11T05:06:33Z | null | MEMBER | null | Follow-up of #6300 to discuss the object-oriented API for the sql functions.
So there are two ways to interact with SQL databases:
- more simple, high-level functions: `read_sql_query`, `read_sql_table`, `to_sql`
- "OO API" for more advanced functionality
The high-level functions are already quite polished (but there... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7962 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7962/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7962/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7962/events | https://github.com/pandas-dev/pandas/issues/7962 | 39,813,240 | MDU6SXNzdWUzOTgxMzI0MA== | 7,962 | BUG: Interpolation with 'limit' argument gives error when there are no nan values in the data series | {
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"color": "009800"... | closed | false | null | [] | null | 1 | 2014-08-08T11:15:40Z | 2014-08-08T12:31:03Z | 2014-08-08T12:30:56Z | CONTRIBUTOR | null | See the following code:
``` python
from pandas import DataFrame
from numpy import NaN
df = DataFrame({'A': [1,2,3,5]})
# interpolation with 'limit' argument gives error when there are
# no nan values in the series:
df.interpolate(limit=1)
# after adding a NaN value, no error
df.loc[1] = NaN
df.interpolate(limit=1)
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https://api.github.com/repos/pandas-dev/pandas/issues/7963 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7963/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7963/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7963/events | https://github.com/pandas-dev/pandas/pull/7963 | 39,815,874 | MDExOlB1bGxSZXF1ZXN0MTk1MjMyNTI= | 7,963 | Support is_dst indicators in tz_localize | {
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closes #7943.
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https://api.github.com/repos/pandas-dev/pandas/issues/7964 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7964/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7964/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7964/events | https://github.com/pandas-dev/pandas/issues/7964 | 39,816,928 | MDU6SXNzdWUzOTgxNjkyOA== | 7,964 | API/ENH: allow Period to be a first-class type via a PeriodBlockinternal type | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2014-08-08T12:21:08Z | 2018-07-06T14:20:18Z | 2018-07-06T14:20:18Z | CONTRIBUTOR | null | Instead of having a represenation of an array of `Period` objects (object dtype) in a Series/DataFrame. Allow an internal type of `PeriodBlock` to represent, similary to `DatetimeBlock`.
Here is a usecase. The following would be very simple if `to_period(...)` returned a `PeriodIndex`
```
In [59]: df = DataFrame({'da... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7965 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7965/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7965/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7965/events | https://github.com/pandas-dev/pandas/issues/7965 | 39,822,085 | MDU6SXNzdWUzOTgyMjA4NQ== | 7,965 | BUG: at with non-unique multi-index buggy | {
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"followers_url": "https://api.github.com/users/jr... | 13 | 2014-08-08T13:33:25Z | 2014-09-17T19:28:01Z | 2014-09-17T19:28:01Z | CONTRIBUTOR | null | I fear that I somehow created a DataFrame with a numeric MultiIndex that triggers (un?)intended behaviour in the `.loc` function. I failed to create a reproducible example with anything but a pickled dump of a DataFrame.
**Question** Is this a bug, or a user error? I'm confused...
### Steps to reproduce
1. Get `http:/... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7966 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7966/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7966/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7966/events | https://github.com/pandas-dev/pandas/pull/7966 | 39,842,818 | MDExOlB1bGxSZXF1ZXN0MTk1Mzg4OTA= | 7,966 | ENH/BUG: Period and PeriodIndex ops supports timedelta-like | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-08-08T16:58:44Z | 2014-08-10T15:20:26Z | 2014-08-10T14:53:57Z | MEMBER | null | Must be revisited after #7954 to remove `_skip_if_not_numpy17_friendly`
Closes #7740.
Allow `Period` and `PeriodIndex` `add` and `sub` to support `timedelta`-like. If period freq is `offsets.Tick`, offsets can be added if the result can have same freq. Otherwise, `ValueError` will be raised.
```
idx = pd.period_rang... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7968 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7968/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7968/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7968/events | https://github.com/pandas-dev/pandas/issues/7968 | 39,877,331 | MDU6SXNzdWUzOTg3NzMzMQ== | 7,968 | How to align title and value? | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7969 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7969/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7969/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7969/events | https://github.com/pandas-dev/pandas/issues/7969 | 39,878,094 | MDU6SXNzdWUzOTg3ODA5NA== | 7,969 | Can't access columns with spaces in them via df.eval | {
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If I have a column name with a space in it (e.g. "foo bar") then there doesn't appear to be a way to access that column via df.eval.
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https://api.github.com/repos/pandas-dev/pandas/issues/7970 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7970/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7970/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7970/events | https://github.com/pandas-dev/pandas/pull/7970 | 39,884,622 | MDExOlB1bGxSZXF1ZXN0MTk1NjM5Njk= | 7,970 | ENH Warn about panel.to_frame() discarding NaN GH7879 | {
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closes #7879
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- [x] use conda.binstar.org/cpcloud channel for versions/packages not in conda defaults
- [x] possibly bring back the ccache, not totally sure what this is doing
this doesn't remove maintenance, but it sure does simplify things, since conda recipes are very easy to create
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```
>>> pd.__version__
'0.14.1-172-gab64d58'
>>> x = np.arange(6, dtype=np.int64)
>>> df = pd.DataFrame({"a": x//2, "b": 2.0*x, "c": 3.0*x})
>>> df
a b c
0 0 0 0
1 0 2 3
2 1 4 6
3 1 6 9
4 2 8 12
5 2 10 15
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-08-10T01:13:29Z | 2014-08-10T03:47:49Z | 2014-08-10T03:47:08Z | CONTRIBUTOR | null | Allow `functools.partial` objects (and similar callables without `__name__` attributes) to be used as `groupby` functions, which also adds support along the tree (e.g. `resample`, which is specifically tested.)
Closes #7929.
This does not address the potential enhancements allowing automatic naming of duplicate-named... | {
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Additional perf improvements for Series.transform (when specifying cythonizable functions)
```
-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
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] | closed | false | null | [] | null | 13 | 2014-08-10T02:18:26Z | 2014-08-10T19:36:37Z | 2014-08-10T13:41:54Z | NONE | null | See this very strange behavior when taking the mean of a dataframe that has a series with uint16 datatype. Why does the mean of column y change after including column x?
```
Python 2.7.7 |Anaconda 2.0.1 (x86_64)| (default, Jun 2 2014, 12:48:16)
Type "copyright", "credits" or "license" for more information.
IPython 2... | {
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"followers_url": "https://api.github.com/users/jr... | 9 | 2014-08-10T07:10:58Z | 2014-09-10T00:02:26Z | 2014-09-10T00:02:26Z | CONTRIBUTOR | null | The interpretation of `min_periods` in the `ewm*()` functions seems rather odd to me. For example (in 0.14.1):
```
In [19]: x
Out[19]:
0 0
1 NaN
2 NaN
3 NaN
4 4
5 NaN
6 6
dtype: float64
In [20]: ewma(x, com=3., min_periods=2)
Out[20]:
0 NaN
1 NaN
2 0.000000
3 0.000000
4 2.... | {
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] | closed | false | null | [] | null | 3 | 2014-08-10T11:17:26Z | 2014-08-10T14:02:45Z | 2014-08-10T14:02:40Z | NONE | null | I just tried to pass `axis=1` on a shift call to a dataframe and it threw an error, I couldn't find an issue here and this is the first time I tried this function so not sure if this was something that used to work and then got broken.
I'm using python 64-bit 3.3.4, pandas 0.14.1 and numpy 1.8.1
```
In [57]:
df = pd... | {
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```
idx = pd.Index([1, 2, 3, 4, 1, 2])
idx.duplicated()
# Index([False, False, False, False, True, True], dtype='bool')
idx.drop_duplicates()
# Int64Index([1, 2, 3, 4], dtype='int64')
idx.duplicated(take_last=True)
# Index([True, True, False, False, False, False], dtype='bool')
idx.drop_duplicates(take_... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7980 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7980/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7980/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7980/events | https://github.com/pandas-dev/pandas/issues/7980 | 39,910,004 | MDU6SXNzdWUzOTkxMDAwNA== | 7,980 | How to deal with this Pandas warning? | {
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] | closed | false | null | [] | null | 4 | 2014-08-10T15:31:00Z | 2014-08-11T13:05:20Z | 2014-08-11T13:05:20Z | NONE | null | data1.loc['2012-1,'yb']=list(y2)
the 'yb' column is a new column,the pandas's warning is "SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame.Try using .loc[row_index,col_indexer] = value instead"
how to fix it?
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https://api.github.com/repos/pandas-dev/pandas/issues/7981 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7981/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7981/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7981/events | https://github.com/pandas-dev/pandas/issues/7981 | 39,910,073 | MDU6SXNzdWUzOTkxMDA3Mw== | 7,981 | .loc indexing with list of list or array fail | {
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``` python
arrays = [[3, 3, 5, 5, 7, 8, 9, 9, 9],
[1, 2, 2, 8, 8, 1, 2, 4, 5]]
tuples = list(zip(*arrays))
df = pd.DataFrame(np.random.randn(9, 4), index=arrays)
print(df)
```
```
0 1 2 3
3 1 -0.406271 -0.365945... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7982 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7982/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7982/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7982/events | https://github.com/pandas-dev/pandas/pull/7982 | 39,916,125 | MDExOlB1bGxSZXF1ZXN0MTk1NzY5NDM= | 7,982 | Fix DataFrame.to_latex() midrule positioning with MultiIndex columns | {
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levels, not columns levels:
```
>>> print pd.DataFrame({('x', 'y'): ['a']}).to_latex()
\begin{tabular}{ll}
\toprule
{} & x \\
\midrule
{} & y \\
0 & a \\
\bottomrule
\end{tabular}
```
The fix is simple: use the number of column levels inst... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7983 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7983/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7983/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7983/events | https://github.com/pandas-dev/pandas/issues/7983 | 39,935,693 | MDU6SXNzdWUzOTkzNTY5Mw== | 7,983 | read_csv could support chunking by contigous values?? | {
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Instead of specifiying chunksize, could give column or columns and it could split when these values change.
e.g.
Say I have a dataset, I know is sorted by date, and there are a lot of records for each date.
I could specify to read_csv to iterate on date, and it will read all ro... | {
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... | 11 | 2014-08-11T16:58:51Z | 2020-08-18T15:18:44Z | null | NONE | null | This could very well be something that just isn't clear to me from reading the docs, but I would like to have my index be unique when I dump the dataframe to SQLite table so that when I append more data I don't get duplicate rows. Here's what my resulting scheme looks like after using the to_sql function
sqlite> .sche... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7985 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7985/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7985/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7985/events | https://github.com/pandas-dev/pandas/issues/7985 | 39,983,426 | MDU6SXNzdWUzOTk4MzQyNg== | 7,985 | BUG: LWOM-SUN (LastWeekOfMonth) should directly work / doc examples of use | {
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... | 3 | 2014-08-11T17:59:37Z | 2020-06-28T18:07:32Z | 2020-06-28T18:07:32Z | CONTRIBUTOR | null | http://pandas.pydata.org/pandas-docs/stable/timeseries.html#dateoffset-objects
is their
Isn't 'LWOM-SUN' supposed to work for the offset?
it raises `ValueError`
```
In [5]: date_range('20130101',periods=5,freq=pd.offsets.LastWeekOfMonth(weekday=pd.offsets.WeekDay.SUN))
Out[5]:
<class 'pandas.tseries.index.Datetime... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/7986 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7986/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7986/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7986/events | https://github.com/pandas-dev/pandas/issues/7986 | 39,984,696 | MDU6SXNzdWUzOTk4NDY5Ng== | 7,986 | ENH: weekofmonth accessor for DatetimeIndex/PeriodIndex | {
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... | 5 | 2014-08-11T18:12:49Z | 2021-08-10T13:10:48Z | null | CONTRIBUTOR | null | http://stackoverflow.com/questions/25249033/week-of-a-month-pandas
should be easy extension
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https://api.github.com/repos/pandas-dev/pandas/issues/7987 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7987/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7987/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7987/events | https://github.com/pandas-dev/pandas/issues/7987 | 39,986,582 | MDU6SXNzdWUzOTk4NjU4Mg== | 7,987 | Annual Holiday with no offset or observance | {
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Example:
```
july_3rd = Holiday('July 4th Eve', month=7, day=3)
```
July 3rd is a nyse exchange early close that is observed only o... | {
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closes https://github.com/pydata/pandas/issues/7987
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"descript... | closed | false | null | [] | null | 10 | 2014-08-11T19:18:44Z | 2014-08-12T12:19:01Z | 2014-08-12T11:21:50Z | CONTRIBUTOR | null | Assume that you have a csv file separated by the sequence `\x01` (namely `chr(1)`):
`0S15SOfKdx\x013580\x015738.0\x011407348006000\n0S15SOfKdx\x0140\x015738.0\x011407351601000\n`
How can I load this in Pandas? I tried everything:
- `pd.read_csv(my_file, sep=chr(1))`
- `pd.read_csv(my_file, sep='\x01')`
with no luck.... | {
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- [x] `pep8` method/function calls where necessary in `io/pytables.py` (maybe tests too)
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``` python
@deprecate_kwarg(old_arg_name='infer_dst', new_arg_name='ambiguous',
mapping={True: 'infer', False: 'raise'})
def tz_localize(self, tz, ambiguous=None):
...
`... | {
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```
X = pd.DataFrame({'a': range(17), 'b': [1] * 17})
X.sort_index(by=['b'], inplace=True)
```
results in:
```
a b
0 0 1
14 14 1
13 13 1
12 12 1
11 11 1
10 10 1
9 9 1
15 15 1
8 8 1
6 6 1
5 5 1
4 4 ... | {
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cc @sinhrks
related #7907
```
C:\Users\Jeff Reback\Documents\GitHub\pandas> more versions.27-32.log
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.5.final.0
python-bits: 32
OS: Windows
OS-release: 7
machine: AMD64
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import datetime
s = pd.Series(pd.date_range('20130101',periods=3))
s-pd.Timestamp('20130101')
s-datetime.datetime(2013,1')
```
This fails as the datetime64 is not converted properly (because numpy datetime ops suck)
```
s-np.datetime64('20130101')
```
e.g. `np.datetime64('20130101').astype('M8[ns]')` is a bug, n... | {
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```
df = pd.DataFrame([[1,2,3],[4,5,6],[7,8,9]])
df.columns = pd.MultiIndex.from_tuples([(0,1),(1,1),(2,1)])
df.groupby(axis=1, level=[0,1]).first()
TypeError: can only sort by level with a hierarchical index
```
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https://api.github.com/repos/pandas-dev/pandas/issues/7998 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/7998/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/7998/comments | https://api.github.com/repos/pandas-dev/pandas/issues/7998/events | https://github.com/pandas-dev/pandas/pull/7998 | 40,055,341 | MDExOlB1bGxSZXF1ZXN0MTk2NjE2NzM= | 7,998 | ENH/CLN: add BoxPlot class inheriting MPLPlot | {
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"followers_url": "https://api.github.com/users/jr... | 10 | 2014-08-12T13:37:51Z | 2014-08-30T01:19:34Z | 2014-08-25T04:10:14Z | MEMBER | null | Like #7809, added `DataFrame.plot(kind='box')` to plot boxplot under the common plotting method.
**NOTE:** `DataFrame.boxplot` remains untouched (few lines are modified to share some definitions).
**NOTE:** This is based on #7736.
```
import pandas as pd
import numpy as np
pd.options.display.mpl_style = 'default'
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"followers_url": "https://api.github.com/users/jr... | 9 | 2014-08-12T13:39:24Z | 2014-08-14T17:13:13Z | 2014-08-14T17:13:13Z | CONTRIBUTOR | null | ```
df = pandas.DataFrame([['a'], ['b']], index=[1,2], columns=['x'])
df.loc[[3]] # does not raise KeyError as documented
```
"ALL of the labels for which you ask, must be in the index or a KeyError will be raised!"
http://pandas.pydata.org/pandas-docs/stable/indexing.html#selection-by-label
and
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https://api.github.com/repos/pandas-dev/pandas/issues/8000 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8000/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8000/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8000/events | https://github.com/pandas-dev/pandas/issues/8000 | 40,056,131 | MDU6SXNzdWU0MDA1NjEzMQ== | 8,000 | DataFrame.interpolate() extrapolates over trailing missing data | {
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... | 17 | 2014-08-12T13:46:04Z | 2019-07-13T16:49:49Z | 2019-07-13T16:49:49Z | CONTRIBUTOR | null | See also the discussion at [StackOverflow](http://stackoverflow.com/questions/25255496/dataframe-interpolate-extrapolates-over-trailing-missing-data).
Linear interpolation on a series with missing data at the end of the array will overwrite trailing missing values with the last non-missing value. In effect, the funct... | {
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