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https://api.github.com/repos/pandas-dev/pandas/issues/12904 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12904/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12904/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12904/events | https://github.com/pandas-dev/pandas/pull/12904 | 148,705,853 | MDExOlB1bGxSZXF1ZXN0NjY2NjkyNDI= | 12,904 | add support for specifying secondary indexes with to_sql | {
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The code also tries to avoid creating duplicate indexes when `keys` is specified in `SQLTable`.
(Once the PR for passing the `keys` this would be useful)
This PR introduces a new method in `SQLTable` called `_is_column_indexed` so that su... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12905 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12905/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12905/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12905/events | https://github.com/pandas-dev/pandas/issues/12905 | 148,711,108 | MDU6SXNzdWUxNDg3MTExMDg= | 12,905 | ValueError: EXT data is too large | {
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... | 22 | 2016-04-15T16:45:07Z | 2019-12-11T13:29:52Z | 2019-12-11T13:29:52Z | NONE | null | Hi guys,
I am happy to help you improve `msgpack.`
I tried to export my massive dataframe this morning using `msgpack`, and I got this error.
`ValueError: EXT data is too large`
What does that mean? Is there a size limit?
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https://api.github.com/repos/pandas-dev/pandas/issues/12906 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12906/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12906/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12906/events | https://github.com/pandas-dev/pandas/pull/12906 | 148,787,898 | MDExOlB1bGxSZXF1ZXN0NjY3MTYxMDE= | 12,906 | BUG: Subclassed DataFrame slicing may return normal Series | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
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read_html is missing the 'decimal' parameter. it'd be useful and more consistent to accept it too.
Example:
```
pd.read_html(html, thousands='.', decimal=',')
```
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https://api.github.com/repos/pandas-dev/pandas/issues/12908 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12908/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12908/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12908/events | https://github.com/pandas-dev/pandas/pull/12908 | 148,847,085 | MDExOlB1bGxSZXF1ZXN0NjY3MzY0NTU= | 12,908 | BUG: SparseSeries.shift may raise NameError or TypeError | {
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Fixed following bugs on current master. Also, moved `TestSparseArrayIndex` to `test_libsparse`
#### 1. shift
```
pd.SparseSeries([1, 2, 3], fill_value=0).shift(1)
# NameError: global name 'k... | {
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closes #11831
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https://api.github.com/repos/pandas-dev/pandas/issues/12910 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12910/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12910/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12910/events | https://github.com/pandas-dev/pandas/pull/12910 | 148,919,538 | MDExOlB1bGxSZXF1ZXN0NjY3NTg2NzI= | 12,910 | BUG: SparseArray numeric ops misc fixes | {
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Fixed following 3 issues occurred on the current master.
### 1. addition ignores rhs `fill_value`
```
pd.SparseArray([1., 1.]) + pd.SparseArray([1., 0.], fill_value=0.)
# [2.0, nan]
# Fill: ... | {
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>>> from pandas import read_csv
>>> from pandas.compat import StringIO
>>> data = """a b c~1 2 3~4 5 6~7 8 9"""
>>> df = read_csv(StringIO(data), lineterminator='~', delim_whitespace=True)
>>> df
Empty DataFrame
Columns: [a, b, c~1, 2, 3~4, 5, 6~7, 8, 9]
Index: []
```
expected:
``` python
>>> df
a b... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12913 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12913/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12913/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12913/events | https://github.com/pandas-dev/pandas/pull/12913 | 148,958,209 | MDExOlB1bGxSZXF1ZXN0NjY3NzAxMzk= | 12,913 | Add test to validate resampling GH9915 | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/12914 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12914/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12914/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12914/events | https://github.com/pandas-dev/pandas/pull/12914 | 148,965,773 | MDExOlB1bGxSZXF1ZXN0NjY3NzI0Mjk= | 12,914 | BUG: sniffing a csv raises with only a header | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12916 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12916/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12916/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12916/events | https://github.com/pandas-dev/pandas/pull/12916 | 148,992,598 | MDExOlB1bGxSZXF1ZXN0NjY3Nzk4ODI= | 12,916 | BUG: TypeError in index coercion | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/12917 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12917/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12917/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12917/events | https://github.com/pandas-dev/pandas/pull/12917 | 149,021,110 | MDExOlB1bGxSZXF1ZXN0NjY3OTEyMzI= | 12,917 | BUG: GH12902 fixed coercion of complex values to float when using gro… | {
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- [x] tests added / passed
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https://api.github.com/repos/pandas-dev/pandas/issues/12918 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12918/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12918/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12918/events | https://github.com/pandas-dev/pandas/issues/12918 | 149,027,682 | MDU6SXNzdWUxNDkwMjc2ODI= | 12,918 | DataFrame.ffill behaves different than DataFrame.interpolate(method='ffill') along axes | {
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"description": "np.nan, pd.NaT, pd.NA, d... | closed | false | null | [] | {
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```
from pandas.util.testing import assert_frame_equal
import numpy as np
import pandas as pd
n = np.nan
test_df = pd.DataFrame([[0, 2, n, n],
[1, n, 4, 6],
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https://api.github.com/repos/pandas-dev/pandas/issues/12919 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12919/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12919/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12919/events | https://github.com/pandas-dev/pandas/pull/12919 | 149,181,806 | MDExOlB1bGxSZXF1ZXN0NjY4NzExNjk= | 12,919 | Add pandas logo to repo | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12920 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12920/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12920/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12920/events | https://github.com/pandas-dev/pandas/issues/12920 | 149,301,402 | MDU6SXNzdWUxNDkzMDE0MDI= | 12,920 | AmbiguousTimeError with set_index() | {
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``` python
In [1]: import pandas as pd
In [2]: pd.__version__
Out[2]: '0.18.0'
In [3]: di = pd.date_range('2006-10-29 00:00:00', periods=3, freq='H', tz='US/Pacific')
In [4]: di
Out[4]:
DatetimeIndex(['2006-10-29 00:00:00-07:00', '2006-10-29 01:00:00-07:00',
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https://api.github.com/repos/pandas-dev/pandas/issues/12921 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12921/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12921/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12921/events | https://github.com/pandas-dev/pandas/pull/12921 | 149,318,462 | MDExOlB1bGxSZXF1ZXN0NjY5NDY5ODQ= | 12,921 | Correct out-of-bounds error with large indeces | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2016-04-19T01:17:34Z | 2016-04-20T00:05:32Z | 2016-04-20T00:04:18Z | CONTRIBUTOR | null | - [x] closes #12527
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/12922 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12922/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12922/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12922/events | https://github.com/pandas-dev/pandas/issues/12922 | 149,368,701 | MDU6SXNzdWUxNDkzNjg3MDE= | 12,922 | DataFrame.to_csv(quoting=csv.QUOTE_NONNUMERIC) quotes numeric values | {
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```
def test_pandas():
import tempfile
import csv
import pandas as pd
import numpy as np
df = pd.DataFrame.from_dict({'column': [1.0, 2.0]})
assert df['column'].dtype == np.dtype('float')
with tempfile.TemporaryFile() as f:
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https://api.github.com/repos/pandas-dev/pandas/issues/12923 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12923/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12923/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12923/events | https://github.com/pandas-dev/pandas/issues/12923 | 149,381,866 | MDU6SXNzdWUxNDkzODE4NjY= | 12,923 | Lots of unexpected behavior using resample after groupby | {
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# PANDAS 0.18 code :
```
df=pd.DataFrame(np.ones((150,4)),columns=['A','B','C','D'],
index=pd.date_range('2014-01-01',freq='D',periods=150))
df2=pd.DataFrame(np.zeros((150,4)),columns=['A','B','C','D'],
index=pd.date_range('2014-01-01',freq='D',periods=150))
df=pd... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12924 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12924/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12924/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12924/events | https://github.com/pandas-dev/pandas/pull/12924 | 149,449,367 | MDExOlB1bGxSZXF1ZXN0NjcwMTA5Nzk= | 12,924 | BUG: Fix argument order in call to super | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2016-04-19T12:40:36Z | 2016-05-19T14:53:00Z | 2016-05-19T14:52:39Z | CONTRIBUTOR | null | - [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
`super` should have arguments (type, object), not (object, type).
I've run `test_fast.sh` using Python 2.7 and it gives [2 failures](https://github.com/pydata/pandas/files/225866/testfail.txt) relating to language locales (I'm using en... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12925 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12925/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12925/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12925/events | https://github.com/pandas-dev/pandas/issues/12925 | 149,449,545 | MDU6SXNzdWUxNDk0NDk1NDU= | 12,925 | ENH: resample().interpolate() | {
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When downsampling on a Resampler object, you now have different `fillna` methods to fill the NaNs (or `asfreq` for a plain reindex like operation without NaN filling). I can possibly make sense to also have `interpolate` available to fill the miss... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12926 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12926/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12926/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12926/events | https://github.com/pandas-dev/pandas/issues/12926 | 149,452,813 | MDU6SXNzdWUxNDk0NTI4MTM= | 12,926 | BUG: resample().asfreq() looses end period with TimedeltaIndex | {
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... | closed | false | null | [] | {
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In [16]: df=pd.DataFrame(data=[1,3], index=[dt.timedelta(), dt.timedelta(minutes=3)])
In [17]: df
Out[17]:
0
00:00:00 1
00:03:00 3
In [18]: df.resample('1T').mean()
Out[18]:
0
00:00:00 1.0
00:01:00 NaN
00:02:00 NaN
00:03:00 3.0
In [19]: df.resample('1T').asfreq()
Out[19]:
0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12927 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12927/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12927/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12927/events | https://github.com/pandas-dev/pandas/issues/12927 | 149,544,054 | MDU6SXNzdWUxNDk1NDQwNTQ= | 12,927 | 2 tests failures on 32bit: test_searchsorted_sorter and test_sparse_max_row | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2016-04-19T18:29:20Z | 2016-04-30T23:17:03Z | 2016-04-30T23:15:55Z | CONTRIBUTOR | null | While building a fresh snapshot (6c692ae) for debians ran into the following consistent one on debian stable and testing (built fine on 64bit, but failed in 32bit userspace):
```
======================================================================
ERROR: test_searchsorted_sorter (pandas.tests.series.test_analytics.T... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12928 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12928/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12928/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12928/events | https://github.com/pandas-dev/pandas/pull/12928 | 149,554,321 | MDExOlB1bGxSZXF1ZXN0NjcwNzMxNzM= | 12,928 | BUG: .asfreq on resample on PeriodIndex/TimedeltaIndex are not | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12929 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12929/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12929/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12929/events | https://github.com/pandas-dev/pandas/pull/12929 | 149,578,640 | MDExOlB1bGxSZXF1ZXN0NjcwODYzOTE= | 12,929 | ENH: multiindex formatting | {
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"color": "0052c... | closed | false | null | [] | null | 13 | 2016-04-19T20:43:30Z | 2016-08-27T12:48:52Z | 2016-08-26T20:24:31Z | CONTRIBUTOR | null | closes #12423
```
In [1]: pd.options.display.width=80
In [2]: pd.options.display.max_seq_items=10
In [3]: pd.options.display.max_seq_items=100
In [4]: mi = pd.MultiIndex.from_tuples([('A', 1), ('A', 2),
('B', 3), ('B', 4)])
In [5]: mi
Out[5]:
MultiIndex(levels=[[u'A... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12930 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12930/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12930/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12930/events | https://github.com/pandas-dev/pandas/pull/12930 | 149,730,164 | MDExOlB1bGxSZXF1ZXN0NjcxNjM3MTM= | 12,930 | COMPAT: Add Pathlib, py.path support for read_hdf | {
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- [*] tests added / passed
- [*] passes `git diff upstream/master | flake8 --diff`
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Closes #11773
Travis-ci test JOB_NAME=27_slow_nnet_LOCALE consistently fails due to locale issue... zh_CN.GB18030??
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- [ ] tests added / passed
- [x ] passes `git diff upstream/master | flake8 --diff`
- [x ] whatsnew entry
added the following examples:
- Top N rows with offset
- Top N rows per group
- ROW_NUMBER() OVER(PARTITION BY day ORDER BY total_bill DESC)
- UPDATE
- DELETE
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https://api.github.com/repos/pandas-dev/pandas/issues/12932 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12932/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12932/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12932/events | https://github.com/pandas-dev/pandas/pull/12932 | 149,763,637 | MDExOlB1bGxSZXF1ZXN0NjcxODM4NzM= | 12,932 | DOC: More examples comparison with sql | {
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- [ ] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
added the following examples:
- Top N rows with offset
- Top N rows per group
- ROW_NUMBER() OVER(PARTITION BY day ORDER BY total_bill DESC)
- UPDATE
- DELETE
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https://api.github.com/repos/pandas-dev/pandas/issues/12933 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12933/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12933/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12933/events | https://github.com/pandas-dev/pandas/issues/12933 | 149,769,662 | MDU6SXNzdWUxNDk3Njk2NjI= | 12,933 | ENH: support decimal option in PythonParser | {
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In [5]: pd.read_csv(StringIO('1,2;2,3'),decimal=',',sep=';',header=None,engine='c')
Out[5]:
0 1
0 1.2 2.3
In [6]: pd.read_csv(StringIO('1,2;2,3'),decimal=',',sep=';',header=None,engine='python')
ValueError: The 'decimal' option is not supported with the 'python' engine
```
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https://api.github.com/repos/pandas-dev/pandas/issues/12934 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12934/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12934/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12934/events | https://github.com/pandas-dev/pandas/issues/12934 | 149,788,138 | MDU6SXNzdWUxNDk3ODgxMzg= | 12,934 | Add parameter defaults for swaplevel | {
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I think that `swaplevel()` deserves default values for its parameters, just like its friends like `stack()` and `unstack()` and `sortlevel()` that also all take an initial `level` argument. I suggest:
```
def swaplevel(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12935 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12935/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12935/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12935/events | https://github.com/pandas-dev/pandas/pull/12935 | 149,815,976 | MDExOlB1bGxSZXF1ZXN0NjcyMTU3ODE= | 12,935 | BUG, ENH: Add support for parsing duplicate columns | {
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Closes #7160.
Closes #9424.
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https://api.github.com/repos/pandas-dev/pandas/issues/12936 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12936/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12936/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12936/events | https://github.com/pandas-dev/pandas/pull/12936 | 149,885,683 | MDExOlB1bGxSZXF1ZXN0NjcyNTgwNTM= | 12,936 | BUG: provide SparseArray creation in a platform independent manner | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-04-20T21:04:04Z | 2016-04-20T21:35:21Z | 2016-04-20T21:33:57Z | CONTRIBUTOR | null | makes creation w/o specifying a dtype choose `np.int64/float64` regardless of the platform. This is similar to how Series works. This only is exposed on windows (as the default ndarray creation is np.int32) rather than np.int64
maybe _should_ use `pandas.core.series._sanitize_array` (but needs some tweeks I think).
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In [195]: df = pd.DataFrame(np.random.randn(14), index=np.arange(138.915, 140.0, 0.08),
columns=['noise'])
In [206]: df
Out[206]:
noise
138.915 -1.474675
138.995 0.768455
139.075 0.154067
139.155 1.201179
139.235 -0.554067
139.315 -0.713285
139.395 0.643849
139.4... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12938 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12938/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12938/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12938/events | https://github.com/pandas-dev/pandas/issues/12938 | 149,906,590 | MDU6SXNzdWUxNDk5MDY1OTA= | 12,938 | Timestamp timezones not preserved for certain indexers | {
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... | 6 | 2016-04-20T22:40:55Z | 2017-03-28T17:12:27Z | 2017-03-28T12:44:10Z | NONE | null | Hi, using different indexers on a dataframes with timezone-aware timestamps may return naive timestamps. (A brief search attempt didn't turn up any related issues.)
#### Code Sample, a copy-pastable example if possible
``` python
>>> import pandas as pd
>>> df = pd.Series([pd.tslib.Timestamp('2016-03-30 14:35:25.50608... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12939 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12939/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12939/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12939/events | https://github.com/pandas-dev/pandas/pull/12939 | 149,914,371 | MDExOlB1bGxSZXF1ZXN0NjcyNzUxOTg= | 12,939 | BUG, DOC: Allow custom line terminator with delim_whitespace=True | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12940 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12940/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12940/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12940/events | https://github.com/pandas-dev/pandas/issues/12940 | 149,974,044 | MDU6SXNzdWUxNDk5NzQwNDQ= | 12,940 | Feature Request: N-Dimensional DataFrames | {
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I made a random test dataset with arbitrary axis data trying to m... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12941 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12941/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12941/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12941/events | https://github.com/pandas-dev/pandas/issues/12941 | 150,013,452 | MDU6SXNzdWUxNTAwMTM0NTI= | 12,941 | Operations on NaT returning float instead of datetime64[ns] | {
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```
df = pd.DataFrame({'t1': pd.NaT, 't2': pd.NaT}, index=[1])
df.min(axis=1)
df.max(axis=1)
df.sum(axis=1)
```
#### Expected Output
All results above return a `float64` series instead of a `datetime64[ns]` series.
#### output of `pd.show_versions()`
```
INSTALLE... | {
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`
pd.isnull(np.array([np.nan, 1, 2, "s"]))
Out[120]: array([False, False, False, False], dtype=bool)
`
`
pd.isnull(pd.Series([np.nan, 1, 2, "s"]))
Out[116]:
0 True
1 False
2 False
3 False
`
#### Expected Output
#### output of `pd.show_versions()`
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https://api.github.com/repos/pandas-dev/pandas/issues/12944 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12944/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12944/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12944/events | https://github.com/pandas-dev/pandas/issues/12944 | 150,112,407 | MDU6SXNzdWUxNTAxMTI0MDc= | 12,944 | COMPAT: python-dateutil 2.5.3 | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-04-21T15:42:49Z | 2016-04-26T21:51:34Z | 2016-04-26T21:51:34Z | CONTRIBUTOR | null | so this parade of dateutil changes causes havoc in the testsuite as we adjust.
previous fixes: #12731, #12613
revert this: https://github.com/pydata/pandas/commit/161724470784da042f8fd5294cfb39acad6dc5c2
Let's see what the correct fixes are and maybe need to ban certain buggy versions.
```
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#### Code Sample
``` python
df = pd.DataFrame({'a': range(10), 'b': range(10,20)})
df.eval('x = a if a < 5 else b', inplace = True)
df
Traceback (most recent call last):
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- [x] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
Travis is not always detecting sudo use and is running forks using container-based infrastructure. `JOB_NAME=27_slow_nnet_LOCALE` fails when using containers because of setlocale. This PR adds `sudo: required` to make sure... | {
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df = pandas.DataFrame([[1,2,3,4,5]], columns=["A", "B", "C", "D", "E"])
# Suppose you want to set df.B to df.C when df.A ==1
# then the following both work:
df.loc[df.A== 1, "B"] = df.loc[df.A == 1, "C"]
df.ix[df.A == 1, "B"] = df.ix[df.A == 1, "C"]
# you can even mix and match them with ix on one side and l... | {
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... | 5 | 2016-04-21T17:02:17Z | 2020-01-21T01:06:10Z | 2020-01-21T01:06:10Z | NONE | null | In the following example, I was surprised that the `None` in the index somehow converts the value 1.0 to be stored as a `nan` in the values. Feel free to close if this is obviously user error :)
#### Code Sample, a copy-pastable example if possible
```
import pandas as pd
d = {(1, 1, None):-1.0, (1, 1, 1):-2.0, (1, ... | {
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... | closed | false | null | [] | null | 27 | 2016-04-21T17:34:39Z | 2017-08-01T22:55:52Z | 2017-08-01T22:55:52Z | CONTRIBUTOR | null | closes #10611
closes #8113
closes #10678
- [ ] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
This is a first go at trying to fix the above problems. I have created two before and after notebooks here: https://gist.github.com/nparley/08c81672b0e3d7d85b00694a671f57ad
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"de... | closed | false | null | [] | null | 2 | 2016-04-21T18:14:59Z | 2016-04-21T20:52:07Z | 2016-04-21T20:50:41Z | CONTRIBUTOR | null | `.apply(...)` on window-based groupbys receive an `ndarray` rather than a Pandas object.
Is this intentional? Is it a performance issue?
It means that functions that work on `Series` can't necessarily be used on groupbys, which limits abstraction.
```
In [7]: pd.Series(range(10)).expanding().apply(lambda x: x.pow(2)... | {
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so this fixes the compat with all dateutils in the test suite
add the `dayfirst` and `yearfirst` args to `Timestamp`. This make testing and compat a lot
easier. xref discussion in #7599 where we didn't implement it, though the feeling was sort of +0.
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... | 2 | 2016-04-22T00:49:51Z | 2019-10-21T20:03:53Z | null | CONTRIBUTOR | null | #### Code
``` python
store = pd.HDFStore('/tmp/tmp.h5')
dfq = pd.DataFrame(np.random.randn(10,4), columns=list('ABCD'), index=pd.date_range('20130101',periods=10))
store.append('dfq', dfq, format='table')
store.select('dfq', where="columns=['A']", chunksize=3) # or iterator=True
```
#### Error
```
------------------... | {
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] | closed | false | null | [] | null | 1 | 2016-04-22T06:08:43Z | 2016-04-22T10:26:41Z | 2016-04-22T10:26:41Z | NONE | null | #### Code Sample, a copy-pastable example if possible
df = pd.DataFrame({'a': [1, 2]}, index={'two', 'one'})
df
df = pd.DataFrame({'a': [1, 2]}, index={'one', 'two'})
df
got the same result :
a
two 1
one 2
#### Expected Output
```
a
```
two 1
one 2
```
a
```
one 1
two 2
#### output of `pd.show_ve... | {
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import numpy as np
import pandas as pd
df = pd.DataFrame(np.arange(0, 15).reshape(5, 3),
index=['a', 'b', 'c', 'd', 'e'],
columns=['c1', 'c2', 'c3'])
How to change all the places where c1==0 to c1=5 for example? (In this example onl... | {
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] | closed | false | null | [] | null | 2 | 2016-04-22T08:06:01Z | 2016-04-22T14:22:58Z | 2016-04-22T14:22:58Z | NONE | null | ```
#### Code Sample, a copy-pastable example if possible
df = pd.DataFrame({'Label': list('AABCCC'),
'Values': [1, 2, 3, 4, 6, 8]})
ranges = [6, 12, 18, 35, 50]
agebins = pd.cut(df['Values'],ranges)
agebins.describe()
```
Not knowing if there is an alternative approach than a covert to numpy array... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12957 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12957/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12957/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12957/events | https://github.com/pandas-dev/pandas/issues/12957 | 150,358,074 | MDU6SXNzdWUxNTAzNTgwNzQ= | 12,957 | ImportError on RangeIndex | {
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- running
1. `conda remove pandas`
2. `conda install pandas`
does not help
- after installing into fresh new virtual env, import works.
Probably it is bad state of the environment, could you ple... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12958 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12958/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12958/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12958/events | https://github.com/pandas-dev/pandas/pull/12958 | 150,374,889 | MDExOlB1bGxSZXF1ZXN0Njc1MTQzNzI= | 12,958 | ENH: Python parser now accepts delim_whitespace=True | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12959 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12959/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12959/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12959/events | https://github.com/pandas-dev/pandas/issues/12959 | 150,404,291 | MDU6SXNzdWUxNTA0MDQyOTE= | 12,959 | Support por python object CSV serialization in python 2 | {
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] | closed | false | null | [] | null | 3 | 2016-04-22T15:43:53Z | 2016-04-22T23:09:14Z | 2016-04-22T23:09:14Z | NONE | null | Let's say we have a file with 2 json encoded rows that we turn into a DataFrame:
```
{"first_name":"Manuel", "last_name":"Garrido Peña","experience":[{"name":"Peña Industries", "start":"May 2014"}]}
{"first_name":"Ana", "last_name":"Cañón", "experience":[{"name":"Cañón technologies","start":"April 2016"}]}
```
If one... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12960 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12960/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12960/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12960/events | https://github.com/pandas-dev/pandas/issues/12960 | 150,408,982 | MDU6SXNzdWUxNTA0MDg5ODI= | 12,960 | CLN/API: combine .swaplevel() into generic | {
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... | 1 | 2016-04-22T16:01:19Z | 2021-04-23T05:07:58Z | null | CONTRIBUTOR | null | xref #12943
seems we have lots of implementations of the same routine with slightly different API.
`pd.DataFrame.swaplevel(self, i, j, axis=0, inplace=False)` (this is before the default args).
I would remove the `copy` arg from `Series` and use something like this.
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https://api.github.com/repos/pandas-dev/pandas/issues/12961 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12961/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12961/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12961/events | https://github.com/pandas-dev/pandas/pull/12961 | 150,428,278 | MDExOlB1bGxSZXF1ZXN0Njc1NDYzODQ= | 12,961 | PERF: some more perf/clean in saslib.pyx | {
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cc @kshedden
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https://api.github.com/repos/pandas-dev/pandas/issues/12962 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12962/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12962/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12962/events | https://github.com/pandas-dev/pandas/issues/12962 | 150,462,715 | MDU6SXNzdWUxNTA0NjI3MTU= | 12,962 | __idiv__ creates a copy? | {
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```
import pandas as pd
mylist = [pd.Series([1,2,3])]
for m in mylist:
m /= 2.0
print '***printing m***'
print m
print
print '***mylist[0] - should be same as m, but isnt***'
print mylist[0]
```
#### observed output:
```
***printing m***
0 0.5
1 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12963 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12963/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12963/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12963/events | https://github.com/pandas-dev/pandas/issues/12963 | 150,471,288 | MDU6SXNzdWUxNTA0NzEyODg= | 12,963 | drop_duplicates slow for data frame of boolean columns | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-04-22T21:05:36Z | 2017-03-20T22:47:22Z | 2017-03-20T22:47:22Z | CONTRIBUTOR | null | In trying to find out the fast way to count unique rows in a data frame, I [stumbled upon an issue](https://gist.github.com/jreback/9758917f02d5c2140b82c9c368b02d3b) where dropping duplicates from a data frame of booleans is quite slow. @jreback asked me to open a ticket.
```
In [1]: import pandas as pd
In [2]: impor... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12964 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12964/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12964/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12964/events | https://github.com/pandas-dev/pandas/pull/12964 | 150,507,728 | MDExOlB1bGxSZXF1ZXN0Njc1OTI3MzI= | 12,964 | TST: Refactor test_parsers.py | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12965 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12965/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12965/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12965/events | https://github.com/pandas-dev/pandas/issues/12965 | 150,511,960 | MDU6SXNzdWUxNTA1MTE5NjA= | 12,965 | version 0.18.0 unstack bug | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12966 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12966/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12966/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12966/events | https://github.com/pandas-dev/pandas/pull/12966 | 150,557,120 | MDExOlB1bGxSZXF1ZXN0Njc2MDc0MTY= | 12,966 | BUG: Sparse concat may fill fill_value with NaN | {
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This also added tests related to #12174 and fixed `concat(axis=1)` issue.
```
# on current master
dense1 = pd.DataFrame({'A': [1, 2, 3, np.nan],
'B': [0, 0, 0, 0],
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See the references SO questions in the issue. but allows highly performant construction of datetime series from specified DataFrame columns with a minimal syntax
```
In [12]: pd.options.display.max_rows=10
In [13]: year = np.arange(2010, 2020)
In [14]: months = np.arange(1, 13)
In [15]: days = np.aran... | {
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pd.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.10.final.0
python-bits: 64
OS: Linux
OS-release: 4.2.0-34-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_IN
pandas: 0.18.0
nose: None
pip: 8.1.1
setuptools: 20.3.1
Cython: 0.23.5
numpy: 1.11.0
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## on current master
```
pd.SparseArray([1, 2, np.nan]) > 0
# [True, True, nan]
# Fill: nan
# IntIndex
# Indices: array([0, 1], dtype=int32)
# Expected
# [True, True, False]
```
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a = pd.Spar... | {
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```
from nsepy import get_history
from datetime import date
import pandas as pd
import requests
from io import BytesIO
import certifi
from scipy import stats
from dateutil.relativedelta import relativedelta
import numpy as np
#import matplotlib.pyplot as plt
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- new parameters are added to the end of the definition to remain backwards compatible.
- `index` defaults to `False` (not `True` as in `to_sql`) to remain backwards compatible.
- added tests
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- [X] tests added / passed in pandas/tseries/tests/test_resample.py: Base.test_resample_interpolate()
These tests simply check that df.resample(...).mean().interpolate() gives the same result than df.resample(...).interpolate()
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https://api.github.com/repos/pandas-dev/pandas/issues/12975 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12975/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12975/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12975/events | https://github.com/pandas-dev/pandas/pull/12975 | 150,696,178 | MDExOlB1bGxSZXF1ZXN0Njc2NDg2Mjk= | 12,975 | fix for read_html with bs4 failing on table with header and one column | {
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- [x] The test is added and passing (while failing before the fix).
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Fix as had been proposed in [PR 9194](https://github.com/pydata/pandas/pull/9194#issuecomment-209849563), b... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12976 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12976/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12976/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12976/events | https://github.com/pandas-dev/pandas/issues/12976 | 150,705,216 | MDU6SXNzdWUxNTA3MDUyMTY= | 12,976 | Make NatType more Timestamp-like and less datetime.datetime-like | {
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"closed_at": "2020-01-30T12:18:05Z",
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In [127]: isinstance(pd.Timestamp(np.nan), pd.tslib.Timestamp)
Out[127]: False
In [128]: isinstance(pd.Timestamp('2015'), pd.tslib.Timestamp)
Out[128]: True
In [129]: isinstance(pd.Timestamp(np.nan), datetime.datetime)
Out[129]: True
In [130]: isinstance(pd.Timestamp('2015'), datetime.datetime)
Out[130]: ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12977 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12977/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12977/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12977/events | https://github.com/pandas-dev/pandas/pull/12977 | 150,776,083 | MDExOlB1bGxSZXF1ZXN0Njc2NzY0ODc= | 12,977 | BUG: GH12824 fixed apply() returns different result depending on whet… | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2016-04-25T07:36:38Z | 2016-05-20T14:09:46Z | 2016-05-20T14:09:29Z | CONTRIBUTOR | null | - [x] closes #12824
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
In `_wrap_applied_output` for `NDFrameGroupBy`, if the first result of `apply` is `None`, find the first non-`None` result to determine behavior
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https://api.github.com/repos/pandas-dev/pandas/issues/12978 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12978/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12978/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12978/events | https://github.com/pandas-dev/pandas/issues/12978 | 150,784,122 | MDU6SXNzdWUxNTA3ODQxMjI= | 12,978 | Add some ExcelWriter Parameters | {
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... | closed | false | null | [] | null | 1 | 2016-04-25T08:17:38Z | 2016-04-25T12:52:20Z | 2016-04-25T12:52:09Z | NONE | null | The `ExcelWriter` class in line 550 of [pandas/pandas/io/excel.py](https://github.com/pydata/pandas/blob/6c692aee6d411d67997c4fadd023a1d4b7f91c12/pandas/io/excel.py#L550) takes a `datetime_format` parameter to format a datetime column.
Wouldn't it be useful to include a `font_size` parameter as well? Otherwise I don't... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12979 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12979/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12979/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12979/events | https://github.com/pandas-dev/pandas/issues/12979 | 150,830,862 | MDU6SXNzdWUxNTA4MzA4NjI= | 12,979 | plot.bar misalignment when width=1 | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-04-25T11:39:10Z | 2016-04-29T16:09:14Z | 2016-04-29T16:09:14Z | CONTRIBUTOR | null | Two minor issues with the width optional argument of plot.bar() in Pandas 0.18.0:
1) Using width=1 (integer) causes misalignment of the x-axis
``` python
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.random((6, 5)) * 10, index=list('abcdef'), columns=list('ABCDE'))
df.plot.bar(stacked=True, width... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12980 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12980/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12980/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12980/events | https://github.com/pandas-dev/pandas/issues/12980 | 150,836,524 | MDU6SXNzdWUxNTA4MzY1MjQ= | 12,980 | possible np.round bug | {
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... | closed | false | null | [] | null | 2 | 2016-04-25T12:07:46Z | 2016-04-25T12:43:23Z | 2016-04-25T12:42:56Z | NONE | null | #### Code Sample, a copy-pastable example if possible
Worked in prior versions...
```
import pandas as pd
raw_data = {'regiment': ['Nighthawks', 'Nighthawks', 'Nighthawks', 'Nighthawks', 'Dragoons', 'Dragoons', 'Dragoons', 'Dragoons', 'Scouts', 'Scouts', 'Scouts', 'Scouts'],
'company': ['infantry', 'infantr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12981 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12981/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12981/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12981/events | https://github.com/pandas-dev/pandas/issues/12981 | 150,880,761 | MDU6SXNzdWUxNTA4ODA3NjE= | 12,981 | Timezone lost on DataFrame assignments with realignment | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-04-25T14:31:11Z | 2016-04-26T13:22:55Z | 2016-04-26T13:22:55Z | CONTRIBUTOR | null | Starting from pandas 0.17, certain assignments to DataFrames cause offset-aware datetime columns to be converted to offset-naive columns. Specifically, it seems that if any data realignment is required when assigning the RHS to a a slice of the DataFrame, then timezone info is lost. Here's an example:
``` python
fr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12982 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12982/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12982/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12982/events | https://github.com/pandas-dev/pandas/pull/12982 | 150,912,969 | MDExOlB1bGxSZXF1ZXN0Njc3NDY0NDg= | 12,982 | BUG: Preserve timezone in unaligned assignments | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-04-25T16:11:22Z | 2016-04-26T13:23:00Z | 2016-04-26T13:22:55Z | CONTRIBUTOR | null | - [x] closes #12981
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
A fix for #12981. When doing a slice assign to a DataFrame where the
right-hand-side was timezone-aware datetime Series which required
realignment to perform the assignment, the timezone would ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12983 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12983/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12983/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12983/events | https://github.com/pandas-dev/pandas/issues/12983 | 150,923,484 | MDU6SXNzdWUxNTA5MjM0ODQ= | 12,983 | DataFrame align() on a subclassed DataFrame does not invoke _constructor() for the subclassed DataFrame | {
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# my_dataframe.py
import pandas as pd
class MySeries(pd.Series):
@property
def _constructor(self):
return MySeries
@property
def _constructor_expanddim(self):
return MyDataFrame
class MyDataFrame(pd.DataFrame):
def __init__(self, data=None, index=None, columns=None, dtype=No... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12984 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12984/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12984/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12984/events | https://github.com/pandas-dev/pandas/issues/12984 | 150,939,144 | MDU6SXNzdWUxNTA5MzkxNDQ= | 12,984 | ENH: classmethods for pd.period_range & pd.date_range | {
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... | closed | false | null | [] | null | 4 | 2016-04-25T17:59:41Z | 2016-04-25T22:20:36Z | 2016-04-25T22:20:36Z | CONTRIBUTOR | null | Floating an idea: `pd.PeriodIndex.from_range` & `pd.DatetimeIndex.from_range` as `classmethod`s to mirror `pd.period_range` & `pd.date_range` respectively. This encapsulates constructors on the class.
Also could have `pd.DatetimeIndex.from_dataframe` for https://github.com/pydata/pandas/pull/12967
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... | 12 | 2016-04-25T21:31:31Z | 2018-04-24T09:42:28Z | 2017-11-25T15:52:41Z | CONTRIBUTOR | null | This is something that works in pandas 0.16.2 but fails in pandas 0.18. If you append to an empty DataFrame, and the DataFrame you are appending contains a tz-aware datetime column, the append fails.
``` python
import pandas
df = pandas.DataFrame(columns=['dates'])
df_to_append = pandas.DataFrame({'dates': pandas.d... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12986 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12986/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12986/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12986/events | https://github.com/pandas-dev/pandas/issues/12986 | 151,000,905 | MDU6SXNzdWUxNTEwMDA5MDU= | 12,986 | BUG: Create Panel from DataFrame of tz-aware datetimes fails | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2016-04-25T22:51:14Z | 2018-07-06T20:21:10Z | 2017-07-10T21:08:21Z | CONTRIBUTOR | null | In pandas 0.18, if you create a Panel where at least one of the items consists of all tz-aware timestamps, then trying to access any elements of that item raises an error.
``` python
import pandas, numpy
data = numpy.array(list(pandas.date_range('2015', periods=24, tz='utc'))).reshape(2,3,4)
panel = pandas.Panel(data... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12987 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12987/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12987/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12987/events | https://github.com/pandas-dev/pandas/issues/12987 | 151,010,722 | MDU6SXNzdWUxNTEwMTA3MjI= | 12,987 | to_panel error when DataFrame contains tz-awared datetime column | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2016-04-26T00:07:10Z | 2018-07-06T20:21:10Z | 2017-07-11T09:55:27Z | CONTRIBUTOR | null | This code fails with an exception in pandas 0.18
``` python
import pandas
df = pandas.DataFrame({'dates': pandas.date_range('2015', periods=6, tz='utc'), 'nums': range(6)},
index=pandas.MultiIndex.from_product([[1, 2], ['a', 'b', 'c']]))
panel = df.to_panel() # this fails
```
The error is:
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```
d = {'Dates':[pd.Timestamp('2013-01-02'),
pd.Timestamp('2013-01-03'),
pd.Timestamp('2013-01-04')],
'Num1':[1,2,3],
'Num2':[-1,-2,-3]}
df = pd.DataFrame(data=d)
>>> df['Dates... | {
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"default"... | closed | false | null | [] | null | 4 | 2016-04-26T07:03:38Z | 2016-04-27T11:09:58Z | 2016-04-27T11:09:58Z | CONTRIBUTOR | null | Reusing encoding/decoding function for a specified encoding doubles speed.
```
import pandas as pd
s1 = pd.Series(["Dzień добрый"]*100000)
s2 = s1.str.encode('cp1251', 'ignore')
%timeit s1.str.encode('cp1251', 'ignore')
%timeit s2.str.decode('cp1251')
```
10 loops, best of 3: 157 ms per loop --> 80.9 ms per loop
10 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/12990 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12990/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12990/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12990/events | https://github.com/pandas-dev/pandas/issues/12990 | 151,103,459 | MDU6SXNzdWUxNTExMDM0NTk= | 12,990 | reset_index() not working properly when DataFrame columns are MultiIndex | {
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"de... | closed | false | null | [] | null | 2 | 2016-04-26T10:57:11Z | 2016-04-26T13:08:48Z | 2016-04-26T13:07:26Z | NONE | null | ## sample input file
[ml_col_idx_read.xlsx](https://github.com/pydata/pandas/files/236380/ml_col_idx_read.xlsx)
## Code Sample 1
```
ddf = pd.read_excel('ml_col_idx_read.xlsx', header=(0,1))
ddf.info()
ddf.reset_index()
```
## Output 1
```
<class 'pandas.core.frame.DataFrame'>
Int64Index: 4 entries, 1 to 4
Data colu... | {
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... | 10 | 2016-04-26T12:32:23Z | 2020-05-31T23:19:46Z | null | NONE | null | Creating a DataFrame with two columns given duplicate names, changing data via indexer changes both columns:
``` python
a = pd.DataFrame(index=['a', 'b', 'c'], columns=['d', 'e', 'd']).fillna(0)
a.iloc[:, 0]['a'] = 3
```
Gives:
d e d
a 3 0 3
b 0 0 0
c 0 0 0
Instead, it should only edit fi... | {
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closes #12941
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... | 14 | 2016-04-26T13:35:21Z | 2020-09-20T23:33:48Z | null | CONTRIBUTOR | null | #12803 added `.dt.weekday_name`. I think its appropriate to return this (and `.weekday`) as ordered categoricals
```
In [1]: s = Series(pd.date_range('20130101',periods=10))
In [2]: s.dt.weekday
Out[2]:
0 1
1 2
2 3
3 4
4 5
5 6
6 0
7 1
8 2
9 3
dtype: int64
In [3]: s.dt.weekday_name
Out[... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-04-26T14:46:47Z | 2016-04-26T15:21:57Z | 2016-04-26T15:21:57Z | CONTRIBUTOR | null | mostly in cython, but in tests as well. This is as per PEP. not to mention that it screws up syntax highliting.
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https://api.github.com/repos/pandas-dev/pandas/issues/12995 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/12995/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/12995/comments | https://api.github.com/repos/pandas-dev/pandas/issues/12995/events | https://github.com/pandas-dev/pandas/issues/12995 | 151,155,698 | MDU6SXNzdWUxNTExNTU2OTg= | 12,995 | PEP: fix up *.pyx | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-04-26T14:50:13Z | 2016-09-06T10:18:08Z | 2016-09-06T10:18:08Z | CONTRIBUTOR | null | we don't by default check the .pyx files, we should. So this issue will cover fixing & updating the `setup.cfg`, need to add: `filename: *.py, *.pyx`
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... | 11 | 2016-04-26T15:53:21Z | 2021-05-26T15:56:21Z | null | CONTRIBUTOR | null | #### Code Sample
```
In [99]: ts = Timestamp('2013-01-10 00:00:00-0500', tz='US/Eastern')
In [100]: pd.io.json.dumps(ts, iso_dates=True)
Out[100]: '"2013-01-10T05:00:00.000Z"'
```
#### Expected Output
```
In [100]: pd.io.json.dumps(ts, iso_dates=True)
Out[100]: '"2013-01-10T00:00:00.000-05:00"'
``... | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2016-04-26T16:30:27Z | 2016-04-26T16:35:28Z | 2016-04-26T16:34:20Z | NONE | null | I am not 100% sure if this is a bug, but it generates very unexpected behaviour!
Essentially, if columns are of type Categorical, selecting a single one using df[column_name] a DataFrame is returned, unlike for columns of other types, for which a Series would be returned.
#### Code Sample, a copy-pastable example if p... | {
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```
>>> from StringIO import StringIO
import pandas as pd
df_csv = """request_hour,request_date,size
03,201... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/13000 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/13000/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/13000/comments | https://api.github.com/repos/pandas-dev/pandas/issues/13000/events | https://github.com/pandas-dev/pandas/issues/13000 | 151,191,921 | MDU6SXNzdWUxNTExOTE5MjE= | 13,000 | printing multi-index dataframe with renamed index produces traceback | {
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#### Code Sample, a copy-pastable example if possible
```
>>> df = pd.DataFrame({'Vals':range(100)})
>>> df = pd.concat([df, ], k... | {
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`>>> import pandas as pd`
`>>> df = pd.DataFrame(np.zeros((4,5),dtype=int))`
`>>> sparse = df.to_sparse()`
`>>> sparse.loc[[1]] != 0`
#### Expected Output
`0 1 2 3 4`
`1 False False False False False`
### Observed Output
`TypeError: _combine_const() got an unexpected key... | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2016-04-26T22:58:14Z | 2016-05-12T15:32:04Z | 2016-05-05T00:34:29Z | CONTRIBUTOR | null | if we can finish up remaining issues, I'd like to release this next sunday/monday (may 1 or 2nd).
Planning on an 0.18.2, so if something is not in then we can address then.
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