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https://api.github.com/repos/pandas-dev/pandas/issues/9602 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9602/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9602/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9602/events | https://github.com/pandas-dev/pandas/issues/9602 | 60,100,538 | MDU6SXNzdWU2MDEwMDUzOA== | 9,602 | DEPR/DOC: rpy deprecation | {
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discussed extensivley in #7385
xref #7385, #9187 #7309, #8255
- [x] Update the docs with some example of... | {
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df = pandas.DataFrame({'a': [1, 0, 0, 0]})
df.groupby(pandas.cut(df.a, [0, 1, 2, 3, 4])).apply(lambda x: len(x))
Out[3]:
a
(0, 1] 1
(1, 2] 0
(2, 3] 0
(3, 4] 3
dtype: int64
```
final group length should be 0 not 3
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https://api.github.com/repos/pandas-dev/pandas/issues/9604 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9604/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9604/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9604/events | https://github.com/pandas-dev/pandas/issues/9604 | 60,143,242 | MDU6SXNzdWU2MDE0MzI0Mg== | 9,604 | BUG: Index not respecting nan_rep in HDF5 serialiazation | {
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... | 7 | 2015-03-06T18:58:45Z | 2015-10-08T22:34:27Z | null | MEMBER | null | ```
In [1]: import pandas
In [2]: institute = 'Nan-Kai Institute of Technology'
In [3]: words = institute.replace("-", ' ').lower().split()
In [4]: words_idces = pandas.Series(range(len(words)), index=words)
In [5]: len([words_idces.loc[w] for w in words])
Out[5]: 5
In [6]: words_idces.to_hdf('/tmp/test.hdf', 'pre... | {
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Added days_in_month property (compatibility alias daysinmonth) to Timestamp, DatetimeIndex, Period, PeriodIndex,
Series.dt.
Although not mentioned in the GH issue, I added the property to Period and PeriodIndex to be consistent with the others: dayofweek, dayofyear, etc.
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"followers_url": "https://api.github.com/users/j... | 2 | 2015-03-06T20:08:11Z | 2020-10-29T01:18:57Z | 2020-10-29T01:18:57Z | CONTRIBUTOR | null | we have a slightly odd naming convention for several index (and .dt) accessors
`dayofweek`
`dayofyear`
(and adding `daysinmonth` in #9605)
so these should prob be `day_of_week`
we should be able to maintain compat on these and just add the new ones.
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[changelog](https://github.com/PyMySQL/PyMySQL/blob/master/CHANGELOG)
and started breaking our builds (only 3.4 oddly)
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### hist_frame
- [ ] `xlabelsize`, `ylabelsize`: nothing specific to hist. Could be for all (non-pie) plot types
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-03-07T14:00:11Z | 2015-04-05T13:52:22Z | 2015-04-05T13:52:22Z | CONTRIBUTOR | null | The labels overlap
``` python
In [1]: df = pd.DataFrame(np.random.randn(30, 4), columns=list('abcd'))
In [2]: ax = df.a.plot(legend=True)
In [3]: df.b.plot(ax=ax, legend=True)
Out[3]: <matplotlib.axes._subplots.AxesSubplot at 0x10938f6a0>
```
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https://api.github.com/repos/pandas-dev/pandas/issues/9611 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9611/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9611/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9611/events | https://github.com/pandas-dev/pandas/pull/9611 | 60,214,415 | MDExOlB1bGxSZXF1ZXN0MzA3MDU1OTg= | 9,611 | API: deprecate setting of .ordered directly (GH9347, GH9190) | {
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closes #9190
closes #9148
so this is option 4).
Default is now `ordered=False` (independently of whether you specify categories or not)
The ordering is still what factorize does (seen order, if no categories are specified).
Add `set_ordered` to change the `ordered` flag, which by default returns a new ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9612 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9612/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9612/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9612/events | https://github.com/pandas-dev/pandas/pull/9612 | 60,230,578 | MDExOlB1bGxSZXF1ZXN0MzA3MTE0Nzk= | 9,612 | DEPR: deprecate pandas.rpy (GH9602) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9613 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9613/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9613/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9613/events | https://github.com/pandas-dev/pandas/issues/9613 | 60,250,616 | MDU6SXNzdWU2MDI1MDYxNg== | 9,613 | Please add YAML front matter block support for pandas.io.parsers.read_csv | {
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File example of the format
https://raw.githubusercontent.com/jrovegno/csvy/master/data.csvy
Regards
Javier
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https://api.github.com/repos/pandas-dev/pandas/issues/9614 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9614/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9614/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9614/events | https://github.com/pandas-dev/pandas/issues/9614 | 60,251,619 | MDU6SXNzdWU2MDI1MTYxOQ== | 9,614 | Type issue in empty groupby from DataFrame with categorical | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2015-03-08T10:54:34Z | 2019-11-13T01:57:19Z | 2019-11-13T01:57:19Z | CONTRIBUTOR | null | In a `DataFrame` without a categorical, the following comparisons work as expected:
``` python
df = pd.DataFrame({'id': [None] * 3, 'spam': [None] * 3})
df['spam'] == 'spam'
df.groupby('id').first()['spam'] == 'spam'
```
However, when a column is `Categorical`, a `groupby` on the all-null column behaves unexpected:
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https://api.github.com/repos/pandas-dev/pandas/issues/9615 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9615/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9615/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9615/events | https://github.com/pandas-dev/pandas/pull/9615 | 60,263,535 | MDExOlB1bGxSZXF1ZXN0MzA3MjE5NDc= | 9,615 | DEPR: deprecate pandas.sandbox.qtpandas | {
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xref #1986, #8788
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https://api.github.com/repos/pandas-dev/pandas/issues/9616 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9616/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9616/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9616/events | https://github.com/pandas-dev/pandas/issues/9616 | 60,288,635 | MDU6SXNzdWU2MDI4ODYzNQ== | 9,616 | getting IOError when creating DataFrame | {
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I am getting error when creating DataFrame and I have no idea on how to fix it
In [6]: import pandas.io.data as web
In [7]: import datetime
In [8]: start = datetime.datetime(2010, 1, 1)
In [9]: end = datetime.datetime(2013, 1, 27)
In [10]: f=web.DataReader("F", 'yahoo', start, end)
In [11]: f
Out[11]: <repr(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9617 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9617/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9617/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9617/events | https://github.com/pandas-dev/pandas/pull/9617 | 60,310,600 | MDExOlB1bGxSZXF1ZXN0MzA3NDIxNTY= | 9,617 | BUG/API: Accessors like .cat raise AttributeError when invalid | {
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attribute. In particular, it is necessary to ensure that tests like
`hasattr(s, 'cat')` work consistently on Python 2 and 3: on Python 2,
`hasattr(s, 'cat')` will return `False` even if a `TypeError` was raised, but
Python 3 more strictly requires... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9618 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9618/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9618/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9618/events | https://github.com/pandas-dev/pandas/issues/9618 | 60,326,756 | MDU6SXNzdWU2MDMyNjc1Ng== | 9,618 | msgpack unpack dataframe error: InvalidIndexError | {
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``` python
from pandas import read_msgpack
msg = df.to_msgpack()
read_msgpack(msg) #==> exception!
```
Full Traceback (most recent call last):
File "/srv/python/venv/local/lib/python2.7/site-packages/pandas/io/packers.py", line 163, in read_msgpack
return read(f... | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-03-09T15:20:03Z | 2015-08-18T12:45:06Z | 2015-03-09T18:42:16Z | CONTRIBUTOR | null | Let's try this again. The sphinx directive didn't seem to work. I just shrunk the static asset.
I'm not at my regular computer and I haven't been able to get the docs to build on this one, so I'm exactly sure how it will look in the page :)
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https://api.github.com/repos/pandas-dev/pandas/issues/9620 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9620/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9620/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9620/events | https://github.com/pandas-dev/pandas/issues/9620 | 60,378,910 | MDU6SXNzdWU2MDM3ODkxMA== | 9,620 | secondary_y not always working | {
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Essentially, the `secondary_y` argument of `plot()` doesn't do anything for boxplots and several other plot types. It will work for line plots however.
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https://api.github.com/repos/pandas-dev/pandas/issues/9621 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9621/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9621/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9621/events | https://github.com/pandas-dev/pandas/pull/9621 | 60,408,311 | MDExOlB1bGxSZXF1ZXN0MzA3OTg5NTU= | 9,621 | fix pymysql at 0.6.3 (GH9608) | {
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fix version to bypass failures for now
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https://api.github.com/repos/pandas-dev/pandas/issues/9622 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9622/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9622/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9622/events | https://github.com/pandas-dev/pandas/pull/9622 | 60,424,371 | MDExOlB1bGxSZXF1ZXN0MzA4MDgzMDE= | 9,622 | API: deprecate setting of .ordered directly (GH9347, GH9190) | {
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closes #9347
closes #9190
closes #9148
This implementes the alternate, and IMHO a nice compromise.
Groupby's will succeed whether ordered or not
ordering ops (sort/argsort/min/max) will still raise.
one though is that we could detect a non-reduction where the ordering matters (maybe we do this i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9623 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9623/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9623/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9623/events | https://github.com/pandas-dev/pandas/pull/9623 | 60,437,112 | MDExOlB1bGxSZXF1ZXN0MzA4MTU2MTg= | 9,623 | Fixes to resample over DST boundaries | {
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closes #8744
closes #8653
closes #9173
closes #9468
closes #8794
fixes all issues but one attached to #5172. There were several issues as mentioned by my comments in the master list. They are:
1. Offset classes were not working properly over DST boundaries. I added flags on the class to handle specia... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9624 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9624/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9624/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9624/events | https://github.com/pandas-dev/pandas/issues/9624 | 60,521,189 | MDU6SXNzdWU2MDUyMTE4OQ== | 9,624 | BUG: adding DatetimeIndex with series of timedeltas results in strange series | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2015-03-10T15:48:56Z | 2015-03-11T01:47:12Z | 2015-03-11T01:47:12Z | MEMBER | null | ```
In [21]: dtidx = pd.date_range('2012-01-01', periods=2)
In [22]: dtidx
Out[22]:
<class 'pandas.tseries.index.DatetimeIndex'>
[2012-01-01, 2012-01-02]
Length: 2, Freq: D, Timezone: None
In [23]: dtidx + pd.Series([pd.Timedelta('10 days'), pd.Timedelta('20 days')])
Out[23]:
2012-01-01 00:00:00 NaT
2012-01-02 00:0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9625 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9625/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9625/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9625/events | https://github.com/pandas-dev/pandas/issues/9625 | 60,544,193 | MDU6SXNzdWU2MDU0NDE5Mw== | 9,625 | Add an option to to_html so that index names do not take a row itself. | {
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a = pd.DataFrame({'x': [1,2,3], 'y': [2,3,4]})
a.index.names = ['a']
a.to_html()
```
it looks like
```
x y
a
0 1 2
1 2 3
2 3 4
```
Can we add an option in `to_html` so that we can achieve the following easily?
For the moment I have to drop the index, and bold the first column via formatter which is not ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9626 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9626/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9626/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9626/events | https://github.com/pandas-dev/pandas/pull/9626 | 60,549,163 | MDExOlB1bGxSZXF1ZXN0MzA4ODA0NzI= | 9,626 | improve error message when importing pandas from source directory | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-03-10T18:46:43Z | 2015-05-05T00:09:03Z | 2015-05-04T22:41:49Z | CONTRIBUTOR | null | Currently if one imports from the source directory without building the C extension the error message is not very helpful:
`ImportError: cannot import name 'hashtable'`
I see a few previous PRs (https://github.com/pydata/pandas/pull/3827, https://github.com/pydata/pandas/pull/3821) that tried to address this but someh... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9627 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9627/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9627/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9627/events | https://github.com/pandas-dev/pandas/issues/9627 | 60,582,840 | MDU6SXNzdWU2MDU4Mjg0MA== | 9,627 | API: remove .str/.cat/.dt tab-completion from types that don't support | {
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btw, if someone wants to do a followup at some point to remove the .str/.cat/.dt from the **dir** on types they don't apply would be gr8. (not that hard, but requires a bit of changing), prob have to make _local_dir a bit more flexible (to add and delete)
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https://api.github.com/repos/pandas-dev/pandas/issues/9628 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9628/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9628/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9628/events | https://github.com/pandas-dev/pandas/pull/9628 | 60,585,360 | MDExOlB1bGxSZXF1ZXN0MzA5MDIyNzM= | 9,628 | Fix table name on comparison with SQL | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9629 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9629/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9629/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9629/events | https://github.com/pandas-dev/pandas/pull/9629 | 60,591,276 | MDExOlB1bGxSZXF1ZXN0MzA5MDU4MzY= | 9,629 | TST/DOC: Fix tests and docs for .cat raising AttributeError if invalid | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-03-11T00:21:03Z | 2015-03-11T01:35:35Z | 2015-03-11T01:35:33Z | MEMBER | null | Follow-up on #9617
Fixes #8814 -- is it fair to say that `hasattr(s, 'cat')` is probably
the best solution we're going to come up with for checking for categorical
data?
CC @jreback @jorisvandenbossche @JanSchulz
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https://api.github.com/repos/pandas-dev/pandas/issues/9630 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9630/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9630/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9630/events | https://github.com/pandas-dev/pandas/pull/9630 | 60,598,508 | MDExOlB1bGxSZXF1ZXN0MzA5MDk3NTI= | 9,630 | DEPR: DatetimeIndex/PeriodsIndex +/- ops (GH9094) | {
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closes #9095
deprecate `DatetimeIndex/PeriodIndex` `+/-` ops which are set ops. In a future version `-` will produce a `TimeDeltaIndex` and `+` a `TypeError`
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https://api.github.com/repos/pandas-dev/pandas/issues/9631 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9631/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9631/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9631/events | https://github.com/pandas-dev/pandas/issues/9631 | 60,599,438 | MDU6SXNzdWU2MDU5OTQzOA== | 9,631 | ERR: clarify exceptions for invalid datetimelike ops | {
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IIRC most of these are `TypeErrors` (see `tseries/tests_base.py`, section on addition/subtraction ops)
but I guess *some* are`NotImplementedError``
```
In [3]: pd.date_range('20130101',periods=5)+Timestamp('20140101')
NotImplementedError:
```
```
In [4]: pd.date_range('20130101',periods=5)+Timestamp('201... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9632 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9632/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9632/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9632/events | https://github.com/pandas-dev/pandas/pull/9632 | 60,640,200 | MDExOlB1bGxSZXF1ZXN0MzA5MzE5MjQ= | 9,632 | Return the right class, when subclassing a DataFrame with multi-level index | {
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"followers_url": "https://api.github.com/users/jr... | 20 | 2015-03-11T10:48:17Z | 2015-05-04T18:58:56Z | 2015-05-04T18:58:49Z | CONTRIBUTOR | null | Subclassing pandas.DataFrame had some issues, when a multi-level index was used. This PR should fix that.
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https://api.github.com/repos/pandas-dev/pandas/issues/9633 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9633/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9633/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9633/events | https://github.com/pandas-dev/pandas/issues/9633 | 60,717,495 | MDU6SXNzdWU2MDcxNzQ5NQ== | 9,633 | fillna not accepting a None value | {
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``` python
df = pandas.DataFrame([np.nan, 42])
df.fillna(value=None)
```
returns a `ValueError` exception (_ValueError: must specify a fill method or value_). Any other value is of course accepted.
I'm not sure if it's a good idea to ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9635 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9635/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9635/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9635/events | https://github.com/pandas-dev/pandas/issues/9635 | 60,799,613 | MDU6SXNzdWU2MDc5OTYxMw== | 9,635 | Hdf5/PyTables support for TimedeltaIndex | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-03-12T10:40:11Z | 2015-04-04T18:40:47Z | 2015-04-04T18:40:47Z | CONTRIBUTOR | null | When stored in HDFStore, TimedeltaIndex are converted into Int64Index.
``` python
df = pd.DataFrame(np.random.normal(size=(10,5)))
df.index = pd.timedelta_range(start='0s',periods=10,freq='1s')
store = pd.HDFStore('test.h5')
store['df'] = df
df = store['df']
print df.index
```
```
Int64Index([0, 1000000000, 200000000... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9637 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9637/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9637/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9637/events | https://github.com/pandas-dev/pandas/pull/9637 | 60,842,648 | MDExOlB1bGxSZXF1ZXN0MzEwNTAxODY= | 9,637 | fixed header=list (to create a MultiIndex) for read_excel | {
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... | 3 | 2015-03-12T16:01:26Z | 2015-05-12T12:19:49Z | 2015-05-12T12:19:49Z | CONTRIBUTOR | null | closes #4679
This is a very simple fix to allow passing a list go the header argument of read_excel so that it creates a MultiIndex for columns. Given what is said in issue #4679, I am not really sure it is supposed to work, but with this fix, it works for my files. One thing discussed in issue #4679, which I did not... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9639 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9639/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9639/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9639/events | https://github.com/pandas-dev/pandas/pull/9639 | 60,950,931 | MDExOlB1bGxSZXF1ZXN0MzEwOTI1Mzg= | 9,639 | Rearrange into logical sections and add relevant links | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9640 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9640/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9640/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9640/events | https://github.com/pandas-dev/pandas/pull/9640 | 60,962,526 | MDExOlB1bGxSZXF1ZXN0MzEwOTUzNjg= | 9,640 | support constructing Panel or Panel4D with scalar data, fixes #8285 | {
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... | closed | false | null | [] | null | 4 | 2015-03-13T10:17:34Z | 2015-03-13T13:44:09Z | 2015-03-13T13:21:07Z | MEMBER | null | Is something like [this](http://stackoverflow.com/a/29014295/2858145) is worth including in pandas (although it will not work i.e. in Windows)?
If yes, I will put together a PR (also supporting Python2).
(I could also implement a platform independent alternative... but locking would not be atomic, so race conditions ... | {
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Is this correct? (assuming so I just added what the warning message... | {
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I added an automatic 'contents' in the beginning, so this gives all headers automatically, and in this way restricted the list in the beginning to just the highlights (then it can be copied exactly like this to the release notes in release.rst
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> ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support sep=None with delim_whitespace=False; you can avoid this warning by specifying engine='python'
Is this warning correct that it is not implemented for the... | {
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Right now it's on the same level as Series, DataFrame, and Panel. Should be indented one more.
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reduce memeory usage necessary for using `to_hdf`
- was copying always in astyping
- was ravelling then reshaping
- was constantly allocating a new chunked buffer, now re-uses the same buffer
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I did this through the GH online editor. Let's see if it works.
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``` python
import numpy as np
import pandas as pd
def multiindex_version_1(data):
n, m = data.shape
tuples = [('a', _m) for _m in xrange(m-1)... | {
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- http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html
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``` python
N = 5
columns = pd.MultiIndex.from_tuples([('a', 0), ('a', 1), ('b', 0), ('b', 1)])
df1 = pd.DataFrame(np.random.rand(N, 4), columns=columns)
df2 = pd.DataFrame(np.random.rand(N), columns=['c'])
df1_copy = df1.copy()
df2_copy = df2.copy()
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was tricky to distinguish this case from others, but I think this is a reasonably robust soln.
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I had some trouble getting the HDF5 import of DataFrame objects to work on the R side (pandas is fine). I've added an example to the documentation with a simple load function in R which assembles an R data.frame from the corresponding *_items and *_values nodes in the HDF5 file.
NOTE: Any improvements to... | {
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Small change to fix issue 9635. I'm a beginner contributor, feel free to crush it out.
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The `tslib.maybe_get_tz... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9664 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9664/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9664/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9664/events | https://github.com/pandas-dev/pandas/issues/9664 | 62,178,185 | MDU6SXNzdWU2MjE3ODE4NQ== | 9,664 | BUG: groupby datetime object and transform gives KeyError | {
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```
x = pd.DataFrame() #Start with an empty data frame
x['name'] = ['Bob','Alice','Bob']
x['date'] = ['2015-02-01','2015-02-02','2015-02-03']
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https://api.github.com/repos/pandas-dev/pandas/issues/9666 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9666/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9666/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9666/events | https://github.com/pandas-dev/pandas/pull/9666 | 62,209,739 | MDExOlB1bGxSZXF1ZXN0MzEyODQ1MTg= | 9,666 | New function to sample from frames (Issue #2419 ) | {
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Creates a function `.sample()` in generic.py to sample from pandas objects. Returns either a fixed number of rows or a share. Also includes a number of tests in `test_sample()` -- I am open to added suggestions.
Input from users with panel experience appreciated!
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https://api.github.com/repos/pandas-dev/pandas/issues/9667 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9667/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9667/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9667/events | https://github.com/pandas-dev/pandas/pull/9667 | 62,270,052 | MDExOlB1bGxSZXF1ZXN0MzEzMDM5NjU= | 9,667 | ENH: add StringMethods (.str accessor) to Index, fixes #9068 | {
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``` python
In [1]: import pandas as pd
In [2]: df = pd.DataFrame({'a': pd.Categorical(['a', 'b', 'a'])},
... index=pd.Categorical(['a', 'b', 'a']))
In [3]: df.dtypes
Out[3]:
a category
dtype: object
In [4]: df.index... | {
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"... | closed | false | null | [] | null | 5 | 2015-03-17T04:46:50Z | 2015-03-17T23:55:36Z | 2015-03-17T23:19:49Z | NONE | null | I have a large CSV file that contains a single column of integers. When loading the CSV file with read_csv, nearly 2/3rds of the approximately 1.5 million values are loaded as ints while the remaining values are loaded as strings. I see no obvious problem with the file that would lead to this behavior.
The file I used ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9670 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9670/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9670/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9670/events | https://github.com/pandas-dev/pandas/issues/9670 | 62,345,524 | MDU6SXNzdWU2MjM0NTUyNA== | 9,670 | Numerically unstable mean calculation for Timedeltas. | {
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```
In [11]: dAllTags.describe()
Out [11]:
finalPeriod
count 74501
mean -1 days +02:40:08.792662
std 500 days 06:32:37.640848
min 2 days 00:51:49.730000
25% ... | {
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```
from pandas import Dat... | {
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Hop, revival of PR9662, after some bad git moves.
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https://api.github.com/repos/pandas-dev/pandas/issues/9673 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9673/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9673/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9673/events | https://github.com/pandas-dev/pandas/pull/9673 | 62,433,170 | MDExOlB1bGxSZXF1ZXN0MzEzNDcwMjQ= | 9,673 | Fix for issue #9671 | {
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`self.style` can be a list of strings or a string. If it is a string, we make a list containing that string, so that we only have to deal with a list of strings. We check every element in that list and raise an error if it has a color symbol.
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https://api.github.com/repos/pandas-dev/pandas/issues/9674 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9674/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9674/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9674/events | https://github.com/pandas-dev/pandas/pull/9674 | 62,731,660 | MDExOlB1bGxSZXF1ZXN0MzE0NDQ1Mjk= | 9,674 | DataFrame.plot error when both 'color' and 'style' arguments are passed (GH9671) | {
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`self.style` can be a list of strings or a string. If it is a string, we make a list containing that string, so that we only have to deal with a list of strings. We check every element in that list and raise an error if it has a color symbol.
The test makes sure that calling `plot()` and passing both `col... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9675 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9675/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9675/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9675/events | https://github.com/pandas-dev/pandas/issues/9675 | 62,745,414 | MDU6SXNzdWU2Mjc0NTQxNA== | 9,675 | global name 'iNaT' is not defined | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-03-18T17:16:56Z | 2015-03-25T23:03:52Z | 2015-03-25T23:03:52Z | NONE | null | Trying to perform this operation on a groupby object called clusters:
`clusters.agg({'diffs': lambda x: x.quantile(.5)})`
where diffs is a column of Timedelta objects.
Getting the error:
```
/usr/local/lib/python2.7/dist-packages/pandas/core/groupby.pyc in aggregate(self, func_or_funcs, *args, **kwargs)
2305 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9676 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9676/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9676/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9676/events | https://github.com/pandas-dev/pandas/issues/9676 | 62,774,931 | MDU6SXNzdWU2Mjc3NDkzMQ== | 9,676 | BUG: entries missing when reading from pytables hdf store using "where" statement | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9677 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9677/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9677/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9677/events | https://github.com/pandas-dev/pandas/issues/9677 | 62,815,148 | MDU6SXNzdWU2MjgxNTE0OA== | 9,677 | need for 'save_dataframe' | {
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] | closed | false | null | [] | null | 15 | 2015-03-18T22:07:56Z | 2015-03-19T02:52:20Z | 2015-03-18T23:11:25Z | NONE | null | Saving and Retrieving are basic to data operations. The defacto save / retrieve in
pandas, at least from Wes's book, seems to be to_csv and .read_csv These are great,
but what is saved is not what is returned:
In [49] frame
Out[49]:
fun people state
0 pinball Joe OH
1 food Mary ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9678 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9678/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9678/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9678/events | https://github.com/pandas-dev/pandas/issues/9678 | 62,817,456 | MDU6SXNzdWU2MjgxNzQ1Ng== | 9,678 | BUG/SQL: to_sql sqlalchemy.exc.DataError for datetime64[ns] column in Redshift | {
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```
df.info()
[output]
<class 'pandas.core.frame.DataFrame'>
Int64Index: 11 entries, 0 to 1684
Data col... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9679 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9679/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9679/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9679/events | https://github.com/pandas-dev/pandas/issues/9679 | 62,817,608 | MDU6SXNzdWU2MjgxNzYwOA== | 9,679 | new column based on a condition of the others columns (like ifelse in R) | {
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] | closed | false | null | [] | null | 1 | 2015-03-18T22:24:40Z | 2015-03-18T23:07:21Z | 2015-03-18T23:05:56Z | NONE | null | Hi everyone,
How can I do a ifelse statement R-like in a pandas dataframe.
I want to compute a new column via a calculation from the others columns.
It's been a while, so I ask to the community. I used to do a simple ifelse(cond, true, false) with R
on a dataframe.I look for the same result.
here is my code:
import... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9680 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9680/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9680/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9680/events | https://github.com/pandas-dev/pandas/issues/9680 | 62,944,418 | MDU6SXNzdWU2Mjk0NDQxOA== | 9,680 | TimedeltaIndexed Series raises ValueError instead of AttributeError | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-03-19T10:17:38Z | 2015-04-28T00:54:11Z | 2015-04-28T00:54:11Z | CONTRIBUTOR | null | ``` python
ts = pd.Series(np.random.normal(size=10),index=pd.timedelta_range(start=0,periods=10,freq='1s'))
ts.foo
```
raises
```
ValueError: cannot create timedelta string converter for [foo]
```
Shouldn't it raise
```
AttributeError: 'Series' object has no attribute 'foo'
```
?
```
pd.show_versions()
INSTALLED... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9681 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9681/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9681/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9681/events | https://github.com/pandas-dev/pandas/pull/9681 | 62,964,608 | MDExOlB1bGxSZXF1ZXN0MzE1MTYyMjk= | 9,681 | BUG: workaround PyTables 319, but not setting expected rows (GH8265, GH9676) | {
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closes #9676
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https://api.github.com/repos/pandas-dev/pandas/issues/9683 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9683/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9683/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9683/events | https://github.com/pandas-dev/pandas/pull/9683 | 63,011,434 | MDExOlB1bGxSZXF1ZXN0MzE1MzIyODc= | 9,683 | Bug: Access unknown attribute of timedeltaindexed series used to raise ValueError | {
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And now it raises AttributeError.
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https://api.github.com/repos/pandas-dev/pandas/issues/9684 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9684/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9684/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9684/events | https://github.com/pandas-dev/pandas/issues/9684 | 63,088,750 | MDU6SXNzdWU2MzA4ODc1MA== | 9,684 | BUG: groupby apply throws error if custom func doesn't return non-None value. | {
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Minimal code to replicate:
```
test_df = pd.DataFrame({'groups': [0,0,1,1], 'random_vars': [8,7,4,5]})... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/9685 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9685/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9685/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9685/events | https://github.com/pandas-dev/pandas/pull/9685 | 63,103,977 | MDExOlB1bGxSZXF1ZXN0MzE1NzE3ODY= | 9,685 | Fixes groupby.apply() error when no returns #9684 | {
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Returns empty object even if all entries are missing.
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These are changes to get vbench running under python3. There are quite a few tests that need modification, but with these changes the code will parse and the suite can run (along with [vbench#36](https://github.com/pydata/vbench/pull/36)).
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https://api.github.com/repos/pandas-dev/pandas/issues/9687 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9687/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9687/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9687/events | https://github.com/pandas-dev/pandas/issues/9687 | 63,205,161 | MDU6SXNzdWU2MzIwNTE2MQ== | 9,687 | DataFrame.interpolate(axis=1, method="time", inplace=True) | {
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```
import pandas as pd
import numpy as np
periods=5
idx = pd.date_range(start="2014-01-01", periods=periods)
data = np.random.rand(periods, periods)
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-03-20T12:53:05Z | 2015-04-10T10:54:14Z | 2015-03-26T09:49:50Z | CONTRIBUTOR | null | This format is used, e.g., in datasets from the ECB.
Code example:
In [25]: PD.period_range(start = '2012Q1', periods = 4, freq = 'Q')
Out[25]:
<class 'pandas.tseries.period.PeriodIndex'>
[2012Q1, ..., 2012Q4]
Length: 4, Freq: Q-DEC
## In [26]: PD.period_range(start = '2012-Q1', periods = 4, freq = 'Q')
ValueError ... | {
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@jreback you suggested to remove the highlights alltogether now we have the automatic table of contents, but I think it is not fully equivalent (eg the deprecations I added now are not directly visible in the table of cont... | {
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``` python
df = DataFrame(data={
'test': ['<a href="http://reallylongurlthateasilyislongerthan50characters.htm">short linkname</a>'],
})
```
…as the `<td><a href="http://reallylongurlthateasilyislongertha...</td>` will be broken HTML, and the `a` ... | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2015-03-20T15:16:08Z | 2015-03-25T10:55:44Z | 2015-03-25T10:55:23Z | CONTRIBUTOR | null | When converting to datetime64, pandas does:
``` python
if col_type == 'datetime64':
try:
tz = col.tzinfo
return DateTime(timezone=True)
except:
return DateTime
if col_type == 'timedelta64':
```
2 problems
1. The exception catch i... | {
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"followers_url": "https://api.github.com/users/jorisva... | 11 | 2015-03-20T20:46:38Z | 2016-11-26T11:26:53Z | 2016-11-26T11:26:53Z | NONE | null | I have been successfully parsing a csv file in 0.14.1, just upgraded yesterday and now the following code breaks:
```
df = pd.io.parsers.read_csv(fname,
skiprows=range(1, 9))
```
here is the file:
https://www.dropbox.com/s/grhi6e9vihjf92t/testtown2.csv?dl=0
Versions:
```
INSTALLED VE... | {
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Tested:
- [x] windows
- [x] macosx
- [x] linux
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-03-21T01:39:57Z | 2015-03-25T23:03:40Z | 2015-03-25T23:03:40Z | NONE | null | Changes to be committed:
modified: pandas/core/series.py
modified: pandas/tests/test_series.py
Fixes global reference to iNaT (should be tslib.iNaT) in series._maybe_box.
Adds test `test_datetime_timedelta_quantiles` to check for proper return value
in test_series.py.
Issue #9675
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There's still some weird issues with dtypes. In my test case there's a DataFrame with dtypes [int, float, int]. After the interpolation they should be downcasts to [int, int, int] when the missing value is filled. But along the way a transpose changes things to `[flo... | {
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```
import numpy as np
df = pd.DataFrame({'col1':[1,1,2,2], 'col2':[1,2,3,np.nan]})
# Works fine
df.groupby('col1').transform(sum)['col2']
# Throws error
df.groupby('col1')['col2'].transform(sum)
```
Error:
Traceback (most recent call last):
```
Fi... | {
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"... | closed | false | null | [] | null | 1 | 2015-03-22T15:46:59Z | 2015-09-10T14:36:02Z | 2015-03-23T01:27:08Z | CONTRIBUTOR | null | There is a xport file reader on Github here:
https://github.com/jcushman/xport
Would it be reasonable (with the author's permission) to port this into Pandas?
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-03-22T17:05:19Z | 2015-03-23T10:55:42Z | 2015-03-23T10:55:36Z | CONTRIBUTOR | null | Switch count() to size(), so that when we build the expanded values we're using the size of the groups and not simply the number of non-null values they have. Fixes #9697.
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https://api.github.com/repos/pandas-dev/pandas/issues/9700 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9700/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9700/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9700/events | https://github.com/pandas-dev/pandas/issues/9700 | 63,554,841 | MDU6SXNzdWU2MzU1NDg0MQ== | 9,700 | BUG: groupby.transform confused about index | {
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... | closed | false | null | [] | {
"closed_at": "2015-05-11T15:46:03Z",
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"followers_url": "https://api.github.com/users/jr... | 0 | 2015-03-22T17:17:25Z | 2015-04-29T10:31:53Z | 2015-04-29T10:31:53Z | CONTRIBUTOR | null | Under some circumstances, `transform` is getting confused about what the output index should be:
```
>>> df = pd.DataFrame({"c1": [1], "c2": [2]})
>>> df
c1 c2
0 1 2
>>> df.groupby('c1').transform(sum)
c2
0 NaN
1 2
```
I haven't chased down why, but since we have
```
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https://api.github.com/repos/pandas-dev/pandas/issues/9701 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/9701/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/9701/comments | https://api.github.com/repos/pandas-dev/pandas/issues/9701/events | https://github.com/pandas-dev/pandas/pull/9701 | 63,575,410 | MDExOlB1bGxSZXF1ZXN0MzE2OTQ2NzY= | 9,701 | ENH Make year and quarter dash-separatable | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2015-03-22T20:52:39Z | 2015-03-26T10:43:40Z | 2015-03-26T09:49:51Z | CONTRIBUTOR | null | This closes #9688 by making years and quarters separable by dashes.
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