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https://api.github.com/repos/pandas-dev/pandas/issues/14308 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14308/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14308/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14308/events | https://github.com/pandas-dev/pandas/pull/14308 | 179,633,564 | MDExOlB1bGxSZXF1ZXN0ODcwMjUzNTI= | 14,308 | PERF: unnecessary materialization of a MultiIndex.values when introspecting memory_usage | {
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In [2]: import string
...: import pandas as pd
...: import numpy as np
...:
...: def memory_usage(f):
...: return f.memory_usage(deep=True).sum()
...:
...: N = 100
...: M = len(string.uppercase)
...: df = pd.DataFrame({'value' : np.random.randn(N*M)},
...: index... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-09-28T00:16:01Z | 2016-09-28T10:08:52Z | 2016-09-28T10:08:52Z | CONTRIBUTOR | null | - [x] closes #10480
- [x] tests not needed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry not needed
Just making the description (hopefully) a little clearer.
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https://api.github.com/repos/pandas-dev/pandas/issues/14310 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14310/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14310/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14310/events | https://github.com/pandas-dev/pandas/issues/14310 | 179,710,215 | MDU6SXNzdWUxNzk3MTAyMTU= | 14,310 | SparseDataFrame loc multiple index is slow | {
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... | 10 | 2016-09-28T08:28:36Z | 2019-09-17T21:08:29Z | 2019-09-17T21:08:29Z | NONE | null | ``` python
In [1]: import pandas as pd
In [2]: df = pd.DataFrame([[1, 0, 0],[0,0,0]])
# non sparse
In [19]: %time df.loc[0]
CPU times: user 367 µs, sys: 14 µs, total: 381 µs
Wall time: 374 µs
Out[19]:
0 1
1 0
2 0
Name: 0, dtype: int64
In [20]: %time df.loc[[0]]
CPU times: user 808 µs, sys: 57 µs, total: 865... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14311 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14311/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14311/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14311/events | https://github.com/pandas-dev/pandas/issues/14311 | 179,713,190 | MDU6SXNzdWUxNzk3MTMxOTA= | 14,311 | DataFrame.apply(axis=1) to return a series with dictionary as value | {
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"color": "005... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2016-09-28T08:43:05Z | 2016-09-28T15:52:29Z | 2016-09-28T10:18:30Z | NONE | null | ``` python
# Your code here
df = pd.util.testing.makeTimeDataFrame(5)
df2 = df.reset_index()
ff = lambda row: {'some key': row['A']}
# this is what I want, but my dataframe is unfortunately like df2
df.apply(ff, axis = 1)
2000-01-03 {u'some key': 1.70177486613}
2000-01-04 {u'some key': -0.833481157829}
2000-01... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14312 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14312/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14312/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14312/events | https://github.com/pandas-dev/pandas/issues/14312 | 179,726,904 | MDU6SXNzdWUxNzk3MjY5MDQ= | 14,312 | read_html() performance when HTML malformed | {
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"default"... | closed | false | null | [] | null | 5 | 2016-09-28T09:46:05Z | 2018-12-12T11:22:41Z | 2018-12-11T23:19:38Z | CONTRIBUTOR | null | When parsing thousands of HTML files, I noticed there was a rather large gap in performance when using `pd.read_html` and when parsing by hand using `lxml` - one that could not be attributed to the `pandas` overhead in handling edge cases.
I looked into it a little bit and found out `pandas` uses `lxml`, but only when... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14313 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14313/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14313/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14313/events | https://github.com/pandas-dev/pandas/issues/14313 | 179,734,261 | MDU6SXNzdWUxNzk3MzQyNjE= | 14,313 | BUG: resample and apply modify the index type for empty Series | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-09-28T10:20:48Z | 2017-08-09T10:37:21Z | 2017-08-09T10:37:21Z | NONE | null | #### A small, complete example of the issue
Consider the following two resamplings on empty Series:
``` python
>>> import pandas as pd
# These work:
>>> pd.Series(index=pd.DatetimeIndex([]), data=[]).resample('H').apply(np.sum).index
DatetimeIndex([], dtype='datetime64[ns]', freq='H')
>>> pd.Series(index=pd.Dateti... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14314 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14314/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14314/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14314/events | https://github.com/pandas-dev/pandas/issues/14314 | 179,736,472 | MDU6SXNzdWUxNzk3MzY0NzI= | 14,314 | read_sql_query type detection when missing data | {
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] | closed | false | null | [] | null | 12 | 2016-09-28T10:32:11Z | 2019-06-06T15:28:45Z | 2019-06-06T15:28:44Z | NONE | null | I have choosen Pandas for an ETL project and encountered data type detection problems.
I already posted on StackOverflow and responses were pointing the fact that missing values can make data type detection error in Pandas.
Here is the post containing code example and behaviour :
http://stackoverflow.com/questions/3... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14315 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14315/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14315/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14315/events | https://github.com/pandas-dev/pandas/issues/14315 | 179,753,014 | MDU6SXNzdWUxNzk3NTMwMTQ= | 14,315 | to_sql function takes forever to insert in oracle database | {
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I am using `pd.to_sql` method to insert dataframe in the database. When I use a `MySQL` database, inserti... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14316 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14316/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14316/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14316/events | https://github.com/pandas-dev/pandas/issues/14316 | 179,896,002 | MDU6SXNzdWUxNzk4OTYwMDI= | 14,316 | Slicing with reversed datetime index | {
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Create dataframe and date reversed dataframe.
``` python
>>> import pandas as pd
>>> dates = pd.dat... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14317 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14317/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14317/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14317/events | https://github.com/pandas-dev/pandas/pull/14317 | 179,929,233 | MDExOlB1bGxSZXF1ZXN0ODcyMjk5MTY= | 14,317 | BUG: date slicing with reverse sorted index | {
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- [ ] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
cc @shoyer - good diagnosis!
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https://api.github.com/repos/pandas-dev/pandas/issues/14318 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14318/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14318/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14318/events | https://github.com/pandas-dev/pandas/pull/14318 | 179,960,892 | MDExOlB1bGxSZXF1ZXN0ODcyNTE2Njc= | 14,318 | Enforce boolean types | {
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- [ x ] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
This PR only addresses the `inplace` argument, though there was a comment on #14189 that identifies the issue as being with the `copy` argument as well. I can build this out further to a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14319 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14319/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14319/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14319/events | https://github.com/pandas-dev/pandas/issues/14319 | 179,964,421 | MDU6SXNzdWUxNzk5NjQ0MjE= | 14,319 | pd.read_sql_query() does not convert NULLs to NaN | {
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``` python
from sqlalchemy import create_engine
import pandas as pd
engine = create_engine('sqlite://')
conn = engine.connect()
conn.execute("create table test (a float)")
for _ in range(5):
conn.execute("insert into test values (NULL)")
df = pd.read_sql_query("select ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14320 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14320/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14320/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14320/events | https://github.com/pandas-dev/pandas/issues/14320 | 179,982,946 | MDU6SXNzdWUxNzk5ODI5NDY= | 14,320 | BUG: Frequency not set for empty Series | {
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#### A small, complete example of the issue
It works for non-empty series:
``` python
>>> pd.Series(index=pd.DatetimeIndex(["2016-09-29 11:00"]), data=[3]).asfreq('H').index
DatetimeIndex(['2016-09-29 11:00:00'], dtype='dateti... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14321 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14321/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14321/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14321/events | https://github.com/pandas-dev/pandas/issues/14321 | 180,021,658 | MDU6SXNzdWUxODAwMjE2NTg= | 14,321 | Expose pandas.json.dump in the public API? | {
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Would you consider making this function public, or at least as public as `pandas.json.dumps` which are at least imported into/as `pandas.io.json.dumps`.
I find the performance o... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14322 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14322/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14322/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14322/events | https://github.com/pandas-dev/pandas/issues/14322 | 180,050,856 | MDU6SXNzdWUxODAwNTA4NTY= | 14,322 | BUG in plotting timeseries data with twinx (different data representation on each ax) | {
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... | open | false | null | [] | null | 8 | 2016-09-29T13:35:13Z | 2016-11-26T09:15:56Z | null | NONE | null | Simplified the example.
During issue reporting i updated my pandas version from 0.13 to 0.18.1 - with version 0.13 i was able to add the whole DataFrame to my plot, only after i selected some rows between dates it produces the error. After the update the behaviour became worse - also adding the whole DataFrame to the p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14323 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14323/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14323/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14323/events | https://github.com/pandas-dev/pandas/issues/14323 | 180,097,622 | MDU6SXNzdWUxODAwOTc2MjI= | 14,323 | DatetimeIndex union fails in 0.19rc1 when constructed from differences in DatetimeIndexes | {
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``` python
x = pd.DatetimeIndex(['20160923', '20160924']) ... | {
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Merged in PR #14453
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``` python
# Your code here
# This is what I have in my project's setup.py
install_requires=['pandas']
```
and my install command is the usual `python setup.py install`
#### Expected Output
pip installs an official release of pandas
#### Actual Output
``` bash
Processin... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14327 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14327/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14327/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14327/events | https://github.com/pandas-dev/pandas/issues/14327 | 180,426,731 | MDU6SXNzdWUxODA0MjY3MzE= | 14,327 | Grouping by index and column fails on DataFrame with single index | {
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#### Example
The following snippet shows how a MultiIndex DataFrame (`df`) may be grouped by a combination of a column (`B`) and a named index level (`inner`) using a `Grouper` object.
``` python
import pandas as pd
import numpy as np
idx = pd.MultiIndex.from_tuples([('a', 1), ('a', 2), ('a', 3),... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14328 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14328/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14328/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14328/events | https://github.com/pandas-dev/pandas/issues/14328 | 180,435,701 | MDU6SXNzdWUxODA0MzU3MDE= | 14,328 | RuntimeWarning: Invalid value encountered in percentile RuntimeWarning | {
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I am Using Pycharm
PyCharm Community Edition 2016.2.3
Build #PC-162.1967.10, built on September 7, 2016
JRE: 1.8.0_112-release-b343 x86_64
JVM: OpenJDK 64-Bit Server VM by JetBrains s.r.o
``` python
arr = np.array([[1,2,np.nan],[np.nan,3,4]])
dframe1 = DataFrame(arr,index=[... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14329 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14329/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14329/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14329/events | https://github.com/pandas-dev/pandas/pull/14329 | 180,469,271 | MDExOlB1bGxSZXF1ZXN0ODc2MDkwMjA= | 14,329 | to_latex encoding issue | {
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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/14330 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14330/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14330/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14330/events | https://github.com/pandas-dev/pandas/pull/14330 | 180,477,086 | MDExOlB1bGxSZXF1ZXN0ODc2MTM1ODM= | 14,330 | BUG: mixed freq timeseries plotting with shared axes (GH13341) | {
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cc @sinhrks @TomAugspurger
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https://api.github.com/repos/pandas-dev/pandas/issues/14332 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14332/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14332/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14332/events | https://github.com/pandas-dev/pandas/pull/14332 | 180,481,558 | MDExOlB1bGxSZXF1ZXN0ODc2MTYzNzk= | 14,332 | DOC: fix some sphinx build issues | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14333 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14333/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14333/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14333/events | https://github.com/pandas-dev/pandas/pull/14333 | 180,489,605 | MDExOlB1bGxSZXF1ZXN0ODc2MjEyODI= | 14,333 | Bug: Grouping by index and column fails on DataFrame with single index (GH14327) | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Don't know if this is too late for 0.19.0 but I went ahead and added the whatsnew entry there for now.
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"followers_url": "https://api.github.com/users/jre... | 2 | 2016-10-03T00:13:34Z | 2016-10-25T10:51:36Z | 2016-10-25T10:51:36Z | CONTRIBUTOR | null | #### Overview
A `Grouper` object configured with only a `key` specification may be passed to `groupby` to group a DataFrame by a particular column. For example:
``` python
In [19]: import pandas as pd
In [20]: df = pd.DataFrame({'A': [0, 0, 0, 1, 1, 1],
...: 'B': [1, 1, 2, 2, 3, 3],
...: ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14335 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14335/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14335/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14335/events | https://github.com/pandas-dev/pandas/issues/14335 | 180,641,477 | MDU6SXNzdWUxODA2NDE0Nzc= | 14,335 | Feature Request: add explicit support for double (multiple) inequalities | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2016-10-03T13:34:18Z | 2016-10-04T14:34:43Z | 2016-10-03T13:45:15Z | CONTRIBUTOR | null | This will improve readability:
As is:
``` python
df[(8 < df.foo + df.bar) & (df.foo + df.bar <= 42)].measure.sum()
```
To be:
``` python
df[8 < df.foo + df.bar <= 42].measure.sum()
```
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https://api.github.com/repos/pandas-dev/pandas/issues/14336 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14336/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14336/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14336/events | https://github.com/pandas-dev/pandas/issues/14336 | 180,644,225 | MDU6SXNzdWUxODA2NDQyMjU= | 14,336 | API: add DataFrame.nunique() and DataFrameGroupBy.nunique() | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2016-10-03T13:45:59Z | 2017-01-23T13:41:51Z | 2017-01-23T13:41:25Z | CONTRIBUTOR | null | When exploring a data set, I often need to `df.apply(pd.Series.nunique)` or `df.apply(lambda x: x.nunique())`. How about adding this as `nunique()`-method parallel to `DataFrame.count()` (`count` and `unique` are also the two most basic infos displayed by `DataFrame.describe()`)?
I think there are also use cases for t... | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2016-10-03T15:12:49Z | 2016-10-03T15:48:19Z | 2016-10-03T15:47:56Z | MEMBER | null | #### A small, complete example of the issue
``` python
In [2]: df = pd.DataFrame({'float' : range(4),
...: 'int' : range(4)},
...: index=pd.MultiIndex.from_product([[1,2]]*2))
In [3]: df['float'] = df['float'].astype(float)
In [4]: df.loc[(1,), 'int']
Out[4]:
1 0
2 ... | {
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"followers_url": "https://api.github.com/users/jre... | 10 | 2016-10-03T16:12:34Z | 2016-10-15T19:27:11Z | 2016-10-15T19:27:11Z | CONTRIBUTOR | null | ``` python
df = DataFrame(data={'data': np.random.randint(0, 100, size=5500000),
'date': [dt(2016, 1, 1)] * 5500000})
for period, g in df.groupby(pd.DatetimeIndex(df.date).to_period('D')):
print(g)
```
#### Expected Output
outputs dataframe
#### Output of `pd.show_versions()`
0.19.0
The... | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2016-10-03T20:53:29Z | 2016-11-23T13:09:47Z | 2016-11-23T13:09:47Z | NONE | null | When using a for loop with a dictionary of dataframes, DataFrame.drop() raises an unexpected error, apparently unable to find the label, even when that label exists and is handled correctly in a single df.
#### A small, complete example of the issue
``` python
>>> for key in dfs2:
>>> dfs2[key].drop('0',axis=0,inpl... | {
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"followers_url": "https://api.github.com/users/jorisva... | 5 | 2016-10-03T22:57:17Z | 2016-10-31T14:54:50Z | 2016-10-19T23:26:55Z | CONTRIBUTOR | null | - [x] closes #14320
- [x] tests added / passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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``` python
{{nogil_str}}
{{tab}}prev = arr[0]
{{tab}}for i in range(1, n):
{{tab}} cur = arr[i]
{{tab}} if timelike and cur == iNaT:
{{tab}} is_monotonic_inc = 0
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"followers_url": "https://api.github.com/users/jre... | 9 | 2016-10-04T00:22:28Z | 2016-10-26T12:12:19Z | 2016-10-25T10:51:36Z | CONTRIBUTOR | null | - [x] closes #14334
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Bug in Numpy causes inf values to be falsely converted to integers. I added a ValueError exception similar to the exception for trying to convert NaN to an integer.
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https://api.github.com/repos/pandas-dev/pandas/issues/14344 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14344/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14344/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14344/events | https://github.com/pandas-dev/pandas/pull/14344 | 180,812,593 | MDExOlB1bGxSZXF1ZXN0ODc4MzcyMzY= | 14,344 | DOC: Correct uniqueness of index for Series | {
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Just wanted to fix the docstring to reflect the fact that the index labels neither need to be unique ~~nor hashable~~.
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https://api.github.com/repos/pandas-dev/pandas/issues/14345 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14345/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14345/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14345/events | https://github.com/pandas-dev/pandas/issues/14345 | 180,925,247 | MDU6SXNzdWUxODA5MjUyNDc= | 14,345 | TST: failing test at tseries/tests/test_base.py TestDatetimeIndexOps test_nat | {
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``` python
======================================================================
FAIL: test_nat (pandas.tseries.tests.test_base.TestDatetimeIndexOps)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/matt... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14346 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14346/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14346/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14346/events | https://github.com/pandas-dev/pandas/pull/14346 | 181,032,084 | MDExOlB1bGxSZXF1ZXN0ODc5OTQxOTU= | 14,346 | BUG: GH14323 Union of differences from DatetimeIndex incorrect | {
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"followers_url": "https://api.github.com/users/jre... | 4 | 2016-10-04T23:40:04Z | 2016-10-24T22:34:25Z | 2016-10-24T22:34:21Z | CONTRIBUTOR | null | - [ ] closes #14323
- [ ] tests added / passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
Sets freq to None when doing a difference operation on a DatetimeIndex
or TimedeltaIndex, rather than retaining the frequency (which can cause
problems with downstream operations). Frequency of ... | {
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Changed tm.assert_numpy_array_equal(idx._nan_idxs, np.array([], dtype=np.int64)
np.int64 to npintp
All tests now pass on 32bit linux install.
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---
- [x] closes #14338
- [x] tests not needed / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
asv
```
before after ratio
[c41c6511] [96b364a4]
- 2.44s 46.28ms 0.02 groupby.groupby_period.time_groupby_sum
```
cc @sinhrks , @bmoscon
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... | 14 | 2016-10-05T05:11:46Z | 2016-10-10T04:46:39Z | 2016-10-10T04:46:39Z | CONTRIBUTOR | null | #### Example Code
`print(pd.DataFrame({'a': np.zeros(1000, 'V4')}))`
#### Results
Non-deterministic behavior. Sometimes you get all zeros, sometimes you get garbage like this:
```
a
0 [1, 0, 0, 0]
1 [0, 0, 0, 0]
2 [8, 0, 0, 0]
3 [0, 0, 0, 0]
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```
import pandas as pd
pd.to_datetime(datetime.datetime(2016,1,1), unit='s')
Traceback (most recent call last):
File "/home/julienv/.pycharm_helpers/pydev/pydevd_exec2.py", line 3, in Exec
exec(exp, global_vars, local_vars)
File "<input>", line 1, in <module>
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making ticker as category:
``` python
trades.ticker = ... | {
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This issue is for how to do this, as we are ready to merge some 0.19.1 fixes. So nee... | {
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"followers_url": "https://api.github.com/users/j... | 1 | 2016-10-05T12:49:01Z | 2018-01-05T19:15:38Z | 2018-01-05T19:15:38Z | CONTRIBUTOR | null | #### Background
During the review of @jreback's PR last year to cleanup the sorting API (#10726) there was some discussion of how the DataFrame API could eventually support sorting by a combination of columns and index levels. I'm interested in working on implementing this soon and would like to continue the discussi... | {
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### Pandas 0.18
``` python
In [1]: import pandas as pd
In [2]: index = pd.DatetimeIndex(freq='1H', periods=0, end='2015')
In [3]: index._maybe_cast_slice_bound('2015-01-02', 'right', 'loc')
Out[3]: Timestamp('2015-0... | {
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"followers_url": "https://api.github.com/users/j... | 6 | 2016-10-05T14:00:26Z | 2017-12-01T17:29:25Z | 2017-12-01T16:45:20Z | CONTRIBUTOR | null | - [x] `.groupby` #5677
- [ ] `.sort_values` #14353, though this is directly in combat with `.sort_index` and non-explict
- [x] `.merge` (this issue)
#### Overview
@jorisvandenbossche
As a part of the [Pandas 1.0](https://docs.google.com/document/d/151ct8jcZWwh7XStptjbLsda6h2b3C0IuiH_hfZnUA58/edit#) goal to "Mak... | {
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```
======================================================================
ERROR: test_readonly_axis_zlib_to_sql (pandas.io.tests.test_packers.TestCompression)
----------------------------------------------------------------------
Traceback (most recent... | {
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In [7]: df = pd.DataFrame(np.random.randn(10, 2))
In [8]: df.iloc[1, 1] = np.nan
In [9]: df.quantile(.5)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-9-66d518aa86c6> in <module>()
---->... | {
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... | 2 | 2016-10-05T18:53:17Z | 2020-05-03T10:37:35Z | null | NONE | null | #### A small, complete example of the issue
``` python
pd.read_json('[{}, null]') # This raises `AttributeError`
pd.read_json('[null, {}]') # This does not
```
While this isn't a big problem, the output is not as expected. The only way I see this causing issues for me is for parsing JSON received on a server; the r... | {
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- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
reproduction case:
``` python
In [1]: array = np.array([1, 2, 3])
In [2]: array.flags.writeable = False
In [3]: series = pd.Series(array)
In [4]: series[0] = -1
In [5]: series
Out[5]:
0 -1
1 2
2 3
dtyp... | {
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pd.date_range returns a different number of dates when used with different dates and the same DateOffset. Note that both dates are month end dates and that 2008 is a leap year (potential source of bug).
``` python
In [1]:
month = pd.to_datetime('2007-02-28')
pd.date_range(m... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14361 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14361/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14361/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14361/events | https://github.com/pandas-dev/pandas/issues/14361 | 181,293,069 | MDU6SXNzdWUxODEyOTMwNjk= | 14,361 | Selecting an element or row of mixed int/float DataFrame returns all floats | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2016-10-05T23:45:22Z | 2016-10-06T22:54:03Z | 2016-10-06T00:57:30Z | CONTRIBUTOR | null | #### A small, complete example of the issue
``` python
In [37]: df = pd.DataFrame(dict(a=[0,1,2,3],b=[0.0,1.0,2.0,3.0]))
In [38]: df
Out[38]:
a b
0 0 0.0
1 1 1.0
2 2 2.0
3 3 3.0
In [39]: df.dtypes
Out[39]:
a int64
b float64
dtype: object
In [40]: df.iloc[0]
Out[40]:
a 0.0
b 0.0
Name: 0, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14362 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14362/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14362/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14362/events | https://github.com/pandas-dev/pandas/issues/14362 | 181,301,305 | MDU6SXNzdWUxODEzMDEzMDU= | 14,362 | BUG: clipboard functions windows 10 py3.5 | {
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"closed_at": "2016-12-24T22:50:46Z",
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"followers_url": "https://api.github.com/users/jr... | 1 | 2016-10-06T00:54:38Z | 2016-11-18T22:43:10Z | 2016-11-18T22:42:37Z | CONTRIBUTOR | null | This seems to work ok in the current version of pyperclip, but is broken in our vendored version, so likely just need to update.
https://github.com/asweigart/pyperclip
https://github.com/asweigart/pyperclip/pull/41
```
# Your code here
In [1]: df = pd.DataFrame(np.random.randn(10, 2))
In [2]: df.to_clipboard()
-----... | {
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... | closed | false | null | [] | {
"closed_at": "2017-05-06T10:20:19Z",
"closed_issues": 987,
"created_at": "2016-02-08T15:30:21Z",
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"followers_url": "https://api.github.com/users/jr... | 3 | 2016-10-06T01:22:24Z | 2016-10-12T09:15:58Z | 2016-10-12T09:15:49Z | CONTRIBUTOR | null | Currently the cython cache on travis doesn't pick up change in `.pxd` files Most of this commit history is trial and error - but 479c311 shows this working
https://travis-ci.org/pydata/pandas/jobs/166041112
```
$ ci/prep_cython_cache.sh
cython_files.tar motd.legal-displayed pip pyxfiles
Cache available - checking... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14364 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14364/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14364/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14364/events | https://github.com/pandas-dev/pandas/issues/14364 | 181,347,612 | MDU6SXNzdWUxODEzNDc2MTI= | 14,364 | Inconsistent behaviour on empty RangeIndex intersection | {
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Two empty RangeIndex objects with same starts and stops will have a non-null intersection.
## Code example
``` python
import pandas as pd
# Two empty rangeindexes
a = pd.RangeIndex(0, 0)
b = pd.RangeIndex(0, 0)
# Also empty but different start and stops
c = pd.RangeIndex(1, 1)
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"followers_url": "https://api.github.com/users/jre... | 6 | 2016-10-06T09:00:24Z | 2016-10-06T15:46:36Z | 2016-10-06T09:25:23Z | CONTRIBUTOR | null | - [ ] closes #xxxx
- [ ] tests added / passed
- [ ] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
The warning is about something that have been fixed for almost 3 years. Every time a new user excited about pandas start reading the docs, they have to waste brain-cycles ignoring that big red war... | {
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```
a ,a ,a
1,2,3
4,5,6
7,8,9
```
note the white space next to the char.
``` python
>>> import pandas
>>> df = pandas.read_table('test.csv', sep=',')
>>> df.columns
Index([u'a ', u'a .1', u'a .2'], dtype='object')
```
again, note the white space between the char and the ... | {
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... | 7 | 2016-10-06T17:35:11Z | 2019-10-27T18:26:21Z | null | CONTRIBUTOR | null | ```
In [2]: df = pd.DataFrame({'A' : pd.Series(list('aabc')).astype('category'), 'B' : range(4)})
In [3]: df
Out[3]:
A B
0 a 0
1 a 1
2 b 2
3 c 3
In [4]: df.dtypes
Out[4]:
A category
B int32
dtype: object
In [5]: df.dtypes.value_counts()
Out[5]:
category 1
int32 1
dtype: int64
In [6]: d... | {
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Is there something special going on here that `pd.concat` seems to interpret `axis='rows'` as `axis=1`?
``` python
In [1]: import pandas as pd
In [2]: pd.__version__
Out[2]: '0.19.0'
In [3]: import numpy as np
In [5]: df1 = pd.DataFrame({'A':np.random.normal(size=5)}, in... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14370 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14370/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14370/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14370/events | https://github.com/pandas-dev/pandas/issues/14370 | 181,583,510 | MDU6SXNzdWUxODE1ODM1MTA= | 14,370 | inconsistant result shape from dataframe.apply depending on if a date column is present | {
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``` python
import pandas as pd
df1 = pd.DataFrame.from_items([('A', [1,2,3]), ('B', [4, 5, 6])])
df2 = pd.DataFrame.from_items([('A', [pd.datetime(1970,1,1), pd.datetime(1970,1,1), pd.datetime(1970,1,1)]), ('B', [4, 5, 6])])
f = lambda row: [row.B + 3]
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https://api.github.com/repos/pandas-dev/pandas/issues/14371 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14371/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14371/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14371/events | https://github.com/pandas-dev/pandas/pull/14371 | 181,597,737 | MDExOlB1bGxSZXF1ZXN0ODgzODkyNTM= | 14,371 | BUG: Fix linux Qt clipboard QApplication() creation | {
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A Qt application cannot instantiate multiple `QApplication` instances,
so we create a new `QApplication` only when the global
`QApplication.instance()` is None.
Failing sample:
```
from PyQt4.QtGui import QApplication
myapp = QApplication([])
from pandas.util.clipboard import clipboard_get # <--- ERROR... | {
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``` python
import pandas
pandas.read_clipboard()
---------------------------------------------------------------------------
... | {
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"followers_url": "https://api.github.com/users/jorisva... | 14 | 2016-10-07T10:49:09Z | 2016-10-17T15:15:18Z | 2016-10-08T11:31:08Z | CONTRIBUTOR | null | """the example is merely
pip install pandas - which fails, so download and run
python ./setup.py build
```
I fear it is a specific behavior of gcc compared to not gcc/gnu 'features' (aka NGNU for 'Not "GNU Not Unix"')
I will attach the .cpp, as well as a .i (-E) output, as well as verbose include file processing (.i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14374 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14374/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14374/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14374/events | https://github.com/pandas-dev/pandas/issues/14374 | 181,638,933 | MDU6SXNzdWUxODE2Mzg5MzM= | 14,374 | ExcelWriter not able to save using PyQt4 | {
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Would it be possible to use pandas ... | {
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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/14378 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14378/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14378/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14378/events | https://github.com/pandas-dev/pandas/pull/14378 | 181,835,222 | MDExOlB1bGxSZXF1ZXN0ODg1NTExOTA= | 14,378 | BUG: Convert float freqstrs to ints at finer resolution | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2016-10-08T16:32:21Z | 2019-01-18T18:25:57Z | 2016-12-14T16:08:04Z | CONTRIBUTOR | null | - [x] closes #8419
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
Passing `'0.5min'` as a frequency string should generate 30 second
intervals, rather than five minute intervals. By recursively increasing
resolution until one is found for which the frequency is... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14379 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14379/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14379/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14379/events | https://github.com/pandas-dev/pandas/issues/14379 | 181,842,124 | MDU6SXNzdWUxODE4NDIxMjQ= | 14,379 | In read_csv, setting index_col breaks functionality of converters when engine='python' | {
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When setting index_col, and a converters dict, output of engine='c' is correct and output of engine='python' is wrong
``` python
def first(s):
return s[0]
io = StringIO('col1,col2\n1_,a\n2_,b\n')
print pd.read_csv(io, index_col=0, converters = {0 : first})
col2
col1
1 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14380 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14380/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14380/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14380/events | https://github.com/pandas-dev/pandas/pull/14380 | 181,852,656 | MDExOlB1bGxSZXF1ZXN0ODg1NjEzNzc= | 14,380 | BUG: pivot_table may raise TypeError without values | {
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- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
`pivot_table` raises `TypeError` when `index` or `columns` is array-like and `values` is not specified.
```
df = pd.DataFrame({'A': [1, 2, 3, 4, 5]},
index=pd.DatetimeIndex(['2011-01-01', '2011-02... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14381 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14381/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14381/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14381/events | https://github.com/pandas-dev/pandas/issues/14381 | 181,857,416 | MDU6SXNzdWUxODE4NTc0MTY= | 14,381 | Dataframe constructor fails when given dict with None value | {
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``` python
# Your code here
import pandas as pd
pd.Dataframe(dict(a=None), index= [0])
```
```
In [3]: pd.DataFrame(dict(a=None),index=[0])
---------------------------------------------------------------------------
AttributeError Traceback (most... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14382 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14382/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14382/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14382/events | https://github.com/pandas-dev/pandas/issues/14382 | 181,879,225 | MDU6SXNzdWUxODE4NzkyMjU= | 14,382 | BUG:to_csv error when the file include space and '(' ')' | {
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``` python
# Your code here
# -*- coding: utf-8 -*-
import pandas as pd
from pandas import DataFrame
f = pd.read_excel('./123.xlsx',index_col = None)
f2 = pd.DataFrame()
for i in range(0,len(f)):
f2.loc[i,'Term'] = f.loc[i,'Term']
if f.loc[i,'P-value'] <= 0.05:
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https://api.github.com/repos/pandas-dev/pandas/issues/14383 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14383/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14383/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14383/events | https://github.com/pandas-dev/pandas/pull/14383 | 181,922,515 | MDExOlB1bGxSZXF1ZXN0ODg2MDA5Mzk= | 14,383 | ENH: feather support in the pandas IO api | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14384 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14384/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14384/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14384/events | https://github.com/pandas-dev/pandas/pull/14384 | 181,923,776 | MDExOlB1bGxSZXF1ZXN0ODg2MDE3NDA= | 14,384 | BUG: Fix issue with inserting duplicate columns in a dataframe (GH14291) | {
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
I've been sitting on this simple fix because it seems a little kludgy. SparseDataFrame doesn't do anything parallel to broadcasting in its _sanitize_column method... should it?
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https://api.github.com/repos/pandas-dev/pandas/issues/14385 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14385/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14385/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14385/events | https://github.com/pandas-dev/pandas/issues/14385 | 181,924,542 | MDU6SXNzdWUxODE5MjQ1NDI= | 14,385 | Python pandas use method of merge， return empty DataFrame | {
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``` python
#
df1 = pd.read_excel('gz.xlsx')
df2 = pd.read_excel('dyml.xlsx')
pd.merge(df1, df2, on = 'name')
```
#### df1 and df2 have the same data in column name,but it can't merge
#### Output of `Empty DataFrame`
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https://api.github.com/repos/pandas-dev/pandas/issues/14386 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14386/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14386/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14386/events | https://github.com/pandas-dev/pandas/issues/14386 | 182,022,899 | MDU6SXNzdWUxODIwMjI4OTk= | 14,386 | Support exporting to JSON Table Schema | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14387 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14387/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14387/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14387/events | https://github.com/pandas-dev/pandas/issues/14387 | 182,023,833 | MDU6SXNzdWUxODIwMjM4MzM= | 14,387 | DOC: Series.sum skipna= param defaults to None | {
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Docs for pandas.Series.sum state that "skipna=None" in the function name, but then reads "skipna : boolean, default True" in the "parameters" section.
**It is not clear whether the default is "None" or "True".**
Many thanks.
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https://api.github.com/repos/pandas-dev/pandas/issues/14388 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14388/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14388/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14388/events | https://github.com/pandas-dev/pandas/pull/14388 | 182,069,128 | MDExOlB1bGxSZXF1ZXN0ODg3MDA0MjI= | 14,388 | DOC: Add details to DataFrame groupby transform | {
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- [X] tests added / passed
- [X] passes `git diff upstream/master | flake8 --diff`
- [ ] whatsnew entry
Add requirements for user function in groupby transform
closes #13543
[skip ci]
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https://api.github.com/repos/pandas-dev/pandas/issues/14389 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14389/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14389/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14389/events | https://github.com/pandas-dev/pandas/pull/14389 | 182,125,308 | MDExOlB1bGxSZXF1ZXN0ODg3MzgxODk= | 14,389 | BUG: Allow concat to take string axis names | {
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---
- [x] closes #14369
- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
This uses [`_get_axis_number`](https://github.com/pydata/pandas/blob/master/pandas/core/generic.py#L327-L338) to convert a string `axis` parameter to an integer. This ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14390 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14390/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14390/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14390/events | https://github.com/pandas-dev/pandas/issues/14390 | 182,131,633 | MDU6SXNzdWUxODIxMzE2MzM= | 14,390 | BUG: Line delimited json is breaks if string includes `}` | {
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#### Example
``` python
import pandas as pd
pd.DataFrame([{'a': 'foo}', 'b': 'bar'}, {'a': 'foo2', 'b': 'bar2'}]).to_json(orient='records', lines=True)
'{"a":"foo}"\n"b":"bar"},{"a":"foo2"\n"b":"bar2"}'
```
#### Expected Output... | {
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- [x] tests added / passed
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- [x] tests added / passed
- [x] passes `git diff upstream/master | flake8 --diff`
- [x] whatsnew entry
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"followers_url": "https://api.github.com/users/jorisva... | 5 | 2016-10-11T01:45:08Z | 2016-10-26T10:51:14Z | 2016-10-26T10:51:13Z | CONTRIBUTOR | null | #### A small, complete example of the issue
As called out in #14381, if `dtype` is not specified, values of `None` should be coerced to `np.nan`. However, when a list of only `None` is passed to `data`, the `None` remains.
``` python
>>> pd.DataFrame([None])
0
0 None
>>> pd.DataFrame([None, None])
0
0 ... | {
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``` python
"""Example of Pandas bug."""
from numpy.random import randn
from pandas import DataFrame, read_msgpack
POWER = 6
ROWS = 10 ** POWER
COLS = 280
SIZE = ROWS * COLS
# COL_NAMES = ['Columns']
print('rows: {:,}; cols: {}; data points: {:,}; float memory (bytes): {:,}... | {
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```
import pandas as pd
import numpy as np
a = pd.DataFrame(np.random.randint(0,100,size=(100, 4)))
a.tail(1)/a.head(1)
```
Expected Behavior:
some float point value
Actual Behavior:
```
0 1 2 3
0 NaN NaN NaN NaN
99 NaN NaN NaN NaN
```
Confirmed on OSX python3, Pandas v0.19.0 v0.18.1
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https://api.github.com/repos/pandas-dev/pandas/issues/14396 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14396/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14396/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14396/events | https://github.com/pandas-dev/pandas/issues/14396 | 182,248,911 | MDU6SXNzdWUxODIyNDg5MTE= | 14,396 | pandas.*.sample may return empty objects if frac <= 2^{-axis_length} | {
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"description": "R... | closed | false | null | [] | null | 6 | 2016-10-11T12:18:37Z | 2017-12-22T14:01:33Z | 2017-12-22T14:01:33Z | CONTRIBUTOR | null | #### A small, complete example of the issue
``` python
import pandas as pd
axis_length = 1
df = pd.Series([0])
df.sample(frac=2**(-axis_length))
Series([], dtype: int64)
```
#### Expected Output
Series([1], dtype: int64)
#### Why?
I tried to sample fractions of groups, some groups containted only one entry and we... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14397 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14397/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14397/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14397/events | https://github.com/pandas-dev/pandas/issues/14397 | 182,251,669 | MDU6SXNzdWUxODIyNTE2Njk= | 14,397 | first_valid_index for all NaN DataFrame | {
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"color": "00... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2016-10-11T12:32:52Z | 2016-10-11T16:13:00Z | 2016-10-11T16:12:41Z | NONE | null | Similar to [this one](https://github.com/pydata/pandas/issues/9752), but on a non-empty DataFrame whose values are all NaN.
This raises an error, instead of returning None
``` python
pd.Series([np.nan]).first_valid_index() # this returns None
pd.DataFrame([np.nan]).first_valid_index() # raise error
>>> pd.__version_... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14398 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14398/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14398/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14398/events | https://github.com/pandas-dev/pandas/issues/14398 | 182,258,371 | MDU6SXNzdWUxODIyNTgzNzE= | 14,398 | Incompatibility between pandas.infer_freq and pandas.to_timedelta | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2016-10-11T13:04:22Z | 2016-10-12T15:19:10Z | 2016-10-12T15:19:10Z | NONE | null | #### A small, complete example of the issue
The output of `pd.infer_freq` is "D" while `pd.to_timedelta` expects "1D".
``` python
import pandas as pd
dates = pd.date_range(start='2016-10-01', end='2016-10-10', freq='1D')
freq = pd.infer_freq(dates)
delta = pd.to_timedelta(freq)
```
#### Expected Output
delta = Timed... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14399 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14399/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14399/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14399/events | https://github.com/pandas-dev/pandas/issues/14399 | 182,393,677 | MDU6SXNzdWUxODIzOTM2Nzc= | 14,399 | ENH: Create limitation on HDF5 queries such that users do not go over RAM | {
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"description": "read_hdf... | closed | false | null | [] | null | 4 | 2016-10-11T22:46:34Z | 2021-05-08T00:09:01Z | 2021-05-08T00:09:01Z | NONE | null | #### A small, complete example of the issue
Create a "max_size" parameter for `HDFStore.select()` which stops the user from executing queries over RAM limit, or any limit set by user. At the moment, if users try to create a pandas `df` from this query larger than RAM, the script simply freezes.
This issue was discus... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14400 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14400/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14400/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14400/events | https://github.com/pandas-dev/pandas/issues/14400 | 182,618,323 | MDU6SXNzdWUxODI2MTgzMjM= | 14,400 | [ENH] Need a best dtype method | {
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Basically, the `pandas.read_*` methods and constructors are awesome at [assigning the highest level of dtype](http://pandas.pydata.org/pandas-docs/stable/basics.html#dtypes) that can include all values of a column. But such functionality is lacking for DataFrames created by other methods (stack, unst... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14401 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14401/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14401/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14401/events | https://github.com/pandas-dev/pandas/issues/14401 | 182,621,680 | MDU6SXNzdWUxODI2MjE2ODA= | 14,401 | BUG: pd.to_numeric(..., downcast='unsigned') should accept 0 | {
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"description": "Unexpected or buggy dtyp... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2016-10-12T20:09:50Z | 2016-12-14T16:37:00Z | 2016-11-17T13:10:59Z | CONTRIBUTOR | null | with 0.19.0.
```
In [28]: pd.to_numeric(pd.Series([1,2,3]), downcast='unsigned')
Out[28]:
0 1
1 2
2 3
dtype: uint8
In [29]: pd.to_numeric(pd.Series([0,1,2,3]), downcast='unsigned')
Out[29]:
0 0
1 1
2 2
3 3
dtype: int64
```
```
In [30]: np.iinfo(np.uint8).min
Out[30]: 0
```
I think 0 is a legi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14402 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14402/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14402/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14402/events | https://github.com/pandas-dev/pandas/issues/14402 | 182,628,310 | MDU6SXNzdWUxODI2MjgzMTA= | 14,402 | AmbiguousTimeError: Cannot infer dst time from Timestamp('2015-11-01 01:00:03'), try using the 'ambiguous' argument | {
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... | closed | false | null | [] | {
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This issue appears very similar to #11619 and #11626, both of which have been closed. The traceback is below.
``` python
df['Timestamp'] = df['Timestamp Date'] + " " + df['Timestamp Time']
df['Timestamp'] = pd.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14403 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14403/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14403/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14403/events | https://github.com/pandas-dev/pandas/issues/14403 | 182,628,729 | MDU6SXNzdWUxODI2Mjg3Mjk= | 14,403 | Add decimal option to read_excel | {
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"followers_url": "https://api.github.com/users/jreback/followers",... | 26 | 2016-10-12T20:41:23Z | 2021-11-05T13:05:22Z | 2021-11-05T13:05:22Z | NONE | null | The `pd.read_csv()` function has a `decimal` option, which allows it to parse European dates very easily:
```
pd.read_csv("afile.csv", decimal=',')
```
This option is not present in `pd.read_excel()`, but it could also be very useful there.
It would be even more useful if this option was a list of characters to inte... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14404 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14404/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14404/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14404/events | https://github.com/pandas-dev/pandas/pull/14404 | 182,636,563 | MDExOlB1bGxSZXF1ZXN0ODkwOTU3OTk= | 14,404 | Bug: Made it so that 0 was included in uint8 | {
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- [ ] tests added / passed
- [ ] passes git diff upstream/master | flake8 --diff
- [ ] whatsnew entry
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https://api.github.com/repos/pandas-dev/pandas/issues/14405 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14405/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14405/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14405/events | https://github.com/pandas-dev/pandas/pull/14405 | 182,640,641 | MDExOlB1bGxSZXF1ZXN0ODkwOTg4MDI= | 14,405 | BUG: Bug in localizing an ambiguous timezone when a boolean is passed | {
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```
In [1]: s = pd.Series([Timestamp('2015-11-01 01:00:03')])
In [2]: s
Out[2]:
0 2015-11-01 01:00:03
dtype: datetime64[ns]
In [3]: s.dt.tz_localize('US/Central', ambiguous=False)
Out[3]:
0 2015-11-01 01:00:03-06:00
dtype: datetime64[ns, US/Central]
In [4]: s.dt.tz_localize('US/Central', ambiguo... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/14406 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/14406/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/14406/comments | https://api.github.com/repos/pandas-dev/pandas/issues/14406/events | https://github.com/pandas-dev/pandas/pull/14406 | 182,641,267 | MDExOlB1bGxSZXF1ZXN0ODkwOTkyNjI= | 14,406 | Convert readthedocs links for their .org -> .io migration for hosted projects | {
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... | 0 | 2016-10-12T22:03:46Z | 2021-05-02T00:32:25Z | null | CONTRIBUTOR | null | xref #14400
```
In [49]: df = pd.DataFrame({'c1' : list('ABC'),
...: 'c2' : list('123'),
...: 'c3' : np.random.randn(3),
...: 'c4' : np.arange(3)})
In [50]: df
Out[50]:
c1 c2 c3 c4
0 A 1 0.645628 0... | {
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