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https://api.github.com/repos/pandas-dev/pandas/issues/8501 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8501/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8501/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8501/events | https://github.com/pandas-dev/pandas/pull/8501 | 45,130,854 | MDExOlB1bGxSZXF1ZXN0MjIzNjY1Mzg= | 8,501 | Raise more specific exception on concat([None]) | {
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ConcatenationError follows the pattern of MergeError which is used in the same file when something is wrong with a caller's inputs to merge().
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so it appears that matplotlib changed the version string in 1.4.0 to be `unicode` (and not a string).
(to be honest I would call that a bug, separate issue).
BUT our tests now fail because of this, I guess
`str(matploblib.__v... | {
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I discovered the SparseDataFrame very recently and ran into the following:
``` python
In [19]: %paste
In [6]: df = DataFrame(randn(10000, 4))
In [7]: df.ix[:9998] = np.nan
In [8]: sdf = df.to_sparse()
## -- End pasted text --
In [20]: sdf.values.nbytes == randn(10000,4).nbytes
Out[20]: True
In [21]: sdf.densi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8505 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8505/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8505/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8505/events | https://github.com/pandas-dev/pandas/issues/8505 | 45,209,189 | MDU6SXNzdWU0NTIwOTE4OQ== | 8,505 | Behavior of pandas.DataFrame.duplicated() | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8506 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8506/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8506/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8506/events | https://github.com/pandas-dev/pandas/issues/8506 | 45,223,228 | MDU6SXNzdWU0NTIyMzIyOA== | 8,506 | groupby.apply raises ValueError when as_index=True on 0.15 RC1 | {
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The following code ran perfectly fine on 0.14.1, but breaks on 0.15 RC1, raising
ValueError: cannot reindex from a duplicate axis.
Is it a bug or an intended change of behaviour? Thanks.
``` python
import pandas as pd
import numpy as np
d = {'Quantity' : pd.Series([1., 2., 3., 4., 5.],
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"f... | 19 | 2014-10-08T15:48:29Z | 2019-12-17T18:14:09Z | 2019-12-17T18:14:09Z | CONTRIBUTOR | null | It would be really great if `to_(filetype)` supported writing to S3.
Here is an example upload to s3 function that takes in a local file and places it on a s3 bucket.
``` python
def upload_to_s3(local_file_path, file_name, bucket_name, s3_directory):
"""
Returns
----------
Uploads local file to appro... | {
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"followers_url": "https://api.github.com/users/jre... | 9 | 2014-10-08T19:42:39Z | 2014-10-30T11:19:44Z | 2014-10-08T20:06:42Z | MEMBER | null | From the example in the v0.13.1 whatsnew docs (http://pandas.pydata.org/pandas-docs/version/0.15.0/whatsnew.html#id12):
```
df = DataFrame({'col':['foo', 0, np.nan]}).sort()
df2 = DataFrame({'col':[np.nan, 0, 'foo']}, index=[2,1,0])
df.equals(df)
```
gives:
```
In [3]: df.equals(df)
C:\Anaconda\lib\site-packages\num... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8510 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8510/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8510/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8510/events | https://github.com/pandas-dev/pandas/pull/8510 | 45,287,572 | MDExOlB1bGxSZXF1ZXN0MjI0NDkwMjE= | 8,510 | DOC: fix example sql chunksize | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8511 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8511/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8511/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8511/events | https://github.com/pandas-dev/pandas/issues/8511 | 45,288,711 | MDU6SXNzdWU0NTI4ODcxMQ== | 8,511 | Indexing problem with in-place operator | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-10-08T19:55:26Z | 2014-10-09T13:36:59Z | 2014-10-09T13:36:59Z | CONTRIBUTOR | null | Hi, thanks to all of you who spend time on this project, it is invaluable to me.
Unfortuatnely, i think I have run into an indexing-type issue, either that or my expectations are incorrect. Consider the following script:
``` python
import random
import pandas
import numpy as np
columns = list('abcdefg')
subcols = co... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8512 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8512/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8512/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8512/events | https://github.com/pandas-dev/pandas/pull/8512 | 45,295,789 | MDExOlB1bGxSZXF1ZXN0MjI0NTQwMjU= | 8,512 | BUG: Suppress FutureWarning when comparing object arrays | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8513 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8513/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8513/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8513/events | https://github.com/pandas-dev/pandas/pull/8513 | 45,298,775 | MDExOlB1bGxSZXF1ZXN0MjI0NTU4NTA= | 8,513 | ENH: axvlines - boolean option to parallel_coordinates plot | {
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"followers_url": "https://api.github.com/users/jr... | 12 | 2014-10-08T21:22:27Z | 2015-09-03T15:25:02Z | 2014-12-05T20:16:33Z | CONTRIBUTOR | null | Determines whether vertical lines will be added to parallel_coordinates plot. I was using parallel coordinates to make a seasonality chart - plotting years on top of each other (days/months of year on x-axis). With that many xticks, the vertical lines were overwhelming. It's possible to remove the lines after the fact,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8514 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8514/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8514/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8514/events | https://github.com/pandas-dev/pandas/issues/8514 | 45,299,083 | MDU6SXNzdWU0NTI5OTA4Mw== | 8,514 | pd.option_context without 'with' changes option values | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2014-10-08T21:25:21Z | 2014-11-29T16:48:19Z | 2014-11-29T16:48:19Z | MEMBER | null | Just wondering if this is a bug, from http://stackoverflow.com/questions/26246864/restoring-the-default-display-context-in-pandas
If you use `pd.option_context` accidentally without `with`, this changes the default option values.
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https://api.github.com/repos/pandas-dev/pandas/issues/8515 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8515/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8515/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8515/events | https://github.com/pandas-dev/pandas/issues/8515 | 45,299,689 | MDU6SXNzdWU0NTI5OTY4OQ== | 8,515 | Module xlrd is not installed with 0.14; creates an Import Error when using read_excel | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2014-10-08T21:30:17Z | 2017-09-21T18:15:44Z | 2014-10-08T22:49:43Z | NONE | null | After doing
```
conda create -n dummy_python python=2.7 pandas=0.14 ipython=2.0
```
and then activating dummy_python, I get the following error with a simple .xlsx file that has 3 sheets:
``` python
In [4]: pandas.read_excel('candidate_test.xlsx', sheetname='prices')
-------------------------------------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8516 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8516/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8516/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8516/events | https://github.com/pandas-dev/pandas/issues/8516 | 45,302,834 | MDU6SXNzdWU0NTMwMjgzNA== | 8,516 | add xray to ecosystem docs? | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-10-08T22:00:26Z | 2014-10-10T22:32:42Z | 2014-10-10T22:32:42Z | MEMBER | null | Would it be appropriate to add [xray](https://github.com/xray/xray) to the ecosystem docs?
In brief, the goal of xray is to provide N-dimensional variants of the core pandas data structure (e.g., [as more flexible alternatives to pd.Panel](http://xray.readthedocs.org/en/stable/faq.html)).
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https://api.github.com/repos/pandas-dev/pandas/issues/8517 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8517/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8517/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8517/events | https://github.com/pandas-dev/pandas/issues/8517 | 45,323,733 | MDU6SXNzdWU0NTMyMzczMw== | 8,517 | Feature request: Series.flatmap, DataFrame.flatmap | {
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"de... | closed | false | null | [] | null | 21 | 2014-10-09T03:35:17Z | 2019-05-31T23:45:20Z | 2015-10-20T23:14:36Z | NONE | null | I'm working on some language analysis and using pandas to munge the data and grab some descriptive stats. This is just an illustrative example, I'm doing all kinds of slighty different things.
Suppose I have a series containing chunks of text, and I want to turn the line into multiple lines, preserving the index value... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8518 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8518/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8518/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8518/events | https://github.com/pandas-dev/pandas/issues/8518 | 45,344,939 | MDU6SXNzdWU0NTM0NDkzOQ== | 8,518 | BUG: read_pickle and categorical data | {
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``` python
df = pd.DataFrame({'a':['x','y','x']})
df.to_pickle('/tmp/df.pkl')
pd.read_pickle('/tmp/df.pkl')
df['a'] = df['a'].astype('cate... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8519 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8519/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8519/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8519/events | https://github.com/pandas-dev/pandas/pull/8519 | 45,354,535 | MDExOlB1bGxSZXF1ZXN0MjI0ODYzNjU= | 8,519 | BUG: fix CategoricalBlock pickling | {
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Apparently, `NonConsolidatableMixIn.__init__` was copied from a pre-`BlockPlacement` version of `SparseBlock.__init__` which was incompatible with placement being a slice. The current one is, so I moved it to NonConsolidatableMixIn class almost verbatim.
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https://api.github.com/repos/pandas-dev/pandas/issues/8520 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8520/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8520/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8520/events | https://github.com/pandas-dev/pandas/pull/8520 | 45,358,277 | MDExOlB1bGxSZXF1ZXN0MjI0ODg0NDI= | 8,520 | BUG: Bug in inplace operations with column sub-selections on the lhs (GH8511) | {
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closes #5104
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https://api.github.com/repos/pandas-dev/pandas/issues/8521 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8521/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8521/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8521/events | https://github.com/pandas-dev/pandas/issues/8521 | 45,371,660 | MDU6SXNzdWU0NTM3MTY2MA== | 8,521 | ENH: resample(..., base='start') for automaticly determining base. | {
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"closed_at": "2020-07-28T18:13:47Z",
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```python
import pandas as pd
import datetime as dt
import numpy as np
datetime_start = dt.datetime(2014, 9, 1, 9, 30)
datetime_end = dt.datetime(2014, 9, 1, 16, 0)
tt = pd.date_range(datetime_start, datetime_end, freq='1Min')
df = pd.DataFrame(np.arange(len(tt)), index=tt, columns=['A'])
```
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https://api.github.com/repos/pandas-dev/pandas/issues/8522 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8522/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8522/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8522/events | https://github.com/pandas-dev/pandas/issues/8522 | 45,390,139 | MDU6SXNzdWU0NTM5MDEzOQ== | 8,522 | Error with all boolean indices for Series | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2014-10-09T16:53:56Z | 2014-10-10T08:36:26Z | 2014-10-09T18:32:16Z | NONE | null | The following code works fine with pandas 0.14.1
``` python
import pandas as pd
pd.Series([1, 1], index=[True, False]).drop(True)
```
Output:
``` python
False 1
dtype: int64
```
In pandas 0.15rc1, the code blows up and produces the following error:
```
ValueError Traceback (most r... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8523 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8523/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8523/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8523/events | https://github.com/pandas-dev/pandas/pull/8523 | 45,392,182 | MDExOlB1bGxSZXF1ZXN0MjI1MDg1MDA= | 8,523 | BUG/REGR: bool-like Indexes not properly coercing to object (GH8522) | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-10-09T17:11:37Z | 2014-10-09T18:32:16Z | 2014-10-09T18:32:16Z | CONTRIBUTOR | null | closes #8522
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https://api.github.com/repos/pandas-dev/pandas/issues/8524 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8524/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8524/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8524/events | https://github.com/pandas-dev/pandas/issues/8524 | 45,422,175 | MDU6SXNzdWU0NTQyMjE3NQ== | 8,524 | Klib upgrade (factorizing performance increase) | {
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"f... | 16 | 2014-10-09T21:50:24Z | 2019-10-21T20:06:54Z | null | NONE | null | Hi,
I'm working with two colleagues (@FrancescElies & @JaviBi4) on seeing if we can add groupby to bcolz, what we did first was to see if we can make Pandas' excellent klib implementation more library independent. See https://github.com/CarstVaartjes/khash
A while back khash (https://github.com/attractivechaos/klib) w... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8525 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8525/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8525/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8525/events | https://github.com/pandas-dev/pandas/issues/8525 | 45,433,482 | MDU6SXNzdWU0NTQzMzQ4Mg== | 8,525 | DataFrame throws MemoryError (pandas/lib.c:9308) | {
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```
>>> df2 = pandas.DataFrame(df_data, index=df_ind, columns=df_cols)
python(86000,0x7fff7a7aa310) malloc: *** mach_vm_map(size=200447690256384) failed (error code=3)
*** error: can't allocate region
*** set a breakpoint in malloc_error_break to debug
Tr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8526 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8526/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8526/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8526/events | https://github.com/pandas-dev/pandas/pull/8526 | 45,441,435 | MDExOlB1bGxSZXF1ZXN0MjI1Mzc1NDE= | 8,526 | index into multi-index past the lex-sort depth | {
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"followers_url": "https://api.github.com/users/jr... | 21 | 2014-10-10T02:56:48Z | 2014-11-22T14:47:11Z | 2014-11-21T23:20:24Z | CONTRIBUTOR | null | closes https://github.com/pydata/pandas/issues/7724
closes https://github.com/pydata/pandas/issues/2646
on current master:
```
>>> df
jolia
jim joe jolie joline
1 z 2014-10-14 a 30
y 2014-10-13 b 3
x 2014-10-12 c 15
0 z 2014-10-11 ... | {
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For instance, this code
``` Python
df = pd.read_stata(file)
df['w_age_educ'] = df['w_age'] * df['weduc']
print(df[['... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8528 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8528/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8528/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8528/events | https://github.com/pandas-dev/pandas/issues/8528 | 45,464,941 | MDU6SXNzdWU0NTQ2NDk0MQ== | 8,528 | rot parameter for BARH plots | {
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] | closed | false | null | [] | null | 2 | 2014-10-10T09:58:33Z | 2015-10-20T23:13:01Z | 2015-10-20T23:13:01Z | CONTRIBUTOR | null | when doing dataframe.plot(kind='barh',rot=45), then the labels of the y axis are rotated. Generally rotation is applied to avoid label overlapping, and that's a problem mostly for the x axis.
Should not therefore the keyword apply to the x axis, even though technically the y axis is the "category axis" in this case?
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https://api.github.com/repos/pandas-dev/pandas/issues/8529 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8529/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8529/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8529/events | https://github.com/pandas-dev/pandas/issues/8529 | 45,466,872 | MDU6SXNzdWU0NTQ2Njg3Mg== | 8,529 | fontsize parameter in .plot() | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8530 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8530/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8530/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8530/events | https://github.com/pandas-dev/pandas/issues/8530 | 45,469,005 | MDU6SXNzdWU0NTQ2OTAwNQ== | 8,530 | Series.drop() with boolean index: inconsistent behaviour | {
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When the `label` passed to the `drop` method of a `Series` is not in the index:
(a) if the index is not all booleans then an error is raised
(b) if the index is all booleans and has length > 1 then no error is raised; the original series ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8531 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8531/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8531/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8531/events | https://github.com/pandas-dev/pandas/issues/8531 | 45,471,665 | MDU6SXNzdWU0NTQ3MTY2NQ== | 8,531 | bug in tz_localize when summer/winter time change | {
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Encounter the issue when trying to resample hourly a series.
```
import pandas as pd
from datetime import datetime as dt
import pytz
tz = 'Europe/Berlin'
d = dt(2014,10,26,02,00)
tz = pytz.timezone(tz)
tz.localize(d)
x = pd.Series(0., [d]).ind... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8532 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8532/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8532/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8532/events | https://github.com/pandas-dev/pandas/issues/8532 | 45,490,259 | MDU6SXNzdWU0NTQ5MDI1OQ== | 8,532 | BUG: Series not correctly formatted in truncated output | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2014-10-10T15:05:59Z | 2015-03-17T00:18:39Z | 2015-03-17T00:18:39Z | MEMBER | null | Overview of the issues:
- [ ] Number of rows is incorrect (#7508)
- [ ] Setting `pd.options.display.max_rows` to larger values has no effect (https://github.com/pydata/pandas/issues/7508#issuecomment-58669898)
- [ ] formatting seems to occur seperately for both parts (this issue #8532, see two exaples below)
---
When... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8533 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8533/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8533/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8533/events | https://github.com/pandas-dev/pandas/issues/8533 | 45,495,922 | MDU6SXNzdWU0NTQ5NTkyMg== | 8,533 | Accept SQLAlchemy Connection as con param in pd.read_sql_query() | {
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However, as most (all?) DB servers associate a session with a connection, this preclud... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8534 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8534/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8534/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8534/events | https://github.com/pandas-dev/pandas/pull/8534 | 45,508,188 | MDExOlB1bGxSZXF1ZXN0MjI1NzgyMDA= | 8,534 | Add xray to ecosystem docs | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8535 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8535/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8535/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8535/events | https://github.com/pandas-dev/pandas/pull/8535 | 45,539,292 | MDExOlB1bGxSZXF1ZXN0MjI1OTgzNjY= | 8,535 | DOC: Clean up Sphinx Issues, fix tabs, in Cookbook | {
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Continues to address #6918
Initial PR: https://github.com/pydata/pandas/pull/8288
PS - apologies for wanting to rush the first PR. My eveni... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8536 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8536/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8536/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8536/events | https://github.com/pandas-dev/pandas/pull/8536 | 45,550,121 | MDExOlB1bGxSZXF1ZXN0MjI2MDMyNDA= | 8,536 | BUG: Dont add None to plot legend. | {
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Building the docs now to check that everything looks ok.
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https://api.github.com/repos/pandas-dev/pandas/issues/8537 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8537/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8537/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8537/events | https://github.com/pandas-dev/pandas/issues/8537 | 45,552,907 | MDU6SXNzdWU0NTU1MjkwNw== | 8,537 | Deprecation/FutureWarnings raised by `==` on NumPy arrays in NumPy version1.9 | {
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Summary: NumPy is changing the behavior of `==`. It no longer checks for `is` relationships between elements. Therefore,
In older versions of NumPy:
> > > array([nan], dtype=object) == array([nan], dtype=object)
> > > array([ True], dtype=bool)
In future Num... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8538 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8538/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8538/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8538/events | https://github.com/pandas-dev/pandas/issues/8538 | 45,553,932 | MDU6SXNzdWU0NTU1MzkzMg== | 8,538 | PERF: speed up tshift, possibly by caching offset ops | {
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"f... | 1 | 2014-10-11T15:23:35Z | 2018-07-08T14:32:59Z | 2018-07-06T23:01:49Z | CONTRIBUTOR | null | http://stackoverflow.com/questions/26295861/pandas-tshift-slow-in-groups
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https://api.github.com/repos/pandas-dev/pandas/issues/8539 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8539/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8539/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8539/events | https://github.com/pandas-dev/pandas/issues/8539 | 45,557,346 | MDU6SXNzdWU0NTU1NzM0Ng== | 8,539 | Label slices on Series with MultiIndex | {
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```
In [174]: a
Out[174]:
hour year weekday workingday
0 2011 0 0 count 4.000000
mean 76.750000
std 53.368998
min 17.000... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8540 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8540/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8540/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8540/events | https://github.com/pandas-dev/pandas/issues/8540 | 45,558,559 | MDU6SXNzdWU0NTU1ODU1OQ== | 8,540 | Enhancement: XLSB support in read_excel() | {
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Spec from Microsoft:
http://msdn.microsoft.com/en-us/library/cc313133(v=office.12).aspx
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https://api.github.com/repos/pandas-dev/pandas/issues/8541 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8541/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8541/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8541/events | https://github.com/pandas-dev/pandas/pull/8541 | 45,560,509 | MDExOlB1bGxSZXF1ZXN0MjI2MDc2NDg= | 8,541 | BUG: Plot with ``label`` would overwrite index name | {
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"followers_url": "https://api.github.com/users/jre... | 2 | 2014-10-11T19:51:12Z | 2017-04-05T02:06:11Z | 2014-10-28T03:56:19Z | CONTRIBUTOR | null | Closes https://github.com/pydata/pandas/issues/8494
I took the easy solution and just copied the series.
Alternatively we could attach a label property to the MPLObject, and check that wherever we check the index name.
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https://api.github.com/repos/pandas-dev/pandas/issues/8542 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8542/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8542/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8542/events | https://github.com/pandas-dev/pandas/issues/8542 | 45,563,739 | MDU6SXNzdWU0NTU2MzczOQ== | 8,542 | groupby, TimeGrouper error | {
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```
In [61]: import datetime
In [62]: import pandas as pd
In [63]: df = pd.DataFrame.from_records ( [[datetime.datetime(2014,9,10),1234,"start"],
[datetime.datetime(2013,10,10),1234,"start"]], columns = ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8543 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8543/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8543/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8543/events | https://github.com/pandas-dev/pandas/issues/8543 | 45,566,631 | MDU6SXNzdWU0NTU2NjYzMQ== | 8,543 | PERF: Slowness in multi-level indexes with datetime levels | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2014-10-12T00:59:45Z | 2014-10-13T11:36:56Z | 2014-10-13T11:36:56Z | CONTRIBUTOR | null | A MultiIndex with a DatetimeIndex level is slower than a similar index with numeric levels:
```
lev1 = range(10000)
lev2 = range(100)
mi = pd.MultiIndex.from_product([lev1, lev2])
%time mi.values
```
CPU times: user 571 ms, sys: 41 ms, total: 612 ms
Wall time: 612 ms
```
lev1 = range(10000)
lev2 = pd.date_range('1/1... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2014-10-12T01:56:02Z | 2014-10-13T15:32:55Z | 2014-10-13T11:36:39Z | CONTRIBUTOR | null | Addresses #8543. The benefits are most pronounced when there are a small number of distinct datetimes relative to the number of rows in the index.
vbench results with `-r multi`:
```
-------------------------------------------------------------------------------
Test name | head[ms]... | {
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... | 17 | 2014-10-12T04:37:14Z | 2021-02-03T21:23:26Z | null | CONTRIBUTOR | null | http://pandas.pydata.org/developers.html
- https://mail.python.org/mailman/listinfo/pandas-dev
Examples:
- https://en.wikipedia.org/wiki/Responsible_disclosure
- https://docs.djangoproject.com/en/dev/internals/security/#reporting-security-issues
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... | closed | false | null | [] | null | 5 | 2014-10-13T04:46:47Z | 2014-10-13T11:41:39Z | 2014-10-13T11:39:25Z | NONE | null | ``` python
In [93]: ts= pd.Timestamp(datetime.datetime(2014, 1,1)).tz_localize(
...: 'America/New_York')
...: df=pd.DataFrame([1],index=[ts])
...: df
Out[93]:
0
2014-01-01 00:00:00-05:00 1
In [94]: df.to_excel('/home/yank/2.xls')
TypeError: can't subtract offset-naive and o... | {
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... | 5 | 2014-10-13T08:18:02Z | 2015-05-09T16:07:17Z | 2015-05-09T16:07:17Z | CONTRIBUTOR | null | This should close #8524.
The idea is that quadratic probing `(i**2 + i)/2` is faster than double hashing and can be shown to traverse all elements if `nbuckets == 2**N`.
This branch compiles and passes tests, but I haven't done any benchmarks yet.
## TODO
(probably in other issues)
- [ ] see if the "flag compression... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8548 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8548/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8548/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8548/events | https://github.com/pandas-dev/pandas/pull/8548 | 45,637,126 | MDExOlB1bGxSZXF1ZXN0MjI2NDE3NDc= | 8,548 | BUG: inconsistent and undocumented option "converters" to read_excel | {
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What's still missing is th... | {
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- Move any/all implementations from DataFrame to NDFrame, adding support for Series
- Special case single dimension case in NDFrame, to handle numpy.any/all specific arguments
- Add assorted NotImplementedErrors in cases where arguments are ignored (including in preexisting _reduce functions)
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"followers_url": "https://api.github... | 4 | 2014-10-14T20:31:39Z | 2018-08-14T10:49:11Z | 2018-08-14T10:49:11Z | NONE | null | Subtracting a scalar datetime from a series returns timedeltas, but doesn't do the same for a dataframe.
```
import pandas as pd
series = pd.Series(pd.date_range('2000-1-1', periods=100), index=range(0, 100))
df = pd.DataFrame(series)
date = pd.Timestamp('1995-1-1')
series - date
#0 1826 days ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8555 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8555/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8555/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8555/events | https://github.com/pandas-dev/pandas/issues/8555 | 45,805,647 | MDU6SXNzdWU0NTgwNTY0Nw== | 8,555 | BUG: Index name lost when using .loc with list of indices | {
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Example:
``` python
import pandas as pd
d=pd.DataFrame(
[
[1,2,3],
[4,5,6],
[7,8,9]
],
columns=... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8556 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8556/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8556/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8556/events | https://github.com/pandas-dev/pandas/issues/8556 | 45,816,187 | MDU6SXNzdWU0NTgxNjE4Nw== | 8,556 | DatetimeIndex very slow repr performance | {
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```
dr = pd.date_range('20000101', freq='D', periods=100000)
%time dr._is_dates_only
```
This takes about 500ms on my machine. Scales linearly with the size of the index (I interrupted a repr on a 5mm-length index and discovered this). Probably a go... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8557 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8557/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8557/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8557/events | https://github.com/pandas-dev/pandas/pull/8557 | 45,818,593 | MDExOlB1bGxSZXF1ZXN0MjI3NTQ2ODc= | 8,557 | PERF: fixup datetime_index repr perf (GH8556) | {
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"followers_url": "https://api.github.com/users/jr... | 0 | 2014-10-15T00:56:51Z | 2014-10-15T01:24:00Z | 2014-10-15T01:24:00Z | CONTRIBUTOR | null | closes #8556
low hanging fruit (and now is pretty scale independent).
```
In [1]: dr = pd.date_range('20000101', freq='D', periods=100000)
In [2]: %timeit dr._is_dates_only
10000000 loops, best of 3: 87.6 ns per loop
In [3]: pd.__version__
Out[3]: '0.15.0rc1-38-g857042f'
```
I do recall this slipping in sometime ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8558 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8558/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8558/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8558/events | https://github.com/pandas-dev/pandas/issues/8558 | 45,820,888 | MDU6SXNzdWU0NTgyMDg4OA== | 8,558 | VIS: plot with `use_index=False` shouldn't plot the index name | {
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n [1]: df = pd.Series([1, 2, 3], index=['a', 'b', 'c'])
In [2]: df.index.name = 'The Index'
In [5]: df.plot(use_index=False)
Out[5]: <matplotlib.axes._subplots.AxesSubplot at 0x10b1a1438>
```
The x axis la... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8559 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8559/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8559/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8559/events | https://github.com/pandas-dev/pandas/issues/8559 | 45,836,297 | MDU6SXNzdWU0NTgzNjI5Nw== | 8,559 | Zero counts in Series.value_counts for categoricals | {
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... | 30 | 2014-10-15T07:14:22Z | 2020-09-08T04:13:12Z | 2018-07-06T22:49:02Z | NONE | null | `Series.value_counts()` also shows categories with count 0.
Thought this would be a bug but according to [doc](http://pandas.pydata.org/pandas-docs/version/0.15.0/categorical.html#operations) it is intentional.
This makes the output of value_counts inconsistent when switching between category and non-category dtype. ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8560 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8560/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8560/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8560/events | https://github.com/pandas-dev/pandas/issues/8560 | 45,838,981 | MDU6SXNzdWU0NTgzODk4MQ== | 8,560 | df.query() doesn't follow python truthy-ness? | {
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... | 13 | 2014-10-15T07:55:55Z | 2020-08-13T19:05:50Z | null | NONE | null | ``` python
In [44]: df=pd.DataFrame([[0,10],[1,20]],columns=['cat','count'])
...: df
Out[44]:
cat count
0 0 10
1 1 20
In [45]: df.query('cat')
Out[45]:
cat count
0 0 10
1 1 20
```
Expected the first row where cat==0 to be dropped since 0 is Falsey.
This unhelpful exception i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8561 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8561/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8561/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8561/events | https://github.com/pandas-dev/pandas/pull/8561 | 45,888,881 | MDExOlB1bGxSZXF1ZXN0MjI3OTYwODg= | 8,561 | DOC/FIX: In R it's still levels... | {
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-> one word replacement in the docs
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https://api.github.com/repos/pandas-dev/pandas/issues/8562 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8562/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8562/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8562/events | https://github.com/pandas-dev/pandas/pull/8562 | 45,905,303 | MDExOlB1bGxSZXF1ZXN0MjI4MDY2NjE= | 8,562 | API: Unify SQLTable code for fallback and SQLAlchemy mode and move differences into database class | {
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... | 13 | 2014-10-15T19:03:15Z | 2016-01-20T14:15:53Z | 2016-01-20T14:15:53Z | CONTRIBUTOR | null | In discussion of the SQL API in #7960 , it has been suggested that it may be possible to factor out differences in SQLAlchemy and fallback backend . This is an initial attempt to do so. Now `SQLTable` is uncoupled from the backend. `PandasSQL` is base class for `SQLDatabase` (SQLAlchemy backend) and `SQLiteDatabase`... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8563 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8563/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8563/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8563/events | https://github.com/pandas-dev/pandas/pull/8563 | 45,907,424 | MDExOlB1bGxSZXF1ZXN0MjI4MDgwNjQ= | 8,563 | DOC: fix formatting read_csv comment kwarg explanation | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8564 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8564/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8564/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8564/events | https://github.com/pandas-dev/pandas/pull/8564 | 45,927,499 | MDExOlB1bGxSZXF1ZXN0MjI4MjAyMTM= | 8,564 | ENH: Add type conversion to read_stata and StataReader | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2014-10-15T22:24:29Z | 2014-11-12T15:51:49Z | 2014-10-17T07:22:32Z | CONTRIBUTOR | null | Added upcasting of numeric types which will default numeric data to either
int64 or float64. This option has been enabled by default.
closes #8527
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https://api.github.com/repos/pandas-dev/pandas/issues/8566 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8566/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8566/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8566/events | https://github.com/pandas-dev/pandas/pull/8566 | 45,937,317 | MDExOlB1bGxSZXF1ZXN0MjI4MjY0ODY= | 8,566 | Switch default colormap for scatterplot to 'Greys' | {
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default rainbow colormap (https://github.com/pydata/pandas/pull/7780#issuecomment-49533995).
I'm now regreting choosing 'RdBu' as the default colormap. I think a simple
black-white colormap is a more conservative and better default choice for
co... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8567 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8567/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8567/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8567/events | https://github.com/pandas-dev/pandas/pull/8567 | 45,940,455 | MDExOlB1bGxSZXF1ZXN0MjI4MjgxODM= | 8,567 | DOC: ignore_na warning | {
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] | closed | false | null | [] | null | 1 | 2014-10-16T01:59:17Z | 2014-10-18T12:42:19Z | 2014-10-16T12:49:02Z | CONTRIBUTOR | null | Added a warning about the new default behavior of the `ewm*()` differing from prior versions.
Also cleaned up some formatting.
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https://api.github.com/repos/pandas-dev/pandas/issues/8568 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8568/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8568/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8568/events | https://github.com/pandas-dev/pandas/issues/8568 | 45,985,382 | MDU6SXNzdWU0NTk4NTM4Mg== | 8,568 | df.query doesn't handle negation properly | {
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In [13]: df=pd.DataFrame([[0,10],[1,20]],columns=['cat','count'])
...: df
Out[13]:
cat count
0 0 10
1 1 20
In [14]: df.query('cat > 0')
Out[14]:
cat count
1 1 20
In [15]: df.query('~(cat > 0)')
Out[15]:
cat count
1 1 20
0 0 10
In [16]: df.query(' not ... | {
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```
import pandas as pd
import numpy as np
series = pd.Series(range(0, 10))
series.get(np.nan)
# returns None
series = series.reindex(pd.Float64Index(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8570 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8570/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8570/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8570/events | https://github.com/pandas-dev/pandas/pull/8570 | 46,052,139 | MDExOlB1bGxSZXF1ZXN0MjI4OTczNDQ= | 8,570 | PERF: improve perf of array_equivalent_object (GH8512) | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8571 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8571/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8571/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8571/events | https://github.com/pandas-dev/pandas/issues/8571 | 46,087,406 | MDU6SXNzdWU0NjA4NzQwNg== | 8,571 | API: define __copy__ NDFrame | {
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this allows `copy.copy(df)` to work properly
by definition 'always' deep
```
__copy__ = copy
__deepcopy__ = copy
```
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https://api.github.com/repos/pandas-dev/pandas/issues/8572 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8572/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8572/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8572/events | https://github.com/pandas-dev/pandas/issues/8572 | 46,087,762 | MDU6SXNzdWU0NjA4Nzc2Mg== | 8,572 | DOC/API: document how to use metadata | {
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... | 11 | 2014-10-17T11:04:25Z | 2021-04-11T05:20:00Z | null | CONTRIBUTOR | null | from [SO](http://stackoverflow.com/questions/26421221/propogation-of-metadata-from-dataframe-to-series/26423596#26423596)
xref #2485
xref #7868
- [ ] documentation (maybe in the cookbook) to start.
- [ ] add _metadata to Index
- [ ] top-level metadata control (maybe)
```
def unit_meta(self, other, method=None):
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https://api.github.com/repos/pandas-dev/pandas/issues/8573 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8573/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8573/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8573/events | https://github.com/pandas-dev/pandas/issues/8573 | 46,099,492 | MDU6SXNzdWU0NjA5OTQ5Mg== | 8,573 | Using resample() with groupby on this DataFrame causes Segmentation Fault | {
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I reduced the DataFrame as far as I could in reproducing the crash. Also noted that i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8575 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8575/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8575/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8575/events | https://github.com/pandas-dev/pandas/pull/8575 | 46,122,532 | MDExOlB1bGxSZXF1ZXN0MjI5MzkxOTA= | 8,575 | TST/PERF: optimize tm.makeStringIndex | {
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It also does:
```
* add tm.rands_array(nchars, size) function to generate string arrays
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Closes #7935
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``` python
In [64]: d=pd.DataFrame(["%06d" %x for x in range(1000000)])
...: d.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 1000000 entries, 0 to 999999
Data columns (total 1 columns):
0 1000000 non-null object
dtypes: object(1)
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In [10]: df=pd.DataFrame([range(100)]*100)
...: df.transpose
Out[10]:
<bound method DataFrame.transpose of 0 1 2 3 4 5 6 7 8 9 ... 90 91 92 93 94 95 96 97 98 99
0 0 1 2 3 4 5 6 7 8 9 ... 90 91 92 93 94 95 96 97 98 99
1 0 1 2 3 4 ... | {
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``` python
from pandas.io import gbq
```
gives the following error:
``` python
>>> from pandas.io import gbq
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python2.7/site-packages/pandas/__init__.py", line 45, in <module>
from pandas.io.api import *
File ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8582 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8582/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8582/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8582/events | https://github.com/pandas-dev/pandas/issues/8582 | 46,208,111 | MDU6SXNzdWU0NjIwODExMQ== | 8,582 | groupby with as_index=False, inconsistency between max and idxmax | {
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>>> df = pd.DataFrame(np.random.randint(0, 100, (50, 2)), columns=['jim', 'joe'])
>>> ts = pd.Series(np.random.randint(0, 3, 50))
>>> df.groupby(ts, as_index=False).idxmax()
jim joe
0 25 36
1 22 5
2 3 4
>>> df.groupby(ts, as_index=False).max()
NaN jim joe
0 0 93 94
1 1 94 89
2 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8583 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8583/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8583/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8583/events | https://github.com/pandas-dev/pandas/pull/8583 | 46,216,639 | MDExOlB1bGxSZXF1ZXN0MjI5ODUzMjc= | 8,583 | DOC/REL: adapt make.py file to upload with other user than pandas | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8584 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8584/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8584/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8584/events | https://github.com/pandas-dev/pandas/issues/8584 | 46,217,212 | MDU6SXNzdWU0NjIxNzIxMg== | 8,584 | BUG: Passing multiple levels to stack when having mixed integer/string level names | {
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Using the example of the docs (http://pandas.pydata.org/pandas-docs/stable/reshaping.html#multiple-levels):
```
columns = MultiIndex.from_tuples([('A', 'cat', 'long'), ('B', 'cat', 'long'), ('A', 'dog', 'short'), ('B', 'dog', 'short')],
names=['exp', 'animal', 'hair_le... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8585 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8585/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8585/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8585/events | https://github.com/pandas-dev/pandas/pull/8585 | 46,217,313 | MDExOlB1bGxSZXF1ZXN0MjI5ODU2MTU= | 8,585 | BUG: column name conflict & as_index=False breaks groupby ops | {
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"followers_url": "https://api.github.com/users/jre... | 11 | 2014-10-19T21:00:29Z | 2014-12-07T13:23:35Z | 2014-10-28T00:04:25Z | CONTRIBUTOR | null | closes https://github.com/pydata/pandas/issues/7115
closes https://github.com/pydata/pandas/issues/8112
closes https://github.com/pydata/pandas/issues/8582
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https://api.github.com/repos/pandas-dev/pandas/issues/8586 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8586/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8586/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8586/events | https://github.com/pandas-dev/pandas/pull/8586 | 46,217,451 | MDExOlB1bGxSZXF1ZXN0MjI5ODU2ODU= | 8,586 | DOC/REL: clean-up and restructure v0.15.0 whatsnew file (GH8477) | {
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What did I change:
- some general clean-up (blank lines, ..)
- put the different new feature sections in front (as also in the highlights section)
- the 2-level menu structure as discussed in #8477
- API section: move some entries to the 'enhancements' section (entries that were not 'real' (in sense of ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8587 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8587/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8587/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8587/events | https://github.com/pandas-dev/pandas/pull/8587 | 46,223,425 | MDExOlB1bGxSZXF1ZXN0MjI5ODg2MTM= | 8,587 | BUG: LooseVersion was used incorrectly | {
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"followers_url": "https://api.github.com/users/jre... | 6 | 2014-10-20T00:50:35Z | 2014-10-30T11:20:23Z | 2014-10-20T12:23:30Z | CONTRIBUTOR | null | closes #8581
Version comparison had a formatting error resulting in "TypeError: expected string or buffer" and preventing Spyder from loading (and probably other issues). Fixed.
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https://api.github.com/repos/pandas-dev/pandas/issues/8588 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8588/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8588/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8588/events | https://github.com/pandas-dev/pandas/issues/8588 | 46,264,362 | MDU6SXNzdWU0NjI2NDM2Mg== | 8,588 | DOC/API: clarify groupby sorting behavior | {
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from [SO](http://stackoverflow.com/questions/26456125/python-pandas-is-order-preserved-when-using-groupby-and-agg/26465555#26465555resample forces a sort)
groupby only sorts if sort is True and the index is NOT monotonic.
just like ... | {
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"followers_url": "https://api.github.com/users/jre... | 2 | 2014-10-20T17:20:06Z | 2014-10-30T11:19:44Z | 2014-10-24T18:36:38Z | CONTRIBUTOR | null | Works in 0.14.1:
``` python
In [11]: s = pd.Series(np.random.randn(100))
In [12]: pd.cut(s, 10, retbins=True)
Out[12]:
( (0.993, 1.376]
(-0.924, -0.541]
(-0.158, 0.226]
(-1.695, -1.308]
(-0.924, -0.541]
(-0.541, -0.158]
(-0.158, 0.226]
(-0.541, -0.158]
(0.609, 0.993]
(0.226, 0.609]
(0.2... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8590 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8590/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8590/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8590/events | https://github.com/pandas-dev/pandas/pull/8590 | 46,344,205 | MDExOlB1bGxSZXF1ZXN0MjMwNTY1ODA= | 8,590 | ENH: improve bigquery connector to optionally allow use of gcloud credentials | {
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... | 42 | 2014-10-21T01:06:54Z | 2015-05-14T15:52:50Z | 2015-05-09T16:08:56Z | NONE | null | closes #8489
The pandas google bigquery connector can be difficult to use from an ipython notebook: when no authentication token exists, it fails silently (and can hang the notebook). This happens because the oauth2client library is trying to bring up a browser on the console, to request an auth token.
This PR pro... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8591 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8591/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8591/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8591/events | https://github.com/pandas-dev/pandas/issues/8591 | 46,344,467 | MDU6SXNzdWU0NjM0NDQ2Nw== | 8,591 | Pandas 15.0: TypeError: can't pickle busdaycalendar objects | {
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"id": ... | closed | false | null | [] | {
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``` python
import pandas as pd
import numpy as np
from pandas.tseries.offsets import CustomBusinessDay
from datetime import datetime
week... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8592 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8592/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8592/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8592/events | https://github.com/pandas-dev/pandas/pull/8592 | 46,350,432 | MDExOlB1bGxSZXF1ZXN0MjMwNjAxODM= | 8,592 | ENH: Raise error in certain unhandled _reduce cases. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8593 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8593/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8593/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8593/events | https://github.com/pandas-dev/pandas/issues/8593 | 46,384,736 | MDU6SXNzdWU0NjM4NDczNg== | 8,593 | API: specification of functions in .agg | {
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"description": "Apply, A... | open | false | null | [] | null | 2 | 2014-10-21T11:57:10Z | 2021-04-11T05:21:06Z | null | CONTRIBUTOR | null | - [ ] `pd.Summary`
- [x] dict-of-dict #9052
- [ ] named functions #10100
From [SO](http://stackoverflow.com/questions/26456125/python-pandas-is-order-preserved-when-using-groupby-and-agg/26465555?noredirect=1#comment41593401_26465555)
```
In [100]: df = pd.DataFrame({'A': ['group1', 'group1', 'group2', 'group2', 'gr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8594 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8594/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8594/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8594/events | https://github.com/pandas-dev/pandas/issues/8594 | 46,387,298 | MDU6SXNzdWU0NjM4NzI5OA== | 8,594 | Series.drop() with MultiIndex: inconsistent behaviour | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2014-10-21T12:28:00Z | 2019-12-26T13:35:09Z | 2019-12-26T13:35:09Z | NONE | null | The behaviour below occurs in versions `'0.15.0rc1-21-g32c5016'` and `'0.14.1'`.
When the `label` passed to the `drop` method of a `Series` is not in the axis:
(a) if the index is not a `MultiIndex` then an exception is raised (in most cases; see issue #8530)
(b) if the index is a `MultiIndex` then an exception is not... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8595 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8595/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8595/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8595/events | https://github.com/pandas-dev/pandas/issues/8595 | 46,392,842 | MDU6SXNzdWU0NjM5Mjg0Mg== | 8,595 | API: cut interval formatting | {
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... | 11 | 2014-10-21T13:26:30Z | 2018-07-06T22:19:16Z | 2018-07-06T22:19:16Z | NONE | null | it would be nice to have number in front of all labels. put number like 00, 01, 02 in front of labels so that it would order appropriately.
Lib\site-packages\pandas\tools\tile.py
```
def _format_levels(bins, prec, right=True,
include_lowest=False):
fmt = lambda v: _format_label(v, precision=pre... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8596 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8596/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8596/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8596/events | https://github.com/pandas-dev/pandas/issues/8596 | 46,428,546 | MDU6SXNzdWU0NjQyODU0Ng== | 8,596 | BUG: DataFrame outer merge changes key columns from int64 to float64 | {
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... | 18 | 2014-10-21T18:38:30Z | 2020-03-15T11:20:13Z | 2016-05-27T12:41:32Z | CONTRIBUTOR | null | ```
import pandas as pd
df1 = pd.DataFrame({'key': [1,2,3,4], 'val1': [1,2,3,4]})
df2 = pd.DataFrame({'key': [1,2,3,5], 'val2': [1,2,3,4]})
df = df1.merge(df2, how='outer')
```
Was expecting `key` to stay int64, since a merge can't introduce missing key values if none were present in the inputs.
```
print df.dtypes... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8597 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8597/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8597/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8597/events | https://github.com/pandas-dev/pandas/issues/8597 | 46,436,496 | MDU6SXNzdWU0NjQzNjQ5Ng== | 8,597 | Functions should raise on unexpected keyword arguments in **kwargs | {
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"f... | 3 | 2014-10-21T19:50:20Z | 2018-07-08T14:33:28Z | 2018-07-06T22:16:18Z | CONTRIBUTOR | null | A lot of functions in pandas ignore any additional keyword arguments in `**kwargs`. This makes it very easy for unnoticed mistakes in the code, without getting any error; I have personally came across both cases below in my code:
```
>>> def foo(df):
... df.drop('joe', axis=1, inplce=True) # mis-spelling a keywor... | {
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"followers_url": "https://api.github.com/users/jre... | 1 | 2014-10-21T21:40:19Z | 2014-10-30T11:20:23Z | 2014-10-21T23:20:26Z | CONTRIBUTOR | null | The pointer to `read_sql_query` is not specified correctly in `doc/source/io.rst` .
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https://api.github.com/repos/pandas-dev/pandas/issues/8599 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8599/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8599/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8599/events | https://github.com/pandas-dev/pandas/pull/8599 | 46,480,802 | MDExOlB1bGxSZXF1ZXN0MjMxMzk1MTk= | 8,599 | Use '+' to qualify memory usage in df.info() if appropriate | {
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https://api.github.com/repos/pandas-dev/pandas/issues/8600 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/8600/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/8600/comments | https://api.github.com/repos/pandas-dev/pandas/issues/8600/events | https://github.com/pandas-dev/pandas/issues/8600 | 46,496,880 | MDU6SXNzdWU0NjQ5Njg4MA== | 8,600 | API/PERF: add a performance string-object memory computation | {
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... | 1 | 2014-10-22T10:57:00Z | 2021-04-11T05:22:09Z | 2021-04-11T05:22:09Z | CONTRIBUTOR | null | xref #8599, #8578
allow a nice UX and a more correct estimate of memory usage for object (string) columns
prob will require a cythonized evaluation
this would replace the need for the '+' on object dtypes for mem usage
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