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https://api.github.com/repos/pandas-dev/pandas/issues/10503 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10503/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10503/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10503/events | https://github.com/pandas-dev/pandas/issues/10503 | 92,902,147 | MDU6SXNzdWU5MjkwMjE0Nw== | 10,503 | Simple operation unexpectedly changes dtype | {
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I can't find any documentation that says this should happen, so I think it's a bug. But maybe something's happening that I don't understand. When I do a simple operation (adding 1 to a slice), suddenly the dtype of the columns changes from uint32 to int64.
Any ideas why this is happening? Bug?
Thanks
Make a sa... | {
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Not sure if the feature is the one mentioned in the link below. It's called groupsort.
http://wesmckinney.com/blog/tag/pandas/
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```
df = pd.DataFrame({'A': [1, 2, 3 ,4], 'B': [5, 6, 7, 8]})
# OK
df.groupby(pd.Categorical(['A', 'B', 'A', 'B'])).groups
# {'A': [0, 2], 'B': [1, 3]}
# OK
df.groupby(pd.Categorical(['A', 'B', 'A', 'B']), sort=False).groups
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-07-04T00:01:37Z | 2016-05-06T07:38:12Z | 2015-07-06T12:01:50Z | CONTRIBUTOR | null | See PR below. Includes tests and release doc edits.
https://github.com/pydata/pandas/pull/10384
I'm just having a little problem with merging a simple two line conflict. I'm in the process of learning, so be gentle =P
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The fix also did some refactoring related to `assert_index_equal`. Added `check_exact` and `check_less_precise`, and moved logics from `assert_series_equal` and `assert_frame_equal` for cleanups.
Followings are the list of tested and what the output looks like
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https://api.github.com/repos/pandas-dev/pandas/issues/10510 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10510/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10510/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10510/events | https://github.com/pandas-dev/pandas/issues/10510 | 93,011,846 | MDU6SXNzdWU5MzAxMTg0Ng== | 10,510 | Installation problem on FreeBSD 10.0 with Python 3.4.3 | {
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I'm attempting to install pandas in a virtualenv on a FreeBSD system with Python 3.4.3. I can't see that I'm missing any obvious steps or dependancies. I get an error in a C module when importing pandas if I install pandas from pip, from a release tarball and with the repo (same error every time) that would imply ... | {
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1. Add a new column whose values at each cell is a python list of the ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10512 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10512/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10512/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10512/events | https://github.com/pandas-dev/pandas/pull/10512 | 93,057,040 | MDExOlB1bGxSZXF1ZXN0MzkyMTQxNjI= | 10,512 | TST: Deprecate assert_numpy_array_equivalent | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10513 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10513/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10513/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10513/events | https://github.com/pandas-dev/pandas/pull/10513 | 93,156,476 | MDExOlB1bGxSZXF1ZXN0MzkyMjg3NTg= | 10,513 | BUG: display.precision options seems off-by-one (GH10451) | {
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I made a call here in response to my questions on #10451 and hopefully people like it. I made it clear that "precision" refers to places after the decimal, not significant figures, and changed the default value to match so that for many pandas users no change would be detected. I updated the Options doc... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10514 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10514/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10514/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10514/events | https://github.com/pandas-dev/pandas/issues/10514 | 93,239,499 | MDU6SXNzdWU5MzIzOTQ5OQ== | 10,514 | DataFrame constructor ignores key order when data is an OrderedDict and orient is 'columns' | {
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I had look at this and found the error is in index.py line 5746 on pandas 0.16.2:
```
def _union_indexes(indexes):
if len(indexes) == 0:
raise AssertionError('Must h... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10515 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10515/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10515/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10515/events | https://github.com/pandas-dev/pandas/issues/10515 | 93,245,774 | MDU6SXNzdWU5MzI0NTc3NA== | 10,515 | read_csv should present the column name/index in case 'Integer column has NA values' exception | {
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```
---------------------------------------------------------------------------
Exception Traceback (most recent call last)
<ipython-input-21-06190a246c08> in <module>()
2 d3_df = pd.read_csv(d3_file, sep='|', skipinitialspace=True, header=None,
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https://api.github.com/repos/pandas-dev/pandas/issues/10516 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10516/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10516/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10516/events | https://github.com/pandas-dev/pandas/pull/10516 | 93,257,845 | MDExOlB1bGxSZXF1ZXN0MzkyNTg4ODQ= | 10,516 | Read Stata version 118 files closes #9882 | {
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This extends the Stata reader to handle version 118 (stata 14) format files.
It correctly handles the test file posted by @makmanalp. I don't have stata14 now to generate additional test files, but I'm not sure that it's necessary.
There is one point I'm not sure about, relating to the way that strls ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10517 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10517/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10517/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10517/events | https://github.com/pandas-dev/pandas/issues/10517 | 93,335,702 | MDU6SXNzdWU5MzMzNTcwMg== | 10,517 | Explore use of ReadStat for binary format read/write | {
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"f... | 2 | 2015-07-06T17:46:15Z | 2020-12-06T22:11:18Z | 2019-12-22T16:56:11Z | CONTRIBUTOR | null | As mentioned in #4052. [ReadStat](https://github.com/WizardMac/ReadStat) is an MIT-licensed C library for reading and writing R, SAS, Stata, and SPSS binary files. [Haven](https://github.com/hadley/haven) uses it.
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https://api.github.com/repos/pandas-dev/pandas/issues/10518 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10518/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10518/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10518/events | https://github.com/pandas-dev/pandas/pull/10518 | 93,343,371 | MDExOlB1bGxSZXF1ZXN0MzkyOTYyNjg= | 10,518 | DOC: Clarified PyTables "natural" names | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-07-06T18:27:37Z | 2015-07-07T15:53:59Z | 2015-07-07T15:53:55Z | CONTRIBUTOR | null | The HDF5 documentation "Notes & Caveats" defines a PyTables NaturalNameWarning vaguely, and incorrectly states that a natural name may not begin with an underscore. I clarified the definition of a natural identifier. The relevant regex is defined [here](https://github.com/PyTables/PyTables/blob/2fde39957c7b5263dd4d0b11... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10519 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10519/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10519/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10519/events | https://github.com/pandas-dev/pandas/issues/10519 | 93,361,508 | MDU6SXNzdWU5MzM2MTUwOA== | 10,519 | GroupBy.apply calling function twice | {
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"followers_url": "https://api.github.com/users/j... | 6 | 2015-07-06T19:44:22Z | 2019-01-26T15:19:38Z | 2015-07-06T20:19:07Z | CONTRIBUTOR | null | ``` python
def foo(x):
print "hello"
_ = pd.DataFrame({'a':[1]}).groupby(["a"]).apply(foo)
```
```
hello
hello
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10520 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10520/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10520/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10520/events | https://github.com/pandas-dev/pandas/pull/10520 | 93,379,069 | MDExOlB1bGxSZXF1ZXN0MzkzMTE2Mjc= | 10,520 | Fix and tests for issue #10154 inconsistent behavior with invalid dates | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-07-06T21:15:58Z | 2015-07-07T10:19:46Z | 2015-07-07T10:19:46Z | CONTRIBUTOR | null | closes #10154
This addresses the original issue and another discovered with the test cases.
Please review the tests to be sure you agree with the assertions.
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https://api.github.com/repos/pandas-dev/pandas/issues/10521 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10521/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10521/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10521/events | https://github.com/pandas-dev/pandas/issues/10521 | 93,396,762 | MDU6SXNzdWU5MzM5Njc2Mg== | 10,521 | BUG: inconsisten multi-level indexing when levels are dropped | {
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},
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"color": "0b02e1",
"default": false,
"description": "Related to indexing on s... | closed | false | null | [] | {
"closed_at": "2021-07-02T07:59:17Z",
"closed_issues": 2396,
"created_at": "2020-11-11T19:05:43Z",
"creator": {
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"followers_url": "https://api.github.com/users/j... | 5 | 2015-07-06T22:58:51Z | 2020-12-30T13:50:13Z | 2020-12-30T13:50:13Z | NONE | null | `DF.loc['A', :, 1]` returns a DataFrame with the full MultiIndex if the second level has more than one entry, and a truncated index if the second level has only one entry (same as, e.g., `DF.loc['A',0,1]`). Is this the intended behavior?
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https://api.github.com/repos/pandas-dev/pandas/issues/10522 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10522/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10522/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10522/events | https://github.com/pandas-dev/pandas/issues/10522 | 93,465,599 | MDU6SXNzdWU5MzQ2NTU5OQ== | 10,522 | sort seems to sort inplace by default unlike documentation | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2015-07-07T07:57:57Z | 2015-07-07T11:23:26Z | 2015-07-07T09:28:41Z | CONTRIBUTOR | null | Hello,
I noticed
```
df_ohlc['high'].sort(ascending=False)
```
raises
```
ValueError: This Series is a view of some other array, to sort in-place you must create a copy
```
which seems to mean that, by default, sort uses by default `inplace=True`
but according to
http://pandas.pydata.org/pandas-docs/stable/gener... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10523 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10523/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10523/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10523/events | https://github.com/pandas-dev/pandas/issues/10523 | 93,534,969 | MDU6SXNzdWU5MzUzNDk2OQ== | 10,523 | Reading from Excel mangles columns | {
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"description": "read_exc... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jorisva... | 6 | 2015-07-07T13:52:27Z | 2021-01-06T09:18:38Z | 2018-11-13T22:36:42Z | NONE | null | As far as I can tell, both methods of reading an Excel sheet (through ExcelFile and read_excel) do not have the option to avoid mangling duplicate columns, which exists for read_csv (https://github.com/pydata/pandas/issues/3468).
I have an Excel file that looks like this:
```
foo foo bar bar baz baz
A B... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10524 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10524/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10524/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10524/events | https://github.com/pandas-dev/pandas/issues/10524 | 93,594,161 | MDU6SXNzdWU5MzU5NDE2MQ== | 10,524 | Inconsistent handling of variables with missing values in groupby | {
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``` python
df = pd.DataFrame(dict(a=["a", "a", "a", "b", "b", "b"],
x=[True, True, False, True, np.nan, False]))
```
This works fine:
``` python
df.x.mean()
0.59999999999999998
```
But this fails:
``` python
df.groupby("a").x.mean()
--------------------------... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10525 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10525/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10525/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10525/events | https://github.com/pandas-dev/pandas/pull/10525 | 93,599,313 | MDExOlB1bGxSZXF1ZXN0Mzk0MDIzMzY= | 10,525 | Fix a typo 'does' -> 'do' | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10526 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10526/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10526/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10526/events | https://github.com/pandas-dev/pandas/issues/10526 | 93,609,154 | MDU6SXNzdWU5MzYwOTE1NA== | 10,526 | read_json from url, Accept Header? | {
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and only delivers json if this tag is higher ranked than 'text/html'.
See: [Flask: Handling Accept Headers](http://flask.pocoo.org/snippets/45/)
It seems, that the pandas request in '_url_open' has no such header at all.
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10527 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10527/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10527/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10527/events | https://github.com/pandas-dev/pandas/pull/10527 | 93,687,621 | MDExOlB1bGxSZXF1ZXN0Mzk0Mzk4MzY= | 10,527 | BUG: GH9618 in read_msgpack where DataFrame has duplicate column names | {
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"followers_url": "https://api.github.com/users/jr... | 10 | 2015-07-08T04:04:17Z | 2015-07-18T13:30:47Z | 2015-07-18T13:30:43Z | CONTRIBUTOR | null | To close #9618
Note I modified `encode`, so it's not backward compatible.
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https://api.github.com/repos/pandas-dev/pandas/issues/10528 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10528/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10528/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10528/events | https://github.com/pandas-dev/pandas/issues/10528 | 93,705,212 | MDU6SXNzdWU5MzcwNTIxMg== | 10,528 | Series.dt.tz_localize() changes the dtype to object | {
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"followers_url": "https://api.github.com/users/jorisva... | 2 | 2015-07-08T06:06:14Z | 2015-07-08T09:29:06Z | 2015-07-08T09:29:06Z | NONE | null | ```
import pandas as pd
index = pd.date_range("2015-01-01", "2015-10-1", freq="W-SUN")
s = pd.Series(index)
print index.dtype
print s.dtype
print index.tz_localize("utc").dtype
print s.dt.tz_localize("utc").dtype
```
here is the output:
```
datetime64[ns]
datetime64[ns]
datetime64[ns]
object
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10529 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10529/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10529/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10529/events | https://github.com/pandas-dev/pandas/pull/10529 | 93,770,462 | MDExOlB1bGxSZXF1ZXN0Mzk0Njg2OTA= | 10,529 | BUG : read_csv() twice decodes stream on URL file #10424 | {
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... | 3 | 2015-07-08T11:53:41Z | 2015-10-25T15:29:19Z | 2015-10-25T15:29:12Z | NONE | null | As described in #10424 , reading non-utf-8 csv files from URL leads to decoding problems, i.e. a decoding may first be made in io.common.get_filepath_or_buffer() when file is URL.
Modification done makes this function read stream from URL without decoding (this is done later, at the same place as for local files).
It'... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10530 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10530/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10530/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10530/events | https://github.com/pandas-dev/pandas/issues/10530 | 93,832,061 | MDU6SXNzdWU5MzgzMjA2MQ== | 10,530 | BUG: 'base' argument when resampling TimedelataIndex has no effect | {
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"description": "Timedelt... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-07-08T16:20:46Z | 2018-09-27T13:46:13Z | 2015-08-15T22:41:03Z | CONTRIBUTOR | null | ``` python
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.normal(size=(100,4)))
df.index = pd.timedelta_range(start='0s', periods=100, freq='s')
print df.resample('10s',base=5)
```
The resampled index is still aligned to 0.
The base argument seems to never be used, it doesn't raise any error when... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10531 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10531/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10531/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10531/events | https://github.com/pandas-dev/pandas/issues/10531 | 93,857,728 | MDU6SXNzdWU5Mzg1NzcyOA== | 10,531 | get_dummies(df,sparse=True) does not return sparse DataFrame | {
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``` python
In [216]: pd.version.version
Out[216]: '0.16.2'
In [217]: df = pd.DataFrame(np.random.randint(10,size=(10000,5)),columns=list('abcde'))
In [218]: df.head()
Out[218]:
a b c d e
0 2 6 1 4 0
1 5 2 6 8 5
2 0 8 7 3 1
3 9 2 6 3 1
4... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10532 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10532/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10532/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10532/events | https://github.com/pandas-dev/pandas/issues/10532 | 93,972,466 | MDU6SXNzdWU5Mzk3MjQ2Ng== | 10,532 | Merging issue | {
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sharesdb:
```
PARTICIPANTNAME 2015-06-28
```
0 THE HONGKONG AND SHANGHAI BANKING 765945421
1 THE HONGKONG AND SHANGHAI BANKING 398945696
tmpdb:
```
PARTICIPANTNAME 2015-06-29
```
0 THE HONGKONG AND SHAN... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10533 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10533/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10533/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10533/events | https://github.com/pandas-dev/pandas/issues/10533 | 94,009,113 | MDU6SXNzdWU5NDAwOTExMw== | 10,533 | New feature: support timedelta as limit when using interpolate method=time | {
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"description": "np.nan, ... | open | false | null | [] | null | 1 | 2015-07-09T10:14:49Z | 2021-04-18T07:14:55Z | null | CONTRIBUTOR | null | When we call the interpolate function based on time, it would be useful to be able to give a limit expressed as a timedelta (instead of a number of row).
Use case
- I've a time series measurement of temperature in function of time. The measurements are not performed at a constant frequency
- I want to interpolate miss... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10534 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10534/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10534/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10534/events | https://github.com/pandas-dev/pandas/issues/10534 | 94,068,865 | MDU6SXNzdWU5NDA2ODg2NQ== | 10,534 | No way to force read numerics as string in `read_html ` | {
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Options to read them as string?
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https://api.github.com/repos/pandas-dev/pandas/issues/10535 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10535/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10535/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10535/events | https://github.com/pandas-dev/pandas/pull/10535 | 94,116,416 | MDExOlB1bGxSZXF1ZXN0Mzk2MTIwMjI= | 10,535 | BUG: get_dummies not returning SparseDataFrame | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10536 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10536/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10536/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10536/events | https://github.com/pandas-dev/pandas/issues/10536 | 94,116,779 | MDU6SXNzdWU5NDExNjc3OQ== | 10,536 | Concat does not work for sparse series | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-07-09T18:16:36Z | 2016-04-18T19:55:34Z | 2016-04-18T19:55:34Z | CONTRIBUTOR | null | Concatenating two sparse series does not return sparse data structures as expected:
```
In [1]: import pandas as pd
In [2]: ts = pd.Series([0, 1, 1, 2, 3, 0 ,0 ,0])
In [3]: sts = ts.to_sparse()
In [4]: print type(pd.concat([sts, sts], axis=0))
<class 'pandas.core.series.Series'>
In [5]: print type(pd.concat([sts, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10537 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10537/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10537/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10537/events | https://github.com/pandas-dev/pandas/issues/10537 | 94,126,777 | MDU6SXNzdWU5NDEyNjc3Nw== | 10,537 | BUG: Inconsistent date parsing of month/year | {
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>>> pd.Timestamp('2014-06')
Timestamp('2014-06-01 00:00:00')
>>> pd.Timestamp('06-2014')
Timestamp('2014-06-09 00:00:00')
```
When parsing a string "YYYY-MM", the day defaults to the 1st of the month (the behavior I would expect, consistent with defaulting hour minute and second to 0), while "MM-YYYY" defaults the... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10538 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10538/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10538/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10538/events | https://github.com/pandas-dev/pandas/issues/10538 | 94,168,943 | MDU6SXNzdWU5NDE2ODk0Mw== | 10,538 | Merging Index on Column Output Behavior | {
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"de... | closed | false | null | [] | null | 6 | 2015-07-09T22:43:39Z | 2015-08-20T13:05:10Z | 2015-08-20T13:05:10Z | NONE | null | Merging two data frames, the first using the index, and the second using a column,with a left join has an unusual behavior. Logically, the merged Dataframe should keep the index column, and discard the right Dataframe's join column(a right join logically has the reverse argument). Here is an illustrative example:
``... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10539 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10539/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10539/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10539/events | https://github.com/pandas-dev/pandas/issues/10539 | 94,176,941 | MDU6SXNzdWU5NDE3Njk0MQ== | 10,539 | BUG: DataFrame.shift(axis=1) with multiple blocks of same type | {
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... | 6 | 2015-07-09T23:45:37Z | 2020-09-26T22:59:04Z | 2020-09-26T22:59:04Z | CONTRIBUTOR | null | Shows up whenver you have multiple blocks of the same type in a dataframe.
Int example:
```
In [1]: a = pd.Series([1,2,3])
In [2]: b = pd.Series([4,5,6])
In [3]: df1 = pd.DataFrame({'a': a, 'b': b})
In [4]: df2 = pd.DataFrame({'a': a}).assign(b=b)
In [5]: df1._data.blocks
Out[5]: (IntBlock: slice(0, 2, 1), 2 x 3,... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10540 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10540/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10540/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10540/events | https://github.com/pandas-dev/pandas/issues/10540 | 94,179,669 | MDU6SXNzdWU5NDE3OTY2OQ== | 10,540 | ENH: drop_duplicates(consecutive=True) to drop only consecutive duplicates | {
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... | 5 | 2015-07-10T00:11:38Z | 2020-08-11T11:14:03Z | null | CONTRIBUTOR | null | DataFrame.drop_duplicates can be useful to 'sparsify' a frame, requiring less
memory/storage. However, it doesn't handle the case where a value later reverts
to an earlier value. For example:
```
In [2]: df = pd.DataFrame(index=pd.date_range('20020101', periods=5, freq='D'),
data={'poll_supp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10541 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10541/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10541/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10541/events | https://github.com/pandas-dev/pandas/pull/10541 | 94,201,112 | MDExOlB1bGxSZXF1ZXN0Mzk2NDgyNjM= | 10,541 | ENH: Update exception message to resolve #10515 | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-07-10T02:57:13Z | 2015-07-10T12:57:14Z | 2015-07-10T12:57:06Z | CONTRIBUTOR | null | Made a quick change to the `Exception` raised in `_convert_with_dtype` per the issue raised in #10515.
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https://api.github.com/repos/pandas-dev/pandas/issues/10542 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10542/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10542/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10542/events | https://github.com/pandas-dev/pandas/pull/10542 | 94,381,536 | MDExOlB1bGxSZXF1ZXN0Mzk3MTk0MTM= | 10,542 | CLN: cleanup up platform / python version checks. fix GB10151 | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-07-10T20:04:16Z | 2015-07-11T20:07:32Z | 2015-07-11T16:47:31Z | CONTRIBUTOR | null | Notes:
- I did not use `is_platform_xxx` on `pandas/util/clipboard.py` because this module is a fork. So I guess better not deviate from the original, right?
- I added the helper `_skip_if_windows` function in `pandas/util/testing.py`, I added an underscore before `skip` to maintain consistency with other `skip` functi... | {
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I'm not 100% sure that I implemented this per the documentation or that my tests are complete but I'd be glad to make any necessary changes.
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"color": "005... | closed | false | null | [] | null | 1 | 2015-07-11T08:22:44Z | 2015-07-11T13:08:36Z | 2015-07-11T13:08:36Z | CONTRIBUTOR | null | Creating an empty Series with `dtype` as a string-type results in an instance with `dtype=object`.
``` python
import pandas as pd
dtype = 'S1' ... | {
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``` py
In [1]: import pandas as pd
In [2]: class Subclassed(pd.Series):
...: pass
...:
In [3]: type(Subclassed(range(10)))
Out[3]: __main__.Subclassed
In [4]: type(Subclassed(range(10)) + Subclassed(range(10)))
Out[4]: ... | {
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import pandas as pd
# scalar (OK)
s = 1
pd.eval('s', engine='numexpr')
# 1L
pd.eval('s', engine='python')
#1
# array
a = np.array([1])
# OK
pd.eval('a', engine='python')
# array([1])
# NG
pd.eval('a', engine='numexpr')
# 1L
```
Internally, we can distinguish them using returned shape.
```
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-07-11T15:28:16Z | 2015-08-14T18:40:52Z | 2015-08-14T18:40:52Z | CONTRIBUTOR | null | When a `Series` is of length one, I would expect `iloc[[-1]]` to produce the same result as `iloc[[0]]`. However `iloc[[-1]]` produces an error, even though `iloc[[0]]` and `iloc[-1]` work.
```
In [178]: import pandas as pd
In [179]: pd.Series(['a', 'b'], index=['A', 'B']).iloc[[-1]]
Out[179]:
B b
dtype: object
... | {
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Reading this file produces the expected behavior:
```
1,2,3
3,8,3
#comment
5,5,5
```
```
In [52]: pandas.read_csv('commentBugTest.csv',comment='#')
Out[52]:
1 2 3
0 3 8 3
1 5 5 5
```
However, if the last line in the file is a comment, you get unexpected NaNs:
```
1,2,3
3,8,3
#comment
```
``... | {
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... | 7 | 2015-07-11T20:12:55Z | 2021-11-15T19:03:25Z | null | NONE | null | So here's my setup (using pandas 0.16.2):
``` python
>>> midx = pd.MultiIndex.from_product([['bar', 'baz', 'foo', 'qux'], ['one', 'two']],names=['first','second'])
>>> df = pd.DataFrame(np.random.randint(10,size=(8,8)),index=midx)
>>> df
0 1 2 3 4 5 6 7
first second
bar ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10550 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10550/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10550/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10550/events | https://github.com/pandas-dev/pandas/issues/10550 | 94,507,165 | MDU6SXNzdWU5NDUwNzE2NQ== | 10,550 | columns become "unlinked" from a DataFrame when a new row is created | {
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... | 4 | 2015-07-11T20:56:41Z | 2019-10-06T01:58:55Z | 2019-10-06T01:58:55Z | NONE | null | ...perhaps this is the desired behavior, but it is not at all what I expected and had me very confused for a good while as I tried to figure out why I suddenly couldn't change values in the DataFrame I was using like I always had before.
Below is an MWE. Basically what happens is that if you assign a value to a row t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10551 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10551/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10551/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10551/events | https://github.com/pandas-dev/pandas/issues/10551 | 94,507,859 | MDU6SXNzdWU5NDUwNzg1OQ== | 10,551 | ENH: Allow read_csv dtype to accept category | {
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"... | closed | false | null | [] | null | 1 | 2015-07-11T21:10:52Z | 2015-07-11T21:23:46Z | 2015-07-11T21:23:46Z | MEMBER | null | Like R's `stringsAsFactors`, it is nice to create `category` when read data. Currently, it raises `TypeError`.
```
import pandas as pd
import StringIO
pd.read_csv(StringIO.StringIO("""A, B
a, c
b, d"""), dtype={'A': 'category'})
# TypeError: data type "category" not understood
```
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... | 3 | 2015-07-11T21:18:36Z | 2021-06-12T00:42:34Z | null | MEMBER | null | All of the following should be equivalent:
```
In [21]: df = pd.DataFrame({'a': [1], 'b': [2], 'c': [3]}).set_index(['a', 'b'])
In [22]: df.loc[1]
Out[22]:
c
b
2 3
In [23]: df.loc[(1,), slice(None)]
Out[23]:
c
b
2 3
In [24]: df.loc[(1, slice(None)), slice(None)]
Out[24]:
c
a b
1 2 3
```
In the last o... | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-07-11T21:36:54Z | 2020-12-07T08:17:00Z | 2015-07-13T02:40:09Z | NONE | null | In a subclass of pandas objects, pickling an object doesn't serialize properties of an instance of that subclass, even if the attribute has been added to `_metadata`. It would be hard to override this behavior entirely in the subclass, because it will require updates to `__getstate__` and `__setstate__`, and probably a... | {
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"f... | 1 | 2015-07-12T13:55:16Z | 2015-07-12T13:58:18Z | null | NONE | null | Hi all,
I observed now several times that `pivot_table()` requires a lot of memory when I wanted to reshape a `Data.Frame` in table format (id, name, value) into matrix format (index=id, columns=name, values=value):
``` python
print(d)
# id sample value
1 A 1
2 A 2
1 ... | {
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... | 22 | 2015-07-12T20:06:31Z | 2020-05-25T21:46:18Z | null | MEMBER | null | In my discussion with Jonathan and others and at the SciPy sprints, we agreed that it would be really nice to expose some minimal tools for manipulating and view the internal pandas blocks system. For example, it should be possible to:
1. manually consolidate blocks
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https://api.github.com/repos/pandas-dev/pandas/issues/10558 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10558/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10558/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10558/events | https://github.com/pandas-dev/pandas/pull/10558 | 94,601,173 | MDExOlB1bGxSZXF1ZXN0Mzk3NjkxODc= | 10,558 | BUG: pd.eval with numexpr engine coerces 1 element numpy array to scalar | {
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"followers_url": "https://api.github.com/users/jr... | 2 | 2015-07-12T21:35:36Z | 2015-07-20T21:19:12Z | 2015-07-20T21:19:08Z | MEMBER | null | Closes #10546. Used `assert_numpy_atray_equivalent` to guarantee array comparison, not scalar. This should be prior to #10542 and being changed to use `assert_numpy_array_equal` in #10542.
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https://api.github.com/repos/pandas-dev/pandas/issues/10559 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10559/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10559/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10559/events | https://github.com/pandas-dev/pandas/issues/10559 | 94,601,866 | MDU6SXNzdWU5NDYwMTg2Ng== | 10,559 | Minor improvement: Change to_excel "sheet_name" to "sheetname" | {
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... | 2 | 2015-07-12T21:46:02Z | 2017-05-23T19:36:28Z | 2017-05-23T19:36:28Z | NONE | null | pd.read_excel() takes "sheetname" as an argument.
pd.DataFrame.to_excel() takes "sheet_name" as an argument.
For consistency, I think one ought to be changed to match the other.
On my windows installation of pandas 0.16.2, I modified to_excel to take sheetname rather than sheet_name. All I had to do was locate frame.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10560 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10560/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10560/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10560/events | https://github.com/pandas-dev/pandas/issues/10560 | 94,640,745 | MDU6SXNzdWU5NDY0MDc0NQ== | 10,560 | TypeError in SparseSeries.__repr__ when series longer than max_rows | {
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... | 1 | 2015-07-13T05:12:40Z | 2016-04-03T14:20:30Z | 2016-04-03T14:20:30Z | CONTRIBUTOR | null | ``` python
In [2]: pd.__version__
Out[2]: '0.16.2-123-gdf1f5cf'
In [3]: pd.options.display.max_rows = 3
In [4]: pd.Series(randn(3)).to_sparse()
Out[4]:
0 1.100684
1 -0.924482
2 -0.106069
dtype: float64
BlockIndex
Block locations: array([0], dtype=int32)
Block lengths: array([3], dtype=int32)
In [5]: pd.Serie... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10562 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10562/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10562/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10562/events | https://github.com/pandas-dev/pandas/pull/10562 | 94,768,740 | MDExOlB1bGxSZXF1ZXN0Mzk4MzQ3MDA= | 10,562 | BUG: #8243 Change unary - to ~. Fixes numpy warning in ols. | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10563 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10563/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10563/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10563/events | https://github.com/pandas-dev/pandas/issues/10563 | 94,778,425 | MDU6SXNzdWU5NDc3ODQyNQ== | 10,563 | ERR: show SettingWithCopyWarning on Panel assignments if possible | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2015-07-13T18:12:06Z | 2018-07-06T20:21:07Z | 2017-07-10T21:07:20Z | NONE | null | This involves incorrect pickling of Pandas Panel values. From what I've seen, it occurs when new values of a different data type are assigned to a Pandas Panel axis. Everything functions well until the panel is pickled. When the pickle is read the old values appear. In the example below floats are reassigned as objects... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10564 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10564/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10564/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10564/events | https://github.com/pandas-dev/pandas/issues/10564 | 94,939,281 | MDU6SXNzdWU5NDkzOTI4MQ== | 10,564 | COMPAT: allow multi-indexes to be written to Excel (even they cannot be read back in) | {
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... | 2 | 2015-07-14T13:26:08Z | 2016-02-02T19:53:54Z | 2016-02-02T19:53:46Z | MEMBER | null | ``` python
In [10]: s = pd.Series(np.arange(1000.0), name='foo')
In [11]: s.name
Out[11]: 'foo'
In [12]: pd.rolling_mean(s, 30).name is None
Out[12]: True
In [13]: pd.__version__
Out[13]: '0.16.2'
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10566 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10566/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10566/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10566/events | https://github.com/pandas-dev/pandas/issues/10566 | 94,951,510 | MDU6SXNzdWU5NDk1MTUxMA== | 10,566 | CLN: compat.bind_method and core.common.bind_method | {
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"followers_url": "https://api.github.com/users/jr... | 7 | 2015-07-14T13:59:54Z | 2015-08-20T13:23:56Z | 2015-08-20T13:23:56Z | CONTRIBUTOR | null | I'd like to remove `bind_method` from [here](https://github.com/pydata/pandas/blob/master/pandas/compat/__init__.py#L149-171) and [here](https://github.com/pydata/pandas/blob/master/pandas/core/common.py#L116-138), as I don't see any benefit over `setattr(cls, name, func)`. Is there any?
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combine_first() loses timezone information for datetime columns
```
dts1 = pd.date_range('20150101','20150105',tz='UTC')
df1 = pd.DataFrame({'DATE':dts1})
dts2 = pd.date_range('20150103','20150105',tz='UTC')
df2 = pd.DataFrame({'DATE':dts2})
df = df1.combine_first(df2)
df.DATE[0].tz # thi... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10568 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10568/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10568/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10568/events | https://github.com/pandas-dev/pandas/pull/10568 | 94,985,093 | MDExOlB1bGxSZXF1ZXN0Mzk5MzUyMjk= | 10,568 | ENH: Added DataFrame.round and associated tests | {
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I'm constantly messing about with the number of decimal places displayed by doing `np.round(df, 2)` so thought this flexible `round`, with different numbers of decimals per column, should be part of the `DataFram... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10569 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10569/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10569/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10569/events | https://github.com/pandas-dev/pandas/pull/10569 | 94,999,056 | MDExOlB1bGxSZXF1ZXN0Mzk5NDE5OTQ= | 10,569 | ERR: Boolean comparisons of a Series vs None will now be equivalent to null comparisons | {
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numpy 1.10 shows a deprecation warning for this. this should eliminate a bunch of these.
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https://api.github.com/repos/pandas-dev/pandas/issues/10570 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10570/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10570/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10570/events | https://github.com/pandas-dev/pandas/pull/10570 | 95,004,709 | MDExOlB1bGxSZXF1ZXN0Mzk5NDUwMjI= | 10,570 | COMPAT: Allow multi-indexes to be written to excel | {
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Closes #10564
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https://api.github.com/repos/pandas-dev/pandas/issues/10571 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10571/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10571/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10571/events | https://github.com/pandas-dev/pandas/issues/10571 | 95,010,340 | MDU6SXNzdWU5NTAxMDM0MA== | 10,571 | pd.concat DataFrames with an all None object column converts None to nan | {
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``` python
>>> import pandas as pd
>>> df1 = pd.DataFrame(data=[[1, None], [2, None]], columns=['a', 'b'])
>>> df2 = pd.DataFrame(data=[[3, None], [4, None]], columns=['a', 'b'])
>>> df1
a b
0 1 None
1 2 None
>>> df1.dtypes
a int64
b object
dtype: object
>>> df2
a b
0 3 None
1 ... | {
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] | closed | false | null | [] | null | 8 | 2015-07-14T22:21:28Z | 2015-09-15T01:12:12Z | 2015-09-14T19:41:30Z | NONE | null | Google's libraries support Python 3 since version 1.4.0, so we could add support for Python 3 in read_gbq method.
Also it is not always useful to see "Job not yet complete" printings, so I've added optional parameter that allows disable it.
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https://api.github.com/repos/pandas-dev/pandas/issues/10573 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10573/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10573/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10573/events | https://github.com/pandas-dev/pandas/issues/10573 | 95,072,168 | MDU6SXNzdWU5NTA3MjE2OA== | 10,573 | New GLIBC requirement? | {
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ImportError: /lib64/libc.so.6: version `GLIBC_2.14' not found
With 0.16.2 this does not happen. Is GLIBC_2.14 absolutely required for some new functionality? Why does the bubble not burst during `python setup.py install` then?
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``` python
0 1 2 3 4 5 6 7
first second third
bar one three 4 9 7 8 5 0 7 8
four 6 8 1 5 9 9 1 7
two three 7 5 2 6 7 8 5 9
four 0 8 8 5 3 5 8 3
baz one t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10576 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10576/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10576/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10576/events | https://github.com/pandas-dev/pandas/pull/10576 | 95,104,119 | MDExOlB1bGxSZXF1ZXN0Mzk5ODczMzI= | 10,576 | BUG: Fix typo-related bug to resolve #9266 | {
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Tried replicating the test case provided in the original issue. Let me know if it needs any changes or fixes.
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https://api.github.com/repos/pandas-dev/pandas/issues/10577 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10577/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10577/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10577/events | https://github.com/pandas-dev/pandas/pull/10577 | 95,119,549 | MDExOlB1bGxSZXF1ZXN0Mzk5OTIxNzM= | 10,577 | Fixed bug where read_csv ignores dtype arg if input is empty. | {
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"color": "531... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 14 | 2015-07-15T06:38:56Z | 2015-07-18T11:20:49Z | 2015-07-18T11:20:37Z | CONTRIBUTOR | null | The `CParser` implementation for `pd.read_csv` ignores argument `dtype` if the input is empty. This pull request fixes this so that a DataFrame with the expected column types is returned.
``` Python
import pandas as pd
import c... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10578 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10578/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10578/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10578/events | https://github.com/pandas-dev/pandas/issues/10578 | 95,138,018 | MDU6SXNzdWU5NTEzODAxOA== | 10,578 | MemoryError when plotting two DataFrames, one with odd DatetimeIndex | {
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"description": "Me... | open | false | null | [] | null | 7 | 2015-07-15T08:49:10Z | 2021-04-18T07:21:10Z | null | NONE | null | Was trying to upsample a DataFrame by non-integer amount, then compare the two. When trying to plot the second DF, pandas tries to allocate a lot of memory, and finally throws MemoryError after a few seconds.
Minimal working example
``` python
import pandas as pd
# Create data for 288 seconds
index = pd.date_range(s... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10579 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10579/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10579/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10579/events | https://github.com/pandas-dev/pandas/issues/10579 | 95,163,295 | MDU6SXNzdWU5NTE2MzI5NQ== | 10,579 | ENH: Enhancement, new functionality request: Irregular time exponential smoothing | {
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"description": "rolling,... | open | false | null | [] | null | 13 | 2015-07-15T10:53:12Z | 2020-03-31T04:58:07Z | null | NONE | null | Not sure if it is OK to make the request here, but here you go.
Can a feature be added to exponential smoothing where
alpha = time decay = (time_now - time_previous)/time_scale;
where time_scale and the difference are given in a specific unit eg milli/micro/nanoseconds.
This would really speed up temporally irregul... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10580 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10580/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10580/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10580/events | https://github.com/pandas-dev/pandas/issues/10580 | 95,167,546 | MDU6SXNzdWU5NTE2NzU0Ng== | 10,580 | DataFrame.resample Can Be Very Innaccurate With Timedelta Rule | {
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"color": "0052cc"... | closed | false | null | [] | null | 10 | 2015-07-15T11:13:26Z | 2015-07-15T13:05:05Z | 2015-07-15T12:02:09Z | NONE | null | DataFrame.resample() is not accurate, at least when using time delta as rule.
This is because it does not interpolate between values when up-sampling, nor does aggregation take into account the exact sampling point when down-sampling. When a new sampling point falls between two original samples:
- when up-sampling, th... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10581 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10581/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10581/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10581/events | https://github.com/pandas-dev/pandas/issues/10581 | 95,170,751 | MDU6SXNzdWU5NTE3MDc1MQ== | 10,581 | encoding not respected on read_msgpack | {
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"description": "Unicode strings",
"i... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 1 | 2015-07-15T11:36:53Z | 2015-08-18T11:09:49Z | 2015-08-18T11:09:49Z | CONTRIBUTOR | null | as discussed on https://groups.google.com/forum/#!topic/pydata/ngROaML_hLI
encoding does not seem to be respected on reading a msgpack, below i am expecting to get back what
I put in as utf8
```
In [17]: s
Out[17]: u'\u2019'
In [18]: s = pd.Series({'a' : u"\u2019" })
In [19]: s.values[0]
Out[19]: u'\u2019'
In [20]... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10582 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10582/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10582/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10582/events | https://github.com/pandas-dev/pandas/issues/10582 | 95,193,840 | MDU6SXNzdWU5NTE5Mzg0MA== | 10,582 | ValueError and IndexError for pivot_table | {
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... | 7 | 2015-07-15T13:27:06Z | 2021-04-18T07:21:55Z | null | NONE | null | I'v found two examples of pivot_table which unexpectedly fail but for different reasons:
``` python
NUM_ROWS = 51364452
NUM_INDEX = 34262015
NUM_COLUMNS = 1732
df = pd.DataFrame({'A' : np.random.randint(NUM_INDEX, size=NUM_ROWS),
'B' : np.random.randint(NUM_COLUMNS, size=NUM_ROWS),
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10583 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10583/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10583/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10583/events | https://github.com/pandas-dev/pandas/issues/10583 | 95,224,153 | MDU6SXNzdWU5NTIyNDE1Mw== | 10,583 | TimedeltaIndex raises error when slicing from '0s' | {
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... | closed | false | null | [] | {
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"followers_url": "https://api.github.com/users/jr... | 5 | 2015-07-15T15:32:38Z | 2015-09-01T19:38:53Z | 2015-09-01T19:38:53Z | CONTRIBUTOR | null | ``` python
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.normal(size=(10,4)))
df.index = pd.timedelta_range(start='0s', periods=10, freq='s')
print(df.loc['0s':,:])
```
raises a `ValueError: invalid resolution`, while `print(df.loc['5s':,:])` works.
Workaround : `print(df.loc[pd.Timedelta('0s')... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10584 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10584/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10584/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10584/events | https://github.com/pandas-dev/pandas/issues/10584 | 95,243,283 | MDU6SXNzdWU5NTI0MzI4Mw== | 10,584 | Pandas 'unstack' returns a Series instead of a Dataframe? | {
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"de... | closed | false | null | [] | null | 3 | 2015-07-15T17:06:21Z | 2015-07-15T19:32:55Z | 2015-07-15T19:32:55Z | NONE | null | What causes Pandas 'unstack' to output a series instead of a Dataframe?
import pandas as pd;
events = pd.DataFrame.from_csv('/Users/davidlaxer/gdelt/events/20150613.export.CSV', sep='\t', index_col='GLOBALEVENTID')
e = events.unstack()
type(e)
Out[129]:
pandas.core.series.Series
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https://api.github.com/repos/pandas-dev/pandas/issues/10585 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10585/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10585/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10585/events | https://github.com/pandas-dev/pandas/issues/10585 | 95,256,374 | MDU6SXNzdWU5NTI1NjM3NA== | 10,585 | DataFrame constructor fails when passed a list with an empty array. | {
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"de... | closed | false | null | [] | null | 1 | 2015-07-15T18:12:54Z | 2015-07-15T18:22:31Z | 2015-07-15T18:22:18Z | CONTRIBUTOR | null | ``` Python
import pandas as pd
import numpy as np
data = {'a': np.empty(0)}
df = pd.DataFrame(data)
print df
rows, cols = data.values(), data.keys()
print rows, cols
df = pd.DataFrame(rows, columns=cols)
```
```
Empty DataFrame
Columns: [a]
Index: []
[array([], dtype=float64)] ['a']
Traceback (most recent call las... | {
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The documentation suggests:
```
You can also specify the axis argument to .loc to interpret the passed slicers on a single axis.
see http://pandas.pydata.org/pandas-docs/stable/advanced.html#using-s... | {
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```
In [17]: s = Series(list('aabbcd')*1000000).astype('category')
In [18]: result = pd.concat([s,s])
In [19]: result2 = Series(pd.Categorical(pd.conca... | {
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Attempting to use a multiply operation with a multi index.
```
import pandas as pd
import numpy as np
d = {'Alpha': [1,2,3,4,5,6,7,8,9]
,'Beta':tuple('ABCDEFGHI')
,'C': np.random.randint(1,10,9)
,'D': np.random.randint(100,200... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10589 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10589/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10589/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10589/events | https://github.com/pandas-dev/pandas/pull/10589 | 95,290,952 | MDExOlB1bGxSZXF1ZXN0NDAwNzAwNjQ= | 10,589 | DOC: Small improvement to convert_objects doc | {
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[skip ci]
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https://api.github.com/repos/pandas-dev/pandas/issues/10590 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10590/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10590/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10590/events | https://github.com/pandas-dev/pandas/issues/10590 | 95,293,744 | MDU6SXNzdWU5NTI5Mzc0NA== | 10,590 | Inconsistency, NaT included in result of groupby method first but not NaN | {
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Demonstration of the inconsistency. (note that both `NaT` and `NaN` in the data frame are produced by `np.nan`, the difference is t... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10591 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10591/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10591/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10591/events | https://github.com/pandas-dev/pandas/issues/10591 | 95,294,612 | MDU6SXNzdWU5NTI5NDYxMg== | 10,591 | TST: test_read_famafrench fails with HTTP 404 | {
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http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html
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https://api.github.com/repos/pandas-dev/pandas/issues/10592 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10592/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10592/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10592/events | https://github.com/pandas-dev/pandas/issues/10592 | 95,294,998 | MDU6SXNzdWU5NTI5NDk5OA== | 10,592 | ENH: Add "select all" option for duplicates | {
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I often check to see if I have duplicates by some primary key, and if I do, I then want to look at ALL rows with the same primary key. Right now, duplicates /... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10593 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10593/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10593/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10593/events | https://github.com/pandas-dev/pandas/pull/10593 | 95,303,608 | MDExOlB1bGxSZXF1ZXN0NDAwNzY2NTk= | 10,593 | DOC-10371 Add note regarding supported interpolation methods for Series/DF | {
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Suggested improvement for https://github.com/pydata/pandas/issues/10371
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https://api.github.com/repos/pandas-dev/pandas/issues/10594 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10594/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10594/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10594/events | https://github.com/pandas-dev/pandas/issues/10594 | 95,305,624 | MDU6SXNzdWU5NTMwNTYyNA== | 10,594 | DOC: Add more examples for Series resampling in tutorials | {
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"followers_url": "https://api.github.com/users/jorisva... | 3 | 2015-07-15T22:39:19Z | 2015-07-15T22:50:20Z | 2015-07-15T22:47:55Z | CONTRIBUTOR | null | It would be nice to see more resampling examples in the Tutorials section [here](http://pandas.pydata.org/pandas-docs/stable/timeseries.html).
Some examples I am working on for this:
- example using custom `how` function
- example showing how to use `base`
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https://api.github.com/repos/pandas-dev/pandas/issues/10595 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10595/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10595/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10595/events | https://github.com/pandas-dev/pandas/issues/10595 | 95,310,549 | MDU6SXNzdWU5NTMxMDU0OQ== | 10,595 | Make _get_notnull_col_dtype a static method | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10596 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10596/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10596/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10596/events | https://github.com/pandas-dev/pandas/issues/10596 | 95,311,487 | MDU6SXNzdWU5NTMxMTQ4Nw== | 10,596 | Methods on an PeriodIndex that return an empty set don't return a PeriodIndex object | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2015-07-15T23:27:50Z | 2015-07-28T21:43:15Z | 2015-07-28T21:43:15Z | CONTRIBUTOR | null | ``` python
In [27]: period_index=pd.PeriodIndex(start='2015-01-01',end='2015-03',freq='B')
period_index
Out[27]: <class 'pandas.tseries.period.PeriodIndex'>
[2015-01-01, ..., 2015-03-02]
Length: 43, Freq: B
In [28]: period_index.difference(period_index)
Out[28]: Index([], dtype='object')
```
I think this should retur... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10597 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10597/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10597/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10597/events | https://github.com/pandas-dev/pandas/pull/10597 | 95,312,659 | MDExOlB1bGxSZXF1ZXN0NDAwODE0NTc= | 10,597 | Improve categorical concat speed by ~20x | {
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before (current master):
``` python
In [1]: s = pd.Series(list('aabbcd')*1000000).astype('category')
In [2]: timeit pd.concat([s,s])
1 loops, best of 3: 573 ms per loop
```
after (this PR):
``` python
In [1]: s = pd.Series(list('aabbcd')*1000000).astype('category')
In [2]: timeit pd.concat([s,s])
10... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10598 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10598/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10598/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10598/events | https://github.com/pandas-dev/pandas/issues/10598 | 95,318,888 | MDU6SXNzdWU5NTMxODg4OA== | 10,598 | CI: migrate to travis container infrastructure | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2015-07-16T00:19:18Z | 2016-06-24T00:01:47Z | 2016-06-24T00:01:47Z | CONTRIBUTOR | null | http://docs.travis-ci.com/user/migrating-from-legacy/
trivial I think to remove the `sudo`. but prob have to change some stuff (as we
use _some_ apt stuff)
currently we externally cache, so that would have to be figure out (at a later date is ok)
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https://api.github.com/repos/pandas-dev/pandas/issues/10599 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10599/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10599/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10599/events | https://github.com/pandas-dev/pandas/pull/10599 | 95,320,283 | MDExOlB1bGxSZXF1ZXN0NDAwODM5Mjk= | 10,599 | Empty subtypes of Index return their type, rather than Index | {
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"followers_url": "https://api.github.com/users/jr... | 8 | 2015-07-16T00:25:13Z | 2015-07-24T07:34:42Z | 2015-07-24T07:34:42Z | CONTRIBUTOR | null | Resolves #10596
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https://api.github.com/repos/pandas-dev/pandas/issues/10601 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10601/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10601/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10601/events | https://github.com/pandas-dev/pandas/issues/10601 | 95,387,146 | MDU6SXNzdWU5NTM4NzE0Ng== | 10,601 | BUG in dealing with deprecated argument in convert_objects | {
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The deprecation warning is triggered, but the value of the keyword argument should also be adapted so it still works with the new code I think (from a failure in the docs)
```
In [1]: from datetime import datetime
In [2]: s = pd.Series([datetime(2001,1,1,0,0), 'foo', 1.0, 1,
...: pd.Ti... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/10602 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10602/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10602/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10602/events | https://github.com/pandas-dev/pandas/pull/10602 | 95,452,235 | MDExOlB1bGxSZXF1ZXN0NDAxMzg2NzY= | 10,602 | BUG: Fix issue with old-style usage in convert_objects | {
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"followers_url": "https://api.github.com/users/jr... | 20 | 2015-07-16T15:00:18Z | 2016-02-16T16:30:00Z | 2015-09-06T17:14:50Z | CONTRIBUTOR | null | Fix to temporary allow passing 'coerce' to variables
closes #10601
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