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essentially was doing a assignment of `np.nan` to a numpy array of dtype `datetime64[ns]`
which works correct (set's the value to `iNaT`) on little endian, for some reason on big
endian doesn't work, explicity change the `nan` to `iNaT`
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``` python
======================================================================
ERROR: test_spam_url (pandas.io.tests.test_html.TestReadHtmlBase)
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"i... | 1 | 2013-07-20T19:54:59Z | 2013-07-20T20:59:21Z | 2013-07-20T20:59:21Z | CONTRIBUTOR | null | related #4299
cc @Komnomnomnom
weird that this doesn't break on travis (but did on my vagrant machine), and on debian testing....
any thoughts?
```
> /home/vagrant/pandas_master/pandas/io/tests/test_json/test_ujson.py(109)test_encodeDoubleTinyExponential()
-> self.assertEqual(num, ujson.decode(ujson.encode(num)))
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"i... | 3 | 2013-07-21T14:50:56Z | 2016-10-12T23:04:01Z | 2013-07-21T17:10:32Z | CONTRIBUTOR | null | @cpcloud
cc @jtratner
https://travis-ci.org/pydata/pandas/jobs/9323458
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"i... | 8 | 2013-07-21T16:12:14Z | 2014-07-16T08:20:06Z | 2013-07-21T17:10:32Z | MEMBER | null | closes #4309
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https://api.github.com/repos/pandas-dev/pandas/issues/4311 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4311/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4311/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4311/events | https://github.com/pandas-dev/pandas/issues/4311 | 17,024,860 | MDU6SXNzdWUxNzAyNDg2MA== | 4,311 | Rank by multiple columns | {
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... | 5 | 2013-07-21T21:32:43Z | 2019-11-20T09:52:40Z | 2018-06-21T19:22:41Z | CONTRIBUTOR | null | I don't _think_ this is possible atm, but would be a nice enhancement.
Similar to how you can pass list of columns to sort*.
http://stackoverflow.com/questions/17775935/sql-like-window-functions-in-pandas-row-numbering-in-python-pandas-dataframe
_\_probably there is a cheeky answer/hack to this q using sort...*
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This might be trying to coerce `object` dtype to a real dtype (int/float) and is failing
Should prob raise for now (or work). Not working with iloc/loc.
```
In [66]: df = DataFrame([['1','2','3','.4',5,6.,'foo']],co... | {
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closes #2583
``` python
In [3]: spx = DataReader('^GSPC', data_source='yahoo')
In [4]: spx.head()
Out[4]:
Open High Low Close Volume Adj Close
Date ... | {
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to say round by minute
http://stackoverflow.com/questions/17781159/round-pandas-datetime-index
by hour
https://github.com/pydata/pandas/issues/4314
might be simpler to use numpy astype here
http://stackoverflow.com/questions/23315163/merging-two-pandas-timeseries-shifted-by-1-second
```
In [75]: index = ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4315 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4315/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4315/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4315/events | https://github.com/pandas-dev/pandas/issues/4315 | 17,048,275 | MDU6SXNzdWUxNzA0ODI3NQ== | 4,315 | API: Would it be useful for everyone if DataFrame.to_html (and to_string) had an argument to specify justify settings for each column? | {
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Currently it is only possible to specify justify settings for column headers. This would extremely useful when used in conjunction with IPython Notebook.
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The source did not have much (a... | {
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I have a field set where "NA" is meaningful, but not meaning "not applicable" (it refers to the name of my school's Homeroom). There's no obvious way to handle this edge case...
On 0.11.0
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https://api.github.com/repos/pandas-dev/pandas/issues/4319 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4319/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4319/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4319/events | https://github.com/pandas-dev/pandas/issues/4319 | 17,069,145 | MDU6SXNzdWUxNzA2OTE0NQ== | 4,319 | "&" doesn't raise ValueError according to nose, but it does in the shell | {
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``` python
import numpy as np
import numbers
def randbool(p=0.5, size=None):
if size is None:
size = ()
if isinstance(size, numbers.Integral):
size = (size,)
return np.random.rand(*size) <= p
```
```
In [1]: x = randb... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4320 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4320/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4320/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4320/events | https://github.com/pandas-dev/pandas/pull/4320 | 17,069,374 | MDExOlB1bGxSZXF1ZXN0NzA4OTMzNw== | 4,320 | TST: skip some tests if scikits is installed but not scipy GH3376 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4321 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4321/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4321/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4321/events | https://github.com/pandas-dev/pandas/pull/4321 | 17,070,793 | MDExOlB1bGxSZXF1ZXN0NzA5MDIxMA== | 4,321 | DOC: Update computation.rst | {
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"followers_url": "https://api.github.com/users/wesm... | 10 | 2013-07-22T21:36:55Z | 2013-09-24T00:04:00Z | 2013-08-23T17:51:59Z | CONTRIBUTOR | null | From [this SO question](http://stackoverflow.com/questions/17797384/date-and-time-in-pandas-read-csv), with input to include thousands:
```
In [1]: s = '06.02.2013;13:00;1.000,215;0,215;0,185;0,205;0,00'
In [2]: pd.read_csv(StringIO(s), sep=';', header=None, parse_dates={'Dates': [0, 1]}, index_col=0, decimal=',')
O... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4323 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4323/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4323/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4323/events | https://github.com/pandas-dev/pandas/pull/4323 | 17,072,748 | MDExOlB1bGxSZXF1ZXN0NzA5MTQwNQ== | 4,323 | SQL alchemy file structure | {
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Merge this into the sql branch so we can start incorporating bug fixes into the new file structure of `sql.py` / `sql_legacy.py`.
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"followers_url": "https://api.github.com/users/wesm... | 25 | 2013-07-22T23:45:56Z | 2013-10-28T01:32:24Z | 2013-09-29T20:03:21Z | CONTRIBUTOR | null | After #3482 is merged, some additional methods to fixup
- [x] Series.replace (use generic/replace) via f4fe5fd03816deab1dc71e958ebbb4d9c1b9d35d
- [x] Series align (use generic/align), PR #4800
- [x] Move Arithmetic/Comparison methods to generic, #4051, #5034
- [ ] Fillna column wise, #4514
- [x] Verify Copy for Series ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4325 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4325/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4325/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4325/events | https://github.com/pandas-dev/pandas/issues/4325 | 17,077,225 | MDU6SXNzdWUxNzA3NzIyNQ== | 4,325 | HDFStore object display is reduced in 0.12.0rc1 and slow for big files. | {
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``` python
store = pd.HDFStore('/u/paige/maye/raid/rdr20_month_samples/nominal/C9.h5')
pd.__version__
'0.12.0rc1'
store
<cla... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4326 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4326/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4326/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4326/events | https://github.com/pandas-dev/pandas/issues/4326 | 17,083,840 | MDU6SXNzdWUxNzA4Mzg0MA== | 4,326 | Comparing NaN to each other always results in False | {
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from io import StringIO
def null():
""" return a nan: is there a better way to do this? """
return pd.read_csv(StringIO("NA\n"), header=No... | {
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... | 14 | 2013-07-23T06:54:57Z | 2016-01-08T14:07:46Z | 2016-01-08T14:07:46Z | NONE | null | Running Ubuntu 12.10. The recommended way of running tests (http://pandas.pydata.org/pandas-docs/stable/install.html#running-the-test-suite)
```
nosetests pandas
```
did not work. I had to use:
```
nosetests --exe pandas
```
It would also be useful to know how to avoid the:
```
OperationalError: (1046, 'No datab... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4328 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4328/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4328/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4328/events | https://github.com/pandas-dev/pandas/issues/4328 | 17,093,601 | MDU6SXNzdWUxNzA5MzYwMQ== | 4,328 | BUG: Crash using to_csv with QUOTE_NONE | {
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I can write DataFrames to a file using to_csv fine unless I pass the option: quoting=pandas.io.parsers.csv.QUOTE_NONE in which case I get exceptions of the form:
packages/pandas/core/format.py", line 1054, in _save_chu... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4329 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4329/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4329/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4329/events | https://github.com/pandas-dev/pandas/issues/4329 | 17,093,872 | MDU6SXNzdWUxNzA5Mzg3Mg== | 4,329 | Reading from mongodb (BSON) | {
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"f... | 18 | 2013-07-23T10:29:55Z | 2018-07-06T19:37:10Z | 2018-07-06T19:37:10Z | CONTRIBUTOR | null | Now we have a neat read_json function (#3804), it'd be really neat if we could read in from mongo using this i.e. without have to create an intermediary python object.
_I wasn't even sure how to return a json (bson) string from a mongo query, though surely this ought to be relatively easy..._
I've no idea how much of... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4330 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4330/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4330/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4330/events | https://github.com/pandas-dev/pandas/issues/4330 | 17,097,604 | MDU6SXNzdWUxNzA5NzYwNA== | 4,330 | ENH: enable HDFStore of Series in Table format | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4331 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4331/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4331/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4331/events | https://github.com/pandas-dev/pandas/issues/4331 | 17,121,561 | MDU6SXNzdWUxNzEyMTU2MQ== | 4,331 | add rand, ror, rxor methods to frame | {
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In [11]: s = True
In [12]: df = DataFrame(rand(10, 5)> 0.5)
In [13]: df
Out[13]:
0 1 2 3 4
0 True False False True False
1 True False False True False
2 False False True False False
3 True False False True False
4 False False True True False
5 False F... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4332 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4332/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4332/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4332/events | https://github.com/pandas-dev/pandas/issues/4332 | 17,124,563 | MDU6SXNzdWUxNzEyNDU2Mw== | 4,332 | ENH: Excel to support reading Timedeltas | {
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"followers_url": "https://api.github.com/users/jr... | 33 | 2013-07-23T20:48:05Z | 2014-04-24T10:27:41Z | 2014-04-24T10:27:41Z | CONTRIBUTOR | null | ExcelFile should print out line or even cell warnings
Today I was spending quite some time debugging why a decoding error stopped the code from reading in a table.
I thought the skiprows counts from 0 (= Excel row 1). It was always failing.
In one line there were column headers, the next line contained units which c... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4335 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4335/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4335/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4335/events | https://github.com/pandas-dev/pandas/issues/4335 | 17,128,122 | MDU6SXNzdWUxNzEyODEyMg== | 4,335 | ENH/BUG: pd.read_csv(): usecols does not work when also using skipfooter | {
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``` python
>>> import pandas as pd
>>> pd.__version__
'0.10.1'
>>> import StringIO
>>> data = 'a,b,c,d\n1,2,3,foo\n4,5,6,bar\n7,8,9,baz'
>>> df = pd.read_csv(StringIO.StringIO(data), usecols=[1])
>>> df
b
0 2
1 5
2 8
>>> df = pd.read_csv(StringIO.StringIO(data), usecols=[1], skipfooter=1)
>>>... | {
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"followers_url": "https://api.github.com/users/wesm... | 2 | 2013-07-23T23:17:32Z | 2013-09-27T02:26:30Z | 2013-09-27T02:26:30Z | MEMBER | null | A new module `core.align` would hold a couple of generic alignment functions, one of which will be `align_multiple` or possibly `align2` (taking 2 pandas objects) and then `align` would take a sequence of pandas objects to align.
Need to think about the API a bit more.
Psuedocode-ish:
``` python
df = DataFrame(...)
... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4337 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4337/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4337/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4337/events | https://github.com/pandas-dev/pandas/issues/4337 | 17,137,488 | MDU6SXNzdWUxNzEzNzQ4OA== | 4,337 | Creating DataFrame Changes Time Unit of datetime64 Series | {
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```
foo = pd.Series(np.array([np.datetime64(datetime.date(2012, 1, 1), 'M')]))
```
```
In [64]: foo.dtype
Out[64]: dtype('<M8[M]')
```
but then:
```
In [65]: pd.DataFrame({"date":foo,}).date.dtype
Out[65]: dtype('<M8[ns]')
```
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https://api.github.com/repos/pandas-dev/pandas/issues/4338 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4338/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4338/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4338/events | https://github.com/pandas-dev/pandas/issues/4338 | 17,137,623 | MDU6SXNzdWUxNzEzNzYyMw== | 4,338 | ENH: Series Creation Does Not Intelligently Handle datetime.date | {
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"followers_url": "https://api.github.com/users/jorisva... | 11 | 2013-07-24T03:17:03Z | 2018-10-26T10:58:25Z | 2018-10-26T10:58:19Z | CONTRIBUTOR | null | For example:
```
In [77]: pd.Series([datetime.datetime(2012, 1, 1)]).dtype
Out[77]: dtype('<M8[ns]')
```
works as expected.
However:
```
In [78]: pd.Series([datetime.date(2012, 1, 1)]).dtype
Out[78]: dtype('O')
```
create a Series of type object rather than datetime64.
You can get the desired effect:
```
In [89]... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4339 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4339/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4339/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4339/events | https://github.com/pandas-dev/pandas/issues/4339 | 17,145,933 | MDU6SXNzdWUxNzE0NTkzMw== | 4,339 | Bug: no ecoding setting for xls.parse | {
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my excel file contains units in a row:
"m²", "°", etc.
It appears that this generates unicode errors:
```
UnicodeDecodeError: 'utf8' codec can't decode byte 0xb0 in position 339: invalid start byte
```
Please see the discussion / documentation here:
- https://groups.google.com/forum/#!searchin/openpyxl-users... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4340 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4340/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4340/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4340/events | https://github.com/pandas-dev/pandas/issues/4340 | 17,146,063 | MDU6SXNzdWUxNzE0NjA2Mw== | 4,340 | xls.parse: fails to skip lines | {
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my excel file is like:
- metadata (10 rows)
- header (1 row)
- units (1 row)
- data (250 rows)
Now, I am trying to read it like:
df = xlsall.parse(sheetname='mydata', skiprows=11, header=10)
But it would not assign the information in row 11 as column labels but rather use the units in row 12 (counting from 1)... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4341 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4341/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4341/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4341/events | https://github.com/pandas-dev/pandas/issues/4341 | 17,149,417 | MDU6SXNzdWUxNzE0OTQxNw== | 4,341 | ENH: infer frequency from np.datetime64 in DatetimeIndex construction | {
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"f... | 2 | 2013-07-24T10:27:37Z | 2019-07-24T00:42:15Z | 2019-07-24T00:42:15Z | CONTRIBUTOR | null | see #4337
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https://api.github.com/repos/pandas-dev/pandas/issues/4342 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4342/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4342/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4342/events | https://github.com/pandas-dev/pandas/issues/4342 | 17,155,390 | MDU6SXNzdWUxNzE1NTM5MA== | 4,342 | Series with MultiIndex with PeriodIndex can't do unstack() | {
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"followers_url": "https://api.github.com/users/jr... | 4 | 2013-07-24T13:10:36Z | 2014-05-10T15:32:36Z | 2014-05-10T15:32:36Z | NONE | null | Here is the code:
``` python
import pandas as pd
idx1 = pd.PeriodIndex(["2013-01", "2013-01", "2013-02", "2013-02"], freq="M")
idx2 = ["a","b","a","b"]
value = [1,2,3,4]
idx = pd.MultiIndex.from_arrays([idx1, idx2])
s = pd.Series(value, index=idx)
s.unstack()
```
It will raise following exception:
```
anaconda/li... | {
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"followers_url": "https://api.github.com/users/jr... | 3 | 2013-07-24T14:15:27Z | 2017-03-10T14:36:34Z | 2017-03-10T14:36:33Z | CONTRIBUTOR | null | http://stackoverflow.com/questions/17818783/populate-a-pandas-sparsedataframe-from-a-scipy-sparse-matrix
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https://api.github.com/repos/pandas-dev/pandas/issues/4344 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4344/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4344/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4344/events | https://github.com/pandas-dev/pandas/issues/4344 | 17,159,366 | MDU6SXNzdWUxNzE1OTM2Ng== | 4,344 | ENH: support a string 'hash' for Series | {
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"f... | 4 | 2013-07-24T14:17:35Z | 2013-07-24T22:00:37Z | 2013-07-24T22:00:37Z | CONTRIBUTOR | null | useful in comparsion to other series
easy with integers but tricky with say floats
anyone think of a better way?
http://stackoverflow.com/questions/17836105/finding-rows-in-pandas-data-frame-with-same-values
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https://api.github.com/repos/pandas-dev/pandas/issues/4345 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4345/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4345/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4345/events | https://github.com/pandas-dev/pandas/issues/4345 | 17,167,121 | MDU6SXNzdWUxNzE2NzEyMQ== | 4,345 | test_time_series_plot_color_with_empty_kwargs fails with custom matplotlibrc | {
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"closed_at": "2013-12-30T19:53:14Z",
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2013-07-24T16:33:17Z | 2013-07-30T20:28:58Z | 2013-07-30T20:28:58Z | CONTRIBUTOR | null | The reason is that it tests for particular line colors, but I have my matplotlib colors tweaked, so the default values aren't `r`, `g`, and `b`. The test should probably look at the default `color_cycle` in matplotlib and check against those values.
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https://api.github.com/repos/pandas-dev/pandas/issues/4346 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4346/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4346/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4346/events | https://github.com/pandas-dev/pandas/pull/4346 | 17,175,240 | MDExOlB1bGxSZXF1ZXN0NzE0NzE3OQ== | 4,346 | BUG: fill_value is ignored when reindexing empty series | {
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"followers_url": "https://api.github.com/users/wesm... | 5 | 2013-07-24T19:10:18Z | 2014-06-25T22:22:35Z | 2013-09-24T01:30:08Z | CONTRIBUTOR | null | Here's a snippet depicting the, probably, buggy behaviour:
``` python
>>> import pandas as pd
>>> s = pd.Series()
>>> s.reindex([1,2,3])
1 NaN
2 NaN
3 NaN
dtype: float64
>>> s.reindex([1,2,3], fill_value=0.0)
1 NaN
2 NaN
3 NaN
dtype: float64
>>> pd.version.version
'0.12.0.dev-d7c6eb1'
```
I'd expect the l... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4347 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4347/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4347/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4347/events | https://github.com/pandas-dev/pandas/issues/4347 | 17,179,602 | MDU6SXNzdWUxNzE3OTYwMg== | 4,347 | BUG: Panel resample not working with loffset | {
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"followers_url": "https://api.github.com/users/jorisva... | 1 | 2013-07-24T20:37:43Z | 2018-07-06T20:21:01Z | 2017-07-11T09:55:12Z | CONTRIBUTOR | null | from the ML: https://groups.google.com/forum/#!topic/pystatsmodels/bCatleGJ4UU
```
In [15]: p = Panel(randn(10,100,5),major_axis=pd.date_range('20130101',periods=100))
In [16]: p
Out[16]:
<class 'pandas.core.panel.Panel'>
Dimensions: 10 (items) x 100 (major_axis) x 5 (minor_axis)
Items axis: 0 to 9
Major_axis axis: ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4348 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4348/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4348/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4348/events | https://github.com/pandas-dev/pandas/issues/4348 | 17,185,509 | MDU6SXNzdWUxNzE4NTUwOQ== | 4,348 | master (e21ccad3) creates a 0.12.0 egg | {
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So it looks like it's going backwards (see below timestamps):
()[maye@luna6 .../python2.7/site-packages]$ ll pandas*
pandas-0.12.0.dev_4c2d050-py2.7-linux-x86_64.egg:
total 8.0K
drwxr-xr-x 2 maye 4.0K Jul 16 11:45 EGG-INFO
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```
======================================================================
ERROR: test_banklist_header (pandas.io.tests.test_html.TestReadHtmlBase)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/tmp/buildd/pandas-0.12.0/debian/tmp/usr/l... | {
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```
ERROR: test_read_dta10 (pandas.io.tests.test_stata.StataTests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/usr/lib/python3/dist-packages/pandas/io/tests/test_stata.py", li... | {
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see #2592
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https://api.github.com/repos/pandas-dev/pandas/issues/4356 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4356/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4356/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4356/events | https://github.com/pandas-dev/pandas/pull/4356 | 17,209,835 | MDExOlB1bGxSZXF1ZXN0NzE2NTg4MA== | 4,356 | TST/BUG/CLN: make stata IO tests use temporary files for writing | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4357 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4357/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4357/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4357/events | https://github.com/pandas-dev/pandas/issues/4357 | 17,210,988 | MDU6SXNzdWUxNzIxMDk4OA== | 4,357 | FAIL: test_get_multi2 (pandas.io.tests.test_data.TestGoogle) | {
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pan = web.get_data_google(['GE', 'MSFT', 'INTC'], 'JAN-01-12', 'JAN-31-12')
result = pan.Open.ix['Jan-15-12':'Jan-20-12']
```
has shape (5, 3), not (4, 3) as claimed in the test:
```
GE INTC MSFT
Date
2012-01-16 17.65 NaN NaN
2012-01-17 17.85 25.18 28.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4358 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4358/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4358/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4358/events | https://github.com/pandas-dev/pandas/pull/4358 | 17,213,693 | MDExOlB1bGxSZXF1ZXN0NzE2Nzk5OA== | 4,358 | BUG: Fix brittle pivot margins | {
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"followers_url": "https://api.github.com/users/wesm... | 15 | 2013-07-25T14:19:36Z | 2014-06-23T03:12:15Z | 2013-08-12T13:21:40Z | CONTRIBUTOR | null | closes #3334 Brittle pivot margins
Issue was that pivot tables that use all columns of the original DataFrame in rows and cols failed on the margin computation. This is a special case for margins: one should use the index itself as the value.
```
>> df = DataFrame({'Response' : ['Y', 'N' ,'N', 'Y', 'Y', 'N'],
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https://api.github.com/repos/pandas-dev/pandas/issues/4359 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4359/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4359/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4359/events | https://github.com/pandas-dev/pandas/issues/4359 | 17,216,325 | MDU6SXNzdWUxNzIxNjMyNQ== | 4,359 | BUG: read_json silently skipping records? | {
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`orient='index'` and column is non_unique?
I'm trying out to_json and read_json on a data frame with 800k rows. However, after calling to_json on the file, read_json gets back only 2k rows. This happens if I call them in series or if I give to_json a filenam... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4360 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4360/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4360/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4360/events | https://github.com/pandas-dev/pandas/pull/4360 | 17,216,733 | MDExOlB1bGxSZXF1ZXN0NzE2OTY3NQ== | 4,360 | Fix issue #4345: graphics test failure | {
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The `test_time_series_plot_color_with_empty_kwargs` method in `test_graphics.py` uses the matplotlib default color cycle rather than 'r', 'g', and 'b'.
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"f... | 4 | 2013-07-25T15:12:45Z | 2013-07-26T10:40:04Z | 2013-07-26T10:40:04Z | NONE | null | If possible, it would be really useful to allow for an extra parameter that can override the default behaviour of the `pandas.Series.value_counts()` function to allow for sorting by by another series. we are looking to push the result out to a bar plot, and it makes sense to have the category (x-axis) displayed in a p... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4362 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4362/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4362/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4362/events | https://github.com/pandas-dev/pandas/issues/4362 | 17,217,735 | MDU6SXNzdWUxNzIxNzczNQ== | 4,362 | BUG: Series/Dataframe to_json not returning miliseconds | {
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> date_format : type of date conversion (epoch = epoch milliseconds, iso = ISO8601)
> default is epoch
The json exporting function seems to be returning the epoch _nanoseconds_ rather than the _milliseconds_ as suggested by the documentation.
``` python
s = pd.Seri... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4363 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4363/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4363/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4363/events | https://github.com/pandas-dev/pandas/issues/4363 | 17,220,085 | MDU6SXNzdWUxNzIyMDA4NQ== | 4,363 | BUG: read_table error with tabs, dtype and index_col | {
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"followers_url": "https://api.github.com/users/jorisva... | 5 | 2013-07-25T16:06:06Z | 2016-04-26T17:23:52Z | 2016-04-26T17:22:34Z | NONE | null | This gist demonstrates the problem:
https://gist.github.com/brentp/6066942
It's discussed in this thread:
https://groups.google.com/forum/#!topic/pydata/hIIZpZqbY5M
As discussed in the thread, there is some interaction when specifying dtype, index_col, and sep in read_csv.
As the gist shows, things work find with se... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4364 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4364/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4364/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4364/events | https://github.com/pandas-dev/pandas/pull/4364 | 17,222,783 | MDExOlB1bGxSZXF1ZXN0NzE3MzA2OA== | 4,364 | World Bank I/O docs and minimal improvement | {
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- ENH: Return a DataFrame full of floats instead of full of strings
RE: https://github.com/pydata/pandas/issues/4354
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In [29]: df = DataFrame(randint(2, size=(8e6, 10)))
In [30]: time df.sum()
CPU times: user 1.21 s, sys: 0.03 s, total: 1.24 s
Wall time: 1.23 s
Out[30]:
0 3999325
1 3998264
2 4000047
3 3997902
4 4001078
5 4001965
6 4001701
7 4000482
8 3997581
9 4000691
dtype: int64
In [31]: time df.m... | {
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- change the `_quiet` field (default is `False`) to a warning (about duplicates in readback)
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cc @cpcloud
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https://api.github.com/repos/pandas-dev/pandas/issues/4370 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4370/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4370/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4370/events | https://github.com/pandas-dev/pandas/issues/4370 | 17,265,675 | MDU6SXNzdWUxNzI2NTY3NQ== | 4,370 | ER/DOC: Sorting in multi-index columns: misleading error message, unclear docs | {
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Have a look at this example:
``` python
import pandas as pd
import numpy as np
from StringIO import StringIO
print "Pandas version %s\n\n" % pd.__version__
data1 = """idx,metric
0,2.1
1,2.5
2,3"""
data2 = """idx,metric
0,2.7
1,2.2
2,2.8"""
df1 = pd.read_csv(StringIO(data1))
df2 = pd.read_csv(StringIO(... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4371 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4371/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4371/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4371/events | https://github.com/pandas-dev/pandas/issues/4371 | 17,268,164 | MDU6SXNzdWUxNzI2ODE2NA== | 4,371 | pivot_table returns a Series instead of a DataFrame depending upon the datatype of the values parameter | {
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```
df = pandas.read_csv("a.csv")
print df
table = pandas.pivot_table(df, values=['Sales1'] ,rows='State' , aggfunc=np.sum)
print type(table)
table = pandas.pivot_table(df, values='Sales1' ,rows='State' , aggfunc=np.sum)
print type(table)
Contents of a.csv
City,Sales1
Mumbai,1
The Output
Ci... | {
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does not build on windows
cc @jtratner
can change to using a HashTable (I think we discussed this anyhow)
?
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to_json will raise ValueErrors where non-unique indices or columns would cause invalid JSON to be produced. Updated docstring and added some tests.
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The error only seems to occur when the columns are not unique:
``` python
In [5]: import pandas as pd
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see this: https://github.com/playpauseandstop/kikola/blob/master/kikola/utils/timedelta.py
```
In [58]: data
Out[58]: ' completed deadline\n15-07-2013 23:10 15-07-2013 23:15\n16-07-2013 00:20 16-07-2013 00:15\n16-07-2013 00:20 16-07-2013 00:15\n16-07-20... | {
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new object.
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https://api.github.com/repos/pandas-dev/pandas/issues/4382 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4382/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4382/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4382/events | https://github.com/pandas-dev/pandas/issues/4382 | 17,303,048 | MDU6SXNzdWUxNzMwMzA0OA== | 4,382 | pd.io.parsers.read_csv ignores skiprows when parse_dates is set to a dict | {
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2013-07-27T20:27:09Z | 2013-09-24T20:37:17Z | 2013-09-24T20:37:17Z | CONTRIBUTOR | null | For example:
```
pd.io.parsers.read_csv("http://www.datazoa.com/publish/export.asp?hash=yjPceG6fHL&uid=dzadmin&a=exportcsv",skiprows=range(1,13+1),skipfooter=4,parse_dates={"date":[0]})
```
has 907 rows.
As does:
```
pd.io.parsers.read_csv("http://www.datazoa.com/publish/export.asp?hash=yjPceG6fHL&uid=dzadmin&a=exp... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4383 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4383/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4383/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4383/events | https://github.com/pandas-dev/pandas/issues/4383 | 17,303,053 | MDU6SXNzdWUxNzMwMzA1Mw== | 4,383 | CLN/ENH: Specify Exceptions in io.common._is_url | {
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"followers_url": "https://api.github.com/users/wesm... | 7 | 2013-07-27T20:28:02Z | 2013-07-27T23:38:50Z | 2013-07-27T23:38:50Z | CONTRIBUTOR | null | This is `_is_url`, it has a blanket `except` statement, I'm thinking it would be better to specify the exceptions here (caused an issue for me while editing earlier). Not sure which exceptions should go here (ValueError, TypeError?), anyone have an idea?
``` python
def _is_url(url):
try:
return urlparse.u... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4384 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4384/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4384/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4384/events | https://github.com/pandas-dev/pandas/pull/4384 | 17,303,390 | MDExOlB1bGxSZXF1ZXN0NzIxNTk4Nw== | 4,384 | CLN/ENH/BLD: Remove need for 2to3 for Python 3. | {
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Many changes to make codebase compatible in 2 and 3. For `range`, `zip`, `map`, etc. tried to favor iterators over needing to use lists.
Changes:
- No more 2to3 in setup.py
- merges util/compat and util/py3compat into pandas/compat
- incorporates useful parts of the six library into compat (+ a... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4385 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4385/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4385/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4385/events | https://github.com/pandas-dev/pandas/issues/4385 | 17,305,153 | MDU6SXNzdWUxNzMwNTE1Mw== | 4,385 | TST: s3 codepath in get_filepath_or_buffer isn't tested. | {
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``` python
if _is_s3_url(filepath_or_buffer):
try:
import boto
except:
raise ImportError("boto... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4386 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4386/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4386/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4386/events | https://github.com/pandas-dev/pandas/issues/4386 | 17,307,263 | MDU6SXNzdWUxNzMwNzI2Mw== | 4,386 | DOC/BUG: pivot_table returns Series in specific circumstance | {
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"followers_url": "https://api.github.com/users/jr... | 6 | 2013-07-28T04:56:00Z | 2017-04-18T22:37:17Z | 2017-04-18T22:37:17Z | CONTRIBUTOR | null | The docstrings and other documentation say that the `pivot_table` function **returns a DataFrame**. However, this likely leads to confusion like #4371, because under narrow circumstances, passing a certain set of argument dtypes results in the function **returning a Series** (see ipython examples at end):
1. values i... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4387 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4387/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4387/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4387/events | https://github.com/pandas-dev/pandas/issues/4387 | 17,307,559 | MDU6SXNzdWUxNzMwNzU1OQ== | 4,387 | Make bar plot on secondary axis, the line plot on the primary axis wont show. | {
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"f... | 2 | 2013-07-28T05:43:36Z | 2021-05-10T17:42:17Z | null | NONE | null | Following issue #3598,
```
df = pd.DataFrame(np.random.uniform(size=10).reshape(5,2),columns=['A','B'])
df['A'] = df['A'] * 100
df.A.plot()
df.B.plot(kind='bar',secondary_y=True)
plt.show()
```
This gives the right plot, with `A` plotted as line in the primary axis, and `B` is plotted as bar in the secondary axis.
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- Fixed bug with `.values` raising an error on a DataFrame with duplicate columns and
mixed dtypes, surfaced in GH4377
- Fixed bug with duplicate columns and type conversion in `read_json` when
`orient='split'`
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https://api.github.com/repos/pandas-dev/pandas/issues/4389 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4389/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4389/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4389/events | https://github.com/pandas-dev/pandas/issues/4389 | 17,314,377 | MDU6SXNzdWUxNzMxNDM3Nw== | 4,389 | DOC: only put bug fix references in release.rest and not in whatsnew | {
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"followers_url": "https://api.github.com/users/wesm... | 6 | 2013-07-28T17:06:40Z | 2013-09-21T12:00:22Z | 2013-09-20T23:09:13Z | CONTRIBUTOR | null | I think this is pretty duplicative and unless its a _major_ bug fix should be avoided (in whatsnew), though I am +1 for API/enhancements...etc
need a 1-time cleanout of v0.13.0 txt...then (let's leave prior version alone)
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In [9]: s = Series(randn(10), index=period_range('1/1/2001', periods=10))
In [10]: s
Out[10]:
2001-01-01 -0.677
2001-01-02 0.058
2001-01-03 -1.200
2001-01-04 -1.152
2001-01-05 -2.646
2001-01-06 -1.068
2001-01-07 -1.232
2001-01-08 0.452
2001-01-09 0.476
2001-01-10 -1.387
Freq: D, dtype: float... | {
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The `display.height` option is dperecated. It's value is interogated by
`get_conosole_size()`, whose only caller in the codebase summarily ignores
that bit of the `(width,height)` retval.
Another ugly ricochet from the `repr()` cluster***\* of 0.11. a tar ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4392 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4392/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4392/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4392/events | https://github.com/pandas-dev/pandas/pull/4392 | 17,317,224 | MDExOlB1bGxSZXF1ZXN0NzIyMDgyMA== | 4,392 | ENH: add git names to test_perf.py | {
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hashes to test between commits.
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] | closed | false | null | [] | null | 5 | 2013-07-28T23:08:57Z | 2013-08-01T14:54:36Z | 2013-07-28T23:21:42Z | NONE | null | Is it possible this will be included in 0.13?
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https://api.github.com/repos/pandas-dev/pandas/issues/4394 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4394/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4394/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4394/events | https://github.com/pandas-dev/pandas/pull/4394 | 17,319,050 | MDExOlB1bGxSZXF1ZXN0NzIyMTUzMQ== | 4,394 | BUG: Fix .iat indexing with a PeriodIndex GH4390 | {
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Interesting fixed this as well (only affects `get`)
```
In [1]: s = Series(randn(10),date_range('20130101',periods=10))
In [2]: s[0]
Out[2]: 1.1755210838393764
In [3]: s
Out[3]:
2013-01-01 1.175521
2013-01-02 0.007910
2013-01-03 -1.235595
2013-01-04 0.478245
2013-01-05 -0.140616
2013-01-0... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4395 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4395/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4395/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4395/events | https://github.com/pandas-dev/pandas/pull/4395 | 17,319,785 | MDExOlB1bGxSZXF1ZXN0NzIyMTgxOA== | 4,395 | DOC: added Google Finance to pandas.io.DataReader documentation | {
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and that assert better has some descriptive failure message (or to be replaced with assertEqual/eq_)?
```
======================================================================
FAIL: test_round_trip_frame (pandas.io... | {
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`assert (left.dtype == right.dtype),
"Left Dtype: {0}, Right Dtype: {1}".format(left.dtype,right.dtype)`
in `assert_*_equal`
will be useful in seeing what is actually failing as the 2nd parameter
gets raised in the `AssertionError(2nd parm)`
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"followers_url": "https://api.github.com/users/wesm... | 3 | 2013-07-29T03:09:20Z | 2013-10-21T21:35:44Z | 2013-10-21T21:35:44Z | MEMBER | null | I don't know if anyone's profiled the test suite, but we'd get major performance boosts if we wrote a Cython version of assert_almost_equal. Is there another open issue for this already?
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https://api.github.com/repos/pandas-dev/pandas/issues/4399 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4399/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4399/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4399/events | https://github.com/pandas-dev/pandas/pull/4399 | 17,346,509 | MDExOlB1bGxSZXF1ZXN0NzIzNTc2Nw== | 4,399 | DOC: typo fix | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4400 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4400/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4400/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4400/events | https://github.com/pandas-dev/pandas/issues/4400 | 17,347,416 | MDU6SXNzdWUxNzM0NzQxNg== | 4,400 | TST: more testing of indexing with sparse | {
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It would be nice if common operations like indexing/slicing is available for sparse dataframes as for their dense counterparts.
Thanks!
``` python
In [1]: import pandas as pd
In [2]: import numpy as np
In [3]: A = np.zeros((3,4))
In [4]: A[:] = np.nan
In [5]: A[2,3] = ... | {
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