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} | 9 | 2015-05-11T14:50:19Z | 2016-04-11T12:54:39Z | 2016-04-11T12:54:39Z | MEMBER | null | Ref: #10008.
Though this still under work (needs #10089 to simplify `get_dummies` flow), would like to discuss followings.
~~#### `.str.extract` note: overlaps with #11386~~
~~Currently it returns `Series` for a single group and `DataFrame` for multiples. To support `expand` kw, we have to choose :~~
~~1. Add `expand` option keeping existing behavior with warning for future change to `extract=True` (current impl).~~
~~2. Add `expand` option keeping existing behavior. Standardize `extract=None` (or other option) to select returning dimensionality automatically.~~
~~3. Add `expand` option with default `True` (or `False`). This breaks the API.~~
~~4. Make `Index.str.extract` return `MultiIndex` in multiple group case without adding `expand` option.~~
#### `.str.get_dummies`
1. Add `expand` kw with default `True`. Currently this always returns `DataFrame` (and raises `TypeError` in `Index`). This doesn't break an API (current impl).
2. Make `Index.str.get_dummies` return `MultiIndex` without adding `expand` option.
CC @mortada
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} | 1 | 2015-05-11T15:06:09Z | 2015-05-12T08:32:24Z | 2015-05-12T08:32:16Z | CONTRIBUTOR | null | I'd like to be able to manage my own connections and transactions with sqlalchemy:
``` python
def foo(connection):
pd.read_sql_query(query, con=connection)
def bar(connection, data):
data.to_sql(name='foo', con=connection)
def main():
with engine.connection() as conn, conn.begin():
bar(foo(), connection=conn)
bar(some_other_data, connection=conn)
```
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} | 34 | 2015-05-11T15:35:25Z | 2015-07-03T20:44:15Z | 2015-07-03T17:44:56Z | CONTRIBUTOR | null | Fixes #7877
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| null | 7 | 2015-05-11T18:58:14Z | 2015-05-16T15:37:58Z | 2015-05-11T19:03:18Z | CONTRIBUTOR | null | This is new in 0.16.1
``` python
In [1]: import pandas as pd
In [2]: pd.__version__
Out[2]: '0.16.1'
In [3]: f = pd.DataFrame({'a': [0, 10, 20, 30, 40], 'b': [5, 4 ,3, 2, 1]},
index=[1, 2, 3, 4, 4])
In [4]: f.dtypes
Out[4]:
a int64
b int64
dtype: object
In [6]: pd.DataFrame(columns=['a', 'b'], dtype=f.dtypes).dtypes
Out[6]:
a object
b object
dtype: object
```
Also other mechanisms to convey dtype information yield uninformative errors
``` python
In [7]: pd.DataFrame(columns=['a', 'b'], dtype={'a': 'i4', 'b': 'f4'}).dtypes
ValueError: entry not a 2- or 3- tuple
In [8]: pd.DataFrame(columns=['a', 'b'], dtype=[('a', 'i4'), ('b', 'f4')]).dtypes
NotImplementedError: compound dtypes are not implementedin the DataFrame constructor
```
Is there a way to create an empty DataFrame with given dtypes in 0.16.1?
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} | 12 | 2015-05-11T19:44:11Z | 2015-06-02T19:26:11Z | 2015-05-16T14:52:56Z | CONTRIBUTOR | null | fixes #10093
@jorisvandenbossche this covers `Series`, `DataFrame` and `Panel`, please take a look
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} | 5 | 2015-05-11T22:15:45Z | 2015-06-02T19:26:11Z | 2015-05-12T10:47:23Z | CONTRIBUTOR | null | closes #10087
I think this is fairly straightforward, however I am not sure if the prior code comparing `display.width` to 0 was correct... is `display.width` ever supposed to be set to 0? It looks suspiciously similar to a snippet from `Series.__unicode__()`, but that is looking at `display.max_rows`. Maybe it was brought over incorrectly?
If it should just be a simple comparison to None, not 0 as it was before, just let me know and I'll amend this.
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} | 15 | 2015-05-12T02:08:07Z | 2021-04-18T06:45:19Z | null | NONE | null | http://connor-johnson.com/2014/08/28/tidyr-and-pandas-gather-and-melt/
In the spirit of the excellent assign method, wondering if there is support for some tidyr style transformations?
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} | 18 | 2015-05-12T06:42:39Z | 2015-08-03T12:45:00Z | 2015-08-03T12:40:55Z | CONTRIBUTOR | null | closes #10086
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} | 3 | 2015-05-12T12:34:22Z | 2015-06-02T19:26:11Z | 2015-05-13T12:28:09Z | CONTRIBUTOR | null | mostly remove unused stuff
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| null | 4 | 2015-05-12T17:33:21Z | 2020-05-07T22:16:26Z | 2020-05-07T22:16:26Z | NONE | null | I have tried the example code found on the xlsxwriter webpage at http://xlsxwriter.readthedocs.org/en/latest/example_pandas_column_formats.html
However it does not format the columns as expected - they simply appear unformatted (no numeric rounding, percentages.)
It seems that calling set_column is being ignored. Is this because perhaps not to_excel() is doing some formatting itself which can't be overwritten?
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| null | 1 | 2015-05-12T17:59:31Z | 2015-05-12T19:06:45Z | 2015-05-12T19:06:33Z | NONE | null | Pandas will dump MultiIndex dataframes as invalid JSON in 0.16.0. For example this dataframe:
```
0
a c 1
b d 2
```
Will dump as: `{"0":{"["a","c"]":1,"["b","d"]":2}}`. You can see that the keys aren't escaping their double quote character and this isn't readable as JSON.
The following snippet illustrates how to recreate this:
``` python
import pandas
df = pandas.DataFrame([1,2], index=[['a','b'],['c','d']])
pandas.read_json(df.to_json())
...
ValueError: No ':' found when decoding object value
```
My pandas versions:
```
pandas.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.6.final.0
python-bits: 64
OS: Darwin
OS-release: 14.3.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
pandas: 0.16.0
nose: 1.3.6
Cython: None
numpy: 1.9.2
scipy: None
statsmodels: None
IPython: 3.1.0
sphinx: None
patsy: None
dateutil: 2.4.2
pytz: 2013b
bottleneck: None
tables: None
numexpr: None
matplotlib: 1.4.3
openpyxl: None
xlrd: None
xlwt: 1.0.0
xlsxwriter: 0.5.5
lxml: None
bs4: 4.3.2
html5lib: 0.999
httplib2: 0.9.1
apiclient: 1.4.0
sqlalchemy: 0.9.3
pymysql: None
psycopg2: None
```
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} | 2 | 2015-05-12T19:05:06Z | 2015-08-15T23:41:09Z | 2015-08-15T23:41:09Z | CONTRIBUTOR | null | this was changed in #9921 (worked prior to 0.16.0)
cc @evanpw
so using a multiple grouper where one item is a datetimelike fails as the `name in self.indices` fails. Instead `.get_group()` can be used to fix
```
In [1]: df = DataFrame({'A' : np.arange(5), 'B' : ['foo','bar','foo','bar','bar'], 'C' : Timestamp('20130101') })
In [2]: df
Out[2]:
A B C
0 0 foo 2013-01-01
1 1 bar 2013-01-01
2 2 foo 2013-01-01
3 3 bar 2013-01-01
4 4 bar 2013-01-01
In [3]: df.groupby(['B','C']).filter(lambda x: True)
Out[3]:
Empty DataFrame
Columns: [A, B, C]
Index: []
In [4]: df.groupby(['B']).filter(lambda x: True)
Out[4]:
A B C
0 0 foo 2013-01-01
1 1 bar 2013-01-01
2 2 foo 2013-01-01
3 3 bar 2013-01-01
4 4 bar 2013-01-01
In [5]: df.groupby(['C']).filter(lambda x: True)
Out[5]:
A B C
0 0 foo 2013-01-01
1 1 bar 2013-01-01
2 2 foo 2013-01-01
3 3 bar 2013-01-01
4 4 bar 2013-01-01
```
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} | 1 | 2015-05-12T20:00:01Z | 2015-06-23T14:11:23Z | 2015-06-23T14:11:23Z | CONTRIBUTOR | null | ```
In [12]: import pandas as pd
In [13]: mi = pd.MultiIndex.from_tuples([('A','a',1), ('A','a',2)],
names=['Upper','Lower','Num'])
In [14]: mi.drop_duplicates()
Out[14]:
MultiIndex(levels=[['A'], ['a'], [1, 2]],
labels=[[0, 0], [0, 0], [0, 1]])
In [16]: mi.names
Out[16]: FrozenList(['Upper', 'Lower', 'Num'])
In [18]: mi.drop_duplicates().names
Out[18]: FrozenList([None, None, None])
```
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} | 3 | 2015-05-12T21:05:54Z | 2015-08-07T00:15:40Z | 2015-06-23T14:11:23Z | CONTRIBUTOR | null | Closes #10115.
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} | 4 | 2015-05-12T21:22:27Z | 2018-09-23T12:11:02Z | 2018-09-23T12:11:02Z | CONTRIBUTOR | null | Here's the bug:
``` python
In [27]: idx = pd.date_range("2014-10-25 22:00:00", "2014-10-26 00:30:00",
freq="30T", tz="Europe/London")
In [28]: series = pd.Series(np.random.randn(len(idx)), index=idx)
In [31]: series
Out[31]:
2014-10-25 22:00:00+01:00 -0.874014
2014-10-25 22:30:00+01:00 1.316258
2014-10-25 23:00:00+01:00 -1.334616
2014-10-25 23:30:00+01:00 -1.200390
2014-10-26 00:00:00+01:00 -0.341764
2014-10-26 00:30:00+01:00 1.509091
Freq: 30T, dtype: float64
In [29]: series.resample('30T')
---------------------------------------------------------------------------
AmbiguousTimeError Traceback (most recent call last)
<ipython-input-29-bb9e86068ce1> in <module>()
----> 1 series.resample('30T')
/usr/local/lib/python2.7/dist-packages/pandas/core/generic.pyc in resample(self, rule, how, axis, fill_method, closed, label, convention, kind, loffset, limit, base)
3195 fill_method=fill_method, convention=convention,
3196 limit=limit, base=base)
-> 3197 return sampler.resample(self).__finalize__(self)
3198
3199 def first(self, offset):
/usr/local/lib/python2.7/dist-packages/pandas/tseries/resample.pyc in resample(self, obj)
83
84 if isinstance(ax, DatetimeIndex):
---> 85 rs = self._resample_timestamps()
86 elif isinstance(ax, PeriodIndex):
87 offset = to_offset(self.freq)
/usr/local/lib/python2.7/dist-packages/pandas/tseries/resample.pyc in _resample_timestamps(self, kind)
273 axlabels = self.ax
274
--> 275 self._get_binner_for_resample(kind=kind)
276 grouper = self.grouper
277 binner = self.binner
/usr/local/lib/python2.7/dist-packages/pandas/tseries/resample.pyc in _get_binner_for_resample(self, kind)
121 kind = self.kind
122 if kind is None or kind == 'timestamp':
--> 123 self.binner, bins, binlabels = self._get_time_bins(ax)
124 elif kind == 'timedelta':
125 self.binner, bins, binlabels = self._get_time_delta_bins(ax)
/usr/local/lib/python2.7/dist-packages/pandas/tseries/resample.pyc in _get_time_bins(self, ax)
162 first, last = ax.min(), ax.max()
163 first, last = _get_range_edges(first, last, self.freq, closed=self.closed,
--> 164 base=self.base)
165 tz = ax.tz
166 binner = labels = DatetimeIndex(freq=self.freq,
/usr/local/lib/python2.7/dist-packages/pandas/tseries/resample.pyc in _get_range_edges(first, last, offset, closed, base)
392 if (is_day and day_nanos % offset.nanos == 0) or not is_day:
393 return _adjust_dates_anchored(first, last, offset,
--> 394 closed=closed, base=base)
395
396 if not isinstance(offset, Tick): # and first.time() != last.time():
/usr/local/lib/python2.7/dist-packages/pandas/tseries/resample.pyc in _adjust_dates_anchored(first, last, offset, closed, base)
459
460 return (Timestamp(fresult).tz_localize(first_tzinfo),
--> 461 Timestamp(lresult).tz_localize(first_tzinfo))
462
463
pandas/tslib.pyx in pandas.tslib.Timestamp.tz_localize (pandas/tslib.c:10535)()
pandas/tslib.pyx in pandas.tslib.tz_localize_to_utc (pandas/tslib.c:50297)()
AmbiguousTimeError: Cannot infer dst time from Timestamp('2014-10-26 01:00:00'),
try using the 'ambiguous' argument
```
This is my hacky work-around:
``` python
In [35]: series.tz_convert('UTC').resample('30T').tz_convert('Europe/London')
Out[35]:
2014-10-25 22:00:00+01:00 -0.874014
2014-10-25 22:30:00+01:00 1.316258
2014-10-25 23:00:00+01:00 -1.334616
2014-10-25 23:30:00+01:00 -1.200390
2014-10-26 00:00:00+01:00 -0.341764
2014-10-26 00:30:00+01:00 1.509091
Freq: 30T, dtype: float64
```
The bug disappears if the end date of the index is beyond the DST boundary:
``` python
In [37]: idx = pd.date_range("2014-10-25 22:00:00", "2014-10-26 02:30:00",
freq="30T", tz="Europe/London")
In [38]: series = pd.Series(np.random.randn(len(idx)), index=idx)
In [39]: series.resample('30T')
Out[39]:
2014-10-25 22:00:00+01:00 -0.626598
2014-10-25 22:30:00+01:00 1.799176
2014-10-25 23:00:00+01:00 -0.388075
2014-10-25 23:30:00+01:00 0.641487
2014-10-26 00:00:00+01:00 -0.488203
2014-10-26 00:30:00+01:00 0.477301
2014-10-26 01:00:00+01:00 0.040997
2014-10-26 01:30:00+01:00 -1.996542
2014-10-26 01:00:00+00:00 -0.016655
2014-10-26 01:30:00+00:00 -1.445823
2014-10-26 02:00:00+00:00 -0.713523
2014-10-26 02:30:00+00:00 -0.122274
Freq: 30T, dtype: float64
```
All is fine if the start date is on a DST boundary but the end date is beyond the boundary:
``` python
In [47]: idx = pd.date_range("2014-10-26 00:30:00", "2014-10-26 02:30:00",
freq="30T", tz="Europe/London")
In [48]: series = pd.Series(np.random.randn(len(idx)), index=idx)
In [49]: series.resample('30T')
Out[49]:
2014-10-26 00:30:00+01:00 2.371051
2014-10-26 01:00:00+01:00 -0.033473
2014-10-26 01:30:00+01:00 -0.988517
2014-10-26 01:00:00+00:00 -0.664475
2014-10-26 01:30:00+00:00 0.865772
2014-10-26 02:00:00+00:00 -1.051219
2014-10-26 02:30:00+00:00 -1.478477
Freq: 30T, dtype: float64
```
(As always, I must say a huge THANK YOU to everyone working on Pandas; it really is a great bit of software)
```
In [50]: pd.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.9.final.0
python-bits: 64
OS: Linux
OS-release: 3.19.0-16-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
pandas: 0.16.1
nose: 1.3.4
Cython: 0.22
numpy: 1.9.2
scipy: 0.14.0
statsmodels: 0.6.1
IPython: 3.1.0
sphinx: 1.2.3
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.2
bottleneck: None
tables: 3.1.1
numexpr: 2.4
matplotlib: 1.4.3
openpyxl: None
xlrd: 0.9.2
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.3.2
html5lib: 0.999
httplib2: 0.9
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: 2.5.3 (dt dec pq3 ext)
```
Possibly related:
- #9623
- #9119
- #8744
- #5172
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} | 6 | 2015-05-13T02:08:14Z | 2017-11-09T12:31:26Z | 2017-11-09T11:49:39Z | NONE | null | X axis was inverted automatically and unexpectedly when plotting a series of data against another series of data using pandas.
My example code blow creates three plots, only some, not all, of which shows inverted x axis. I think this behavior is very confusing for users even if there was some rationale behind it. IMHO, automatic inversion of x axis is unnecessary because a user can use invert_xaxis() in case one wants to invert it. On [stackoverflow](http://stackoverflow.com/questions/29908874/x-axis-inverted-unexpectedly-by-pandas-plot), a workaround was suggested, but no direct solution.
```
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
df2 = pd.DataFrame(np.random.randn(10, 3), columns=["a", "b", "c"])
df3 = df2*1.1
df3.rename(columns={"a": "a*1.1", "b": "b*1.1", "c": "c*1.1"}, inplace=True)
df23 = df2.join(df3)
fig, ax_list = plt.subplots(1,3)
ax=ax_list[0]
df23[["a", "a*1.1"]].plot(ax=ax, x="a")
ax.axis('equal')
ax.set_title("(x,y)=(a,a*1.1)")
print ax.get_xlim() ## Added for clarity
ax=ax_list[1]
df23[["b", "b*1.1"]].plot(ax=ax, x="b")
ax.axis('equal')
ax.set_title("(x,y)=(b,b*1.1)")
print ax.get_xlim() ## Added for clarity
ax=ax_list[2]
df23[["c", "c*1.1"]].plot(ax=ax, x="c")
ax.axis('equal')
ax.set_title("(x,y)=(c,c*1.1)")
print ax.get_xlim() ## Added for clarity
```
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} | 9 | 2015-05-13T08:42:46Z | 2015-06-02T19:25:20Z | 2015-05-19T12:27:19Z | CONTRIBUTOR | null | Using pandas 0.16.1, tested in several environments:
``` python
>>> import pandas as pd
>>> s = pd.Series([0, 1])
>>> ax = s.plot(label='stuff')
>>> assert ax.lines[0].get_label() == 'stuff'
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AssertionError
```
This is a regression since 0.16.0. I think the problem is in this line in pandas.tools.plotting.MPLPlot._compute_plot_data():
`label = self.kwds.pop('label', None)`
It should read:
`label = self.label`
because the label has been popped before and stored in an attribute.
I want to make a pull request but it will take some time to install git, set up a development environment and get my fingers to relearn their way through it all so it will be a lot of opportunities to beat me.
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https://api.github.com/repos/pandas-dev/pandas/issues/10120 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10120/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10120/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10120/events | https://github.com/pandas-dev/pandas/issues/10120 | 75,915,306 | MDU6SXNzdWU3NTkxNTMwNg== | 10,120 | ERROR: test_creating_and_reading_multiple_sheets (pandas.io.tests.test_excel.ExcelReaderTests) | {
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| null | 9 | 2015-05-13T09:26:03Z | 2015-05-13T15:35:58Z | 2015-05-13T12:33:25Z | CONTRIBUTOR | null | #
## ERROR: test_creating_and_reading_multiple_sheets (pandas.io.tests.test_excel.ExcelReaderTests)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/io/tests/test_excel.py", line 474, in test_creating_and_reading_multiple_sheets
for sheetname, df in dfs.iteritems():
AttributeError: 'dict' object has no attribute 'iteritems'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/io/tests/test_excel.py", line 475, in test_creating_and_reading_multiple_sheets
df.to_excel(ew,sheetname)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/io/excel.py", line 619, in **exit**
self.close()
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/io/excel.py", line 623, in close
return self.save()
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/io/excel.py", line 651, in save
return self.book.save(self.path)
File "/usr/lib64/python3.3/site-packages/openpyxl/workbook/workbook.py", line 280, in save
save_workbook(self, filename)
File "/usr/lib64/python3.3/site-packages/openpyxl/writer/excel.py", line 211, in save_workbook
writer.save(filename)
File "/usr/lib64/python3.3/site-packages/openpyxl/writer/excel.py", line 194, in save
self.write_data(archive)
File "/usr/lib64/python3.3/site-packages/openpyxl/writer/excel.py", line 88, in write_data
archive.writestr(ARC_WORKBOOK_RELS, write_workbook_rels(self.workbook))
File "/usr/lib64/python3.3/site-packages/openpyxl/writer/workbook.py", line 316, in write_workbook_rels
i += 1
UnboundLocalError: local variable 'i' referenced before assignment
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https://api.github.com/repos/pandas-dev/pandas/issues/10121 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10121/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10121/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10121/events | https://github.com/pandas-dev/pandas/issues/10121 | 75,916,364 | MDU6SXNzdWU3NTkxNjM2NA== | 10,121 | Multiple test errors related to time/date/timezones | {
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} | 5 | 2015-05-13T09:28:37Z | 2015-06-02T19:25:20Z | 2015-05-15T20:26:36Z | CONTRIBUTOR | null | #
## ERROR: test moving from daylight savings to standard time
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_offsets.py", line 3898, in test_fallback_plural
expected_utc_offset=hrs_post
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_offsets.py", line 3845, in _test_all_offsets
self._test_offset(offset_name=name, offset_n=n, **kwds)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_offsets.py", line 3851, in _test_offset
self.assertTrue(get_utc_offset_hours(t) == expected_utc_offset)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_offsets.py", line 3809, in get_utc_offset_hours
return (o.days \* 24 \* 3600 + o.seconds) / 3600.0
AttributeError: 'NoneType' object has no attribute 'days'
#
## ERROR: test moving from standard to daylight savings
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_offsets.py", line 3909, in test_springforward_plural
expected_utc_offset=hrs_post
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_offsets.py", line 3845, in _test_all_offsets
self._test_offset(offset_name=name, offset_n=n, **kwds)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_offsets.py", line 3851, in _test_offset
self.assertTrue(get_utc_offset_hours(t) == expected_utc_offset)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_offsets.py", line 3809, in get_utc_offset_hours
return (o.days \* 24 \* 3600 + o.seconds) / 3600.0
AttributeError: 'NoneType' object has no attribute 'days'
#
## ERROR: test_timestamp_tz_convert (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 341, in test_timestamp_tz_convert
conv = idx[0].tz_convert(self.tzstr('US/Pacific'))
File "pandas/tslib.pyx", line 502, in pandas.tslib.Timestamp.tz_convert (pandas/tslib.c:10823)
TypeError: Cannot convert tz-naive Timestamp, use tz_localize to localize
#
## ERROR: test_utc_with_system_utc (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 848, in test_utc_with_system_utc
self.assertEqual(ts, ts.tz_convert(dateutil.tz.tzutc()))
File "pandas/tslib.pyx", line 502, in pandas.tslib.Timestamp.tz_convert (pandas/tslib.c:10823)
TypeError: Cannot convert tz-naive Timestamp, use tz_localize to localize
#
## ERROR: test_with_tz (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 382, in test_with_tz
central = dr.tz_convert(tz)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/index.py", line 1599, in tz_convert
raise TypeError('Cannot convert tz-naive timestamps, use '
TypeError: Cannot convert tz-naive timestamps, use tz_localize to localize
#
## ERROR: test_tz_convert_roundtrip (pandas.tseries.tests.test_timezones.TestTimeZones)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 1034, in test_tz_convert_roundtrip
reset = converted.tz_convert(None)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/index.py", line 1599, in tz_convert
raise TypeError('Cannot convert tz-naive timestamps, use '
TypeError: Cannot convert tz-naive timestamps, use tz_localize to localize
#
## ERROR: test_tz_convert_roundtrip (pandas.tseries.tests.test_tslib.TestTimestamp)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_tslib.py", line 312, in test_tz_convert_roundtrip
reset = converted.tz_convert(None)
File "pandas/tslib.pyx", line 502, in pandas.tslib.Timestamp.tz_convert (pandas/tslib.c:10823)
TypeError: Cannot convert tz-naive Timestamp, use tz_localize to localize
#
## FAIL: test_append_with_timezones_dateutil (pandas.io.tests.test_pytables.TestHDFStore)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/io/tests/test_pytables.py", line 2037, in test_append_with_timezones_dateutil
self.assertRaises(TypeError, store.append, 'df_tz', df)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 1576, in assertRaises
_callable(_args, *_kwargs)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 1640, in __exit__
raise AssertionError("{0} not raised.".format(name))
AssertionError: TypeError not raised.
#
## FAIL: test_period_resample_with_local_timezone_dateutil (pandas.tseries.tests.test_timeseries.TestTimeSeries)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timeseries.py", line 2049, in test_period_resample_with_local_timezone_dateutil
assert_series_equal(result, expected)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 686, in assert_series_equal
assert_index_equal(left.index, right.index, check_names=check_names)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 543, in assert_index_equal
right.dtype))
AssertionError: [index] left [int64 PeriodIndex(['2013-11-01', '2013-11-02'], dtype='int64', freq='D')], right [PeriodIndex(['2013-10-31', '2013-11-01'], dtype='int64', freq='D') int64]
#
## FAIL: test_ambiguous_flags (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 471, in test_ambiguous_flags
self.assert_numpy_array_equal(dr, localized)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 644, in assert_numpy_array_equal
'{0} is not equal to {1}.'.format(np_array, assert_equal))
AssertionError: DatetimeIndex(['2011-11-06 00:00:00', '2011-11-06 01:00:00',
'2011-11-06 02:00:00', '2011-11-06 03:00:00',
'2011-11-06 04:00:00'],
dtype='datetime64[ns]', freq='H', tz=None) is not equal to DatetimeIndex(['2011-11-06 00:00:00', '2011-11-06 01:00:00',
'2011-11-06 01:00:00', '2011-11-06 02:00:00',
'2011-11-06 03:00:00'],
dtype='datetime64[ns]', freq=None, tz=None).
#
## FAIL: test_ambiguous_infer (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 432, in test_ambiguous_infer
self.assertRaises(pytz.AmbiguousTimeError, dr.tz_localize, tz)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 1576, in assertRaises
_callable(_args, *_kwargs)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 1640, in __exit__
raise AssertionError("{0} not raised.".format(name))
AssertionError: AmbiguousTimeError not raised.
#
## FAIL: test_ambiguous_nat (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 517, in test_ambiguous_nat
self.assert_numpy_array_equal(di_test, localized)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 644, in assert_numpy_array_equal
'{0} is not equal to {1}.'.format(np_array, assert_equal))
AssertionError: DatetimeIndex(['2011-11-06 00:00:00-04:00', 'NaT',
'NaT', '2011-11-06 02:00:00-05:00',
'2011-11-06 03:00:00-05:00'],
dtype='datetime64[ns]', freq=None, tz='US/Eastern') is not equal to DatetimeIndex(['2011-11-06 00:00:00', '2011-11-06 01:00:00',
'2011-11-06 01:00:00', '2011-11-06 02:00:00',
'2011-11-06 03:00:00'],
dtype='datetime64[ns]', freq=None, tz=None).
#
## FAIL: test_datetimeindex_tz_nat (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 811, in test_datetimeindex_tz_nat
self.assertTrue(idx[0].tzinfo is not None)
AssertionError: False is not true
#
## FAIL: test_frame_no_datetime64_dtype (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 672, in test_frame_no_datetime64_dtype
self.assertEqual(e['B'].dtype, 'O')
AssertionError: dtype('<M8[ns]') != 'O'
#
## FAIL: test_index_with_timezone_repr (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 562, in test_index_with_timezone_repr
self.assertIn('2010-04-13 00:00:00', rng_repr)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 577, in assertIn
assert a in b, "%s: %r is not in %r" % (msg.format(a, b), a, b)
AssertionError: : '2010-04-13 00:00:00' is not in "DatetimeIndex(['2010-04-13', '2010-04-14', '2010-04-15', '2010-04-16',\n '2010-04-17', '2010-04-18', '2010-04-19', '2010-04-20',\n '2010-04-21', '2010-04-22', '2010-04-23', '2010-04-24',\n '2010-04-25', '2010-04-26', '2010-04-27', '2010-04-28',\n '2010-04-29', '2010-04-30', '2010-05-01', '2010-05-02',\n '2010-05-03', '2010-05-04', '2010-05-05', '2010-05-06'],\n dtype='datetime64[ns]', freq='D', tz=None)"
#
## FAIL: test_infer_tz (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 538, in test_infer_tz
self.assertRaises(Exception, tools._infer_tzinfo, start, end)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 1576, in assertRaises
_callable(_args, *_kwargs)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 1640, in __exit__
raise AssertionError("{0} not raised.".format(name))
AssertionError: Exception not raised.
#
## FAIL: test_localize_utc_conversion (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 107, in test_localize_utc_conversion
self.assert_numpy_array_equal(converted.asi8, expected_naive.asi8)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 644, in assert_numpy_array_equal
'{0} is not equal to {1}.'.format(np_array, assert_equal))
AssertionError: [1331337600000000000 1331339400000000000 1331341200000000000
1331343000000000000 1331344800000000000 1331346600000000000
1331348400000000000 1331350200000000000 1331352000000000000
1331353800000000000 1331355600000000000 1331357400000000000
1331359200000000000 1331361000000000000 1331362800000000000
1331364600000000000 1331366400000000000 1331368200000000000
1331370000000000000 1331371800000000000 1331373600000000000
1331375400000000000 1331377200000000000 1331379000000000000
1331380800000000000 1331382600000000000 1331384400000000000
1331386200000000000 1331388000000000000 1331389800000000000
1331391600000000000 1331393400000000000 1331395200000000000
1331397000000000000 1331398800000000000 1331400600000000000
1331402400000000000 1331404200000000000 1331406000000000000
1331407800000000000 1331409600000000000 1331411400000000000
1331413200000000000 1331415000000000000 1331416800000000000
1331418600000000000 1331420400000000000 1331422200000000000
1331424000000000000] is not equal to [1331355600000000000 1331357400000000000 1331359200000000000
1331361000000000000 1331362800000000000 1331364600000000000
1331366400000000000 1331368200000000000 1331370000000000000
1331371800000000000 1331373600000000000 1331375400000000000
1331377200000000000 1331379000000000000 1331380800000000000
1331382600000000000 1331384400000000000 1331386200000000000
1331388000000000000 1331389800000000000 1331391600000000000
1331393400000000000 1331395200000000000 1331397000000000000
1331398800000000000 1331400600000000000 1331402400000000000
1331404200000000000 1331406000000000000 1331407800000000000
1331409600000000000 1331411400000000000 1331413200000000000
1331415000000000000 1331416800000000000 1331418600000000000
1331420400000000000 1331422200000000000 1331424000000000000
1331425800000000000 1331427600000000000 1331429400000000000
1331431200000000000 1331433000000000000 1331434800000000000
1331436600000000000 1331438400000000000 1331440200000000000
1331442000000000000].
#
## FAIL: test_localize_utc_conversion_explicit (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 122, in test_localize_utc_conversion_explicit
self.assertTrue(np.array_equal(converted.asi8, expected_naive.asi8))
AssertionError: False is not true
#
## FAIL: test_timedelta_push_over_dst_boundary (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 184, in test_timedelta_push_over_dst_boundary
self.assertEqual(result, expected)
AssertionError: Timestamp('2012-03-11 04:00:00') != Timestamp('2012-03-11 05:00:00')
#
## FAIL: test_timedelta_push_over_dst_boundary_explicit (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 197, in test_timedelta_push_over_dst_boundary_explicit
self.assertEqual(result, expected)
AssertionError: Timestamp('2012-03-11 04:00:00') != Timestamp('2012-03-11 05:00:00')
#
## FAIL: test_tz_localize_dti (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 210, in test_tz_localize_dti
self.assert_numpy_array_equal(dti2.values, dti_utc.values)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 644, in assert_numpy_array_equal
'{0} is not equal to {1}.'.format(np_array, assert_equal))
AssertionError: ['2005-01-01T01:00:00.000000000+0100' '2005-01-01T01:00:00.001000000+0100'
'2005-01-01T01:00:00.002000000+0100' ...,
'2005-01-01T01:00:30.254000000+0100' '2005-01-01T01:00:30.255000000+0100'
'2005-01-01T01:00:30.256000000+0100'] is not equal to ['2005-01-01T06:00:00.000000000+0100' '2005-01-01T06:00:00.001000000+0100'
'2005-01-01T06:00:00.002000000+0100' ...,
'2005-01-01T06:00:30.254000000+0100' '2005-01-01T06:00:30.255000000+0100'
'2005-01-01T06:00:30.256000000+0100'].
#
## FAIL: test_utc_box_timestamp_and_localize (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 335, in test_utc_box_timestamp_and_localize
self.assertTrue('EDT' in repr(rng_eastern[0].tzinfo) or 'tzfile' in repr(rng_eastern[0].tzinfo))
AssertionError: False is not true
#
## FAIL: test_with_tz_ambiguous_times (pandas.tseries.tests.test_timezones.TestTimeZoneSupportDateutil)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 411, in test_with_tz_ambiguous_times
self.assertRaises(pytz.NonExistentTimeError, dr.tz_localize, tz)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 1576, in assertRaises
_callable(_args, *_kwargs)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 1640, in __exit__
raise AssertionError("{0} not raised.".format(name))
AssertionError: NonExistentTimeError not raised.
#
## FAIL: test_tz_localize_roundtrip (pandas.tseries.tests.test_timezones.TestTimeZones)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_timezones.py", line 963, in test_tz_localize_roundtrip
localized.tz_localize(tz)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 1640, in **exit**
raise AssertionError("{0} not raised.".format(name))
AssertionError: TypeError not raised.
#
## FAIL: test_constructor (pandas.tseries.tests.test_tslib.TestTimestamp)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_tslib.py", line 60, in test_constructor
self.assertEqual(result.value, expected_tz)
AssertionError: 1404205200000000000 != 1404230400000000000
#
## FAIL: test_repr (pandas.tseries.tests.test_tslib.TestTimestamp)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_tslib.py", line 196, in test_repr
self.assertIn(tz_repr, repr(date_tz))
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 577, in assertIn
assert a in b, "%s: %r is not in %r" % (msg.format(a, b), a, b)
AssertionError: : '/America/Los_Angeles' is not in "Timestamp('2014-03-07 00:00:00')"
#
## FAIL: test_tz_localize_roundtrip (pandas.tseries.tests.test_tslib.TestTimestamp)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tseries/tests/test_tslib.py", line 299, in test_tz_localize_roundtrip
localized.tz_localize(tz)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 1640, in **exit**
raise AssertionError("{0} not raised.".format(name))
AssertionError: TypeError not raised.
#
## FAIL: test_getitem_setitem_datetime_tz_dateutil (pandas.tests.test_series.TestSeries)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tests/test_series.py", line 5431, in test_getitem_setitem_datetime_tz_dateutil
assert_series_equal(result, ts)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/util/testing.py", line 681, in assert_series_equal
assert_almost_equal(left.values, right.values, check_less_precise)
File "das/src/testing.pyx", line 58, in pandas._testing.assert_almost_equal (pandas/src/testing.c:2758)
File "das/src/testing.pyx", line 93, in pandas._testing.assert_almost_equal (pandas/src/testing.c:1843)
File "das/src/testing.pyx", line 140, in pandas._testing.assert_almost_equal (pandas/src/testing.c:2590)
AssertionError: expected -0.71627 but got -0.58678, with decimal 5
---
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| null | 2 | 2015-05-13T09:54:14Z | 2015-05-13T10:23:43Z | 2015-05-13T10:10:48Z | NONE | null | World Bank provides latitude and longitude as strings (and an empty string as a missing value). It's inconvenient so, I parse it to floats. Additionally, I added some description to the `wb.get_countries` function.
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} | 6 | 2015-05-13T10:34:46Z | 2015-05-13T11:18:10Z | 2015-05-13T10:43:14Z | NONE | null | I see #1807 issue reoccurring in my setup:
```
>>> Series(Series([1,3,4]).unique())
0 1
1 3
2 4
dtype: int64
```
And this doesn't return anything:
```
>>> Series(Series([1,3,4]).unique()).sort()
```
## INSTALLED VERSIONS
commit: None
python: 2.7.5.final.0
python-bits: 64
OS: Linux
OS-release: 3.14.4-200.fc20.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
pandas: 0.16.1-13-gf6c7d89
nose: 1.3.0
Cython: 0.21.1
numpy: 1.8.2
scipy: 0.12.1
statsmodels: None
IPython: 0.13.2
sphinx: None
patsy: None
dateutil: 1.5
pytz: 2012d
bottleneck: None
tables: 3.0.0
numexpr: 2.2.2
matplotlib: 1.3.1
openpyxl: None
xlrd: 0.9.3
xlwt: None
xlsxwriter: 0.7.2
lxml: None
bs4: 4.3.2
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: 2.5.1 (dt dec pq3 ext
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https://api.github.com/repos/pandas-dev/pandas/issues/10124 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10124/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10124/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10124/events | https://github.com/pandas-dev/pandas/pull/10124 | 75,960,058 | MDExOlB1bGxSZXF1ZXN0MzUzMTkwOTE= | 10,124 | BUG: Filter/transform fail in some cases when multi-grouping with a datetime-like key | {
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} | 5 | 2015-05-13T11:58:09Z | 2015-07-30T17:14:50Z | 2015-07-30T16:09:29Z | CONTRIBUTOR | null | Fixes GH #10114, and a related problem in transform which was already present in 0.16.0
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} | 12 | 2015-05-13T15:46:42Z | 2015-09-30T18:58:36Z | 2015-09-22T14:12:52Z | CONTRIBUTOR | null | xref #8342, #11008, #9747
a branch to repro on travis: https://github.com/jreback/pandas/commit/262c5f13c9cde338ae5c8d93e0de1db00d28c5e9
```
nosetests pandas.io.tests.test_excel
E...................S./usr/lib64/python3.4/site-packages/openpyxl/styles/styleable.py:111: UserWarning: Use formatting objects such as font directly
warn("Use formatting objects such as font directly")
/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
ES/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E./usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E.....S...................S../usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
E/usr/lib64/python3.4/site-packages/openpyxl/styles/__init__.py:52: UserWarning: Call to deprecated function or class copy (Copy formatting objects like font directly).
def copy(self):
ESSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSS.....S.................................................
======================================================================
ERROR: test_creating_and_reading_multiple_sheets (pandas.io.tests.test_excel.ExcelReaderTests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 474, in test_creating_and_reading_multiple_sheets
for sheetname, df in dfs.iteritems():
AttributeError: 'dict' object has no attribute 'iteritems'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 475, in test_creating_and_reading_multiple_sheets
df.to_excel(ew,sheetname)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 619, in __exit__
self.close()
File "/local/src/opensource/pandas/pandas/io/excel.py", line 623, in close
return self.save()
File "/local/src/opensource/pandas/pandas/io/excel.py", line 651, in save
return self.book.save(self.path)
File "/usr/lib64/python3.4/site-packages/openpyxl/workbook/workbook.py", line 298, in save
save_workbook(self, filename)
File "/usr/lib64/python3.4/site-packages/openpyxl/writer/excel.py", line 196, in save_workbook
writer.save(filename, as_template=as_template)
File "/usr/lib64/python3.4/site-packages/openpyxl/writer/excel.py", line 179, in save
self.write_data(archive, as_template=as_template)
File "/usr/lib64/python3.4/site-packages/openpyxl/writer/excel.py", line 65, in write_data
archive.writestr(ARC_WORKBOOK_RELS, write_workbook_rels(self.workbook))
File "/usr/lib64/python3.4/site-packages/openpyxl/writer/workbook.py", line 319, in write_workbook_rels
i += 1
UnboundLocalError: local variable 'i' referenced before assignment
======================================================================
ERROR: test_basics_with_nan (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 641, in test_basics_with_nan
self.frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_bool_types (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 688, in test_bool_types
frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_colaliases (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 734, in test_colaliases
self.frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_datetimes (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1218, in test_datetimes
write_frame.to_excel(path, 'Sheet1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_duplicated_columns (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1178, in test_duplicated_columns
write_frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_excel_date_datetime_format (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 864, in test_excel_date_datetime_format
df.to_excel(writer1, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_excel_roundtrip_datetime (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 838, in test_excel_roundtrip_datetime
tsf.to_excel(path, 'test1', merge_cells=self.merge_cells)
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_excel_roundtrip_indexname (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 820, in test_excel_roundtrip_indexname
df.to_excel(path, merge_cells=self.merge_cells)
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_excel_sheet_by_name_raise (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 552, in test_excel_sheet_by_name_raise
gt.to_excel(pth)
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_excelwriter_contextmanager (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 564, in test_excelwriter_contextmanager
self.frame.to_excel(writer, 'Data1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_float_types (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 676, in test_float_types
frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_inf_roundtrip (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 698, in test_inf_roundtrip
frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_int_types (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 656, in test_int_types
frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_mixed (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 621, in test_mixed
self.mixed_frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_roundtrip (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 579, in test_roundtrip
self.frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_roundtrip_indexlabels (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 755, in test_roundtrip_indexlabels
self.frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_sheets (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 709, in test_sheets
self.frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_swapped_columns (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1192, in test_swapped_columns
write_frame.to_excel(path, 'test1', columns=['B', 'A'])
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_float_format (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 969, in test_to_excel_float_format
df.to_excel(filename, 'test1', float_format='%.2f')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_multiindex (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 905, in test_to_excel_multiindex
frame.to_excel(path, 'test1', header=False)
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_multiindex_dates (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 927, in test_to_excel_multiindex_dates
tsframe.to_excel(path, 'test1', merge_cells=self.merge_cells)
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_multiindex_no_write_index (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 952, in test_to_excel_multiindex_no_write_index
frame2.to_excel(path, 'test1', index=False)
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_output_encoding (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 987, in test_to_excel_output_encoding
df.to_excel(filename, sheet_name='TestSheet', encoding='utf8')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_periodindex (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 889, in test_to_excel_periodindex
xp.to_excel(path, 'sht1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_unicode_filename (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1005, in test_to_excel_unicode_filename
df.to_excel(filename, 'test1', float_format='%.2f')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_tsframe (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 632, in test_tsframe
df.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_write_cells_merge_styled (pandas.io.tests.test_excel.Openpyxl2Tests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1229, in wrapped
orig_method(self, *args, **kwargs)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1382, in test_write_cells_merge_styled
writer.write_cells(initial_cells, sheet_name=sheet_name)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_basics_with_nan (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 641, in test_basics_with_nan
self.frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_bool_types (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 688, in test_bool_types
frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_colaliases (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 734, in test_colaliases
self.frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_datetimes (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1218, in test_datetimes
write_frame.to_excel(path, 'Sheet1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_duplicated_columns (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1178, in test_duplicated_columns
write_frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_excel_010_hemstring (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1139, in test_excel_010_hemstring
res = roundtrip(df)
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1128, in roundtrip
df.to_excel(path, header=header, merge_cells=self.merge_cells)
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_excel_date_datetime_format (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 864, in test_excel_date_datetime_format
df.to_excel(writer1, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_excel_roundtrip_datetime (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 838, in test_excel_roundtrip_datetime
tsf.to_excel(path, 'test1', merge_cells=self.merge_cells)
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_excel_roundtrip_indexname (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 820, in test_excel_roundtrip_indexname
df.to_excel(path, merge_cells=self.merge_cells)
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_excel_sheet_by_name_raise (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 552, in test_excel_sheet_by_name_raise
gt.to_excel(pth)
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_excelwriter_contextmanager (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 564, in test_excelwriter_contextmanager
self.frame.to_excel(writer, 'Data1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_float_types (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 676, in test_float_types
frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_inf_roundtrip (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 698, in test_inf_roundtrip
frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_int_types (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 656, in test_int_types
frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_mixed (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 621, in test_mixed
self.mixed_frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_roundtrip (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 579, in test_roundtrip
self.frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_roundtrip_indexlabels (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 755, in test_roundtrip_indexlabels
self.frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_sheets (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 709, in test_sheets
self.frame.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_swapped_columns (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1192, in test_swapped_columns
write_frame.to_excel(path, 'test1', columns=['B', 'A'])
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_float_format (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 969, in test_to_excel_float_format
df.to_excel(filename, 'test1', float_format='%.2f')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_multiindex (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 905, in test_to_excel_multiindex
frame.to_excel(path, 'test1', header=False)
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_multiindex_dates (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 927, in test_to_excel_multiindex_dates
tsframe.to_excel(path, 'test1', merge_cells=self.merge_cells)
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_multiindex_no_write_index (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 952, in test_to_excel_multiindex_no_write_index
frame2.to_excel(path, 'test1', index=False)
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_output_encoding (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 987, in test_to_excel_output_encoding
df.to_excel(filename, sheet_name='TestSheet', encoding='utf8')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_periodindex (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 889, in test_to_excel_periodindex
xp.to_excel(path, 'sht1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_to_excel_unicode_filename (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 1005, in test_to_excel_unicode_filename
df.to_excel(filename, 'test1', float_format='%.2f')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
======================================================================
ERROR: test_tsframe (pandas.io.tests.test_excel.OpenpyxlTests_NoMerge)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/local/src/opensource/pandas/pandas/io/tests/test_excel.py", line 632, in test_tsframe
df.to_excel(path, 'test1')
File "/local/src/opensource/pandas/pandas/core/frame.py", line 1267, in to_excel
startrow=startrow, startcol=startcol)
File "/local/src/opensource/pandas/pandas/io/excel.py", line 778, in write_cells
xcell.style = xcell.style.copy(**style_kwargs)
File "/usr/lib64/python3.4/site-packages/openpyxl/compat/__init__.py", line 67, in new_func
return obj(*args, **kwargs)
TypeError: copy() got an unexpected keyword argument 'font'
----------------------------------------------------------------------
Ran 216 tests in 3.809s
FAILED (SKIP=60, errors=55)
```
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} | 6 | 2015-05-13T16:21:21Z | 2015-12-17T19:09:51Z | 2015-06-03T19:03:09Z | CONTRIBUTOR | null | In pandas 0.16.1, I get a ValueError when trying to mask an empty DataFrame:
``` python
>>> import pandas as pd
>>> df = pd.DataFrame()
>>> df[df>0]
Traceback (most recent call last):
File "<ipython-input-3-efe84c9ebabc>", line 1, in <module>
df[df>0]
File "C:\Python27\lib\site-packages\pandas\core\frame.py", line 1787, in __getitem__
return self._getitem_frame(key)
File "C:\Python27\lib\site-packages\pandas\core\frame.py", line 1859, in _getitem_frame
raise ValueError('Must pass DataFrame with boolean values only')
ValueError: Must pass DataFrame with boolean values only
```
Using 'where' works as expected:
``` python
>>> df.where(df>0)
Out[4]:
Empty DataFrame
Columns: []
Index: []
```
Also, masking a Series works as expected:
``` python
>>> ts = pd.Series()
>>> ts[ts>0]
Out[6]: Series([], dtype: float64)
```
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} | 2 | 2015-05-13T16:58:51Z | 2016-12-19T00:26:09Z | 2016-12-19T00:26:08Z | CONTRIBUTOR | null | ``` python
In [62]: index = pd.MultiIndex.from_arrays([['a', 'b', 'c'], [1, 2]])
In [63]: index
Out[63]:
MultiIndex(levels=[['a', 'b', 'c'], [1, 2]],
labels=[[0, 1, 2], [0, 1]])
```
Probably not what the user wants, and we rely on them being the same length in, e.g. `index.shape` which will raise a ValueError if you access it.
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} | 5 | 2015-05-13T20:05:26Z | 2021-04-18T06:45:53Z | null | NONE | null | #10063 doesn't appear to have been completely fixed. While the exact example I gave now works (the resample), what if instead of a resample I had wanted to do a tshift? I would have wanted to be able to do `df.groupby(level='symbol').tshift(1, 'D')`, which still returns an empty DataFrame. Here, there's no aggregating in the time dimension so the TimeGrouper syntax that was the proposed solution wouldn't make sense.
I also don't understand why the `df.groupby([pd.Grouper(level='symbol'), pd.Grouper(level='dt', freq='M')]).mean()` syntax is necessary instead of simply being able to do `df.groupby(level='symbol').resample('M', how='mean')`? The latter seems like much better design.
```
df = DataFrame({'A' : 1 },index=pd.MultiIndex.from_product([list('ab'),date_range('20130101',periods=80)],names=['one','two']))
df.groupby([pd.Grouper(level='one'),pd.Grouper(level='two',freq='M')]).tshift(-1,'M')
```
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} | 59 | 2015-05-13T23:43:47Z | 2015-06-06T03:14:27Z | 2015-06-06T03:14:27Z | CONTRIBUTOR | null | Today @shoyer and I were talking about a new "protocol" that will let us sidestep the whole macro / method chaining issue. The basic idea is that pandas objects define a `pipe` method (ideally other libraries will implement this to, assuming this is useful).
Based on the discussions below, we're leaning towards a method like
``` python
def pipe(self, func, *args, **kwargs):
pipe_func = getattr(func, '__pipe_func__', func)
return pipe_func(self, *args, **kwargs)
```
That's it. This lets you write code like:
``` python
import seaborn as sns
(sns.load_dataset('iris')
.query("sepal_length > 5")
.assign(sepal_ratio = lambda df: df.sepal_length / df.sepal_width)
.pipe(lambda df: sns.violinplot(x='species', y='sepal_ratio', data=df))
)
```
seaborn didn't have to do anything! If the DataFrame is the first argument to the function, things are even simpler:
``` python
def f(x):
return x / 2
df['sepal_length'].pipe(f)
```
Users or libraries can work around the need for the (somewhat ugly) `lambda _:`, by using the `__pipe_func__` attribute of the function being `pipe`d in. This is where a protocol (de facto or official) would be useful, since libraries that know nothing else about each other can rely on it. As an example, consider seaborn's violin plot, which expects a DataFrame as its fourth argument, `data`. Seaborn can define a simple decorator to attach a `__pipe_func__` attribute, allowing _it_ to define how it expects to be `pipe`d to.
``` python
def pipeable(func):
def pipe_func(data, *args, **kwargs):
return func(*args, data=data, **kwargs)
func.__pipe_func__ = pipe_func
return func
# now we decorate all the Seaborn methods as pipeable
@pipeable
def violinplot(x=None, y=None, hue=None, data=None, ...):
# ...
```
And users write
``` python
(sns.load_dataset('iris')
.query("sepal_length > 5")
.assign(sepal_ratio = lambda x: x.sepal_length / x.sepal_width)
.pipe(sns.violinplot, x='species', y='sepal_ratio')
)
```
### Why?
Heavily nested function calls are bad. They're hard to read, and can easily introduce bugs. Consider:
``` python
# f, g, and h are functions that take and receive a DataFrame
result = f(g(h(df), arg1=1), arg2=2, arg3=3)
```
For pandas, the approach has been to add `f`, `g`, and `h` as methods to (say) `DataFrame`
``` python
(df.h()
.g(arg1=1)
.f(arg2=2, arg3=3)
)
```
The code is certainly cleaner. It reads and flows top to bottom instead of inside-out. The function arguments are next to the function calls. But there's a hidden cost. DataFrame has something like 200+ methods, which is crazy. It's less flexible for users since it's hard to get their own functions into pipelines (short of monkey-patching). With `.pipe`, we can
``` python
(df.pipe(h)
.pipe(g, arg1=1)
.pipe(f, arg2=2, arg3=3)
)
```
The other way around the nested calls is using temporary variables:
``` python
r1 = h(df)
r2 = g(r1, arg1=1)
r3 = f(r2, arg2=2, arg3=3)
```
Which is better, but not as good as the `.pipe` solution.
---
A relevant thread on python-ideas, started by @mrocklin: https://mail.python.org/pipermail/python-ideas/2015-March/032745.html
This doesn't achieve everything macros could. We still can't do things like `df.plot(x=x_col, y=y_col)` where `x_col` and `y_col` are captured by `df`'s namespace. But it may be good enough.
Going to cc a bunch of people here, who've had interest in the past.
@shoyer
@mrocklin
@datnamer
@dalejung
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} | 7 | 2015-05-14T02:56:38Z | 2015-08-18T12:44:40Z | 2015-05-19T12:27:19Z | CONTRIBUTOR | null | Closes https://github.com/pydata/pandas/issues/10119, a regression in 0.16.1
Basically `Series.plot(label='foo')` isn't actually setting the label.
I want to look at one more thing. With this fix you'd need
``` python
s.plot(label='foo', legend=True
```
to get the legend to actually show up. I can't remember what the old behavior was. At least for seaborn, setting a label implies that the legend should be drawn (e.g. `sns.kdeplot(s, label='foo')`)
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} | 8 | 2015-05-14T10:42:15Z | 2015-09-19T00:38:07Z | 2015-06-05T22:03:42Z | CONTRIBUTOR | null | Example:
``` .python
>>> df = pd.DataFrame({'a' : pd.Categorical('xyxy'), 'b' : 1, 'c' : 2})
>>> df.groupby(['a', 'b']).get_group(('x', 1))
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/evanpw/Workspace/pandas/pandas/core/groupby.py", line 601, in get_group
inds = self._get_index(name)
File "/home/evanpw/Workspace/pandas/pandas/core/groupby.py", line 429, in _get_index
sample = next(iter(self.indices))
File "/home/evanpw/Workspace/pandas/pandas/core/groupby.py", line 414, in indices
return self.grouper.indices
File "pandas/src/properties.pyx", line 34, in pandas.lib.cache_readonly.__get__ (pandas/lib.c:41912)
File "/home/evanpw/Workspace/pandas/pandas/core/groupby.py", line 1305, in indices
return _get_indices_dict(label_list, keys)
File "/home/evanpw/Workspace/pandas/pandas/core/groupby.py", line 3762, in _get_indices_dict
return lib.indices_fast(sorter, group_index, keys, sorted_labels)
File "pandas/lib.pyx", line 1385, in pandas.lib.indices_fast (pandas/lib.c:23843)
TypeError: Cannot convert Categorical to numpy.ndarray
```
The problem is that `Grouping.group_index` is a CategoricalIndex, so calling `get_values()` gives you a `Categorical`, which needs one more application of `get_values()` to get an `ndarray`
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} | 7 | 2015-05-14T12:57:00Z | 2015-06-10T13:40:52Z | 2015-06-09T10:49:18Z | CONTRIBUTOR | null | Fixes GH #9565. I also made the handling of out-of-range integers consistent with the C engine: parse as a string rather than a double.
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} | 11 | 2015-05-14T14:48:28Z | 2018-07-07T11:19:33Z | 2018-07-07T11:19:28Z | NONE | null | When I pass cursor as data to DataFrame constructor an error occurs.
```
cursor = sqlite.execute(sql)
pd.DataFrame(cursor)
/usr/lib/python3/dist-packages/pandas/core/frame.py in __init__(self, data, index, columns, dtype, copy)
255 copy=copy)
256 elif isinstance(data, collections.Iterator):
--> 257 raise TypeError("data argument can't be an iterator")
258 else:
259 try:
TypeError: data argument can't be an iterator
```
But normal generators is accepted
```
def gen():
yield (1,2,3)
yield (4,5,6)
yield (7,8,9)
pd.DataFrame(gen())
Out[171]:
0 1 2
0 1 2 3
1 4 5 6
2 7 8 9
```
It feels like inconsistence.
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} | 4 | 2015-05-14T14:53:02Z | 2015-11-13T05:40:17Z | 2015-05-14T15:55:15Z | MEMBER | null | Related to #10081. Make a short path using numpy's string funcs when all the target values are strings. Otherwise, use current path.
Followings are current comparison results:
```
import pandas as pd
import numpy as np
import string
import random
np.random.seed(1)
s = [''.join([random.choice(string.ascii_letters + string.digits) for i in range(3)]) for i in range(1000000)]
# s_str uses short path
s_str = pd.Series(s)
# set object
s[-1] = 1
# s_obj uses current path
s_obj = pd.Series(s)
```
```
%timeit s_str.str.lower()
#1 loops, best of 3: 696 ms per loop
%timeit s_obj.str.lower()
#1 loops, best of 3: 1.46 s per loop
%timeit s_str.str.split('a')
#1 loops, best of 3: 1.55 s per loop
%timeit s_obj.str.split('a')
#1 loops, best of 3: 3.52 s per loop
```
The logic has an overhead to check whether target values are all-string using `lib.is_string_array`. But this should be speed-up in most cases because it takes relatively shorter time than string ops, and (I believe) values should be all-string in most cases.
```
%timeit pd.lib.is_string_array(s_str.values)
#10 loops, best of 3: 21.9 ms per loop
```
If it looks OK, I'll work on all the funcs which is supported by numpy.
- [ ] Add all numpy funcs
- http://docs.scipy.org/doc/numpy/reference/routines.char.html
- [ ] Add tests to check numpy results for all-string values are identical as current results.
- [ ] Add vbench (both for all-string and object-included)
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} | 0 | 2015-05-14T15:53:07Z | 2015-06-02T19:26:11Z | 2015-05-19T21:21:48Z | MEMBER | null | Further work on #9886
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} | 2 | 2015-05-14T16:14:04Z | 2015-05-14T16:22:41Z | 2015-05-14T16:22:12Z | NONE | null | In pandas/pandas/io/parsers.py line 1000, np.uin8 is referred. It is an inexistent member in numpy. I suppose it's a typo for np.uint8.
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} | 1 | 2015-05-14T19:34:37Z | 2015-06-04T13:50:27Z | 2015-06-04T13:50:27Z | CONTRIBUTOR | null | from [SO](http://stackoverflow.com/questions/30245145/pandas-groupby-apply-vs-agggregate-with-missing-categories)
```
missing = pd.Categorical(list('aaa'), categories=['a', 'b'])
dense = pd.Categorical(list('abc'))
values = np.arange(len(dense))
df = pd.DataFrame({'missing': missing, 'dense': dense, 'values': values})
grouped = df.groupby(['missing', 'dense'])
# does reindex output for missing categories
grouped.mean()
grouped.agg(np.mean)
# does not reindex the output for the missing categories
grouped.apply(lambda chunk: np.mean(chunk))
```
So the `_wrap_applied_output` need a call to `_reindex_output` as a post-processing step.
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| null | 9 | 2015-05-14T21:20:10Z | 2015-06-30T10:55:21Z | 2015-05-29T08:40:01Z | MEMBER | null | I am not sure I understood the last comment in [the previous pull request](https://github.com/pydata/pandas/pull/9526), but anyway this is a rebased version.
In the previous PR I proposed to simply make the `__get__` of `is_unique` directly rely on `self.initialized`, but I am no more so sure it is a good idea, since the current status is slightly redundant but clearer (and coherent with the use of "is_monotonic").
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https://api.github.com/repos/pandas-dev/pandas/issues/10140 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10140/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10140/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10140/events | https://github.com/pandas-dev/pandas/issues/10140 | 76,519,053 | MDU6SXNzdWU3NjUxOTA1Mw== | 10,140 | Grouping by pd.cut() results creates a categorical index | {
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} | 12 | 2015-05-14T23:03:39Z | 2015-06-20T12:48:09Z | 2015-06-20T12:48:09Z | NONE | null | After upgrading from 0.16.0 to 0.16.1, some of my plotting stopped functioning right, and after debugging I figured out that it was an issue with the groupby results---namely, that they're getting a `CategoricalIndex` even though they're being grouped by a number.
This is basically what I do in my code (simplified for this example):
```
df = pd.DataFrame()
df['x'] = 100 * np.random.random(100)
df['y'] = df.x**2
binedges = np.arange(0,110,10)
binlabels = np.arange(5,105,10)
z = df.groupby(pd.cut(df.x,bins=binedges ,labels=binlabels )).y.mean()
```
And here's what that produces:
```
x
5 21.809599
15 215.432515
25 556.803743
35 1282.261483
45 1941.166247
55 3104.923704
65 4256.942052
75 5862.686054
85 7304.835127
95 8810.194492
Name: y, dtype: float64
```
When I tried plotting this, the scale was all messed up---it was treating each of the 10 bins as an element of `[0,1,2,...,9]`, which wasn't apparent until I tried changing the `xticks` parameter and everything went screwy. Took a while to debug, but finally found the culprit, by looking at `z.index`:
```
CategoricalIndex([5, 15, 25, 35, 45, 55, 65, 75, 85, 95], categories=[5, 15, 25, 35, 45, 55, 65, 75, ...], ordered=True, name=u'x', dtype='category')
```
This isn't the desired behavior, right? I know the `CategoricalIndex` feature is new, but I don't think this was an intended feature. This same code previously produced an `Int64Index` that would plot just fine, and there's no use case I can see for changing that. Or if that was what was intended, is there any way to select an `Int64Index` instead (other than converting it after the fact)?
UPDATE: Also note that this screws up using pd.cut() to create bins in a dataframe, because the indices don't line up afterward. So doing something like
```
df['bin'] = pd.cut(df.x,bins=mybins,labels=mylabels)
```
will just result in an empty column. So I can't imagine that this is the correct behavior.
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} | 1 | 2015-05-15T02:03:35Z | 2015-06-02T19:26:12Z | 2015-05-15T13:09:15Z | CONTRIBUTOR | null | found quite a few more under `pandas/tseries/` ... this should be it for now :)
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} | 12 | 2015-05-15T04:33:27Z | 2015-06-04T15:18:02Z | 2015-06-04T13:50:27Z | CONTRIBUTOR | null | closes #10138
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} | 8 | 2015-05-15T07:42:27Z | 2018-06-26T22:53:49Z | 2018-06-26T22:53:49Z | CONTRIBUTOR | null | I am relatively new to pandas, but have been using raw HDF5 files for a long itme, so apologies if this feature or something equivalent already exists.
As stated in the documentation, it is possible to create hierarchies of data stores:
``` python
store.put('/first_group/df1', df1)
store.put('/first_group/df2', df2)
store.put('/second_group/df3', df3)
```
However, it seems that `store.keys()` can only provide a flattened list of all available groups. It would be nice to be able to walk the HDF5 file hierarchically. A couple examples (this is borrowing a bit from the h5py API):
``` python
# do stuff on each subgroup/substore in /first_group
for s in store['first_group'].values() :
# do stuff on df1 and df2
# visit each group at the root level
for s in store.values() :
if 'df1' in s :
# do stuff on any store named 'df1'
```
The main use case I would have for something like this is that I have many dataframes with different schema but would like to group some of them together and then iterate through those groups.
Best way I can think to emulate this is to parse the strings in `store.keys()`, but that is pretty ugly.
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} | 10 | 2015-05-15T10:32:42Z | 2021-04-18T06:48:01Z | 2021-04-18T06:48:01Z | CONTRIBUTOR | null | Are BDay and bday the same? Is one of them deprecated or something?
```
In [48]: pd.datetools.BDay?
Init signature: pd.datetools.BDay(self, n=1, normalize=False, **kwds)
Docstring: DateOffset subclass representing possibly n business days
File: c:\python27\lib\site-packages\pandas\tseries\offsets.py
Type: type
In [49]: pd.datetools.bday?
Type: BusinessDay
String form: <BusinessDay>
File: c:\python27\lib\site-packages\pandas\tseries\offsets.py
Signature: pd.datetools.bday(self, other)
Docstring: DateOffset subclass representing possibly n business days
Call signature: pd.datetools.bday(other)
```
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} | 5 | 2015-05-15T10:34:53Z | 2015-06-02T19:25:20Z | 2015-05-26T10:32:56Z | CONTRIBUTOR | null | At the moment there's no easy way to partially sort the DataFrame to get top N rows, could be useful feature.
There's partial sorting available for numpy within the [bottleneck](http://berkeleyanalytics.com/bottleneck/reference.html#bottleneck.partsort) library.
Here's link to SO question about numpy partial sort - http://stackoverflow.com/questions/10337533/a-fast-way-to-find-the-largest-n-elements-in-an-numpy-array
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| null | 1 | 2015-05-15T11:09:53Z | 2015-05-15T17:08:13Z | 2015-05-15T17:08:13Z | CONTRIBUTOR | null | #
## FAIL: test_sum (pandas.tests.test_series.TestSeries)
Traceback (most recent call last):
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tests/test_series.py", line 2302, in test_sum
self._check_stat_op('sum', np.sum)
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tests/test_series.py", line 2666, in _check_stat_op
testit()
File "/var/tmp/portage/dev-python/pandas-0.16.1/work/pandas-0.16.1-python3_3/lib/pandas/tests/test_series.py", line 2639, in testit
self.assertTrue(np.isnan(f(allna)))
AssertionError: False is not true
---
## INSTALLED VERSIONS
commit: None
python: 3.4.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.0.2-lh-nvidia
machine: x86_64
processor: Intel(R) Core(TM) i7-2600 CPU @ 3.40GHz
byteorder: little
LC_ALL: None
LANG: en_GB.utf8
pandas: 0.16.1
nose: 1.3.6
Cython: 0.22
numpy: 1.9.2
scipy: 0.15.1
statsmodels: None
IPython: 3.1.0
sphinx: 1.3.1
patsy: None
dateutil: 2.4.2
pytz: 2015.4
bottleneck: 1.0.0
tables: 3.1.1
numexpr: 2.4.1
matplotlib: 1.4.3
openpyxl: 2.2.2
xlrd: 0.9.3
xlwt: 1.0.0
xlsxwriter: None
lxml: 3.4.4
bs4: 4.3.2
html5lib: 0.999
httplib2: 0.9.1
apiclient: None
sqlalchemy: None
pymysql: 0.6.6.None
psycopg2: 2.6 (dt dec pq3 ext lo64)
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https://api.github.com/repos/pandas-dev/pandas/issues/10147 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10147/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10147/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10147/events | https://github.com/pandas-dev/pandas/issues/10147 | 76,738,392 | MDU6SXNzdWU3NjczODM5Mg== | 10,147 | BUG: Odd behavior of kwarg 'how' in MultiIndex-to-Index join | {
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"color": "02d7e1",
"default": false,
"description": "Concat, Merge/Join, Stack/Unstack, Explode",
"id": 13098779,
"name": "Reshaping",
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| null | 4 | 2015-05-15T14:13:29Z | 2019-03-01T03:01:59Z | 2019-03-01T03:01:59Z | NONE | null | ``` python
import pandas as pd
import numpy as np
from pandas.util.testing import assert_frame_equal
df = pd.DataFrame(np.arange(12).reshape(-1, 3),
columns=['a', 'b', 'c'])
df.index = pd.MultiIndex.from_tuples(
[(1, 2000), (1, 2001), (2, 2000), (2, 2001)],
names=['id', 'year'])
s = pd.Series([True, True], index=[1, 3], name='flag')
s.index.name = 'id'
# These two should *NOT* be the same, but they are both like a standard 'inner'
left = df.join(s, how='left')
inner = df.join(s, how='inner')
assert_frame_equal(left, inner)
# These two should *NOT* be the same, but they are both like a standard 'outer'
right = df.join(s, how='right')
outer = df.join(s, how='outer')
assert_frame_equal(right, outer)
# A standard 'left' merge is actually achieved with a MultiIndex by invoking `how='right'`
std_left = df.reset_index('year').join(s, how='left').set_index('year', append=True)
assert_frame_equal(right, std_left)
```
My impression from the example in #6356 is that the effect of `how` should not change with a MultiIndex. I know that #6363 is what was actually merged, so please correct me if my understanding is wrong.
## INSTALLED VERSIONS
commit: None
python: 2.7.9.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
pandas: 0.16.1
nose: 1.3.6
Cython: 0.22
numpy: 1.9.2
scipy: 0.15.1
statsmodels: 0.6.1
IPython: 3.1.0
sphinx: None
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.4
bottleneck: 1.1.0dev
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.3
openpyxl: None
xlrd: 0.9.3
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.4
pymysql: None
psycopg2: None
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} | 3 | 2015-05-15T15:05:32Z | 2015-05-16T14:36:34Z | 2015-05-15T16:28:39Z | NONE | null | I have a 2 DataFrame objects that I am trying to merge on a hierarchical index in one (top below) object with two columns in another (bottom below):
However, merging these via the following:
```
ecmo_by_year = pd.merge(pd.DataFrame(ecmo_count, columns=['ECMO']), runs_sex,
left_index=True, right_on=('YearEcls', 'Sex'))
```
Yields an incorrect ValueError:
```
ValueError: len(right_on) must equal the number of levels in the index of "left"
```
There are two levels in the hierarchical index, and two columns specified to join on the other, so this appears not to be a problem.
Running Pandas 0.16.1 on Python 3.4 (Homebrew) on OS X 10.10.
This code ran just fine on previous versions of Pandas (0.15), so it looks like a bug was introduced.
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} | 0 | 2015-05-15T19:51:00Z | 2015-06-02T19:25:20Z | 2015-06-01T11:45:10Z | MEMBER | null | Though API doc says `Index.union` can accept `Index` or array-like, it raises errors.
- http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Index.union.html
```
import numpy as np
import pandas as pd
idx = pd.Index([1, 2, 3])
idx.union([2, 3, 4])
# AttributeError: 'list' object has no attribute 'dtype'
idx.union(pd.Series([2, 3, 4]))
# AttributeError: 'Series' object has no attribute 'is_monotonic'
idx.union(np.array([2, 3, 4]))
# AttributeError: 'numpy.ndarray' object has no attribute 'is_monotonic'
```
NOTE: `intersection` looks OK.
```
idx.intersection([2, 3, 4])
# Int64Index([2, 3], dtype='int64')
idx.intersection(pd.Series([2, 3, 4]))
# Int64Index([2, 3], dtype='int64')
idx.union([2, 3, 4])
# Int64Index([2, 3], dtype='int64')
```
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} | 0 | 2015-05-15T19:59:59Z | 2015-06-27T03:51:56Z | 2015-06-27T03:51:56Z | MEMBER | null | Both `Series.value_counts` and `Index.value_counts` should preserve its name in resulted `Series.name`? Current behaviors are below:
```
s = pd.Series([1, 2, 1], name='a')
idx = pd.Index([1, 2, 1], name='a')
result = s.value_counts()
result.name, result.index.name
# (None, None) # should be ('a', None)?
result = idx.value_counts()
result.name, result.index.name
# (None, None) # should be ('a', None)?
didx = pd.date_range('2011-01-01', freq='D', periods=3, name='a')
result = didx.value_counts()
# (None, 'a') # should be ('a', None)?
```
```
```
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} | 1 | 2015-05-15T20:34:09Z | 2015-07-11T20:06:14Z | 2015-07-11T20:06:14Z | CONTRIBUTOR | null | we have in various locations
`os.name, platform.system(), sys.platform`
for detecting platform. Recently add are these functions
in `pandas/compat/__init__.py` as `is_platform_*` which are reasonable to standardize on
however, need to find & fix all the other references to make this nice and clean
this includes code and tests
Ideally also add: `skip_if_windows` functions in `pandas/util/testing.py` (and replace the use of the direct comparisons) would be gr8.
futhermore any references to to python 3 checks should use PY3 (in pandas/compat):
```
./pandas/tseries/tests/test_timeseries.py:
50 : if sys.version_info > (3,) and sys.platform == 'win32':
54 : if sys.version_info < (3,) or sys.platform != 'win32':
```
I think we could use an update on the wiki on the same
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```
pd.to_datetime(2291991, format="%m%d%Y", coerce=True, exact=True)
```
Returns a TypeError: ValueError: day is out of range for month
While
```
pd.to_datetime(3321991, format="%m%d%Y", coerce=True, exact=True)
```
Returns NaT. Which is what I would expect.
In any case they should return the same error or value
Joris Van den Bossche pointed out on the mailing list:
"It has something to do with the number of the day, only values above 31 convert to NaT, 31 or lower raises the error (eg also 31 April raise error instead of giving NaT)"
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} | 20 | 2015-05-16T18:00:20Z | 2015-06-02T19:25:20Z | 2015-05-30T20:41:19Z | NONE | null | Say there is a array of type int64
for convenience, that me just put is some large number
test1 = pd.Series(20150515061816532, index=list(range(500)), dtype='int64')
test1.describe()
Out[152]:
count 5.000000e+02
**mean -1.674297e+16**
std 0.000000e+00
min 2.015052e+16
25% 2.015052e+16
50% 2.015052e+16
75% 2.015052e+16
max 2.015052e+16
Look at the mean, it overflow, and become negative. Obviously the mean should be 20150515061816532
In [153]: test1.sum()
**Out[153]: -8371486542801285616** This is wrong.
The computation should have been sum them up as **float**, and devided by total count.
I think we need to examine other parts of code that involve similar situation.
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} | 2 | 2015-05-16T21:12:36Z | 2015-06-09T23:46:30Z | 2015-06-09T23:46:30Z | NONE | null | Trying to remove a `nan` category from Categorical series fails if categories are made of floats.
In the docs it says:
> Note: As integer Series can’t include NaN, the categories were converted to _object_.
So it is probably linked to this with `float` remaining `float` and `nan` != `nan`.
If this is intended behavior perhaps would be useful to add this to the docs?
```
import pandas as pd
df = pd.DataFrame({'a': pd.Categorical([1,2,3]),
'b': pd.Categorical(list('abc')),
'c': pd.Categorical([1.1,2.1,3.1])})
for col in df.columns:
df[col].cat.add_categories(pd.np.nan, inplace=True)
print df[col]
df[col].cat.remove_categories(pd.np.nan)
0 1
1 2
2 3
Name: a, dtype: category
Categories (4, object): [1, 2, 3, NaN]
0 a
1 b
2 c
Name: b, dtype: category
Categories (4, object): [a, b, c, NaN]
0 1.1
1 2.1
2 3.1
Name: c, dtype: category
Categories (4, float64): [1.1, 2.1, 3.1, NaN]
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
d:\Anaconda\envs\py2k\lib\site-packages\pandas\core\categorical.pyc in _delegate_method(self, name, *args, **kwargs)
1643 from pandas import Series
1644 method = getattr(self.categorical, name)
-> 1645 res = method(*args, **kwargs)
1646 if not res is None:
1647 return Series(res, index=self.index)
d:\Anaconda\envs\py2k\lib\site-packages\pandas\core\categorical.pyc in remove_categories(self, removals, inplace)
753 not_included = removals - set(self._categories)
754 if len(not_included) != 0:
--> 755 raise ValueError("removals must all be in old categories: %s" % str(not_included))
756 new_categories = [ c for c in self._categories if c not in removals ]
757 return self.set_categories(new_categories, ordered=self.ordered, rename=False,
ValueError: removals must all be in old categories: set([nan])
```
---
```
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.9.final.0
python-bits: 64
pandas: 0.16.1
numpy: 1.9.2
...
```
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} | 5 | 2015-05-16T21:26:19Z | 2015-06-02T19:26:12Z | 2015-06-01T11:45:10Z | MEMBER | null | Closes #10149.
- Added explicit tests for array-likes in set-ops, `intersection`, `union`, `difference` and `sym_diff`.
- `TimedeltaIndex` previously did additional input check which is inconsistent with others. Made it work as the same manner as others.
- `MultiIndex` set-ops should only accept list-likes of tuples. Implement the logic and add explicit test.
- Changed to understandable error message for `str` which has `__iter__` in py3.
```
# current error msg
idx.intersection('aaa')
# TypeError: Index(...) must be called with a collection of some kind, 'aaa' was passed
```
NOTE: This DOESN'T care the `name` attribute checks, which is being worked in #9965.
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} | 3 | 2015-05-16T21:31:49Z | 2015-06-02T19:26:12Z | 2015-05-18T11:59:45Z | MEMBER | null | Closes #9926.
CC @hsperr I've changed `common._maybe_match_names` to work with not-named objects, and hopefully can use in #9965 also.
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| null | 2 | 2015-05-17T02:58:00Z | 2015-05-18T11:06:09Z | 2015-05-18T11:06:04Z | NONE | null | I'm working on a project involving log file analysis and wrote a method which takes a regex, a file name and list of column names, parses the data and returns a pandas DataFrame.
I haven't extensively tested this yet, but the code below successfully reads in an apache log file using the regex below and returns a DataFrame with all the data in the correct columns. Would anyone else find this useful and if so, what would I need to do to contribute this to the code base?
Thanks,
``` python
""" io from regex """
from pandas import DataFrame
import re
def read_from_regex(**kwargs):
"""
Read text from an input file, apply a regex to it and store data into a DataFrame
Returns
-------
parsed : DataFrame
"""
pattern = kwargs.get('r')
columns = kwargs.get('columns')
inputFile = open(kwargs.get('input'), 'r')
table = []
for line in inputFile:
matchObj = re.search(pattern, line)
if matchObj:
row = {}
fieldCount = len(matchObj.groups())
if len(columns) > 0:
for i in range(1, fieldCount):
row[columns[i]] = matchObj.group(i)
else:
for i in range(1, fieldCount):
row[i] = matchObj.group(i)
table.append(row)
return DataFrame(table)
def main():
pattern = r'(\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3})\s(\S+)\s(\S+)\s\[(\d{2}/\w+?/\d{4}:\d{2}:\d{2}:\d{2}\s-\d{4})\]\s"([A-Z]+)\s(\S+?)\s(\S+)"\s(\d{3})\s(\S+?)\s"(\S+?)"\s"(.+?)"'
columnNames = ['ipAddress', 'remoteLogname', 'username', 'dateTime', 'request', 'requestLine' , '', 'responseCode', 'bytesSent', 'referrer', 'userAgent' ]
data = read_from_regex( r=pattern, input='apache-logs.txt', columns=columnNames )
print( data.describe() )
if __name__ == "__main__":main() ## with if
```
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} | 2 | 2015-05-17T05:48:48Z | 2015-06-10T20:01:31Z | 2015-06-10T20:01:31Z | NONE | null | Suppose that we want to create a dataframe from a dictionary.
``` python
import pandas as pd,numpy as np
#1) Form dataframe
ix=pd.date_range('1/1/2015',periods=5,freq='D')
df0=pd.DataFrame(np.random.normal(size=(len(ix),5)),index=ix)
#2) Split dataframe into 2 dictionaries, based on sign
d={'+':{},'-':{}}
for loc in df0.index:
d['+'][loc]=df0.loc[loc][df0.loc[loc]>=0]
d['-'][loc]=df0.loc[loc][df0.loc[loc]<0]
#3) Convert dictionary to dataframe
print pd.DataFrame.from_dict(d['+'],orient='index')
```
This returns a dataframe of positive values, with NaN in place of the negative values. Now, it appears the exact same operation fails if we use "df.index.values" instead of "df.index".
``` python
d={'+':{},'-':{}}
for loc in df0.index.values: # NOTE .values!
d['+'][loc]=df0.loc[loc][df0.loc[loc]>=0]
d['-'][loc]=df0.loc[loc][df0.loc[loc]<0]
print pd.DataFrame.from_dict(d['+'],orient='index')
```
Now the outcome is a dataframe with all None. I think the problem is some inconsistency between pandas' datetime and numpy's datetime formats.
Pandas version 0.16.1, Numpy version 1.9.2. Thanks.
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} | 16 | 2015-05-17T14:03:31Z | 2017-12-13T16:19:00Z | 2015-09-25T12:19:15Z | NONE | null | the following works quickly in 0.15.2 and has a performance issue on the last operation df.T.duplicated() in 0.16.0 and 0.16.1
also on a private data set that works on 0.15.2 i get an error on 0.16.0 and 0.16.1 on the same operation.
code:
``` python
import pandas,numpy
df = pandas.DataFrame({'A': [1 for x in range(1000)],
'B': [1 for x in range(1000)]})
print (numpy.count_nonzero(df.duplicated()))
print (numpy.count_nonzero(df.T.duplicated()))
df = pandas.DataFrame({'A': [1 for x in range(1000000)],
'B': [1 for x in range(1000000)]})
print (numpy.count_nonzero(df.duplicated()))
print (numpy.count_nonzero(df.T.duplicated()))
this is the error i get on the private data set (code not reproduce yet with synthetic data):
File "C:\Anaconda3\lib\site-packages\pandas\util\decorators.py", line 88, in wrapper
return func(*args, **kwargs)
File "C:\Anaconda3\lib\site-packages\pandas\core\frame.py", line 2867, in duplicated
labels, shape = map(list, zip( * map(f, vals)))
File "C:\Anaconda3\lib\site-packages\pandas\core\frame.py", line 2856, in f
labels, shape = factorize(vals, size_hint=min(len(self), _SIZE_HINT_LIMIT))
File "C:\Anaconda3\lib\site-packages\pandas\core\algorithms.py", line 135, in factorize
labels = table.get_labels(vals, uniques, 0, na_sentinel)
File "pandas\hashtable.pyx", line 813, in pandas.hashtable.PyObjectHashTable.get_labels (pandas\hashtable.c:14025)
ValueError: Buffer has wrong number of dimensions (expected 1, got 2)
```
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| null | 5 | 2015-05-18T12:36:58Z | 2015-05-20T08:23:54Z | 2015-05-18T14:23:28Z | NONE | null | What seems to be the problem here?
The xticklabels for the first axes defined in a gridspec are not visible when plotting with pandas. The corresponding plot using pyplot.plot does have the labels.
pandas 0.16
matplotlib 1.4.3
``` python
import pandas as pd
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
%matplotlib inline
df = pd.DataFrame(np.random.randn(8, 4), index=np.arange(8), columns=['A', 'B', 'C', 'D'])
```
Matplotlib
``` python
gs = mpl.gridspec.GridSpec(2, 4)
ax1 = plt.subplot(gs[0,:-1])
ax2 = plt.subplot(gs[0,-1])
ax3 = plt.subplot(gs[1,:-2])
ax4 = plt.subplot(gs[1,-2:])
ax1.plot(df.index.values, df.A)
ax2.plot(df.index.values, df.B)
ax3.plot(df.index.values, df.C)
ax4.plot(df.index.values, df.D)
gs.tight_layout(plt.gcf())
```
pandas
``` python
gs = mpl.gridspec.GridSpec(2, 4)
ax1 = plt.subplot(gs[0,:-1])
ax2 = plt.subplot(gs[0,-1])
ax3 = plt.subplot(gs[1,:-2])
ax4 = plt.subplot(gs[1,-2:])
df.A.plot(ax=ax1)
df.B.plot(ax=ax2)
df.C.plot(ax=ax3)
df.D.plot(ax=ax4)
gs.tight_layout(plt.gcf())
```
It seems that xticklabels are absent when plotting with pandas to the first axis generated in a gridspec. Switching ax1 and ax2 definition:
pandas
``` python
gs = mpl.gridspec.GridSpec(2, 4)
ax2 = plt.subplot(gs[0,-1])
ax1 = plt.subplot(gs[0,:-1])
ax3 = plt.subplot(gs[1,:-2])
ax4 = plt.subplot(gs[1,-2:])
df.A.plot(ax=ax1)
df.B.plot(ax=ax2)
df.C.plot(ax=ax3)
df.D.plot(ax=ax4)
gs.tight_layout(plt.gcf())
```
Related?
http://stackoverflow.com/questions/29552382/legend-overriding-x-label-and-x-ticks
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} | 9 | 2015-05-18T13:29:40Z | 2015-08-21T07:33:31Z | 2015-08-21T07:33:31Z | MEMBER | null | Closes #9556
xref #9568, #4916, #4191
However, while writing this up, I started to doubt a bit if this is necessary.
`DataFrame.from_csv` is implemented as a round-trip method together with `to_csv`. If you use a plain `df.to_csv(path)`, you cannnot read it in as `pd.read_csv(path)` to get exactly the same. You at least need `pd.read_csv(path, index_col=True)` and a `parse_dates` keyword if you have datetimes.
Secondly, there is also the question of `Series.from_csv`. It would be logical to deprecate this as well, but for this you don't directly have an alternative (but `pd.read_csv(path, index_col=0)[0]` will work). There is also for example this SO answer of Wes: http://stackoverflow.com/questions/13557559/how-to-write-read-pandas-series-to-from-csv (and it is used in the Python for Data Analysis book).
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} | 4 | 2015-05-18T14:07:13Z | 2021-04-18T06:48:49Z | null | NONE | null | read_csv does not return the data table expected if there's only one line in the CSV file and skipfooter is used and the line directly after the table is blank and skip_blank_lines=True.
```
>>> import pandas as pd
>>> import StringIO
>>> test_csv = StringIO.StringIO('a,b,c\n1,2,3\n\nend\n')
>>> pd.read_csv(test_csv, skip_footer=2, engine='python')
Empty DataFrame
Columns: [a, b, c]
Index: []
```
But if the more than one line is in the data table or the line after the data table is not blank or skip_blank_lines is set to False, everything is ok:
```
>>> test_csv = StringIO.StringIO('a,b,c\n1,2,3\n4,5,6\n\nend\n')
>>> pd.read_csv(test_csv, skip_footer=2, engine='python')
a b c
0 1 2 3
1 4 5 6
>>> test_csv = StringIO.StringIO('a,b,c\n1,2,3\nend\n\n')
>>> pd.read_csv(test_csv, skip_footer=2, engine='python')
a b c
0 1 2 3
>>> test_csv = StringIO.StringIO('a,b,c\n1,2,3\n\nend\n')
>>> pd.read_csv(test_csv, skip_footer=2, engine='python', skip_blank_lines=False)
a b c
0 1 2 3
```
This occurs in every version from 0.15.0 onwards (ie since skip_blank_lines was introduced).
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} | 1 | 2015-05-18T15:19:38Z | 2016-02-27T16:10:05Z | 2016-02-27T16:10:00Z | CONTRIBUTOR | null | xref #9697
I think we can detect the returned values and if they are not scalars, give a nicer error message. Further a doc-note would be helpful.
```
In [4]: cols = pd.MultiIndex.from_tuples([('syn', 'A'), ('mis', 'A'), ('non', 'A'), ('syn', 'C'), ('mis', 'C'), ('non', 'C'),
('syn', 'T'), ('mis', 'T'), ('non', 'T'), ('syn', 'G'), ('mis', 'G'), ('non', 'G')])
In [5]: df = pd.DataFrame(np.random.randint(1, 10, (4,12)), columns=cols, index=['A', 'C', 'G', 'T'])
In [6]: df.groupby(axis=1, level=1).transform(lambda z: z.div(z.sum(axis=1), axis=0))
ValueError: Length mismatch: Expected axis has 4 elements, new values have 12 elements
```
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| null | 1 | 2015-05-18T19:43:07Z | 2015-05-18T20:31:00Z | 2015-05-18T20:30:57Z | CONTRIBUTOR | null | The docstring listed 'method' before 'value' which is not consistent
with the order of the arguments when calling the method.
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| null | 9 | 2015-05-19T01:58:11Z | 2015-05-19T03:15:18Z | 2015-05-19T03:15:18Z | NONE | null | create a file named logging.py anywhere as follows
# !/usr/bin/env python
print "hello"
Then
> > python
> > import pandas
you will get the following error
AttributeError: 'module' object has no attribute 'getLogger'
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} | 12 | 2015-05-19T06:42:07Z | 2015-08-02T17:03:33Z | 2015-08-02T17:03:33Z | CONTRIBUTOR | null | ez_setup.py is few years out of date, we should stop distributing it.
Up to date versions of Python 2 and 3 provide setuptools and pip out of the box `python -m ensurepip --upgrade`. For other Python versions, we can simply point users to the up to date instructions at https://packaging.python.org/en/latest/installing.html#requirements-for-installing-packages.
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| null | 3 | 2015-05-19T11:14:33Z | 2015-05-20T10:55:42Z | 2015-05-20T10:55:42Z | NONE | null | Hi,
There is a strange behavior when I want to reindex a Multi-Index (float64) of a Series: some of the original values are dropped from the reindexed object.
Here is the test case:
``` python
>>> import pandas as pd
>>> import numpy as np
>>> df_g=pd.Series(index=pd.MultiIndex.from_tuples([(10.,4.2),(11.,5.2),(14,7.8)]),data=[0.01,0.2,0.684])
10 4.2 0.010
11 5.2 0.200
14 7.8 0.684
dtype: float64
>>> df_g_r=pd.Series(index=pd.MultiIndex.from_product([np.arange(0,360,1.),np.arange(0,25,0.1)])).fillna(0)
>>> df_g.reindex(df_g_r.index).dropna()
10 4.2 0.01
11 5.2 0.20
dtype: float64
```
Anyone has an idea of what is going on? Is there any workaround for this?
Many thanks,
Greg
## INSTALLED VERSIONS
commit: None
python: 2.7.6.final.0
python-bits: 64
OS: Linux
OS-release: 3.13.0-51-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
pandas: 0.15.2
nose: 1.3.4
Cython: 0.21.2
numpy: 1.8.2
scipy: 0.15.1
statsmodels: None
IPython: 2.3.1
sphinx: 1.2.2
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.4
bottleneck: 0.8.0
tables: 3.1.1
numexpr: 2.4
matplotlib: 1.4.2
openpyxl: 1.8.6
xlrd: 0.9.3
xlwt: 0.7.5
xlsxwriter: None
lxml: 3.3.3
bs4: None
html5lib: None
httplib2: 0.8
apiclient: None
rpy2: None
sqlalchemy: 0.9.8
pymysql: 0.6.6.None
psycopg2: None
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} | 1 | 2015-05-19T14:46:09Z | 2015-06-02T19:25:20Z | 2015-05-20T22:02:19Z | MEMBER | null | Should a datetime column should use the same precision for all, padding with zeros, just like a float column does?
```
In [121]: df = pd.DataFrame({'datetime': pd.date_range('1/1/2000 09:00:00', freq="5ms",periods=10), 'float': np.arange(0,0.05,0.005)})
In [122]: df
Out[122]:
datetime float
0 2000-01-01 09:00:00 0.000
1 2000-01-01 09:00:00.005000 0.005
2 2000-01-01 09:00:00.010000 0.010
3 2000-01-01 09:00:00.015000 0.015
4 2000-01-01 09:00:00.020000 0.020
5 2000-01-01 09:00:00.025000 0.025
6 2000-01-01 09:00:00.030000 0.030
7 2000-01-01 09:00:00.035000 0.035
8 2000-01-01 09:00:00.040000 0.040
9 2000-01-01 09:00:00.045000 0.045
```
so that the first row would show `2000-01-01 09:00:00.000000`?
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} | 5 | 2015-05-19T15:46:04Z | 2015-06-02T19:26:12Z | 2015-05-20T22:02:19Z | CONTRIBUTOR | null | closes #10170
```
In [3]: Series(date_range('20130101 09:00:00',periods=5,freq='D'))
Out[3]:
0 2013-01-01 09:00:00
1 2013-01-02 09:00:00
2 2013-01-03 09:00:00
3 2013-01-04 09:00:00
4 2013-01-05 09:00:00
dtype: datetime64[ns]
In [4]: Series(date_range('20130101 09:00:00',periods=5,freq='s'))
Out[4]:
0 2013-01-01 09:00:00
1 2013-01-01 09:00:01
2 2013-01-01 09:00:02
3 2013-01-01 09:00:03
4 2013-01-01 09:00:04
dtype: datetime64[ns]
In [2]: s = Series(date_range('20130101 09:00:00',periods=5,freq='ms'))
In [3]: s.iloc[1] = np.nan
In [4]: s
Out[4]:
0 2013-01-01 09:00:00.000
1 NaT
2 2013-01-01 09:00:00.002
3 2013-01-01 09:00:00.003
4 2013-01-01 09:00:00.004
dtype: datetime64[ns]
In [6]: Series(date_range('20130101 09:00:00',periods=5,freq='us'))
Out[6]:
0 2013-01-01 09:00:00.000000
1 2013-01-01 09:00:00.000001
2 2013-01-01 09:00:00.000002
3 2013-01-01 09:00:00.000003
4 2013-01-01 09:00:00.000004
dtype: datetime64[ns]
In [7]: Series(date_range('20130101 09:00:00',periods=5,freq='N'))
Out[7]:
0 2013-01-01 09:00:00.000000000
1 2013-01-01 09:00:00.000000001
2 2013-01-01 09:00:00.000000002
3 2013-01-01 09:00:00.000000003
4 2013-01-01 09:00:00.000000004
dtype: datetime64[ns]
```
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| null | 1 | 2015-05-19T21:04:34Z | 2015-05-19T21:06:58Z | 2015-05-19T21:06:58Z | NONE | null | https://github.com/pydata/pandas/issues/5580
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} | 3 | 2015-05-20T08:33:49Z | 2016-01-07T00:21:16Z | 2016-01-07T00:21:16Z | NONE | null | interpolation : {‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’}
This would make it consistent with numpy.percentile options (new in 1.9). See http://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.percentile.html
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} | 2 | 2015-05-20T09:42:45Z | 2020-09-22T01:57:12Z | null | NONE | null | ```
df = pd.DataFrame({'a':[55,66,77],'b':[100,111,112],'ch':['x','y','z']})
df.index = pd.Index([10,11,12])
In [6]: df
Out[6]:
a b ch
10 55 100 x
11 66 111 y
12 77 112 z
In [7]: df.loc[10,('b','ch')]
....
ValueError: No axis named 1 for object type <class 'pandas.core.series.Series'>
In [8]: df.ix[10,('b','ch')]
Out[8]: 100
```
more or less understandable, probably both should not work though.
but then, using the same indexing, the setting operation works, unpacking the tuple into the correct columns, as one would use the correct list selector `df.ix[10,['b','ch']]` or `df.loc[10,['b','ch']]`
```
In [10]: df.ix[10,('b','ch')] = (200,'i')
In [11]: df
Out[11]:
a b ch
10 55 200 i
11 66 111 y
12 77 112 z
In [12]: df.loc[10,('b','ch')] = (300,'j')
In [13]: df
Out[13]:
a b ch
10 55 300 j
11 66 111 y
12 77 112 z
```
For .ix setting should throw the same error as for retrieving?
For .loc setting should throw an error as you should expect to set a tuple to a single column?
Is this wanted behavior?
P.S.: New to advanced / multi-index slicing, my searches didn't bring up that very issue despite the fact that all issues around this indexing seem somehow related.
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| null | 11 | 2015-05-20T10:56:23Z | 2015-05-20T17:18:08Z | 2015-05-20T10:59:32Z | CONTRIBUTOR | null | It appears that `loc` now enlarges the result if an index is not found - a behavior I find confusing, because
``` python
df.loc[['missing_label']]
```
gives a `KeyError` while
``` python
df.loc[['existing_label', 'missing_label']]
```
works just fine. Apparently this was changed in 0.15. I have older code that relied on catching errors for the case where some labels might be missing, which now doesn't work. How can I do a `loc` select, guaranteeing that I will get an error if a non-existing label is given - i.e. do the same as `loc` but without ever enlarging the result?
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} | 4 | 2015-05-20T11:57:53Z | 2015-06-27T22:04:40Z | 2015-06-27T22:04:40Z | CONTRIBUTOR | null | xref https://github.com/pydata/pandas/issues/9426, fixed in #9597
`axis=1` is ok
```
df1 = pandas.DataFrame(numpy.random.randn(6, 3), columns=["a", "b", "c"])
df2 = pandas.DataFrame(numpy.random.randn(7, 4), columns=["g", "h", "a", "c"])
df2['h'] = pandas.Series(pandas.Categorical(["one", "one", "two", "one", "two", "two", "one"]))
df = pandas.concat((df1, df2))
```
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https://api.github.com/repos/pandas-dev/pandas/issues/10178 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10178/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10178/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10178/events | https://github.com/pandas-dev/pandas/issues/10178 | 78,511,138 | MDU6SXNzdWU3ODUxMTEzOA== | 10,178 | pd.to_datetime much slower with supplied format than when format is inferred | {
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} | 11 | 2015-05-20T12:46:20Z | 2015-07-20T23:25:42Z | 2015-07-20T23:25:42Z | NONE | null | It is **much slower** when converting a date string to supply a date format for a column than for it to be inferred. I would've though there should be less work to do when the format is known (and supplied)
To test
``` python
df = DataFrame({'date_text':["2015-05-18" for i in range(10**6)]})
%timeit pd.to_datetime(df['date_text'],infer_datetime_format=True, box=False).values.view('i8')/10**9
10 loops, best of 3: 115 ms per loop
#Top line from %prun of same command:
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.095 0.095 0.095 0.095 {pandas.tslib.array_to_datetime}
%timeit pd.to_datetime(df['date_text'],format="%Y-%m-%d", box=False).values.view('i8')/10**9
1 loops, best of 3: 2.27 s per loop
#Top line from %prun of same command:
ncalls tottime percall cumtime percall filename:lineno(function)
1 2.282 2.282 2.282 2.282 {pandas.tslib.array_strptime}
```
This plot is taken from this [S/O post](http://stackoverflow.com/questions/30330428/converting-string-date-to-epoch-time-not-working-with-cython-and-posix-c-librari) which shows the difference over a larger range of sizes (and compared to other methods).
## INSTALLED VERSIONS
commit: None
python: 2.7.9.final.0
python-bits: 64
OS: Linux
OS-release: 3.13.0-52-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
pandas: 0.15.2
nose: 1.3.4
Cython: 0.22
numpy: 1.9.2
scipy: 0.14.0
statsmodels: 0.5.0
IPython: 2.2.0
sphinx: 1.2.3
patsy: 0.3.0
dateutil: 2.2
pytz: 2014.10
bottleneck: None
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.0
openpyxl: 2.2.0-b1
xlrd: 0.9.3
xlwt: 0.7.5
xlsxwriter: 0.5.7
lxml: 3.4.0
bs4: 4.3.2
html5lib: None
httplib2: 0.9
apiclient: 1.4.0
rpy2: None
sqlalchemy: 1.0.0
pymysql: None
psycopg2: None
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} | 5 | 2015-05-20T15:34:57Z | 2015-06-27T22:04:27Z | 2015-06-27T22:04:22Z | NONE | null | Contains a proposed fix for #10177
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https://api.github.com/repos/pandas-dev/pandas/issues/10180 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/10180/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/10180/comments | https://api.github.com/repos/pandas-dev/pandas/issues/10180/events | https://github.com/pandas-dev/pandas/issues/10180 | 78,623,198 | MDU6SXNzdWU3ODYyMzE5OA== | 10,180 | Segfault when writing data out of order to pd.HDFStore via append | {
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| null | 13 | 2015-05-20T17:47:02Z | 2015-11-24T11:40:51Z | 2015-11-24T11:40:50Z | NONE | null | I am trying to append chunks of data to an (initially empty) HDF5 frame with pd.HDFStore. The chunks come in out of order, and sometimes certain orders produce segfaults. This script seems to consistently segfault after loading file 31 (_update, see comments for better example_). You will notice that by looking at the time stamps outputted by the script it appears to be when hdf5 tries to fill some gap data. I can produce more files that trigger segfaults if necessary.
I've managed to narrow it down to the following line in `pytables.py`
```
> /home/user/env/lib/python3.4/site-packages/pandas/io/pytables.py(3738)write_data_chunk()
3737 self.table.append(rows)
-> 3738 self.table.flush()
3739 except Exception as detail:
```
```
INSTALLED VERSIONS
------------------
commit: None
python: 3.4.2.final.0
python-bits: 64
OS: Linux
OS-release: 3.16.0-4-amd64
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
pandas: 0.16.1
nose: 1.3.3
Cython: 0.22
numpy: 1.9.2
scipy: None
statsmodels: None
IPython: 2.1.0
sphinx: None
patsy: None
dateutil: 2.4.2
pytz: 2015.4
bottleneck: None
tables: 3.2.0
numexpr: 2.4
matplotlib: None
openpyxl: None
xlrd: 0.9.3
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.3.2
html5lib: None
httplib2: 0.9
apiclient: None
sqlalchemy: 0.9.8
pymysql: None
psycopg2: 2.6 (dt dec pq3 ext lo64)
HDF5 Versions:
~/user$ dpkg -l | grep "hdf5"
ii hdf5-helpers 1.8.13+docs-15 amd64 Hierarchical Data Format 5 (HDF5) - Helper tools
ii hdf5-tools 1.8.13+docs-15 amd64 Hierarchical Data Format 5 (HDF5) - Runtime tools
rc libhdf5-7:amd64 1.8.12+docs-1 amd64 Hierarchical Data Format 5 (HDF5) - runtime files - serial version
ii libhdf5-8:amd64 1.8.13+docs-15 amd64 Hierarchical Data Format 5 (HDF5) - runtime files - serial version
rc libhdf5-cpp-7:amd64 1.8.12+docs-1 amd64 Hierarchical Data Format 5 (HDF5) - C++ libraries
ii libhdf5-cpp-8:amd64 1.8.13+docs-15 amd64 Hierarchical Data Format 5 (HDF5) - C++ libraries
ii libhdf5-dev 1.8.13+docs-15 amd64 Hierarchical Data Format 5 (HDF5) - development files - serial version
```
A script to reproduce:
```
import os
import pandas as pd
_dir = 'test_files'
_file = './hdf5_test.h5'
def write_to_file(series):
store = pd.HDFStore(_file, 'a')
frame = pd.DataFrame(series)
print("Appending data from {0} to {1}".format(
frame.index[0], frame.index[-1]))
store.append('test', frame)
store.close()
if __name__ == "__main__":
if os.path.isfile(_file):
os.remove(_file)
files = os.listdir(_dir)
for f in files:
series = pd.read_pickle(os.path.join(_dir, f))
print("Writing data: %s" % f)
write_to_file(series)
```
zipped pickled files for test: http://s000.tinyupload.com/?file_id=60238823358379433453
Here is a pastebin of the data _where segfault is occuring_ from the example in csv format:
http://pastebin.com/FRsygCUG
_note, you may need the actual files to reproduce this, but as you can see from the pastebin that the data isn't malformed_
It is trying to fill the the following gap in the original data:
`2011-01-04 17:55:00` to`2011-01-05 22:15:00`
with an append which results in a segfault
Script output:
```
Writing data: 00
Appending data from 2011-01-03 13:40:00 to 2011-01-04 17:55:00
Writing data: 01
Appending data from 2011-01-05 22:15:00 to 2011-01-07 02:30:00
Writing data: 02
Appending data from 2011-01-04 18:00:00 to 2011-01-05 22:15:00
Segmentation fault
```
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} | 5 | 2015-05-21T09:22:18Z | 2015-06-07T22:22:40Z | 2015-06-07T22:22:40Z | CONTRIBUTOR | null | I searched the issues list for "empty dataframe" but did not find anything matching.
In pandas 0.16.1, the result of adding 2 empty dataframes is not equal to another empty dataframe.
This code, in pandas 0.15.2, does what is expected:
``` python
import pandas as pd
pd.show_versions()
df1 = pd.DataFrame()
df2 = pd.DataFrame()
assert df1.equals(df1)
assert df2.equals(df1)
assert (df1+df1).equals(df2)
```
It fails in 0.16.1.
0.15.2 output:
``` python
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.7.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 26 Stepping 5, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en_GB
pandas: 0.15.2
nose: 1.3.6
Cython: 0.21.1
numpy: 1.9.2
scipy: 0.15.1
statsmodels: None
IPython: 3.1.0
sphinx: 1.3.1
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.4
bottleneck: 0.8.0
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.0
openpyxl: 1.8.5
xlrd: 0.9.3
xlwt: 0.7.5
xlsxwriter: 0.7.2
lxml: 3.4.0
bs4: 4.3.2
html5lib: 0.999
httplib2: None
apiclient: None
rpy2: None
sqlalchemy: 0.9.7
pymysql: None
psycopg2: None
```
0.16.1 output:
``` python
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.9.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 26 Stepping 5, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
pandas: 0.16.1
nose: 1.3.6
Cython: 0.22
numpy: 1.9.2
scipy: 0.14.0
statsmodels: 0.6.1
IPython: 3.1.0
sphinx: 1.3.1
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.4
bottleneck: 0.8.0
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.3
openpyxl: None
xlrd: 0.9.3
xlwt: None
xlsxwriter: 0.7.2
lxml: None
bs4: 4.3.2
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: 1.0.4
pymysql: None
psycopg2: None
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
c:\test_empty_add_0.16.1.py in <module>()
11 assert df2.equals(df1)
12
---> 13 assert (df1+df1).equals(df2)
AssertionError:
```
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} | 5 | 2015-05-21T09:44:11Z | 2015-06-10T06:47:12Z | 2015-06-10T06:47:12Z | NONE | null | According to the docstring, the following is allowed:
``` Python
pd.set_option('display.max_seq_items', None)
```
With 0.16.1 this results in a TypeError when pretty printing an index. This is because the None value is compared against lenght of the index to see if we need to limit output.
``` Python
TypeError: unorderable types: int() > NoneType()
```
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} | 5 | 2015-05-21T11:38:34Z | 2015-06-09T12:19:32Z | 2015-06-09T12:19:32Z | NONE | null | If foo.csv contains
``` csv
x,y
1,2
```
then you get the normal behavior:
``` py
>>> df = pd.read_csv('foo.csv', index_col=0)
>>> list(df.columns)
['y']
>>> df.index.name
'x'
```
but if you remove the data row "1,2" in the CSV the index name gets dropped:
``` py
>>> df = pd.read_csv('foo.csv', index_col=0)
>>> list(df.columns)
['y']
>>> df.index.name
None
```
This means round-tripping with to_csv/read_csv fails for empty dataframes.
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} | 7 | 2015-05-21T13:51:22Z | 2015-06-02T19:26:12Z | 2015-05-23T06:41:18Z | MEMBER | null | Add `Index.difference` to api doc rather than deprecated `Index.diff` (#8226)
And is it OK to remove `Index.diff` alias because #6581 lists #8227 (which closes #8226)?
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} | 8 | 2015-05-21T14:17:09Z | 2021-06-17T03:07:31Z | null | MEMBER | null | Derived from #10157. Would like to clarify what these results should be. Basically, I think:
- The result must be `CategoricalIndex`
- The result should have the same values as the result of normal `Index` which has the same original values.
- Result's `category` should only include categories which the result actually has.
Followings are current results.
## intersection
```
# for reference
pd.Index([1, 2, 3, 1, 2, 3]).intersection(pd.Index([2, 3, 4, 2, 3, 4]))
# Int64Index([2, 2, 3, 3], dtype='int64')
pd.CategoricalIndex([1, 2, 3, 1, 2, 3]).intersection(pd.CategoricalIndex([2, 3, 4, 2, 3, 4]))
# CategoricalIndex([2, 2, 3, 3], categories=[1, 2, 3], ordered=False, dtype='category')
# -> Is this OK or it should have categories=[2, 3]?
```
## union
Doc says "Form the union of two Index objects and sorts if possible". I'm not sure whether the last sentence says "raise error if sort is impossible" or "not sort if impossible"?
- http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Index.union.html
```
pd.Index([1, 2, 4]).union(pd.Index([2, 3, 4]))
# Int64Index([1, 2, 3, 4], dtype='int64')
pd.CategoricalIndex([1, 2, 4]).union(pd.CategoricalIndex([2, 3, 4]))
# CategoricalIndex([1, 2, 4, 3], categories=[1, 2, 3, 4], ordered=False, dtype='category')
# -> Should be sorted?
```
```
pd.Index([1, 2, 3, 1, 2, 3]).union(pd.Index([2, 3, 4, 2, 3, 4]))
# InvalidIndexError: Reindexing only valid with uniquely valued Index objects
-> This should results Index([1, 2, 3, 1, 2, 3, 4, 4])?
pd.CategoricalIndex([1, 2, 3, 1, 2, 3]).union(pd.CategoricalIndex([2, 3, 4, 2, 3, 4]))
# TypeError: type() takes 1 or 3 arguments
# -> should raise understandable error, or Int64Index shouldn't raise (and return unsorted result?)
```
## difference
```
pd.CategoricalIndex([1, 2, 4, 5]).difference(pd.CategoricalIndex([2, 3, 4]))
# Int64Index([1, 5], dtype='int64')
# -> should be CategoricalIndex?
```
## sym_diff
```
pd.CategoricalIndex([1, 2, 4, 5]).sym_diff(pd.CategoricalIndex([2, 4]))
# Int64Index([1, 5], dtype='int64')
# -> should be CategoricalIndex?
```
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| null | 4 | 2015-05-21T15:21:30Z | 2015-05-22T01:53:48Z | null | MEMBER | null | Suppose you have two dataframes with multi-index with non-matching names. When you `concat` these, the name of the first index will be used, and the indices are just merged ignoring the names of the levels.
Small example:
```
In [41]: df1 = pd.DataFrame([[1,2], [3,4]], index=pd.MultiIndex.from_tuples([('a', 1), ('a', 2)], names=['A', 'B']))
In [42]: df2 = pd.DataFrame([[5,6], [7,8]], index=pd.MultiIndex.from_tuples([(1, 'b'), (2, 'b')], names=['B', 'A']))
In [43]: df1
Out[43]:
0 1
A B
a 1 1 2
2 3 4
In [44]: df2
Out[44]:
0 1
B A
1 b 5 6
2 b 7 8
In [45]: pd.concat([df1, df2])
Out[45]:
0 1
A B
a 1 1 2
2 3 4
1 b 5 6
2 b 7 8
```
This of course stems from the fact that index (level) names are not 'real' labels like eg column names, but following the aligning logic in pandas for index labels, this can give a bit unexpected results.
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} | 10 | 2015-05-21T16:08:46Z | 2015-06-16T15:40:21Z | 2015-06-07T22:22:40Z | CONTRIBUTOR | null | Fixes #10181
I added a couple of lines to the dataframe test `test_operators` to assert that adding two empty dataframes returns a dataframe that is equal (both using `assert_frame_equal` as well as `.equals`) to an empty dataframe.
I couldn't get vbench to install (I am running on windows) - the error was:
```
c:\dev\code\opensource\pandas-rekcahpassyla>pip install git+https://github.com/pydata/vbench
You are using pip version 6.0.8, however version 6.1.1 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.
Collecting git+https://github.com/pydata/vbench
Cloning https://github.com/pydata/vbench to c:\users\redacted\appdata\local\temp\pip-ruiahg-build
fatal: unable to connect to github.com:
github.com[0: 192.30.252.129]: errno=No error
Clone of 'git://github.com/yarikoptic/vbenchtest.git' into submodule path 'vbench/tests/vbenchtest/vbenchtest' failed
Complete output from command C:\dev\bin\git\cmd\git.exe submodule update --init --recursive -q:
----------------------------------------
Command "C:\dev\bin\git\cmd\git.exe submodule update --init --recursive -q" failed with error code 1 in c:\users\redacted\appdata\local\temp\pip-ruiahg-build
```
The test suite failed for me in master with 1 failure. The same failure, but no others, were observed when running in my branch.
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} | 2 | 2015-05-21T18:13:28Z | 2015-06-02T19:26:12Z | 2015-05-23T06:40:55Z | CONTRIBUTOR | null | …fixes
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| null | 1 | 2015-05-21T20:44:21Z | 2015-05-21T20:55:42Z | 2015-05-21T20:55:42Z | NONE | null | I got `Illegal instruction` error when executing the code below in docker with OS X and ubuntu. However, it works fine using CoreOS. I also find other people have the same issue too. http://stackoverflow.com/questions/29882125/illegal-instruction-core-dumped-when-loading-hdf
Any idea for this?
``` python
import pandas as pd
df = pd.DataFrame([[1,2,3], [2,3,4]], columns=['a', 'b', 'c'])
df.to_hdf(
'test.h5',
'sites',
data_columns=True,
format='t',
complevel=5,
complib='blosc'
)
```
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| null | 2 | 2015-05-21T23:22:54Z | 2015-05-22T21:06:40Z | 2015-05-22T21:06:40Z | NONE | null | I believe I found a bug in interpolation for MultiIndex where linear interpolation works on MultiIndex that contain strings and floats but not for DateTimes. It sounds like linear interpolation on MultiIndexes is not officially supported until next major release however I thought I'd raise this finding in case it helps (and to get experience working as a GitHub noob).
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} | 3 | 2015-05-22T08:53:39Z | 2015-10-23T20:52:42Z | 2015-10-23T20:52:42Z | NONE | null | It seems that pandas.DataFrame operations on Index with timezone-aware dates is order of magnitude slower than on regular datetimes.
for a 500k datetimes created with pandas.date_range, and using DataFrame.shift() to compute deltas between dates, timings goes from **17ms** for standard datetimes to **16seconds** for timezone-aware datetimes.
I don't understand why it is so slow with timezones objects.
I already posted a complete message related to this behavior on stackoverflow yesterday :
http://stackoverflow.com/questions/30385481/performance-of-timezone-aware-pandas-datetimeindex
I'm using latest pandas 0.16.1 from Anaconda, and latest numpy 1.9.2
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} | 2 | 2015-05-22T09:44:57Z | 2015-06-18T15:36:30Z | 2015-06-18T15:36:30Z | CONTRIBUTOR | null | Another somewhat degenerate case that works in 0.15.2, fails in 0.16.1
``` python
import pandas as pd
pd.show_versions()
ts = pd.TimeSeries()
ts[pd.datetime(2012, 1, 1)] = 47
ts2 = pd.TimeSeries(0, pd.date_range('2011-01-01', '2011-01-01'))[:0]
ts2[pd.datetime(2012, 1, 1)] = 47
```
0.15.2 output:
``` python
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.9.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 26 Stepping 5, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
pandas: 0.15.2
nose: 1.3.4
Cython: 0.21
numpy: 1.9.2
scipy: 0.14.0
statsmodels: 0.5.0
IPython: 3.0.0-dev
sphinx: 1.2.3
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.4
bottleneck: 0.8.0
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.2
openpyxl: None
xlrd: 0.9.3
xlwt: None
xlsxwriter: 0.5.7
lxml: 3.4.0
bs4: 4.3.2
html5lib: 0.999
httplib2: None
apiclient: None
rpy2: None
sqlalchemy: 0.9.7
pymysql: None
psycopg2: None
```
0.16.1 output:
``` python
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.9.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 26 Stepping 5, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
pandas: 0.16.1-46-g0aceb38
nose: 1.3.6
Cython: 0.22
numpy: 1.9.2
scipy: 0.14.0
statsmodels: 0.6.1
IPython: 3.1.0
sphinx: 1.3.1
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.4
bottleneck: 0.8.0
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.3
openpyxl: None
xlrd: 0.9.3
xlwt: None
xlsxwriter: 0.7.2
lxml: None
bs4: 4.3.2
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: 1.0.4
pymysql: None
psycopg2: None
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
c:\test_set_empty_series_with_freq.py in <module>()
11 ts2 = pd.TimeSeries(0, pd.date_range('2011-01-01', '2011-01-01'))[:0]
12
---> 13 ts2[pd.datetime(2012, 1, 1)] = 47
c:\python\envs\pandas-0.16.1\lib\site-packages\pandas\core\series.pyc in __setitem__(self, key, value)
687 # do the setitem
688 cacher_needs_updating = self._check_is_chained_assignment_possible()
--> 689 setitem(key, value)
690 if cacher_needs_updating:
691 self._maybe_update_cacher()
c:\python\envs\pandas-0.16.1\lib\site-packages\pandas\core\series.pyc in setitem(key, value)
660 pass
661 try:
--> 662 self.loc[key] = value
663 except:
664 print ""
c:\python\envs\pandas-0.16.1\lib\site-packages\pandas\core\indexing.pyc in __setitem__(self, key, value)
113 def __setitem__(self, key, value):
114 indexer = self._get_setitem_indexer(key)
--> 115 self._setitem_with_indexer(indexer, value)
116
117 def _has_valid_type(self, k, axis):
c:\python\envs\pandas-0.16.1\lib\site-packages\pandas\core\indexing.pyc in _setitem_with_indexer(self, indexer, value)
272 if self.ndim == 1:
273 index = self.obj.index
--> 274 new_index = index.insert(len(index),indexer)
275
276 # this preserves dtype of the value
c:\python\envs\pandas-0.16.1\lib\site-packages\pandas\tseries\index.pyc in insert(self, loc, item)
1523 # check freq can be preserved on edge cases
1524 if self.freq is not None:
-> 1525 if (loc == 0 or loc == -len(self)) and item + self.freq == self[0]:
1526 freq = self.freq
1527 elif (loc == len(self)) and item - self.freq == self[-1]:
c:\python\envs\pandas-0.16.1\lib\site-packages\pandas\tseries\index.pyc in __getitem__(self, key)
1351 getitem = self._data.__getitem__
1352 if np.isscalar(key):
-> 1353 val = getitem(key)
1354 return Timestamp(val, offset=self.offset, tz=self.tz)
1355 else:
IndexError: index 0 is out of bounds for axis 0 with size 0
```
Proposed https://github.com/pydata/pandas/pull/10194
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} | 10 | 2015-05-22T09:59:41Z | 2015-06-18T12:56:00Z | 2015-06-18T12:56:00Z | CONTRIBUTOR | null | Proposed fix for #10193
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| null | 1 | 2015-05-22T10:44:27Z | 2015-05-22T14:04:39Z | 2015-05-22T14:04:39Z | CONTRIBUTOR | null | Found this bug through https://github.com/pydata/pandas/pull/10188 - it caused build failure
``` python
import numpy as np
import pandas as pd
pd.show_versions()
df = pd.DataFrame([[2, 2]], index=pd.DatetimeIndex(['2011-01-01']))
df2 = pd.DataFrame([[1, 1]], index=pd.DatetimeIndex(['2011-01-01']))
df[df > df2] = 47
assert np.all(df.values==47)
df = pd.DataFrame()
df2 = pd.DataFrame()
df[df > df2] = 47
```
results in this error (in both 0.15.2 and 0.16.1)
``` python
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.9.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 26 Stepping 5, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
pandas: 0.16.1-46-g0aceb38
nose: 1.3.6
Cython: 0.22
numpy: 1.9.2
scipy: 0.14.0
statsmodels: 0.6.1
IPython: 3.1.0
sphinx: 1.3.1
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.4
bottleneck: 0.8.0
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.3
openpyxl: None
xlrd: 0.9.3
xlwt: None
xlsxwriter: 0.7.2
lxml: 3.4.4
bs4: 4.3.2
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: 1.0.4
pymysql: None
psycopg2: None
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
c:\test_set_empty_frame_with_boolean.py in <module>()
14 df2 = pd.DataFrame()
15
---> 16 df[df > df2] = 47
17
c:\python\envs\pandas-0.16.1\lib\site-packages\pandas\core\frame.pyc in __setitem__(self, key, value)
2119 self._setitem_array(key, value)
2120 elif isinstance(key, DataFrame):
-> 2121 self._setitem_frame(key, value)
2122 else:
2123 # set column
c:\python\envs\pandas-0.16.1\lib\site-packages\pandas\core\frame.pyc in _setitem_frame(self, key, value)
2153 # df[df > df2] = 0
2154 if key.values.dtype != np.bool_:
-> 2155 raise TypeError('Must pass DataFrame with boolean values only')
2156
2157 self._check_inplace_setting(value)
TypeError: Must pass DataFrame with boolean values only
```
Proposed https://github.com/pydata/pandas/pull/10196
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} | 3 | 2015-05-22T11:34:19Z | 2015-05-22T15:35:03Z | 2015-05-22T14:24:16Z | NONE | null | Hi,
I get a warning that confused me, and in my opinion is wrong.
See code - that should produce warning with further comments.
## INSTALLED VERSIONS
commit: None
python: 2.7.9.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 42 Stepping 7, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
pandas: 0.16.1
nose: 1.3.4
Cython: 0.22
numpy: 1.9.2
scipy: 0.15.1
statsmodels: 0.6.1
IPython: 3.0.0
sphinx: None
patsy: 0.3.0
dateutil: 2.4.0
pytz: 2015.2
bottleneck: None
tables: 3.1.1
numexpr: 2.4
matplotlib: 1.4.3
openpyxl: None
xlrd: 0.9.3
xlwt: None
xlsxwriter: 0.7.1
lxml: None
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 0.9.9
pymysql: None
psycopg2: None
`````` python
import pandas as pd
import sqlite3 as sql
con = sql.connect("Temp_db.db")
df = pd.DataFrame(columns=[["FIRST", "FIRST", "SECOND", "SECOND"], ["ONE", "TWO", "ONE", "TWO"]]) # no space in any column
# following 'to_sql' produces warning:
# UserWarning: The spaces in these column names will not be changed. In pandas versions < 0.14, spaces were converted to underscores.
# However, there are no spaces (see above)
df.to_sql("tmp_table", con=con, if_exists="replace")
# refering to page: http://pydoc.net/Python/pandas/0.14.0/pandas.io.sql/
import re
columns = list(map(str, df.columns))
pat = re.compile('\s+')
print columns
# OUTPUT: ["('FIRST', 'ONE')", "('FIRST', 'TWO')", "('SECOND', 'ONE')", "('SECOND', 'TWO')"]
# ('FIRST',X'ONE'): At position X of a tuple is a whitespace that falsly produces the warning:
print any(map(pat.search, columns)) #true
# quick and dirty fix
columns = [i.replace("', '", "','") for i in columns]
print columns
print any(map(pat.search, columns)) #false
```python
``````
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| null | 1 | 2015-05-22T13:52:43Z | 2015-05-22T14:45:58Z | 2015-05-22T14:45:58Z | NONE | null | Hi,
I have been trying to use the `read_fwf()` dataframe method in pandas 0.16.0. I have supplied a list of tuples for the _colspec_ parameter. There are 9 tuples specified. I have also supplied a list to the _names_ parameter, with 9 column names.
Here's some code:
```
df = pd.read_fwf('c:/6starts.tab',
header=None,
colspec=[(0, 11), (11, 14), (14, 43), (43, 49), (49, 69), (69, 98), (98, 110), (110, 133), (133, 145)],
names=['lotid', 'lottype', 'part', 'qty', 'startdate', 'proc', 'rnum', 'material', 'who'])
```
Here's the traceback (sorry about the formatting):
---
ValueError Traceback (most recent call last)
<ipython-input-15-ff4a00f4ef2b> in <module>()
10 (110, 133),
11 (133, 145)],
---> 12 names=['lotid', 'lottype', 'part', 'qty', 'startdate', 'proc', 'rnum', 'material', 'who']
13 )
C:\Program Files\Anaconda\lib\site-packages\pandas\io\parsers.py in read_fwf(filepath_or_buffer, colspecs, widths, **kwds)
499 kwds['colspecs'] = colspecs
500 kwds['engine'] = 'python-fwf'
--> 501 return _read(filepath_or_buffer, kwds)
502
503
C:\Program Files\Anaconda\lib\site-packages\pandas\io\parsers.py in _read(filepath_or_buffer, kwds)
254 return parser
255
--> 256 return parser.read()
257
258 _parser_defaults = {
C:\Program Files\Anaconda\lib\site-packages\pandas\io\parsers.py in read(self, nrows)
713 raise ValueError('skip_footer not supported for iteration')
714
--> 715 ret = self._engine.read(nrows)
716
717 if self.options.get('as_recarray'):
C:\Program Files\Anaconda\lib\site-packages\pandas\io\parsers.py in read(self, rows)
1561 content = content[1:]
1562
-> 1563 alldata = self._rows_to_cols(content)
1564 data = self._exclude_implicit_index(alldata)
1565
C:\Program Files\Anaconda\lib\site-packages\pandas\io\parsers.py in _rows_to_cols(self, content)
1936 msg = ('Expected %d fields in line %d, saw %d' %
1937 (col_len, row_num + 1, zip_len))
-> 1938 raise ValueError(msg)
1939
1940 if self.usecols:
**ValueError: Expected 9 fields in line 1, saw 7**
---
The problem I'm seeing is that pandas does not appear to be using _colspec_ to parse the file. Instead it seems to be using whitespace and is detecting 7 distinct columns based on that.
I have tried specifying `delimiter=''`to see if that would make a difference, but it doesn't fix it. I have also tried specifying `usecols=[0, 1, 2, 3, 4, 5, 6, 7, 8]` and that seems to prevent the exception occurring, but it still only reads in 7 columns and pads the last 2 columns with _NaN_.
In the snapshot above, the first column is fine, however the 2nd and 3rd columns are merged together (the 'D ' and the '8SL*****' bit). The next snapshot shows some of the desired column widths (highlighted in pink):
I think the issue is in the PythonParser class within the parsers.py file, in the __rows_to_cols()_ method, but I'm not familiar enough with it yet to attempt any sort of fix.
Here is the version information from pandas.show_versions():
## INSTALLED VERSIONS
commit: None
python: 2.7.6.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
pandas: 0.16.0
nose: 1.3.4
Cython: 0.22
numpy: 1.9.2
scipy: 0.15.1
statsmodels: 0.6.1
IPython: 3.1.0
sphinx: 1.2.3
patsy: 0.3.0
dateutil: 2.4.1
pytz: 2015.2
bottleneck: None
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.4.3
openpyxl: 1.8.5
xlrd: 0.9.3
xlwt: 0.7.5
xlsxwriter: 0.6.7
lxml: 3.4.2
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 0.9.9
pymysql: None
psycopg2: None
Please let me know if you need any more information.
Thanks,
Adrian.
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} | 23 | 2015-05-22T20:19:47Z | 2015-06-30T16:58:13Z | 2015-06-30T10:55:04Z | CONTRIBUTOR | null | closes #8882
closes #10139
This is now implemented for all groupbys with the factorization part as well (which is actually a big part fo the time)
```
In [2]: N = 1000000
In [3]: ngroups = 1000
In [4]: np.random.seed(1234)
In [5]: df = DataFrame({'key' : np.random.randint(0,ngroups,size=N),
...: 'data' : np.random.randn(N) })
```
```
def f():
df.groupby('key')['data'].sum()
# run consecutivily
def g2():
for i in range(2):
f()
def g4():
for i in range(4):
f()
def g8():
for i in range(8):
f()
# run in parallel
@test_parallel(num_threads=2)
def pg2():
f()
@test_parallel(num_threads=4)
def pg4():
f()
@test_parallel(num_threads=8)
def pg8():
f()
```
So seeing a nice curve as far as addtl cores are used (as compared to some of my previous posts).
```
In [19]: df
Out[19]:
after before speedup
2 27.3 52.1 1.908425
4 44.8 105.0 2.343750
8 83.2 213.0 2.560096
```
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} | 5 | 2015-05-22T20:57:41Z | 2015-06-02T19:26:12Z | 2015-05-25T11:29:35Z | CONTRIBUTOR | null | Old docstring seemed to be incorrect; overlapping indices are supported e.g.
``` python
>>> import pandas as pd
>>> x = pd.Series(['A', 'B', 'C'])
>>> y = pd.Series(['D', 'E', 'F'])
>>> x.append(y)
0 A
1 B
2 C
0 D
1 E
2 F
dtype: object
```
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| null | 3 | 2015-05-22T21:36:56Z | 2015-05-23T12:40:37Z | 2015-05-23T12:40:37Z | NONE | null | Using a df.diff().hist method creates a different (and inaccurate) multiple plot than using the matplotlib api.
My data are Super Rugby differential scores. The matrix of data is below.
``` python
#Create base matrix of score differentials across Teams (row) x Round (col)
S15_Base = np.matrix([[-10,6,-24,0,28,43,-12,42,-5,-17,14,-6,41,0],#Crus
[10,-10,-5,0,4,-4,-24,8,0,5,-2,1,20,-17],#Reb
[44,-2,5,12,29,-15,0,17,-2,-5,13,-3,-1,10],#Brum
[-44,12,-7,-18,-29,0,-1,-8,-21,1,-16,0,-41,17],#Red
[-14,-17,-3,3,-28,4,1,4,2,0,5,-2,5,-10],#Lion
[14,4,29,0,7,7,24,5,0,-5,16,6,8,4],#Hurr
[-5,-11,-1,-3,-7,0,-12,-7,2,-6,-14,17,-20,5],#Blues
[5,2,24,-3,9,-1,10,7,0,17,8,-1,0,-4],#Chiefs
[-6,17,-8,-16,17,1,6,-42,-2,-7,0,-33,-8,-15],#Sharks
[6,0,1,-19,-17,-43,-10,-17,9,-1,-5,8,0,-21],#Cheetahs
[-12,-4,8,19,0,1,12,-4,21,7,-2,2,0,-5],#Bulls
[12,11,3,16,-9,0,-18,-5,14,7,2,-8,1,0],#Stormers
[-12,10,0,18,-7,15,12,0,-14,5,2,3,-7,15],#Waratahs
[12,-12,-29,-12,-4,-1,-6,0,-9,-7,-8,-17,7,0],#Force
[0,-6,7,3,7,-7,18,0,5,6,-13,33,-5,21],#Highlanders
])
```
I create a dataframe with:
```
import pandas as pd
s15df = pd.DataFrame(S15_Base.T, columns=['Crusaders', 'Rebels', 'Brumbies', 'Reds', 'Lions', 'Hurricanes', 'Blues', 'Chiefs',
'Sharks', 'Cheetahs', 'Bulls', 'Stormers', 'Waratahs', 'Force', 'Highlanders'])
```
The following call produces the multiple plots by team:
``` python
s15df.diff().hist(color='purple', alpha=0.5, figsize=(12,8),sharey=True,sharex=True,bins=20)
```
The result is different in at least one instance (for the Sharks, who never win by 60pts or more), yet have a bin reflecting this frequency. I checked using:
`s15df.Sharks.plot(kind='hist',bins=20)` and
`fig = plt.figure()`
`ax = fig.add_subplot(111)`
`x = [s15df.Sharks ,s15df.Crusaders,s15df.Reds]`
`numBins = 20`
`ax.hist(x,numBins,color=['green','blue','red'],alpha=0.8)`
`plt.show()`
Both the latter two plots were identical and numerically correct, but different than the multiple plot.
PS: Please forgive me if I err in any way posting this as an issue -- am a huge fan of pandas but novice in the issue-tracking thing! :)
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} | 1 | 2015-05-23T13:20:21Z | 2015-06-02T19:26:12Z | 2015-05-25T14:17:18Z | CONTRIBUTOR | null | Updated docs throughout DataFrame methods to mention
that axis can be set to 'index' or 'column' instead of 0 or 1
which improves readability significantly.
Fixes #9658
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