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} | 3 | 2013-07-11T09:14:35Z | 2013-09-27T12:39:28Z | 2013-09-27T12:39:28Z | NONE | null | Hi,
If I have a test.csv file looks like below
```
SecId Time Price P2 P3
10000 2013-5-11 100 10 1
500 2013-5-12 101 11 1
```
if I read in the above file with the following code
```
df =pd.read_csv('test.csv', usecols=['Time', 'Price'], parse_dates=True, index_col=0)
```
then `df.index.name` will be `SecId` instead of `Time`
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} | 13 | 2013-07-11T10:55:52Z | 2016-10-12T23:03:59Z | 2013-09-24T03:43:59Z | CONTRIBUTOR | null | http://stackoverflow.com/questions/17591104/in-pandas-can-i-deeply-copy-a-dataframe-including-its-index-and-column/17591423#17591423
This means if we change the index in place, e.g. with name:
```
df1 = df.copy()
df1.index.name = 'ffg'
```
This changes the name of the df.index.
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So I wondered what the cause of this is, and it seems that because the `@savefig` pseudo-decorator is (usually) set with a `width=6in` the figure becomes a little bit enlarged/shrunken, with the result that the figure is not sharp anymore.
So I tried what it would give if you remove this width. I tried some things (only in visualization.rst and rplot.rst):
- Current situation:
http://jorisvandenbossche.github.io/example-pandas-docs/html-plot-current/visualization.html
- `width=6in` removed, so all figures keeping their own size (and becomen, in general a little bit smaller):
http://jorisvandenbossche.github.io/example-pandas-docs/html-plot-withoutwidth/visualization.html
- `width=6in` removed, so all figures keeping their own size but set larger in the mpl_stylesheet (from `(6,4)` to `(8,6)`):
http://jorisvandenbossche.github.io/example-pandas-docs/html-plot-withoutwidth-larger/visualization.html
I think the second one, with removing the width, is better than the current situation (only df.hist does not seem to follow the default size and is too large with removing the width parameter).
What do you guys think?
@y-p I think you are the last one who touched this to uniform the width of all figures (to 6 inch)
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} | 2 | 2013-07-11T11:48:07Z | 2013-10-03T00:31:53Z | 2013-08-16T19:34:11Z | CONTRIBUTOR | null | I think upcasting to float should occur here.
For example:
```
In [1]: df = pd.DataFrame([[0, 0]])
In [2]: df.loc[0] = np.nan
In [3]: df
Out[3]:
0 1
0 -9223372036854775808 -9223372036854775808
```
Sometimes this is caught:
```
In [11]: df = pd.DataFrame([[0]])
In [12]: df.loc[0] = np.nan
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-12-92653b6a9ef8> in <module>()
----> 1 df.loc[0] = np.nan
/Users/234BroadWalk/pandas/core/indexing.pyc in __setitem__(self, key, value)
86
87 self._setitem_with_indexer(indexer, value)
---> 88
89 def _has_valid_tuple(self, key):
90 pass
/Users/234BroadWalk/pandas/core/indexing.pyc in _setitem_with_indexer(self, indexer, value)
183 if np.prod(values.shape):
184 values[indexer] = value
--> 185
186 def _align_series(self, indexer, ser):
187 # indexer to assign Series can be tuple or scalar
ValueError: cannot convert float NaN to integer
```
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I'm looking only quickly at this, but I'm wondering if this should be recognized and return an offset.
```
from pandas.tseries.frequencies import get_offset
get_offset('30s')
```
or if in statsmodels we should accept custom offsets in place of frequency strings.
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======================================================================
FAIL: test_get_quote_string (pandas.io.tests.test_data.TestYahoo)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/travis/virtualenv/python2.7_with_system_site_packages/local/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/util/testing.py", line 765, in network_wrapper
return t(*args, **kwargs)
File "/home/travis/virtualenv/python2.7_with_system_site_packages/local/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/io/tests/test_data.py", line 121, in test_get_quote_string
assert_frame_equal(df, df2)
File "/home/travis/virtualenv/python2.7_with_system_site_packages/local/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/util/testing.py", line 238, in assert_frame_equal
check_less_precise=check_less_precise)
File "/home/travis/virtualenv/python2.7_with_system_site_packages/local/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/util/testing.py", line 197, in assert_series_equal
assert_almost_equal(left.values, right.values, check_less_precise)
File "/home/travis/virtualenv/python2.7_with_system_site_packages/local/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/util/testing.py", line 141, in assert_almost_equal
assert_almost_equal(a[i], b[i], check_less_precise)
File "/home/travis/virtualenv/python2.7_with_system_site_packages/local/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/util/testing.py", line 170, in assert_almost_equal
1, a / b, decimal=decimal, err_msg=err_msg(a, b), verbose=False)
File "/home/travis/virtualenv/python2.7_with_system_site_packages/local/lib/python2.7/site-packages/numpy/testing/utils.py", line 468, in assert_almost_equal
raise AssertionError(msg)
AssertionError:
Arrays are not almost equal to 5 decimals expected 1.07000 but got 1.06000
----------------------------------------------------------------------
Ran 3530 tests in 193.433s
FAILED (SKIP=37, failures=1)
The command "ci/script.sh" exited with 1.
after_script
$ ci/print_versions.py
INSTALLED VERSIONS
------------------
Python: 2.7.3.final.0
OS: Linux 2.6.32-042stab061.2 #1 SMP Fri Aug 24 09:07:21 MSK 2012 x86_64
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
Cython: 0.19.1
Numpy: 1.7.1
Scipy: 0.9.0
statsmodels: 0.5.0.dev-c9062e4
patsy: 0.1.0
scikits.timeseries: 0.91.3
dateutil: 2.1
pytz: 2013b
bottleneck: 0.6.0
PyTables: 2.3.1
numexpr: 2.1
matplotlib: 1.2.1
openpyxl: 1.6.2
xlrd: 0.9.2
xlwt: 0.7.5
sqlalchemy: Not installed
lxml: 3.2.1
bs4: 4.0.2
html5lib: 1.0b2
Done. Your build exited with 1.
```
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} | 2 | 2013-07-11T15:27:45Z | 2013-09-10T21:49:25Z | 2013-07-24T20:05:17Z | CONTRIBUTOR | null | http://pandas.pydata.org/pandas-docs/dev/timeseries.html#custom-business-days-experimental
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} | 0 | 2013-07-11T15:28:25Z | 2014-06-27T14:38:03Z | 2013-07-11T15:33:03Z | NONE | null | https://github.com/pypa/pip/issues/974
2011k is the version shipped with precise, I hope that's conservative enough
to avoid disruption for existing users.
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} | 18 | 2013-07-11T15:45:24Z | 2013-09-16T17:24:30Z | 2013-07-24T21:45:38Z | CONTRIBUTOR | null | Any reason not to give `DataFrame` a `.isin()` method like `Series`?
The new wrinkle is that the user needs to specify if they want a logical OR or AND.
e.g.
``` python
In [26]: df = pd.DataFrame({'vals': [1, 2, 3, 4], 'ids': ['a', 'b', 'f', 'f'],
'ids2': ['e', 'f', 'c', 'f']})
In [27]: df
Out[27]:
ids ids2 vals
0 a e 1
1 b f 2
2 f c 3
3 f f 4
In [1]: other_ids = pd.Series(['a', 'b', 'c', 'c'])
df.isin(other_ids, how='or')
ids ids2 vals
0 a e 1
1 b f 2
2 f c 3
df.isin(other_ids, how='and')
```
See [this SO post](http://stackoverflow.com/questions/17596733/filtering-rows-from-pandas-dataframe-using-concatenated-strings/17597500#17597500) maybe.
If someone else wants to take this, feel free. Can't promise a PR any time soon, but maybe in the fall :)
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} | 2 | 2013-07-11T15:56:50Z | 2016-10-12T23:03:59Z | 2013-07-17T13:34:50Z | CONTRIBUTOR | null | Trying current master build on Debian sid with
```
$> welp bs4
PATH : /usr/lib/python2.7/dist-packages/bs4/__init__.pyc
SRC PATH : /usr/share/pyshared/bs4/__init__.py
VERSION : Not found
__version__: '4.2.0'
PACKAGE : python-bs4
ii python-bs4 4.2.0-2 all error-tolerant HTML parser for Python
python-bs4:
Installed: 4.2.0-2
Candidate: 4.2.0-2
Version table:
*** 4.2.0-2 0
900 http://debian.lcs.mit.edu/debian/ jessie/main amd64 Packages
600 http://debian.lcs.mit.edu/debian/ sid/main amd64 Packages
100 /var/lib/dpkg/status
4.1.0-1 0
100 http://debian.lcs.mit.edu/debian/ wheezy/main amd64 Packages
```
test crashes
```
======================================================================
ERROR: test_to_html_compat (pandas.io.tests.test_html.TestReadHtmlBase)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_html.py", line 88, in test_to_html_compat
index_col=0)[0]
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_html.py", line 67, in run_read_html
return read_html(*args, **kwargs)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/html.py", line 900, in read_html
attrs)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/html.py", line 772, in _parse
for table in tables]
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/html.py", line 186, in <genexpr>
return (self._build_table(table) for table in tables)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/html.py", line 345, in _build_table
body = self._parse_raw_tbody(table)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/html.py", line 367, in _parse_raw_tbody
res = self._parse_tr(tbody[0])
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/html.py", line 399, in _parse_tr
return element.find_all('tr')
File "/usr/lib/python2.7/dist-packages/bs4/element.py", line 1167, in find_all
return self._find_all(name, attrs, text, limit, generator, **kwargs)
File "/usr/lib/python2.7/dist-packages/bs4/element.py", line 485, in _find_all
return [element for element in generator
File "/usr/lib/python2.7/dist-packages/bs4/element.py", line 1185, in descendants
current = current.next_element
AttributeError: 'NoneType' object has no attribute 'next_element'
```
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} | 11 | 2013-07-11T16:00:03Z | 2013-07-18T04:21:25Z | 2013-07-18T01:11:41Z | CONTRIBUTOR | null | While building debian package for 0.11.0+git43-g7b2eaa4, matplotlib 1.1.1~rc2-1 and while building it should use Agg backend, that is how tests are invoked
```
python-test%: python-install%
ifeq (,$(filter nocheck,$(DEB_BUILD_OPTIONS)))
echo "backend : Agg" >| $(CURDIR)/build/matplotlibrc
: # Run unittests here against installed pandas
echo "$*" | grep -q '^3' && PY=3 || PY=$*; \
export PYTHONPATH=`/bin/ls -d $$PWD/debian/tmp/usr/lib/python$$PY/*/`; \
export MPLCONFIGDIR=$(CURDIR)/build HOME=$(CURDIR)/build; \
cd build/; python$* /usr/bin/nosetests -s -v -a '!network' $(EXCLUDE_TESTS$*) pandas;
else
: # Skip unittests due to nocheck
endif
```
and here is a prototypical error (there is more for other invocations for the _check):
```
======================================================================
ERROR: test_line_plot_period_frame (pandas.tseries.tests.test_plotting.TestTSPlot)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/tseries/tests/test_plotting.py", line 165, in test_line_plot_period_frame
_check_plot_works(df.plot, df.index.freq)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/tseries/tests/test_plotting.py", line 1006, in _check_plot_works
plt.savefig(path)
File "/usr/lib/pymodules/python2.7/matplotlib/pyplot.py", line 471, in savefig
return fig.savefig(*args, **kwargs)
File "/usr/lib/pymodules/python2.7/matplotlib/figure.py", line 1185, in savefig
self.canvas.print_figure(*args, **kwargs)
File "/usr/lib/pymodules/python2.7/matplotlib/backend_bases.py", line 2021, in print_figure
**kwargs)
File "/usr/lib/pymodules/python2.7/matplotlib/backends/backend_agg.py", line 477, in print_png
filename_or_obj, self.figure.dpi)
RuntimeError: Error building image
```
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} | 43 | 2013-07-11T16:03:58Z | 2016-10-12T23:04:00Z | 2013-07-16T14:19:22Z | CONTRIBUTOR | null | typical error with
```
======================================================================
FAIL: test_banklist (pandas.io.tests.test_html.TestReadHtmlBase)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_html.py", line 114, in test_banklist
attrs={'id': 'table'})
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_html.py", line 67, in run_read_html
return read_html(*args, **kwargs)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/html.py", line 900, in read_html
attrs)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/html.py", line 769, in _parse
raise retained
AssertionError: No tables found
```
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https://api.github.com/repos/pandas-dev/pandas/issues/4215 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4215/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4215/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4215/events | https://github.com/pandas-dev/pandas/issues/4215 | 16,639,252 | MDU6SXNzdWUxNjYzOTI1Mg== | 4,215 | test_invalid_colormap: ValueError not raised | {
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} | 10 | 2013-07-11T16:05:59Z | 2016-10-12T23:04:00Z | 2013-07-13T18:19:43Z | CONTRIBUTOR | null | ```
======================================================================
FAIL: test_invalid_colormap (pandas.tests.test_graphics.TestDataFrameGroupByPlots)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.11.0+git43-g7b2eaa4/debian/tmp/usr/lib/python2.7/dist-packages/pandas/tests/test_graphics.py", line 995, in test_invalid_colormap
self.assertRaises(ValueError, df.plot, colormap='invalid_colormap')
AssertionError: ValueError not raised
```
that is under Agg backend and matplotlib 1.1.1~rc2-1
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https://api.github.com/repos/pandas-dev/pandas/issues/4216 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4216/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4216/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4216/events | https://github.com/pandas-dev/pandas/issues/4216 | 16,639,581 | MDU6SXNzdWUxNjYzOTU4MQ== | 4,216 | VIS: DataFrame.plot(kind='kde') does not display the legend. | {
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I would like to have the legend when I display the 'kde' (also called 'dentity') of a DataFrame. The `plot` method works well with the other `kind` options (i.e. `bar`, `barh` and `line`).
Following piece of code:
``` python
import numpy as np
import pandas as pd
df = pd.DataFrame({'X': np.random.randn(500),
'Y': 2. + np.random.randn(500)*0.75})
# then
df.plot(kind='kde')
```
does not display the legend for `X` and `Y` (even if I set `legend=True` which is the default value of the `legend` parameter). Note: I'm on master > 0.12rc1
Best regards,
Damien
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} | 2 | 2013-07-11T16:29:01Z | 2014-06-27T11:45:17Z | 2013-07-14T14:26:48Z | MEMBER | null | Closes #4203.
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} | 2 | 2013-07-11T20:19:26Z | 2014-06-16T22:16:17Z | 2013-07-25T01:37:31Z | NONE | null | closes https://github.com/pydata/pandas/issues/4046
```
λ sudo python ./setup.py develop
...
Installed /home/user1/src/pandas
Processing dependencies for pandas==v0.12.0rc1-48-g9442eac
Searching for numpy==1.7.1
Best match: numpy 1.7.1
Adding numpy 1.7.1 to easy-install.pth file
λ python -c 'import pandas; print pandas.version.version'
v0.12.0rc1-48-g9442eac
```
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} | 4 | 2013-07-11T21:27:15Z | 2013-07-26T18:47:14Z | 2013-07-26T12:03:37Z | NONE | null | entries with "Inf" (beginning with upper case I) will assign that column a dtype of object while "inf" is parsed as infinity.
I believe that in R, the function write.table uses "Inf" (with the uppercase) which would make importing tables exported from R more difficult.
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} | 28 | 2013-07-12T00:54:27Z | 2014-06-14T11:07:09Z | 2013-07-26T12:03:37Z | CONTRIBUTOR | null | Makes 'inf' checks case insensitive using strcasecmp
Fixes #4219.
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https://api.github.com/repos/pandas-dev/pandas/issues/4221 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4221/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4221/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4221/events | https://github.com/pandas-dev/pandas/pull/4221 | 16,679,313 | MDExOlB1bGxSZXF1ZXN0Njg5MDM2OA== | 4,221 | BUG: Display the legend when calling plot with kind='density'. GH4216 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4222 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4222/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4222/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4222/events | https://github.com/pandas-dev/pandas/issues/4222 | 16,683,515 | MDU6SXNzdWUxNjY4MzUxNQ== | 4,222 | sparc test_read_dta10: KeyError: 0 self.dtyplist = [self.DTYPE_MAP[typ] for typ in typlist] | {
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======================================================================
ERROR: test_read_dta10 (pandas.io.tests.test_stata.StataTests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_stata.py", line 205, in test_read_dta10
written_and_read_again = self.read_dta(path)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_stata.py", line 41, in read_dta
return read_stata(file, convert_dates=True)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/stata.py", line 38, in read_stata
reader = StataReader(filepath_or_buffer, encoding)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/stata.py", line 305, in __init__
self._read_header()
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/stata.py", line 331, in _read_header
self.dtyplist = [self.DTYPE_MAP[typ] for typ in typlist]
KeyError: 0
```
on 0.12.0~rc1+git43-g7b2eaa4-1
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https://api.github.com/repos/pandas-dev/pandas/issues/4223 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4223/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4223/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4223/events | https://github.com/pandas-dev/pandas/issues/4223 | 16,683,556 | MDU6SXNzdWUxNjY4MzU1Ng== | 4,223 | BLD: sparc test_decimalDecodeTest - {u'a': 4.56} + {u'a': 4.5600000000000005} | {
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} | 9 | 2013-07-12T14:17:33Z | 2013-07-18T20:31:48Z | 2013-07-18T20:31:48Z | CONTRIBUTOR | null | ```
======================================================================
FAIL: test_decimalDecodeTest (pandas.io.tests.test_json.test_ujson.UltraJSONTests)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_json/test_ujson.py", line 102, in test_decimalDecodeTest
self.assertEqual(sut, decoded)
AssertionError: {u'a': 4.56} != {u'a': 4.5600000000000005}
- {u'a': 4.56}
+ {u'a': 4.5600000000000005}
```
on 0.12.0~rc1+git43-g7b2eaa4-1
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https://api.github.com/repos/pandas-dev/pandas/issues/4224 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4224/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4224/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4224/events | https://github.com/pandas-dev/pandas/issues/4224 | 16,685,498 | MDU6SXNzdWUxNjY4NTQ5OA== | 4,224 | fast cross correlation function/method | {
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} | [] | closed | false | null | [] | null | 3 | 2013-07-12T14:56:03Z | 2013-07-20T22:21:36Z | 2013-07-20T22:21:36Z | MEMBER | null | this is bordering on not being the domain of pandas, but i think a library that is advertised at being good at time series should include this functionality
the numpy version is dog slow
something like
``` python
s.xcorr(s2, lags=100, scaling='normalized') # first 100 lags, scaled to be -1 <= 0 <= 1
df.xcorr() # all non repeating pairs of series_i, series_j xcorrs
df.xcorr(s2) # xcorr of all series in a frame with s2
```
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] | closed | false | null | [] | null | 1 | 2013-07-12T19:27:22Z | 2013-07-13T00:33:18Z | 2013-07-13T00:33:18Z | NONE | null | the following code creates an infinite loop in python:
import pandas as pd
cols = [pd.Period('1998', 'A-DEC'), pd.Period('1999', 'A-DEC'), 'test']
df = pd.DataFrame(np.random.randn(10, 3), columns=cols)
df[[pd.Period('1998'), pd.Period('1999')]]
It appears to be because Index.get_indexer changes the index from an int type to an object and recalls get_indexer which then changes it back to an object.
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} | 8 | 2013-07-12T21:23:55Z | 2013-08-10T01:48:29Z | 2013-07-14T13:32:53Z | NONE | null | Shouldn't it carry all possible properties instead?
Steps to reproduce:
``` python
import pandas as pd
st = pd.Timestamp('2013-07-01 00:00:00', tz='America/Los_Angeles')
et = pd.Timestamp('2013-07-02 00:00:00', tz='America/Los_Angeles')
dr = pd.date_range(st, et, freq='H', name='timebucket')
assert dr.name == 'timebucket'
dr = dr[1:]
assert dr.name == None
```
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] | closed | false | null | [] | null | 11 | 2013-07-12T23:33:43Z | 2013-07-13T00:27:45Z | 2013-07-13T00:26:57Z | MEMBER | null | i'm an sql noob, but this seems like it should work without a hitch
```
In [11]: import sqlite3 as sql
In [12]: dfi = DataFrame(randint(10, size=(10, 3)))
In [13]: conn = sql.connect(':memory:')
In [14]: dfi.to_sql('blah', conn)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-14-25b1bf847714> in <module>()
----> 1 dfi.to_sql('blah', conn)
/home/phillip/Documents/code/py/pandas/pandas/core/frame.pyc in to_sql(self, name, con, flavor, if_exists, **kwargs)
1519 """
1520 from pandas.io.sql import write_frame
-> 1521 write_frame(self, name, con, flavor=flavor, if_exists=if_exists, **kwargs)
1522
1523 @Appender(fmt.docstring_to_string, indents=1)
/home/phillip/Documents/code/py/pandas/pandas/io/sql.pyc in write_frame(frame, name, con, flavor, if_exists, **kwargs)
206 create = "DROP TABLE %s" % name
207 elif not exists:
--> 208 create = get_schema(frame, name, flavor)
209
210 if create is not None:
/home/phillip/Documents/code/py/pandas/pandas/io/sql.pyc in get_schema(frame, name, flavor, keys)
289 lookup_type = lambda dtype: get_sqltype(dtype.type, flavor)
290 # Replace spaces in DataFrame column names with _.
--> 291 safe_columns = [s.replace(' ', '_').strip() for s in frame.dtypes.index]
292 column_types = zip(safe_columns, map(lookup_type, frame.dtypes))
293 if flavor == 'sqlite':
AttributeError: 'numpy.int64' object has no attribute 'replace'
```
i'm guessing this is because `sqlite3` doesn't see `int64` objects as `int`s.
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} | 0 | 2013-07-13T00:44:41Z | 2014-07-16T08:19:04Z | 2013-07-13T01:27:34Z | CONTRIBUTOR | null | closes #4222
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} | 1 | 2013-07-13T14:34:58Z | 2013-07-14T19:21:18Z | 2013-07-14T19:21:09Z | CONTRIBUTOR | null | Initializing a DatetimeIndex with a list of strings behaves differently than initializing with a numpy array of strings. To me these should behave the same and I personally like the list behavior better. My understanding of the tz argument to DatetimeIndex is that it is localizing rather than converting in which case the numpy array case is inconsistent. I don't think there should be an assumption made about the tz of the strings before indicating it by localizing.
``` python
>>> idx = ['11/10/2005 08:00:00','11/10/2005 09:00:00']
>>> DatetimeIndex(idx, tz='US/Eastern')
<class 'pandas.tseries.index.DatetimeIndex'>
[2005-11-10 08:00:00, 2005-11-10 09:00:00]
Length: 2, Freq: None, Timezone: US/Eastern
>>> import numpy as np
>>> idxnp = np.array(idx)
>>> DatetimeIndex(idxnp, tz='US/Eastern')
<class 'pandas.tseries.index.DatetimeIndex'>
[2005-11-10 03:00:00, 2005-11-10 04:00:00]
Length: 2, Freq: None, Timezone: US/Eastern
```
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} | 3 | 2013-07-13T14:42:43Z | 2013-10-02T21:01:13Z | 2013-10-02T21:01:13Z | CONTRIBUTOR | null | Many times data is already presented assuming a local timezone (e.g., with two hour 1s in the fall dst). Currently there is no way to localize this data as it raises an ambiguous time error. Please see the link for an example.
http://stackoverflow.com/questions/17370826/create-pandas-timezone-aware-datetimeindex-on-already-local-timezone
I think many times the simple assumption about the second hour being non-dst is a sound one and should be available. Perhaps there is already a way to do this, but I have yet to find it.
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} | 8 | 2013-07-13T18:27:35Z | 2014-06-18T22:09:26Z | 2013-07-14T19:20:15Z | MEMBER | null | Possibly a fix for #4229.
The rationale is that an array of strings should be handled in the same way as a list of strings (after applying `np.asarray(list)`), and I supposed that the list was handling the timezone correctly.
##
More in detail:
- handling of the list of strings: https://github.com/pydata/pandas/blob/master/pandas/tseries/index.py#L196 => returning `data`
- handling of an array of strings: https://github.com/pydata/pandas/blob/master/pandas/tseries/index.py#L211 => returning directly `subarr`
Because in the case of an array `subarr` is set as a DatetimeIndex (instead of as `.values` attribute of it => array of datetime64), the array is not localized to UTC (https://github.com/pydata/pandas/blob/master/pandas/tseries/index.py#L249) but assumed to be UTC. So, in fact, the `tz` keyword is ignored.
##
Something else: it is not completely clear what the `tz` keyword is supposed to do (it is not documented in the DatetimeIndex docstring). But I assumed it is to say that the given values to DatetimeIndex are in that timezone (and so the behaviour with a list is correct). However, it is also a little bit strange that eg `to_datetime` has not such of a keyword then.
##
PS: the PR is not ready (I want to add some tests, release notes, and there is too much whitespace in the commit), but I just wanted to submit it already to see if this makes sense.
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} | 1 | 2013-07-14T00:08:49Z | 2013-08-23T13:03:32Z | 2013-08-23T13:03:32Z | CONTRIBUTOR | null | ```
import pandas as pd
df = pd.DataFrame({'a': [], 'b': [], 'c': []})
df = df.set_index(['a', 'b'])
print df.c.index.names
print df.c[df.c.isnull()].index.names
```
Output:
```
['a', 'b']
[None]
```
The problem is that the empty boolean mask isn't recognized as a boolean array by infer_dtype in inference.pyx.
I have a fix here: 87b9f21d0f298e35c5ec965b48b53ff17d40ab7e. If you agree with the approach I'll submit the PR.
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} | 12 | 2013-07-14T00:18:58Z | 2014-06-14T18:14:51Z | 2013-08-23T13:03:40Z | CONTRIBUTOR | null | #4235
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} | 19 | 2013-07-14T14:21:47Z | 2014-06-23T00:41:35Z | 2013-07-24T21:45:47Z | CONTRIBUTOR | null | WIP for now.
See #4211 for more info.
A few things to check before this is ready to merge:
This is basically a convenience method. I use the `Series` method for each column passed, and aggregate the methods sensibly.
A few questions before merge though:
- Do we have a preference for `any`/`all` vs. `and`/`or`? Seems like `any/all` would be more consistent with other methods like `df.dropna(how='all')`
- I'm not thrilled about all the nested if statements. The problem is accepting both dicts and just flat arrays as values. The idea is to use dicts like `{colname: array_of_possible_values}` if the set of possible values to match against differs by columns (most likely case I think). I need the extra nested if statement here:
``` python
if how == 'and':
if isinstance(values, dict):
cond_n = len(values)
else:
cond_n = len(self.columns) # Flat matching.
elif how == 'or':
cond_n = 1
```
since the two ways of calling will be a bit different. If you're passing a dict it will probably just be df.isin(values=dict). If you don't care which column matches what, the call will be df[subset_of_columns].isin(values). It's messy, but it works.
- I check for empty values, and raise an error instead of just returning all `False`s. Passing an empty list as values, it would actually would work. `Series.isin([])` will return all Falses. But it would fail on an empty dict, so I just check for it ahead of time and raise an error.
- Also, I may have messed up the history. I thought I rebased and squashed everything into one commit, but apparently not. I had some merge conflicts that I had to fix (just picking HEAD over the old stuff everywhere). I'll take a closer look at this. Also I may have done `git pull` instead of `git pull --rebase` at some point. Will that mess up the history?
Happy to move this to .13 also.
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} | 3 | 2013-07-14T23:54:55Z | 2014-06-16T17:36:41Z | 2013-07-15T01:07:52Z | CONTRIBUTOR | null | Removed ambiguous ujson test, see #4223, #4186.
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} | 1 | 2013-07-15T03:51:42Z | 2014-07-03T21:40:16Z | 2013-07-15T04:02:51Z | MEMBER | null | closes #4239 #4194
using scipy 0.10 for 2.7 builds and 0.12 for 3.2 and 3.3 builds
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cc @cpcloud @jtratner
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'Series', 'date_range' or other Pandas methods are missing 'pd.'.
If you evaluate the code examples, you get this error:
```
NameError: name 'Series' is not defined
```
NOTE: This error occurs when you're evaluating sample code in the docs.
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} | 2 | 2013-07-15T21:50:54Z | 2013-07-15T22:56:02Z | 2013-07-15T22:56:02Z | CONTRIBUTOR | null | The following currently are exceptions in master(the corresponding operations on DataFrames work though)
```
In [4]: s = Series([1,2,3,4],['foo','bar','foo','bah'])
In [5]: s.ix[['foo','bar','bah','bam']]
NotImplementedError: cannot handle non-unique indexing for non-DataFrame (yet)
In [6]: s[['foo','bar','bah','bam']]
AssertionError: Index length did not match values
```
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```
In [3]: s = Series([1,2,3,4],['foo','bar','foo','bah'])
In [4]: s.ix[['foo','bar','bah','bam']]
Out[4]:
foo 1
foo 3
bar 2
bah 4
bam NaN
dtype: float64
In [5]: s[['foo','bar','bah','bam']]
Out[5]:
foo 1
foo 3
bar 2
bah 4
bam NaN
dtype: float64
```
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commit 1e69dade1309b494e43f26f9831326c2ce63f7de
Merge: 5be1e5a 5b908a5
Author: Phillip Cloud [email protected]
Date: Mon Jul 15 16:17:06 2013 -0700
```
Merge pull request #4248 from cpcloud/mpl-1.1.1-build
BLD: use mpl 1.1.1 in python 2.7 production travis build
```
This happened after doing:
``` python
python setup.py clean
python setup.py install
```
Here's the error:
``` python
In [1]: import pandas
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
<ipython-input-1-d6ac987968b6> in <module>()
----> 1 import pandas
/Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/site-packages/pandas-0.12.0.dev_1e69dad-py2.7-macosx-10.5-x86_64.egg/pandas/__init__.pyc in <module>()
25 import pandas.core.config_init
26
---> 27 from pandas.core.api import *
28 from pandas.sparse.api import *
29 from pandas.stats.api import *
/Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/site-packages/pandas-0.12.0.dev_1e69dad-py2.7-macosx-10.5-x86_64.egg/pandas/core/api.py in <module>()
16 from pandas.core.panel4d import Panel4D
17 from pandas.core.groupby import groupby
---> 18 from pandas.core.reshape import (pivot_simple as pivot, get_dummies,
19 lreshape)
20
/Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/site-packages/pandas-0.12.0.dev_1e69dad-py2.7-macosx-10.5-x86_64.egg/pandas/core/reshape.py in <module>()
6 import numpy as np
7
----> 8 import six
9
10 from pandas.core.series import Series
ImportError: No module named six
```
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} | 7 | 2013-07-16T02:52:45Z | 2014-06-26T17:39:32Z | 2013-07-31T12:20:38Z | CONTRIBUTOR | null | Cleans up imports throughout pandas, removing unused and reordering to
better match PEP8 where reasonable. Thanks to PyCharm for making this much
easier. Doesn't change any .pyx or .pyd files. (inspired by import issue
in #4249)
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} | 8 | 2013-07-16T02:55:33Z | 2016-10-12T23:04:00Z | 2013-07-17T13:28:48Z | CONTRIBUTOR | null | Was testing 0.12.0~rc1+git79-g50eff60 on a sparc for the recent fixes: test_html tests puked before trying with
```
======================================================================
ERROR: test_bad_url_protocol (pandas.io.tests.test_html.TestReadHtmlBase)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_html.py", line 98, in setUp
self.try_skip()
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_html.py", line 87, in try_skip
self.flavor != ['lxml']):
AttributeError: 'TestReadHtmlBase' object has no attribute 'flavor'
```
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} | 2 | 2013-07-16T02:57:41Z | 2016-10-12T23:04:00Z | 2013-07-17T13:29:00Z | CONTRIBUTOR | null | with 0.12.0~rc1+git79-g50eff60
```
======================================================================
FAIL: test_fallback_success (pandas.io.tests.test_html.TestReadHtmlLxml)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_html.py", line 449, in test_fallback_success
'html5lib'])
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_html.py", line 420, in run_read_html
return read_html(*args, **kwargs)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/html.py", line 906, in read_html
attrs)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/html.py", line 765, in _parse
parser = _parser_dispatch(flav)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/html.py", line 723, in _parser_dispatch
raise AssertionError("You're using a version"
AssertionError: You're using a version of BeautifulSoup4 (4.2.0) that has been known to cause problems on certain operating systems such as Debian. Please install a version of BeautifulSoup4 != 4.2.0, both earlier and later releases will work.
```
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} | 19 | 2013-07-16T10:48:28Z | 2014-07-11T22:39:12Z | 2013-08-21T13:32:23Z | NONE | null | when using raise e, the error stack app user received will begin in _apply_standard method.
Use raise instead, so that user could received error stack in funv(v) call. Easier for user to debug.
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} | 7 | 2013-07-16T12:13:12Z | 2013-07-22T16:50:58Z | 2013-07-22T16:50:58Z | NONE | null | We use 9999-12-31 as end of time while processing. No issue with it in .10.1 or .11 release. Was trying .12rc1 and ran into the issue where I can create a dataframe with 9999-12-31 00:00:00 but if an apply operation does the same, there is an overflow reported.
In [1]: import pandas as pd
In [2]: import datetime
In [3]: data = [("a{0}".format(i), 99991231, 20130715) for i in xrange(10)]
In [4]: data
Out[4]:
[('a0', 99991231, 20130715),
('a1', 99991231, 20130715),
('a2', 99991231, 20130715),
('a3', 99991231, 20130715),
('a4', 99991231, 20130715),
('a5', 99991231, 20130715),
('a6', 99991231, 20130715),
('a7', 99991231, 20130715),
('a8', 99991231, 20130715),
('a9', 99991231, 20130715)]
In [5]: df = pd.DataFrame(data)
In [6]:
In [6]: df
Out[6]:
0 1 2
0 a0 99991231 20130715
1 a1 99991231 20130715
2 a2 99991231 20130715
3 a3 99991231 20130715
4 a4 99991231 20130715
5 a5 99991231 20130715
6 a6 99991231 20130715
7 a7 99991231 20130715
8 a8 99991231 20130715
9 a9 99991231 20130715
## In [8]: df.apply(lambda x: (x[0], datetime.datetime(9999,12,31),datetime.datetime(9999,12,31)), axis=1)
ValueError Traceback (most recent call last)
/home/ahanda/python/learning/src/<ipython-input-8-5b4db85f40d0> in <module>()
----> 1 df.apply(lambda x: (x[0], datetime.datetime(9999,12,31),datetime.datetime(9999,12,31)), axis=1)
/logs/tmp/taserv/pandasrc/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/core/frame.pyc in apply(self, func, axis, broadcast, raw, args, **kwds)
4414 return self._apply_raw(f, axis)
4415 else:
-> 4416 return self._apply_standard(f, axis)
4417 else:
4418 return self._apply_broadcast(f, axis)
/logs/tmp/taserv/pandasrc/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/core/frame.pyc in _apply_standard(self, func, axis, ignore_failures)
4503 if axis == 1:
4504 result = result.T
-> 4505 result = result.convert_objects(copy=False)
4506
4507 return result
/logs/tmp/taserv/pandasrc/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/core/frame.pyc in convert_objects(self, convert_dates, convert_numeric, copy)
1712 return self._constructor(self._data.convert(convert_dates=convert_dates,
1713 convert_numeric=convert_numeric,
-> 1714 copy=copy))
1715
1716 #----------------------------------------------------------------------
/logs/tmp/taserv/pandasrc/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/core/internals.pyc in convert(self, _args, *_kwargs)
1305
1306 def convert(self, _args, *_kwargs):
-> 1307 return self.apply('convert', _args, *_kwargs)
1308
1309 def replace(self, _args, *_kwargs):
/logs/tmp/taserv/pandasrc/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/core/internals.pyc in apply(self, f, _args, *_kwargs)
1267 applied = f(blk, _args, *_kwargs)
1268 else:
-> 1269 applied = getattr(blk,f)(_args, *_kwargs)
1270
1271 if isinstance(applied,list):
/logs/tmp/taserv/pandasrc/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/core/internals.pyc in convert(self, convert_dates, convert_numeric, copy)
721 values = self.iget(i)
722
--> 723 values = com._possibly_convert_objects(values, convert_dates=convert_dates, convert_numeric=convert_numeric)
724 values = _block_shape(values)
725 items = self.items.take([i])
/logs/tmp/taserv/pandasrc/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/core/common.pyc in _possibly_convert_objects(values, convert_dates, convert_numeric)
1108
1109 else:
-> 1110 values = lib.maybe_convert_objects(values, convert_datetime=convert_dates)
1111
1112 # convert to numeric
/logs/tmp/taserv/pandasrc/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/lib.so in pandas.lib.maybe_convert_objects (pandas/lib.c:36583)()
/logs/tmp/taserv/pandasrc/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/tslib.so in pandas.tslib.convert_to_tsobject (pandas/tslib.c:12743)()
/logs/tmp/taserv/pandasrc/lib/python2.7/site-packages/pandas-0.12.0rc1-py2.7-linux-x86_64.egg/pandas/tslib.so in pandas.tslib._check_dts_bounds (pandas/tslib.c:13800)()
ValueError: Out of bounds nanosecond timestamp: 9999-12-31 00:00:00
In [9]: df.apply(lambda x: (x[0], datetime.datetime(2100,12,31),datetime.datetime(2100,12,31)), axis=1)
Out[9]:
0 1 2
0 a0 2100-12-31 00:00:00 2100-12-31 00:00:00
1 a1 2100-12-31 00:00:00 2100-12-31 00:00:00
2 a2 2100-12-31 00:00:00 2100-12-31 00:00:00
3 a3 2100-12-31 00:00:00 2100-12-31 00:00:00
4 a4 2100-12-31 00:00:00 2100-12-31 00:00:00
5 a5 2100-12-31 00:00:00 2100-12-31 00:00:00
6 a6 2100-12-31 00:00:00 2100-12-31 00:00:00
7 a7 2100-12-31 00:00:00 2100-12-31 00:00:00
8 a8 2100-12-31 00:00:00 2100-12-31 00:00:00
9 a9 2100-12-31 00:00:00 2100-12-31 00:00:00
In [11]: data1 = [("a{0}".format(i), datetime.datetime(9999,12,31), datetime.datetime(9999,12,31)) for i in xrange(10)]
In [12]: df1 = pd.DataFrame(data1)
In [13]: df1
Out[13]:
0 1 2
0 a0 9999-12-31 00:00:00 9999-12-31 00:00:00
1 a1 9999-12-31 00:00:00 9999-12-31 00:00:00
2 a2 9999-12-31 00:00:00 9999-12-31 00:00:00
3 a3 9999-12-31 00:00:00 9999-12-31 00:00:00
4 a4 9999-12-31 00:00:00 9999-12-31 00:00:00
5 a5 9999-12-31 00:00:00 9999-12-31 00:00:00
6 a6 9999-12-31 00:00:00 9999-12-31 00:00:00
7 a7 9999-12-31 00:00:00 9999-12-31 00:00:00
8 a8 9999-12-31 00:00:00 9999-12-31 00:00:00
9 a9 9999-12-31 00:00:00 9999-12-31 00:00:00
In [15]: np.version.version
Out[15]: '1.6.1'
In [16]: pd.version.version
Out[16]: '0.12.0rc1'
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https://api.github.com/repos/pandas-dev/pandas/issues/4256 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4256/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4256/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4256/events | https://github.com/pandas-dev/pandas/issues/4256 | 16,808,490 | MDU6SXNzdWUxNjgwODQ5MA== | 4,256 | Storing string in indf file (python 3 only issue) | {
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} | [] | closed | false | null | [] | null | 8 | 2013-07-16T13:10:33Z | 2013-07-16T13:48:10Z | 2013-07-16T13:38:30Z | NONE | null | `str` from python 3 are more or less the same as `unicode` from python 2.7. It appears that numpy or pytables or pandas (check the guilty but I vote for pytables) does not properly handle python 3 string and see them as object.
Since it's working with python 2.7, it should be a way to revert python 3 string to python 2.7 string if no other cleaner solution exists...
Here there is some code to play with:
``` python
import pandas as pd
df = pd.DataFrame([ ['span', '2000', 's', '0.1', '2000.', '10.'],
['dt', '10', 's', '0.1', '2.', '0.1'],
['t_A', '1750', 's', '0.', '1000.', '1.'],
['d_alpha', '0.05', 'µm', '0', '100', '0.005'],
['orientation', '1', ' ', '0', '100', '1'],
['sac', '1', ' ', '0', '1', '1'],
],
columns=['name', 'value', 'unit', 'min', 'max', 'step'])
print(df)
print(df.values.dtype)
```
```
name value unit min max step
0 span 2000 s 0.1 2000. 10.
1 dt 10 s 0.1 2. 0.1
2 t_A 1750 s 0. 1000. 1.
3 d_alpha 0.05 µm 0 100 0.005
4 orientation 1 0 100 1
5 sac 1 0 1 1
object
```
``` python
df.to_hdf('test.h5', 'df')
```
```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-19-ed2af0f74bd2> in <module>()
----> 1 df.to_hdf('test.h5', 'df')
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/pandas/core/generic.py in to_hdf(self, path_or_buf, key, **kwargs)
486 """ activate the HDFStore """
487 from pandas.io import pytables
--> 488 return pytables.to_hdf(path_or_buf, key, self, **kwargs)
489
490 # install the indexerse
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/pandas/io/pytables.py in to_hdf(path_or_buf, key, value, mode, complevel, complib, **kwargs)
156 if isinstance(path_or_buf, str):
157 with get_store(path_or_buf, mode=mode, complevel=complevel, complib=complib) as store:
--> 158 f(store)
159 else:
160 f(path_or_buf)
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/pandas/io/pytables.py in <lambda>(store)
152 def to_hdf(path_or_buf, key, value, mode=None, complevel=None, complib=None, **kwargs):
153 """ store this object, close it if we opened it """
--> 154 f = lambda store: store.put(key, value, **kwargs)
155
156 if isinstance(path_or_buf, str):
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/pandas/io/pytables.py in put(self, key, value, table, append, **kwargs)
534 table
535 """
--> 536 self._write_to_group(key, value, table=table, append=append, **kwargs)
537
538 def remove(self, key, where=None, start=None, stop=None):
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/pandas/io/pytables.py in _write_to_group(self, key, value, index, table, append, complib, **kwargs)
869 raise ValueError('Compression not supported on non-table')
870
--> 871 s.write(obj = value, append=append, complib=complib, **kwargs)
872 if s.is_table and index:
873 s.create_index(columns = index)
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/pandas/io/pytables.py in write(self, obj, **kwargs)
1996 self.attrs.ndim = data.ndim
1997 for i, ax in enumerate(data.axes):
-> 1998 self.write_index('axis%d' % i, ax)
1999
2000 # Supporting mixed-type DataFrame objects...nontrivial
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/pandas/io/pytables.py in write_index(self, key, index)
1633 setattr(self.attrs, '%s_variety' % key, 'regular')
1634 converted = _convert_index(index).set_name('index')
-> 1635 self.write_array(key, converted.values)
1636 node = getattr(self.group, key)
1637 node._v_attrs.kind = converted.kind
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/pandas/io/pytables.py in write_array(self, key, value)
1805 self.write_array_empty(key, value)
1806 else:
-> 1807 self._handle.createArray(self.group, key, value)
1808
1809 getattr(self.group, key)._v_attrs.transposed = transposed
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/tables/_past.py in oldfunc(*args, **kwargs)
33 def oldfunc(*args, **kwargs):
34 warn(warnmsg, PendingDeprecationWarning, stacklevel=2)
---> 35 return obj(*args, **kwargs)
36 oldfunc.__doc__ = (
37 obj.__doc__ or '') + "\n\n.. warning::\n\n " + warnmsg + "\n"
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/tables/file.py in create_array(self, where, name, obj, title, byteorder, createparents, atom, shape)
890 parentnode = self._get_or_create_path(where, createparents)
891 return Array(parentnode, name,
--> 892 obj=obj, title=title, byteorder=byteorder)
893
894 createArray = previous_api(create_array)
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/tables/array.py in __init__(self, parentnode, name, obj, title, byteorder, _log, _atom)
185 # Ordinary arrays have no filters: leaf is created with default ones.
186 super(Array, self).__init__(parentnode, name, new, Filters(),
--> 187 byteorder, _log)
188
189 def _g_create(self):
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/tables/leaf.py in __init__(self, parentnode, name, new, filters, byteorder, _log)
260 # is a lazy property that automatically handles their loading.
261
--> 262 super(Leaf, self).__init__(parentnode, name, _log)
263
264 def __len__(self):
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/tables/node.py in __init__(self, parentnode, name, _log)
264 # Create or open the node and get its object ID.
265 if new:
--> 266 self._v_objectid = self._g_create()
267 else:
268 self._v_objectid = self._g_open()
/home/hadim/local/virtualenvs/st3/lib/python3.3/site-packages/tables/array.py in _g_create(self)
202 # Raise an error in case of unsupported object
203 if nparr.dtype.kind in ['V', 'U', 'O']: # in void, unicode, object
--> 204 raise TypeError("Array objects cannot currently deal with void, "
205 "unicode or object arrays")
206
TypeError: Array objects cannot currently deal with void, unicode or object arrays
```
PS: I also tried to play with .decode .encode, python codecs module without success
PS2: I know storing this kind of data in DataFrame and h5 file may not be the best way, but that's another question (I prefer to have all my data in one single file if you ever ask)
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} | 1 | 2013-07-16T13:15:20Z | 2014-06-28T10:41:40Z | 2013-07-16T14:19:22Z | MEMBER | null | closes #4214, #4252, #4253
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https://api.github.com/repos/pandas-dev/pandas/issues/4258 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4258/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4258/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4258/events | https://github.com/pandas-dev/pandas/pull/4258 | 16,809,406 | MDExOlB1bGxSZXF1ZXN0Njk1MzU5OQ== | 4,258 | ENH: Dataframe isin2 | {
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"description": "RC1 ANN went out on 2013-12-6: https://groups.google.com/forum/#!topic/pydata/OHutLByJvK0\r\nTwo weeks, clear all reported bugs then call it on 2013-12-20. \r\n(@y-p)\r\n\r\nsince we've had some bugs reported at a high enough rate, extending rc by one\r\nweek until 2013-12-27. \r\n(@y-p)\r\n\r\nBumping to clear debian sparc\r\n2013-12-30. \r\n(@y-p)",
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} | 12 | 2013-07-16T13:32:27Z | 2014-06-20T16:16:29Z | 2013-07-24T21:45:38Z | CONTRIBUTOR | null | fixes #4211, an alternative (on top of) #4237
DataFrame isin method:
```
In [11]: df = pd.DataFrame([['a', 'a', 'c'], ['b', 'e', 'a'], ['c', 'a', 'f']], columns=['A', 'A', 'B'])
In [12]: df
Out[12]:
A A B
0 a a c
1 b e a
2 c a f
In [13]: df.isin(['a'])
Out[13]:
A A B
0 True True False
1 False False True
2 False True False
In [14]: df.isin({'A': ['a']})
Out[14]:
A A B
0 True True False
1 False False False
2 False True False
In [15]: df.isin({0: ['a']}, iloc=True)
Out[15]:
A A B
0 True False False
1 False False False
2 False False False
```
cc @TomAugspurger
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https://api.github.com/repos/pandas-dev/pandas/issues/4259 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4259/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4259/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4259/events | https://github.com/pandas-dev/pandas/pull/4259 | 16,812,544 | MDExOlB1bGxSZXF1ZXN0Njk1NTMyNA== | 4,259 | TST/BLD: add proper skips for bad bs4 version | {
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} | 4 | 2013-07-16T14:31:36Z | 2014-07-16T08:19:30Z | 2013-07-16T21:29:53Z | MEMBER | null | Make sure things are being properly skipped because of a bad bs4 version.
Also adds a 4.2.0 known bad version of bs4 to 26 travis build so that we can verify that tests are being skipped when the version is bad.
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https://api.github.com/repos/pandas-dev/pandas/issues/4260 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4260/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4260/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4260/events | https://github.com/pandas-dev/pandas/issues/4260 | 16,813,496 | MDU6SXNzdWUxNjgxMzQ5Ng== | 4,260 | HDF5 files not compatible between python 2 and 3 ? | {
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} | [] | closed | false | null | [] | null | 10 | 2013-07-16T14:47:59Z | 2013-07-16T16:27:25Z | 2013-07-16T15:13:33Z | NONE | null | I have a problem loading a h5 file from python 3 to python 2 and vice versa. I can't post the code which generate h5 file because is part of a big project. I'll try to upload h5 file directly later.
Here is the error when I load **FROM python 3.3** an h5 file created **BY python 2.7**:
```
Traceback (most recent call last):
File "/home/hadim/local/virtualenvs/st3/src/master/build/lib.linux-x86_64-3.3/pandas/core/index.py", line 1539, in _get_level_number
level = self.names.index(level)
ValueError: 'side' is not in list
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "main.py", line 49, in <module>
meta = SimuIO().read(results_file)
File "../kt_simul/io/simuio.py", line 210, in read
KD.spbL.traj = spbs.xs('A', level='side').values.T[0]
File "/home/hadim/local/virtualenvs/st3/src/master/build/lib.linux-x86_64-3.3/pandas/core/frame.py", line 2335, in xs
loc, new_ax = labels.get_loc_level(key, level=level)
File "/home/hadim/local/virtualenvs/st3/src/master/build/lib.linux-x86_64-3.3/pandas/core/index.py", line 2322, in get_loc_level
level = self._get_level_number(level)
File "/home/hadim/local/virtualenvs/st3/src/master/build/lib.linux-x86_64-3.3/pandas/core/index.py", line 1542, in _get_level_number
raise Exception('Level %s not found' % str(level))
Exception: Level side not found
Closing remaining open files: simu.h5... done
```
Here is the error when I load **FROM python 2.7** an h5 file created **BY python 3.3**:
```
Traceback (most recent call last):
File "main.py", line 49, in <module>
meta = SimuIO().read(results_file)
File "/home/hadim/.phd/dev/kt_simul/kt_simul/io/simuio.py", line 197, in read
param_root = build_tree(store['params'])
File "/home/hadim/local/virtualenvs/st/src/master/pandas/io/pytables.py", line 289, in __getitem__
return self.get(key)
File "/home/hadim/local/virtualenvs/st/src/master/pandas/io/pytables.py", line 422, in get
return self._read_group(group)
File "/home/hadim/local/virtualenvs/st/src/master/pandas/io/pytables.py", line 930, in _read_group
return s.read(**kwargs)
File "/home/hadim/local/virtualenvs/st/src/master/pandas/io/pytables.py", line 2194, in read
values = self.read_array('block%d_values' % i)
File "/home/hadim/local/virtualenvs/st/src/master/pandas/io/pytables.py", line 1776, in read_array
data = node[:]
File "/home/hadim/local/virtualenvs/st/local/lib/python2.7/site-packages/tables/vlarray.py", line 661, in __getitem__
return self.read(start, stop, step)
File "/home/hadim/local/virtualenvs/st/local/lib/python2.7/site-packages/tables/vlarray.py", line 801, in read
outlistarr = [atom.fromarray(arr) for arr in listarr]
File "/home/hadim/local/virtualenvs/st/local/lib/python2.7/site-packages/tables/atom.py", line 1151, in fromarray
return cPickle.loads(array.tostring())
ValueError: unsupported pickle protocol: 3
Closing remaining open files: simu.h5... done
```
---
Version command run:
``` python
import sys
print(sys.version)
import numpy
print(numpy.__version__)
import tables
print(tables.__version__)
import pandas
print (pandas.__version__)
```
Python 3 shell:
```
3.3.1 (default, Apr 17 2013, 22:30:32)
[GCC 4.7.3]
1.7.1
3.0.0
0.12.0.dev-404dfab
```
Python 2 shell:
```
2.7.4 (default, Apr 9 2013, 18:05:19)
[GCC 4.7.3]
1.7.1
3.0.0
0.12.0.dev-4c2d050
```
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https://api.github.com/repos/pandas-dev/pandas/issues/4261 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4261/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4261/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4261/events | https://github.com/pandas-dev/pandas/issues/4261 | 16,814,051 | MDU6SXNzdWUxNjgxNDA1MQ== | 4,261 | Print skipped tests at the end of travis runs | {
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https://api.github.com/repos/pandas-dev/pandas/issues/4263 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4263/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4263/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4263/events | https://github.com/pandas-dev/pandas/issues/4263 | 16,822,607 | MDU6SXNzdWUxNjgyMjYwNw== | 4,263 | python3.2 offsets.py: TypeError: Cannot cast ufunc subtract input from dtype('<M8[D]') to dtype('<M8[us]') with casting rule 'same_kind' | {
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} | 23 | 2013-07-16T17:32:44Z | 2013-07-17T14:01:17Z | 2013-07-17T14:01:17Z | CONTRIBUTOR | null | in pandas.tseries.tests.test_daterange.TestCustomDateRange tests many fail at v0.12.0rc1-90-g4c2d050
```
======================================================================
ERROR: test_repr (pandas.tseries.tests.test_daterange.TestCustomDateRange)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.12.0~rc1+git90-g4c2d050/debian/tmp/usr/lib/python3/dist-packages/pandas/tseries/tests/test_daterange.py", line 383, in setUp
self.rng = cdate_range(START, END)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.12.0~rc1+git90-g4c2d050/debian/tmp/usr/lib/python3/dist-packages/pandas/tseries/index.py", line 1791, in cdate_range
tz=tz, normalize=normalize, name=name, **kwargs)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.12.0~rc1+git90-g4c2d050/debian/tmp/usr/lib/python3/dist-packages/pandas/tseries/index.py", line 180, in __new__
tz=tz, normalize=normalize)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.12.0~rc1+git90-g4c2d050/debian/tmp/usr/lib/python3/dist-packages/pandas/tseries/index.py", line 373, in _generate
index = _generate_regular_range(start, end, periods, offset)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.12.0~rc1+git90-g4c2d050/debian/tmp/usr/lib/python3/dist-packages/pandas/tseries/index.py", line 1663, in _generate_regular_range
dates = list(xdr)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.12.0~rc1+git90-g4c2d050/debian/tmp/usr/lib/python3/dist-packages/pandas/tseries/offsets.py", line 1363, in generate_range
next_date = offset.apply(cur)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.12.0~rc1+git90-g4c2d050/debian/tmp/usr/lib/python3/dist-packages/pandas/tseries/offsets.py", line 453, in apply
time = dt64 - day64
TypeError: Cannot cast ufunc subtract input from dtype('<M8[D]') to dtype('<M8[us]') with casting rule 'same_kind'
```
system info
```
INSTALLED VERSIONS
------------------
Python: 3.2.4.final.0
OS: Linux 3.2.0-4-amd64 #1 SMP Debian 3.2.41-2 x86_64
LC_ALL: None
LANG: en_US
Cython: 0.19
Numpy: 1.8.0.dev-Unknown
Scipy: 0.10.1
statsmodels: Not installed
patsy: Not installed
scikits.timeseries: Not installed
dateutil: 2.0
pytz: 2012c
bottleneck: Not installed
PyTables: Not Installed
numexpr: 2.1
matplotlib: Not installed
openpyxl: Not installed
xlrd: Not installed
xlwt: Not installed
sqlalchemy: Not installed
lxml: 3.2.0
bs4: 4.2.1
html5lib: Not installed
```
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} | 14 | 2013-07-16T19:18:29Z | 2014-05-16T20:26:42Z | 2014-05-16T20:26:42Z | NONE | null | The docstring for `DataFRame.boxplot` claims that the method returns matplotlib axes:
```
Returns
-------
ax : matplotlib.axes.AxesSubplot
```
In fact, it instead returns a dict:
```
In [71]: data.boxplot()
Out[71]:
{'boxes': [<matplotlib.lines.Line2D at 0x10e376110>,
<matplotlib.lines.Line2D at 0x10e491350>,
<matplotlib.lines.Line2D at 0x10e477590>,
<matplotlib.lines.Line2D at 0x10eb0e7d0>,
<matplotlib.lines.Line2D at 0x10eb3da10>,
<matplotlib.lines.Line2D at 0x10eb7ec50>,
<matplotlib.lines.Line2D at 0x10eb9be90>],
'caps': [<matplotlib.lines.Line2D at 0x10e3ab5d0>,
<matplotlib.lines.Line2D at 0x10ebbc4d0>,
<matplotlib.lines.Line2D at 0x10e357690>,
...
<matplotlib.lines.Line2D at 0x10eb020d0>,
<matplotlib.lines.Line2D at 0x10eb02710>,
<matplotlib.lines.Line2D at 0x10eb0b310>,
<matplotlib.lines.Line2D at 0x10eb0b950>,
<matplotlib.lines.Line2D at 0x10eb9a550>,
<matplotlib.lines.Line2D at 0x10eb9ab90>]}
```
Aside from being inconsistent with the documentation, this is inconvenient because I am no longer able to manipulate the axes of the plot directly.
Using Pandas 0.12.0.dev-af85719
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} | 0 | 2013-07-16T21:12:16Z | 2016-10-12T23:04:01Z | 2013-07-16T22:02:44Z | CONTRIBUTOR | null | ```
======================================================================
ERROR: pandas.io.tests.test_html.test_bs4_version_fails
----------------------------------------------------------------------
Traceback (most recent call last):
File "/usr/lib/python3/dist-packages/nose/case.py", line 198, in runTest
self.test(*self.arg)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/io/tests/test_html.py", line 83, in test_bs4_version_fails
flavor='bs4')
File "/usr/lib/python3.2/unittest/case.py", line 557, in assertRaises
callableObj(*args, **kwargs)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/io/html.py", line 906, in read_html
attrs)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/io/html.py", line 765, in _parse
parser = _parser_dispatch(flav)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/io/html.py", line 719, in _parser_dispatch
raise ImportError("html5lib not found please install it")
ImportError: html5lib not found please install it
```
on 4c2d050
there is no python3-html5lib on any debian system yet
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} | 6 | 2013-07-16T21:13:37Z | 2013-07-17T14:02:32Z | 2013-07-17T14:02:32Z | CONTRIBUTOR | null | on sparc 4c2d050
```
======================================================================
ERROR: test_value_counts_nunique (pandas.tests.test_series.TestSeries)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/tests/test_series.py", line 2633, in test_value_counts_nunique
result = s.value_counts()
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/core/series.py", line 1422, in value_counts
normalize=normalize)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/core/algorithms.py", line 186, in value_counts
keys, counts = htable.value_count_object(values, mask)
File "hashtable.pyx", line 935, in pandas.hashtable.value_count_object (pandas/hashtable.c:14937)
TypeError: unhashable type: 'NaTType'
```
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} | 0 | 2013-07-16T21:49:06Z | 2013-07-16T22:17:54Z | 2013-07-16T22:17:54Z | MEMBER | null | occasional timeout is starting to get annoying
https://travis-ci.org/pydata/pandas/builds/9156655
i removed it for a previous pr that i shoudn't have
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} | 0 | 2013-07-16T21:59:30Z | 2014-06-16T09:24:22Z | 2013-07-16T22:17:54Z | MEMBER | null | closes #4268
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} | 20 | 2013-07-16T22:33:59Z | 2014-07-02T17:36:34Z | 2013-07-22T18:53:02Z | NONE | null | This is a relatively trival 'fix', which makes it easier to sub-class Pandas Series' and Dataframes. Basically, it makes more consistent use of `self._constructor` when constructing outputs from operations on Series' and DataFrames. For example, with these changes, this is now possible:
``` python
In [1]: from pandas import Series
In [2]: class MySeries(Series):
def say_hello(self):
print "hello!"
In [3]: s = MySeries([1,2,3,4,5])
In [4]: s.say_hello()
hello!
In [5]: s.__class__
Out[5]: __main__.MySeries
In [6]: s2 = s[1:3]
In [7]: s2.__class__
Out[7]: __main__.MySeries
In [8]: s2.say_hello()
hello!
```
This addresses (to some extent) issues #1713 and #60 and the issues mentioned therein. After these changes, all nosetests continue to pass (except those that skip).
Note: This is my first 'pull request', so be gentle!
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} | 7 | 2013-07-17T11:43:33Z | 2013-09-29T21:22:26Z | 2013-09-29T21:22:26Z | CONTRIBUTOR | null | ```
In [1]: df = DataFrame(columns=list('xyz'))
In [2]: df
Out[2]:
Empty DataFrame
Columns: [x, y, z]
Index: []
In [3]: df.dtypes
Out[3]:
x NaN
y NaN
z NaN
dtype: float64
In [5]: df['x'].dtype
Out[5]: dtype('O')
```
expected
```
In [11]: Series(dict([ (s,np.dtype('O')) for s in list('xyz')]))
Out[11]:
x object
y object
z object
dtype: object
```
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} | 3 | 2013-07-17T11:54:12Z | 2013-08-23T14:33:19Z | 2013-08-23T14:33:19Z | CONTRIBUTOR | null | writing to an HDFStore with an empty-frame with invalid dtypes raises, maybe should just proceed (or is it the dtypes call that is actually wrong here: see #4272)
came up in this question: http://stackoverflow.com/questions/17691912/problems-with-merging-on-disk-tables-with-millions-of-rows/17698740#17698740
```
In [26]: df = DataFrame(randn(10,2),columns=list('AB'))
In [28]: df['C'] = 'foo'
In [33]: df.to_hdf('test.h5','df',mode='w',table=True)
In [35]: pd.read_hdf('test.h5','df')
Out[35]:
A B C
0 -1.123712 -1.146515 foo
1 0.921705 1.800419 foo
2 -0.769236 -0.553307 foo
3 -0.747601 -1.783439 foo
4 -1.110340 1.601026 foo
5 0.743869 -2.135140 foo
6 1.033699 2.028479 foo
7 -0.755478 -1.060223 foo
8 0.079326 -2.671624 foo
9 -2.262756 0.406850 foo
In [36]: pd.read_hdf('test.h5','df').dtypes
Out[36]:
A float64
B float64
C object
dtype: object
In [37]: df[df.C=='bar']
Out[37]:
Empty DataFrame
Columns: [A, B, C]
Index: []
In [38]: df[df.C=='bar'].dtypes
Out[38]:
A NaN
B NaN
C NaN
dtype: float64
In [39]: df[df.C=='bar'].to_hdf('test.h5','df',append=True)
TypeError: Cannot serialize the column [C] because
its data contents are [empty] object dtype
```
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} | 5 | 2013-07-17T12:18:46Z | 2013-08-21T21:13:08Z | 2013-07-20T01:40:54Z | CONTRIBUTOR | null | Testing d070a1f
```
======================================================================
FAIL: test_frame_from_json_to_json (pandas.io.tests.test_json.test_pandas.TestPandasContainer)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/io/tests/test_json/test_pandas.py", line 149, in test_frame_from_json_to_json
raise_ok=ValueError)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/io/tests/test_json/test_pandas.py", line 111, in _check_all_orients
_check_orient(df, "index", dtype=dtype, convert_axes=False)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/io/tests/test_json/test_pandas.py", line 96, in _check_orient
assert_frame_equal(df, unser, check_less_precise=False, check_dtype=check_dtype)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/util/testing.py", line 239, in assert_frame_equal
check_less_precise=check_less_precise)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/util/testing.py", line 198, in assert_series_equal
assert_almost_equal(left.values, right.values, check_less_precise)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/util/testing.py", line 142, in assert_almost_equal
assert_almost_equal(a[i], b[i], check_less_precise)
File "/home/yoh/deb/gits/pkg-exppsy/pandas/debian/tmp/usr/lib/python3/dist-packages/pandas/util/testing.py", line 130, in assert_almost_equal
assert a == b, "%s != %s" % (a, b)
AssertionError: 0.0 != \U30000000\U2e000000\U30000000
```
all previously reported sparc issues seems to be silent now
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} | 1 | 2013-07-17T12:22:30Z | 2016-10-12T23:04:01Z | 2013-07-17T14:37:44Z | CONTRIBUTOR | null | Now (d070a1f) that #4265 fixed, all the test_html tests fail similarly
```
======================================================================
ERROR: test_bad_url_protocol (pandas.io.tests.test_html.TestReadHtmlBase)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.12.0~rc1+git101-gd070a1f/debian/tmp/usr/lib/python3/dist-packages/pandas/io/tests/test_html.py", line 290, in test_bad_url_protocol
'.*Water.*')
File "/usr/lib/python3.2/unittest/case.py", line 557, in assertRaises
callableObj(*args, **kwargs)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.12.0~rc1+git101-gd070a1f/debian/tmp/usr/lib/python3/dist-packages/pandas/io/tests/test_html.py", line 91, in run_read_html
return read_html(*args, **kwargs)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.12.0~rc1+git101-gd070a1f/debian/tmp/usr/lib/python3/dist-packages/pandas/io/html.py", line 906, in read_html
attrs)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.12.0~rc1+git101-gd070a1f/debian/tmp/usr/lib/python3/dist-packages/pandas/io/html.py", line 765, in _parse
parser = _parser_dispatch(flav)
File "/home/yoh/deb/gits/pkg-exppsy/build-area/pandas-0.12.0~rc1+git101-gd070a1f/debian/tmp/usr/lib/python3/dist-packages/pandas/io/html.py", line 719, in _parser_dispatch
raise ImportError("html5lib not found please install it")
ImportError: html5lib not found please install it
```
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} | 0 | 2013-07-17T13:34:28Z | 2014-06-16T19:19:22Z | 2013-07-17T14:37:44Z | MEMBER | null | closes #4275
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} | 5 | 2013-07-17T19:06:40Z | 2021-10-29T01:55:27Z | null | CONTRIBUTOR | null | - `numeric_only=True` flag to `min,max,idxmax,idxmin` to select out numeric only
- fix `idxmax` on object dtypes (related to #4147)
related is #6287
Just happened to come across this. Related to #2982
```
df = pd.DataFrame([["zimm", 2.5],["biff", 1.],["bid", 12.]])
```
This is fine (I was surprised it worked for objects)
```
df.max()
```
This falls down
```
df.idxmax()
```
I'd be fine if there's a strong performance reason not to support this, though it would be nice to not return an error at least. Maybe a stop-gap solution is to only return a solution for numeric types similar to the quantiles method.
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} | 11 | 2013-07-17T19:33:22Z | 2013-07-18T03:15:42Z | 2013-07-18T03:00:27Z | NONE | null | <pre>
from pandas import *
df = read_csv(open('mydata.csv.gz', 'r'), compression='gzip', index_col=False)
df = df[(df.land != 1)]
print df
# <class 'pandas.core.frame.DataFrame'>
# Int64Index: 977579 entries, 0 to 1100398
# Data columns (total 89 columns):
# <snip>
# sample 100,000 rows, only use some of the columns
rows = np.random.choice(df.index.values, 100000)
keep_cols = ['sq_ft', 'zip', 'year', 'bathrooms', 'bedrooms', 'floors']
sampled_df = df.ix[rows, keep_cols]
sampled_df.loc[sampled_df.year.notnull()].year # works fine
sampled_df.loc[sampled_df.year.notnull(),['year']] # MemoryError
---------------------------------------------------------------------------
MemoryError Traceback (most recent call last)
<ipython-input-114-f9c1e2bc7b58> in <module>()
1 #sampled_df.loc[sampled_df['year'].notnull(),['year']]
2 sampled_df.loc[sampled_df.year.notnull()].year
----> 3 sampled_df.loc[sampled_df.year.notnull(),['year']]
/home/jprior/Scratch/VENV1/lib/python2.7/site-packages/pandas/core/indexing.pyc in __getitem__(self, key)
695 def __getitem__(self, key):
696 if type(key) is tuple:
--> 697 return self._getitem_tuple(key)
698 else:
699 return self._getitem_axis(key, axis=0)
/home/jprior/Scratch/VENV1/lib/python2.7/site-packages/pandas/core/indexing.pyc in _getitem_tuple(self, tup)
260 # ugly hack for GH #836
261 if self._multi_take_opportunity(tup):
--> 262 return self._multi_take(tup)
263
264 # no shortcut needed
/home/jprior/Scratch/VENV1/lib/python2.7/site-packages/pandas/core/indexing.pyc in _multi_take(self, tup)
300 index = self._convert_for_reindex(tup[0], axis=0)
301 columns = self._convert_for_reindex(tup[1], axis=1)
--> 302 return self.obj.reindex(index=index, columns=columns)
303 elif isinstance(self.obj, Panel4D):
304 conv = [self._convert_for_reindex(x, axis=i)
/home/jprior/Scratch/VENV1/lib/python2.7/site-packages/pandas/core/frame.pyc in reindex(self, index, columns, method, level, fill_value, limit, copy, takeable)
2623 if index is not None:
2624 frame = frame._reindex_index(index, method, copy, level,
-> 2625 fill_value, limit, takeable)
2626
2627 return frame
/home/jprior/Scratch/VENV1/lib/python2.7/site-packages/pandas/core/frame.pyc in _reindex_index(self, new_index, method, copy, level, fill_value, limit, takeable)
2703 new_index, indexer = self.index.reindex(new_index, method, level,
2704 limit=limit, copy_if_needed=True,
-> 2705 takeable=takeable)
2706 return self._reindex_with_indexers(new_index, indexer, None, None,
2707 copy, fill_value)
/home/jprior/Scratch/VENV1/lib/python2.7/site-packages/pandas/core/index.pyc in reindex(self, target, method, level, limit, copy_if_needed, takeable)
930 raise ValueError("cannot reindex a non-unique index "
931 "with a method or limit")
--> 932 indexer, _ = self.get_indexer_non_unique(target)
933
934 return target, indexer
/home/jprior/Scratch/VENV1/lib/python2.7/site-packages/pandas/core/index.pyc in get_indexer_non_unique(self, target, **kwargs)
843 tgt_values = target.values
844
--> 845 indexer, missing = self._engine.get_indexer_non_unique(tgt_values)
846 return Index(indexer), missing
847
/home/jprior/Scratch/VENV1/lib/python2.7/site-packages/pandas/index.so in pandas.index.IndexEngine.get_indexer_non_unique (pandas/index.c:5049)()
MemoryError:
</pre>
Sorry I haven't figured out how to reproduce the error with a toy example.
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} | 5 | 2013-07-18T00:59:57Z | 2014-06-13T10:27:53Z | 2013-07-18T03:15:21Z | MEMBER | null | get_data_famafrench was not returning any data because of an incorrect slice
and read + splitlines != readlines for zipfiles
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} | 0 | 2013-07-18T02:41:10Z | 2014-07-09T17:56:10Z | 2013-07-18T03:00:27Z | CONTRIBUTOR | null | closes #4280
Had a weird memory allocation scheme (that's why is a _scheme_!) when determining
a non-unique indexer. Fixed to use a dynamic schema
```
In [1]: columns = list('ABCDEFG')
def gen_test(l,l2):
return pd.concat([ DataFrame(randn(l,len(columns)),index=range(l),columns=columns),
DataFrame(np.ones((l2,len(columns))),index=[0]*l2,columns=columns) ])
In [3]: df = gen_test(900000,100000)
In [5]: mask = np.arange(100000)
In [6]: df
Out[6]:
<class 'pandas.core.frame.DataFrame'>
Int64Index: 1000000 entries, 0 to 0
Data columns (total 7 columns):
A 1000000 non-null values
B 1000000 non-null values
C 1000000 non-null values
D 1000000 non-null values
E 1000000 non-null values
F 1000000 non-null values
G 1000000 non-null values
dtypes: float64(7)
In [7]: df.loc[mask]
Out[7]:
<class 'pandas.core.frame.DataFrame'>
Int64Index: 200000 entries, 0 to 99999
Data columns (total 7 columns):
A 200000 non-null values
B 200000 non-null values
C 200000 non-null values
D 200000 non-null values
E 200000 non-null values
F 200000 non-null values
G 200000 non-null values
dtypes: float64(7)
```
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} | 0 | 2013-07-18T10:27:55Z | 2014-06-18T21:16:11Z | 2013-07-18T11:25:04Z | CONTRIBUTOR | null | {
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Objections?
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} | 1 | 2013-07-18T13:36:31Z | 2014-07-16T08:19:50Z | 2013-07-19T01:50:27Z | CONTRIBUTOR | null | Smallest PR ever.
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} | 5 | 2013-07-18T13:44:44Z | 2013-09-20T23:03:43Z | 2013-09-20T23:03:37Z | CONTRIBUTOR | null | Is the current behavior a regression/bug or are the docs incorrect?
This [1] suggests that the following should raise an error. It doesn't for me on f1d35ee nor is its behavior obvious.
```
randn = np.random.randn
df = pd.DataFrame(randn(5,5))
df.ix[-2:]
```
[1] http://pandas.pydata.org/pandas-docs/dev/gotchas.html#integer-indexing
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} | 2 | 2013-07-18T22:10:32Z | 2013-09-22T20:35:39Z | 2013-09-22T20:35:39Z | MEMBER | null | i got this email and didn't know if this was a perf regression we should care about
```
Wes,
I'm stuck on something and I was hoping for your help.
I wrote a function a year back that iterates element by element through a
DataFrame of about 1200 columns by 2000 rows. It runs some basic operations,
but nothing crazy. It used to take something like 5 seconds to complete, and
now maybe 100x that. The only thing I can think of that's changed is my pandas
version (and it's dependancies such as numpy).
You can see my stackoverflow question about the same here:
http://stackoverflow.com/questions/17538902/is-there-a-way-to-speed-up-this-pandas-function
At the bottom of my question is a simple example function I just created (to
try and isolate the problem) that seems to take very long to complete (73
seconds) on my computer. Does this sound right to you? Wondering if you have
any thoughts, as I'm not sure what to do now. I know vectorized functions are
preferred, I have certain cases that require elementwise functions and would
like to figure out a way to get decent speed.
Thanks for any help!
```
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} | 7 | 2013-07-18T22:26:28Z | 2013-09-21T01:16:29Z | 2013-09-21T01:16:29Z | CONTRIBUTOR | null | Numpy 1.8 API change in mean?
```
/home/data/flash_supression/yarik/scripts/utils.pyc in paired_t_anal(d, value, testcol, rows, cols, print_pt, plots, aggfunc)
162 pvalues = np.array(pvalues, ndmin=1)
163
--> 164 pt_paired_t = DataFrame(np.array([np.mean(v0, axis=0),
165 np.mean(v1, axis=0),
166 np.mean(v10, axis=0),
/usr/lib/pymodules/python2.7/numpy/core/fromnumeric.pyc in mean(a, axis, dtype, out, keepdims)
2481 try:
2482 mean = a.mean
-> 2483 return mean(axis=axis, dtype=dtype, out=out)
2484 except AttributeError:
2485 pass
TypeError: mean() got an unexpected keyword argument 'dtype'
```
complete "line" calling this is
```
pt_paired_t = DataFrame(np.array([np.mean(v0, axis=0),
np.mean(v1, axis=0),
np.mean(v10, axis=0),
tvalues, pvalues]),
index=Index(['mean(%s)' % lvalues[0],
'mean(%s)' % lvalues[1],
'mean effect',
't-score', 'p-value'],
name=contrast_s),
columns = columns)
```
it used to work before ... did not check for sure yet though if it is pandas or recent numpy upgrade (if I did any)
more information:
```
ipdb> print a.mean
<bound method DataFrame.mean of cond full profile
subject
01jul10sc.dat 1.572131 1.569658
01oct10cs.dat 1.491370 1.678300
...
```
and if to provide ndarray compatibility here then interface should match numpy's where dtype is a valid argument to mean
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https://buildd.debian.org/status/fetch.php?pkg=pandas&arch=powerpc&ver=0.12.0~rc1%2Bgit112-gb79996c-1&stamp=1374189622&file=log
```
======================================================================
FAIL: test_nat_parse (pandas.io.tests.test_parsers.TestCParserHighMemory)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_parsers.py", line 607, in test_nat_parse
tm.assert_frame_equal(result,df)
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/util/testing.py", line 238, in assert_frame_equal
check_less_precise=check_less_precise)
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/util/testing.py", line 197, in assert_series_equal
assert_almost_equal(left.values, right.values, check_less_precise)
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/util/testing.py", line 141, in assert_almost_equal
assert_almost_equal(a[i], b[i], check_less_precise)
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/util/testing.py", line 172, in assert_almost_equal
assert a == b, "%s != %s" % (a, b)
AssertionError: 2262-04-10T00:12:45.292707840+0000 != 2262-04-10T00:12:45.292707840+0000
======================================================================
FAIL: test_nat_parse (pandas.io.tests.test_parsers.TestCParserLowMemory)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_parsers.py", line 607, in test_nat_parse
tm.assert_frame_equal(result,df)
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/util/testing.py", line 238, in assert_frame_equal
check_less_precise=check_less_precise)
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/util/testing.py", line 197, in assert_series_equal
assert_almost_equal(left.values, right.values, check_less_precise)
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/util/testing.py", line 141, in assert_almost_equal
assert_almost_equal(a[i], b[i], check_less_precise)
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/util/testing.py", line 172, in assert_almost_equal
assert a == b, "%s != %s" % (a, b)
AssertionError: 2262-04-10T00:12:45.292707840+0000 != 2262-04-10T00:12:45.292707840+0000
======================================================================
FAIL: test_nat_parse (pandas.io.tests.test_parsers.TestPythonParser)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/io/tests/test_parsers.py", line 607, in test_nat_parse
tm.assert_frame_equal(result,df)
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/util/testing.py", line 238, in assert_frame_equal
check_less_precise=check_less_precise)
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/util/testing.py", line 197, in assert_series_equal
assert_almost_equal(left.values, right.values, check_less_precise)
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/util/testing.py", line 141, in assert_almost_equal
assert_almost_equal(a[i], b[i], check_less_precise)
File "/«BUILDDIR»/pandas-0.12.0~rc1+git112-gb79996c/debian/tmp/usr/lib/python2.7/dist-packages/pandas/util/testing.py", line 172, in assert_almost_equal
assert a == b, "%s != %s" % (a, b)
AssertionError: 2262-04-10T00:12:45.292707840+0000 != 2262-04-10T00:12:45.292707840+0000
```
good news -- those seems to be the only failures on powerpc (for python 2.7 at least, python 3 did not have chance to get any testing yet due to 2.7 failing)
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} | 17 | 2013-07-19T16:10:17Z | 2018-05-18T07:33:25Z | 2018-05-18T07:33:25Z | NONE | null | When I use pd.Series.tolist as a reducer with a single column groupby, it works.
When I do the same with multiindex, it does not.
It seems the "fast" cython groupby function, which has no quarrel with reducing into lists, throws an exception if the index is "complex", which seem to mean multiindex. When that exception is caught, the groupby function falls back to the "pure_python" groupby, which throws a new exception if the reducing function returns a list.
Is this a bug or is there some logic to this which is not apparent to me?
Reproduce:
```
import pandas as pd
s1 = pd.Series(randn(5), index=['a', 'b', 'c', 'd', 'e'])
df = pd.DataFrame([s1], columns=['a', 'b', 'c', 'd', 'e'])
for i in range(0,10):
s1 = pd.Series(randn(5), index=['a', 'b', 'c', 'd', 'e'])
df2 = pd.DataFrame([s1], columns=['a', 'b', 'c', 'd', 'e'])
df = pd.concat([df, df2])
df['gk'] = 'foo'
df['gk2'] = 'bar'
# This works.
df.groupby(['gk']).agg(pd.Series.tolist)
# This does not.
df.groupby(['gk', 'gk2']).agg(pd.Series.tolist)
```
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} | 5 | 2013-07-19T16:56:42Z | 2013-10-02T19:10:22Z | 2013-10-02T19:10:22Z | CONTRIBUTOR | null | I have a series with a multiindex (datetime, int).
When I try to access a slice corresponding to a date using a Timestamp I have an exception printed to screen if the size of the series is >= 1e6.
No problem if I access the same slice with a string.
No problem with an equivalent dataframe.
Tested on 0.10.1 and 0.11, I'm sorry but I don't have access to 0.12rc1.
``` python
In [1]: import pandas as pd
In [2]: pd.__version__
Out[2]: '0.11.0'
In [3]: np.__version__
Out[3]: '1.7.1'
In [4]: df = pd.DataFrame(randn(1000, 1000), index=pd.date_range('2000-1-1', periods=1000))
In [5]: s = df.stack() # s has 1e6 lines
In [6]: s.head()
Out[6]:
2000-01-01 0 -0.555228
1 -0.152952
2 0.401490
3 -1.057106
4 -0.987895
dtype: float64
In [7]: s['2000-1-4'].head()
Out[7]:
0 -1.009647
1 0.094427
2 0.105180
3 -2.166810
4 -0.767165
dtype: float64
In [8]: s[pd.Timestamp('2000-1-4')].head()
Exception TypeError: TypeError('Cannot compare Timestamp with (<Timestamp: 2002-09-26 00:00:00>, 999)',) in 'pandas.index._bin_search' ignored
Out[8]:
0 -1.009647
1 0.094427
2 0.105180
3 -2.166810
4 -0.767165
dtype: float64
In [9]: s2 = s[:-1].copy() # s2 has 1e6 - 1 lines
In [10]: s2['2000-1-4'].head()
Out[10]:
0 -1.009647
1 0.094427
2 0.105180
3 -2.166810
4 -0.767165
dtype: float64
In [11]: s2[pd.Timestamp('2000-1-4')].head()
Out[11]:
0 -1.009647
1 0.094427
2 0.105180
3 -2.166810
4 -0.767165
dtype: float64
In [12]: df2 = pd.DataFrame(s)
In [13]: df2.ix['2000-1-4'].head()
Out[13]:
0
0 -1.009647
1 0.094427
2 0.105180
3 -2.166810
4 -0.767165
In [14]: df2.ix[pd.Timestamp('2000-1-4')].head()
Out[14]:
0
0 -1.009647
1 0.094427
2 0.105180
3 -2.166810
4 -0.767165
```
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```
In [1]: DataFrame([[1e-16,'foo',1e-8]],columns=list('ABC')).to_json()
ValueError: ujson currently cannot accurately format float data less
than 1e-15. A work-around is to multiply the data by
a large positive factor and divide on deseriliazation
```
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} | 5 | 2013-07-19T20:02:59Z | 2014-06-15T07:02:25Z | 2013-07-20T00:30:57Z | CONTRIBUTOR | null | please test test_perf.py -- I have rebased against master and had to resolve conflicts
Cheers,
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} | 17 | 2013-07-19T20:23:13Z | 2013-09-13T22:54:42Z | 2013-09-13T22:54:42Z | CONTRIBUTOR | null | ``` python
import pandas
import array
x=array.array('i', range(10))
pdf = pandas.DataFrame.from_items([('a', x)])
# fails with:
# ValueError: If use all scalar values, must pass index
```
Also, since x has a `__len__` may be the error message should not refer to a scalar.
Explicit casting to numpy arrays is a workaround, but it would seem convenient to have it done within the constructor for `DataFrame`:
``` python
import numpy
pdf = pandas.DataFrame.from_items([('a', numpy.asarray(x))])
```
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"description": "RC1 ANN went out on 2013-12-6: https://groups.google.com/forum/#!topic/pydata/OHutLByJvK0\r\nTwo weeks, clear all reported bugs then call it on 2013-12-20. \r\n(@y-p)\r\n\r\nsince we've had some bugs reported at a high enough rate, extending rc by one\r\nweek until 2013-12-27. \r\n(@y-p)\r\n\r\nBumping to clear debian sparc\r\n2013-12-30. \r\n(@y-p)",
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} | 16 | 2013-07-19T22:48:00Z | 2013-08-26T19:14:52Z | 2013-08-26T19:14:52Z | NONE | null | It'd be really cool when plotting kde's to be able to set the bandwidth used for the kde and the indices at which it is evaluated. This is done with the bw_method kwarg for scipy.stats.gaussian_kde for scipy >= 0.11, a couple years old now, for the former; a variable ind is created in the pandas class KdePlot's _make_plot method and passed to gkde.evaluate.
Here's a patch which implements this functionality: https://github.com/khgitting/pandas/compare/master...kde_kwargs
I'm having trouble passing the Travis CI tests here: https://travis-ci.org/khgitting/pandas/jobs/9284591
It appears the tests use an older version of scipy where gaussian_kde does not take bw_method kwarg. I'd love to be able to resolve this, but am not sure what the right course of action is. Any advice?
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} | 8 | 2013-07-19T23:09:52Z | 2014-07-16T08:19:56Z | 2013-07-20T01:45:17Z | CONTRIBUTOR | null | closes #4042
This makes ujson handle very big and very small numbers a bit better, it doesn't help with precision but it should at least be able to handle very small and large exponentials now:
```
In [4]: from pandas.json import dumps
In [5]: dumps(1e-5)
Out[5]: '0.00001'
In [6]: dumps(1e-6)
Out[6]: '0.000001'
In [7]: dumps(1e-7)
Out[7]: '0.0000001'
In [8]: dumps(1e-8)
Out[8]: '0.00000001'
In [9]: dumps(1e-9)
Out[9]: '0.000000001'
In [10]: dumps(1e-10)
Out[10]: '0.0000000001'
In [11]: dumps(1e-11)
Out[11]: '0.0'
In [12]: dumps(1e-11, double_precision=15)
Out[12]: '0.00000000001'
In [13]: dumps(1e-12, double_precision=15)
Out[13]: '0.000000000001'
In [14]: dumps(1e-13, double_precision=15)
Out[14]: '0.0000000000001'
In [15]: dumps(1e-14, double_precision=15)
Out[15]: '0.00000000000001'
In [16]: dumps(1e-15, double_precision=15)
Out[16]: '0.000000000000001'
In [17]: dumps(1e-16, double_precision=15)
Out[17]: '1e-16'
In [18]: dumps(1e-16)
Out[18]: '1e-16'
In [19]: dumps(1e-17)
Out[19]: '1e-17'
In [20]: dumps(1e-40)
Out[20]: '1e-40'
In [21]: dumps(1e-100)
Out[21]: '1e-100'
In [22]: dumps(1e-400)
Out[22]: '0.0'
In [28]: dumps(1e40)
Out[28]: '1e+40'
In [29]: dumps(1e100)
Out[29]: '1e+100'
In [30]: dumps(1e400)
Out[30]: 'null'
In [31]: from pandas.json import loads
In [32]: loads(dumps(1e100))
Out[32]: 1e+100
In [33]: loads(dumps(1e40))
Out[33]: 1e+40
In [34]: loads(dumps(1e-40))
Out[34]: 1e-40
```
I have also modified it to throw a `ValueError` when a bad value is given for `double_precision`:
```
In [25]: dumps(1e-400, double_precision=-1)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-25-e15fa4642646> in <module>()
----> 1 dumps(1e-400, double_precision=-1)
ValueError: Invalid value '-1' for option 'double_precision', max is '15'
In [26]: dumps(1e-400, double_precision=16)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-26-ab74b2f14c7f> in <module>()
----> 1 dumps(1e-400, double_precision=16)
ValueError: Invalid value '16' for option 'double_precision', max is '15'
```
Tested on Python 2.7 on Arch-64. T'would be great if someone could test this out on windows.
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https://api.github.com/repos/pandas-dev/pandas/issues/4300 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/4300/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/4300/comments | https://api.github.com/repos/pandas-dev/pandas/issues/4300/events | https://github.com/pandas-dev/pandas/pull/4300 | 16,998,269 | MDExOlB1bGxSZXF1ZXN0NzA1NjQ4MA== | 4,300 | ENH: expose ujson precise_float argument on decode | {
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} | 9 | 2013-07-19T23:36:46Z | 2014-06-19T13:51:40Z | 2013-07-20T00:58:15Z | CONTRIBUTOR | null | The new version of ujson takes a boolean `precise_float` argument when decoding, this should be exposed when decoding pandas objects.
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