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https://api.github.com/repos/pandas-dev/pandas/issues/1201 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1201/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1201/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1201/events | https://github.com/pandas-dev/pandas/issues/1201 | 4,454,896 | MDU6SXNzdWU0NDU0ODk2 | 1,201 | .ix indexing can't handle duplicate index values | {
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(Pdb) result
A B C D
foo 2 3 4 5
bar 7 8 9 10
baz 12 13 14 15
qux 12 13 14 15
foo 12 13 14 15
bar 12 13 14 15
(Pdb) result.ix['bar']
*** Exception: Reindexing only valid with uniquely valued Index objects
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1202 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1202/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1202/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1202/events | https://github.com/pandas-dev/pandas/issues/1202 | 4,455,611 | MDU6SXNzdWU0NDU1NjEx | 1,202 | Business frequencies error in tsplot | {
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```
/home/wesm/code/pandas/pandas/tseries/plotting.py in tsplot(series, plotf, *args, **kwargs)
77 # Convert DatetimeIndex to PeriodIndex
78 if isinstance(series.index, DatetimeIndex):
---> 79 idx = series.index.... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1203 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1203/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1203/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1203/events | https://github.com/pandas-dev/pandas/issues/1203 | 4,455,720 | MDU6SXNzdWU0NDU1NzIw | 1,203 | Optimize Index.join for forward/backfilling | {
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"f... | 1 | 2012-05-07T15:03:09Z | 2019-01-01T17:24:29Z | 2019-01-01T17:24:29Z | MEMBER | null | Related to #216
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https://api.github.com/repos/pandas-dev/pandas/issues/1204 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1204/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1204/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1204/events | https://github.com/pandas-dev/pandas/issues/1204 | 4,457,665 | MDU6SXNzdWU0NDU3NjY1 | 1,204 | Improve parser performance when handling special characters | {
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at least comments should be preprocessed
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"f... | 2 | 2012-05-07T18:50:56Z | 2018-07-06T19:41:56Z | 2018-07-06T19:41:56Z | MEMBER | null | http://stackoverflow.com/questions/10484106/pandas-reading-csv-orientation
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https://api.github.com/repos/pandas-dev/pandas/issues/1206 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1206/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1206/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1206/events | https://github.com/pandas-dev/pandas/issues/1206 | 4,460,500 | MDU6SXNzdWU0NDYwNTAw | 1,206 | Series.interpolate with index of type float gives wrong result | {
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The logic for Series.interpolate assumes the indexes are equally spaced. With a floating point index this is not the desired interpolation. For example:
``` python
x1 = np.array([0, 0.25, 0.77, 1.2, 1.4, 2.6, 3.1])
y1 = np.array([0, 1.1, 0.5, 1.5, 1.2, 2.1, 2.4])
x2 = np.array([0, 0.25, 0.66, 1.0, 1.2, 1.4, 3.1... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1207 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1207/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1207/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1207/events | https://github.com/pandas-dev/pandas/issues/1207 | 4,461,063 | MDU6SXNzdWU0NDYxMDYz | 1,207 | Streamline / test perf of groupby Cython functions | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-05-07T19:55:16Z | 2012-05-08T14:44:07Z | 2012-05-08T14:44:07Z | MEMBER | null | Currently there's a single column special case. Does this actually impact performance?
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https://api.github.com/repos/pandas-dev/pandas/issues/1208 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1208/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1208/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1208/events | https://github.com/pandas-dev/pandas/issues/1208 | 4,461,119 | MDU6SXNzdWU0NDYxMTE5 | 1,208 | Eliminate doc + strings requiring index values be unique | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-05-07T19:58:28Z | 2012-05-19T19:24:51Z | 2012-05-19T19:24:19Z | CONTRIBUTOR | null | These are in lots of places. Need a round of docs clean up after full support for non-unique has been built in
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https://api.github.com/repos/pandas-dev/pandas/issues/1209 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1209/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1209/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1209/events | https://github.com/pandas-dev/pandas/pull/1209 | 4,464,130 | MDExOlB1bGxSZXF1ZXN0MTMwMzc0OQ== | 1,209 | Datetime tweaks to improve numpy 1.6/1.7 datetime64 compatibility | {
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API which would be nice to evolve. Pandas wasn't directly using this API for
functionality or interoperability, but more as a consequence of borrowing some
of the functional datetime operations from the numpy codebase.
As a result of do... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1211 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1211/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1211/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1211/events | https://github.com/pandas-dev/pandas/issues/1211 | 4,465,272 | MDU6SXNzdWU0NDY1Mjcy | 1,211 | Can't use PeriodIndex as DataFrame columns | {
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DataFrame(randn(10, 5), columns=period_range('1/1/2000', periods=5))
/pandas/pandas/core/frame.pyc in _apply_standard(self, func, axis, ignore_failures)
3209 try:
3210 if hasattr(e, 'args'):
-> 3211 e.args = e.args + ('occurre... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1212 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1212/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1212/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1212/events | https://github.com/pandas-dev/pandas/pull/1212 | 4,469,118 | MDExOlB1bGxSZXF1ZXN0MTMwNTgwOQ== | 1,212 | ENH: Add support for converting DataFrames to R data.frames and matrices | {
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The biggest drawback here is the use of an intermediate, ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1213 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1213/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1213/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1213/events | https://github.com/pandas-dev/pandas/issues/1213 | 4,471,701 | MDU6SXNzdWU0NDcxNzAx | 1,213 | Reading NA values properly from XLS files | {
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"I've got an excel file created from Paste Values that when read with pandas.ExcelFile returns int 42 for #N/A values.
Looking at http://stackoverflow.com/questions/4928629/xlrd-excel-script-converting-n-a-to-42 it would seem I'd need to be able to access the xlrd cell type rather tha... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1214 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1214/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1214/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1214/events | https://github.com/pandas-dev/pandas/issues/1214 | 4,473,149 | MDU6SXNzdWU0NDczMTQ5 | 1,214 | lib.reduce can't handle non-object index types | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1215 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1215/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1215/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1215/events | https://github.com/pandas-dev/pandas/issues/1215 | 4,473,555 | MDU6SXNzdWU0NDczNTU1 | 1,215 | Handling of array of Period objects -> PeriodIndex | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1216 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1216/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1216/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1216/events | https://github.com/pandas-dev/pandas/issues/1216 | 4,474,142 | MDU6SXNzdWU0NDc0MTQy | 1,216 | Add usecols argument to text file readers | {
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http://slendrmeans.wordpress.com/2012/04/14/will-it-python-machine-learning-for-hackers-chapter-1-part-1-loading-the-data
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https://api.github.com/repos/pandas-dev/pandas/issues/1217 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1217/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1217/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1217/events | https://github.com/pandas-dev/pandas/issues/1217 | 4,474,589 | MDU6SXNzdWU0NDc0NTg5 | 1,217 | MultiIndex formatting failure when index name coincides with first value | {
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(Pdb) grouped
value
a b c
0 foo 3.169106
b 1 bar 1.060375
(Pdb) grouped.index
MultiIndex([('a', 0, 'foo'), ('b', 1, 'bar')], dtype=object)
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1218 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1218/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1218/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1218/events | https://github.com/pandas-dev/pandas/pull/1218 | 4,482,162 | MDExOlB1bGxSZXF1ZXN0MTMxMTc3OQ== | 1,218 | ENH: Allow different number of rows & columns in histogram plot | {
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I added a simple way to allow this. The number of columns will not exceed the number of row... | {
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## FAIL: test_reindex_pad (pandas.tests.test_series.TestSeries)
Traceback (most recent call last):
File "C:\Program Files (x86)\Jenkins\workspace\pandas-windows-test-py27\pandas\tests\test_series.py", line 2263, in test_reindex_pad
assert_series_equal(reindexed, expected)
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https://api.github.com/repos/pandas-dev/pandas/issues/1220 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1220/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1220/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1220/events | https://github.com/pandas-dev/pandas/issues/1220 | 4,485,088 | MDU6SXNzdWU0NDg1MDg4 | 1,220 | "cumplyr"-like functionality | {
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http://www.johnmyleswhite.com/notebook/2012/05/03/cumplyr-extending-the-plyr-package-to-handle-cross-dependencies/
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https://api.github.com/repos/pandas-dev/pandas/issues/1221 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1221/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1221/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1221/events | https://github.com/pandas-dev/pandas/issues/1221 | 4,485,239 | MDU6SXNzdWU0NDg1MjM5 | 1,221 | Optimize _ensure_* functions in Cython using NumPy C API | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1222 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1222/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1222/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1222/events | https://github.com/pandas-dev/pandas/issues/1222 | 4,492,031 | MDU6SXNzdWU0NDkyMDMx | 1,222 | DataFrame.sort_index use with MultiIndex | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1223 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1223/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1223/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1223/events | https://github.com/pandas-dev/pandas/issues/1223 | 4,493,990 | MDU6SXNzdWU0NDkzOTkw | 1,223 | df.irow(slice(0, df.shape[0])).index != df.irow(slice(0, -1)).index | {
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```
In [108]: df = pandas.DataFrame(numpy.arange(12).reshape(3, 4))
In [109]: df
Out[109]:
0 1 2 3
0 0 1 2 3
1 4 5 6 7
2 8 9 10 11
In [110]: df.irow(slice(0, df.shape[0]))
Out[110]:
0 1 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1224 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1224/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1224/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1224/events | https://github.com/pandas-dev/pandas/issues/1224 | 4,504,625 | MDU6SXNzdWU0NTA0NjI1 | 1,224 | Better vectorize period field access | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1225 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1225/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1225/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1225/events | https://github.com/pandas-dev/pandas/pull/1225 | 4,530,266 | MDExOlB1bGxSZXF1ZXN0MTMzMjYxNA== | 1,225 | Tread parsing of xlrd cell errors as NaN | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1226 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1226/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1226/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1226/events | https://github.com/pandas-dev/pandas/pull/1226 | 4,536,421 | MDExOlB1bGxSZXF1ZXN0MTMzNTUwOQ== | 1,226 | ENH: Add JSON export option for DataFrame #631 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1227 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1227/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1227/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1227/events | https://github.com/pandas-dev/pandas/pull/1227 | 4,537,643 | MDExOlB1bGxSZXF1ZXN0MTMzNjA1NA== | 1,227 | ENH: convert multiple text file columns to a single date column | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1228 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1228/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1228/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1228/events | https://github.com/pandas-dev/pandas/issues/1228 | 4,547,961 | MDU6SXNzdWU0NTQ3OTYx | 1,228 | Broken quarter -> Period parsing | {
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In [1]: Period('2007Q2', freq='Q-JUN')
Out[1]: Period('2007Q4', 'Q-JUN')
```
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In [4]: Series(np.array([tm.rands(10) for _ in xrange(10)], dtype='O'))
Out[4]:
0 uU7IsfsSR0
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https://api.github.com/repos/pandas-dev/pandas/issues/1230 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1230/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1230/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1230/events | https://github.com/pandas-dev/pandas/issues/1230 | 4,549,041 | MDU6SXNzdWU0NTQ5MDQx | 1,230 | Writing PeriodIndex to HDFStore | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1231 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1231/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1231/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1231/events | https://github.com/pandas-dev/pandas/issues/1231 | 4,549,193 | MDU6SXNzdWU0NTQ5MTkz | 1,231 | Resampling of minutely / secondly periods -> 5 minute, etc. | {
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```
In [10]: ts
Out[10]:
2000-01-01 00:00:00-05:00 1.673428
2000-01-01 00:00:01-05:00 -0.647638
2000-01-01 00:00:02-05:00 0.185806
2000-01-01 00:00:03-05:00 -1.181972
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https://api.github.com/repos/pandas-dev/pandas/issues/1235 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1235/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1235/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1235/events | https://github.com/pandas-dev/pandas/issues/1235 | 4,557,160 | MDU6SXNzdWU0NTU3MTYw | 1,235 | Don't store class reference in HDFStore | {
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if np.nan is supplied, replace will mimic fillna (e.g., replace nan, inf or any value that is true if passed to isnull)
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# Save to hdf5.
kw = dict(table=True, compression='zlib')
store = pandas.HDFStore('ADCP_series.h5', 'w')
store.put('ADCP', ADCP, **kw)
store.put('Ancillary', Anc, **kw)
store.close()
On my Enthought Python Distribution I can load it fine (also with my previous setup),
pandas.__version__
Out[2]: '0.6.1'
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In [92]: a = DataFrame([1,2, None, 3, 4])
In [93]: a
Out[93]:
0
0 1
1 2
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3 3
4 4
In [94]: a.apply(lambda x: str(x[0]), axis=1)
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In [95]: a.apply(lambda x: int(x[0]), axis=1)
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#557
inplace keyword
#805
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## In [67]: ts.at_time(ts.index[2])
IndexError Traceback (most recent call last)
/home/chang/Dropbox/git/pandas/<ipython-input-67-324c3adda78b> in <module>()
----> 1 ts.at_time(ts.index[2])
/home/chang/Dropbox/git/pandas/pandas/core/series.py in at_time... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1250 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1250/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1250/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1250/events | https://github.com/pandas-dev/pandas/issues/1250 | 4,634,875 | MDU6SXNzdWU0NjM0ODc1 | 1,250 | Docs for multi-column parse_dates in parsers | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1251 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1251/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1251/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1251/events | https://github.com/pandas-dev/pandas/issues/1251 | 4,641,648 | MDU6SXNzdWU0NjQxNjQ4 | 1,251 | Use parsed date column as index | {
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(maybe as simple as a call to set_index)?
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https://api.github.com/repos/pandas-dev/pandas/issues/1252 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1252/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1252/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1252/events | https://github.com/pandas-dev/pandas/issues/1252 | 4,641,663 | MDU6SXNzdWU0NjQxNjYz | 1,252 | Option to remove parsed date component columns | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1253 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1253/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1253/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1253/events | https://github.com/pandas-dev/pandas/issues/1253 | 4,641,692 | MDU6SXNzdWU0NjQxNjky | 1,253 | Add parser option to return a Series if single column | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1254 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1254/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1254/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1254/events | https://github.com/pandas-dev/pandas/issues/1254 | 4,646,144 | MDU6SXNzdWU0NjQ2MTQ0 | 1,254 | HDFStore.get(non_existing_key) raises NoSuchNodeError | {
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"followers_url": "https://api.github.com/users/wesm/... | 1 | 2012-05-18T17:31:16Z | 2012-07-12T21:44:13Z | 2012-07-12T21:43:53Z | CONTRIBUTOR | null | Here is clipped traceback. I guess you need to catch NoSuchNodeError also. Or maybe it is better to ask pytables to make NoSuchNodeError a subclass of AttributeError? I am using PyTables 2.3.1 and 0.7.3.
```
/.../local/lib/python2.7/site-packages/pandas/io/pytables.pyc in get(self, key)
258 """
259 ... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1255 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1255/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1255/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1255/events | https://github.com/pandas-dev/pandas/issues/1255 | 4,647,761 | MDU6SXNzdWU0NjQ3NzYx | 1,255 | Improve Series.interpolate to use index values | {
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```
x1 = np.array([0, 0.25, 0.77, 1.2, 1.4, 2.6, 3.1])
y1 = np.array([0, 1.1, 0.5, 1.5, 1.2, 2.1, 2.4])
x2 = np.array([0, 0.25, 0.66, 1.0, 1.2, 1.4, 3.1])
y2 = np.array([0, 0.2, 0.8, 1.1, 2.2, 0.1, 2.4])
df1 = DataFrame(data=y1, index=x1, ... | {
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"f... | 3 | 2012-05-18T19:21:24Z | 2021-04-11T01:49:34Z | null | MEMBER | null | http://stackoverflow.com/questions/10475488/calculating-crossing-intercept-points-of-a-series-or-dataframe
```
def cross(series, cross=0, direction='cross'):
"""
Given a Series returns all the index values where the data values equal
the 'cross' value.
Direction can be 'rising' (for rising edge), 'f... | {
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In [5]: means_by_hour_of_day = training_data.groupby('hour')[target_names].mean()
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
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In [20]: rng = date_range('1/1/2000','12/31/2000')
In [21]: ts = Series(np.random.randn(len(rng)), index=rng)
In [22]: ts.resample('M', kind='period')
Out[22]:
Jan-2000 0.280017
Feb-2000 0.010740
Mar-2000 -0.175855
Apr-2000 -0.080775
May-2000 0.253388
Jun-2000 0.072629
Jul-2000 0.136193
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https://api.github.com/repos/pandas-dev/pandas/issues/1260 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1260/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1260/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1260/events | https://github.com/pandas-dev/pandas/issues/1260 | 4,660,996 | MDU6SXNzdWU0NjYwOTk2 | 1,260 | Test equality of timestamps with different time zones | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1261 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1261/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1261/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1261/events | https://github.com/pandas-dev/pandas/issues/1261 | 4,661,318 | MDU6SXNzdWU0NjYxMzE4 | 1,261 | Add nanosecond field accessor functions | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1262 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1262/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1262/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1262/events | https://github.com/pandas-dev/pandas/issues/1262 | 4,661,437 | MDU6SXNzdWU0NjYxNDM3 | 1,262 | pandas should not import scipy automatically | {
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>>> import pandas
>>> import sys
>>> 'scipy' in sys.modules
True
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1263 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1263/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1263/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1263/events | https://github.com/pandas-dev/pandas/pull/1263 | 4,667,179 | MDExOlB1bGxSZXF1ZXN0MTM5MTA3OQ== | 1,263 | ENH: Add JSON export option for DataFrame (take 2) | {
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All tests pass apart from the two below, tested on 64 bit OSX and 32 bit Ubuntu.
Time stamp JSON encoding/decoding in test_frame and test_series fails. I haven't looked into this too much, as Wes mentioned the work with timestamps was still ongoi... | {
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In [7]: tips.groupby('sex').agg({'tip' : {'mean' : 'mean', 'std' : 'std'}, 'size' : 'sum'})
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
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---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/home/wesm/Dropbox/book/svn/data/haiti/<ipython-input-165-efa692752119> in <module>()
----> 1 data.describe()
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Port-au-Prince 184
Jacmel 45
Pétionville 33
Leogane 24
Léogâne 22
index : Index([Port-au-Prince, Jacmel, Pétionville, Leogane, Léogâne], dtype=object)
```
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https://api.github.com/repos/pandas-dev/pandas/issues/1280 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1280/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1280/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1280/events | https://github.com/pandas-dev/pandas/pull/1280 | 4,682,664 | MDExOlB1bGxSZXF1ZXN0MTM5ODEzNQ== | 1,280 | Flex comp | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1281 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1281/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1281/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1281/events | https://github.com/pandas-dev/pandas/pull/1281 | 4,683,089 | MDExOlB1bGxSZXF1ZXN0MTM5ODMzMQ== | 1,281 | ENH: pct change for Series and DataFrame #1271 | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1282 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1282/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1282/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1282/events | https://github.com/pandas-dev/pandas/issues/1282 | 4,685,636 | MDU6SXNzdWU0Njg1NjM2 | 1,282 | Conversion to R matrix wreaks havoc in case of mixed type DataFrames | {
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I have two possible solutions I can send as pull request, and I would like to ask which is better:
1. raise ValueError for mixed type datafr... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1283 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1283/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1283/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1283/events | https://github.com/pandas-dev/pandas/pull/1283 | 4,685,830 | MDExOlB1bGxSZXF1ZXN0MTM5OTQ5NA== | 1,283 | BUG: Raise TypeError when converting mixed-type DataFrames, use proper NA types, close #1282 | {
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1. The use of improper NA types in R, which can cause issues when converting to matrices (NA_Logical gets converted to 0)
2. Improper casting when converting a mixed-type DataFrame to matrix, which will cause all sorts of problems: thus mixed types DataFrame raise a TypeE... | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1284 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1284/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1284/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1284/events | https://github.com/pandas-dev/pandas/pull/1284 | 4,686,295 | MDExOlB1bGxSZXF1ZXN0MTM5OTY5MA== | 1,284 | DOC: Add documentation for conversion to R objects | {
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Just wanted to put it out there.
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This is something that surprised me.
When reading from csv the values "True" and "False" are converted to bool, while "TRUE" and "FALSE"' to object
Using a converter {...: np.bool} I could take it into account.
Is it useful to take more possibilities into account knowing that there are a lot of poss... | {
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IndexError Traceback (most recent call last)
/home/adam/bin/jtds/<ipython-input-6-879cfff3d748> in <module>()
----> 1 DataFrame.from_records( [(1,2,3)], columns=['a','b','a'])
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https://api.github.com/repos/pandas-dev/pandas/issues/1299 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1299/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1299/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1299/events | https://github.com/pandas-dev/pandas/pull/1299 | 4,720,438 | MDExOlB1bGxSZXF1ZXN0MTQxNTI3Nw== | 1,299 | named index column for parser | {
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https://api.github.com/repos/pandas-dev/pandas/issues/1300 | https://api.github.com/repos/pandas-dev/pandas | https://api.github.com/repos/pandas-dev/pandas/issues/1300/labels{/name} | https://api.github.com/repos/pandas-dev/pandas/issues/1300/comments | https://api.github.com/repos/pandas-dev/pandas/issues/1300/events | https://github.com/pandas-dev/pandas/issues/1300 | 4,721,194 | MDU6SXNzdWU0NzIxMTk0 | 1,300 | option to suppress plotting of corresponding higher frequency reference | {
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"followers_url": "https://api.github.com/users/jorisva... | 4 | 2012-05-23T21:22:06Z | 2017-01-06T12:12:59Z | 2017-01-06T12:12:53Z | CONTRIBUTOR | null | > In pandas 0.8.0, the time series plotting will be much improved (see
> attached example plot)
> What I'd love to see is an option to switch the reference time value off for aggregated time series.
Examples:
- I have an average of wind speeds created from 5 years of data --> plotting a year would not make sense
- dai... | {
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