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MDExOlB1bGxSZXF1ZXN0ODgyMzcxNw==
5,101
BUG: fix PeriodIndex join with DatetimeIndex stack overflow
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3
2013-10-03T22:04:19Z
2014-07-16T08:33:03Z
2013-10-04T02:39:18Z
MEMBER
null
closes #3899.
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20,488,346
MDU6SXNzdWUyMDQ4ODM0Ng==
5,102
BUG: in .groupby.SeriesGroupBy plot not accessible?
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15
2013-10-03T22:46:08Z
2016-10-12T23:04:15Z
2013-10-04T17:19:18Z
CONTRIBUTOR
null
Previously, in `0.12` and earlier, I could quickly visualize `groupby` objects with a call to `.plot()`. Currently in master, the `.plot` method on a `groupby` object raises, with following error: ``` python --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) <ipython-input-63-3760a47a721b> in <module>() ----> 1 grp.kWh.plot() /pandas/pandas/core/groupby.pyc in __getattr__(self, attr) 250 251 if hasattr(self.obj, attr) and attr != '_cache': --> 252 return self._make_wrapper(attr) 253 254 raise AttributeError("%r object has no attribute %r" % /pandas/pandas/core/groupby.pyc in _make_wrapper(self, name) 265 "using the 'apply' method".format(kind, name, 266 type(self).__name__)) --> 267 raise AttributeError(msg) 268 269 f = getattr(self.obj, name) AttributeError: Cannot access callable attribute 'plot' of 'SeriesGroupBy' objects, try using the 'apply' method ```
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20,491,531
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5,103
DataFrame.cumsum() breaks when using a DataFrame that was filled using the isnan() function
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4
2013-10-04T00:18:10Z
2013-10-04T18:18:26Z
2013-10-04T00:48:13Z
NONE
null
Most help documents I've seen suggest using the fillna() function to fill a DataFrame. However, if you try to use the results of that fill operation with other functions, it can break. For example, the following code: `df = DataFrame(index=["A","B","C"], columns = [1,2,3,4,5]) df2 = df.fillna(1) df2.cumsum()` Fails with the following error message: ``` File "<stdin>", line 1, in <module> File "/Library/Python/2.7/site-packages/pandas/core/generic.py", line 827, in cumsum mask = np.isnan(self.values) TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe'' ``` However, creating a DataFrame filled with ones using the following works just fine: `df = DataFrame(np.ones((3,5)),index=["A","B","C"], columns = [1,2,3,4,5])`
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20,492,024
MDU6SXNzdWUyMDQ5MjAyNA==
5,104
ENH: Allow inplace arithmetic operations
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15
2013-10-04T00:34:19Z
2014-10-09T13:36:59Z
2014-10-09T13:36:59Z
CONTRIBUTOR
null
In current master (and before the initial arithmetic refactor), `__iadd__` doesn't do anything, it's just a synonym for `__add__` (or not defined). (just for reference, `v0.12.0` had `__iadd__ = __add__` on `Series` and no `__add__` defined on `DataFrame`). It would be great to support in place ops on `+=` and friends. Is this possible to do?
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5,105
BUG: allow plot, boxplot, hist and completion on GroupBy objects
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8
2013-10-04T00:57:36Z
2014-06-20T23:44:00Z
2013-10-04T17:19:18Z
MEMBER
null
closes #5102 also fixes extra plots created by groupby plotting (couldn't find an issue), now there's a test that ensures that groupby only plots the number of axes/figures it's supposed to removes an unused internal groupby parameter
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20,493,251
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5,106
BUG: read_html should convert array skiprows into a list
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1
2013-10-04T01:23:01Z
2014-07-11T22:34:05Z
2013-10-04T02:56:27Z
MEMBER
null
not sure why this is only showing up here, but it should be converted to a `list` anyway: https://travis-ci.org/cpcloud/pandas/jobs/12117482
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StopIteration in read_html
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25
2013-10-04T05:03:20Z
2019-01-21T14:24:20Z
2019-01-21T14:24:20Z
CONTRIBUTOR
null
``` pd.read_html("http://www.sec.gov/Archives/edgar/data/1174922/000119312513329016/d548026d10q.htm",header=[1,2,3]) ``` ``` ----> 1 pd.read_html("http://www.sec.gov/Archives/edgar/data/1174922/000119312513329016/d548026d10q.htm",header=[1,2,3]) /home/alex/git/pandas/pandas/io/html.pyc in read_html(io, match, flavor, header, index_col, skiprows, infer_types, attrs, parse_dates, tupleize_cols, thousands) 838 'data (you passed a negative value)') 839 return _parse(flavor, io, match, header, index_col, skiprows, infer_types, --> 840 parse_dates, tupleize_cols, thousands, attrs) /home/alex/git/pandas/pandas/io/html.pyc in _parse(flavor, io, match, header, index_col, skiprows, infer_types, parse_dates, tupleize_cols, thousands, attrs) 710 return [_data_to_frame(table, header, index_col, skiprows, infer_types, 711 parse_dates, tupleize_cols, thousands) --> 712 for table in tables] 713 714 /home/alex/git/pandas/pandas/io/html.pyc in _data_to_frame(data, header, index_col, skiprows, infer_types, parse_dates, tupleize_cols, thousands) 600 skiprows=_get_skiprows(skiprows), 601 parse_dates=parse_dates, tupleize_cols=tupleize_cols, --> 602 thousands=thousands) 603 df = tp.read() 604 /home/alex/git/pandas/pandas/io/parsers.pyc in TextParser(*args, **kwds) 1173 """ 1174 kwds['engine'] = 'python' -> 1175 return TextFileReader(*args, **kwds) 1176 1177 /home/alex/git/pandas/pandas/io/parsers.pyc in __init__(self, f, engine, **kwds) 485 self.options['has_index_names'] = kwds['has_index_names'] 486 --> 487 self._make_engine(self.engine) 488 489 def _get_options_with_defaults(self, engine): /home/alex/git/pandas/pandas/io/parsers.pyc in _make_engine(self, engine) 601 elif engine == 'python-fwf': 602 klass = FixedWidthFieldParser --> 603 self._engine = klass(self.f, **self.options) 604 605 def _failover_to_python(self): /home/alex/git/pandas/pandas/io/parsers.pyc in __init__(self, f, **kwds) 1291 self.data = f 1292 -> 1293 self.columns = self._infer_columns() 1294 1295 # we are processing a multi index column /home/alex/git/pandas/pandas/io/parsers.pyc in _infer_columns(self) 1485 1486 while self.pos <= hr: -> 1487 line = self._next_line() 1488 1489 this_columns = [] /home/alex/git/pandas/pandas/io/parsers.pyc in _next_line(self) 1544 line = self.data[self.pos] 1545 except IndexError: -> 1546 raise StopIteration 1547 else: 1548 while self.pos in self.skiprows: StopIteration: ```
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API: drop support for numpy < 1.7
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11
2013-10-04T14:47:39Z
2014-07-09T20:09:04Z
2014-01-24T14:30:54Z
CONTRIBUTOR
null
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5,109
Assigning to a Sliced Panel fails when slicing with boolean arrays
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2
2013-10-04T15:28:52Z
2018-07-06T20:21:02Z
2017-07-10T21:09:02Z
CONTRIBUTOR
null
This is similar to Issue #1533 and I've adapted the example from there. ``` python import numpy as np import pandas as pd a = pd.Panel(items=[1,2,3], major_axis=[11,22,33], minor_axis=[111,222,333]) b = pd.DataFrame(np.random.randn(2,3), index=[111,333], columns=[1,2,3]) c = pd.DataFrame(np.mat('1 2 3; 4 5 6'), index=[111,333], columns=[1,2,3]) # works now print "\na.ix[...] before" print a.ix[:, 22, [111, 333]] a.ix[:, 22, [111, 333]] = b print "\na.ix[...] after" print a.ix[:, 22, [111, 333]] tf = np.array([True, True, True]) tf2 = np.array([True, False, True]) # boolean indexing returns the same data print "\na.ix[tf, ...] before" print a.ix[tf, 22, tf2] a.ix[tf, 22, tf2] # but assigning to it fails try: a.ix[tf, 22, tf2] = c print "\na.ix[tf, ...] after" a.ix[tf, 22, tf2] except Exception, e: print e # however if we first create view into the Panel v = a.ix[:, 22, :] print "\nv.ix[tf, ...] before" print v.ix[tf2, tf] # then assigning works v.ix[tf2, tf] = c print "\nv.ix[tf, ...] after" print v.ix[tf2, tf] print "\na.ix[tf, ...] after" print a.ix[tf, 22, tf2] ``` produces output ``` a.ix[...] before 1 2 3 111 NaN NaN NaN 333 NaN NaN NaN a.ix[...] after 1 2 3 111 0.329258 0.759436 -0.070773 333 0.528950 -1.276978 0.084436 a.ix[tf, ...] before 1 2 3 111 0.329258 0.759436 -0.070773 333 0.528950 -1.276978 0.084436 shape mismatch: objects cannot be broadcast to a single shape v.ix[tf, ...] before 1 2 3 111 0.329258 0.759436 -0.070773 333 0.528950 -1.276978 0.084436 v.ix[tf, ...] after 1 2 3 111 1 2 3 333 4 5 6 a.ix[tf, ...] after 1 2 3 111 1 2 3 333 4 5 6 ```
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20,536,285
MDU6SXNzdWUyMDUzNjI4NQ==
5,110
DOC: build error from infer_dst feature
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6
2013-10-04T16:38:08Z
2013-10-04T16:54:53Z
2013-10-04T16:54:53Z
MEMBER
null
Error message: ``` AmbiguousTimeError: Cannot infer dst time from Timestamp('2011-11-06 01:00:00', tz=None), try using the 'infer_dst' argument ``` pr on the way
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5,111
DOC: doc fixups
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1
2013-10-04T16:54:20Z
2014-07-16T08:33:10Z
2013-10-04T16:54:53Z
MEMBER
null
closes #5110.
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MDExOlB1bGxSZXF1ZXN0ODg0ODM5MQ==
5,112
API: convert objects on fillna when object result dtype, related (GH5103)
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0
2013-10-04T18:18:26Z
2014-07-04T13:18:07Z
2013-10-04T19:53:42Z
CONTRIBUTOR
null
related #5103
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20,549,324
MDU6SXNzdWUyMDU0OTMyNA==
5,113
virtualenv installation fails on mac OSX 10.8.5. virtualenv 1.8.4; python 2.7.2
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2013-10-04T20:55:47Z
2013-10-05T04:25:34Z
2013-10-05T04:25:34Z
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``` $ bin/pip install pandas Downloading/unpacking pandas Downloading pandas-0.12.0.tar.gz (3.2MB): 3.2MB downloaded Running setup.py egg_info for package pandas Running from numpy source directory. Traceback (most recent call last): File "<string>", line 16, in <module> File "/Users/timanovsky/pandas/build/pandas/setup.py", line 548, in <module> **setuptools_kwargs) File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/distutils/core.py", line 112, in setup _setup_distribution = dist = klass(attrs) File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/dist.py", line 260, in __init__ File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/dist.py", line 284, in fetch_build_eggs File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/pkg_resources.py", line 563, in resolve File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/pkg_resources.py", line 799, in best_match File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/pkg_resources.py", line 811, in obtain File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/dist.py", line 327, in fetch_build_egg File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/command/easy_install.py", line 446, in easy_install File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/command/easy_install.py", line 476, in install_item File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/command/easy_install.py", line 655, in install_eggs File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/command/easy_install.py", line 930, in build_and_install File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/command/easy_install.py", line 919, in run_setup File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/sandbox.py", line 62, in run_setup File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/sandbox.py", line 105, in run File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/sandbox.py", line 64, in <lambda> File "setup.py", line 214, in <module> FULLVERSION += "-%s" % rev File "setup.py", line 191, in setup_package MICRO = 0 File "/var/folders/3z/0r_ycyx15l58th50t5trb1mc0000gn/T/easy_install-D6SLmc/numpy-1.7.1/numpy/distutils/core.py", line 25, in <module> File "/var/folders/3z/0r_ycyx15l58th50t5trb1mc0000gn/T/easy_install-D6SLmc/numpy-1.7.1/numpy/distutils/command/build_ext.py", line 16, in <module> File "/var/folders/3z/0r_ycyx15l58th50t5trb1mc0000gn/T/easy_install-D6SLmc/numpy-1.7.1/numpy/distutils/system_info.py", line 220, in <module> File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/sandbox.py", line 203, in _open File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/sandbox.py", line 199, in _violation setuptools.sandbox.SandboxViolation: SandboxViolation: open('/dev/null', 'w') {} The package setup script has attempted to modify files on your system that are not within the EasyInstall build area, and has been aborted. This package cannot be safely installed by EasyInstall, and may not support alternate installation locations even if you run its setup script by hand. Please inform the package's author and the EasyInstall maintainers to find out if a fix or workaround is available. Complete output from command python setup.py egg_info: Running from numpy source directory. Traceback (most recent call last): File "<string>", line 16, in <module> File "/Users/timanovsky/pandas/build/pandas/setup.py", line 548, in <module> **setuptools_kwargs) File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/distutils/core.py", line 112, in setup _setup_distribution = dist = klass(attrs) File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/dist.py", line 260, in __init__ File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/dist.py", line 284, in fetch_build_eggs File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/pkg_resources.py", line 563, in resolve File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/pkg_resources.py", line 799, in best_match File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/pkg_resources.py", line 811, in obtain File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/dist.py", line 327, in fetch_build_egg File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/command/easy_install.py", line 446, in easy_install File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/command/easy_install.py", line 476, in install_item File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/command/easy_install.py", line 655, in install_eggs File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/command/easy_install.py", line 930, in build_and_install File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/command/easy_install.py", line 919, in run_setup File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/sandbox.py", line 62, in run_setup File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/sandbox.py", line 105, in run File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/sandbox.py", line 64, in <lambda> File "setup.py", line 214, in <module> FULLVERSION += "-%s" % rev File "setup.py", line 191, in setup_package MICRO = 0 File "/var/folders/3z/0r_ycyx15l58th50t5trb1mc0000gn/T/easy_install-D6SLmc/numpy-1.7.1/numpy/distutils/core.py", line 25, in <module> File "/var/folders/3z/0r_ycyx15l58th50t5trb1mc0000gn/T/easy_install-D6SLmc/numpy-1.7.1/numpy/distutils/command/build_ext.py", line 16, in <module> File "/var/folders/3z/0r_ycyx15l58th50t5trb1mc0000gn/T/easy_install-D6SLmc/numpy-1.7.1/numpy/distutils/system_info.py", line 220, in <module> File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/sandbox.py", line 203, in _open File "/Users/timanovsky/pandas/lib/python2.7/site-packages/setuptools-0.6c11-py2.7.egg/setuptools/sandbox.py", line 199, in _violation setuptools.sandbox.SandboxViolation: SandboxViolation: open('/dev/null', 'w') {} The package setup script has attempted to modify files on your system that are not within the EasyInstall build area, and has been aborted. This package cannot be safely installed by EasyInstall, and may not support alternate installation locations even if you run its setup script by hand. Please inform the package's author and the EasyInstall maintainers to find out if a fix or workaround is available. ---------------------------------------- Command python setup.py egg_info failed with error code 1 in /Users/timanovsky/pandas/build/pandas Storing complete log in /Users/timanovsky/.pip/pip.log ```
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20,554,335
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5,114
MultiIndex DataFrame with tuple columns error?
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2013-10-04T22:54:48Z
2013-10-08T11:48:45Z
2013-10-08T11:48:45Z
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Hi, I am using pandas 0.12.0 and numpy 1.7.1. I get the below error when storing to a CSV a DataFrame with a multiIndex column composed of tuples and then loading it afterwards. Thanks for your help! ``` python import pandas as pd import numpy as np tup = ('a','g','b') arrays = [[tup] * 4, range(1,5)] tuples = zip(*arrays) multi_columns = pd.MultiIndex.from_tuples(tuples, names=['first','second']) index = range(1,10) df = pd.DataFrame(index = index, columns=multi_columns) df.to_csv('test.csv', tupleize_cols=False) df2 = pd.read_csv('test.csv', index_col = 0, parse_dates = True, header=[0,1], tupleize_cols=False) df.columns[0][0] ('a', 'g', 'b') df2.columns[0][0] "('a', 'g', 'b')" df2[df.columns[0][0],] TypeError: not all arguments converted during string formatting ```
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No WeekOfMonth Defined for Weekends
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15
2013-10-05T01:03:05Z
2016-12-11T14:06:54Z
2016-12-11T14:06:54Z
CONTRIBUTOR
null
``` In [35]: pd.date_range("2013-1-1", periods=4,freq='WOM-1SAT') ----> 1 pd.date_range("2013-1-1", periods=4,freq='WOM-1SAT') /home/alex/git/pandas/pandas/tseries/index.pyc in date_range(start, end, periods, freq, tz, normalize, name) 1724 """ 1725 return DatetimeIndex(start=start, end=end, periods=periods, -> 1726 freq=freq, tz=tz, normalize=normalize, name=name) 1727 1728 /home/alex/git/pandas/pandas/tseries/index.pyc in __new__(cls, data, freq, start, end, periods, copy, name, tz, verify_integrity, normalize, **kwds) 158 # if a passed freq is None, don't infer automatically 159 if freq != 'infer': --> 160 freq = to_offset(freq) 161 else: 162 freq_infer = True /home/alex/git/pandas/pandas/tseries/frequencies.pyc in to_offset(freqstr) 463 delta = delta + offset 464 except Exception: --> 465 raise ValueError("Could not evaluate %s" % freqstr) 466 467 if delta is None: ValueError: Could not evaluate WOM-1SAT ``` I will fix as part of #5004
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BUG: Apparent Canopy IPython bugs with PySide bindings.
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7
2013-10-05T04:30:05Z
2013-10-08T23:55:51Z
2013-10-08T23:55:51Z
CONTRIBUTOR
null
Opening up a separate issue about some Canopy IPython bugs that pandas (or new BigQuery IO module) may be producing. @azbones, @jacobschaer, @sean-schaefer and others, let's work here to figure it out. Related comments in #4140.
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5,117
CLN: Remove redundant initialization from Int64Index and Float64Index constructor
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3
2013-10-05T16:02:04Z
2014-07-16T08:33:14Z
2013-10-05T19:43:22Z
CONTRIBUTOR
null
`Int64Index` repeated itself and actually reconstructed an ndarray twice when passed in data was an iterable. This simplifies it down but does not actually change any behavior. (you'll see that there was basically exactly the same code twice)
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5,118
BUG: Failing eval tests on OS X
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16
2013-10-05T16:18:46Z
2013-10-16T12:56:19Z
2013-10-16T12:56:19Z
CONTRIBUTOR
null
These two tests fail (note the warning that it generates, happens in one other place but the test passes). ``` pandas.computation.tests.test_eval.TestAlignment.test_basic_series_frame_alignment('numexpr', 'python') ... /Users/jtratner/scratch/pandas/pandas/core/index.py:900: RuntimeWarning: tp_compare didn't return -1 or -2 for exception result.sort() FAIL pandas.computation.tests.test_eval.TestAlignment.test_basic_series_frame_alignment('numexpr', 'pandas') ... FAIL ``` Traceback: ``` FAIL: pandas.computation.tests.test_eval:TestAlignment.test_basic_series_frame_alignment('numexpr', 'python') /usr/local/bin/vim +872 pandas/computation/tests/test_eval.py # check_basic_series_frame_alignment testit(r_idx_type, c_idx_type, index_name) /usr/local/bin/vim +867 pandas/computation/tests/test_eval.py # testit assert_frame_equal(res, expected) /usr/local/bin/vim +312 pandas/util/testing.py # assert_frame_equal assert_index_equal(left.columns, right.columns) /usr/local/bin/vim +192 pandas/util/testing.py # assert_index_equal right.dtype)) AssertionError: [index] left [object Index([1, 2000-01-03 00:00:00, 2000-01-04 00:00:00, 2000-01-05 00:00:00, 2, 4, 3, 0, 2000-01-06 00:00:00, 2000-01-07 00:00:00, 2000-01-10 00:00:00, 2000-01-11 00:00:00], dtype=object)], right [Index([2000-01-03 00:00:00, 2000-01-04 00:00:00, 2000-01-05 00:00:00, 2000-01-06 00:00:00, 2000-01-07 00:00:00, 2000-01-10 00:00:00, 2000-01-11 00:00:00, 0, 1, 2, 3, 4], dtype=object) object] FAIL: pandas.computation.tests.test_eval:TestAlignment.test_basic_series_frame_alignment('numexpr', 'pandas') /usr/local/bin/vim +872 pandas/computation/tests/test_eval.py # check_basic_series_frame_alignment testit(r_idx_type, c_idx_type, index_name) /usr/local/bin/vim +867 pandas/computation/tests/test_eval.py # testit assert_frame_equal(res, expected) /usr/local/bin/vim +312 pandas/util/testing.py # assert_frame_equal assert_index_equal(left.columns, right.columns) /usr/local/bin/vim +192 pandas/util/testing.py # assert_index_equal right.dtype)) AssertionError: [index] left [object Index([1, 2000-01-03 00:00:00, 2000-01-04 00:00:00, 2000-01-05 00:00:00, 2, 4, 3, 0, 2000-01-06 00:00:00, 2000-01-07 00:00:00, 2000-01-10 00:00:00, 2000-01-11 00:00:00], dtype=object)], right [Index([2000-01-03 00:00:00, 2000-01-04 00:00:00, 2000-01-05 00:00:00, 2000-01-06 00:00:00, 2000-01-07 00:00:00, 2000-01-10 00:00:00, 2000-01-11 00:00:00, 0, 1, 2, 3, 4], dtype=object) object] ```
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5,119
CLN: Remove leftover test.py file
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2013-10-05T16:25:24Z
2014-07-16T08:33:15Z
2013-10-05T16:32:34Z
CONTRIBUTOR
null
Extra test file at top level with a set_trace on it was checked in with the json normalize PR. I'm assuming it shouldn't be here. @jreback @cpcloud? I think it's causing the test suite to hang for me, since I run it from within the pandas directory.
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ENH?: __repr__ method for Index objects
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13
2013-10-05T20:03:05Z
2013-12-20T17:21:48Z
2013-12-20T17:06:46Z
NONE
null
It often happens that I print a MultiIndex object (whether on purpose or not) which leads to flooding my interpreter and makes it unresponsive for a couple of seconds since often the length of my indexers exceeds 500-1000k. I was thinking about adding a neat `__repr__` for Indexers that summarizes levels + length or just omits what's in the middle once a certain length is exceeded. It seems this has not been tackled so far when looking at the current master, but please feel free to close this issue if this is a dupe (checked but did not find anything related). Any pointers are welcome.
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CLN: clean up parser options
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6
2013-10-05T22:34:34Z
2014-06-24T19:40:22Z
2013-10-05T23:28:25Z
MEMBER
null
Also add a test to make sure that the C parser options validation is actually covered example travis fail: https://travis-ci.org/pydata/pandas/jobs/12171563 explanation (for the record): if you print out `options` before this commit you'll see that they are all overwritten with a single value. Whatever this value is will depend on how the `_parser_defaults` dictionary happens to be ordered (which is random because of hashing). This caused a bug because the value of `value` is retained from the loop over `_parser_defaults`, and `default` is _not_ reassigned in the two loops that follow the loop over `_parser_defaults`, so all the values end up being the same as the last argument that was iterated over from `_parser_defaults`. magic explained :tada:
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5,122
TST: Tests and fix for unhandled data types in Excel writers.
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7
2013-10-06T08:18:32Z
2014-06-16T01:40:59Z
2013-10-14T01:40:48Z
CONTRIBUTOR
null
Added tests and a fix for unhandled numpy data types in the Excel writers. Issue #3122.
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BUG: Segfault on isnull(MultiIndex)
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4
2013-10-06T16:54:17Z
2013-10-11T12:01:34Z
2013-10-11T12:01:34Z
CONTRIBUTOR
null
``` In [1]: from pandas import * In [2]: idx = MultiIndex.from_tuples([(0, 'a'), (1, 'b'), (2, 'c')]) In [3]: pd.isnull(idx) Segmentation fault: 11 (pandas-dev)dhcp80fff527:pandas tom$ ``` This is on latest master (`'0.12.0-757-g69b67f3'`). Numpy 1.7.1.
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20,582,542
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5,124
Add indexer and str to API documentation
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27
2013-10-06T16:58:05Z
2014-09-03T22:59:19Z
2013-10-15T18:40:49Z
CONTRIBUTOR
null
closes https://github.com/pydata/pandas/issues/5068
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21
2013-10-06T17:25:14Z
2014-06-13T10:01:30Z
2013-10-11T12:01:34Z
CONTRIBUTOR
null
Now raises NotImplementedError b/c not yet clear what it should return. Fixes #5123.
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20,583,928
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5,126
Docs for read_html : parse_dates
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9
2013-10-06T18:34:02Z
2016-10-12T23:04:16Z
2013-10-11T20:56:30Z
CONTRIBUTOR
null
`parse_dates` should have a little more documentation (I did look at docs on read_csv as well). It is not clear to me what the default value of parse_dates is. Alson on read_html is listed as "bool" whereas on read_csv as "boolean, list of ints or names, list of lists, or dict". I am not sure what setting parse_dates=False does.
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20,584,913
MDExOlB1bGxSZXF1ZXN0ODg2ODkwMw==
5,127
add test for indexing with integer arrays
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6
2013-10-06T19:39:58Z
2014-06-23T23:20:34Z
2013-10-06T23:55:33Z
NONE
null
I had a try at solving issue #5006, but it does not look as trivial to me as @jreback suggested. ;-) I added a test for indexing with int-typed arrays containing single indices, which currently fails. I spent some time reading test_indexing, because my hunch is that it could be better integrated with the existing tests (e.g. using check_result), but anyhow - any test is better than none, I guess. The failing test goes through `_iLocIndexer._getitem_axis()` -> `_NDFrameIndexer._get_loc()` -> `Series._ixs()` -> `index.get_value_at()` -> `util.get_value_at()`, but I don't see the point where that should've been different right now. Sorry, but I lack time for solving this at the moment.
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5,128
ENH: Support for PyExcelerate as an Excel writer engine.
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7
2013-10-06T19:42:15Z
2014-06-29T09:44:06Z
2013-12-22T21:02:16Z
CONTRIBUTOR
null
This is an initial patch to add PyExcelerate as an Excel writer engine. **It isn't suitable for merge** yet since there is issue with date handling in PyExcelerate that I am working to resolve with the authors. I just want this to appear on the pandas timeline for now so I can refer to it in other PRs. 1. The requirements files are missing since the PR will require a PyExcelerate update and release. Also, the `print_versions.py` entry. 2. There is also a failing test due to versioning. 3. There is currently no merged cell support. I'll fix all these before the final PR request. John
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5,129
Exception with read_html and header
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23
2013-10-06T20:02:32Z
2016-10-12T23:04:16Z
2014-02-27T19:02:44Z
CONTRIBUTOR
null
``` python In [5]: pd.read_html("http://pastebin.com/raw.php?i=7mAF0Ei6",infer_types=False, header=[0,1])[0] --------------------------------------------------------------------------- ----> 1 pd.read_html("http://pastebin.com/raw.php?i=7mAF0Ei6",infer_types=False, header=[0,1])[0] /home/alex/git/pandas/pandas/io/html.pyc in read_html(io, match, flavor, header, index_col, skiprows, infer_types, attrs, parse_dates, tupleize_cols, thousands) 838 'data (you passed a negative value)') 839 return _parse(flavor, io, match, header, index_col, skiprows, infer_types, --> 840 parse_dates, tupleize_cols, thousands, attrs) /home/alex/git/pandas/pandas/io/html.pyc in _parse(flavor, io, match, header, index_col, skiprows, infer_types, parse_dates, tupleize_cols, thousands, attrs) 710 return [_data_to_frame(table, header, index_col, skiprows, infer_types, 711 parse_dates, tupleize_cols, thousands) --> 712 for table in tables] 713 714 /home/alex/git/pandas/pandas/io/html.pyc in _data_to_frame(data, header, index_col, skiprows, infer_types, parse_dates, tupleize_cols, thousands) 600 skiprows=_get_skiprows(skiprows), 601 parse_dates=parse_dates, tupleize_cols=tupleize_cols, --> 602 thousands=thousands) 603 df = tp.read() 604 /home/alex/git/pandas/pandas/io/parsers.pyc in TextParser(*args, **kwds) 1171 """ 1172 kwds['engine'] = 'python' -> 1173 return TextFileReader(*args, **kwds) 1174 1175 /home/alex/git/pandas/pandas/io/parsers.pyc in __init__(self, f, engine, **kwds) 481 self.options['has_index_names'] = kwds['has_index_names'] 482 --> 483 self._make_engine(self.engine) 484 485 def _get_options_with_defaults(self, engine): /home/alex/git/pandas/pandas/io/parsers.pyc in _make_engine(self, engine) 596 elif engine == 'python-fwf': 597 klass = FixedWidthFieldParser --> 598 self._engine = klass(self.f, **self.options) 599 600 def _failover_to_python(self): /home/alex/git/pandas/pandas/io/parsers.pyc in __init__(self, f, **kwds) 1294 if len(self.columns) > 1: 1295 self.columns, self.index_names, self.col_names, _ = self._extract_multi_indexer_columns( -> 1296 self.columns, self.index_names, self.col_names) 1297 else: 1298 self.columns = self.columns[0] /home/alex/git/pandas/pandas/io/parsers.pyc in _extract_multi_indexer_columns(self, header, index_names, col_names, passed_names) 734 # if we find 'Unnamed' all of a single level, then our header was too long 735 for n in range(len(columns[0])): --> 736 if all([ 'Unnamed' in c[n] for c in columns ]): 737 raise _parser.CParserError("Passed header=[%s] are too many rows for this " 738 "multi_index of columns" % ','.join([ str(x) for x in self.header ])) TypeError: argument of type 'float' is not iterable ```
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5,130
Make _LxmlFrameParser more extensible
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19
2013-10-06T20:07:50Z
2016-10-12T23:04:16Z
2014-01-29T03:59:48Z
CONTRIBUTOR
null
Allow creating a `_LiberalLxmlFrameParser` (see conversation on: https://github.com/pydata/pandas/issues/4469#issuecomment-22142824) For now I will factor out: ``` parser = HTMLParser(recover=False) ``` so that subclass can change the behavior. Would there be an issue with adding `_LiberalLxmlFrameParser` to the Pandas codebase?
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5,131
ENH: Added lxml-liberal html parsing flavor
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29
2013-10-06T20:51:31Z
2014-07-21T06:35:36Z
2013-11-01T00:23:43Z
CONTRIBUTOR
null
Closes #5130
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5,132
BUG: set_names should not change is_ relationship
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2013-10-06T22:25:20Z
2014-07-16T08:33:25Z
2013-10-06T23:24:16Z
CONTRIBUTOR
null
inplace change shouldn't change identity on set names (my bad)
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5,133
to_json should validate its arguments
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0
2013-10-06T22:27:31Z
2013-10-06T22:30:11Z
2013-10-06T22:30:11Z
MEMBER
null
``` In [67]: df Out[67]: counter created 05-16-13 3 05-17-13 1 05-18-13 1 In [68]: print df.to_json('asdfasdf') None In [69]: print df.to_dict('series') {'counter': created 05-16-13 3 05-17-13 1 05-18-13 1 Name: counter, dtype: int64} In [70]: print df.counter.to_json('asdfasdf') None In [71]: print df.counter.to_json('index') None ``` The "default" value of `'index'` (whose default is actually `None`) doesn't do what it says.
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BUG: Treat a list/ndarray identically for iloc indexing with list-like (GH5006)
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0
2013-10-06T23:55:10Z
2014-06-18T14:51:20Z
2013-10-07T00:10:08Z
CONTRIBUTOR
null
closes #5006
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PERF: perf of e6b99f4 vs v0.12.0
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3
2013-10-07T00:29:03Z
2013-10-13T23:33:01Z
2013-10-13T23:33:01Z
CONTRIBUTOR
null
I have put boxes by the ones 2 look at, some/most of these were caused by #3482, but always worth taking a look. - [x] frame_xs_col, miniscule - [x] groupby_multi_python, #3482 - [x] concat_series_axis1, series construction overhead (so ok) - [x] period_setitem, issue #5155, will need to be address in 0.14 - [x] frame_iloc_dups, miniscule - [x] reshape_stack_simple, fixed after #5178 - [x] frame_iteritems, #3482 - [x] frame_fancy_lookup, series construction overhead (so ok) - [x] sparse_frame_constructor, #3482 - [x] timeseries_period_downsample_mean, PR #5204 - [x] series_timestamp_compare, PR #5154 (was boxing isnull) - [x] reindex_daterange_pad, PR #5178 (not using specialized indexer) - [x] reindex_daterange_backfill, PR #5178 (not using specialized indexer) The good ``` ------------------------------------------------------------------------------- Test name | head[ms] | base[ms] | ratio | ------------------------------------------------------------------------------- plot_timeseries_period | 54.3883 | 1061.3217 | 0.0512 | timeseries_to_datetime_YYYYMMDD | 9.4270 | 42.3674 | 0.2225 | write_store_table_mixed | 36.2830 | 116.2400 | 0.3121 | packers_write_hdf_table | 29.6400 | 77.6550 | 0.3817 | write_store_table_panel | 47.1393 | 88.3977 | 0.5333 | write_store_table | 30.7643 | 56.7960 | 0.5417 | read_csv_thou_vb | 17.3206 | 30.3980 | 0.5698 | frame_getitem_single_column | 25.7526 | 40.0293 | 0.6433 | ``` The bad ``` ------------------------------------------------------------------------------- Test name | head[ms] | base[ms] | ratio | ------------------------------------------------------------------------------- frame_xs_col | 0.0350 | 0.0233 | 1.5051 | groupby_multi_python | 123.9320 | 81.8870 | 1.5135 | concat_series_axis1 | 93.0324 | 60.6890 | 1.5329 | period_setitem | 212.0950 | 138.1503 | 1.5352 | frame_iloc_dups | 0.3070 | 0.1993 | 1.5403 | reshape_stack_simple | 1.9557 | 1.1647 | 1.6792 | frame_iteritems | 37.6317 | 19.2017 | 1.9598 | frame_fancy_lookup | 3.4526 | 1.6307 | 2.1173 | sparse_frame_constructor | 12.2224 | 5.3250 | 2.2953 | timeseries_period_downsample_mean | 14.1153 | 5.4576 | 2.5863 | series_timestamp_compare | 7.3427 | 1.8593 | 3.9491 | reindex_daterange_pad | 2.8083 | 0.6460 | 4.3476 | reindex_daterange_backfill | 2.8074 | 0.6456 | 4.3482 | ------------------------------------------------------------------------------- Test name | head[ms] | base[ms] | ratio | ------------------------------------------------------------------------------- Ratio < 1.0 means the target commit is faster then the baseline. Seed used: 1234 Target [e6b99f4] : Merge pull request #5134 from jreback/list_index BUG: Treat a list/ndarray identically for iloc indexing with list-like (GH5006) Base [8c0a34f] : RLS: set released to True, edit release dates ```
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BUG/CLN: fillna with string-like raises
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0
2013-10-07T01:17:50Z
2013-10-07T13:00:51Z
2013-10-07T13:00:51Z
CONTRIBUTOR
null
The `fillna` should work with this type of replacement (_could_ just directly call `replace` if `method=None` in fact). ``` In [1]: df = DataFrame(dict(A = [1,np.nan])) In [2]: df Out[2]: A 0 1 1 NaN In [3]: df.fillna('') ValueError: could not convert string to float: In [4]: df.replace(np.nan,'') Out[4]: A 0 1 1 ``` http://stackoverflow.com/questions/19215383/how-to-not-display-nan-in-ipython-notebook-html-table-of-pandas-dataframe
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1
2013-10-07T03:03:53Z
2014-06-12T23:21:59Z
2013-10-07T12:27:06Z
CONTRIBUTOR
null
Adds `datetime.time` support to JSON serialiser. Note: - times are encoded to strings and will be decoded to strings. - `date_unit` and `date_format` params have no affect on `time` serialisation, they are always iso formatted. Fixes #4873
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ENH: json default_handler param
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2
2013-10-07T06:02:37Z
2014-06-15T16:16:36Z
2013-10-07T12:36:33Z
CONTRIBUTOR
null
This adds a `default_handler` param to `to_json`, which if passed must be a callable which takes one argument (the object to convert) and returns a serialisable object. The `default_handler` will only be used if an object cannot otherwise be serialised. Note right now the JSON serialiser has direct handling for: - Python basic types `bool`, `int`, `long`, `float`. - Python containers `dict`, `list`, `tuple` and `set`. - Python byte and unicode strings. - Python decimal. - Python `datetime` and `date`. - Python `None`. - Numpy arrays. - Numpy scalars - `NaN` and `NaT` - Pandas `Index`, `Series`, `DataFrame` and `Timestamp` - any subclasses of the above. If an object is not recognised the fallback behaviour with this PR would be: 1. if a `toDict` method is defined by the unrecognised object that will be called and its returned `dict` will be JSON serialised. 2. if a `default_handler` has been passed to `to_json` that will be called to convert the object. 3. otherwise an attempt is made to convert the object to a `dict` by iterating over its attributes.
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20,609,006
MDExOlB1bGxSZXF1ZXN0ODg4MDgyNA==
5,139
TST: fillna(values) equiv of replace(np.nan,values)
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0
2013-10-07T12:48:49Z
2014-06-26T11:25:23Z
2013-10-07T13:00:51Z
CONTRIBUTOR
null
closes #5136 (just tests), as not a bug
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20,613,546
MDU6SXNzdWUyMDYxMzU0Ng==
5,140
[sparc, python2.6] test_replace_value_is_none: expected -100000000.00000 but got 0.00000
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closed
false
null
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2
2013-10-07T14:13:34Z
2013-10-08T12:13:38Z
2013-10-08T12:13:38Z
CONTRIBUTOR
null
endianness issue I guess. Seems to happen only with python2.6 on that box: http://nipy.bic.berkeley.edu/builders/pandas-py2.6-wheezy-sparc/builds/149/steps/shell_4/logs/stdio `schroot -c wheezy` would bring you into that env (for anyone with access)
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5,141
[sparc, python3.3] test_BytesIO_input and test_variable_width_unicode: UnicodeDecodeError: 'ascii' codec can't decode byte 0xd7 in position 0: ordinal not in range(128)
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closed
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1
2013-10-07T14:15:51Z
2013-10-08T02:04:28Z
2013-10-08T02:04:28Z
CONTRIBUTOR
null
http://nipy.bic.berkeley.edu/builders/pandas-py3.x-sid-sparc/builds/230/steps/shell_4/logs/stdio ``` ====================================================================== ERROR: test_variable_width_unicode (pandas.io.tests.test_parsers.TestFwfColspaceSniffing) ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/tests/test_parsers.py", line 2322, in test_variable_width_unicode colspecs=[(0, 4), (5, 9)], header=None) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 433, in read_fwf return _read(filepath_or_buffer, kwds) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 203, in _read parser = TextFileReader(filepath_or_buffer, **kwds) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 483, in __init__ self._make_engine(self.engine) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 598, in _make_engine self._engine = klass(self.f, **self.options) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 2084, in __init__ PythonParser.__init__(self, f, **kwds) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 1291, in __init__ self.columns = self._infer_columns() File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 1523, in _infer_columns line = self._next_line() File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 1550, in _next_line line = next(self.data) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 2066, in next line = next(self.f) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/encodings/ascii.py", line 26, in decode return codecs.ascii_decode(input, self.errors)[0] UnicodeDecodeError: 'ascii' codec can't decode byte 0xd7 in position 0: ordinal not in range(128) ====================================================================== ERROR: test_BytesIO_input (pandas.io.tests.test_parsers.TestPythonParser) ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/tests/test_parsers.py", line 2150, in test_BytesIO_input result = pd.read_fwf(BytesIO("\u05e9\u05dc\u05d5\u05dd\n\u05e9\u05dc\u05d5\u05dd".encode('utf8')), widths=[2,2]) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 433, in read_fwf return _read(filepath_or_buffer, kwds) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 203, in _read parser = TextFileReader(filepath_or_buffer, **kwds) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 483, in __init__ self._make_engine(self.engine) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 598, in _make_engine self._engine = klass(self.f, **self.options) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 2084, in __init__ PythonParser.__init__(self, f, **kwds) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 1291, in __init__ self.columns = self._infer_columns() File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 1482, in _infer_columns line = self._next_line() File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 1550, in _next_line line = next(self.data) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/site-packages/pandas-0.12.0_755_ge6b99f4-py3.3-linux-sparc64.egg/pandas/io/parsers.py", line 2066, in next line = next(self.f) File "/home/buildslave/nd-bb-slave-sparc-sid/pandas-py3_x-sid-sparc/build/venv/lib/python3.3/encodings/ascii.py", line 26, in decode return codecs.ascii_decode(input, self.errors)[0] UnicodeDecodeError: 'ascii' codec can't decode byte 0xd7 in position 0: ordinal not in range(128) ---------------------------------------------------------------------- Ran 4083 tests in 1851.237s FAILED (SKIP=291, errors=2) ```
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20,640,528
MDU6SXNzdWUyMDY0MDUyOA==
5,142
doc generation fails on windows
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{ "closed_at": "2014-05-30T12:17:57Z", "closed_issues": 755, "created_at": "2014-01-03T20:19:04Z", "creator": null, "description": "2014-02-3: previous version released", "due_on": "2014-05-31T07:00:00Z", "html_url": "https://github.com/pandas-dev/pandas/milestone/24", "id": 526062, "labels_url": "https://api.github.com/repos/pandas-dev/pandas/milestones/24/labels", "node_id": "MDk6TWlsZXN0b25lNTI2MDYy", "number": 24, "open_issues": 0, "state": "closed", "title": "0.14.0", "updated_at": "2016-12-29T13:57:13Z", "url": "https://api.github.com/repos/pandas-dev/pandas/milestones/24" }
23
2013-10-07T21:31:30Z
2014-01-24T16:50:09Z
2014-01-24T16:22:19Z
CONTRIBUTOR
null
``` [...] reading sources... [ 75%] io Exception occurred while building, starting debugger: Traceback (most recent call last): File "c:\portabel\python27\lib\site-packages\sphinx\cmdline.py", line 246, in main app.build(force_all, filenames) File "c:\portabel\python27\lib\site-packages\sphinx\application.py", line 212, in build self.builder.build_update() File "c:\portabel\python27\lib\site-packages\sphinx\builders\__init__.py", lin e 214, in build_update 'out of date' % len(to_build)) File "c:\portabel\python27\lib\site-packages\sphinx\builders\__init__.py", lin e 234, in build purple, length): File "c:\portabel\python27\lib\site-packages\sphinx\builders\__init__.py", lin e 134, in status_iterator for item in iterable: File "c:\portabel\python27\lib\site-packages\sphinx\environment.py", line 470, in update_generator self.read_doc(docname, app=app) File "c:\portabel\python27\lib\site-packages\sphinx\environment.py", line 621, in read_doc raise SphinxError(str(err)) SphinxError: 'utf8' codec can't decode byte 0x84 in position 25: invalid start b yte ``` The problem is the following line in io.rst: ``` data = 'word,length\nTr\xe4umen,7\nGr\xfc\xdfe,5' ```
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20,641,179
MDU6SXNzdWUyMDY0MTE3OQ==
5,143
Replace partial matches behavior
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8
2013-10-07T21:43:36Z
2016-10-12T23:04:16Z
2013-10-08T04:35:21Z
CONTRIBUTOR
null
I ran into some unexpected behavior with `replace` today. I want to replace the answer with a numeric value according to the dictionary `weights` ``` python In [33]: df.answer.head() Out[33]: 0 Strongly Agree 1 Agree 2 Neutral 3 Disagree 4 Strongly Disagree Name: answer, dtype: object In [34]: weights Out[34]: {'Agree': 4, 'Disagree': 2, 'Neutral': 3, 'Strongly Agree': 5, 'Strongly Disagree': 1} In [35]: df.answer.replace(weights).head() Out[35]: 0 4 1 4 2 3 3 2 4 2 dtype: int64 ``` It looks like replace matches on the first part, `Agree`, or `Disagree` and doesn't make it through the dict to the `Strongly`s. Am I just being a noob with how regexes work, or is this a bug?
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MDU6SXNzdWUyMDY0MjE4NA==
5,144
Import StataReader, StataWriter under pandas?
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3
2013-10-07T22:01:52Z
2013-10-08T14:52:33Z
2013-10-07T22:20:40Z
CONTRIBUTOR
null
The classes are already documented as API, but they are not in the corresponding api.py files and therefore not available as `pandas.*`, unlike classes like `ExcelFile` or `HDFStore`, which are available under the `pandas` module.
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20,645,805
MDExOlB1bGxSZXF1ZXN0ODkwMTYzNA==
5,145
BUG: allow tuples in recursive call to replace
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15
2013-10-07T23:24:10Z
2014-06-24T07:44:28Z
2013-10-08T04:35:21Z
MEMBER
null
This avoids the seeming passage of regular expressions closes #5143.
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Improve config lookups when you know exactly what key you want
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2013-10-08T00:10:50Z
2013-10-08T14:37:51Z
2013-10-08T14:37:51Z
CONTRIBUTOR
null
Right now sometimes getting config options iterates over a list filtering on regular expressions, which seems like overdoing it when internal code knows exactly what it wants. Makes sense to add getitem and set item to bypass the checks (and then add an update method to set up everything).
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18
2013-10-08T00:11:28Z
2013-11-21T19:59:05Z
2013-11-21T15:26:54Z
CONTRIBUTOR
null
Right now sometimes getting config options iterates over a list filtering on regular expressions, which seems like overdoing it when internal code knows exactly what it wants. Makes sense to add getitem and set item to bypass the checks (and then add an update method to set up everything). https://github.com/pydata/pandas/commit/7aa7880f#diff-1e746a348e7db9596f3d053134d00e74R515
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5,148
ENH: Cleanup backend for Offsets and Period
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88
2013-10-08T00:39:32Z
2014-10-23T17:15:44Z
2014-07-28T14:59:20Z
CONTRIBUTOR
null
This PR is a work in progress Fixes #5306 - Removing unused imports Fixes #5082 - Added `inferred_freq_offset` Fixes #5028 - fixed issues with `_offset_map` Fixes #4878 - `freq` parameter for `Period` init supports full set of Offsets. Fixes #5418 - raise `DateParseError` rather than incorrect `KeyError` for invalid frequencies
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TST: use default utf8 encoding when passing encoding to parser as Bytes (GH5141)
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0
2013-10-08T01:50:52Z
2014-07-16T08:33:38Z
2013-10-08T02:04:28Z
CONTRIBUTOR
null
closes #5141
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some of pandas.io.tests.test_html.TestReadHtml should be conditioned on presence of lxml
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7
2013-10-08T02:47:41Z
2016-10-12T23:04:16Z
2013-10-08T03:41:58Z
CONTRIBUTOR
null
Testing on my local armel box (heh -- bringing now my own media box into the game): it seems to avoid #4473 but whines about ``` ====================================================================== ERROR: test_parse_dates_combine (pandas.io.tests.test_html.TestReadHtml) ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/yoh/deb/gits/pkg-exppsy/pandas/pandas/io/tests/test_html.py", line 580, in test_parse_dates_combine index_col=1) File "/home/yoh/deb/gits/pkg-exppsy/pandas/pandas/io/html.py", line 840, in read_html parse_dates, tupleize_cols, thousands, attrs) File "/home/yoh/deb/gits/pkg-exppsy/pandas/pandas/io/html.py", line 698, in _parse parser = _parser_dispatch(flav) File "/home/yoh/deb/gits/pkg-exppsy/pandas/pandas/io/html.py", line 657, in _parser_dispatch raise ImportError("lxml not found please install it") ImportError: lxml not found please install it ====================================================================== ERROR: test_parse_dates_list (pandas.io.tests.test_html.TestReadHtml) ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/yoh/deb/gits/pkg-exppsy/pandas/pandas/io/tests/test_html.py", line 572, in test_parse_dates_list res = read_html(expected, parse_dates=[0], index_col=0) File "/home/yoh/deb/gits/pkg-exppsy/pandas/pandas/io/html.py", line 840, in read_html parse_dates, tupleize_cols, thousands, attrs) File "/home/yoh/deb/gits/pkg-exppsy/pandas/pandas/io/html.py", line 698, in _parse parser = _parser_dispatch(flav) File "/home/yoh/deb/gits/pkg-exppsy/pandas/pandas/io/html.py", line 657, in _parser_dispatch raise ImportError("lxml not found please install it") ImportError: lxml not found please install it ```
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MDExOlB1bGxSZXF1ZXN0ODkwNTE1NQ==
5,151
TST/CI/BUG: fix borked call to read_html testing code
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0
2013-10-08T03:12:45Z
2014-06-27T22:14:09Z
2013-10-08T03:41:58Z
MEMBER
null
closes #5150.
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MDU6SXNzdWUyMDY1MzQwNA==
5,152
BUG: Passing ambiguous ndarray[datetime64[ns]] to DatetimeIndex constructor can cause ValueError with wrong offset
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2013-10-08T03:50:50Z
2016-12-11T14:06:54Z
2016-12-11T14:06:54Z
CONTRIBUTOR
null
if you give infer_freq 5 consecutive weekdays, it'll come back with 'D' as its inferred frequency. But if your actual frequency is `BDay`, then, when DatetimeIndex checks that the frequency matches, 'B' != 'D'. (note that verify_integrity=False skips this). This leads to a more general issue about `infer_freq` with ambiguous cases. I think it makes the most sense to move these sorts of checks to a method on offset that takes a frequence and an Index or ndarray, and determines whether it is compatible. This matters because you can hit some edge cases when you pass freq and also datetime64[ns] to the DatetimeIndex constructor and more generally because comparing freqstr is probably not the best way to go about checking whether a frequency matches. Default implementation could be: ``` python def is_compatible(freqstr, arr=None): return freqstr == self.freqstr ``` and then bday could do something like (and this is totally psuedocode) ``` python def is_compatible(freqstr, arr=None): if freqstr == self.freqstr: return True if arr is not None and len(arr) <= 5: if freqstr == 'D': # or other compatibles that ensure it's consecutive return all(is_weekday(date) for date in arr) ``` This gets more complicated with multiplied offsets, but I think it's worth considering. ``` python from datetime import datetime import pandas as pd dates = [datetime(2013, 10, 7), datetime(2013, 10, 8), datetime(2013, 10, 9)] ind = pd.DatetimeIndex(dates, freq=pd.tseries.frequencies.BDay()) ind2 = pd.DatetimeIndex(ind.values, freq=pd.tseries.frequencies.BDay(), verify_integrity=False) ind3 = pd.DatetimeIndex(ind.values, freq=pd.tseries.frequencies.BDay()) ``` produces this Traceback: ``` Traceback (most recent call last): File "test2.py", line 8, in <module> ind3 = pd.DatetimeIndex(ind.values, freq=pd.tseries.frequencies.BDay()) File "../pandas/tseries/index.py", line 280, in __new__ raise ValueError('Dates do not conform to passed ' ValueError: Dates do not conform to passed frequency ``` cc @cancan101 - this is what we need to deal with in adding your offsets. I believe that every other offset can be returned from infer_freq, so these offsets would be different and therefore could _never_ pass integrity checks. So either we'd need to change infer_freq and/or define some kind of is_compatible method that intelligently covers all the ways in which the frequency could be something different than its freqstr.
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20,653,640
MDU6SXNzdWUyMDY1MzY0MA==
5,153
Document the "default NaN values" in Parser
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4
2013-10-08T04:01:18Z
2016-08-22T20:44:51Z
2016-08-22T13:10:34Z
CONTRIBUTOR
null
For example from docs (http://pandas.pydata.org/pandas-docs/stable/generated/pandas.io.parsers.read_csv.html): ``` keep_default_na : bool, default True If na_values are specified and keep_default_na is False the default NaN values are overridden, otherwise they’re appended to ``` But it is not clear what those default values are.
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5,154
PERF: remove auto-boxing on isnull/notnull
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4
2013-10-08T13:04:26Z
2014-07-16T08:33:41Z
2013-10-08T13:14:12Z
CONTRIBUTOR
null
- API/CLN: provide isnull/notnull on NDFrame objects - PERF: remove auto-boxing on isnull/notnull related #5135
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20,679,858
MDU6SXNzdWUyMDY3OTg1OA==
5,155
PERF: fastpath on Period construction from PeriodIndex
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11
2013-10-08T13:50:21Z
2014-08-07T11:34:54Z
2014-08-07T11:34:54Z
CONTRIBUTOR
null
vbench already in timeseries/period_setitem very inefficient because on the boxing of the PeriodIndex (to an object index), it recomputes the freq for each Period (even though it is passed), need a fastpath on this type of construction ``` In [1]: rng = period_range('1/1/1990', freq='S', periods=20000) In [2]: df = DataFrame(index=range(len(rng))) In [3]: def f(): ...: df['col'] = rng ...: Ordered by: internal time ncalls tottime percall cumtime percall filename:lineno(function) 40000 0.055 0.000 0.095 0.000 abc.py:128(__instancecheck__) 20000 0.043 0.000 0.345 0.000 period.py:66(__init__) 20000 0.037 0.000 0.381 0.000 period.py:683(<lambda>) 80031 0.037 0.000 0.131 0.000 {isinstance} 20000 0.034 0.000 0.223 0.000 frequencies.py:76(get_freq_code) 60003 0.029 0.000 0.029 0.000 _weakrefset.py:68(__contains__) 20000 0.028 0.000 0.063 0.000 frequencies.py:464(_base_and_stride) 20000 0.028 0.000 0.028 0.000 {method 'match' of '_sre.SRE_Pattern' objects} 20000 0.027 0.000 0.038 0.000 frequencies.py:767(_period_str_to_code) 40000 0.023 0.000 0.144 0.000 common.py:1730(is_integer) 1 0.016 0.016 0.398 0.398 {pandas.lib.map_infer} 40007 0.010 0.000 0.010 0.000 {getattr} 20000 0.009 0.000 0.012 0.000 frequencies.py:112(_get_freq_str) 60000 0.008 0.000 0.008 0.000 {method 'get' of 'dict' objects} 40000 0.006 0.000 0.006 0.000 {method 'group' of '_sre.SRE_Match' objects} 20000 0.004 0.000 0.004 0.000 {method 'lower' of 'str' objects} 20000 0.002 0.000 0.002 0.000 {method 'upper' of 'str' objects} 20015 0.002 0.000 0.002 0.000 {len} ```
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20,680,486
MDU6SXNzdWUyMDY4MDQ4Ng==
5,156
BUG: read_csv with bad file coreing
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6
2013-10-08T14:00:04Z
2013-11-02T05:32:30Z
2013-10-19T21:13:49Z
CONTRIBUTOR
null
from ML: https://groups.google.com/forum/#!topic/pydata/KO-PmQdBUZI ``` In [1]: data = """c1\ntext11,text12\ntext21,text22""" In [2]: read_csv(StringIO(data)) Out[2]: c1 text11 text12 text21 text22 In [3]: read_csv(StringIO(data),header=0,names=list('abc')) Bus error (core dumped) ```
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20,681,593
MDExOlB1bGxSZXF1ZXN0ODkxODY3Mw==
5,157
BUG: Fix to_datetime() uncaught error with unparseable inputs #4928
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0
2013-10-08T14:17:38Z
2014-06-17T13:24:48Z
2013-10-08T14:30:56Z
CONTRIBUTOR
null
closes #4928
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DOC: Added filtering example to groupby doc
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2
2013-10-08T14:30:31Z
2013-10-08T14:51:18Z
2013-10-08T14:51:04Z
NONE
null
closes https://github.com/pydata/pandas/issues/4630
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20,692,529
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5,159
API/PERF: restore auto-boxing on isnull/notnull for Series (w/o copy) preserves perf gains
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0
2013-10-08T17:05:16Z
2014-07-16T08:33:46Z
2013-10-08T17:26:45Z
CONTRIBUTOR
null
restore API before #5154 boxing via null/isnull is same as 0.12 (aside from now `isnull/notnull` are now available on `NDFrame` objs as well)
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5,160
DOC: add DataFrame et al class docstring to api docs
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18
2013-10-08T20:54:57Z
2014-06-18T10:12:24Z
2013-10-14T18:18:38Z
MEMBER
null
closes #4790 I copied the approach of numpy: extending the autosummary class template to automatically generate all method stub files: - https://github.com/numpy/numpy/blob/master/doc/source/_templates/autosummary/class.rst - example output: http://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html I added `DataFrame`, `Series`, `Panel`, `Index` and `DatetimeIndex`. Others? (eg `Timestamp`) Or too much? The only issue at the moment is that normally also a list of attributes should be included, which is not the case (only a list of methods)
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several bugs and/or unexpected behavior cases (pandas v. 0.12.0)
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5
2013-10-08T21:40:29Z
2013-11-01T12:50:07Z
2013-10-15T13:14:48Z
NONE
null
``` import numpy as np import pandas as pd from pandas import Series, DataFrame from pandas.tseries import offsets ``` ``` # bug 1: the dtype of "id" changes from int to float, why? df1 = DataFrame([[1, 10.0], [2, 20.0]], columns=['id', 'value']) df2 = DataFrame([[2, -20.0], [3, -30.0]], columns=['id', 'value']) df = pd.merge(df1, df2, on='id', how='outer', suffixes=['_a', '_b']) print df1.dtypes print df2.dtypes print df.dtypes # watch dtype of column "id" print ``` ``` # bug 2: MultiIndex is int32 instead of being int64 df1 = DataFrame([0,1], index=[2*[2L**32-1], ['1','2']], columns=['value']) print df1.unstack(level=0) # OK df2 = DataFrame([0,1], index=[2*[2L**32], ['1','2']], columns=['value']) print df2.unstack(level=0) # FAILS df3 = DataFrame([0,1], index=[2*[str(2L**32)], ['1','2']], columns=['value']) print df3.unstack(level=0) # OK ``` ``` # bug 3: inconsistent result for application of pd.tseries.offsets.MonthEnd() t1_start = pd.Timestamp('02/01/2000') t1_end = pd.Timestamp(t1_start+pd.tseries.offsets.MonthEnd()) # t1_end is the end of February t2_start = pd.date_range('2000-02-01', '2000-03-01', freq='6M') t2_end = t2_start+pd.tseries.offsets.MonthEnd() # t2_end is the end of March, why? print ``` ``` # bug 4: unexpected behaviour for "group by" data = DataFrame(\ {'A': [1,1,1,1,1, 2,2,2, 3 ], 'B': ['a',np.NaN,'b',np.NaN,'c', np.NaN,np.NaN,np.NaN, 'd'], 'C': [np.NaN,np.NaN,10,np.NaN,np.NaN, np.NaN,np.NaN,np.NaN, 30], 'D': [-1,np.NaN,np.NaN,np.NaN,-1, np.NaN,np.NaN,np.NaN, -3]}) data_1 = data.copy() data_2 = data.copy() grouped = data_1[['B','C']].groupby(data_1['A']) data_1[['B','C']] = grouped.fillna(method='ffill') data_1[['B','C']] = grouped.fillna(method='bfill') grouped = data_2[['B','C']].groupby(data_2['A']) data_2[['B','C']] = grouped.fillna(method='ffill') grouped = data_2[['B','C']].groupby(data_2['A']) data_2[['B','C']] = grouped.fillna(method='bfill') # data_1 and data_2 differ, why? maybe I missunderstand something here? ```
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DataFrame.copy(True) does not copy index properly
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2013-10-09T11:52:42Z
2013-10-10T16:36:41Z
2013-10-09T12:00:09Z
CONTRIBUTOR
null
It seemed that after DataFrame.copy(deep=True) does not copy the data of index but keeps the reference to it. version: pandas-0.12.0 For example: ``` df1 = pd.DataFrame({'data':0}, index=pd.date_range('2001-01-01','2001-01-05')) df1 = df1.tz_localize('UTC') print 'DF1 initial' print df1 df2 = df1.copy() df2.index.tz = 'US/Eastern' print 'DF2' print df2 print 'DF1 was also updated' print df1 ``` results in: ``` DF1 initial data 2001-01-01 00:00:00+00:00 0 2001-01-02 00:00:00+00:00 0 2001-01-03 00:00:00+00:00 0 2001-01-04 00:00:00+00:00 0 2001-01-05 00:00:00+00:00 0 DF2 data 2000-12-31 19:00:00-05:00 0 2001-01-01 19:00:00-05:00 0 2001-01-02 19:00:00-05:00 0 2001-01-03 19:00:00-05:00 0 2001-01-04 19:00:00-05:00 0 DF1 was also updated data 2000-12-31 19:00:00-05:00 0 2001-01-01 19:00:00-05:00 0 2001-01-02 19:00:00-05:00 0 2001-01-03 19:00:00-05:00 0 2001-01-04 19:00:00-05:00 0 ``` This particular example, indeed, has a simple workaround in the way how timezone should be converted: ``` df2 = df2.tz_convert('US/Eastern') ```
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5,163
ER: empty frame assignment to frame results in unclear error message
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0
2013-10-09T12:22:46Z
2020-04-27T02:52:26Z
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CONTRIBUTOR
null
http://stackoverflow.com/questions/19267029/why-pandas-transform-fails-if-you-only-have-a-single-column/19271841#19271841 Even though this is a correct error message, when it comes out of a groupby assignment via transform its 'unclear'. (as the assignment when the rhs has a single-column 'works') ``` In [48]: df = DataFrame(index=range(3)) In [49]: df Out[49]: Empty DataFrame Columns: [] Index: [0, 1, 2] In [50]: df['foo'] = DataFrame(index=range(3)) --------------------------------------------------------------------------- ValueError: Wrong number of items passed 1, indices imply 0 ```
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ENH: add to_frame method to Series
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2013-10-09T20:02:07Z
2014-06-13T06:38:18Z
2013-10-10T13:00:50Z
CONTRIBUTOR
null
Adding a method to Series to promote it to a DataFrame. I've wished this existed so that when a method returns a series, and you could easily promote it to a DataFrame so that it's easier to add columns to it.
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DOC: Fix name in interpolate plot.
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describe() shows wrong dtype
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Pandas version: 0.12.0. Usecase / how to reproduce: In ipython, type: In [1]: x = pd.Series([1, 2]) In [2]: print x.dtype Out[2]: dtype('int64') In [3]: x.describe() Out[3]: count 2.000000 mean 1.500000 std 0.707107 min 1.000000 25% 1.250000 50% 1.500000 75% 1.750000 max 2.000000 dtype: float64 <----------------------- This is wrong
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API: add Series.info method
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ENH/DOC: call for Timestamp
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8
2013-10-10T01:24:53Z
2017-10-31T00:32:07Z
2017-10-31T00:32:07Z
CONTRIBUTOR
null
When you create a timestamp with a timezone and don't use a keyword argument, it fails silently: ``` >> pd.Timestamp('2012-01-01', 'US/Pacific') Timestamp('2012-01-01 00:00:00', tz=None) ```
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DOC/CLN: A few fixes and cleanup for doc warnings/errors
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1
2013-10-10T02:21:30Z
2014-07-16T08:33:51Z
2013-10-11T20:56:30Z
MEMBER
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closes #5126.
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RVT: revert 4912 change of 4030 nose import bug
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2013-10-10T04:37:53Z
2014-07-16T08:33:53Z
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pd.HDFStore.select errors out when query contains a single quote
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2013-10-10T14:36:30Z
2013-10-15T14:42:46Z
2013-10-15T13:14:33Z
NONE
null
replacing single quotes with `\\'`seems to work. This is with pandas 0.11 with pd.Term, seems like pandas is moving to string queries rather than pd.Term in the future?
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NONE
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- [x] #5694 ``` df = pd.DataFrame([0], index=[datetime(2012, 11, 4, 23, 0, 0)]) df = df.tz_localize('America/New_York') df.resample(rule='D', how='sum') ``` raises a AmbiguousTimeError even though datetime(2012, 11, 4, 23, 0, 0) is not ambiguous. - [x] #8601 ``` idx = date_range('2014-10-08 00:00','2014-10-09 00:00', freq='D', tz='Europe/Berlin') pd.Series(5, idx).resample('MS') ``` - [ ] #8744 ``` index = pd.to_datetime(pd.Series([ '2014-10-26 07:35:49', '2014-10-26 07:45:08', '2014-10-26 08:04:58' ])) df = pd.DataFrame(np.arange(len(index)), index=index) df = df.tz_localize('Asia/Krasnoyarsk', ambiguous='NaT') df.resample('D') AmbiguousTimeError: Cannot infer dst time from Timestamp('2014-10-26 01:00:00'), try using the 'ambiguous' argument ``` - [x] #8653 (might be separate issue) ``` import datetime import pytz as tz import pandas as pd rome = tz.timezone('Europe/Rome') dr = [] for i in range(2): dp = datetime.datetime(2014, 10, 25) + datetime.timedelta(days=i) dr.append(rome.localize(dp)) series = {} for i, ddr in enumerate(dr): series[ddr] = i * 10 s1 = pd.Series(series) s1 = s1.resample('D', how='mean') ``` - [x] #9119 - [ ] #9173 - [x] #9468
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BUG: Creating pivot with margins crashes
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1
2013-10-10T16:33:06Z
2014-04-09T12:19:40Z
2014-04-09T12:19:40Z
NONE
null
I'm trying to create simple pivot ``` python import pandas as pd import numpy import datetime s1 = pd.Series([datetime.datetime.now() - datetime.timedelta(days=i) for i in range(5)]) s2 = pd.Series(['a1', 'a1', 'a2', 'a2', 'a3']) s3 = pd.Series([i for i in range(5)]) frame = pd.DataFrame({'s1': s1, 's2': s1, 's3': s3}) pivot = pd.pivot_table(frame, rows='s2', cols='s1', values='s3', margins=True) ``` It happens if I set "margins=True" and cols for pivot is datetime. ``` Traceback (most recent call last): File "./aa.py", line 12, in <module> p = pd.pivot_table(b, rows='s2', cols='s1', values='s3', margins=True) File "/usr/local/lib/python2.6/dist-packages/pandas/tools/pivot.py", line 135, in pivot_table cols=cols, aggfunc=aggfunc) File "/usr/local/lib/python2.6/dist-packages/pandas/tools/pivot.py", line 174, in _add_margins piece[all_key] = margin[key] File "/usr/local/lib/python2.6/dist-packages/pandas/core/frame.py", line 2119, in __setitem__ self._set_item(key, value) File "/usr/local/lib/python2.6/dist-packages/pandas/core/frame.py", line 2166, in _set_item NDFrame._set_item(self, key, value) File "/usr/local/lib/python2.6/dist-packages/pandas/core/generic.py", line 679, in _set_item self._data.set(key, value) File "/usr/local/lib/python2.6/dist-packages/pandas/core/internals.py", line 1781, in set self.insert(len(self.items), item, value) File "/usr/local/lib/python2.6/dist-packages/pandas/core/internals.py", line 1801, in insert new_items = self.items.delete(loc) File "/usr/local/lib/python2.6/dist-packages/pandas/core/index.py", line 2610, in delete new_labels = [np.delete(lab, loc) for lab in self.labels] File "/usr/local/lib/python2.6/dist-packages/numpy/lib/function_base.py", line 3456, in delete "invalid entry") ValueError: invalid entry ```
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5,174
Failing interpolation test
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42
2013-10-10T16:49:41Z
2013-10-28T22:58:08Z
2013-10-28T19:52:51Z
MEMBER
null
``` $ nosetests pandas/tests/test_generic.py:TestSeries.test_interp_quad F ====================================================================== FAIL: test_interp_quad (pandas.tests.test_generic.TestSeries) ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/phillip/Documents/code/py/pandas/pandas/tests/test_generic.py", line 339, in test_interp_quad assert_series_equal(result, expected) File "/home/phillip/Documents/code/py/pandas/pandas/util/testing.py", line 452, in assert_series_equal assert_attr_equal('dtype', left, right) File "/home/phillip/Documents/code/py/pandas/pandas/util/testing.py", line 369, in assert_attr_equal assert_equal(left_attr,right_attr,"attr is not equal [{0}]" .format(attr)) File "/home/phillip/Documents/code/py/pandas/pandas/util/testing.py", line 354, in assert_equal assert a == b, "%s: %r != %r" % (msg.format(a,b), a, b) AssertionError: attr is not equal [dtype]: dtype('int64') != dtype('float64') ---------------------------------------------------------------------- Ran 1 test in 0.041s FAILED (failures=1) ```
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5,175
BUG: DateOffset weekday around DST produces unexpected results
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35
2013-10-10T17:03:01Z
2014-09-04T22:18:50Z
2014-09-04T22:18:50Z
CONTRIBUTOR
null
I want next Monday: ``` def next_week_start(t): return t + pd.DateOffset(weekday=0) ``` But for DST (fall back is Sunday 2013-11-03): ``` >> next_week_start(pd.Timestamp("2013-10-30", tz="US/Pacific")) Timestamp('2013-11-03 23:00:00-0800', tz='US/Pacific') ``` which is Sunday at 11pm, not Monday.
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20,821,509
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5,176
pivot_table with margins=True fails
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2013-10-10T17:14:06Z
2013-10-15T14:41:15Z
2013-10-15T14:40:55Z
NONE
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Coming from http://stackoverflow.com/q/19300730/624829 <pre> import pandas as pd values = pd.Series(i for i in range(5)) rows = pd.Series(['a', 'b', 'a', 'a', 'b']) columns = pd.date_range('20130101',periods=5) df = pd.DataFrame({'values': values, 'rows': rows, 'columns': columns}) pivot = pd.pivot_table( data=df, rows='rows', cols='columns', values='values', margins=True ) </pre> This call fails down to that traceback: <pre> Traceback (most recent call last): File "./test.py", line 17, in <module> margins=True File "/usr/local/lib/python2.6/dist-packages/pandas/tools/pivot.py", line 135, in pivot_table cols=cols, aggfunc=aggfunc) File "/usr/local/lib/python2.6/dist-packages/pandas/tools/pivot.py", line 174, in _add_margins piece[all_key] = margin[key] File "/usr/local/lib/python2.6/dist-packages/pandas/core/frame.py", line 2119, in __setitem__ self._set_item(key, value) File "/usr/local/lib/python2.6/dist-packages/pandas/core/frame.py", line 2166, in _set_item NDFrame._set_item(self, key, value) File "/usr/local/lib/python2.6/dist-packages/pandas/core/generic.py", line 679, in _set_item self._data.set(key, value) File "/usr/local/lib/python2.6/dist-packages/pandas/core/internals.py", line 1781, in set self.insert(len(self.items), item, value) File "/usr/local/lib/python2.6/dist-packages/pandas/core/internals.py", line 1801, in insert new_items = self.items.delete(loc) File "/usr/local/lib/python2.6/dist-packages/pandas/core/index.py", line 2610, in delete new_labels = [np.delete(lab, loc) for lab in self.labels] File "/usr/lib/pymodules/python2.6/numpy/lib/function_base.py", line 3339, in delete "invalid entry") ValueError: invalid entry </pre> Resetting the columns attribute on the df before workarounds the issue: <pre> df.columns = ['rows', 'columns', 'values'] </pre>
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API: make allclose comparison on dtype downcasting (GH5174)
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0
2013-10-10T18:45:36Z
2014-07-16T08:33:56Z
2013-10-10T19:54:28Z
CONTRIBUTOR
null
TST: update interpolate tests to account for correct dtype inferernce closes #5174
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MDExOlB1bGxSZXF1ZXN0OTAwNzI2MA==
5,178
PERF: calling get_indexer twice when a specialized indexer (e.g. pad) could be called instead
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0
2013-10-10T21:51:56Z
2014-07-16T08:33:58Z
2013-10-10T22:17:34Z
CONTRIBUTOR
null
better on reindexing ``` Invoked with : --ncalls: 3 --repeats: 3 ------------------------------------------------------------------------------- Test name | head[ms] | base[ms] | ratio | ------------------------------------------------------------------------------- frame_reindex_upcast | 12.3383 | 12.7693 | 0.9662 | frame_reindex_both_axes | 36.2797 | 36.2826 | 0.9999 | frame_reindex_both_axes_ix | 34.7884 | 34.7476 | 1.0012 | frame_reindex_axis1 | 555.0433 | 553.5540 | 1.0027 | frame_reindex_axis0 | 87.8770 | 82.8171 | 1.0611 | reindex_fillna_pad | 0.6303 | 0.5744 | 1.0974 | reindex_frame_level_align | 0.6430 | 0.5836 | 1.1017 | reindex_fillna_backfill | 0.6286 | 0.5697 | 1.1035 | reindex_frame_level_reindex | 0.5973 | 0.5407 | 1.1048 | reindex_fillna_pad_float32 | 0.5320 | 0.4800 | 1.1083 | reindex_fillna_backfill_float32 | 0.5307 | 0.4773 | 1.1119 | dataframe_reindex | 0.4213 | 0.3650 | 1.1541 | frame_reindex_columns | 0.3730 | 0.3120 | 1.1954 | reindex_multiindex | 1.4537 | 1.1006 | 1.3208 | reindex_daterange_pad | 1.2333 | 0.6417 | 1.9221 | reindex_daterange_backfill | 1.2383 | 0.6430 | 1.9258 | ------------------------------------------------------------------------------- Test name | head[ms] | base[ms] | ratio | ------------------------------------------------------------------------------- Ratio < 1.0 means the target commit is faster then the baseline. Seed used: 1234 Target [661adc5] : PERF: calling get_indexer twice when a specialized indexer (e.g. pad) could be called instead Base [8c0a34f] : RLS: set released to True, edit release dates ```
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20,839,515
MDExOlB1bGxSZXF1ZXN0OTAwODE2MA==
5,179
GBQ: Updated Documentation, and added method to generic.py
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9
2013-10-10T22:20:22Z
2014-06-23T01:43:05Z
2013-10-15T00:57:42Z
CONTRIBUTOR
null
Added some documentation for GBQ module
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20,865,102
MDExOlB1bGxSZXF1ZXN0OTAyMjM3Mw==
5,180
TST: addtl pytables tests
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0
2013-10-11T12:14:26Z
2014-07-16T08:34:03Z
2013-10-11T12:26:22Z
CONTRIBUTOR
null
related #5045
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20,871,256
MDExOlB1bGxSZXF1ZXN0OTAyNTc3Mw==
5,181
fix replacement key for deprecated option `display.height`
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2
2013-10-11T14:19:03Z
2014-07-16T08:34:04Z
2013-10-14T01:53:38Z
CONTRIBUTOR
null
replacement key for deprecated option `display.height` was set to `display.height` itself. I believe it should be `display.max_rows` instead. This avoid a weird message in `describe_option()` : ``` display.height: [default: 60] [currently: 60] : int Deprecated. (Deprecated, use `display.height` instead.) ``` (I spotted it while reading the online doc http://pandas.pydata.org/pandas-docs/dev/basics.html?highlight=display.height#working-with-package-options )
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MDU6SXNzdWUyMDg3NDc2OQ==
5,182
KeyError: 'trait_names' in py3k
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5
2013-10-11T15:14:39Z
2013-10-14T21:51:32Z
2013-10-12T01:29:49Z
CONTRIBUTOR
null
When tab completing in ipython notebook on `pd.options...`, nothing shows up, and on the backend (in iterm) I see a `KeyError: 'trait_names'`, with a longer traceback. pd.version.version == '0.12.0' python version == 3.3.2 IPython.version_info == (2, 0, 0, 'dev') Pandas is latest from pip, and ipython is latest from git. It may be an IPython problem. Traceback [here](https://gist.github.com/d10genes/6936334).
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ENH: NDFrame.equals
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10
2013-10-11T16:26:28Z
2014-01-24T21:43:37Z
2014-01-24T21:43:37Z
CONTRIBUTOR
null
seems we need a public version of `tm.assert_frame_equal` maybe `equals` on generic NDFrame objects http://stackoverflow.com/questions/19322506/pandas-nan-comparison seems good on the values comparison (should compare axes/types as well of course) ``` ((df1 == df2) | ((df != df) & (df2 != df2))).values.all() ```
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API: parakeet backend for eval
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3
2013-10-11T18:08:44Z
2017-06-09T20:36:06Z
2017-06-09T20:35:59Z
CONTRIBUTOR
null
this might be interesting as it allows jit optimizations but w/o major deps (like blaze/numba). could be useful as a back end for eval potentially could be used in apply as well http://www.parakeetpython.com/ http://www.phi-node.com/2013/01/just-in-time-compilers-for-number.html
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BUG: Formerly useful behavior now raises.
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3
2013-10-11T22:41:54Z
2013-10-13T15:06:00Z
2013-10-12T13:54:10Z
CONTRIBUTOR
null
I did this: In [1]: df1 = DataFrame([1, 2, 3, 4, 5], index=[1, 2, 1, 2, 3]) In [2]: df2 = DataFrame([1, 2, 3], index=[1, 2, 3]) In [3]: df1.sub(df2) Out[3]: 0 1 0 1 2 2 0 2 2 3 2 which is possible up to and including [this commit](https://github.com/jreback/pandas/commit/725b1951249a795fe01896dff4ce46bd9206021f). Then, [this "bug fix"](https://github.com/jreback/pandas/commit/3f76205f1d4a42ba971ff5be8770b52172b9f822#diff-0) seems to have broken the above usage. It now raises like so: ``` ValueError Traceback (most recent call last) <ipython-input-12-e7e549a4e818> in <module>() ----> 1 df1.sub(df2) /Users/danielallan/Documents/Repos/pandas-danielballan/pandas/core/ops.pyc in f(self, other, axis, level, fill_value) 710 def f(self, other, axis=default_axis, level=None, fill_value=None): 711 if isinstance(other, pd.DataFrame): # Another DataFrame --> 712 return self._combine_frame(other, na_op, fill_value, level) 713 elif isinstance(other, pd.Series): 714 return self._combine_series(other, na_op, fill_value, axis, level) /Users/danielallan/Documents/Repos/pandas-danielballan/pandas/core/frame.pyc in _combine_frame(self, other, func, fill_value, level) 2759 2760 def _combine_frame(self, other, func, fill_value=None, level=None): -> 2761 this, other = self.align(other, join='outer', level=level, copy=False) 2762 new_index, new_columns = this.index, this.columns 2763 /Users/danielallan/Documents/Repos/pandas-danielballan/pandas/core/generic.pyc in align(self, other, join, axis, level, copy, fill_value, method, limit, fill_axis) 2331 copy=copy, fill_value=fill_value, 2332 method=method, limit=limit, -> 2333 fill_axis=fill_axis) 2334 elif isinstance(other, Series): 2335 return self._align_series(other, join=join, axis=axis, level=level, /Users/danielallan/Documents/Repos/pandas-danielballan/pandas/core/generic.pyc in _align_frame(self, other, join, axis, level, copy, fill_value, method, limit, fill_axis) 2362 left = self._reindex_with_indexers({0: [join_index, ilidx], 2363 1: [join_columns, clidx]}, -> 2364 copy=copy, fill_value=fill_value) 2365 right = other._reindex_with_indexers({0: [join_index, iridx], 2366 1: [join_columns, cridx]}, /Users/danielallan/Documents/Repos/pandas-danielballan/pandas/core/generic.pyc in _reindex_with_indexers(self, reindexers, method, fill_value, limit, copy, allow_dups) 1320 indexer = com._ensure_int64(indexer) 1321 new_data = new_data.reindex_indexer(index, indexer, axis=baxis, -> 1322 fill_value=fill_value, allow_dups=allow_dups) 1323 1324 elif baxis == 0 and index is not None and index is not new_data.axes[baxis]: /Users/danielallan/Documents/Repos/pandas-danielballan/pandas/core/internals.pyc in reindex_indexer(self, new_axis, indexer, axis, fill_value, allow_dups) 2884 # trying to reindex on an axis with duplicates 2885 if not allow_dups and not self.axes[axis].is_unique: -> 2886 raise ValueError("cannot reindex from a duplicate axis") 2887 2888 if axis == 0: ValueError: cannot reindex from a duplicate axis ``` I found this very handy. Should it really raise? Can you suggest what I should be doing instead? Thanks.
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5,186
pandas.options should raise an AttributeError subclass
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0
2013-10-11T23:06:47Z
2013-10-12T01:29:49Z
2013-10-12T01:29:49Z
CONTRIBUTOR
null
`hasattr` expects `AttributeError` when looking up. Let's make it simple and backward compatible, replace `KeyError` with this class: ``` python class OptionNotFound(AttributeError, KeyError): """Exception for pandas.options, backwards compatible with KeyError checks""" ``` cc @d10genes this should fix your problem. simple example: ``` python In [5]: class OptionNotFoundError(AttributeError, KeyError): pass In [6]: class MyObject(self): ...: KeyboardInterrupt In [6]: class MyObject(object): ...: @property ...: def prop(self): ...: raise OptionNotFoundError("HEYO!") ...: In [7]: a = MyObject() In [8]: hasattr(a, "prop") Out[8]: False In [9]: OptionNotFoundError = KeyError In [10]: class MyObject(object): @property def prop(self): raise OptionNotFoundError("HEYO!") ....: In [11]: a = MyObject() In [12]: hasattr(a, "prop") --------------------------------------------------------------------------- KeyError Traceback (most recent call last) <ipython-input-12-7205b5401c9b> in <module>() ----> 1 hasattr(a, "prop") <ipython-input-10-7a717a2e41df> in prop(self) 2 @property 3 def prop(self): ----> 4 raise OptionNotFoundError("HEYO!") 5 KeyError: 'HEYO!' In [13]: ```
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20,899,938
MDExOlB1bGxSZXF1ZXN0OTA0MjE5Mg==
5,187
BUG: Allow duplicate indices when performing operations that align (GH5185)
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0
2013-10-11T23:10:20Z
2014-06-14T18:00:07Z
2013-10-12T13:54:10Z
CONTRIBUTOR
null
closes #5185 ``` In [1]: df1 = DataFrame([1, 2, 3, 4, 5], index=[1, 2, 1, 2, 3]) In [2]: df2 = DataFrame([1, 2, 3], index=[1, 2, 3]) In [3]: df1-df2 Out[3]: 0 1 0 1 2 2 0 2 2 3 2 In [4]: df1.sub(df2) Out[4]: 0 1 0 1 2 2 0 2 2 3 2 ```
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20,900,025
MDExOlB1bGxSZXF1ZXN0OTA0MjI0Ng==
5,188
CLN/BUG/ENH: Raise AttributeError with pd.options
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5
2013-10-11T23:13:23Z
2014-07-16T08:34:07Z
2013-10-12T01:29:49Z
CONTRIBUTOR
null
Fixes #5182, closes #5186. It's called OptionError now and it subclasses both AttributeError (for hasattr) and KeyError (for backwards compatibility). Hurray!
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20,905,237
MDExOlB1bGxSZXF1ZXN0OTA0NTEwOQ==
5,189
CLN/ENH: Stop instantiating all offsets on load.
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36
2013-10-12T04:28:45Z
2014-06-12T14:25:30Z
2013-10-15T00:58:56Z
CONTRIBUTOR
null
Implements @wesm's suggestion and clears the way for new offsets. Very simple to extend - map a string to your class in mapping, define a `from_name` classmethod, then class gets passed everything after the `-` (if anything) to its method `from_name()`. Caches to dict afterwards (right now doesn't use cacheable, but could take advantage of that). cc @cancan101 For reference, here are all the existing offset: output aliases (using types because otherwise prints exactly the same). [(None, NoneType), ('A-APR', pandas.tseries.offsets.YearEnd), ('A-AUG', pandas.tseries.offsets.YearEnd), ('A-DEC', pandas.tseries.offsets.YearEnd), ('A-FEB', pandas.tseries.offsets.YearEnd), ('A-JAN', pandas.tseries.offsets.YearEnd), ('A-JUL', pandas.tseries.offsets.YearEnd), ('A-JUN', pandas.tseries.offsets.YearEnd), ('A-MAR', pandas.tseries.offsets.YearEnd), ('A-MAY', pandas.tseries.offsets.YearEnd), ('A-NOV', pandas.tseries.offsets.YearEnd), ('A-OCT', pandas.tseries.offsets.YearEnd), ('A-SEP', pandas.tseries.offsets.YearEnd), ('AS-APR', pandas.tseries.offsets.YearBegin), ('AS-AUG', pandas.tseries.offsets.YearBegin), ('AS-DEC', pandas.tseries.offsets.YearBegin), ('AS-FEB', pandas.tseries.offsets.YearBegin), ('AS-JAN', pandas.tseries.offsets.YearBegin), ('AS-JUL', pandas.tseries.offsets.YearBegin), ('AS-JUN', pandas.tseries.offsets.YearBegin), ('AS-MAR', pandas.tseries.offsets.YearBegin), ('AS-MAY', pandas.tseries.offsets.YearBegin), ('AS-NOV', pandas.tseries.offsets.YearBegin), ('AS-OCT', pandas.tseries.offsets.YearBegin), ('AS-SEP', pandas.tseries.offsets.YearBegin), ('B', pandas.tseries.offsets.BusinessDay), ('BA-APR', pandas.tseries.offsets.BYearEnd), ('BA-AUG', pandas.tseries.offsets.BYearEnd), ('BA-DEC', pandas.tseries.offsets.BYearEnd), ('BA-FEB', pandas.tseries.offsets.BYearEnd), ('BA-JAN', pandas.tseries.offsets.BYearEnd), ('BA-JUL', pandas.tseries.offsets.BYearEnd), ('BA-JUN', pandas.tseries.offsets.BYearEnd), ('BA-MAR', pandas.tseries.offsets.BYearEnd), ('BA-MAY', pandas.tseries.offsets.BYearEnd), ('BA-NOV', pandas.tseries.offsets.BYearEnd), ('BA-OCT', pandas.tseries.offsets.BYearEnd), ('BA-SEP', pandas.tseries.offsets.BYearEnd), ('BAS-APR', pandas.tseries.offsets.BYearBegin), ('BAS-AUG', pandas.tseries.offsets.BYearBegin), ('BAS-DEC', pandas.tseries.offsets.BYearBegin), ('BAS-FEB', pandas.tseries.offsets.BYearBegin), ('BAS-JAN', pandas.tseries.offsets.BYearBegin), ('BAS-JUL', pandas.tseries.offsets.BYearBegin), ('BAS-JUN', 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20,911,134
MDU6SXNzdWUyMDkxMTEzNA==
5,190
API: unify sort API
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32
2013-10-12T13:33:57Z
2014-09-11T00:49:44Z
2014-09-11T00:33:14Z
CONTRIBUTOR
null
related is #2094 related is #6847 (fixes kind and some arg ordering) related is #7121 (make `sortlevel` a part of `sort_index` by adding level arg) the sorting API is currently inconsistent and confusing. here is what exists: Series: - `sort`: calls `Series.order`, in-place, defaults `quicksort` - `order`: do the sort on values, return a new object, defaults `mergesort` - `sort_index`: sort by labels, returns new object Frame: - `sort`: calls `sort_index` - `sort_index`: sorts by the index with no args, otherwise a nested sort of the passed columns The semantics are different between `Series` and `DataFrame`. In `Series`, `sort` mean in-place, `order` returns a new object. `sort/order` sort on the values, while `sort_index` sorts on the index. For a `DataFrame`, `sort` and `sort_index` are the same and sort on a column/list of columns; `inplace` is a keyword. Proposed signature of combined methods. We need to break a `Series` API here. because `sort` is an in-place method which is quite inconsistent with everything else. ``` def sort(self, by=None, axis=0, level=None, ascending=True, inplace=False, kind='quicksort', na_last=True): ``` This is what I think we should do: - make `Series.sort/order` be the same. - by can take a column/list of columns (as it can now), or an index name / `index` to provide index sorting (which means sort by the specifiied axis) - default is `inplace=False` (which is the same as now, except for `Series.sort`). - `Series.sort_index` does `s.sort('index')` - `DataFrame.sort_index` does `df.sort('index')` - eventually deprecate `Series.order` - add `DataFrame.sort_columns` to perform axis=1 sorting This does switch the argument to the current `sort_index`, (e.g. axis is currently first), but I think then allows more natural syntax - `df.sort()` or `df.sort_index()` or `df.sort_index('index')` sort on the index labels - `df.sort(['A','B'],axis=1)` sort on these columns (allow 'index' here as well to sort on the index too) - `df.sort_columns()` or `df.sort('columns')` sort on the column labels - `df.sort_columns()` defaults `axis=1`, so `df.sort_columns(['A','B'])` is equiv of - - `df.sort(['A','B'],axis=1)` - `s.sort()` sort on the values - `s.sort('index')` or `s.sort_index()` sort on the series index
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20,913,448
MDU6SXNzdWUyMDkxMzQ0OA==
5,191
Segmentation fault when conctructing DataFrame with specified datetime dtype of one column
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3
2013-10-12T16:37:13Z
2013-10-12T17:45:28Z
2013-10-12T17:45:28Z
NONE
null
## Description When building a DataFrame with specified column names and dtypes, one might expect one of two possible behaviours: - The column names and dtypes specs are perfectly cromulent, and Pandas goes on to build the object. - The column names or dtypes don't match the data shape, or the dtypes are badly specified, and Pandas gives an error message. Instead, I have encountered a segmentation fault. Now, it is unclear to me whether my column names spec and dtypes are correctly written and if my data is proper too (see example below). But in any case, it should not crash. ## Reproducing To reproduce, please run: ``` python import pandas as pd import datetime as dt import itertools as it df_test = pd.DataFrame(data = list(it.repeat((dt.datetime(2001, 1, 1), "aa", 20), 9)), columns=["A", "B", "C"], dtype=[("A","datetime64[h]"), ("B","str"), ("C","int32")]) ``` ## Modes of failure I have found that the above script always crashes on my machine (see next section for detailed configuration information). It does it in 2 possible ways: ### First mode of failure: hanging ``` Python 2.7.5 (default, Sep 6 2013, 09:55:21) [GCC 4.8.1 20130725 (prerelease)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import pandas as pd >>> import datetime as dt >>> import itertools as it >>> >>> df_test = pd.DataFrame(data = list(it.repeat((dt.datetime(2001, 1, 1), "aa", 20), 9)), ... columns=["A", "B", "C"], ... dtype=[("A","datetime64[h]"), ("B","str"), ("C","int32")]) *** Error in `python': corrupted double-linked list: 0x0000000001bfd8e0 *** ``` After that line, the terminal is dead. ### Second mode of failure: segfault ``` Python 2.7.5 (default, Sep 6 2013, 09:55:21) [GCC 4.8.1 20130725 (prerelease)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import pandas as pd >>> import datetime as dt >>> import itertools as it >>> >>> df_test = pd.DataFrame(data = list(it.repeat((dt.datetime(2001, 1, 1), "aa", 20), 9)), ... columns=["A", "B", "C"], ... dtype=[("A","datetime64[h]"), ("B","str"), ("C","int32")]) *** Error in `python2': double free or corruption (!prev): 0x00000000027161d0 *** ======= Backtrace: ========= /usr/lib/libc.so.6(+0x72ecf)[0x7f2bd7ab9ecf] /usr/lib/libc.so.6(+0x7869e)[0x7f2bd7abf69e] /usr/lib/libc.so.6(+0x79377)[0x7f2bd7ac0377] /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/numpy/core/multiarray.so(_field_transfer_data_free+0x2e)[0x7f2bd634d47e] /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/numpy/core/multiarray.so(+0x9a1c9)[0x7f2bd63a61c9] /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/numpy/core/multiarray.so(+0xa4a3a)[0x7f2bd63b0a3a] /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/numpy/core/multiarray.so(+0xab0a1)[0x7f2bd63b70a1] /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/numpy/core/multiarray.so(+0xb838b)[0x7f2bd63c438b] /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/numpy/core/multiarray.so(+0xb8643)[0x7f2bd63c4643] /usr/lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x4c2f)[0x7f2bd80ec2ef] /usr/lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x850)[0x7f2bd80ed290] /usr/lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x4dc9)[0x7f2bd80ec489] /usr/lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x850)[0x7f2bd80ed290] /usr/lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x4dc9)[0x7f2bd80ec489] /usr/lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x850)[0x7f2bd80ed290] /usr/lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x4dc9)[0x7f2bd80ec489] /usr/lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x850)[0x7f2bd80ed290] /usr/lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x4dc9)[0x7f2bd80ec489] /usr/lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x850)[0x7f2bd80ed290] /usr/lib/libpython2.7.so.1.0(+0x6dbdd)[0x7f2bd807cbdd] /usr/lib/libpython2.7.so.1.0(PyObject_Call+0x43)[0x7f2bd8058c13] /usr/lib/libpython2.7.so.1.0(+0x5841d)[0x7f2bd806741d] /usr/lib/libpython2.7.so.1.0(PyObject_Call+0x43)[0x7f2bd8058c13] /usr/lib/libpython2.7.so.1.0(+0x9de57)[0x7f2bd80ace57] /usr/lib/libpython2.7.so.1.0(+0x9cbcf)[0x7f2bd80abbcf] /usr/lib/libpython2.7.so.1.0(PyObject_Call+0x43)[0x7f2bd8058c13] /usr/lib/libpython2.7.so.1.0(PyEval_EvalFrameEx+0x1321)[0x7f2bd80e89e1] /usr/lib/libpython2.7.so.1.0(PyEval_EvalCodeEx+0x850)[0x7f2bd80ed290] /usr/lib/libpython2.7.so.1.0(PyEval_EvalCode+0x32)[0x7f2bd80ed392] /usr/lib/libpython2.7.so.1.0(+0xf708f)[0x7f2bd810608f] /usr/lib/libpython2.7.so.1.0(PyRun_InteractiveOneFlags+0x140)[0x7f2bd8107fb0] /usr/lib/libpython2.7.so.1.0(PyRun_InteractiveLoopFlags+0x4e)[0x7f2bd810819e] /usr/lib/libpython2.7.so.1.0(PyRun_AnyFileExFlags+0x3e)[0x7f2bd81087fe] /usr/lib/libpython2.7.so.1.0(Py_Main+0xc7f)[0x7f2bd8118c2f] /usr/lib/libc.so.6(__libc_start_main+0xf5)[0x7f2bd7a68bc5] python2[0x400741] ======= Memory map: ======== 00400000-00401000 r-xp 00000000 08:11 1886483 /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/bin/python2 00600000-00601000 r--p 00000000 08:11 1886483 /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/bin/python2 00601000-00602000 rw-p 00001000 08:11 1886483 /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/bin/python2 012d1000-029b7000 rw-p 00000000 00:00 0 [heap] 7f2bced0d000-7f2bced11000 r-xp 00000000 08:01 923895 /usr/lib/python2.7/lib-dynload/termios.so 7f2bced11000-7f2bcef10000 ---p 00004000 08:01 923895 /usr/lib/python2.7/lib-dynload/termios.so 7f2bcef10000-7f2bcef11000 r--p 00003000 08:01 923895 /usr/lib/python2.7/lib-dynload/termios.so 7f2bcef11000-7f2bcef13000 rw-p 00004000 08:01 923895 /usr/lib/python2.7/lib-dynload/termios.so 7f2bcef13000-7f2bcef26000 r-xp 00000000 08:11 57747 /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/pandas/json.so 7f2bcef26000-7f2bcf125000 ---p 00013000 08:11 57747 /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/pandas/json.so 7f2bcf125000-7f2bcf126000 r--p 00012000 08:11 57747 /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/pandas/json.so 7f2bcf126000-7f2bcf127000 rw-p 00013000 08:11 57747 /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/pandas/json.so 7f2bcf127000-7f2bcf171000 r-xp 00000000 08:11 57858 /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/pandas/parser.so 7f2bcf171000-7f2bcf370000 ---p 0004a000 08:11 57858 /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/pandas/parser.so 7f2bcf370000-7f2bcf371000 r--p 00049000 08:11 57858 /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/pandas/parser.so 7f2bcf371000-7f2bcf376000 rw-p 0004a000 08:11 57858 /home/agravier/metahome/.local-common/share/python2.7/venvs/finance64/lib/python2.7/site-packages/pandas/parser.so 7f2bcf376000-7f2bcf377000 rw-p 00000000 00:00 0 7f2bcf377000-7f2bcf3d9000 r-xp 00000000 08:01 798526 /usr/lib/libssl.so.1.0.0 7f2bcf3d9000-7f2bcf5d8000 ---p 00062000 08:01 798526 /usr/lib/libssl.so.1.0.0 7f2bcf5d8000-7f2bcf5dc000 r--p 00061000 08:01 798526 /usr/lib/libssl.so.1.0.0 7f2bcf5dc000-7f2bcf5e3000 rw-p 00065000 08:01 798526 /usr/lib/libssl.so.1.0.0 7f2bcf5e3000-7f2bcf5eb000 r-xp 00000000 08:01 923889 /usr/lib/python2.7/lib-dynload/_ssl.soAborted (core dumped) ``` ## Configuration information Python: ``` Python 2.7.5 ``` uname -a: ``` Linux agravier-archvm 3.10.10-1-ARCH #1 SMP PREEMPT Fri Aug 30 11:30:06 CEST 2013 x86_64 GNU/Linux ``` pip freeze --local: ``` QSTK==0.2.6 matplotlib==1.3.0 nose==1.3.0 numpy==1.7.1 pandas==0.12.0 pyparsing==2.0.1 python-dateutil==2.1 pytz==2013.7 scikit-learn==0.14.1 scipy==0.12.1 six==1.4.1 yolk==0.4.3 ``` ## Concluding remarks Note that in the line that I use to create the data `list(it.repeat((dt.datetime(2001, 1, 1), "aa", 20), 9))`, the number of rows has an influence on whether Python crashes. If less than 9, there is the output: ``` Python 2.7.5 (default, Sep 6 2013, 09:55:21) [GCC 4.8.1 20130725 (prerelease)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import pandas as pd >>> import datetime as dt >>> import itertools as it >>> >>> df_test = pd.DataFrame(data = list(it.repeat((dt.datetime(2001, 1, 1), "aa", 20), 8)), ... columns=["A", "B", "C"], ... dtype=[("A","datetime64[h]"), ("B","str"), ("C","int32")]) >>> df_test A B C 0 2001-01-01 00:00:00 (1972-11-04 17:00:00, , 0) (1970-01-01 20:00:00, , 20) 1 2001-01-01 00:00:00 (1972-11-04 17:00:00, , 0) (1970-01-01 20:00:00, , 20) 2 2001-01-01 00:00:00 (1972-11-04 17:00:00, , 0) (1970-01-01 20:00:00, , 20) 3 2001-01-01 00:00:00 (1972-11-04 17:00:00, , 0) (1970-01-01 20:00:00, , 20) 4 2001-01-01 00:00:00 (1972-11-04 17:00:00, , 0) (1970-01-01 20:00:00, , 20) 5 2001-01-01 00:00:00 (1972-11-04 17:00:00, , 0) (1970-01-01 20:00:00, , 20) 6 2001-01-01 00:00:00 (1972-11-04 17:00:00, , 0) (1970-01-01 20:00:00, , 20) 7 2001-01-01 00:00:00 (1972-11-04 17:00:00, , 0) (1970-01-01 20:00:00, , 20) ``` Now, this output doesn't make much sense to me, it doesn't seem to respect the dtype spec that I give, but it's very possible that I don't understand the dtype spec well and that it's actually perfectly sensible output.
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5,192
BUG: raise NotImplementedError on passing of compound dtypes in constructors (GH5191)
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0
2013-10-12T17:33:55Z
2014-06-27T19:08:14Z
2013-10-12T17:45:29Z
CONTRIBUTOR
null
closes #5191
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5,193
Categorical description fails if only one category is found
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2013-10-12T20:00:00Z
2013-10-12T20:23:55Z
2013-10-12T20:23:55Z
NONE
null
Step to reproduce: ``` pd.Categorical(pd.Series([1,1,1,1])).describe() ```
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BUG: Bug in comparing duplicate frames (GH4421) related
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0
2013-10-12T21:16:16Z
2014-06-22T17:39:20Z
2013-10-12T21:28:42Z
CONTRIBUTOR
null
BUG: Bug in describe on duplicate frames related to #4421
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pd.to_datetime ValueError or TypeError
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5
2013-10-12T21:39:54Z
2013-10-12T23:53:46Z
2013-10-12T23:53:46Z
NONE
null
Hi, I am using pandas 0.12.0 and numpy 1.7.1. Not sure if this is the expected functionality or not. I thought if coerce = True or errors='ignore' I wouldn't get this result: ``` python In [372]: td = pd.Series(['May 04', 'Jun 02', 'Dec 11'], index=[1,2,3]) In [373]: td.apply(pd.to_datetime, format='%b %y', errors='ignore', coerce=True) Out[373]: 1 2004-05-01 00:00:00 2 2002-06-01 00:00:00 3 2011-12-01 00:00:00 dtype: datetime64[ns] In [374]: td = pd.Series(['May 04', 'Jun 02', ''], index=[1,2,3]) In [375]: td.apply(pd.to_datetime, format='%b %y', errors='ignore', coerce=True) --------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-375-0c44a3c36f8e> in <module>() ----> 1 td.apply(pd.to_datetime, format='%b %y', errors='ignore', coerce=True) C:\Python27\lib\site-packages\pandas\core\series.pyc in apply(self, func, convert_dtype, args, **kwds) 2534 values = lib.map_infer(values, lib.Timestamp) 2535 -> 2536 mapped = lib.map_infer(values, f, convert=convert_dtype) 2537 if isinstance(mapped[0], Series): 2538 from pandas.core.frame import DataFrame C:\Python27\lib\site-packages\pandas\lib.pyd in pandas.lib.map_infer (pandas\lib.c:42320)() C:\Python27\lib\site-packages\pandas\core\series.pyc in <lambda>(x) 2523 2524 if kwds or args and not isinstance(func, np.ufunc): -> 2525 f = lambda x: func(x, *args, **kwds) 2526 else: 2527 f = func C:\Python27\lib\site-packages\pandas\tseries\tools.pyc in to_datetime(arg, errors, dayfirst, utc, box, format, coerce, u nit) 127 return _convert_listlike(arg, box=box) 128 --> 129 return _convert_listlike(np.array([ arg ]), box=box)[0] 130 131 class DateParseError(ValueError): C:\Python27\lib\site-packages\pandas\tseries\tools.pyc in _convert_listlike(arg, box) 115 return DatetimeIndex._simple_new(values, None, tz=tz) 116 except (ValueError, TypeError): --> 117 raise e 118 119 if arg is None: ValueError: time data '' does not match format '%b %y' In [376]: ```
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5,196
BUG/ENH: Passing explicit dtype should delegate to appropriate Index subclass (if available)
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2
2013-10-12T22:10:46Z
2015-09-11T14:28:24Z
2015-09-11T14:28:23Z
CONTRIBUTOR
null
e.g. here's wrong behavior on current master ``` python In [1]: import pandas as pd In [2]: ind = pd.Index([1, 2, 3], dtype='int64') In [3]: ind Out[3]: Index([1, 2, 3], dtype='object') ``` Problem is ordering of how passed dtypes work in Index constructor. Make sure this gets fixed in 0.14.
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BUG: Bug in to_datetime with a format and coerce=True not raising (GH5195)
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0
2013-10-12T22:13:49Z
2014-06-24T06:53:46Z
2013-10-12T23:53:46Z
CONTRIBUTOR
null
closes #5195
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20,918,345
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5,198
BUG: recursion limit on eval when operating on different types
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3
2013-10-12T22:20:12Z
2019-07-29T14:38:21Z
2014-03-17T14:18:12Z
CONTRIBUTOR
null
Me being dumb discovered this: ``` python In [209]: bug = pd.DataFrame({"A": [1, 2], 'B': ['c', 'd']}) In [210]: bug Out[210]: A B 0 1 c 1 2 d In [211]: bug.eval('A + B') # stack trace truncated ... RuntimeError: maximum recursion depth exceeded ``` cc @cpcloud
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ENH/API: Accept DataFrame for isin
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26
2013-10-12T22:26:09Z
2017-04-05T02:05:43Z
2013-10-17T20:49:58Z
CONTRIBUTOR
null
API: Series should respect index labels. This would be incompatible, but there hasn't been any official release since `isin` was merged. Will close #4421. Still a WIP for now. Needs more testing. Thoughts on adding an argument to ignore the index? i.e. ``` python In [150]: df = pd.DataFrame({'A': [1, 2, 3, 4], 'B': [2, np.nan, 4, 4]}, index=['a','b','c','d']) In [151]: s = pd.Series([1, 3, 11, 12], index=['a','b','c','d']) In [152]: df.isin(s) Out[152]: A B a True False b False False c False False d False False In [152]: df.isin(s, ignore_index=True) Out[152]: A B a True False b False False c True False d False False ``` I would say there's no need for an `ignore_index` since you could just do `df.isin(s.values)`.
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20,918,684
MDU6SXNzdWUyMDkxODY4NA==
5,200
pd.date_range Attribute_Error
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[]
closed
false
null
[]
null
9
2013-10-12T22:51:46Z
2013-10-12T23:52:04Z
2013-10-12T23:46:56Z
NONE
null
I'm using pandas 0.12 and numpy 1.7.1. I'm trying to calculate the number of business days between two columns of dates. Not all rows have valid dates though, and pd.date_range does not have an ignore errors option, so I'm getting this error: ``` python In [439]: td = pd.DataFrame({'a':[pd.Timestamp('2010-1-1'), pd.Timestamp('2010-2-1')], 'b':[pd.Timestamp('2010-1-10'), p d.Timestamp('2010-2-9')]}) In [440]: td.apply(lambda row: len(pd.date_range(row['a'], row['b'], freq='B')), axis=1) Out[440]: 0 6 1 7 dtype: int64 In [441]: td = pd.DataFrame({'a':[pd.Timestamp('2010-1-1'), pd.Timestamp('2010-2-1')], 'b':[pd.Timestamp('2010-1-10'), p d.NaT]}) In [442]: td.apply(lambda row: len(pd.date_range(row['a'], row['b'], freq='B')), axis=1) --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) <ipython-input-442-30b1500c1594> in <module>() ----> 1 td.apply(lambda row: len(pd.date_range(row['a'], row['b'], freq='B')), axis=1) C:\Python27\lib\site-packages\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) C:\Python27\lib\site-packages\pandas\core\frame.pyc in _apply_standard(self, func, axis, ignore_failures) 4489 # no k defined yet 4490 pass -> 4491 raise e 4492 4493 AttributeError: ("'NaTType' object has no attribute 'tz'", u'occurred at index 1') In [443]: ```
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