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Enable element-wise comparison operations in DataMatrix objects
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"2010-09-29T00:45:31Z"
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re: pystatsmodels e-mail hi everyone, just getting started with pandas and i was wondering if someone could help me out. do pandas.DataMatrix objects support per item comparison operations? i have a two data matrices, and i want to do something like this: div[div > 0.5 \* price] = 0 this would work if div and price were numpy.ndarray objects. any idea how i would do something like this with pandas.DataMatrix objects? thanks, andy
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reindex_like function
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"2010-09-29T00:50:13Z"
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In Series, DataMatrix, WidePanel, etc.
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Binary operations on int DataMatrix
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Reported by kwgoodman, Jun 12, 2010 When adding two int DataMatrix's a ValueError is raised when matrix.py attempt to fill missing values with NaN: > > dma1 = pandas.DataMatrix([[1, 2], [3, 4]], ['a', 'b'], ['c', 'd']) > > dma2 = pandas.DataMatrix([[1, 2], [3, 4]], ['b', 'a'], ['d', 'c']) > > dma1 + dma2 > > <snip> > > ValueError: cannot convert float NaN to integer Delete comment Comment 1 by kwgoodman, Jun 12, 2010 Possible fix: > > x = np.array([1.0]) > > issubclass(x.dtype.type, np.inexact) > > True > > x = np.array([1]) > > issubclass(x.dtype.type, np.inexact) > > False > > x = np.array([1.0], dtype=object) > > issubclass(x.dtype.type, np.inexact) > > False > > x = np.array([1.0], dtype=str) > > issubclass(x.dtype.type, np.inexact) > > False
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Plot keyword arguments are unused in DataFrame plot()
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Reported by twhitcomb, Jul 27, 2010 What steps will reproduce the problem? 1. Import pandas 2. Create a sample DataFrame 3. Plot the DataFrame using a linewidth keyword argument. What is the expected output? What do you see instead? I expect to see the linewidth keyword argument passed through to the plotting routine. Instead, the plot is displayed with the default linewidth (see attached figure). What version of the product are you using? On what operating system? > > > pandas.**version** > > > 0.20000000000000001 > > > Microsoft Windows Vista, Python(x,y) 2.6.5.1 Please provide any additional information below. Looking at the plot function in frame.py it's obvious why this is happening: def plot(self, kind='line', **kwds): # pragma: no cover from pylab import plot ``` for col in sorted(self.columns): s = self[col] plot(s.index, s, label=col) ``` Note that **kwds is not used in the plot command. If I load a new function into my workspace like def plot_frame(frame, *_kwargs): from pylab import plot for col in sorted(frame.columns): s = frame[col] plot(s.index, s, label=col, *_kwargs) Then the arguments are correctly passed on, and I get the proper response, as shown in the other attached figure.
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Python 2.7 testing
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Test pandas on Python 2.7
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Fix argument inconsistency in pandas.stats.moments exp-weighted functions
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"2010-09-29T05:30:56Z"
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Should have min_periods arguments like the other rolling moment functions
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DataMatrix constructor ignores dtype argument if data is a DataMatrix
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"2010-09-29T15:41:55Z"
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``` >>> a = DataMatrix([[1.0,2.0,3.0],[4.0,5.0,6.0]], range(2), range(3)) >>> b = DataMatrix(a, dtype=int) >>> b.values.dtype dtype('float64') ``` Not sure if this was a design decision or not, but it seems like the dtype of b.values should be int.
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np.fix doesn't work
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``` In [28]: np.fix(Series([1,2,3], range(3))) --------------------------------------------------------------------------- Exception Traceback (most recent call last) C:\alei1\basic_mktneutral\<ipython console> in <module>() C:\Python26\lib\site-packages\numpy\lib\ufunclike.pyc in fix(x, y) 43 x = nx.asanyarray(x) 44 if y is None: ---> 45 y = nx.zeros_like(x) 46 y1 = nx.floor(x) 47 y2 = nx.ceil(x) C:\Python26\lib\site-packages\numpy\core\numeric.pyc in zeros_like(a) 92 if isinstance(a, ndarray): 93 res = ndarray.__new__(type(a), a.shape, a.dtype, order=a.flags.fnc) ---> 94 res.fill(0) 95 return res 96 try: C:\Python26\lib\site-packages\pandas\core\series.pyc in fill(self, value, method) 822 """ 823 if value is not None: --> 824 newSeries = self.copy() 825 newSeries[isnull(newSeries)] = value 826 return newSeries C:\Python26\lib\site-packages\pandas\core\series.pyc in copy(self) 342 343 def copy(self): --> 344 return Series(self.values.copy(), index=self.index) 345 346 #------------------------------------------------------------------------------- C:\Python26\lib\site-packages\pandas\core\series.pyc in __new__(cls, data, index, dtype, copy) 136 137 if index is None: --> 138 raise Exception('Index cannot be None!') 139 140 # This is to prevent mixed-type Series getting all casted to ``` i think the bigger problem is overriding the default behavior of the fill() method, which may contribute to other numpy / scipy functions not behaving correctly.
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Fix pandas.io.parsers.parseExcel to be more robust / have correct handling of Excel dates
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Improvements to pandas.io.pytables / unit testing
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"2010-09-30T22:33:14Z"
"2014-07-01T02:55:23Z"
"2011-06-23T19:38:51Z"
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null
Need to incorporate the selection of ranges of data and write unit tests
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Rename {Series, DataFrame, WidePanel}.fill() to something else
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"2010-09-30T22:34:26Z"
"2011-02-19T23:46:00Z"
"2011-02-19T23:46:00Z"
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Will need to give users advance warning of API breakage
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DataFrame and DataMatrix column ordering
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"2010-10-03T17:20:41Z"
"2010-12-11T22:53:14Z"
"2010-12-11T22:53:14Z"
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null
First, thank you for the pandas package -- it's incredibly useful and well done. I know that one of the fundamental concepts behind the data structures is that column ordering doesn't matter. And, as long as one only uses pandas' data access/manipulation functions (eg, sum(), ewma(), etc.), this works fine. But often, it's useful to access the underling values in a numpy array for some more complicated data manipulation. Using the values attribute (or values() method for a series) does this, but it's not always obvious what order the values come back in. For example: <pre> In [1]: dm = DataMatrix(np.arange(2*3).reshape(2,3), index=[1,0], columns=['B', 'A', 'C' ]) In [2]: dm Out[2]: B A C 1 0 1 2 0 3 4 5 In [3]: df = DataFrame(np.arange(2*3).reshape(2,3), index=[1,0], columns=['B', 'A', 'C' ]) In [4]: df Out[4]: A B C 1 1 0 2 0 4 3 5 In [5]: df.values Out[5]: array([[1, 0, 2], [4, 3, 5]]) In [6]: dm.values Out[6]: array([[0, 1, 2], [3, 4, 5]]) </pre> DataMatrix seems to respect the passed in ordering of columns, while DataFrame does not. I know this is documented, and not the biggest deal in the world, but does seem to cause quite a bit of confusion for some. Is it possible to have both data types keep the ordering that's passed in? If a user passes in the same column name twice, could this just throw an exception? Something stills need to be done when an operation is performed on two DataFrames (eg, combining them), but instead of reordering in alphabetical order, how about preserving the column ordering from left to right? Anyway, my bigger concern is actually the following: <pre> In [7]: dm.reindex(columns=['C','B','A']).values Out[7]: array([[2, 0, 1], [5, 3, 4]]) In [8]: df.reindex(columns=['C','B','A']).values Out[8]: array([[1, 0, 2], [4, 3, 5]]) </pre> Regardless of the ordering of the columns after creating a DataFrame/Matrix, a naive users (ie, me) would expect calling reindex and values would return an ndarray with the columns in the same order as was requested. But it looks like this only happens for DataMatrixes (and I'm not even sure that's always guaranteed).
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13
Add PyTable Paths to HDFStore
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4
"2010-10-07T23:42:34Z"
"2012-12-13T01:37:53Z"
"2012-12-12T21:35:57Z"
NONE
null
Hello, I not sure if this was the best way to suggest improvements, but here I go anyway :) I really like the easy of the HDFStore (and the entire project for that matter), but I wanted the ability to store and retrieve DataFrames in Groups below the root. .i.e ``` h5 = HDFStore('test.h5') h5['/groups/below/theroot'] = DataFrame(data, index) df = h5['/groups/below/theroot'] ``` I made the following changes to HDFStore class to do this, and am now using it in production code. If you agree this is something useful then I would like this to become apart of the main code base, using your own approach or the below. I changed the **repr**, **getitem**, and _write_group functions in pandas.io.pytables. ``` def __repr__(self): output = str(self.__class__) + '\n' #Exstract path and kind of all 'pandas_type' pytable Groups. keys, values = zip(*((x._v_pathname, x._v_attrs.pandas_type) for x in self.handle.walkGroups() if hasattr(x._v_attrs,'pandas_type'))) output += adjoin(5, keys, values) return output def __getitem__(self, key): if not key[0] == '/': #Then add root slash so we can use getNode belwo key = '/' + key group = self.handle.getNode(key) return _read_group(group) def _write_group(self, key, value): root = self.handle.root if key[0] == '/': #Assume they want a nested pytable Group final_slash = key.rfind('/') where = key[:final_slash] name = key[final_slash + 1:] else: where = '/' name = key try: group = self.handle.getNode(key) except: group = self.handle.createGroup(where, name, createparents=True) kind = type(value) handler = self._get_write_handler(kind) try: handler(group, value) except Exception: raise group._v_attrs.pandas_type = kind.__name__ return True ``` please let me know if there is questions or concerns... I made it so that it still works just like the original if the user doesn't need groups... Thanks for a great project.
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14
Make more flexible arithmetic functions in DataFrame/DataMatrix
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"2010-10-11T03:19:39Z"
"2011-02-19T16:13:00Z"
"2011-02-19T16:13:00Z"
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For example: ``` df.add(series, axis=0) df.add(series, axis='index') df.add(series, axis='columns') ``` Etc., might be useful in certain cases
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.apply() API consistency fix
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"2010-10-12T16:10:48Z"
"2010-12-11T06:19:58Z"
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DataFrame.apply, Series.applymap, Series.map sort of come across as inconsistent. ``` def f(x): return x.apply(lambda y: 2*y) def g(x): return x.applymap(lambda y: 2*y) a = TimeSeries([1,2],[1,2]) b = DataMatrix({'a':a}) f(b) g(b) f(a) g(a) ```
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16
Outlier detection in pandas.stats.moments functions
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"2010-10-12T16:13:04Z"
"2011-06-23T04:46:14Z"
"2011-06-23T04:46:14Z"
MEMBER
null
Floating point error can result in incorrect output in the rolling_\* functions (need unit tests)
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Better support for mixed-type data
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"2010-10-12T16:13:55Z"
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Across DataFrame and Wide/LongPanel classes
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weights option may not be working in pandas.stats.ols.OLS
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"2011-12-31T16:53:33Z"
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Need to investigate (user notified)
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parseCSV on result of toCSV does not preserve index type
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"2010-10-22T17:59:31Z"
"2011-01-11T03:37:14Z"
"2011-01-11T03:37:14Z"
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From Google Code: http://code.google.com/p/pandas/issues/detail?id=14 First of all, thanks very much for this very nice project. I find it extremely useful. I ran into a very minor issue: What steps will reproduce the problem? 1. Create a DataFrame with date objects in the index 2. Write to csv using toCSV method 3. Read DataFrame using parseCSV method What is the expected output? What do you see instead? I had hoped that the index of the parsed DataFrame would consist of date objects, instead they are strings. What version of the product are you using? On what operating system? Trunk, revision 202. Ubuntu 10.10 Please provide any additional information below. The reason is that toCSV writes the first column header as "index" If it were to leave it blank, things work as I expect.
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Install 0.2beta fail on Debian Lenny / python2.5
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"2010-11-19T14:50:11Z"
"2010-12-17T02:45:20Z"
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Using a stock debian lenny box with: - numpy-1.3.0 built from source - scipy 0.8.0 built from source - matplotlib-1.0.0 built from source - pandas-0.2beta (note: no problems with latest github pull) # Errors: Install 0.2beta mpenning@Bucksnort:~/src/pandas-0.2beta$ sudo python setup.py install running install running build running config_cc unifing config_cc, config, build_clib, build_ext, build commands --compiler options running config_fc unifing config_fc, config, build_clib, build_ext, build commands --fcompiler options running build_src building extension "pandas.lib.tseries" sources pandas.lib - nothing done with h_files = ['pandas/lib/include/wirth.h'] building data_files sources running build_py creating build creating build/lib.linux-i686-2.5 creating build/lib.linux-i686-2.5/pandas copying pandas/**init**.py -> build/lib.linux-i686-2.5/pandas copying pandas/info.py -> build/lib.linux-i686-2.5/pandas copying pandas/version.py -> build/lib.linux-i686-2.5/pandas copying pandas/setup.py -> build/lib.linux-i686-2.5/pandas creating build/lib.linux-i686-2.5/pandas/core copying pandas/core/mixins.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/**init**.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/series.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/collection.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/index.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/panel.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/pytools.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/matrix.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/daterange.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/frame.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/common.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/datetools.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/groupby.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/setup.py -> build/lib.linux-i686-2.5/pandas/core copying pandas/core/api.py -> build/lib.linux-i686-2.5/pandas/core creating build/lib.linux-i686-2.5/pandas/io copying pandas/io/**init**.py -> build/lib.linux-i686-2.5/pandas/io copying pandas/io/parsers.py -> build/lib.linux-i686-2.5/pandas/io creating build/lib.linux-i686-2.5/pandas/lib copying pandas/lib/**init**.py -> build/lib.linux-i686-2.5/pandas/lib copying pandas/lib/build.py -> build/lib.linux-i686-2.5/pandas/lib copying pandas/lib/bench.py -> build/lib.linux-i686-2.5/pandas/lib copying pandas/lib/setup.py -> build/lib.linux-i686-2.5/pandas/lib creating build/lib.linux-i686-2.5/pandas/sandbox copying pandas/sandbox/**init**.py -> build/lib.linux-i686-2.5/pandas/sandbox creating build/lib.linux-i686-2.5/pandas/stats copying pandas/stats/plm.py -> build/lib.linux-i686-2.5/pandas/stats copying pandas/stats/**init**.py -> build/lib.linux-i686-2.5/pandas/stats copying pandas/stats/ols.py -> build/lib.linux-i686-2.5/pandas/stats copying pandas/stats/math.py -> build/lib.linux-i686-2.5/pandas/stats copying pandas/stats/interface.py -> build/lib.linux-i686-2.5/pandas/stats copying pandas/stats/common.py -> build/lib.linux-i686-2.5/pandas/stats copying pandas/stats/fama_macbeth.py -> build/lib.linux-i686-2.5/pandas/stats copying pandas/stats/setup.py -> build/lib.linux-i686-2.5/pandas/stats copying pandas/stats/var.py -> build/lib.linux-i686-2.5/pandas/stats copying pandas/stats/moments.py -> build/lib.linux-i686-2.5/pandas/stats copying pandas/stats/api.py -> build/lib.linux-i686-2.5/pandas/stats creating build/lib.linux-i686-2.5/pandas/util copying pandas/util/**init**.py -> build/lib.linux-i686-2.5/pandas/util copying pandas/util/decorators.py -> build/lib.linux-i686-2.5/pandas/util copying pandas/util/testing.py -> build/lib.linux-i686-2.5/pandas/util running build_ext customize UnixCCompiler customize UnixCCompiler using build_ext building 'pandas.lib.tseries' extension compiling C sources C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fPIC creating build/temp.linux-i686-2.5 creating build/temp.linux-i686-2.5/pandas creating build/temp.linux-i686-2.5/pandas/lib creating build/temp.linux-i686-2.5/pandas/lib/src compile options: '-I/usr/lib/python2.5/site-packages/numpy/core/include -Ipandas/lib/include/ -I/usr/lib/python2.5/site-packages/numpy/core/include -I/usr/include/python2.5 -c' gcc: pandas/lib/src/wirth.c gcc: pandas/lib/src/tseries.c /usr/lib/python2.5/site-packages/numpy/core/include/numpy/__ufunc_api.h:183: warning: ?_import_umath? defined but not used pandas/lib/src/tseries.c:1397: warning: ?__pyx_f_7tseries_get_int16_ptr? defined but not used pandas/lib/src/tseries.c:1434: warning: ?__pyx_f_7tseries_get_int32_ptr? defined but not used pandas/lib/src/tseries.c:1471: warning: ?__pyx_f_7tseries_get_int64_ptr? defined but not used pandas/lib/src/tseries.c:1508: warning: ?__pyx_f_7tseries_get_double_ptr? defined but not used gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions build/temp.linux-i686-2.5/pandas/lib/src/tseries.o build/temp.linux-i686-2.5/pandas/lib/src/wirth.o -o build/lib.linux-i686-2.5/pandas/lib/tseries.so running scons running install_lib copying build/lib.linux-i686-2.5/pandas/lib/tseries.so -> /usr/lib/python2.5/site-packages/pandas/lib running install_data running install_egg_info Removing /usr/lib/python2.5/site-packages/pandas-0.2beta.egg-info Writing /usr/lib/python2.5/site-packages/pandas-0.2beta.egg-info mpenning@Bucksnort:~/src/pandas-0.2beta$ cd mpenning@Bucksnort:~/$ mpenning@Bucksnort:~$ python Python 2.5.2 (r252:60911, Jan 24 2010, 14:53:14) [GCC 4.3.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. > > > import pandas > > > Traceback (most recent call last): > > > File "<stdin>", line 1, in <module> > > > File "/usr/lib/python2.5/site-packages/pandas/**init**.py", line 14, in <module> > > > from pandas.stats.api import * > > > File "/usr/lib/python2.5/site-packages/pandas/stats/api.py", line 7, in <module> > > > from pandas.stats.moments import * > > > File "/usr/lib/python2.5/site-packages/pandas/stats/moments.py", line 365, in <module> > > > _rolling_sum = _wrap_cython(tseries.roll_sum) > > > AttributeError: 'module' object has no attribute 'roll_sum'
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Consistent column ordering between DataFrame and DataMatrix
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"2010-11-19T18:41:36Z"
"2010-11-19T18:42:08Z"
"2010-11-19T18:42:08Z"
MEMBER
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To allow the classes to have more nearly identical behavior
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numpy.dtype size changed runtime warning on XP
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"2010-12-14T16:50:11Z"
"2010-12-19T05:55:29Z"
"2010-12-15T04:07:42Z"
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I've installed numpy from numpy-1.5.1-win32-superpack-python2.6.exe and pandas from pandas-0.2.win32-py2.6.exe. When I import \* from pandas I get the following warnings: Warning (from warnings module): File "C:\Program Files\Python26\lib\site-packages\pandas\core\index.py", line 7 from pandas.lib.tseries import map_indices RuntimeWarning: numpy.dtype size changed, may indicate binary incompatibility Warning (from warnings module): File "C:\Program Files\Python26\lib\site-packages\pandas\core\index.py", line 7 from pandas.lib.tseries import map_indices RuntimeWarning: numpy.flatiter size changed, may indicate binary incompatibility I've had no issues yet using pandas interactively in the window (idle), but if I have embedded the import in a module then I am not able to execute any of the code from the module. Thoughts?
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numpy traceback during easy_install on Debian Lenny
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I'm not sure whether this is due to a problem with my local version of numpy or something else (in perhaps pandas?)... I did not see this previously (same numpy install and other dependencies) when I installed from Github trunk (sometime around November 15, 2010)... ``` [mpenning@Bucksnort ~]$ uname -a Linux Bucksnort 2.6.26-2-686 #1 SMP Thu Sep 16 19:35:51 UTC 2010 i686 GNU/Linux [mpenning@Bucksnort ~]$ cat /etc/issue Debian GNU/Linux 5.0 \n \l [mpenning@Bucksnort ~]$ sudo easy_install -U pandas [sudo] password for mpenning: Searching for pandas Reading http://pypi.python.org/simple/pandas/ Reading http://pandas.sourceforge.net Best match: pandas 0.3.0.beta Downloading http://pypi.python.org/packages/source/p/pandas/pandas-0.3.0.beta.tar.gz#md5=18a39d6aa5df2f3515bada968554f049 Processing pandas-0.3.0.beta.tar.gz Running pandas-0.3.0.beta/setup.py -q bdist_egg --dist-dir /tmp/easy_install-24C3ig/pandas-0.3.0.beta/egg-dist-tmp-Lc7eTD warning: no files found matching 'LICENSE.txt' warning: no files found matching 'README.txt' /usr/lib/python2.5/site-packages/numpy/core/include/numpy/__ufunc_api.h:197: warning: ?_import_umath? defined but not used pandas/lib/src/tseries.c:1535: warning: ?__pyx_f_7tseries_get_int16_ptr? defined but not used pandas/lib/src/tseries.c:1572: warning: ?__pyx_f_7tseries_get_int32_ptr? defined but not used pandas/lib/src/tseries.c:1609: warning: ?__pyx_f_7tseries_get_int64_ptr? defined but not used pandas/lib/src/tseries.c:1646: warning: ?__pyx_f_7tseries_get_double_ptr? defined but not used zip_safe flag not set; analyzing archive contents... Adding pandas 0.3.0.beta to easy-install.pth file Installed /usr/lib/python2.5/site-packages/pandas-0.3.0.beta-py2.5-linux-i686.egg Processing dependencies for pandas Finished processing dependencies for pandas Error in atexit._run_exitfuncs: Traceback (most recent call last): File "/usr/lib/python2.5/atexit.py", line 24, in _run_exitfuncs func(*targs, **kargs) File "/usr/lib/python2.5/site-packages/numpy/distutils/misc_util.py", line 251, in clean_up_temporary_directory from numpy.distutils import log SystemError: Parent module 'numpy.distutils' not loaded Error in sys.exitfunc: Traceback (most recent call last): File "/usr/lib/python2.5/atexit.py", line 24, in _run_exitfuncs func(*targs, **kargs) File "/usr/lib/python2.5/site-packages/numpy/distutils/misc_util.py", line 251, in clean_up_temporary_directory from numpy.distutils import log SystemError: Parent module 'numpy.distutils' not loaded [mpenning@Bucksnort ~]$ python Python 2.5.2 (r252:60911, Jan 24 2010, 14:53:14) [GCC 4.3.2] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import pandas >>> quit() [mpenning@Bucksnort ~]$ ```
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24
Install problems
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3
"2010-12-24T07:27:52Z"
"2010-12-24T21:29:45Z"
"2010-12-24T16:27:12Z"
NONE
null
pypi install of pandas still isn't working on 2.7, even with all dependencies Python 2.7.1 (r271:86832, Nov 27 2010, 18:30:46) [MSC v.1500 32 bit (Intel)] on win32 Type "help", "copyright", "credits" or "license" for more information. > > > import pandas > > > Traceback (most recent call last): > > > File "<stdin>", line 1, in <module> > > > File "pandas__init__.py", line 12, in <module> > > > from pandas.core.api import * > > > File "pandas\core\api.py", line 8, in <module> > > > from pandas.core.common import isnull, notnull > > > File "pandas\core\common.py", line 6, in <module> > > > import pandas.lib.tseries as tseries > > > ImportError: No module named tseries
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25
Souce compile errors
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"2010-12-24T07:32:39Z"
"2010-12-24T21:28:59Z"
"2010-12-24T21:28:59Z"
NONE
null
Old bug opened on google code showed that workaround for the pypi install failures should be to download latest source and compile as such: python setup.py build --compiler=mingw32 python setup.py install tseries.c has two errors stopping compilation pandas\lib\src\tseries.c: In function '__Pyx_c_absf': pandas\lib\src\tseries.c:18906:25: error: #if with no expression pandas\lib\src\tseries.c: In function '__Pyx_c_abs': pandas\lib\src\tseries.c:19026:25: error: #if with no expression pandas\lib\src\tseries.c: At top level: should that be #ifdef?
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26
dtype mismatch when calling .median()
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"2011-01-03T17:15:19Z"
"2011-01-03T23:23:47Z"
"2011-01-03T23:23:47Z"
NONE
null
Using python 2.5.2, pandas 0.3 and numpy 1.5.1 on a debian lenny box... mean() works, but not median() ``` >>> df1['b'].truncate(before=dt.date(2010,12,2),after=dt.date(2010,12,4)) 2010-12-02 6 2010-12-03 7 2010-12-04 8 >>> df1['b'].truncate(before=dt.date(2010,12,2),after=dt.date(2010,12,4)).median() Traceback (most recent call last): File "<stdin>", line 1, in <module> File "build/bdist.linux-i686/egg/pandas/core/series.py", line 486, in median File "moments.pyx", line 70, in tseries.median (pandas/lib/src/tseries.c:5967) File "moments.pyx", line 28, in tseries.kth_smallest (pandas/lib/src/tseries.c:5539) ValueError: Buffer dtype mismatch, expected 'double_t' but got 'long' >>> df1['b'].truncate(before=dt.date(2010,12,2),after=dt.date(2010,12,4)).mean() 7.0 ```
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27
Incorrect T-Stats in FamaMacBeth.py
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"2011-01-03T23:29:47Z"
"2011-02-20T00:53:44Z"
"2011-02-20T00:53:44Z"
CONTRIBUTOR
null
Small bug in the FamaMacBeth class at lines 105-106-- the printed form of the regression results gives the STD twice, rather than the t-stat: <code> std_beta = self._results['std_beta'][i] t_stat = self._results['std_beta'][i] </code> Last one should be t_stat instead of std_beta the second time.
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what is the easiest way to plot a timeseries and dataframe?
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"2011-01-11T04:14:15Z"
"2011-01-29T19:13:49Z"
"2011-01-29T19:13:49Z"
NONE
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it looks like ts.plot and df.plot is not implemented yet. I watched Wes's PyCon 2010 video where he use some functions fplot (presumably it is defined in the pycon_demo.py that was run at the beginning of the demo). pandas is a great package. Hope it will be kept active and keep expanding. Great work. Thanks.
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29
.asfreq() dies when the index values have tzinfo associated with them
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"2011-06-23T04:47:01Z"
"2011-06-23T04:47:01Z"
NONE
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``` >>> # dataframe is indexed at a second granularity, using eastern time >>> dataframe <class 'pandas.core.frame.DataFrame'> Index: 24676 entries , 2010-10-04 00:03:49-04:00 to 2010-10-04 23:59:55-04:00 etf 10897 non-null values etfvol 10897 non-null values fut 17988 non-null values futvol 17988 non-null values ticx 7880 non-null values vix 7465 non-null values vixvol 7465 non-null values >>> dataframe['etf'].index[0] datetime.datetime(2010, 10, 4, 0, 3, 49, tzinfo=<DstTzInfo 'US/Eastern' EDT-1 day, 20:00:00 DST>) >>> >>> # et is a pytz timezone object for eastern time... >>> et <DstTzInfo 'US/Eastern' EST-1 day, 19:00:00 STD> >>> dataframe['fut'].asfreq(et.localize(pn.DateOffset(seconds=1)), method='pad') Traceback (most recent call last): File "<console>", line 1, in <module> File "/usr/lib/python2.5/site-packages/pytz-2010o-py2.5.egg/pytz/tzinfo.py", line 262, in localize if dt.tzinfo is not None: AttributeError: 'DateOffset' object has no attribute 'tzinfo' >>> >>> dataframe['fut'].asfreq(pn.DateOffset(seconds=1), method='pad') Traceback (most recent call last): File "<console>", line 1, in <module> File "/usr/lib/python2.5/site-packages/pandas/core/series.py", line 1103, in asfreq dateRange = DateRange(self.index[0], self.index[-1], offset=freq) File "/usr/lib/python2.5/site-packages/pandas/core/daterange.py", line 70, in __new__ fromInside = start is not None and start > _CACHE_START TypeError: can't compare offset-naive and offset-aware datetimes >>> ```
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resource hog -> .asfreq(DateOffset(seconds=1),method='pad')
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"2011-01-11T12:31:34Z"
"2011-06-14T14:17:06Z"
"2011-06-14T14:17:06Z"
NONE
null
``` >>> df2['a'] 2010-12-01 00:00:00 1 2010-12-02 00:00:00 2 2010-12-03 00:00:00 3 2010-12-04 00:00:00 4 >>> df2['a'].asfreq(pn.DateOffset(seconds=1),method='pad') ## NOTE: The above one-liner runs for over 20 minutes on a 2Ghz Xeon, python 2.5.2, numpy 1.5.1, ## & pandas head from 2011-01-05. It also consumed > 15% (500MB!!!) of available DRAM ## before I manually killed it [mpenning@Bucksnort tickdata]$ free total used free shared buffers cached Mem: 3894944 3771540 123404 0 192340 2328984 -/+ buffers/cache: 1250216 2644728 Swap: 2830328 596 2829732 [mpenning@Bucksnort tickdata]$ cat /proc/cpuinfo ... processor : 3 vendor_id : GenuineIntel cpu family : 15 model : 2 model name : Intel(R) Xeon(TM) CPU 2.00GHz stepping : 7 cpu MHz : 1995.840 cache size : 512 KB physical id : 3 siblings : 2 core id : 0 cpu cores : 1 apicid : 7 initial apicid : 7 fdiv_bug : no hlt_bug : no f00f_bug : no coma_bug : no fpu : yes fpu_exception : yes cpuid level : 2 wp : yes flags : fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe pebs bts cid xtpr bogomips : 3991.51 clflush size : 64 power management: [mpenning@Bucksnort tickdata]$ ```
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Is there a single pdf instead of html documentation/help file?
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"2011-01-13T04:05:11Z"
"2011-02-20T00:07:53Z"
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This may not be the best place to post this question b/c it is not an "issue", just a question that I don't know where else I can post it to. I am just wondering whether there is a single pdf help or documentation file, instead of html help pages on the sourceforge website. Also, I am wondering whether we have a faq or forum that people discuss about usage/tutorial/success stories etc on using pandas, other than this one? may be pystatmodel? Thanks again, Wes for creating this package! -alex
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32
Does pandas support piecewise/multi-period regression?
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"2011-01-18T20:28:41Z"
"2011-01-20T17:42:12Z"
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Hi, I need to do piecewise or multi-period regression where the breakpoint is determined automatically by the algorithm itself. Does pandas support that? Thanks a lot. -alex
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NumPy >= 1.4.0 NaN-handling issues
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"2011-01-22T20:36:36Z"
"2011-02-20T00:50:55Z"
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MEMBER
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There are a few potential NaN-casting problems floating around the codebase, e.g.: ``` df1 = pandas.DataFrame({'x':[5]}) df2 = pandas.DataFrame({'x':[1]}) df1.combineAdd(df2) ```
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34
reindex(method="backfill") and periods within the last date
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"2011-01-24T20:15:05Z"
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I have a DataFrame with 1 minute timestamps, pw. I have a monthly average of the values: ma_pw=pw.groupby(BMonthEnd(+1).rollforward).aggregate(np.mean) When I do a reindex to push that average back into all of the periods for the month, the last day's values are NaN. Here's my reindex attempt: reindexed = ma_pw.reindex(pw.index, method="backfill"). I have worked around this by forcing the hour in my monthly data to something past the last minute that I care about in my by-minute data as follows, but this seems incredibly crude: from dateutil.relativedelta import * newi = [x + relativedelta(hour=20) for x in ma_pw.index] ma_pw.index = newi[:] Then my original reindex works. Is there a clean way to instruct the reindex method to include the datetime objects having the same datetime.date on that last day of the month?
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Added hist method and added auto_x argument to plot method.
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"2011-02-22T08:07:35Z"
"2011-02-27T05:17:56Z"
"2011-02-25T01:41:56Z"
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I have added hist method to frame.py and series.py, and added auto_x argument to plot method, which can be useful for the cases where the index does not consist of numeric values. -Joon
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Install problems on Windows 7
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"2011-02-25T19:07:03Z"
"2013-09-17T12:20:45Z"
"2011-03-02T12:24:08Z"
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I'm on a new computer with Windows 7. I've installed the 32 bit versions of python-2.7.1 and all subsequent requirements. pandas-0.3.0.win32-py2.7.exe does not complete. It just stops and windows claims it is not responding. The same phenomenon happened installing tables-2.2.1.win32-py2.7.exe. I'm assuming that pytables is recommended but not required for pandas. Anyway, both of these installs do not work. Suggestions?
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added describe and scoreatpercentile in frame.py
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Added two methods in frame.py: describe, which returns a DataFrame with summary statistics of each columns of the original DataFrame (with index=columns), and scoreatpercentile, which calculate the score at the given percentile. When I play around with a dataset I use this describe thing a lot so I thought it would be convenient to have this with DataFrame. I think this is crudely implemented so if you think there is a better way please let me know! -Joon
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changed _pfixed in common.py to add a leading space to positive numbers
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"2011-03-22T19:27:42Z"
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So the results of DataFrame.toString() without any float_format argument is aligned around the period. I think it looks much better. :)
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Adding variable description in DataFrame
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"2011-04-06T00:15:26Z"
"2014-03-09T15:18:34Z"
"2014-03-09T15:18:34Z"
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Hi, I think it would be great if DataFrame is able to store additional property (list of strings) which contains the description for each variable (column). And then it can be shown by themselves with variable names as well as in the output of pandas.DataFrame.info(). I think with this DataFrame will be pretty much self contained. Right now I need to keep additional object or a text file which contains those descriptions. Please let me know what do you think! -Joon
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40
Create generic moving window function
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"2011-05-01T17:31:45Z"
"2011-06-28T03:09:55Z"
"2011-06-28T03:09:55Z"
MEMBER
null
Probably no way to make more efficient than naive Python loop, but at least more convenient
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Join methods for WidePanel
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"2011-05-01T17:32:55Z"
"2012-01-05T19:04:25Z"
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e.g. def create_panels_join(a, b): """ return a join of the 2 panels """ d = dict([ (i,(a[i].T.join(v.T)).T) for i, v in b.iteritems() ]) return p.WidePanel.fromDict(d) # this is a 'more' correct version, but have to assure that a[i] is not None def create_panels_join(a, b): """ return a join of the 2 panels """ items = set(a.items) + set(b.items) WidePanel.fromDict(dict([ (i,(a[i].T.join(b[i].T)).T) for i in items ]))
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Slice DataMatrix-- get a view
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"2011-05-01T17:33:45Z"
"2011-05-30T22:59:55Z"
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MEMBER
null
add copy keyword to .xs() method. Won't work with DataFrame, should raise Exception
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HDFStore testing and improvements
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"2011-05-01T17:58:10Z"
"2011-06-23T04:47:33Z"
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Per many requests...just a place holder to remind me to do it
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All days instead of business days?
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"2011-05-06T10:38:14Z"
"2011-05-16T12:03:37Z"
"2011-05-06T19:13:40Z"
NONE
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Hi, I am very new to github and miss a discussion board for pandas. Not sure if issues is the right place for my question, so feel free to delete it, but please point to the right place for questions. The question: I need to aggregate hourly time series to the daily scale, that would include all days, 7 per week. Currently i find only bday class in datetools: <pre> daily_ts = ts.groupby(lambda x: datetools.bday(x)).aggregate(np.nansum) </pre> But bday will skip weekends. datetools.day seem to return timeseries with the same time resolution. How to include weekend days? Many thanks for developing pandas, it's truly nice, and really fast, even when working with large datasets!
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Importing data using HDFStore with pre-epoch dates; "ValueError: timestamp out of range for platform localtime()/gmtime() function"
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"2011-05-20T22:13:31Z"
"2011-06-23T04:17:27Z"
"2011-06-23T04:17:27Z"
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I have data with a DataFrame that goes back to 1949. I imported it from a csv into a hdf5 using HDFStore. That went fine, but when reading from the HDFStore to get a DF back, I get the below stack trace. When looking at the data in the store I see that the index has negative values for preepoch times... ValueError: timestamp out of range for platform localtime()/gmtime() function File "C:\dev\MktDB\test_continuation.py", line 59, in <module> main() File "C:\Python27\lib\site-packages\pandas-0.3.0-py2.7-win32.egg\pandas\io\pytables.py", line 157, in _read_group File "C:\Python27\lib\site-packages\pandas-0.3.0-py2.7-win32.egg\pandas\io\pytables.py", line 173, in _read_frame File "C:\Python27\lib\site-packages\pandas-0.3.0-py2.7-win32.egg\pandas\io\pytables.py", line 210, in _read_index File "C:\Python27\lib\site-packages\pandas-0.3.0-py2.7-win32.egg\pandas\io\pytables.py", line 227, in _unconvert_index File "C:\Users\Shon\AppData\Roaming\Python-Eggs\pandas-0.3.0-py2.7-win32.egg-tmp\pandas\lib\tseries.pyd", line 45, in tseries.array_to_datetime (pandas\lib\src\tseries.c:14378) File "C:\Users\Shon\AppData\Roaming\Python-Eggs\pandas-0.3.0-py2.7-win32.egg-tmp\pandas\lib\tseries.pyd", line 20, in tseries.to_datetime (pandas\lib\src\tseries.c:13910) Any guidance would be most appreciated. Shon
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Configure pandas like pyzmq so checking in .c files is not necessary
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"2011-05-31T16:51:22Z"
"2011-06-28T00:41:31Z"
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MEMBER
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No reason to be checking in the C files and diffs
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Time zone handling in DateRange, etc. using pytz
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"2011-06-03T08:53:52Z"
"2011-06-14T14:43:51Z"
"2011-06-14T14:43:51Z"
MEMBER
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Working on this at the moment, but still more to do
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"Proper" boolean array with NA handling in DataMatrix
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"2011-06-14T14:06:41Z"
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Currently booleans are getting casted to floats in some circumstances in order to handle NAs. Need to devise a workable scheme for boolean data possibly containing NAs.
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Consistent column ordering in mixed-type DataMatrix
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As floats and non-floats are currently segregated, column ordering not reliable. Thus, behavior between DataFrame and DataMatrix is not identical
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Better implementation of rolling_max and min
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"2012-07-12T16:51:03Z"
"2012-07-12T16:51:03Z"
MEMBER
null
Currently using skiplist, unnecessary
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examples not running, error in documentation
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"2011-06-21T14:09:06Z"
"2011-06-21T16:34:40Z"
"2011-06-21T14:38:23Z"
NONE
null
Both examples do not run. In finance.py, on line 83: ``` filledRatio = ibm / ibmMonthly.reindex(ibm.index, fillMethod='pad') ``` should be: ``` filledRatio = ibm / ibmMonthly.reindex(ibm.index, method='pad') ``` As reindex is defined in core/series.py as ``` def reindex(self, index=None, method=None): ``` This error is repeated in the documentation at http://pandas.sourceforge.net (reindex uses the argument fillMethod instead of method). running regressions.py, I get the following error: Traceback (most recent call last): File "regressions.py", line 30, in <module> model = ols(y=Y, x=X) File "/usr/local/lib/python2.6/dist-packages/pandas/stats/interface.py", line 117, in ols return klass(**kwargs) File "/usr/local/lib/python2.6/dist-packages/pandas/stats/ols.py", line 56, in **init** self.sm_ols = sm.OLS(self._y_raw, self._x.values).fit() AttributeError: 'module' object has no attribute 'OLS' It's possible I'm somehow combining incompatible versions of pandas, but I don't see how, considering I downloaded pandas today, once. The first bug, at least seems like a simple code error. Hopefully this is of some help, Colum
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52
Improve fancy indexing when selecting cross-sections
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"2011-06-21T15:49:54Z"
"2011-06-23T04:16:33Z"
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MEMBER
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Something like ``` df.ix[0, ['C', 'B', A']] ``` is currently performing a wasteful reindex(columns=['C', 'B', A']), need to have some better way to infer the "right" order to perform the operations in
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53
Optimized DataFrame.append for block structure if possible
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54
fillna bug on ordered string data
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"2011-06-27T17:53:51Z"
"2011-06-27T23:06:24Z"
"2011-06-27T23:06:24Z"
MEMBER
null
OK ``` x = Series([NaN,1.,NaN,3.,NaN],['a','b','c','d','e'], dtype=object) x.fillna(method='pad') ``` Not OK ``` x = Series([NaN,1.,NaN,3.,NaN],['z','a','b','c','d'], dtype=object) x.fillna(method='pad') ```
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Minor change to CleanCommand so build works with stdeb
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"2011-06-29T00:59:24Z"
"2011-06-29T02:07:07Z"
"2011-06-29T02:06:48Z"
CONTRIBUTOR
null
Hi Wes, i've been following your pandas work for a while, and regularly install it on my ubuntu based systems. I generally use the stdeb (https://github.com/astraw/stdeb) package for creating .deb files from python packages. Unfortunately, some of your recent changes in setup.py in pandas caused a problem with building using stdeb. Essentially the problem is that debhelper tries to run "python setup.py clean -a" at some point, which doesn't work because the customized clean command does not have a "-a" option. I just added a dummy argument "--all, -a" argument that has no effect. No worries if you'd rather not merge it, just wanted to check. thanks
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MDU6SXNzdWUxMTY5NjE4
56
Some reverse binary operations fail with dtype=object
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1
"2011-07-05T19:50:00Z"
"2011-07-08T21:07:28Z"
"2011-07-08T21:07:28Z"
MEMBER
null
See example ``` In [12]: arr = Series(np.random.randn(10), index=np.arange(10), dtype=object) In [13]: arr Out[13]: 0 -0.475934738891 1 0.602096986911 2 0.731158853064 3 -0.268872970066 4 0.607786684074 5 -0.0200444918205 6 1.93289485517 7 1.14860246486 8 -0.138246858663 9 0.382736317471 In [14]: 1. / arr --------------------------------------------------------------------------- TypeError Traceback (most recent call last) /Users/wesm/Downloads/<ipython-input-14-6df87fcc597b> in <module>() ----> 1 1. / arr TypeError: unsupported operand type(s) for /: 'float' and 'Series' ```
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https://api.github.com/repos/pandas-dev/pandas/issues/57
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1,224,282
MDU6SXNzdWUxMjI0Mjgy
57
fillna bug
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1
"2011-07-14T16:28:06Z"
"2011-07-14T16:46:35Z"
"2011-07-14T16:46:35Z"
NONE
null
ser=Series([np.nan,1,2],index=range(3)) ser.fillna(method='backfill') GIVES ValueError: unknown dtype code in numpy.pxd (0)
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https://api.github.com/repos/pandas-dev/pandas/issues/58
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1,228,406
MDU6SXNzdWUxMjI4NDA2
58
setup.py
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"2011-07-15T04:51:09Z"
"2011-07-15T06:54:06Z"
"2011-07-15T06:54:06Z"
NONE
null
sudo python setup.py -v build # fails on Mac OS 10.6 or something can't convert the .pyx files to .c hard linking pandas/src/skiplist.pyx -> pandas-0.4.0.dev20110715_027c90b/pandas/src 'pandas/src/sparse.c' not a regular file -- skipping hard linking pandas/src/sparse.pyx -> pandas-0.4.0.dev20110715_027c90b/pandas/src 'pandas/src/tseries.c' not a regular file -- skipping changing the setup.py as follows: @line10 - from setuptools import setup - from scipy_distutils.core import setup makes it work. thx Pearu: http://osdir.com/ml/python.f2py.user/2003-11/msg00008.html
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https://api.github.com/repos/pandas-dev/pandas/issues/59
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1,232,682
MDU6SXNzdWUxMjMyNjgy
59
Use Pdb.runcall() in debug()
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3
"2011-07-15T21:18:40Z"
"2011-07-15T23:44:55Z"
"2011-07-15T23:44:55Z"
CONTRIBUTOR
null
See attached patch.
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https://api.github.com/repos/pandas-dev/pandas/issues/60
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1,233,249
MDU6SXNzdWUxMjMzMjQ5
60
Easier subclassing
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20
"2011-07-15T23:11:41Z"
"2014-07-30T01:12:20Z"
"2014-07-30T01:12:20Z"
NONE
null
Hi, Currently, sub-classing pandas objects is not as easy as it could be. This is the result of many methods explicitly creating specific classes. E.g. the '_combine_const' method from 'matrix' explicitly returns a DataMatrix object: def _combine_const(self, other, func): if not self: return self ``` # TODO: deal with objects return DataMatrix(func(self.values, other), index=self.index, columns=self.columns) ``` Therefore, arithmetic operations (and some other operations) performed on a new class MyDataMatrix, inheriting form DataMatrix, return a DataMatrix object, rather than a MyDataMatrix object. I can get around the problem using the ugly hack of overriding the problem methods, and forcing the output to the new class. E.g., def _combine_const(self, other, func): temp = super(MyDataMatrix, self)._combine_const(other, func) temp.__class__ = self.**class** return temp However, I feel it would be easier to just change the original methods to return the class of the calling object, rather than a fixed class. E.g., def _combine_const(self, other, func): if not self: return self ``` # TODO: deal with objects return self.__class__(func(self.values, other), index=self.index, columns=self.columns) ``` Hope this makes sense, and I'm not missing something. Thanks for a very useful package!
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61
DataFrame.__ne__ not implemented
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"2011-07-18T02:15:11Z"
"2011-07-20T19:46:26Z"
"2011-07-20T19:46:25Z"
MEMBER
null
See ``` dm = DataFrame({'col1':[1,2],'col2':[1,2]}) dm[dm!=0] = 5 ```
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1,242,419
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62
Add na_omit options to aggregation functions
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1
"2011-07-18T15:37:26Z"
"2011-10-02T02:56:19Z"
"2011-10-02T02:56:19Z"
MEMBER
null
A la R's ``` mean(arr, na.rm=T) ```
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63
Unit testing / cleanup of pandas.io.sql
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numpy.datetime64 type integration
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"2011-07-18T15:39:18Z"
"2012-04-05T00:31:26Z"
"2012-04-05T00:31:26Z"
MEMBER
null
Need to examine use cases and see how hard it will be to switch over
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Add dot method to DataFrame
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"2011-07-18T15:43:35Z"
"2011-11-10T04:08:23Z"
"2011-11-10T04:08:23Z"
MEMBER
null
To enable easy matrix multiplication with DataFrame: ``` df.dot(series) ```
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66
Fancy indexing on single column of DataFrame
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"2011-07-18T15:45:19Z"
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MEMBER
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Things like this does not work ``` df.ix[boolean_vec, 'B'] = val ```
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67
Reindexing Cython code cleanup
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"2011-07-18T15:46:39Z"
"2011-10-02T03:26:44Z"
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MEMBER
null
reindex.pyx is a bit of a mess
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68
Import plyr-like functionality
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Want to be able to do things like: http://cran.r-project.org/web/packages/plyr/index.html
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69
Fancy indexing on WidePanel and n-dimensional version
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"2011-07-18T15:48:30Z"
"2011-09-08T16:42:07Z"
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MEMBER
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see indexing.py, `DataFrameIndexer`, need to make more generic for the n-dimensional case
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70
Implement DataFrame.insert method
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Want to be able to insert columns at specific locations, e.g. ``` df.insert(0, column, value) ```
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71
Enable DataFrame constructor to accept structured/record ndarray
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Enable reindex methods to optionally not copy data when they can
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"2011-07-18T15:52:21Z"
"2011-09-08T16:39:40Z"
"2011-09-08T16:39:40Z"
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If no reshaping is required, reindex currently copies anyway (which is the generally desired behavior: favor immutability): ``` df.reindex(index) ``` but perhaps you could do: ``` df.reindex(index, force_copy=False) ``` if course if reshaping is required, a copy will be created anyway. Should think of a better keyword arg name
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73
Enable Series objects to optionally have a name associated with them
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"2011-10-14T22:18:03Z"
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This would be easy to do / unobtrusive: ``` >>> s = Series(values, index, name='foo') >>> s.name ```
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Test coverage for pandas.stats subpackage
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Heterogeneous type handling in LongPanel
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Now that WidePanel admits non-floating point data, need to_long to work and LongPanel needs an internal block structure
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Sparse cumsum functions do not work
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"2011-07-18T21:00:39Z"
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e.g. SparseSeries.cumsum
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Build error on OS X 10.7: tseries
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"2011-07-21T19:32:25Z"
"2011-10-03T13:53:25Z"
"2011-10-02T02:55:40Z"
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I'm trying to build pandas on OSX 10.7, but run into an error building tseries: building 'pandas._tseries' extension C compiler: llvm-gcc-4.2 -DNDEBUG -g -fwrapv -Os -Wall -Wstrict-prototypes -arch x86_64 -pipe creating build/temp.macosx-10.7-x86_64-2.7 creating build/temp.macosx-10.7-x86_64-2.7/pandas creating build/temp.macosx-10.7-x86_64-2.7/pandas/src compile options: '-I/Library/Python/2.7/site-packages/numpy-2.0.0.dev_e2af7b7_20110721-py2.7-macosx-10.7-intel.egg/numpy/core/include -I/System/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7 -c' llvm-gcc-4.2: pandas/src/tseries.c i686-apple-darwin11-llvm-gcc-4.2: pandas/src/tseries.c: No such file or directory i686-apple-darwin11-llvm-gcc-4.2: no input files i686-apple-darwin11-llvm-gcc-4.2: pandas/src/tseries.c: No such file or directory i686-apple-darwin11-llvm-gcc-4.2: no input files error: Command "llvm-gcc-4.2 -DNDEBUG -g -fwrapv -Os -Wall -Wstrict-prototypes -arch x86_64 -pipe -I/Library/Python/2.7/site-packages/numpy-2.0.0.dev_e2af7b7_20110721-py2.7-macosx-10.7-intel.egg/numpy/core/include -I/System/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7 -c pandas/src/tseries.c -o build/temp.macosx-10.7-x86_64-2.7/pandas/src/tseries.o" failed with exit status 1 I did not get this on Snow Leopard. Running Python 2.7.1 with a current, working numpy 2.0.
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78
Create HierarchicalIndex object to implement multi-level indexing
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"2011-07-24T20:08:48Z"
"2011-09-08T16:38:54Z"
"2011-09-08T16:38:54Z"
MEMBER
null
Also provides a nice way to create pretty pivot tables / cross-tabulations
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79
groupby.pyx
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"2011-07-26T01:42:29Z"
"2011-07-26T02:02:21Z"
"2011-07-26T02:00:58Z"
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Hi Wes, got an error when building " index = np.asarray(index) ## ^ /home/yinchun/diy/pyenv/invest/src/pandas/pandas/src/groupby.pyx:62:28: local variable 'index' referenced before assignment " could i just delete this line?? Thanks, Tim
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Some test data files don't get copied to site-packages
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"2011-07-26T15:41:00Z"
"2013-12-04T00:40:19Z"
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csv/h5/xls files in pandas/io/tests
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bug in DataFrame/DataMatrix toCSV method when index=False
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"2011-07-27T23:02:15Z"
"2011-07-31T16:23:24Z"
"2011-07-31T16:23:24Z"
CONTRIBUTOR
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When index=False an extra column is added because the leading comma is never removed. ``` def toCSV(self, path, nanRep='', cols=None, header=True, index=True, mode='wb'): *<snip>* for idx in self.index: if index: f.write(str(idx)) for col in cols: *<snip>* f.write(',%s' % val) ```
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ImportError: No module named tseries
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"2011-07-28T15:04:34Z"
"2013-12-04T00:40:19Z"
"2011-07-28T15:20:01Z"
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Hi, I downloaded the 0.3.0 package from pypi, installed using "sudo python setup.py install". The install was OK, but in Python when doing "import pandas" I get the following error: "ImportError: No module named tseries" (full output from Ipython below). This was using Ubuntu 10.04 (32), Thanks. ## In [1]: import pandas ImportError Traceback (most recent call last) pandas-0.3.0/<ipython console> in <module>() pandas-0.3.0/pandas/**init**.py in <module>() 10 from pandas.info import **doc** 11 ---> 12 from pandas.core.api import * 13 from pandas.io.parsers import parseCSV, parseText, parseExcel 14 from pandas.stats.api import * pandas-0.3.0/pandas/core/api.py in <module>() 6 import pandas.core.datetools as datetools 7 ----> 8 from pandas.core.common import isnull, notnull 9 from pandas.core.index import Index 10 from pandas.core.daterange import DateRange pandas-0.3.0/pandas/core/common.py in <module>() 8 import numpy as np 9 ---> 10 import pandas.lib.tseries as tseries 11 12 # XXX: HACK for NumPy 1.5.1 to suppress warnings ImportError: No module named tseries
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[suggestion] example for pandas.DataFrame.pivot
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"2011-07-29T15:53:40Z"
"2011-07-30T16:58:47Z"
"2011-07-30T16:58:47Z"
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Please provide some documentation and examples for pandas.DataFrame.pivot, which is noted here: http://pandas.sourceforge.net/generated/pandas.DataFrame.pivot.html#pandas.DataFrame.pivot Thanks!
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84
Create memory-efficient DateIndex
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"2011-07-29T16:26:50Z"
"2012-04-05T00:31:20Z"
"2012-04-05T00:31:20Z"
MEMBER
null
Need to use either numpy.datetime64 or scikits.timeseries.DateArray as the means of implementation
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Enable pandas.core.sparse objects to be stored in HDFStore
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"2011-07-29T22:19:39Z"
"2016-10-12T23:02:34Z"
"2012-05-07T15:05:18Z"
MEMBER
null
Currently SparseDataFrame and friends can't be stored in HDFStore
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86
Push some of Series.ix into Series.__getitem__/__setitem__
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"2011-07-30T01:01:42Z"
"2012-01-13T21:17:59Z"
"2012-01-13T21:17:59Z"
MEMBER
null
Should be able to do stuff like: ``` ts[date1:date2] ``` to mirror ts.ix[date1:date2]. Should respect integer labels while Series.ix will not
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87
[question] possible to use compound logic in indexing
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"2011-08-01T20:13:57Z"
"2011-08-07T19:31:13Z"
"2011-08-07T19:31:13Z"
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null
in your documentation, you have the following example: ``` >>> df[df['A'] > 0.5] A D N S 2009-05-29 00:00:00 0.979307 0.979307 4 5 2009-07-31 00:00:00 0.536261 nan 6 5 2009-09-30 00:00:00 0.537841 nan 8 5 ``` would it be possible to do something like this: ``` >>> df[df['A'] > 0.5 and df['N']>5] ``` where both conditions are satisfied? The syntax supports it, but I'm not getting what I expect.
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88
Document panel {sum, mean, ...} methods
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"2011-08-05T15:46:35Z"
"2011-09-08T16:38:37Z"
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MEMBER
null
e.g. WidePanel.sum has no usage documentation
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89
Fix for issue #80
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1
"2011-08-06T08:02:19Z"
"2014-07-17T17:26:50Z"
"2011-08-07T16:15:41Z"
CONTRIBUTOR
null
Starting small... It looks like the .h5 files in pandas/io/tests were getting copied okay, but the xls and csv files weren't in the package-data, so I added them.
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build error on linux: common.pyx
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"2011-08-07T02:54:27Z"
"2011-08-07T20:40:20Z"
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NONE
null
I tried to build from head . I got the following error. My cython version is 0.12.1. Unfortunately I can't upgrade cython as I don't have root permission. cythoning pandas/src/tseries.pyx to pandas/src/tseries.c ## Error converting Pyrex file to C: ... result[idx] = i PyArray_ITER_NEXT(iter) ``` return result ``` cpdef map_indices_buf(ndarray[object] index): ## ^ /mypath/wesm-pandas-2af6604/pandas/src/common.pyx:110:38: Expected ')'
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91
Change sum/mean/count/std/var/etc. to use bottleneck if available
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"2011-08-07T19:42:03Z"
"2012-01-12T01:03:28Z"
"2012-01-12T01:03:28Z"
MEMBER
null
bottleneck.{nan*} methods are much faster than the pure Python/NumPy versions inside DataFrame, for example.
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92
Enable DataFrame to be sorted by multiple columns
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"2017-03-15T18:46:35Z"
"2011-11-13T18:28:29Z"
MEMBER
null
Code would look more or less like: ``` sorted_df = df.sort(['col1', 'col2']) ```
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Improve Cython multi-groupby code to do aggregation without having to sort the data
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"2011-08-07T21:01:30Z"
"2011-12-16T01:32:07Z"
"2011-12-16T01:32:07Z"
MEMBER
null
Currently doing a lexsort to put things in order-- likely less efficient than it could be
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94
Make DataFrame toString formatting use precision set in numpy.set_printoptions
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"2011-08-07T21:08:46Z"
"2011-09-08T16:41:34Z"
"2011-09-08T16:41:30Z"
MEMBER
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Currently the code involved with this is located in pandas/core/common.py. Shouldn't be very hard to do
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Implement GroupBy __len__ to return number of resulting groups
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"2011-08-09T02:25:36Z"
"2011-08-19T20:11:26Z"
"2011-08-19T20:11:26Z"
NONE
null
Right now there is no way (to my knowledge) to get the number of groups that the DataFrame.groupby() method creates. For example (using Pandas 0.4 dev): ``` from pandas import *; from numpy.random import randn data = { 'A': rand(4), 'B': rand(4), 'C': (0, 1, 1, 1)} df = DataFrame(data) grouping = df.groupby('C') len(grouping) TypeError: object of 'DataFrameGroupBy' has no len() ``` This seems counter intuitive considering iter is implemented. Having the len() method would be very useful if we need to know the number of existing groups prior to iterating through the groups (e.g.. one use case would be to determine the number and layout of subplots, one for each group, in a Matplotlib figure). Right now, I typically just do: ``` grouping = list(df.groupby('C')) n = len(grouping) # do something with n for key, frame in grouping: # do something ``` (updated to fix formatting)
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96
Write Cython function to determine sort order in hierarchical indexes
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97
Problem with Series.plot
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"2011-08-09T18:25:40Z"
"2011-08-09T18:32:55Z"
"2011-08-09T18:32:55Z"
CONTRIBUTOR
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The code snippet below raises an AssertionError from pandas because matplotlib tries to add a dimension to the index ndarray subclass. No big deal, since i can do pylab.plot(np.asarray(ts.index), np.asarray(ts.values) import pandas import datetime import numpy as np values = np.arange(5.) dates = [datetime.datetime(2009, 1, 1, 0, 0), datetime.datetime(2009, 1, 2, 0, 0), datetime.datetime(2009, 1, 5, 0, 0), datetime.datetime(2009, 1, 6, 0, 0), datetime.datetime(2009, 1, 7, 0, 0)] ts = pandas.Series(values, index=dates) ts.plot() Here's the trace back: Traceback (most recent call last): File "pandasplot.py", line 11, in <module> ts.plot() File "/usr/lib/python2.7/dist-packages/pandas/core/series.py", line 1189, in plot ax.plot(x, self.values.astype(float), style, *_kwds) File "/usr/lib/python2.7/dist-packages/matplotlib/axes.py", line 3783, in plot for line in self._get_lines(_args, **kwargs): File "/usr/lib/python2.7/dist-packages/matplotlib/axes.py", line 317, in _grab_next_args for seg in self._plot_args(remaining, kwargs): File "/usr/lib/python2.7/dist-packages/matplotlib/axes.py", line 294, in _plot_args x, y = self._xy_from_xy(x, y) File "/usr/lib/python2.7/dist-packages/matplotlib/axes.py", line 239, in _xy_from_xy x = x[:,np.newaxis] File "/usr/lib/python2.7/dist-packages/pandas/core/index.py", line 110, in __getitem__ return Index(arr_idx[key]) File "/usr/lib/python2.7/dist-packages/pandas/core/index.py", line 50, in **new** assert(subarr.ndim == 1) AssertionError
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98
Calling xs on DataFrame with index but no columns raises Exception
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"2011-08-09T20:53:42Z"
"2011-08-09T22:54:57Z"
"2011-08-09T22:54:57Z"
MEMBER
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example: ``` In [1]: df = DataFrame(index=['a', 'b', 'c']) In [2]: df.ix['a'] ERROR: An unexpected error occurred while tokenizing input The following traceback may be corrupted or invalid The error message is: ('EOF in multi-line statement', (2, 0)) --------------------------------------------------------------------------- IndexError Traceback (most recent call last) /home/wesm/code/pandas/<ipython-input-2-6181dcf1ffea> in <module>() ----> 1 df.ix['a'] /home/wesm/code/pandas/pandas/core/indexing.pyc in __getitem__(self, key) 102 return self._fancy_getitem(key, axis=0) 103 else: --> 104 return self._fancy_getitem_axis(key, axis=0) 105 106 def __setitem__(self, key, value): /home/wesm/code/pandas/pandas/core/indexing.pyc in _fancy_getitem_axis(self, key, axis) 200 return self.frame.xs(idx) 201 else: --> 202 return self.frame.xs(idx, copy=False) 203 else: 204 col = key /home/wesm/code/pandas/pandas/core/frame.pyc in xs(self, key, copy) 839 840 self._consolidate_inplace() --> 841 values = self._data.xs(key, axis=1, copy=copy) 842 return Series(values.as_matrix(), index=self.columns) 843 /home/wesm/code/pandas/pandas/core/internals.pyc in xs(self, key, axis, copy) 451 new_blocks.append(newb) 452 else: --> 453 vals = self.blocks[0].values[slicer] 454 if copy: 455 vals = vals.copy() IndexError: list index out of range ```
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99
Bring back .groups attribute for GroupBy
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"2011-08-09T22:51:30Z"
"2011-08-19T21:07:24Z"
"2011-08-19T20:11:52Z"
MEMBER
null
A bit more complicated now with possible multiple groupings, however.
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100
Remove AmbiguousIndexError in fancy indexing
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[ { "color": "e10c02", "default": false, "description": null, "id": 76811, "name": "Bug", "node_id": "MDU6TGFiZWw3NjgxMQ==", "url": "https://api.github.com/repos/pandas-dev/pandas/labels/Bug" }, { "color": "4E9A06", "default": false, "description": null, "id": 76812, "name": "Enhancement", "node_id": "MDU6TGFiZWw3NjgxMg==", "url": "https://api.github.com/repos/pandas-dev/pandas/labels/Enhancement" } ]
closed
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"2011-08-10T00:51:55Z"
"2011-08-19T20:12:50Z"
"2011-08-19T20:12:50Z"
MEMBER
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.ix field should prefer labels over integers, while **getitem** should prefer integers
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https://api.github.com/repos/pandas-dev/pandas/issues/100/timeline
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