python - No numeric types to aggregate - change in groupby() behaviour? -


i have problem groupy code i'm quite sure once ran (on older pandas version). on 0.9, no numeric types aggregate errors. ideas?

in [31]: data out[31]:  <class 'pandas.core.frame.dataframe'> datetimeindex: 2557 entries, 2004-01-01 00:00:00 2010-12-31 00:00:00 freq: <1 dateoffset> columns: 360 entries, -89.75 89.75 dtypes: object(360)  in [32]: latedges = linspace(-90., 90., 73)  in [33]: lats_new = linspace(-87.5, 87.5, 72)  in [34]: def _get_gridbox_label(x, bins, labels):    ....:             return labels[searchsorted(bins, x) - 1]    ....:   in [35]: lat_bucket = lambda x: _get_gridbox_label(x, latedges, lats_new)  in [36]: data.t.groupby(lat_bucket).mean() --------------------------------------------------------------------------- dataerror                                 traceback (most recent call last) <ipython-input-36-ed9c538ac526> in <module>() ----> 1 data.t.groupby(lat_bucket).mean()  /usr/lib/python2.7/site-packages/pandas/core/groupby.py in mean(self)     295         """     296         try: --> 297             return self._cython_agg_general('mean')     298         except dataerror:     299             raise  /usr/lib/python2.7/site-packages/pandas/core/groupby.py in _cython_agg_general(self, how, numeric_only)    1415     1416     def _cython_agg_general(self, how, numeric_only=true): -> 1417         new_blocks = self._cython_agg_blocks(how, numeric_only=numeric_only)    1418         return self._wrap_agged_blocks(new_blocks)    1419   /usr/lib/python2.7/site-packages/pandas/core/groupby.py in _cython_agg_blocks(self, how, numeric_only)    1455     1456         if len(new_blocks) == 0: -> 1457             raise dataerror('no numeric types aggregate')    1458     1459         return new_blocks  dataerror: no numeric types aggregate

how generating data?

see how output shows data of 'object' type? groupby operations check whether each column numeric dtype first.

in [31]: data out[31]:  <class 'pandas.core.frame.dataframe'> datetimeindex: 2557 entries, 2004-01-01 00:00:00 2010-12-31 00:00:00 freq: <1 dateoffset> columns: 360 entries, -89.75 89.75 dtypes: object(360)

look ↑


did initialize empty dataframe first , filled it? if that's why changed new version before 0.9 empty dataframes initialized float type of object type. if can change initialization dataframe(dtype=float).

you can call frame.astype(float)


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