I got this error generating a data frame consisting of timestamps and data: df = pd.DataFrame(, index=pd. > 1457 raise DataError('No numeric types to aggregate') usr/lib/python2.7/site-packages/pandas/core/groupby.py in _cython_agg_blocks(self, how, numeric_only) > 1417 new_blocks = self._cython_agg_blocks(how, numeric_only=numeric_only)ġ418 return self._wrap_agged_blocks(new_blocks) I have confirmed this bug exists on the latest version of pandas.
usr/lib/python2.7/site-packages/pandas/core/groupby.py in _cython_agg_general(self, how, numeric_only)ġ416 def _cython_agg_general(self, how, numeric_only=True): No numeric types to aggregate change in groupby() behaviour How are you generating your data See how the output shows that your data is of ‘object’ type the groupby operations specifically check whether each column is a numeric dtype first. BUG: DataError: No numeric types to aggregate on .rank 38278 Closed 3 tasks done ppetruneac opened this issue on 2 comments Fixed by 41498 ppetruneac commented on I have checked that this issue has not already been reported. > 297 return self._cython_agg_general('mean') usr/lib/python2.7/site-packages/pandas/core/groupby.py in mean(self) In : data.T.groupby(lat_bucket).mean()ĭataError Traceback (most recent call last) In : lat_bucket = lambda x: _get_gridbox_label(x, latedges, lats_new) Raise code): obj lectedobj objvals obj.values data obj.mgr if numericonly and not isnumericdtype(obj.dtype): raise DataError('No numeric types to aggregate') This is overkill because it is only called once, but is here to mirror the arrayfunc used in DataFrameGroupBy.cythonagggeneral def arrayfunc(values: ArrayLike) -> ArrayLike: try: result. In : def _get_gridbox_label(x, bins, labels): There is, apparently, a VBA add-in for excel. In : lats_new = linspace(-87.5, 87.5, 72) If you ever tried to pivot a table containing non-numeric values, you have surely been struggling with any spreadsheet app to do it easily. Here is what solved my issue: df 'columnname' pd. val.sum() Out 10: key a 1.2 b 5.7 Name: val, dtype: float64 Note that mean this column no longer applies The dtype of a column has nothing to do with the dtype of a single cell, for example: In 12: isinstance(df.
Any ideas? In : dataĭatetimeIndex: 2557 entries, 00:00:00 to 00:00:00 the DataError: No numeric types to aggregate of creating pivottable in Pandas score:2 Got the same problem here, searched for so long just to realize my values were not floats but strings. DataError: No numeric types to aggregate In 10: df.groupby(‘key’). On 0.9, I get No numeric types to aggregate errors.
#No numeric types to aggregate code#
I have a problem with some groupy code which I'm quite sure once ran (on an older pandas version). How are you generating your data See how the output shows that your data is of object type the groupby operations specifically check whether each column is.
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