Panel4D.from_dict(data, intersect=False, orient='items', dtype=None) [source] Construct Panel from dict of DataFrame objects Parameters: data : dict {field : DataFrame} intersect : boolean Intersect indexes of input DataFrames orient : {?items?, ?minor?}, default ?items? The ?orientation? of the data. If the keys of the passed dict should be the items of the result panel, pass ?items? (default). Otherwise if the columns of the values of the passed DataFrame objects should be the items

DataFrame.icol(i) [source] DEPRECATED. Use .iloc[:, i] instead

Resampler.prod(_method='prod', *args, **kwargs) [source] Compute prod of group values See also pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby

DataFrameGroupBy.corrwith(other, axis=0, drop=False) Compute pairwise correlation between rows or columns of two DataFrame objects. Parameters: other : DataFrame axis : {0 or ?index?, 1 or ?columns?}, default 0 0 or ?index? to compute column-wise, 1 or ?columns? for row-wise drop : boolean, default False Drop missing indices from result, default returns union of all Returns: correls : Series

DataFrame.to_records(index=True, convert_datetime64=True) [source] Convert DataFrame to record array. Index will be put in the ?index? field of the record array if requested Parameters: index : boolean, default True Include index in resulting record array, stored in ?index? field convert_datetime64 : boolean, default True Whether to convert the index to datetime.datetime if it is a DatetimeIndex Returns: y : recarray

DataFrame.corrwith(other, axis=0, drop=False) [source] Compute pairwise correlation between rows or columns of two DataFrame objects. Parameters: other : DataFrame axis : {0 or ?index?, 1 or ?columns?}, default 0 0 or ?index? to compute column-wise, 1 or ?columns? for row-wise drop : boolean, default False Drop missing indices from result, default returns union of all Returns: correls : Series

DataFrame.to_panel() [source] Transform long (stacked) format (DataFrame) into wide (3D, Panel) format. Currently the index of the DataFrame must be a 2-level MultiIndex. This may be generalized later Returns: panel : Panel

Index.data return the data pointer of the underlying data

TimedeltaIndex.asi8

Panel4D.get_ftype_counts() [source] Return the counts of ftypes in this object.