to_records(self, index=True, column_dtypes=None, index_dtypes=None) -> 'np.recarray'
Index will be included as the first field of the record array if requested.
Include index in resulting record array, stored in 'index' field or using the index label, if set.
If a string or type, the data type to store all columns. If a dictionary, a mapping of column names and indices (zero-indexed) to specific data types.
If a string or type, the data type to store all index levels. If a dictionary, a mapping of index level names and indices (zero-indexed) to specific data types.
This mapping is applied only if :None:None:`index=True`.
NumPy ndarray with the DataFrame labels as fields and each row of the DataFrame as entries.
Convert DataFrame to a NumPy record array.
DataFrame.from_records
Convert structured or record ndarray to DataFrame.
numpy.recarray
An ndarray that allows field access using attributes, analogous to typed columns in a spreadsheet.
>>> df = pd.DataFrame({'A': [1, 2], 'B': [0.5, 0.75]},This example is valid syntax, but we were not able to check execution
... index=['a', 'b'])
... df A B a 1 0.50 b 2 0.75
>>> df.to_records() rec.array([('a', 1, 0.5 ), ('b', 2, 0.75)], dtype=[('index', 'O'), ('A', '<i8'), ('B', '<f8')])
If the DataFrame index has no label then the recarray field name is set to 'index'. If the index has a label then this is used as the field name:
This example is valid syntax, but we were not able to check execution>>> df.index = df.index.rename("I")
... df.to_records() rec.array([('a', 1, 0.5 ), ('b', 2, 0.75)], dtype=[('I', 'O'), ('A', '<i8'), ('B', '<f8')])
The index can be excluded from the record array:
This example is valid syntax, but we were not able to check execution>>> df.to_records(index=False) rec.array([(1, 0.5 ), (2, 0.75)], dtype=[('A', '<i8'), ('B', '<f8')])
Data types can be specified for the columns:
This example is valid syntax, but we were not able to check execution>>> df.to_records(column_dtypes={"A": "int32"}) rec.array([('a', 1, 0.5 ), ('b', 2, 0.75)], dtype=[('I', 'O'), ('A', '<i4'), ('B', '<f8')])
As well as for the index:
This example is valid syntax, but we were not able to check execution>>> df.to_records(index_dtypes="<S2") rec.array([(b'a', 1, 0.5 ), (b'b', 2, 0.75)], dtype=[('I', 'S2'), ('A', '<i8'), ('B', '<f8')])This example is valid syntax, but we were not able to check execution
>>> index_dtypes = f"<S{df.index.str.len().max()}"See :
... df.to_records(index_dtypes=index_dtypes) rec.array([(b'a', 1, 0.5 ), (b'b', 2, 0.75)], dtype=[('I', 'S1'), ('A', '<i8'), ('B', '<f8')])
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