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DataFrame.to_records(index=True, convert_datetime64=None)[source]

Convert DataFrame to a NumPy record array.

Index will be included as the first field of the record array if requested.


index : bool, default True

Include index in resulting record array, stored in ‘index’ field or using the index label, if set.

convert_datetime64 : bool, default None

Deprecated since version 0.23.0.

Whether to convert the index to datetime.datetime if it is a DatetimeIndex.



NumPy ndarray with the DataFrame labels as fields and each row of the DataFrame as entries.

See also

convert structured or record ndarray to DataFrame.
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]},
...                   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:

>>> 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:

>>> df.to_records(index=False)
rec.array([(1, 0.5 ), (2, 0.75)],
          dtype=[('A', '<i8'), ('B', '<f8')])
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