pandas.Series.view#

Series.view(dtype=None)[source]#

Create a new view of the Series.

This function will return a new Series with a view of the same underlying values in memory, optionally reinterpreted with a new data type. The new data type must preserve the same size in bytes as to not cause index misalignment.

Parameters

dtypedata type: Data type object or one of their string representations.

Returns

Series: A new Series object as a view of the same data in memory.

See also

numpy.ndarray.view: Equivalent numpy function to create a new view of the same data in memory.

Notes

Series are instantiated with dtype=float64 by default. While numpy.ndarray.view() will return a view with the same data type as the original array, Series.view() (without specified dtype) will try using float64 and may fail if the original data type size in bytes is not the same.

Examples

>>> s = pd.Series([-2, -1, 0, 1, 2], dtype='int8')
>>> s
0   -2
1   -1
2    0
3    1
4    2
dtype: int8

The 8 bit signed integer representation of -1 is 0b11111111, but the same bytes represent 255 if read as an 8 bit unsigned integer:

>>> us = s.view('uint8')
>>> us
0    254
1    255
2      0
3      1
4      2
dtype: uint8

The views share the same underlying values:

>>> us[0] = 128
>>> s
0   -128
1     -1
2      0
3      1
4      2
dtype: int8