convert binary string to numpy array

>>> np.frombuffer(b'\x00\x00\x80?\x00\x00\x00@\x00\x00@@\x00\x00\x80@', dtype='<f4') # or dtype=np.dtype('<f4'), or np.float32 on a little-endian system (which most computers are these days)array([ 1.,  2.,  3.,  4.], dtype=float32)

Or, if you want big-endian:

>>> np.frombuffer(b'\x00\x00\x80?\x00\x00\x00@\x00\x00@@\x00\x00\x80@', dtype='>f4') # or dtype=np.dtype('>f4'), or np.float32  on a big-endian systemarray([  4.60060299e-41,   8.96831017e-44,   2.30485571e-41,         4.60074312e-41], dtype=float32)

The b isn't necessary prior to Python 3, of course.

In fact, if you actually are using a binary file to load the data from, you could even skip the using-a-string step and load the data directly from the file with numpy.fromfile().

Also, dtype reference, just in case: http://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html

np.fromstring() is deprecated. Use np.frombuffer() instead.

import numpy as npmy_data = b'\x00\x00\x80?\x00\x00\x00@\x00\x00@@\x00\x00\x80@'# np.fromstring is deprecated# data = np.fromstring(my_data, np.float32)data = np.frombuffer(my_data, np.float32)print(data)

[1. 2. 3. 4.]