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up vote 46 down vote favorite
9

How to get from

["1.1", "2.2", "3.2"]

to

[1.1, 2.2, 3.2]

in NumPy?

share|improve this question
up vote 70 down vote accepted

Well, if you're reading the data in as a list, just do np.array(map(float, list_of_strings)) (or equivalently, use a list comprehension).

However, if it's already a numpy array of strings, there's a better way. Use astype().

import numpy as np
x = np.array(['1.1', '2.2', '3.3'], dtype='|S4')
y = x.astype(np.float)
share|improve this answer
    
and if you have a array with an string that i want to maintain? like ['a','1.1','2.2','3.3'] -> ['a',1.1,2.2,3.3] – MrMartin May 9 '15 at 20:09
3  
@MrMartin - Then use a list. Numpy arrays are deliberately homogenously typed. If you really want, you can use an object array (e.g. np.array(['apple', 1.2, 1, {'b'=None, 'c'=object()}], dtype=object)). However, object arrays don't have any significant advantages over using a list. – Joe Kington May 9 '15 at 20:14

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