How do I import data with different types from file into a Python Numpy array?

Question

Say I have a file myfile.txt containing:

1   2.0000  buckle_my_shoe
3   4.0000  margery_door

How do I import data from the file to a numpy array as an int, float and string?

I am aiming to get:

array([[1,2.0000,"buckle_my_shoe"],
[3,4.0000,"margery_door"]])

I've been playing around with the following to no avail:

a = numpy.loadtxt('myfile.txt',dtype=(numpy.int_,numpy.float_,numpy.string_))

EDIT: Another approach might be to use the ndarray type and convert afterwards.

b = numpy.loadtxt('myfile.txt',dtype=numpy.ndarray)

    array([['1', '2.0000', 'buckle_my_shoe'],
       ['3', '4.0000', 'margery_door']], dtype=object)

Just read the file to a string, split the string on each \n newline and explode those inners with the 3- and 2 spaces. Otherwise you can also just use Regular Expressions to find each lines and split them up (groups). — user1467267
– user1467267, Commented Mar 18, 2013 at 16:18
I think the more important question is what you're going to do with this data after it's imported. While you can use numpy to work with non-numerical data, if you want to do anything fun with it you're probably going to wind up reinventing bits of pandas.. — DSM
– DSM, Commented Mar 18, 2013 at 16:24
For more basic explanations you might want to look at stackoverflow.com/a/10940038/2062965 — strpeter
– strpeter, Commented Nov 24, 2014 at 10:04

root · Accepted Answer · 2013-03-18 16:20:47Z

19

Use numpy.genfromtxt:

import numpy as np
np.genfromtxt('filename', dtype= None)
# array([(1, 2.0, 'buckle_my_shoe'), (3, 4.0, 'margery_door')], 
#       dtype=[('f0', '<i4'), ('f1', '<f8'), ('f2', '|S14')])

answered Mar 18, 2013 at 16:20

root

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Community · Accepted Answer · 2017-05-23 11:33:16Z

7

Pandas can do that for you. The docs for the function you could use are here.

Assuming your columns are tab separated, this should do the trick (adapted from this question):

df = DataFrame.from_csv('myfile.txt', sep='\t')
array = df.values # the array you are interested in

edited May 23, 2017 at 11:33

CommunityBot

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answered Mar 18, 2013 at 16:17

Matthieu

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