Converting int arrays to string arrays in numpy without truncation

Question

Trying to convert int arrays to string arrays in numpy

In [66]: a=array([0,33,4444522])
In [67]: a.astype(str)
Out[67]: 
array(['0', '3', '4'], 
      dtype='|S1')

Not what I intended

In [68]: a.astype('S10')
Out[68]: 
array(['0', '33', '4444522'], 
      dtype='|S10')

This works but I had to know 10 was big enough to hold my longest string. Is there a way of doing this easily without knowing ahead of time what size string you need? It seems a little dangerous that it just quietly truncates your string without throwing an error.

For visitors from 2018 and beyond: a.astype(str) will now work exactly as desired. — Raketenolli
– Raketenolli, Commented Feb 19, 2018 at 16:05

jorgeca · Accepted Answer · 2016-12-12 07:27:38Z

58

You can stay in numpy, doing

np.char.mod('%d', a)

This is twice faster than map or list comprehensions for 10 elements, four times faster for 100. This and other string operations are documented here.

edited Dec 12, 2016 at 7:27

answered Apr 1, 2012 at 17:30

jorgeca

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2 Comments

Mikhail V Over a year ago

Cool, but I can't find documentation for this, could you provide a link if possible?

jorgeca Over a year ago

@MikhailV Sure, just added a link to the answer.

Niklas B. · Accepted Answer · 2012-03-31 19:20:30Z

53

Again, this can be solved in pure Python:

>>> map(str, [0,33,4444522])
['0', '33', '4444522']

Or if you need to convert back and forth:

>>> a = np.array([0,33,4444522])
>>> np.array(map(str, a))
array(['0', '33', '4444522'], 
      dtype='|S7')

answered Mar 31, 2012 at 19:20

Niklas B.

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2 Comments

Dave31415 Over a year ago

Thanks. I guess I need to become more acquainted with map.

Stardust Over a year ago

list(map(str, [0,33,4444522]))

jpp · Accepted Answer · 2018-05-30 17:47:28Z

21

Use arr.astype(str), as int to str conversion is now supported by numpy with the desired outcome:

import numpy as np

a = np.array([0,33,4444522])

res = a.astype(str)

print(res)

array(['0', '33', '4444522'], 
      dtype='<U11')

answered May 30, 2018 at 17:47

jpp

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Comments

NPE · Accepted Answer · 2012-03-31 19:22:23Z

3

You can find the smallest sufficient width like so:

In [3]: max(len(str(x)) for x in [0,33,4444522])
Out[3]: 7

Alternatively, just construct the ndarray from a list of strings:

In [7]: np.array([str(x) for x in [0,33,4444522]])
Out[7]: 
array(['0', '33', '4444522'], 
      dtype='|S7')

or, using map():

In [8]: np.array(map(str, [0,33,4444522]))
Out[8]: 
array(['0', '33', '4444522'], 
      dtype='|S7')

answered Mar 31, 2012 at 19:22

NPE

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6 Comments

Joel Cornett Over a year ago

For large arrays, map() is a better option than a list comprehension because it pushes the execution of the code into C.

jorgeca Over a year ago

@JoelCornett Sometimes map can be slightly faster (in this example it's about 3% faster than using a list comprehension for me), but this isn't always the case, and list comprehensions are considered more pythonic. See stackoverflow.com/a/1247490/1191119

Joel Cornett Over a year ago

@jorgeca: Absolutely, it isn't always the case. Incidentally, as I was doing the research, I came upon this enlightening article by Guido.

jorgeca Over a year ago

@JoelCornett Definitely, that's a great read. I knew it but it's well worth revisiting.

jorgeca Over a year ago

@drevicko here's an updated link

|

Hello Seattle · Accepted Answer · 2016-09-14 11:03:31Z

0

np.apply_along_axis(lambda y: [str(i) for i in y], 0, x)

Example

>>> import numpy as np

>>> x = np.array([-1]*10+[0]*10+[1]*10)
array([-1, -1, -1, -1, -1, -1, -1, -1, -1, -1,  0,  0,  0,  0,  0,  0,  0,
        0,  0,  0,  1,  1,  1,  1,  1,  1,  1,  1,  1,  1])

>>> np.apply_along_axis(lambda y: [str(i) for i in y], 0, x).tolist()
['-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '-1', '0', '0',
 '0', '0', '0', '0', '0', '0', '0', '0', '1', '1', '1', '1', '1', '1',
 '1', '1', '1', '1']

answered Sep 14, 2016 at 11:03

Hello Seattle

1

Comments

Filipe Pinto · Accepted Answer · 2022-11-22 20:26:37Z

0

For those working with Python 3.9, the command should be:

list(map(str, [1,2,3]))

answered Nov 22, 2022 at 20:26

Filipe Pinto

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