Python: Replace a number in array with a string

Question

I have an array of numbers, which I would like to replace with a string depending on some condition. I can replace them with numbers:

d_sex = rand(10)
d_sex[d_sex > 0.5] = 1
d_sex[d_sex <= 0.5] = 0
d_sex

But I cannot do d_sex[d_sex>0.5] = "F". How would I do that in the most pythonic way? Would I create an empty string array? I am looking for something similar to Julia's:

d_sex = rand(50)
s_sex = ifelse(d_sex .> 0.5, "M", "F")
[d_sex s_sex]

I think map would be appropriate docs.python.org/2/library/functions.html#map — gimpycpu
– gimpycpu, Commented Dec 28, 2014 at 8:43
If you're trying to generate random zeros and ones you can use: d_sex = int(random.random() + 0.5). If that's not what you're looking for try adding more details to your question — Reut Sharabani
– Reut Sharabani, Commented Dec 28, 2014 at 8:44
If you want to mix data types, consider a pandas DataFrame. You can have a numpy string (or object) array, but it's not very efficient. — jonrsharpe
– jonrsharpe, Commented Dec 28, 2014 at 8:45

elyase · Accepted Answer · 2014-12-28 08:53:10Z

5

numpy.where is the equivalent of Julia's ifelse:

>>> np.where(d_sex > 0.5, 'M', 'F')
array(['F', 'M', 'M', 'F', 'F', 'M', 'F', 'M', 'F', 'F'], 
  dtype='|S1')

edited Dec 28, 2014 at 8:53

answered Dec 28, 2014 at 8:47

elyase

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Greg · Accepted Answer · 2014-12-28 08:50:44Z

2

If you don't use numpy then map is probably the best thing to do

a = [random() for _ in range(10)]
map(lambda x: 'F' if x > .5 else 'M', a)

answered Dec 28, 2014 at 8:50

Greg

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Irshad Bhat · Accepted Answer · 2014-12-28 09:33:50Z

Set dtype as object and it will allow you to replace float with a string as:

>>> import numpy as np
>>> d_sex = np.random.rand(10).astype('object')
>>> d_sex
array([0.6481844853562397, 0.1369951687351887, 0.4672729496950908,
       0.10511352546752228, 0.3967990781535288, 0.3452032518851482,
       0.34527110292775176, 0.24858258988637605, 0.2890001412667411,
       0.9504476492941463], dtype=object)
>>> d_sex[d_sex>0.5] = 'F'
>>> d_sex[d_sex<=0.5] = 'M'
>>> d_sex
array(['F', 'M', 'M', 'M', 'M', 'M', 'M', 'M', 'M', 'F'], dtype=object)

Vall3y · Accepted Answer · 2014-12-28 08:44:41Z

0

You could use a list comperhension

a = [0, 1, 0]
b = ['F' if i > 0.5 else 'M' for i in a]

=> ['M', 'F', 'M']

answered Dec 28, 2014 at 8:44

Vall3y

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