Convert ndarray to string array

Question

Lets say there is array

values = [[ 116.17265886,   39.92265886,  116.1761427 ,   39.92536232],
          [ 116.20749721,   39.90373467,  116.21098105,   39.90643813],
          [ 116.21794872,   39.90373467,  116.22143255,   39.90643813]]

now I want to convert this to

values = [[ '116.17265886',   '39.92265886',  '116.1761427' ,   '39.92536232'],
          [ '116.20749721',   '39.90373467',  '116.21098105',   '39.90643813'],
          [ '116.21794872',   '39.90373467',  '116.22143255',   '39.90643813']]

I have to ask: why?

Mad Physicist
– Mad Physicist

2022-06-01 20:10:12 +00:00
Commented Jun 1, 2022 at 20:10 — Mad Physicist
– Mad Physicist, Commented Jun 1, 2022 at 20:10
I am doing it in language modeling to train vec2word model.

The Peace of Programming
– The Peace of Programming

2022-06-02 10:59:17 +00:00
Commented Jun 2, 2022 at 10:59 — The Peace of Programming
– The Peace of Programming, Commented Jun 2, 2022 at 10:59

mozway · Accepted Answer · 2022-06-01 18:51:32Z

2

Assuming you really have a numpy array (not a list of list), you can use astype(str):

values = np.array([[ 116.17265886,   39.92265886,  116.1761427 ,   39.92536232],
                   [ 116.20749721,   39.90373467,  116.21098105,   39.90643813],
                   [ 116.21794872,   39.90373467,  116.22143255,   39.90643813]])

out = values.astype(str)

output:

array([['116.17265886', '39.92265886', '116.1761427', '39.92536232'],
       ['116.20749721', '39.90373467', '116.21098105', '39.90643813'],
       ['116.21794872', '39.90373467', '116.22143255', '39.90643813']],
      dtype='<U32')

answered Jun 1, 2022 at 18:51

mozway

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ShyGuyRyRyNewlyTheDataGuy · Accepted Answer · 2022-06-01 20:26:07Z

1

If it's not a numpy array and it is a list of a list of values the following code should work:

for index in range(len(values)):
   values[index] = [str(num) for num in values[index]]
print(values)

For each list it returns a list of each of the values changed to a string, this returns the following.

[['116.17265886', '39.92265886', '116.1761427', '39.92536232'], 
['116.20749721', '39.90373467', '116.21098105', '39.90643813'], 
['116.21794872', '39.90373467', '116.22143255', '39.90643813']]

answered Jun 1, 2022 at 20:26

ShyGuyRyRyNewlyTheDataGuy

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