how to create a numpy array of calculated values inside a loop

Question

I would like to create an array of two columns such that the second column is generated from the first in an array.

This is the best I can do ... it simply stacks x and y, one on top of itself.

import numpy as np
from numpy import array

n= 100
results= np.array([])

for x in range(0, 100):  
    y= x*x
    new_row = [x, y]
    results = np.append(results, new_row)

I got this one to work... eventually!!!!

import numpy as np
from numpy import array

results= np.zeros(shape=(0,2))

for x in range(0, 100): 
    y = x*x
    row = array([[x, y]])
    results = np.concatenate((results, row))

I really like the code examples except my real "x**2" is actually several lines of code. — user8369515
– user8369515, Commented Mar 23, 2019 at 17:35
I've updated my answer - you could just write a function to calculate the other value. This would work the same in @sagarr's answer too as it could change to b = np.column_stack((a, func(a))) — David Buck
– David Buck, Commented Mar 23, 2019 at 18:14
thanks guys. I managed to get another solution (eventually!!!). I use R most of the time and am trying to o python.... — user8369515
– user8369515, Commented Mar 23, 2019 at 18:28

sagarr · Accepted Answer · 2019-03-23 17:33:27Z

2

np.column_stack can do the trick:

>>> a = np.array(range(100))
>>> b = np.column_stack((a, a**a))
>>> b
array([[                   0,                    1],
       [                   1,                    1],
       [                   2,                    4],
       [                   3,                   27],
       [                   4,                  256],
       [                   5,                 3125],
       [                   6,                46656],
       [                   7,               823543],
       [                   8,             16777216],
       [                   9,            387420489],
       [                  10,          10000000000],
       [                  11,         285311670611],
       [                  12,        8916100448256],
       [                  13,      302875106592253],

answered Mar 23, 2019 at 17:33

sagarr

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Comments

David Buck · Accepted Answer · 2019-03-23 18:12:01Z

1

A list comprehension could do that for you:

import numpy as np
results = np.array([[x, x**2] for x in range(100)])

That gives you an array of two columns:

Out[5]: 
array([[   0,    0],
       [   1,    1],
       [   2,    4],
       [   3,    9],
        ...

You've just commented that the function is more complex than just x**2 - one solution is simply to define it as a function, e.g.

import numpy as np

def func(x): # example functionality
    y = x**2
    y = y*2
    return y

results = np.array([[x, func(x)] for x in range(100)])

Out[13]: 
array([[    0,     0],
       [    1,     2],
       [    2,     8],
       [    3,    18],
       ...

edited Mar 23, 2019 at 18:12

answered Mar 23, 2019 at 17:22

David Buck

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