In this post I’m going to run through a function in Python that can quickly complete calculations on numbers in an array

Let’s get into it!

Let’s start be importing numpy and defining an array of the radius of the solar system planets (in km) as radii:

import numpy as np

radii = np.array([2439.7, 6051.8, 6371, 3389.7, 69911, 58232, 25362, 24622])

Now, let’s test the equation that will be used on one number (r):

r = 10
volume = 4/3 * np.pi * r ** 3
print(volume)

>>> 4188.790204786391

After checking that the function is evaluating correctly, we can calcualte the volume of the planets:

volumes = 4/3 * np.pi * radii ** 3
print(volumes)

>>> [6.08272087e+10 9.28415346e+11 1.08320692e+12 1.63144486e+11
     1.43128181e+15 8.27129915e+14 6.83343557e+13 6.25257040e+13]

if we had the radius of a million planets, we could calculate their volumes as quick as typing the below function:

radii = np.random.randint(1,1000,1000000) # creates an array of 1,000,000 elements of random integers between 1 and 1,000

volumes = 4/3 * np.pi * radii ** 3
print(volumes)

>>> [2.69228478e+09 8.86803480e+08 1.56345757e+06 ... 3.40057454e+08
     1.91232096e+09 5.42675431e+08] 

This calculation could have been completed using other means, like a for loop, but that would take so much time and computing power.

Numpy is a very powerful tool to conduct calcualtions. Since a single numpy array, can only contain a single data type, unlike lists or tuples which can contain many data types, the calculation is completed very quickly in fractions of a second.