How to Get Evenly Spaced Numbers Over a Specified Range in Python with Numpy

In this article, we show how to get evenly spaced numbers over a specified range in Python with numpy.

Numpy has a built-in function called linspace that allows us to get evenly spaced numbers over 2 specified points.

This is a great tool if you want a wide range of points over a specified range. It could be a statistical measure or for plotting a graph, etc.

So how can this be done in Python with numpy?

The code below gets 10 evenly spaced numbers from 0 to 5.

>>> numbers= np.linspace(0,5,10) >>> numbers array([ 0. , 0.55555556, 1.11111111, 1.66666667, 2.22222222, 2.77777778, 3.33333333, 3.88888889, 4.44444444, 5. ]) >>> numbers2= np.linspace(0,5,11) >>> numbers2 array([ 0. , 0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. , 4.5, 5. ])

So, first, we must import numpy as np.

We then create a variable named numbers and set it equal to, np.linspace(0,5,10)

This produces an array of 10 numbers including 0 and including 10.

We then create another variable, numbers2, that contains 11 points from 0 to 10.

Now let's say we want a lot of points over a specified range. Let's say that we want 100 data points of evenly spaced numbers from 0 to 10.

The code to do this is shown below.

>>> import numpy as np >>> numbers= np.linspace(0,10,100) >>> numbers array([ 0. , 0.1010101 , 0.2020202 , 0.3030303 , 0.4040404 , 0.50505051, 0.60606061, 0.70707071, 0.80808081, 0.90909091, 1.01010101, 1.11111111, 1.21212121, 1.31313131, 1.41414141, 1.51515152, 1.61616162, 1.71717172, 1.81818182, 1.91919192, 2.02020202, 2.12121212, 2.22222222, 2.32323232, 2.42424242, 2.52525253, 2.62626263, 2.72727273, 2.82828283, 2.92929293, 3.03030303, 3.13131313, 3.23232323, 3.33333333, 3.43434343, 3.53535354, 3.63636364, 3.73737374, 3.83838384, 3.93939394, 4.04040404, 4.14141414, 4.24242424, 4.34343434, 4.44444444, 4.54545455, 4.64646465, 4.74747475, 4.84848485, 4.94949495, 5.05050505, 5.15151515, 5.25252525, 5.35353535, 5.45454545, 5.55555556, 5.65656566, 5.75757576, 5.85858586, 5.95959596, 6.06060606, 6.16161616, 6.26262626, 6.36363636, 6.46464646, 6.56565657, 6.66666667, 6.76767677, 6.86868687, 6.96969697, 7.07070707, 7.17171717, 7.27272727, 7.37373737, 7.47474747, 7.57575758, 7.67676768, 7.77777778, 7.87878788, 7.97979798, 8.08080808, 8.18181818, 8.28282828, 8.38383838, 8.48484848, 8.58585859, 8.68686869, 8.78787879, 8.88888889, 8.98989899, 9.09090909, 9.19191919, 9.29292929, 9.39393939, 9.49494949, 9.5959596 , 9.6969697 , 9.7979798 , 9.8989899 , 10. ])

So just as before, we import numpy as np.

We then create a variable named numbers and set it equal to, np.linspace(0,10,100)

What this line of code does is it gets 100 data points of evenly spaced numbers from 0 to 10.

The linspace() function is a great tool for data science and analysis in Python. It can give us a broad range of analytical tools so that we can great numerous data points for any given set of numbers.

And this is how we can obtain evenly spaced numbers over a specified range in Python using Numpy.

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