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I know that if I use randn,

import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randn(100, 4), columns=list('ABCD'))

gives me what I am looking for, but with elements from a normal distribution. But what if I just wanted random integers?

randint works by providing a range, but not an array like randn does. So how do I do this with random integers between some range?

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numpy.random.randint accepts a third argument (size) , in which you can specify the size of the output array. You can use this to create your DataFrame -

df = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))

Here - np.random.randint(0,100,size=(100, 4)) - creates an output array of size (100,4) with random integer elements between [0,100) .


Demo -

import numpy as np
import pandas as pd
df = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))

which produces:

     A   B   C   D
0   45  88  44  92
1   62  34   2  86
2   85  65  11  31
3   74  43  42  56
4   90  38  34  93
5    0  94  45  10
6   58  23  23  60
..  ..  ..  ..  ..

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