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
The recommended way to create random integers with NumPy these days is to use numpy.random.Generator.integers
. (documentation)
import numpy as np
import pandas as pd
rng = np.random.default_rng()
df = pd.DataFrame(rng.integers(0, 100, size=(100, 4)), columns=list('ABCD'))
df
----------------------
A B C D
0 58 96 82 24
1 21 3 35 36
2 67 79 22 78
3 81 65 77 94
4 73 6 70 96
... ... ... ... ...
95 76 32 28 51
96 33 68 54 77
97 76 43 57 43
98 34 64 12 57
99 81 77 32 50
100 rows × 4 columns
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
.. .. .. .. ..