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Creating a DataFrame with random numbers in Pandas

schedule Aug 12, 2023
Last updated
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To create a DataFrame with random numbers in Pandas, use one of NumPy's functions that generate random numbers:

  • np.random.randint(~) for random integers

  • np.random.default_rng().uniform(~) for random floats

DataFrame with random integers

First, we generate a 2 by 3 NumPy array of random integers:

arr_random = np.random.randint(low=2, high=10, size=(2,3))
arr_random
array([[8, 7, 2],
[2, 3, 6]])

Here, the lower bound is 2 (inclusive) and the upper bound is 10 (exclusive).

We can then initialise a DataFrame using arr_random like so:

pd.DataFrame(arr_random, columns=["A","B","C"], index=["a","b"])
A B C
a 4 4 2
b 3 7 2

DataFrame with random floats

First, we generate a 2 by 3 NumPy array of random floats:

arr_random = np.random.default_rng().uniform(low=5,high=10,size=[2,3])
arr_random
array([[7.04518804, 9.09625941, 5.29815702],
[7.77653952, 9.22222284, 9.0035309 ]])

Note the following:

  • all floats are larger than or equal to 5.

  • all floats are less than 10.

To initialise a DataFrame using arr_random:

pd.DataFrame(arr_random, columns=["A","B","C"])
A B C
0 7.927711 5.560577 5.918331
1 8.487705 9.111051 9.699249
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Published by Isshin Inada
Edited by 0 others
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