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Creating a DataFrame with random numbers in Pandas
schedule Aug 12, 2023
Last updated local_offer
Tags Python●Pandas
tocTable of Contents
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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 integersnp.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 Ca 4 4 2b 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 C0 7.927711 5.560577 5.9183311 8.487705 9.111051 9.699249
Published by Isshin Inada
Edited by 0 others
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