How to Create Pandas DataFrame with Random Data

---

You can use the following basic syntax to create a pandas DataFrame that is filled with random integers:

df = pd.DataFrame(np.random.randint(0,100,size=(10, 3)), columns=list('ABC'))

This particular example creates a DataFrame with 10 rows and 3 columns where each value in the DataFrame is a random integer between 0 and 100.

The following examples shows how to use this syntax in practice.

Example 1: Create Pandas DataFrame with Random Data

The following code shows how to create a pandas DataFrame with 10 rows and 3 columns where each value in the DataFrame is a random integer between 0 and 100:

import pandas as pd
import numpy as np

#create DataFrame
df = pd.DataFrame(np.random.randint(0,100,size=(10, 3)), columns=list('ABC')) 

#view DataFrame
print(df)

    A   B   C
0  72  70  27
1  87  85   7
2   4  42  84
3  85  87  63
4  79  72  30
5  96  99  79
6  26  47  90
7  35  69  56
8  42  47   0
9  97   4  59

Note that each time you run this code, the random integers in the DataFrame will be different.

If you’d like to create a reproducible example where the random integers are the same each time, you can use the following piece of code immediately before you create the DataFrame:

np.random.seed(0)

Now each time you run the code, the random integers in the DataFrame will be the same.

Example 2: Add Column of Random Data to Existing DataFrame

Suppose we have the following existing pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],
                   'points': [18, 22, 19, 14, 14, 11, 20, 28],
                   'assists': [5, 7, 7, 9, 12, 9, 9, 4],
                   'rebounds': [11, 8, 10, 6, 6, 5, 9, 12]})

#view DataFrame
print(df)

  team  points  assists  rebounds
0    A      18        5        11
1    B      22        7         8
2    C      19        7        10
3    D      14        9         6
4    E      14       12         6
5    F      11        9         5
6    G      20        9         9
7    H      28        4        12

We can use the following code to add a new column called “rand” that contains random integers between 0 and 100:

import numpy as np

#add 'rand' column that contains 8 random integers between 0 and 100
df['rand'] = np.random.randint(0,100,size=(8, 1))

#view updated DataFrame
print(df)

  team  points  assists  rebounds  rand
0    A      18        5        11    47
1    B      22        7         8    64
2    C      19        7        10    82
3    D      14        9         6    99
4    E      14       12         6    88
5    F      11        9         5    49
6    G      20        9         9    29
7    H      28        4        12    19

Notice that the new column “rand” has been added to the existing DataFrame.

Additional Resources

The following tutorials explain how to perform other common operations in pandas:

How to Impute Missing Values in Pandas
How to Replace NaN Values with Zero in Pandas
How to Check if Cell is Empty in Pandas