You can use the argument replace=True within the pandas sample() function to randomly sample rows in a DataFrame with replacement:

#randomly select n rows with repeats allowed
df.sample(n=5, replace=True) 

By using replace=True, you allow the same row to be included in the sample multiple times.

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

Example: Sample Rows with Replacement in Pandas

Suppose we have the following pandas DataFrame that contains information about various basketball players:

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

Suppose we use the sample() function to randomly select a sample of rows:

#randomly select 6 rows from DataFrame (without replacement)
df.sample(n=6, random_state=0)

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

Notice that six rows have been selected from the DataFrame and none of the rows appear multiple times in the sample.

Note: The argument random_state=0 ensures that this example is reproducible.

Now suppose we use the argument replace=True to select a random sample of rows with replacement:

#randomly select 6 rows from DataFrame (with replacement)
df.sample(n=6, replace=True, random_state=0)

        team	points	assists	rebounds
4	E	14	12	6
7	H	28	4	12
5	F	11	9	5
0	A	18	5	11
3	D	14	9	6
3	D	14	9	6

Notice that the row with team “D” appears multiple times.

By using the argument replace=True, we allow the same row to appear in the sample multiple times.

Also note that we could select a random fraction of the DataFrame to be included in the sample by using the frac argument.

For example, the following example shows how to select 75% of rows to be included in the sample with replacement:

#randomly select 75% of rows (with  replacement)
df.sample(frac=0.75, replace=True, random_state=0) 

        team	points	assists	rebounds
4	E	14	12	6
7	H	28	4	12
5	F	11	9	5
0	A	18	5	11
3	D	14	9	6
3	D	14	9	6

Notice that 75% of the number of rows (6 out of 8) were included in the sample and at least one of the rows (with team “D”) appeared in the sample twice.

Note: You can find the complete documentation for the pandas sample() function .

The following tutorials explain how to perform other common sampling methods in Pandas: