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 here.
Additional Resources
The following tutorials explain how to perform other common sampling methods in Pandas:
How to Perform Stratified Sampling in Pandas
How to Perform Cluster Sampling in Pandas