Python | Pandas Dataframe.sample ()

Pandas sample() is used to generate a sampled random row or column from the caller’s data frame.

Syntax:

DataFrame.sample (n = None, frac = None, replace = False, weights = None, random_state = None, axis = None)

Parameters :

n: int value, Number of random rows to generate.
frac: Float value, Returns (float value * length of data frame values). frac cannot be used with n.
replace: Boolean value, return sample with replacement if True.
axis: 0 or ’row’ for Rows and 1 or ’column’ for Columns.

Return type: a new object of the same type as the caller.

To load CSV file to use, click here.

Example # 1: Random string from data frame

In this example, two random strings are generated by the .sample () method and compared later.

# pandas package import import pandas as pd   # create data frame from CSV file data = pd.read_csv ( "employees.csv" )   # generate one line row1 = data.sample (n = 1 )   # display row1   # create another row row2 = data.sample (n = 1 )    # display row2

Output:
As shown in the output image, the two generated rows of random samples are different from each other.

Example # 2: Generating 25% of a sample of a data frame
In this example, 25% of a random sample of data is generated from a data frame.

# pandas package import import pandas as pd   # create data frame from CSV file data = pd.read_csv ( " employees.csv " ) < / code>   # generate one line rows = data.sample (frac = . 25 )   # check if the sample is 0.25x or not   if ( 0.25 * ( len (data)) = = len (rows)): print ( "Cool" ) print ( len (data), len (rows))   # display rows

Output:
As shown in the output image, the length of the generated sample is 25% of the data frame. Also the sample is generated randomly.