Python | Pandas Dataframe.sample ()

Michael Zippo

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