How to use the sample() function on a DataFrame in pandas
What is a DataFrame?
A DataFrame is a commonly used 2-dimensional data structure.
It is a table that consists of columns and rows and is used primarily as an object in pandas.
Reqiurements
This requires the pandas library as shown below.
import pandas as pd
Code
Example
A DataFrame can be formed as shown below. This one contains countries that have been put in different groups and are given a different a_score and b_score.
Both the scores are imaginary values for this example.
import pandas as pda_score = [4, 5, 7, 8, 2, 3, 1, 6, 9, 10]b_score = [1, 2, 3, 4, 5, 6, 7, 10, 8, 9]country = ['Pakistan', 'USA', 'Canada', 'Brazil', 'India', 'Beligium', 'Malaysia', 'Peru', 'England', 'Scotland']groups = ['A','A','B','A','B','B','C','A','C','C']df = pd.DataFrame({'group':groups, 'country':country, 'a_score':a_score, 'b_score':b_score})print(df)
The sample() function
The sample function randomly allows the selection of values from a DataFrame or series.
It is useful if you want to select a random sample from a distribution.
Syntax
The function prototype is as follows.
mysample = df.sample(n=5)
Parameter
-
number of values using the
nparameter(n = 3)or
-
a ratio with the
fracparameter(frac = 0.5)
Return value
The return value of this method is the requested sample.
Example
The following example prints four of the rows first, and then half of the rows as shown below.
import pandas as pda_score = [4, 5, 7, 8, 2, 3, 1, 6, 9, 10]b_score = [1, 2, 3, 4, 5, 6, 7, 10, 8, 9]country = ['Pakistan', 'USA', 'Canada', 'Brazil', 'India', 'Beligium', 'Malaysia', 'Peru', 'England', 'Scotland']groups = ['A','A','B','A','B','B','C','A','C','C']df = pd.DataFrame({'group':groups, 'country':country, 'a_score':a_score, 'b_score':b_score})print("the main dataframe")print(df)print("")print("sample_num")sample_num = df.sample(n=3)print(sample_num)print("")print("sample_frac")sample_frac = df.sample(frac=0.5)print(sample_frac)
