Objective:

Learn how to use the where() function in Pandas to conditionally replace values in a DataFrame.


Task : Replacing Values Using where

  1. Use the where() function to replace all Purchase Amount (USD) values below $50 with NaN.

  2. Display the rows of the modified DataFrame.


Python Code:

#Step: 1: To see the full number of rows and columns of df dataframe:

import pandas as pd

pd.set_option('display.max_rows', None)   

pd.set_option('display.max_columns', None)

df


#Step: 2 use where function to do the rest of the tasks:

import pandas as pd

import numpy as np

df['Purchase Amount (USD)'] = df['Purchase Amount (USD)'].where(df['Purchase Amount (USD)'] >= 50, np.nan)

df