pandas.DataFrame.loc
is a function used to select rows from Pandas DataFrame based on the condition provided. In this article, let’s learn to select the rows from Pandas DataFrame based on some conditions.
Syntax: df.loc[df[‘cname’] ‘condition’]
Parameters:
df: represents data frame
cname: represents column name
condition: represents condition on which rows has to be selected
Example 1:
# Importing pandas as pd from pandas import DataFrame # Creating a data frame cart = { 'Product' : [ 'Mobile' , 'AC' , 'Laptop' , 'TV' , 'Football' ], 'Type' : [ 'Electronic' , 'HomeAppliances' , 'Electronic' , 'HomeAppliances' , 'Sports' ], 'Price' : [ 10000 , 35000 , 50000 , 30000 , 799 ] } df = DataFrame(cart, columns = [ 'Product' , 'Type' , 'Price' ]) # Print original data frame print ( "Original data frame:\n" ) print (df) # Selecting the product of Electronic Type select_prod = df.loc[df[ 'Type' ] = = 'Electronic' ] print ( "\n" ) # Print selected rows based on the condition print ( "Selecting rows:\n" ) print (select_prod) |
Output:
Example 2:
# Importing pandas as pd from pandas import DataFrame # Creating a data frame cart = { 'Product' : [ 'Mobile' , 'AC' , 'Laptop' , 'TV' , 'Football' ], 'Type' : [ 'Electronic' , 'HomeAppliances' , 'Electronic' , 'HomeAppliances' , 'Sports' ], 'Price' : [ 10000 , 35000 , 50000 , 30000 , 799 ] } df = DataFrame(cart, columns = [ 'Product' , 'Type' , 'Price' ]) # Print original data frame print ( "Original data frame:\n" ) print (df) # Selecting the product of HomeAppliances Type select_prod = df.loc[df[ 'Type' ] = = 'HomeAppliances' ] print ( "\n" ) # Print selected rows based on the condition print ( "Selecting rows:\n" ) print (select_prod) |
Output:
Example 3:
# Importing pandas as pd from pandas import DataFrame # Creating a data frame cart = { 'Product' : [ 'Mobile' , 'AC' , 'Laptop' , 'TV' , 'Football' ], 'Type' : [ 'Electronic' , 'HomeAppliances' , 'Electronic' , 'HomeAppliances' , 'Sports' ], 'Price' : [ 10000 , 35000 , 50000 , 30000 , 799 ] } df = DataFrame(cart, columns = [ 'Product' , 'Type' , 'Price' ]) # Print original data frame print ( "Original data frame:\n" ) print (df) # Selecting the product of Price greater # than or equal to 25000 select_prod = df.loc[df[ 'Price' ] > = 25000 ] print ( "\n" ) # Print selected rows based on the condition print ( "Selecting rows:\n" ) print (select_prod) |
Output:
Example 4:
# Importing pandas as pd from pandas import DataFrame # Creating a data frame cart = { 'Product' : [ 'Mobile' , 'AC' , 'Laptop' , 'TV' , 'Football' ], 'Type' : [ 'Electronic' , 'HomeAppliances' , 'Electronic' , 'HomeAppliances' , 'Sports' ], 'Price' : [ 10000 , 35000 , 30000 , 30000 , 799 ] } df = DataFrame(cart, columns = [ 'Product' , 'Type' , 'Price' ]) # Print original data frame print ( "Original data frame:\n" ) print (df) # Selecting the product of Price not # equal to 30000 select_prod = df.loc[df[ 'Price' ] ! = 30000 ] print ( "\n" ) # Print selected rows based on the condition print ( "Selecting rows:\n" ) print (select_prod) |
Output: