How to Select Rows from Pandas DataFrame?

10 Jul, 2020
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 framecname: represents column namecondition: represents condition on which rows has to be selected
Example 1:
# Importing pandas as pdfrom pandas import DataFrame  # Creating a data framecart = {'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 frameprint("Original data frame:\n")print(df)  # Selecting the product of Electronic Typeselect_prod = df.loc[df['Type'] == 'Electronic']  print("\n")  # Print selected rows based on the conditionprint("Selecting rows:\n")print (select_prod)
Output:Example 2:
# Importing pandas as pdfrom pandas import DataFrame  # Creating a data framecart = {'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 frameprint("Original data frame:\n")print(df)  # Selecting the product of HomeAppliances Typeselect_prod = df.loc[df['Type'] == 'HomeAppliances']  print("\n")  # Print selected rows based on the conditionprint("Selecting rows:\n")print (select_prod)
Output:Example 3:
# Importing pandas as pdfrom pandas import DataFrame  # Creating a data framecart = {'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 frameprint("Original data frame:\n")print(df)  # Selecting the product of Price greater # than or equal to 25000select_prod = df.loc[df['Price'] >= 25000]  print("\n")  # Print selected rows based on the conditionprint("Selecting rows:\n")print (select_prod)
Output:Example 4:
# Importing pandas as pdfrom pandas import DataFrame  # Creating a data framecart = {'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 frameprint("Original data frame:\n")print(df)  # Selecting the product of Price not # equal to 30000select_prod = df.loc[df['Price'] != 30000]  print("\n")  # Print selected rows based on the conditionprint("Selecting rows:\n")print (select_prod)
Output:
Python pandas-dataFrame
Python-pandas
Python
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