How To Use A List Of Values To Select Rows from Pandas Dataframe – Definitive Guide

Pandas allow you to select a subset of rows based on column or row values.

You can use a list of values to select rows from the pandas dataframe using the df[df[‘column_name’].isin([list_of_values])] statement.

This tutorial teaches you how to use a list of values to select rows from the Pandas dataframe.

If You’re in Hurry

You can use the isin() method to use a list of values to select specific rows from the pandas dataframe.

import pandas as pd 

# List of Tuples
users = [ ('Shivam', 'Pandey', 'India', 1),
             ('Kumar', 'Ram' , 'US', 2 ),
         ('Felix','John' , 'Germany', 3 ),
         ('Michael','John' , 'India', 1 ),
              ]

#Create a DataFrame object
df = pd.DataFrame(  users, 
                    columns = ['First Name' , 'Last Name', 'Country', 'Country_Code']
                    ) 

df[df['Country_Code'].isin([1, 2])]

The rows with country_code 1 and 2 are selected and displayed.

Dataframe Will Look Like

	First Name	Last Name	Country	Country_Code
0	Shivam	Pandey	India	1
1	Kumar	Ram	US	2
3	Michael	John	India	1

If you want to understand details, Read on..

Different methods are available to use a list of values to select a subset of rows from the pandas dataframe.

Let us learn each method in detail.

Sample Dataframe

First, let us create a sample dataframe used for demonstration purposes.

import pandas as pd 

# List of Tuples
users = [ ('Shivam', 'Pandey', 'India', 1),
             ('Kumar', 'Ram' , 'US', 2 ),
         ('Felix','John' , 'Germany', 3 ),
         ('Michael','John' , 'India', 1 ),
              ]

#Create a DataFrame object
df = pd.DataFrame(  users, 
                    columns = ['First Name' , 'Last Name', 'Country', 'Country_Code']
                    ) 

df

Dataframe Will Look Like

	First Name	Last Name	Country	Country_Code
0	Shivam	Pandey	India	1
1	Kumar	Ram	US	2
2	Felix	John	Germany	3
3	Michael	John	India	1

Using isin

You can use the isin() method to use a list of values to select rows from the dataframe.

The condition df['Country_Code'].isin([1, 2])] creates a Mask for each row with True where the Country_Code is 1 or 2 and False for other country_codes. Based on these masks, the df[ ] will return the rows where the mask is True.

Code

The following code will return the rows from the dataframe where the country_code is in 1 or 2.

df[df['Country_Code'].isin([1, 2])]

Dataframe Will Look Like

	First Name	Last Name	Country	Country_Code
0	Shivam	Pandey	India	1
1	Kumar	Ram	US	2
3	Michael	John	India	1

Using Query

This section teaches you how to use the query() method to use a list of values to select rows from the pandas dataframe.

The query() method queries the coloums of the dataframe with a boolean expression. It returns the rows where the expression evaluates to True.

It is similar to using SQL query statements.

Note: This method will throw an error when the column name contains space.

Code

The following code demonstrates how to use the query() method to use a list of values to select rows conditionally from the pandas dataframe.

df.query('Country_Code in [1, 2]')

Dataframe Will Look Like

The rows with country codes 1 and 2 are selected and displayed.

	First Name	Last Name	Country	Country_Code
0	Shivam	Pandey	India	1
1	Kumar	Ram	US	2
3	Michael	John	India	1

Select Rows With Values Not In the list

This section demonstrates how to use the isin() method to select rows with values that are not present in the list. In other words, it is also known as excluding a list of rows.

You can use the isin() method and the ~ operator to specify NOT IN.

It’ll return the rows that don’t match the values specified in the list.

Code

The following code selects rows with country codes, not in 1 and 2.

df[~df['Country_Code'].isin([1, 2])]

Dataframe Will look Like

	First Name	Last Name	Country	Country_Code
2	Felix	John	Germany	3

Select Rows By Index In List Of Values

To select rows using a list of its indexes, you can use the iloc statement.

You can pass the list of indexes to the iloc, and it’ll return those rows. An error will be raised if the specified indexes are out of range.

Code
The following code demonstrates how to select rows by the index in the values list.

df.iloc[[1,3]]

Dataframe Will Look Like

The rows with indexes 1 and 3 are selected and displayed.

	First Name	Last Name	Country	Country_Code
1	Kumar	Ram	US	2
3	Michael	John	India	1

Conclusion

You’ve learned how to use a list of values to select rows from the pandas dataframe.

Also, you’ve learned how to use the isin() method to exclude a specific list of rows from the pandas dataframe.

You May Also Like

• How To Select Rows From Pandas Dataframe
• How To Select Rows From Pandas Dataframe Based On Column Values
• How To Select Columns From Pandas Dataframe