 
  Data Structure Data Structure
 Networking Networking
 RDBMS RDBMS
 Operating System Operating System
 Java Java
 MS Excel MS Excel
 iOS iOS
 HTML HTML
 CSS CSS
 Android Android
 Python Python
 C Programming C Programming
 C++ C++
 C# C#
 MongoDB MongoDB
 MySQL MySQL
 Javascript Javascript
 PHP PHP
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Python - Filter Rows Based on Column Values with query function in Pandas?
To filter rows based on column values, we can use the query() function. In the function, set the condition through which you want to filter records. At first, import the required library −
import pandas as pd
Following is our data with Team Records −
Team = [['India', 1, 100],['Australia', 2, 85],['England', 3, 75],['New Zealand', 4 , 65],['South Africa', 5, 50],['Bangladesh', 6, 40]]
Create a DataFrame from above and add columns as well −
dataFrame = pd.DataFrame(Team, columns=['Country', 'Rank', 'Points'])
Use query() to filter records with “Rank” equal to 5 −
dataFrame.query("Rank == 5")) Example
Following is the complete code −
import pandas as pd # data in the form of list of team rankings Team = [['India', 1, 100],['Australia', 2, 85],['England', 3, 75],['New Zealand', 4 , 65],['South Africa', 5, 50],['Bangladesh', 6, 40]] # Creating a DataFrame and add columns dataFrame = pd.DataFrame(Team, columns=['Country', 'Rank', 'Points']) print"DataFrame...\n",dataFrame # using query to filter rows print"\nFetch Team with Rank 5..\n",dataFrame.query("Rank == 5")  Output
This will produce the following output −
DataFrame... Country Rank Points 0 India 1 100 1 Australia 2 85 2 England 3 75 3 New Zealand 4 65 4 South Africa 5 50 5 Bangladesh 6 40 Fetch Team with Rank 5.. Country Rank Points 4 South Africa 5 50
Example
Let us see another example. Here, we have a different condition to filter rows −
import pandas as pd # data in the form of list of team rankings Team = [['India', 1, 100],['Australia', 2, 85],['England', 3, 75],['New Zealand', 4 , 65],['South Africa', 5, 50],['Bangladesh', 6, 40]] # Creating a DataFrame and add columns dataFrame = pd.DataFrame(Team, columns=['Country', 'Rank', 'Points']) print"DataFrame...\n",dataFrame # using query to filter rows print"\nFetch Team with points above 70 and Rank less than 3..\n" print(dataFrame.query("Points > 70 and Rank <3"))  Output
This will produce the following output −
DataFrame... Country Rank Points 0 India 1 100 1 Australia 2 85 2 England 3 75 3 New Zealand 4 65 4 South Africa 5 50 5 Bangladesh 6 40 Fetch Team with points above 70 and Rank less than 3.. Country Rank Points 0 India 1 100 1 Australia 2 85
Advertisements
 