Filtering Data using Comparison Operators in Python
Pandas is a powerful library for data manipulation in Python that offers several functions for filtering data based on comparison operators. Filtering data is a process of selecting a subset of data that meets certain criteria, and Pandas provides several built-in functions for filtering data based on comparison operators. In this article, we will explain how to filter data using comparison operators in Pandas with practical examples.
Let’s see the examples:
Now, let’s say we want to filter the DataFrame to only include rows where the Age column is greater than or equal to 30. We can use the greater than or equal to (>=) operator to filter the data as follows:
Similarly, we can use other comparison operators like less than (<), greater than (>), equal to (==), and not equal to (!=) to filter data based on specific criteria.
We can also filter data based on multiple conditions by using the and (&) and or (|) operators. For example, let’s say we want to filter the DataFrame to only include rows where the Age is greater than or equal to 30 and the Salary is greater than or equal to 60000. We can use the following code to achieve this:
Filter rows where the Salary is less than 40000:
Filter rows where the Name is not ‘Charlie’:
Filter rows where the Age is between 25 and 40:
Filter rows where the Salary is greater than or equal to 80000 or the Age is less than 20:
Filter rows where the Name starts with ‘A’:
In conclusion, filtering data using comparison operators in Pandas is a powerful tool for data analysis. By using the appropriate comparison operators, you can filter data based on specific criteria quickly and efficiently. With the help of the examples provided in this article, you can get started with filtering data using comparison operators in Pandas and gain valuable insights from your data.