python pandas keep rows with condition

title: filtering rows in python pandas dataframe based on conditions
introduction:
python pandas is a powerful data manipulation library that provides numerous tools for working with structured data. one common task is filtering rows in a dataframe based on certain conditions. in this tutorial, we will explore how to use pandas to keep rows in a dataframe that meet specific criteria.
first, ensure that you have pandas installed. if not, you can install it using:
now, import pandas into your python script or jupyter notebook:
let's create a simple dataframe for demonstration purposes:
now, let's say we want to keep only the rows where the age is greater than 25. we can achieve this using boolean indexing:
you can also filter rows based on multiple conditions. for example, let's keep rows where both age is greater than 25 and salary is less than 60000:
if you want to reset the index of the filtered dataframe, you can use the reset_index method:
filtering rows in a pandas dataframe based on conditions is a fundamental skill for data analysis and manipulation. by using boolean indexing, you can easily keep only the rows that meet specific criteria. this tutorial covered the basics, but pandas offers a wide range of functions for more advanced filtering and manipulation. explore the official pandas documentation for more details: pandas documentation.
now you have the knowledge to efficiently filter rows in a pandas dataframe based on your desired conditions.
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