{"id":200692,"date":"2023-10-29T07:55:38","date_gmt":"2023-10-29T07:55:38","guid":{"rendered":"https:\/\/namso-gen.co\/blog\/how-to-filter-rows-in-pandas-based-on-column-value\/"},"modified":"2023-10-29T07:55:38","modified_gmt":"2023-10-29T07:55:38","slug":"how-to-filter-rows-in-pandas-based-on-column-value","status":"publish","type":"post","link":"https:\/\/namso-gen.co\/blog\/how-to-filter-rows-in-pandas-based-on-column-value\/","title":{"rendered":"How to filter rows in Pandas based on column value?"},"content":{"rendered":"

**To filter rows in Pandas based on column value, you can use boolean indexing.** This allows you to create a boolean array based on the condition you specify, and then use that array to filter the rows of the DataFrame.<\/p>\n

Let’s say you have a DataFrame called df and you want to filter rows where the ‘age’ column is greater than 30. You can achieve this by using the following code:<\/p>\n

“`python
\nfiltered_df = df[df[‘age’] > 30]
\n“`<\/p>\n

This code creates a boolean array where each element corresponds to whether the condition ‘age > 30’ is True or False for that row. Then, it uses this boolean array to filter out only the rows where the condition is True.<\/p>\n

This is a simple and powerful way to filter rows in Pandas based on any column value.<\/p>\n

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