How to Filter Pandas DataFrames by Date Ranges?

Filtering Pandas DataFrames by Date Ranges

One common task in data analysis is to filter a DataFrame based on specific date ranges. Suppose you have a DataFrame with a 'date' column and you need to extract rows within the next two months. Here are the recommended approaches:

Using .loc or .iloc

If the 'date' column is the index of the DataFrame, you can use .loc for label-based indexing or .iloc for positional indexing. For instance:

This code returns all rows where the 'date' index falls between March 1st and April 30th, 2023.

If the 'date' Column is Not the Index

In this case, consider:

• Making the 'date' column the index: Convert the 'date' column to the index using the .set_index() method. This will allow you to use .loc or .iloc as described above.
• Filtering using logical operators: Use the > (greater than) and < (less than) operators in conjunction with & (logical AND) to compare dates and filter the DataFrame. For example:

General Note:

Kindly note that .ix indexing is deprecated in favor of .loc and .iloc. For further details on indexing and selection in Pandas, please refer to the provided documentation link in the answer section.

The above is the detailed content of How to Filter Pandas DataFrames by Date Ranges?. For more information, please follow other related articles on the PHP Chinese website!