How to Efficiently Join DataFrames Based on Datetime Ranges in Pandas?

Joining Dataframes with Column Values within Range

Given two dataframes, df_1 and df_2, where df_1 contains a datetime column and values A and B, and df_2 contains ranges of datetime values and corresponding event information, a common task is to merge these dataframes based on the condition that the datetime values in df_1 lie within the ranges specified in df_2.

A straightforward approach to achieving this involves creating an interval index from the start and end columns of df_2 and setting the closed parameter to both. This ensures that the ranges are inclusive.

Once the interval index is created, we can use the get_loc method of the IntervalIndex to locate the range containing the datetime value from df_1 for each row.

By applying this function to each value in the datetime column of df_1, we can populate a new column, event, which contains the corresponding event information from df_2 for each row in df_1.

This approach offers an efficient way to join dataframes based on a range condition by using the powerful interval indexing capabilities provided by Pandas. The output will be a dataframe with all the columns from both df_1 and df_2, with the event column providing the matched events for each row in df_1.

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