How to Join DataFrames Based on Timestamp Ranges?

Joining DataFrames Based on Column Value Ranges

In the given context, we have two dataframes, df_1 and df_2, where we need to merge them such that the timestamp column in df_1 falls within the start and end columns in df_2.

One approach to achieve this is by creating an interval index from the start and end columns in df_2. We can then use the get_loc method to obtain the corresponding event for each timestamp in df_1. Here's the Python code for this solution:

# Create interval index from df_2
df_2.index = pd.IntervalIndex.from_arrays(df_2['start'], df_2['end'], closed='both')

# Get corresponding event for each timestamp in df_1
df_1['event'] = df_1['timestamp'].apply(lambda x: df_2.iloc[df_2.index.get_loc(x)]['event'])

This will create a new column named event in df_1, which contains the corresponding events for each timestamp that falls within the specified ranges in df_2. The resulting joined dataframe will contain the following columns:

timestamp         A         B event

The output will look similar to:

            timestamp         A         B event
0 2016-05-14 10:54:33  0.020228  0.026572    E1
1 2016-05-14 10:54:34  0.057780  0.175499    E2
2 2016-05-14 10:54:35  0.098808  0.620986    E2
3 2016-05-14 10:54:36  0.158789  1.014819    E2
4 2016-05-14 10:54:39  0.038129  2.384590    E3

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