The following data science interview question is testing for your ability to interpret a 'real life' dataset and quickly extract an insight. This particular question asks for a solution in Python (using Pandas), but it would also be common to solve this in SQL or R.
Below is a table schema for a P2P messaging application. The table contains send/receive message data for the application's users.
||date of the message sent/received, format is 'YYYY-mm-dd'
||timestamp of the message sent/received, epoch seconds
||id of the message sender
||id of the message receiver
Using python (pandas), how would you find the fraction of messages that get a response within 5 minutes? For simplicity, let's limit data to March 1, 2018.
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