Delete rows if the one cell value does not match that of another dataset

I just started learning python yesterday for data analysis but have a problem. Hope somebody will help.

I have two datasets, each with two columns (can be made into one column) and 1000s of rows.

In each dataset, one column is a timestamp, the other is a measurement. I need to correlate the two measurements, but one of the datasets has extra measurements.

I want the code to read one row from the first (full) dataset, check if there is a corresponding measurement in the second dataset made at the same date/time, and if not then delete the extra row from the first dataset. I want to repeat this for all rows in the first dataset. Please see the image illustrating the principle.

In the image 1: the first row of dataset 1 is read and a corresponding measurement for the same time (07/05/2013 08:00) is found somewhere in dataset two, so no problem, and the same for row two. Row three in 1 is measured at 07/05/2013 08:30, but there is no measurement at 07/05/2013 08:30 in 2 so this row 3 from 1 should be deleted.

I need an if statement but I am confused by the mix between indexing cells/rows/columns in the same statement --- the condition checks one cell in a row against a column of another dataset, and then carries out an action not on the individual cell that was checked but the whole row from which the original cell originated.

Thank you