Blocking experimental data

You are working with a manufacturing firm that wants to conduct some experiments on worker productivity. Their dataset only contains 100 rows, so it's important that experimental groups are balanced.

This sounds like a great opportunity to use your knowledge of blocking to assist them. They have provided a productivity_subjects DataFrame. Split the provided dataset into two even groups of 50 entries each.

The libraries numpy and pandas have been imported as np and pd respectively.

Randomly select 50 subjects from the productivity_subjects DataFrame into a new DataFrame block_1 without replacement.
Set a new column, block to 1 for the block_1 DataFrame.
Assign the remaining subjects to a DataFrame called block_2 and set the block column to 2 for this DataFrame.
Concatenate the blocks together into a single DataFrame, and print the count of each value in the block column to confirm the blocking worked.

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Blocking experimental data

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