Assignment Specification $($Use PYTHON only!$)$

Description: This program will use Pandas to process MovieLens movie rating data.

Input: No user provided input. Data from files: movies.csv$,$ tags.csv$,$ and ratings.csv

Please, refer to the README.txt file for details. All the files are in a single zip file on Canvas.

Output:

See details in the Procedure.

Procedure:

Load the three datasets movies.csv$,$ tags.csv$,$ and ratings.csv into three pandas DataFrames.

Print the first $5$ rows of each of the $3$ DataFrames. Leave a blank line before each DataFrame

listing and print an appropriate heading.

Create a single pandas DataFrame containing movieid; title; genres $($all from movies.csv$)$; rating

$($from ratings.csv$)$; tag $($from tags.csv$).$ Make sure every row is referring to the same movieid.

Count the number of movies with rating $5$ and then print $10$ of them $($any $10).$ For each movie,

print title, genres and tag.

Count the number of movies with rating $0\mathrm{.}5$ and then print $10$ of them $($any $10).$ For each movie,

print title, genres and tag.

Print the $3$ most frequent tags with the genres they are related to$.$ For each tag, print tag, genres

and count.

Write $1$ page with your interpretation of the results. This report is NOT a description of the

process or the code, but an interpretation of the results.

Submit the $.$py with the code and a word$/$pdf with the interpretation.