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Download the attached zip file (ml-1m.zip) and extract the files to your development machine. Study theREADME file to understand the contents.
Using Python and SQLite3 exclusively, create 3NF database tables from the three “.DAT” files. They are in CSV format, but are not separated by commas. They use “::” to separate each value. Do not use the PythonCSV class.
TheMovies table (frommovies.dat) will contain four columns:MovieId,MovieTitle,Year, andCategory. You will need to separate the year from the title and store the year in its own column. You will also need to separate the repeating groups inCategory. A separate table is preferred for theMovie-Category relationship.
TheUser table (fromusers.dat) will contain columns forUserID,Gender,AgeCode,Occupation, andZipcode.
TheRatings table will contain columns forUserID,MovieID,Rating, andTimestamp.
Study theREADME file included in the zip. Create extra tables that decode the age and occupation. Include column constraints in your table definitions that correspond to theREADME file.
After all the tables are loaded, create at least two interesting queries about the data and execute the queries via Python. Describe your results.
Be sure to include in yourstdout output, any messages describing what’s going on in the program, i.e. number of records loaded into each table.
Include the following in a Word document to submit:
Your Python source code for all of the above.
STDOUT output.
Analysis of your queries.

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