Create the schema from Part $2-$c in SQLite and populate it with data of at least $5$ students, $4$ courses, and $8$ enrollments $($at least

one of the students should not be enrolled in any courses and at least one course should have zero current enrollments$).$

Student$($StudentID$,$ Name, Address, GradYear$)$

Grade$($CName$,$ Studentip, CGrade$)$

Course$($CName$,$ Department, Credits$)$

You can submit code in this document or as a separate $.$py file. If you submit it separately, please clearly document which part

each answer matches. Please do not submit each part in a separate $.$py file.

a$)$ Create a view that joins the three tables, including all of the records from student table $($i$.$e$.,$ including the non$-$

enrolled students$).$

b$)$ Write and execute python code that uses that view to export all data into a single $.$txt file $($that is a $"$de$-$normalized"

$1$NF file with some redundancy present$).$ This code should include NULLs due to the non$-$enrolled students.

Include a screenshot of the output $.$txt file $($in addition to the python code$)$

c$)$ Add a new row to the de$-$normalized $.$txt file $($you can manually edit the $.$txt file from part b$)$ that violates the

following functional dependency:

CName $$ Credits

$($you can do so by creating a new record that repeats the course name but does not repeat the number of credits

associated with this course name$)$

d$)$ Write python code that will identify the values for which functional dependency was violated in your $.$txt file $($hint:

when the functional dependency is valid, there is only one unique value of Credits for each CName$).$ Your solution

should detect any violation of the CName $$ Credits functional dependency, not just your example. Keep in mind

that functional dependency is violated only in the pre$-$joined $.$txt file, not in the SQLite database, so this solution

must read data from $.$txt file.

e$)$ Suppose I have a new query: $Q_e$ : For every department, display the min, median, and max graduation years.

Use the view from Part $4-$a to re$-$write query $Q_e($i$.$e$.,$ replace the tables in the query's FROM clause by the

view and rewrite the rest of the query accordingly to produce an answer$).$

Use your $.$txt file containing de$-$normalized data from part$-$b to answer $Q_e$ with python instead of SQL$.$

Note that this solution should not use SQLite or SQL language. Your solution should work for any input,

not just for specific department in your data.