Data Manipulation using Pandas Library

This dataset includes scores from three test scores of students at a (fictional) public school and a variety of personal and socio-economic factors that may have interaction effects upon them.

Data Dictionary (column description)

1. Gender: Gender of the student (male/female)
2. EthnicGroup: Ethnic group of the student (group A to E)
3. ParentEduc: Parent(s) education background (from some_highschool to master's degree)
4. LunchType: School lunch type (standard or free/reduced)
5. TestPrep: Test preparation course followed (completed or none)
6. ParentMaritalStatus: Parent(s) marital status (married/single/widowed/divorced)
7. PracticeSport: How often the student parctice sport (never/sometimes/regularly))
8. IsFirstChild: If the child is first child in the family or not (yes/no)
9. NrSiblings: Number of siblings the student has (0 to 7)
10. TransportMeans: Means of transport to school (schoolbus/private)
11. WklyStudyHours: Weekly self-study hours(less that 5hrs; between 5 and 10hrs; more than 10hrs)
12. MathScore: math test score(0-100)
13. ReadingScore: reading test score(0-100)
14. WritingScore: writing test score(0-100)