Beta

## Course Notes

Use this workspace to take notes, store code snippets, or build your own interactive cheatsheet! For courses that use data, the datasets will be available in the `datasets`

folder.

```
# Import any packages you want to use here
import pandas as pd
```

## Problem

You have been given a dataset containing information about students in a school. The dataset includes the following columns:

- 'Name': Name of the student (string)
- 'Age': Age of the student (numerical)
- 'Gender': Gender of the student (categorical: 'Male' or 'Female')
- 'Grade': Grade level of the student (ordinal categorical: 'A', 'B', 'C', 'D', or 'F')
- 'Subject': Subject of study (categorical: 'Math', 'Science', 'English', 'History', or 'Art')
- 'Score': Score obtained by the student in the subject (numerical)

You are required to perform the following tasks:

- Explore the target variable 'Grade' and analyze its distribution in the dataset.
- Convert the 'Gender' column to a categorical data type using pandas.
- Convert the 'Grade' column to an ordinal categorical data type using pandas.
- Group the data by 'Subject' and calculate the average score for each subject.
- Group the data by 'Grade' and 'Subject' and calculate the maximum score for each grade-subject combination.

Feel free to use pandas and any other necessary libraries to solve this problem. Good luck!

```
# Import the csv file
df = pd.read_csv('student.csv')
```