[TOC] ## Solution --- [Pandas](#pandas) [Database](#database) # pandas ### Approach: Group By and Count Distinct #### Intuition In pandas, we can use the groupby function on the `'teacher_id'` column and then count the unique `'subject_id'` per teacher using the `.nunique()` function. #### Algorithm To calculate the number of unique subjects each teacher teaches in the university, we first need to group by `'teacher_id'` and then count the number of unique `'subject_id'`. The renaming of the column is done for the output to match the required format (similar to the `AS` keyword in SQL). Note that we need to specify `axis=1` for it, as we are renaming a column and not a row. Here is an example to help solidify the intuition behind the algorithm: The original table `teacher`:

teacher_id	subject_id	dept_id
1	2	3
1	2	4
1	3	3
2	1	1
2	2	1
2	3	1
2	4	1

The table after grouping by `teacher_id` and counting distinct `subject_id`:

teacher_id	cnt
1	2
2	4

#### Implementation
--- # database ### Approach: Group By and Count Distinct #### Intuition In SQL, the query to count the number of unique subjects each teacher teaches involves grouping by the `teacher_id` and then counting the distinct `subject_id`. #### Algorithm This task requires counting the number of unique subjects each teacher teaches in the university. This implies that we have to group by the teacher_id and then count the distinct subject_id. Here is an example to help solidify the intuition behind the algorithm: The original table `teacher`:

teacher_id	subject_id	dept_id
1	2	3
1	2	4
1	3	3
2	1	1
2	2	1
2	3	1
2	4	1

The table after grouping by `teacher_id` and counting distinct `subject_id`:

teacher_id	cnt
1	2
2	4

#### Implementation ```sql SELECT teacher_id, COUNT(DISTINCT subject_id) AS cnt FROM Teacher GROUP BY teacher_id; ```

Number of Unique Subjects Taught by Each Teacher

Problem Description

Problem Description

Answer Panel