Select a Student’s Name and Age with pandas
Company: Amazon
Role: Software Engineer
Category: Data Manipulation (SQL/Python)
Difficulty: easy
Interview Round: Other
### Problem
You receive a pandas DataFrame named `students` with these columns:
| Column | Source type |
|---|---|
| student_id | int |
| name | object |
| age | int |
Implement:
```python
def selectData(students: pd.DataFrame) -> pd.DataFrame:
...
```
Select the name and age of the student whose `student_id` equals `101`. Return a DataFrame containing the columns `name` and `age`, in that order, as illustrated below. The target ID is fixed at `101`; it is not another function parameter.
### Examples
**Example 1:**
Input `students`:
| student_id | name | age |
|---|---|---|
| 42 | Avery | 11 |
| 101 | Morgan | 14 |
| 9 | Riley | 8 |
Returned values:
| name | age |
|---|---|
| Morgan | 14 |
The match is determined by `student_id`, not by the row's position.
**Example 2:**
Input `students`:
| student_id | name | age |
|---|---|---|
| 101 | Casey | 17 |
| 103 | Casey | 12 |
Returned values:
| name | age |
|---|---|
| Casey | 17 |
A matching name alone does not select a row.
### Constraints and Clarifications
- Use the `student_id` column value to identify the student.
- The result contains `name` followed by `age`, without `student_id`.
- Return a DataFrame rather than a Series, scalar, or printed table.
- The source does not state a uniqueness guarantee, whether ID `101` must exist, a NULL policy, or an output index or row-order requirement. These must not be silently converted into extra input guarantees.
```hint Separate rows from columns
First identify the qualifying row data, then retain the two requested columns.
```
### What a Strong Answer Covers
- Apply equality to the `student_id` column and the fixed value `101`.
- Select only the requested output columns in their stated order.
- Preserve a DataFrame result instead of collapsing it into a single row object.
### Follow-up Questions
- Why is selecting index label `101` different from checking the `student_id` column?
- What behavior does your implementation have if there is no match or more than one match, given that the source does not specify those cases?
Overview: Select the name and age for student_id 101 from a pandas DataFrame. Practice Boolean row filtering, explicit column projection, and preserving the required DataFrame result shape.
