Create a Student DataFrame from a List
Company: Microsoft
Role: Software Engineer
Category: Data Manipulation (SQL/Python)
Difficulty: easy
Interview Round: Other
### Problem
Implement the pandas function below to construct a DataFrame from `student_data`, a two-dimensional list containing student IDs and ages.
```python
def createDataframe(student_data: List[List[int]]) -> pd.DataFrame:
...
```
Each row supplies a student ID followed by an age. Return a DataFrame with columns `student_id` and `age`, in that order. Keep the rows in the same order as the input list.
### Examples
**Example 1:**
Input:
```python
student_data = [[12, 16], [4, 10], [9, 16]]
```
Returned DataFrame values:
| student_id | age |
|---|---|
| 12 | 16 |
| 4 | 10 |
| 9 | 16 |
The row starting with `12` stays first even though `4` is smaller.
**Example 2:**
Input:
```python
student_data = [[25, 19]]
```
Returned DataFrame values:
| student_id | age |
|---|---|
| 25 | 19 |
A single input row still produces a DataFrame with both named columns.
### Constraints and Clarifications
- The supplied signature uses a two-dimensional list of integers.
- The first value of each row is the student ID; the second is the age.
- Return a pandas DataFrame, not the original list or a printed table.
- Preserve input row order. Do not sort by student ID or age.
- The source gives no numeric bounds, row-count bounds, uniqueness guarantee, explicit dtype requirement, or custom index requirement. Do not add validation rules for those unspecified properties.
```hint Name the two columns
Use the relationship between the two values in each input row and the two requested column labels.
```
### What a Strong Answer Covers
- Construct a DataFrame with the exact labels `student_id` and `age`.
- Preserve the input rows and their order.
- Keep column labels separate from the integer data rows.
### Follow-up Questions
- Why would sorting the result violate this task even if all rows remained present?
- How would reversing the two column labels change the meaning of the result?
Overview: Create a pandas DataFrame from a two-dimensional list of student IDs and ages. Use the exact student_id and age columns while preserving the original row order and returning a DataFrame.