Create a DataFrame from List - Practice Coding Problems

Create a DataFrame from List - Problem

Pandas Easy

Write a solution to create a DataFrame from a 2D list called student_data. This 2D list contains the IDs and ages of some students.

The DataFrame should have two columns, student_id and age, and be in the same order as the original 2D list.

Note: The function should return a pandas DataFrame object with the specified column names and data structure.

Input & Output

Example 1 — Basic Student Data

$ Input: student_data = [[1, 15], [2, 11], [3, 11], [4, 20]]

› Output: {"student_id": [1, 2, 3, 4], "age": [15, 11, 11, 20]}

💡 Note: Create DataFrame with student_id and age columns from the 2D list. Each inner list becomes a row with ID in first column and age in second column.

Example 2 — Minimum Data

$ Input: student_data = [[5, 18]]

› Output: {"student_id": [5], "age": [18]}

💡 Note: Single student data creates DataFrame with one row containing student ID 5 and age 18.

Example 3 — Multiple Students Same Age

$ Input: student_data = [[10, 22], [11, 22], [12, 19]]

› Output: {"student_id": [10, 11, 12], "age": [22, 22, 19]}

💡 Note: DataFrame maintains order and allows duplicate ages. Students 10 and 11 both have age 22.

Constraints

1 ≤ student_data.length ≤ 1000
student_data[i].length = 2
1 ≤ student_data[i][0] ≤ 10⁶ (student ID)
1 ≤ student_data[i][1] ≤ 100 (age)

Visualization

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Understanding the Visualization

Input

2D list with student [ID, age] pairs

Transform

Apply DataFrame constructor with column labels

Output

Structured DataFrame with named columns

Key Takeaway

🎯 Key Insight: DataFrame constructor efficiently transforms 2D lists into structured data with proper column labels

Asked in

G Google 15 F Facebook 12 a Amazon 18 M Microsoft 10

The key insight is to use pandas DataFrame constructor with the data parameter and column names. Best approach is the direct constructor method: pd.DataFrame(student_data, columns=['student_id', 'age']). Time: O(n), Space: O(n).

Common Approaches

Approach	Time	Space	Notes
✓ Manual Row-by-Row Construction	O(n)	O(n)	Create empty DataFrame and add each row individually using iterative assignment
Direct DataFrame Constructor	O(n)	O(n)	Use pandas DataFrame constructor with data and column parameters for efficient creation

Manual Row-by-Row Construction — Algorithm Steps

Create empty DataFrame with column names
Loop through each row in student_data
Use loc indexing to assign each row to DataFrame

Visualization

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Step-by-Step Walkthrough

Initialize Empty DataFrame

Create DataFrame with column headers

Add Rows Iteratively

Loop through data and assign each row

Complete DataFrame

Final structured DataFrame

Code -

solution.c — C

#include <stdio.h>
#include <stdlib.h>
#include <string.h>

typedef struct {
    int* student_id;
    int* age;
    int size;
} DataFrame;

DataFrame solution(int** studentData, int rows) {
    DataFrame df;
    df.student_id = (int*)malloc(rows * sizeof(int));
    df.age = (int*)malloc(rows * sizeof(int));
    df.size = rows;
    
    // Add each row manually
    for (int i = 0; i < rows; i++) {
        df.student_id[i] = studentData[i][0];
        df.age[i] = studentData[i][1];
    }
    
    return df;
}

int main() {
    char line[1000];
    fgets(line, sizeof(line), stdin);
    
    // Simple parsing for [[1,15],[2,11],...] format
    int** studentData = (int**)malloc(100 * sizeof(int*));
    int rows = 0;
    
    char* ptr = line + 1; // Skip first '['
    while (*ptr && *ptr != ']') {
        if (*ptr == '[') {
            studentData[rows] = (int*)malloc(2 * sizeof(int));
            ptr++; // Skip '['
            sscanf(ptr, "%d,%d", &studentData[rows][0], &studentData[rows][1]);
            rows++;
            while (*ptr != ']') ptr++; // Find closing bracket
        }
        ptr++;
    }
    
    DataFrame result = solution(studentData, rows);
    
    printf("{\"student_id\":[";
    for (int i = 0; i < result.size; i++) {
        printf("%d", result.student_id[i]);
        if (i < result.size - 1) printf(",");
    }
    printf("],\"age\":[";
    for (int i = 0; i < result.size; i++) {
        printf("%d", result.age[i]);
        if (i < result.size - 1) printf(",");
    }
    printf("]}\n");
    
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(n)

Single loop through n rows to assign each one

✓ Linear Growth

Space Complexity

O(n)

DataFrame stores n rows of student data

⚡ Linearithmic Space

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Input & Output

Constraints

Visualization

Related Problems

Common Approaches

Manual Row-by-Row Construction — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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