Get the Size of a DataFrame - Practice Coding Problems

Get the Size of a DataFrame - Problem

Pandas Easy

Given a DataFrame called players with the following schema:

Column Name	Type
player_id	int
name	object
age	int
position	object
...	...

Write a solution to calculate and display the number of rows and columns of the DataFrame.

Return the result as an array: [number of rows, number of columns]

Input & Output

Example 1 — Basic DataFrame

$ Input: players = [{"player_id": 1, "name": "Alice", "age": 25, "position": "Forward"}, {"player_id": 2, "name": "Bob", "age": 30, "position": "Guard"}, {"player_id": 3, "name": "Charlie", "age": 28, "position": "Center"}]

› Output: [3, 4]

💡 Note: The DataFrame has 3 rows (players) and 4 columns (player_id, name, age, position), so we return [3, 4]

Example 2 — Single Row

$ Input: players = [{"player_id": 1, "name": "Alice", "age": 25, "position": "Forward"}]

› Output: [1, 4]

💡 Note: Only one player with 4 attributes, so dimensions are [1, 4]

Example 3 — Empty DataFrame

$ Input: players = []

› Output: [0, 0]

💡 Note: Empty DataFrame has no rows and no columns, returning [0, 0]

Constraints

DataFrame can have 0 or more rows
DataFrame can have 0 or more columns
All rows must have the same number of columns
Column names are strings
Cell values can be any data type

Visualization

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Understanding the Visualization

Input DataFrame

DataFrame with player data in rows and columns

Get Dimensions

Extract number of rows and columns

Output Array

Return [rows, columns] as result

Key Takeaway

🎯 Key Insight: Use DataFrame.shape property to get dimensions instantly in O(1) time

Asked in

M Meta 15 N Netflix 12 S Spotify 8

The key insight is to use DataFrame's built-in shape property which returns dimensions as a tuple. Best approach uses players.shape to get (rows, columns) instantly. Time: O(1), Space: O(1)

Common Approaches

Approach	Time	Space	Notes
✓ Manual Counting	O(n)	O(1)	Iterate through the DataFrame to count rows and columns manually
Built-in Shape Property	O(1)	O(1)	Use DataFrame.shape property to get dimensions instantly

Manual Counting — Algorithm Steps

Step 1: Initialize counters for rows and columns
Step 2: Iterate through DataFrame to count rows
Step 3: Get column names and count them
Step 4: Return [row_count, column_count]

Visualization

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Step-by-Step Walkthrough

Count Rows

Iterate through each row and increment counter

Count Columns

Get column names and count them

Result

Return [rows, columns] array

Code -

solution.c — C

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

// Simplified C implementation - would need JSON parsing library
int* solution(int rowCount, int columnCount) {
    int* result = malloc(2 * sizeof(int));
    result[0] = rowCount;
    result[1] = columnCount;
    return result;
}

int main() {
    // Simplified for demonstration
    int rowCount = 3;
    int columnCount = 4;
    
    int* result = solution(rowCount, columnCount);
    printf("[%d,%d]\n", result[0], result[1]);
    
    free(result);
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(n)

Need to iterate through all n rows to count them

✓ Linear Growth

Space Complexity

O(1)

Only using a few variables to store counts

✓ Linear Space

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Input & Output

Constraints

Visualization

Related Problems

Common Approaches

Manual Counting — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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