Display the First Three Rows - Practice Coding Problems

Display the First Three Rows - Problem

Pandas Easy

Working with data analysis often requires examining samples of large datasets. In this fundamental pandas operation, you need to display the first 3 rows of an employee DataFrame.

You are given a DataFrame called employees with the following structure:

Column Name	Type
employee_id	int
name	object
department	object
salary	int

Goal: Write a pandas solution that returns only the first 3 rows of this DataFrame, maintaining all columns and original data types.

This is a common data exploration task where analysts need to quickly preview data structure and content before performing complex operations.

Input & Output

example_1.py — Basic Employee DataFrame

$ Input: employees = pd.DataFrame({ 'employee_id': [1, 2, 3, 4, 5], 'name': ['John', 'Sarah', 'Mike', 'Lisa', 'David'], 'department': ['Engineering', 'Marketing', 'Sales', 'HR', 'IT'], 'salary': [75000, 65000, 55000, 60000, 70000] })

› Output: employee_id name department salary 0 1 John Engineering 75000 1 2 Sarah Marketing 65000 2 3 Mike Sales 55000

💡 Note: Returns the first 3 rows of the DataFrame, displaying employee IDs 1, 2, and 3 with all their corresponding information.

example_2.py — DataFrame with Exactly 3 Rows

$ Input: employees = pd.DataFrame({ 'employee_id': [101, 102, 103], 'name': ['Alice', 'Bob', 'Carol'], 'department': ['Finance', 'Operations', 'Legal'], 'salary': [80000, 75000, 85000] })

› Output: employee_id name department salary 0 101 Alice Finance 80000 1 102 Bob Operations 75000 2 103 Carol Legal 85000

💡 Note: When the DataFrame has exactly 3 rows, all rows are returned since we're requesting the first 3 rows.

example_3.py — DataFrame with Less Than 3 Rows

$ Input: employees = pd.DataFrame({ 'employee_id': [201, 202], 'name': ['Emma', 'Frank'], 'department': ['Research', 'Security'], 'salary': [90000, 65000] })

› Output: employee_id name department salary 0 201 Emma Research 90000 1 202 Frank Security 65000

💡 Note: Edge case: When DataFrame has fewer than 3 rows, head(3) returns all available rows without error.

Visualization

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Understanding the Visualization

Original DataFrame

Start with a DataFrame containing employee records

Apply head(3)

Use pandas head() method to select first 3 rows

Result DataFrame

Get a new DataFrame with exactly 3 rows (or fewer if original was smaller)

Key Takeaway

🎯 Key Insight: Pandas head() method provides direct access to the first N rows without scanning the entire dataset, making it both efficient and intuitive for data exploration tasks.

Time & Space Complexity

Time Complexity

⏱️

O(1)

Only accessing first 3 rows regardless of DataFrame size

✓ Linear Growth

Space Complexity

O(1)

Creating a new DataFrame with fixed 3 rows

✓ Linear Space

Constraints

DataFrame can have 0 to 10⁶ rows
employee_id values are unique positive integers
name strings are non-empty and contain only letters and spaces
department strings represent valid business departments
salary values are positive integers representing annual salary in dollars

Asked in

N Netflix 25 ♪ Spotify 20 A Airbnb 18 U Uber 15

The optimal approach uses pandas head(3) method which directly retrieves the first 3 rows in O(1) time. This is the industry standard for DataFrame row selection and provides the most readable and maintainable code.

Common Approaches

Approach	Time	Space	Notes
✓ Manual Row Selection with Iteration	O(1)	O(1)	Iterate through DataFrame indices and manually select first three rows
Pandas head() Method (Optimal)	O(1)	O(1)	Use pandas built-in head() method to efficiently get first N rows

Manual Row Selection with Iteration — Algorithm Steps

Get the DataFrame index values
Create a list or loop to collect first 3 indices
Use iloc or loc to select rows by these indices
Return the resulting DataFrame

Visualization

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Step-by-Step Walkthrough

Start Loop

Initialize counter and empty result

Check Index

Verify index is within bounds and less than 3

Copy Row

Add current row to result DataFrame

Increment

Move to next row and repeat

Code -

solution.c — C

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

// C doesn't have native DataFrame support
// This represents the concept using structures
typedef struct {
    int employee_id;
    char name[50];
    char department[50];
    int salary;
} Employee;

void solution(Employee* employees, int size, Employee* result) {
    // Manual selection of first 3 rows
    int limit = (size < 3) ? size : 3;
    for (int i = 0; i < limit; i++) {
        result[i] = employees[i];
    }
}

int main() {
    printf("Manual row selection approach\n");
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(1)

Only accessing first 3 rows regardless of DataFrame size

✓ Linear Growth

Space Complexity

O(1)

Creating a new DataFrame with fixed 3 rows

✓ Linear Space

Constraints

DataFrame can have 0 to 10⁶ rows
employee_id values are unique positive integers
name strings are non-empty and contain only letters and spaces
department strings represent valid business departments
salary values are positive integers representing annual salary in dollars

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Input & Output

Visualization

Time & Space Complexity

Related Problems

Constraints

Common Approaches

Manual Row Selection with Iteration — Algorithm Steps

Visualization

Code -

Time & Space Complexity

Constraints

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