Is Display the First Three Rows easy or hard?

Display the First Three Rows is categorized as an Easy problem. It primarily tests familiarity with DataFrame APIs or basic iteration logic rather than complex algorithms or data structures.

Display the First Three Rows Python/Java solution

In Python with pandas, the solution is simply employees.head(3). In Java or C++, if the data is stored in arrays or lists, iterate from index 0 to min(3, n) and copy those rows into the result structure. Both implementations rely on selecting the first three entries of the dataset.

How to solve Display the First Three Rows in O(1)?

Use a built-in DataFrame operation that directly returns the first k rows. In pandas, calling df.head(3) selects the first three records without scanning the entire dataset. Because the number of accessed rows is constant, the runtime stays O(1).

What is the best approach for Display the First Three Rows?

The best approach is using built-in DataFrame utilities such as df.head(3) in pandas or an equivalent slice/head method in JavaScript DataFrame libraries. These functions directly return the first three rows without manual iteration. The operation runs in O(1) time and O(1) extra space because only a constant number of rows are accessed.

Is Display the First Three Rows asked at Google/Amazon/Meta?

This problem reflects common data manipulation tasks used in data engineering and analytics interviews rather than traditional algorithm-heavy interviews. Companies that evaluate data processing skills often expect familiarity with DataFrame operations such as selecting rows, filtering, and slicing.

What data structure is used in Display the First Three Rows?

The problem operates on a DataFrame, which is a tabular data structure similar to a table with labeled columns and indexed rows. Internally, many implementations store columns as arrays or series, making row slicing a lightweight index-based operation.

What is the time complexity of Display the First Three Rows?

The optimal solution runs in O(1) time since only three rows are retrieved regardless of dataset size. Manual iteration would technically be O(k) where k = 3, which still behaves like constant time. Space complexity is O(1) for built-in methods or O(k) if copying rows into a new container.

Description Hints 1 Solution Video 1:00

2879. Display the First Three Rows

Easy93.0% acceptance4 companies

DataFrame: employees
+-------------+--------+
| Column Name | Type   |
+-------------+--------+
| employee_id | int    |
| name        | object |
| department  | object |
| salary      | int    |
+-------------+--------+

Write a solution to display the first 3 rows of this DataFrame.

Example 1:

Input:
DataFrame employees
+-------------+-----------+-----------------------+--------+
| employee_id | name      | department            | salary |
+-------------+-----------+-----------------------+--------+
| 3           | Bob       | Operations            | 48675  |
| 90          | Alice     | Sales                 | 11096  |
| 9           | Tatiana   | Engineering           | 33805  |
| 60          | Annabelle | InformationTechnology | 37678  |
| 49          | Jonathan  | HumanResources        | 23793  |
| 43          | Khaled    | Administration        | 40454  |
+-------------+-----------+-----------------------+--------+
Output:
+-------------+---------+-------------+--------+
| employee_id | name    | department  | salary |
+-------------+---------+-------------+--------+
| 3           | Bob     | Operations  | 48675  |
| 90          | Alice   | Sales       | 11096  |
| 9           | Tatiana | Engineering | 33805  |
+-------------+---------+-------------+--------+
Explanation: 
Only the first 3 rows are displayed.

Asked at 4 companies

Google Amazon Microsoft Meta

Hints open one at a time

Hint 1

Consider using a built-in function in pandas library to retrieve the initial rows.

1:00

Still stuck?Read 2 approaches, or watch a walkthrough.

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1class Solution:
  def solve(self):
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Examples

Case 1

Input

{"headers":{"employees":["employee_id","name","department","salary"]},"rows":{"employees":[[3,"Bob","Operations",48675],[90,"Alice","Sales",11096],[9,"Tatiana","Engineering",33805],[60,"Annabelle","InformationTechnology",37678],[49,"Jonathan","HumanResources",23793],[43,"Khaled","Administration",40454]]}}

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