How do you solve Create a DataFrame from List on LeetCode?

Create a DataFrame from List (LeetCode #2877) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Using built-in functions can greatly simplify your code.

What is the time complexity of Create a DataFrame from List?

The optimal solution for Create a DataFrame from List runs in O(n) time and uses O(n) space. This solution is O(n) because it processes the list in a single pass without needing to append repeatedly.

What is the brute force solution for Create a DataFrame from List?

The brute force approach for Create a DataFrame from List is Brute Force, with O(n²) time complexity and O(1) space complexity. We can manually create a DataFrame by iterating through the 2D list and appending each student’s ID and age to a DataFrame. This approach is straightforward but not efficient. The optimal Optimal Solution approach improves this to O(n).

What are the interview tips for Create a DataFrame from List?

Always start with a simple solution before optimizing. Be clear about time and space complexity when discussing your approach. Practice explaining your thought process as you code.

What are common mistakes when solving Create a DataFrame from List?

Not using the correct DataFrame constructor. Overcomplicating the solution with unnecessary loops.

#2877

Create a DataFrame from List

Easy

ArrayDataFrame

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

💡

Intuition

Time O(n)Space O(n)

Using pandas directly to create a DataFrame from the 2D list is the most efficient way. This leverages built-in functions that are optimized for performance.

⚙️

Algorithm

2 steps

1Step 1: Use the pandas DataFrame constructor directly with the 2D list.
2Step 2: Specify the column names as a parameter.

solution.py6 lines

1# Full working Python code
2import pandas as pd
3
4student_data = [[1, 15], [2, 11], [3, 11], [4, 20]]
5df = pd.DataFrame(student_data, columns=['student_id', 'age'])
6print(df)

ℹ

Complexity note: This solution is O(n) because it processes the list in a single pass without needing to append repeatedly.

1Using built-in functions can greatly simplify your code.
2Understanding the underlying data structure helps in optimizing performance.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.