Get the Size of a DataFrame

To solve the Get the Size of a DataFrame problem, use pandas built-in methods to retrieve row and column counts. Return these counts as an array [rows, columns]. This ensures fast and accurate results for any DataFrame structure and avoids manual iteration errors.

Problem Statement

Given a pandas DataFrame named players, write a function to determine its dimensions. Return the number of rows and columns in an array format [number of rows, number of columns].

The DataFrame may have any number of rows and columns, and the solution should rely on Python pandas functions rather than manual counting. This pattern tests your familiarity with DataFrame properties and built-in size methods.

Examples

Example 1

Input: See original problem statement.

Output: See original problem statement.

DataFrame players: +-------------+--------+ | Column Name | Type | +-------------+--------+ | player_id | int | | name | object | | age | int | | position | object | | ... | ... | +-------------+--------+

Example 2

Input: +-----------+----------+-----+-------------+--------------------+ | player_id | name | age | position | team | +-----------+----------+-----+-------------+--------------------+ | 846 | Mason | 21 | Forward | RealMadrid | | 749 | Riley | 30 | Winger | Barcelona | | 155 | Bob | 28 | Striker | ManchesterUnited | | 583 | Isabella | 32 | Goalkeeper | Liverpool | | 388 | Zachary | 24 | Midfielder | BayernMunich | | 883 | Ava | 23 | Defender | Chelsea | | 355 | Violet | 18 | Striker | Juventus | | 247 | Thomas | 27 | Striker | ParisSaint-Germain | | 761 | Jack | 33 | Midfielder | ManchesterCity | | 642 | Charlie | 36 | Center-back | Arsenal | +-----------+----------+-----+-------------+--------------------+

Output: [10, 5]

This DataFrame contains 10 rows and 5 columns.

Constraints

Solution Approach

Use DataFrame shape attribute

The simplest approach is to access the DataFrame's shape property, which returns a tuple (rows, columns). Convert this tuple to a list and return it directly.

Use len for rows and columns

Alternatively, calculate rows with len(df) and columns with len(df.columns). Combine them into a list [len(df), len(df.columns)] to match the expected output format.

Avoid manual iteration

Do not iterate over the DataFrame manually to count rows and columns; it is inefficient and prone to errors. Relying on built-in attributes guarantees accuracy and better performance.

Complexity Analysis

Metric	Value
Time	Depends on the final approach
Space	Depends on the final approach

Time complexity is O(1) since accessing shape or len attributes does not depend on DataFrame size. Space complexity is also O(1) as only a small list of two integers is returned.

What Interviewers Usually Probe

• Looking for knowledge of DataFrame properties in pandas.
• Expecting use of shape attribute or equivalent built-in function.
• Testing understanding of simple, efficient DataFrame operations.

Common Pitfalls or Variants

Common pitfalls

• Attempting to manually count rows and columns using loops.
• Returning a tuple instead of a list as required by the problem.
• Confusing DataFrame shape with DataFrame size (total number of elements).

Follow-up variants

• Return the total number of elements instead of row and column counts using df.size.
• Calculate dimensions for a filtered or sliced DataFrame and return updated counts.
• Provide row and column names along with counts in a dictionary instead of a list.

FAQ

What is the easiest way to get the size of a DataFrame in Python?

Use the df.shape attribute and convert it to a list [rows, columns] for direct results.

Can I use len() to find DataFrame dimensions?

Yes, len(df) gives the number of rows, and len(df.columns) gives the number of columns.

Why shouldn't I iterate manually over the DataFrame to count rows or columns?

Manual iteration is slower and error-prone; built-in methods like shape are precise and O(1).

How does this problem relate to pandas core interview patterns?

It tests basic familiarity with DataFrame attributes, a common and simple interview pattern in data manipulation.

What format should I return for Get the Size of a DataFrame?

Return an array [number of rows, number of columns] as specified, not a tuple or other structure.