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auto_awesomeRename Columns core interview pattern

LeetCode Problem Workspace

Rename Columns

This problem asks you to rename columns in a DataFrame to match a specified format using a built-in function.

Problem Statement

In this problem, you are tasked with renaming the columns of a DataFrame to match a new specified format. You will receive a table with column names, and you need to replace these names with a new set of names.

The problem requires applying a transformation where you map the existing column names to new ones. You can use a dictionary to specify the mapping, then apply a pandas function to perform the renaming.

Examples

Example 1

Input: See original problem statement.

Output: See original problem statement.

DataFrame students +-------------+--------+ | Column Name | Type | +-------------+--------+ | id | int | | first | object | | last | object | | age | int | +-------------+--------+

Example 2

Input: +----+---------+----------+-----+ | id | first | last | age | +----+---------+----------+-----+ | 1 | Mason | King | 6 | | 2 | Ava | Wright | 7 | | 3 | Taylor | Hall | 16 | | 4 | Georgia | Thompson | 18 | | 5 | Thomas | Moore | 10 | +----+---------+----------+-----+

Output: +------------+------------+-----------+--------------+ | student_id | first_name | last_name | age_in_years | +------------+------------+-----------+--------------+ | 1 | Mason | King | 6 | | 2 | Ava | Wright | 7 | | 3 | Taylor | Hall | 16 | | 4 | Georgia | Thompson | 18 | | 5 | Thomas | Moore | 10 | +------------+------------+-----------+--------------+

The column names are changed accordingly.

Constraints

Solution Approach

Pandas `rename()` function

You can use the pandas rename() function with a dictionary to map old column names to new ones. This is a direct solution where the dictionary keys are the current column names, and the values are the new names.

Efficient Column Renaming

Ensure that the columns are renamed efficiently by only modifying the columns parameter in pandas. Avoid unnecessary operations and keep the renaming process as simple as possible.

Verifying Output Format

Once the columns are renamed, verify the output matches the expected format. Check the DataFrame’s column names to confirm they align with the new names, ensuring accuracy.

Complexity Analysis

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

The time and space complexity of this problem depend on the size of the DataFrame. The rename() function typically operates in linear time, O(n), where n is the number of columns being renamed.

What Interviewers Usually Probe

Candidate's ability to use pandas effectively.
Efficiency in solving column renaming problems.
Awareness of built-in function optimization in pandas.

Common Pitfalls or Variants

Common pitfalls

Forgetting to apply the inplace=True parameter, which would return a new DataFrame instead of modifying the original.
Incorrectly specifying the dictionary, leading to mismatched or missed renames.
Not handling edge cases like missing columns in the renaming dictionary.

Follow-up variants

Renaming columns with more complex transformations or additional data formatting.
Performing renaming on columns with special characters or spaces.
Renaming multiple columns in a single step, handling potential conflicts.

FAQ

How do I rename columns in pandas?

You can use the pandas rename() function with a dictionary, where keys are the current column names and values are the new column names.

What is the time complexity of renaming columns in pandas?

The time complexity is typically O(n), where n is the number of columns being renamed.

What happens if the column is not present in the dictionary?

If a column is not present in the dictionary, it will remain unchanged during renaming.

Can I rename columns in-place in pandas?

Yes, you can use the inplace=True parameter to rename the columns directly in the original DataFrame.

What are the common pitfalls in renaming columns?

Common pitfalls include forgetting to set inplace=True, incorrect dictionary syntax, or mismatched column names that lead to errors.

terminal

Solution

Solution 1

#### Python3

import pandas as pd


def renameColumns(students: pd.DataFrame) -> pd.DataFrame:
    students.rename(
        columns={
            'id': 'student_id',
            'first': 'first_name',
            'last': 'last_name',
            'age': 'age_in_years',
        },
        inplace=True,
    )
    return students

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