Reshape Data: Pivot

Problem Description

Write a solution to pivot the data so that each row represents temperatures for a specific month, and each city is a separate column.

Key Insights

• The problem requires transforming a DataFrame where each city has multiple rows for different months into a format where each city is represented as a column.
• The pivot operation typically requires aggregating data based on distinct values in specific columns.
• The resulting table should maintain a clear relationship between months and temperatures across different cities.

Space and Time Complexity

Time Complexity: O(n), where n is the number of entries in the input DataFrame. Space Complexity: O(m * c), where m is the number of unique months and c is the number of unique cities.

Solution

To solve the problem, we will use the pivot operation on the DataFrame. The original DataFrame will be transformed such that:

• The month column becomes the index of the new DataFrame.
• Each unique city becomes a column in the new DataFrame.
• The values in the DataFrame will be filled with the corresponding temperature for each city and month combination.

This can be efficiently achieved using pandas in Python, which provides a built-in method for pivoting DataFrames.

Code Solutions