Grouping Values and Creating Separate Columns in a Pandas DataFrame Using Groupby Operations with Aggregation Functions

Reshaping a DataFrame from Long to Wide Format: Rows to Columns Based on Second Index

Adding Fake Data to a Data Frame Based on Variable Conditions Using R's dplyr Library

Mapping Dictionary Values to Pandas DataFrame Columns Using Map Function

Getting the Top N Most Frequent Values Per Column in a Pandas DataFrame Using Different Methods

Calculating Average Growth Rate Over Past Few Years Using Lagged Data

Assigning Unique IDs to Columns in Pandas DataFrames for Efficient Data Manipulation.

Accessing Values from Index Columns When Working with Grouped Data in Pandas

How to Deduce Information from Pairs in a Dataset Using Programming Techniques

Improving Code Readability and Efficiency: Refactored Municipality Demand Analysis Code