Halloween Candy Analysis Report

Project Background:

In 2017, Walt Hickey from FiveThirthyEight set out to find the Halloween candy most people prefer. To figure it out, he set up an experiment in which online voters could select their favorite candy from randomly generated matchups (for example, Twix or Snickers?).

After compiling about 269,000 votes from 8,371 different IP addresses, Walt calculated the win percentage for each type of candy and included several key attributes (for example, does it contain chocolate?) to find what makes them popular.

Objective :

My task for this project is determining which 3 types of candy are the most popular among the masses.

Here is the breakdown of my thought process

Data Extraction Process:

In this project, I leveraged Power BI's Power Query ETL (Extract, Transform, Load) feature to import data stored in CSV format.

Data Cleaning & Validation Process:

After loading the data into the Power Query Editor, various enhancements, such as updating data types and replacing values, were applied to streamline the data analysis process.

Data Modelling Process:

After applying all desired changes, the table was seamlessly loaded into the Power BI canvas using the Direct Query feature. As only one table was involved, no data modelling was necessary.

Data Analysis & Visualization Process:

A comprehensive set of measures was devised to analyze the key performance indicators (KPIs) and presented in a dashboard format containing an array of visuals.

The static images of the dashboard are revealed below (Click on the image to view it.)

Your thoughts and feedback on this project are much appreciated.