Overview

This Tableau project focuses on analyzing global video game sales data. The dataset includes information such as game rank, name, platform, release year, genre, publisher, and sales figures for different regions.

picture_data_covid
Picture of Sam Pak in Unsplash

Dataset

The raw dataset includes the following columns:

  • ID
  • Marital Status
  • Gender
  • Income
  • Children
  • Education
  • Occupation
  • Home Owner
  • Cars
  • Commute Distance
  • Region
  • Age
  • Purchased Bike

After cleaning the dataset, irrelevant columns were removed, and adjustments were made to enhance readability and analysis.

Cleaning Process

  1. Column Selection: Only relevant columns were retained for analysis, including Gender, Income, Children, Education, Occupation, Home Owner, Cars, Commute Distance, Region, Age, Age Brackets, and Purchased Bike.

  2. Data Transformation: Income values were standardized, removing special characters and converting them to numerical values. Age brackets were introduced to categorize customers into age groups.

Dashboard Creation

The main analysis was conducted through pivot tables to visualize key insights. The dashboard includes the following pivot tables:

  1. Average Income by Gender and Bike Purchase Status: This table provides insights into the average income of customers based on gender and whether they purchased a bike or not.
  2. Count of Purchased Bike by Commute Distance: This table presents the count of bike purchases categorized by commute distance.
  3. Count of Purchased Bike by Age Brackets: This table displays the count of bike purchases categorized by age brackets.

Key Findings

  1. Income Analysis: On average, male customers have a slightly higher income compared to female customers. Customers who purchased a bike tend to have slightly higher incomes overall.
  2. Commute Distance: Most bike purchases occur for customers with commute distances between 0-1 miles and 5-10 miles.
  3. Age Distribution: Middle-aged customers (between 40 and 60 years old) constitute the largest segment of bike purchasers.

Conclusion

The dashboard provides valuable insights into bike sales trends based on customer demographics. Further analysis and exploration can be conducted to uncover additional patterns and optimize marketing strategies.

Dashboard video games sales
Dashboard video games sales

Colophon

thanks Alex for his tutorials and explanations (Alex The Analyst)