Joshua Sunwoo Nam

Dataset Description

This dataset contains video game sales data including game titles, platforms, release years, genres, publishers, regional sales, and total global sales.

Variables and Data Types

• Name - Categorical (Nominal)
• Platform - Categorical (Nominal)
• Year - Numerical (Discrete / Temporal)
• Genre - Categorical (Nominal)
• Publisher - Categorical (Nominal)
• NA_Sales - Quantitative (Continuous, Ratio)
• EU_Sales - Quantitative (Continuous, Ratio)
• JP_Sales - Quantitative (Continuous, Ratio)
• Other_Sales - Quantitative (Continuous, Ratio)
• Global_Sales - Quantitative (Continuous, Ratio)

Key Statistics

Central Tendency (Global Sales)

• Mean: 0.5409 million units
• Median: 0.17 million units
• Mode: 0.02 million units

Spread / Variability (Global Sales)

• Minimum: 0.01 million units
• Maximum: 82.74 million units
• Range: 82.73 million units
• Standard Deviation: 1.57

The large difference between the mean (0.54) and median (0.17), along with the wide range (82.73), indicates that global sales are highly skewed. Most games sell relatively small amounts, while a few blockbuster titles account for extremely high sales.

Visualization 1: Global Sales by Genre and Platform

Questions:

• Which genres generate the highest global sales overall?
• Are certain platforms strongly associated with specific genres?

Reflection: Action, sports, and shooter genres consistently produce the largest share of global sales. Popular platforms repeatedly appear within these genres, suggesting that successful hardware ecosystems help amplify genre success. This shows how platform adoption and content type reinforce each other.

Design choices: I used a horizontal stacked bar chart because it makes it easy to compare total sales by genre (bar length) while also showing platform contributions (color stacks) in the same view. Sorting genres by total sales supports quick ranking and the tooltip provides exact totals without cluttering the chart with labels.

Visualization 2: Sales Over Time by Platform and Genre

Questions:

• How does total global sales change over time, and when do major platforms show clear peaks and declines?
• During a platform’s peak years, which genres are most present (as seen through the tooltip breakdown)?

Reflection: The stacked area pattern highlights platform “life cycles”: platforms rise, peak, and then fade as newer systems enter. The tooltip reveals that genre composition varies across years, suggesting that platform success is not only about the hardware generation but also about what genres were selling strongly during that time period.

Design choices: I chose a stacked area chart because it emphasizes change over time and shows how different platforms contribute to the total sales each year. Stacking makes overall market volume visible while color separates platform contributions. Tooltips include genre so viewers can inspect the genre context without overloading the chart visually.

Visualization 3: Regional Sales vs. Platform

Questions:

• For each platform, how do total sales compare across regions (NA, EU, JP, Other)?
• Which platforms show the strongest regional skew (one region making up most of the platform’s sales)?

Reflection: The visualization makes regional preferences easy to spot: some platforms have much larger totals in North America and Europe, while others show relatively stronger performance in Japan. This indicates that platform popularity is not uniform globally and is shaped by regional market differences.

Design choices: I used a bar chart with region encoded by color because it supports direct comparison of regional totals within the same platform. The tooltip provides precise sales totals by region, and the consistent platform x-axis makes it easy to scan across systems.

Visualization 4: What Genre Each Region Prefers

Questions:

• Within each region (NA, EU, JP, Other), which genres make up the largest share of total sales?
• How does the genre mix differ between regions (e.g., does Japan emphasize different genres than NA/EU)?

Reflection: This view tells a regional “taste” story: each region has a distinct genre composition, with some genres taking a much larger portion of the sales in specific markets. Comparing the donut charts side-by-side shows that regional demand is not identical, and certain genres appear more dominant in some regions than others.

Design choices: I chose donut charts because the goal is to compare proportions (genre share) within each region rather than just totals. Faceting creates small multiples that make side-by-side comparison easy. The donut form highlights composition clearly, and tooltips provide exact sales amounts for each genre segment.