Data Visualization

Data Visualization Skill

Chart Selection Guide

Bar Chart

Use when:

• Comparing categories
• Showing rankings
• Displaying discrete data

Best practices:

• Sort bars by value (descending) unless natural order exists
• Use horizontal bars for long category names
• Limit to ~10 categories for readability
• Use consistent colors

Example: Product sales by category, user signups by region

Line Chart

Use when:

• Showing trends over time
• Displaying continuous data
• Comparing multiple series

Best practices:

• Use time on x-axis
• Limit to 3-5 lines for clarity
• Use distinct colors/styles
• Mark important events/annotations

Example: Daily active users over time, revenue trends

Scatter Plot

Use when:

• Showing relationships between two variables
• Identifying correlations
• Finding outliers

Best practices:

• Use appropriate axis scales
• Add trend line if relationship exists
• Color-code by category if relevant
• Label outliers

Example: Price vs. demand, user engagement vs. retention

Heatmap

Use when:

• Showing patterns in two dimensions
• Comparing categories across time
• Displaying correlation matrices

Best practices:

• Use intuitive color scale (low to high)
• Include values in cells if space allows
• Sort rows/columns meaningfully
• Use diverging colors for centered data

Example: User activity by hour/day, correlation matrix

Pie Chart

Use when:

• Showing parts of a whole
• Few categories (3-5 max)

Best practices:

• Limit to 5-7 slices
• Sort slices by size
• Use distinct colors
• Consider bar chart alternative

Example: Market share, revenue by segment

Histogram

Use when:

• Showing distribution of continuous data
• Identifying skewness
• Understanding data shape

Best practices:

• Choose appropriate bin size
• Use consistent bin widths
• Label axes clearly
• Overlay distribution curve if helpful

Example: User age distribution, transaction amount distribution