Pie Chart

Use me when you want to show how a whole pie gets divided into slices. I'm perfect for answering "what percentage of the total is this?" - like market share, budget breakdowns, or survey responses. Just don't slice me into too many tiny pieces (stick to 5-7 categories) - I'm not great with 20 micro-slices that make your head spin!

Overview

A pie chart is a circular statistical graphic divided into slices to illustrate numerical proportion. Each slice represents a category's contribution to the total, with the arc length (and typically the area) proportional to the quantity it represents.

Best used for:

• Showing part-to-whole relationships
• Displaying relative proportions or percentages
• Comparing a small number of categories (ideally 5-7 or fewer)
• Making quick visual comparisons of market share or composition
• Presenting simple data where exact values are less important than proportions

Common Use Cases

Business & Market Analysis

• Market share by company or product
• Revenue breakdown by product line or region
• Budget allocation across departments
• Customer segmentation by demographic
• Sales distribution by category

Operations & Resources

• Resource allocation (time, budget, personnel)
• Inventory composition by category
• Production output by facility
• Cost structure analysis
• Service usage distribution

Survey & Research

• Poll results and voting patterns
• Demographic distributions
• Response category breakdown
• Preference surveys
• Satisfaction ratings

Options

Target Column

Required - Select one or more categorical columns to visualize.

The target column determines what categories will form the slices of your pie chart. You can add multiple columns to create multiple pie charts for comparison.

Slice Value

Optional - Define how to calculate the size of each slice.

This group input allows you to specify a numerical column and an aggregation function to determine slice sizes. If not specified, the chart shows counts of each category.

Column

Select the numerical column containing values to aggregate.

Aggregation Function

Choose how to aggregate the values:

Options:

• Sum - Total of all values (e.g., total revenue per category)
• Count - Number of occurrences
• Mean - Average value per category
• Median - Middle value per category
• Min - Minimum value
• Max - Maximum value
• Std - Standard deviation
• Var - Variance
• First - First value encountered
• Last - Last value encountered

Settings

Top 20

Optional - Show only the top 20 categories.

When enabled, limits the pie chart to the 20 largest slices. Useful when you have many categories and want to focus on the most significant ones.

Hide Empty Values

Optional - Exclude categories with no data or zero values.

Removes slices that would have zero size, making the chart cleaner and easier to read.

Annotate Segments

Optional - Display values or percentages on each slice.

Shows the actual values or percentages directly on the pie slices for easier reading.

Tips for Effective Pie Charts

1. Limit Categories:

   • Keep to 5-7 slices maximum for readability
   • Consider grouping small categories into "Other"
   • Use "Top 20" setting for datasets with many categories

2. Order Matters:

   • Start at 12 o'clock position
   • Place largest slice first or use logical ordering
   • Group similar categories together

3. Use Percentages:

   • Enable annotations to show exact percentages
   • Percentages are more intuitive than raw values for pie charts
   • Consider if the total is meaningful

4. Consider Alternatives:

   • Use bar charts when precise comparisons are needed
   • Use bar charts when you have more than 7 categories
   • Use treemaps for hierarchical data

5. Color Selection:

   • Use distinct colors for each slice
   • Ensure good contrast between adjacent slices
   • Consider colorblind-friendly palettes

6. Highlight Important Data:

   • Use "exploded" slices to emphasize key categories
   • Combine less important categories into "Other"

Example Scenarios

Market Share Analysis

Budget Allocation

Product Category Distribution

Customer Segmentation

Troubleshooting

Issue: Too many small slices are hard to read

• Solution: Combine small categories (< 5%) into "Other" category, filter to top N categories, or consider using a bar chart instead.

Issue: Labels overlap or don't fit

• Solution: Move labels outside the pie, increase pie size, reduce number of slices, or abbreviate long labels.

Issue: Can't compare slice sizes accurately

• Solution: Add percentage labels to each slice, sort slices by size (largest to smallest), or consider using a bar chart for more precise comparison.

Issue: Need to show subcategories

• Solution: Use a donut chart with nested rings, create a sunburst chart, or use hierarchical visualization like treemap.

Issue: Colors are hard to distinguish

• Solution: Limit to 5-7 slices, use contrasting colors, ensure sufficient color difference between adjacent slices, or use patterns.

Issue: Percentages don't add up to 100%

• Solution: Check for rounding errors, verify data aggregation is correct, ensure no missing or null values in data.

Issue: Need to show trends over time

• Solution: Don't use pie charts for time series. Use stacked bar chart, stacked area chart, or multiple small pies with clear time labels.

Issue: Slice is too small to see

• Solution: Use "explode" feature to pull out small slice, add callout labels, group into "Other", or use donut chart with summary in center.