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Comparative And Part To Whole Visuals

Learn Comparative And Part To Whole Visuals for free with explanations, exercises, and a quick test (for Data Visualization Engineer).

Published: December 28, 2025 | Updated: December 28, 2025

Who this is for

Data Visualization Engineers and BI practitioners who must compare categories, versions, or time periods, and show how parts contribute to a total in clear, decision-ready visuals.

Prerequisites

  • Basic chart literacy (bar/line/area/pie).
  • Comfort with categorical and time-based data.
  • Ability to compute percentages and sort/rank categories.

Why this matters

In real projects you will:

  • Compare A/B test results across segments.
  • Show product sales by region and how each region contributes to total revenue.
  • Reveal budget vs. actuals and which components drove the variance.
  • Track market share composition over time to flag shifts.

Choosing the right comparative or part-to-whole visual makes patterns obvious and decisions faster.

Concept explained simply

Two common analytic tasks:

  • Comparative: Which is bigger/smaller? By how much? How did it change?
  • Part-to-whole: What makes up the total? What share does each part have?

Mental model

Match the task to the most accurate visual encoding:

  • Highest accuracy: position on a common baseline (grouped bars, dot plots).
  • Next: length (bars, lollipops).
  • Lower accuracy: angle/area (pie, donut, treemap). Use when communicating composition at a glance, not fine precision.
Quick rules of thumb
  • Compare magnitudes: horizontal bar chart sorted by value.
  • Compare two points per category: slope chart or dot plot with connecting line.
  • Compare many groups across few categories: grouped bars or small multiples.
  • Part-to-whole (one point): pie/donut (≤6 slices), or treemap for many parts.
  • Part-to-whole across time: stacked area (for trends) or stacked bars (discrete periods).
  • Relative composition across categories/time: 100% stacked bars.

Choosing the right visual

  • Single-category comparison (10–30 items): sorted horizontal bars.
  • Compare two measures per category (e.g., plan vs. actual): grouped bars or bullet chart.
  • Compare before vs. after for each category: slope chart (few categories) or dot plot.
  • Show change drivers to total: waterfall chart.
  • Part-to-whole with few parts (≤6): donut/pie; label shares directly.
  • Part-to-whole with many parts: treemap or bars with “Other” grouped.
  • Part-to-whole across time: stacked area for smooth trends, 100% stacked bars to compare relative shares.
When to avoid certain charts
  • Pie/donut with many slices or tiny differences: use bars instead.
  • Stacked bars for comparing non-baseline segments across categories: use grouped bars or 100% stacked bars.
  • Dual axes with different scales: prefer normalization or small multiples.

Worked examples

Example 1: Compare quarterly sales by product

Task: Compare Q1 vs. Q2 sales across five products and see which grew the most.

  • Recommended: dot plot per product (two dots Q1 and Q2) with a line, or grouped bars.
  • Why: shared baseline/position comparison is precise; the connecting line shows direction of change.
Design notes
  • Sort products by Q2 value or absolute change.
  • Color encode increase vs. decrease lightly; use labels for deltas.

Example 2: Market share by region

Task: Show composition of market share across four competitors in three regions and compare relative dominance.

  • Recommended: 100% stacked bars with one bar per region.
  • Why: relative shares are the focus; percentages sum to 100% per region.
Alternative

Use small multiples of pies (one per region) only if ≤4 slices and differences are large. Otherwise 100% stacked bars are easier to compare.

Example 3: Budget vs. actuals and drivers

Task: Show which line items drove the variance to total budget.

  • Recommended: waterfall chart from budget to actual with increases/decreases by line item.
  • Why: isolates contribution of each part to the final difference.
Design notes
  • Order steps logically (e.g., revenue drivers then cost drivers).
  • Label totals and key drivers directly.

Exercises

Do these without tools first; sketch on paper. Then build in your favorite BI tool.

Exercise 1 — Pick the right chart

You have product mix for three regions (North, South, West). Each region sells five products (A–E). Stakeholder goals: (1) compare each product’s share within a region, (2) see which product dominates per region, (3) quickly compare regions.

Deliverable: choose a single primary chart type and list key design choices (ordering, labels, colors).

  • Timebox: 8 minutes.
  • Accuracy check: can a viewer answer the three goals in under 10 seconds?
Show solution

Use 100% stacked bars with one bar per region; segments are products A–E. Sort regions by the share of the top product or by a consistent rule (alphabetical) and order segments consistently across bars. Label overall region shares by top product and add exact percentages on hover or as data labels if space allows. Alternative: three small-multiple pies if ≤5 products and shares are distinct, but 100% stacked bars remain easier to compare across regions.

Exercise 2 — Fix the visual

You’re given a pie chart with 12 expense categories. The top two categories are 28% and 22%; the rest are 5–8% each. Redesign to communicate the composition clearly and highlight top drivers.

Deliverable: specify chart type, ordering, labeling, and any grouping.

  • Timebox: 7 minutes.
  • Accuracy check: can a viewer see the top 3 and the long tail instantly?
Show solution

Use a sorted horizontal bar chart of categories by percentage. Label bars with exact % values and cumulative % at the end of each bar if helpful. Optionally group small categories into “Other” to keep to ≤8 bars and show an explorable breakdown elsewhere. Keep a zero baseline. Alternatively, a treemap works if space is tight, but bars allow easier ranking.

Self-check checklist

  • Did you choose position/length encodings for precise comparisons?
  • Are categories sorted in a meaningful order?
  • Is there a clear baseline (zero for bars) when comparing magnitudes?
  • For composition, can viewers read proportions without decoding a legend maze?
  • Did you keep pie/donut slices to ≤6 and label shares directly?

Common mistakes and how to self-check

  • Too many slices in pies/donuts. Fix: switch to bars or group into “Other”.
  • Comparing non-baseline segments in stacked bars. Fix: use grouped bars or 100% stacked bars if relative shares matter.
  • Non-zero baseline for bars. Fix: always start at zero for length comparisons.
  • Overusing dual axes. Fix: normalize, use small multiples, or split charts.
  • Color overload. Fix: use muted palette; only highlight what matters.
  • Inconsistent category order across panels. Fix: lock a common order for comparability.

Practical projects

Project 1: Channel mix dashboard

  1. List acquisition channels and weekly sessions for 12 weeks.
  2. Build stacked area for absolute trend and 100% stacked bars per week to compare mix.
  3. Add a small multiple of top 3 channels for deep dives.

Project 2: Cost structure breakdown

  1. Collect monthly expenses by category.
  2. Show current month composition as sorted bars with top N + Other.
  3. Add a waterfall from budget to actual to explain variance.

Project 3: Product adoption comparison

  1. Take 6 cohorts and measure conversion at 3 milestones.
  2. Use slope charts (3 points) per cohort as small multiples.
  3. Highlight cohorts with the steepest drop.

Learning path

  • Start: Basic bar/line literacy and labeling best practices.
  • This subskill: comparative visuals (bar, dot, slope) and part-to-whole (stacked, pie/donut, treemap).
  • Next: highlighting/annotation, small multiples, and dashboard layout for comparisons.
  • Later: perceptual principles and interaction patterns for comparisons.

Next steps

  • Apply one worked example to your current dataset today.
  • Replace one pie/donut in your dashboard with a bar or 100% stacked bar and measure time-to-insight with a teammate.
  • Take the quick test below. Everyone can take it for free; only logged-in users get saved progress.

Mini challenge (10 minutes)

You track five features’ usage across two releases. In 10 minutes, sketch a visual that shows which features gained or lost share of total usage while also allowing absolute comparison. Write 3 design choices you made and why.

Quick Test

Take the test to check your understanding. Everyone can take it for free; only logged-in users get saved progress.

Practice Exercises

2 exercises to complete

Instructions

You have product mix for three regions (North, South, West). Each region sells five products (A–E). Stakeholder goals: (1) compare each product’s share within a region, (2) see which product dominates per region, (3) quickly compare regions. Deliverable: choose a single primary chart type and list key design choices (ordering, labels, colors). Timebox: 8 minutes.
Expected Output
100% stacked bars with one bar per region; consistent segment order; direct percentage labels or concise data labels; optional highlight for the dominant product per region.

Comparative And Part To Whole Visuals — Quick Test

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