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Stacked bar chart

A stacked bar chart divides each bar into segments representing component values whose combined length or height represents a total.

How 5 Manning books explain it

D3.js in Action, Third Edition

A stacked bar chart represents multiple series within each bar by vertically or horizontally adjoining segments whose combined extent encodes a total.

How it is used
Shows category contributions and total trends over time with segmented bars.
How deep it goes
Walks through stack output, scales, rectangle joins, axes, and order or offset effects.
Examples
Uses music-format sales by year and a rectangle data join to construct the chart.
What you can do after
Build it from scratch with d3.stack(), D3 scales, SVG rectangles, axes, and configurable order or offset.

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Everyday Data Visualization

A bar composed of segments whose combined length or height represents a total and whose segments represent components.

How it is used
Uses stacked bars to show totals composed of categories, then evaluates whether they serve a trend or comparison task.
How deep it goes
Explains practical chart-selection trade-offs and alternatives without detailing chart-construction mechanics.
Examples
Uses weekly avocado sales by product category, then compares individual, clustered, and dumbbell-bar alternatives across regions.
What you can do after
Evaluate/understand when stacking preserves a useful total and when unstacked comparisons communicate patterns more clearly.

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Starting Data Analytics with Generative AI and Python

A stacked bar plot displays multiple component values as segments accumulated within each bar.

How it is used
Uses composition-oriented charts to compare order-status totals across product categories.
How deep it goes
Explains pivoting, plotting, formatting, interpretation, and readability limits, but does not develop statistical theory.
Examples
Demonstrates order statuses by product category and discusses stacked alternatives for product popularity and review-score distributions.
What you can do after
Apply it via pandas and Matplotlib to compare totals and component distributions, then inspect crowded or misleading outputs.

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Pandas Workout: 200 exercises to make you a stronger data analyst

A bar plot in which multiple component values are stacked within each bar to show a total and its parts.

How it is used
Uses grouped taxi data to compare totals and revenue composition across months, years, or passenger counts.
How deep it goes
Explains grouping, component selection, summation, and stacked plotting, but does not develop chart customization beyond size and legend.
Examples
Uses New York taxi revenue components grouped by year-month and passenger count.
What you can do after
Build it from scratch by aggregating component columns and calling pandas plot.bar with stacked=True.

Read how Pandas Workout: 200 exercises to make you a stronger data analyst explains stacked bar chart →

Data Storytelling with Altair and AI

A stacked bar chart displays categorical quantities as segments within bars so component values form a total.

How it is used
Communicates how categorical components contribute to a total and helps audiences grasp an extracted insight quickly.
How deep it goes
Explains category selection, percentage calculation, reshaping, encodings, and scale limitations, but defers deeper visualization theory.
Examples
Uses pet participation percentages and competition times reshaped into stacked series as concrete charting examples.
What you can do after
Builds a stacked bar chart from tabular data and revises the design when scale differences prevent effective comparison.

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Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.