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Stacked bar chart

As explained in 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.

A stacked bar chart combines several component values into one bar, making both the total and its breakdown visible. In a taxi-revenue analysis, each bar can represent a month while fare, extras, taxes, tips, and tolls form its colored segments. section 11.10

Break down taxi revenue by month

Group the data by pickup year and month, select the revenue components, sum them, and plot the result with stacking enabled: `(df.groupby([df['tpep_pickup_datetime'].dt.year, df['tpep_pickup_datetime'].dt.month])[['fare_amount','extra','mta_tax','tip_amount','tolls_amount']].sum().plot.bar(stacked=True, figsize=(10,10)))` Each bar shows total revenue, while its colored segments reveal how much came from fares, extras, taxes, tips, and tolls. A legend identifies the components.

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

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 it assumes
Assumes familiarity with pandas DataFrames, groupby, column selection, aggregation, and bar plotting.
What you can do after
Build it from scratch by aggregating component columns and calling pandas plot.bar with stacked=True.
How it connects
Connects pandas groupby aggregation with bar plots, legends, and comparative data visualization.

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This explainer was generated by Manning's knowledge graph from the text of Pandas Workout: 200 exercises to make you a stronger data analyst. The section links point to the parts of the book it draws on.