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Data Analysis and Visualization with Python / Resources

Learner resource

Accessibility Equivalents for Data Analysis Outputs

Applies to: charts, tables, notebooks, reports, and course pages

Purpose

Charts are useful, but not every learner or reader can access visual details in the same way. Every important chart needs a text or table equivalent so the analysis remains understandable.

Chart equivalent standard

For each important chart, include:

  • chart title;
  • chart type;
  • data used;
  • main pattern;
  • important values or ranges;
  • limitation or caution;
  • source or dataset note.

Text equivalent template

Chart title:

Chart type:

What it shows:

Main pattern:

Important values:

Limit:

Table equivalent template

ItemValueNote

Color and contrast

  • Do not use color as the only way to communicate meaning.
  • Use labels, legends, markers, or line styles where useful.
  • Avoid low-contrast text.
  • Avoid too many similar colors in one chart.
  • For categorical charts, keep palette choices consistent inside a report.

Notebook requirements

  • Important charts must be followed by a short interpretation.
  • Important summary tables should have clear column names.
  • Avoid screenshots of tables when real tables are possible.
  • Keep long tables summarized and provide the full table only when useful.

Course page requirements

  • Decorative images need concise alt text or can be marked decorative by implementation.
  • Instructional charts need meaningful alt text.
  • If a chart is central to the lesson, include the key values or interpretation in nearby text.