Python Data Automation · Chapter 7 of 10

Visualization

Use Matplotlib with pandas outputs to build clear line and bar charts for trend and category comparison.

Why this chapter matters

Clear plots help teams see performance changes quickly and reduce misinterpretation in KPI discussions.

What you will learn

  • Choose chart types that match trend or comparison questions.
  • Label axes, units, legends, and titles clearly.
  • Export figures with reproducible size and layout settings.

Lessons in this chapter

  1. Line charts for trendsPlot ordered time-series values correctly.
  2. Bar charts for categoriesCompare grouped values without visual distortion.
  3. Chart annotationAdd targets and notes that explain gaps and outliers.
  4. Guide: data visualizationTurn summary tables into report-ready visuals. Read the full guide →

Study task

Plot weekly revenue with a target line, then create a bar chart for current-week revenue by channel.

Chapter checkpoint

Why must time values be sorted before line plotting?

Unsorted time points can create misleading line paths and hide actual trend direction.