Data Visualization in Python with Matplotlib Competency (Intermediate Level)

  • 10m
  • 10 questions
The Data Visualization in Python with Matplotlib Competency (Intermediate Level) benchmark will measure your ability to recall, relate, demonstrate, and apply data visualization concepts and techniques in Python using the Matplotlib library. You will be evaluated on your ability to recognize and apply data visualization concepts, techniques, tools, and functions in Matplotlib. A learner who scores high on this benchmark demonstrates that they have the required data visualization skills to understand, apply, and work independently on visualizations in their projects.

Topics covered

  • create a chart with two lines using two axes objects with the twinx() function
  • create a figure object with multiple axes objects and create line charts in the axes
  • create bar and lollipop charts that visualize multiple related variables in one chart
  • create drawn Lollipop charts to compare categorical data to continuous values
  • illustrate how autocorrelation and cross-correlation can be used to identify recurring patterns in data through Matplotlib
  • use Matplotlib to create a heatmap that visualizes correlations and has labels for each correlation
  • use Matplotlib to create exploded pie charts and treemaps
  • use Matplotlib to use correlation heatmaps to visually represent covariate relationships
  • use Matplotlib to visualize compositions over a period of time using area charts and changes over time using stem plots
  • use Matplotlib to visualize how individual proportions add up to a whole using pie charts