Data Visualization Proficiency (Advanced Level)

Topics covered

• configure elements such as text and icons to create an infographic
• create a box-and-whisker-plot with separate categories on the x-axis and based on the color of the box, then add lines linking the means for all categories
• create a Sankey diagram to visualize data
• create a waffle or KPI chart with a grid of percentages that update based on an index that in turn updates based on the value of a spin button
• create a waterfall chart to show the cumulative effect of positive and negative values over a specified period of time to add up to a total final value
• create a waterfall chart to visualize the cumulative effect of positive and negative values when analyzing the financials of a company
• create bar and lollipop charts that visualize multiple related variables in one chart
• create drawn Lollipop charts to compare categorical data to continuous values
• create maps to visualize geographical data
• customize scatter plots to have three dimensions using the sizes of data points
• display the relationship between two variables and understand what kind of model might be most useful to represent that relationship
• identify relationships between entities using a network chart
• represent data using a clustered bar chart
• 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 visualize compositions over a period of time using area charts and changes over time using stem plots
• visualize data using a stacked bar chart
• visualize proportions in data using donut charts
• visualize the flow of data using a Sankey diagram
• work with different kinds of gauge charts, such as tanks, thermometers, and joysticks