Data Visualization Competency (Intermediate Level)

Topics covered

• classify the advantages and disadvantages of variants of line charts, such as stacked line charts, 100% stacked line charts, and 3D line charts
• configure a basic bar chart and table that influence each other
• create a basic area chart, illustrate a major disadvantage of an ordinary area chart, then change the opacity of areas in order to overcome this problem
• create a histogram to bin a continuous data series, visualize the counts of rows in each bin, and create histograms for normally and non-normally distributed data series
• create and customize basic grid charts
• create basic combo charts with bars and lines
• customize a clustered column chart, add trendlines and format the chart, then create a basic line chart
• customize histograms using various options, such as the overflow and underflow bins to truncate the histogram on either side
• describe the difference between a column chart and a bar chart, create a clustered bar chart, and perform various operations, such as sorting on that chart
• display your visualization inline in a Jupyter notebook
• identify the components of a Plotly graph
• illustrate the use of the gradient fill feature, change various aspects of a gradient-filled line chart, and work with radial gradients and linear gradients
• import an Excel file as an XML file and separately import a JSON file into Excel and open it up in the Power Query Editor
• use a pivot table to access aggregate values in hierarchical data
• use a radar chart to visualize the multivariate ordinal data and illustrate the advantages and disadvantages of radar charts
• use Matplotlib to create exploded pie charts and treemaps
• use the pie-of-pie chart type to create one pie chart with an 'other' category and a second pie chart that expands the fields in that 'other' category
• use trendlines to explore the suitability of various kinds of regression models, such as linear regression and polynomial regression via a line chart
• visualize statistical data using box-and-whisker plots
• visualize the trend of a stock's performance based on high, low, and close values over a specific period of time using the Excel High-Low-Close stock chart