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Use the Divorce data (Case Study 01) to generate appropriate visualization of histograms, density plots, pie charts, heatmaps, barplots, and paired correlation plots.
Use the SOCR Resource Hierarchical data (JSON) to generate some tree/graph displays of the structural information.
facet_grid(); 4) all figures have year as x axis; 5) the first figure includes three curves(fossil, nuclear and renewable) for each subplot; the second figure includes two curves(consumption and production) for each subplot.MTH_1, MTH_2, …, MTH_12. (Hint: you need obtain the correlation matrix first, then apply the corrplot package. Try to some alternative methods as well, circle, pie, mixed etc.)time=0) to generate a heat plot. Set RowSideColors, ColSideColors and rainbow. [Hint: you may need to select columns, properly convert the data, and normalize it.]Overall_Score vs. Average_Income(USD) include title and label the axes. Then try qplot for Overall_Score vs. Average_Income(USD): 1) fill with the Stress_Level; 2) Size the points according to Hiring_Potential; and 3) label using Job_Title.cutree() and select any \(k\) you prefer. (Use variables Q1 - Q28).