Learning the best packages for data visualisation in R

Basic chart types for plotting distribution e.g. Shapiro-Wilk:

• Histogram  (simple & overlayed)
• Smoothed density (simple & overlayed)
• QQ plot
• Box Plots (jitters)

Categorical data

• Bar Chart for one categorical variable 
• Bar Chart for multiple categorical variables  
• Clustered bars (Stacked)
• Dumbbell chart
• Pie chart 
• Sankey chart
• Spine Plot
  
• Mosaic plot

Categorical and continuous vars

• Age pyramid
• Heatmap
• Cleveland dot plot
  

Only continuous vars

• Scatter chart
• Bubble chart
• Time-series plot

Hierarchical data

• Dendrogram
• Sunburst plot
• Circular packing 
  

Plotting regression outcomes

• Correlation plot
• Forest plot
• Margins plot
• ROC plot

Spatial graphics 

• ggmap 
• rworlmap
• Geographic Scatterplot 
• Micromaps
• Choropleth map

working with ggplot2

• Basic use of the aesthetic components
• Combining geoms and stats
• Changing plot themes (regular and minimal)
• using ggpubr
• using ggthemes
• Advanced color schemes with RColorBrewer
• Saving with transparent backgrounds

Combining multiple charts (mfrow and mfcol)