This post demonstrates the use of two very cool R packages - ggrepel and patchwork. ggrepel deals with overlapping text labels (Code#1 at the bottom of this post): patchwork is a very convenient new package for combining multiple different plots together (i.e. what we usually to use grid and gridExtra for). More info: https://github.com/slowkow/ggrepel https://github.com/thomasp85/patchwork To really demonstrate the power of them, let’s make a global map of country names using ggrepel:

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What is Shiny? Shiny is an R package (install.packages("shiny")) for making your outputs interactive. Furthermore, Shiny creates web apps meaning your work can be shared online with people who don’t use R. In other words: with Shiny, R people can make websites without ever learning Javascript etc. I am completely obsessed with Shiny and these days I end up presenting most of my work in a Shiny app. If it’s not worth putting in a Shiny app it’s not worth doing.

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With a simple combination of mutate_if and fct_explicit_na, you can replace all NAs in all factors with “Missing”: dplyr reference: http://dplyr.tidyverse.org/reference forcats reference: http://dplyr.tidyverse.org/reference

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ggplot includes built in and seamless functionality that summarises your data before plotting it. As shown in the example below, ggplot_build() can be used to access the summarised dataset. fill y count prop x PANEL group ... #D7301F 0.2147239 35 1 1 1 4 ... #FC8D59 0.6871166 77 1 1 1 3 ... #FDCC8A 0.9570552 44 1 1 1 2 ... #FEF0D9 1.0000000 7 1 1 1 1 ... #D7301F 0.

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install.packages(‘maps’) iso = maps::iso3166 > str(iso) 'data.frame': 269 obs. of 5 variables: $ a2 : chr "AW" ... $ a3 : chr "ABW" ... $ ISOname : chr "Aruba" .. $ mapname : chr "Aruba" ... $ sovereignty: chr "Netherlands" ...

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