data exploration

A Scientist's Guide to R: Step 3.1 - data visualization with ggplot2+

1 TL;DR 2 Introduction 3 Setup 4 ggplot2 basics 5 aesthetic customization 5.1 titles/labels 5.2 fill 5.3 colour/color 5.4 reordering factors 5.5 colour palettes 5.6 colourblind-friendly palettes 5.7 size 5.8 shape 5.9 linetype 5.10 alpha (transparency/opacity) 5.11 jittering to reduce overplotting 5.12 coordinates 5.12.1 coord_flip() 5.12.2 coord_cartesian() 5.13 guides (legends) 5.14 x & y axis modifications 5.14.1 scale_x_continuous()/scale_y_continuous() 5.14.2 scale_x_discrete()/scale_y_discrete() 5.

A Scientist's Guide to R: Step 3.0 - exploring data with elucidate

1 TL;DR 2 Introduction 3 Installation & Setup 4 Interrogating Data 4.1 checking for row copies() and dupes() 4.2 count()-ing unique values 4.3 describe()-ing missingness & extreme values 5 Descriptives 5.1 describe() a vector with summary statistics 5.2 grouped descriptions 5.3 describe_all() columns in a data frame 5.4 confidence intervals 6 To see, look 6.1 Anscombe’s lesson: numeric descriptions can be misleading 6.2 plot_*-ting data with elucidate 6.