README.md

In artidata/artidata.viz: Artidata's Personal Data Visualization Package

artidata.viz

Artidata’s Personal Data Visualization Package

Installation

Install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("artidata/artidata.viz")

Example

Setting up a random dataset:

library(artidata.viz)
library(data.table)
library(ggplot2)
library(scales)

set.seed(240193)

N=10000

dtA=data.table(x=runif(N,-3,3),y=runif(N,-3,3),z="A")

dtB=data.table(x=rnorm(N),y=rnorm(N),z="B")

dtC=data.table(x=seq(-3,3,length.out = N))
dtC[,":="(y=0.5*x+rnorm(N,sd=0.5),z="C"),]

dtD=data.table(x=c(rnorm(N/2,-1,.75),rnorm(N/2,1,.75)),
               y=c(rnorm(N/2,1,.75),rnorm(N/2,-1,.75)),
               z="D")

dt1=rbindlist(list(dtA,dtB,dtC,dtD))

The default scatter plot:

ggplot(dt1,aes(x,y))+
  geom_point(size=0.1)+
  facet_wrap(vars(z))

The default ggplot2 2D-histogram:

ggplot(dt1,aes(x,y))+
  geom_bin2d()+
  facet_wrap(vars(z))

2D-Histogram output:

hist2d(dt1,facet=1)

You can also add Linear Regression line:

hist2d(dt1,facet=1,hasLine=T)

artidata/artidata.viz documentation built on May 4, 2020, 3:06 p.m.