nammoooo / r-visualization

Data Visualisation by R

R-Visualization

GG plots – Grammar of graphics

**Data layer** – data which visualization to be done

**Aesthetics layer** – metrics/scales onto which data has to be mapped – X, Y, shape, size, col

**Geometric layer** – Type of plots/geometry which has to be created – histogram, bar, box etc

**Facet layer** – dividing the plot into subgroups/facets -

**Theme layer** – adding themes to the final layer

histogram

ggplot(data = diamonds,aes(x=price)) + geom_histogram(fill="green",col="red")

Setting binwidth

ggplot(data = diamonds,aes(x=price)) + geom_histogram(fill="green",col="red",bins = 10)

bar plot

ggplot(data = diamonds,aes(x=cut)) + geom_bar () ggplot(data = diamonds,aes(x=cut)) + geom_bar (fill="palegreen",col="orange")

table(diamonds$cut) Fair Good Very Good Premium Ideal 1610 4906 12082 13791 21551

scatter-plot

ggplot(data = diamonds,aes(x=carat,y=price)) + geom_point() ggplot(data = diamonds,aes(x=carat,y=price)) + geom_point (col="orange")

continous numerical value scatter-plot

ggplot(data = diamonds,aes(x=carat,y=price,col=price)) + geom_point ()

categorical data value scatter-plot

ggplot(data = diamonds,aes(x=carat,y=price,col=cut)) + geom_point ()

Boxplot - numerical & categorical distribution

ggplot(data = diamonds,aes(x=clarity,y=carat,col=cut)) + geom_boxplot() ggplot(data = diamonds,aes(x=clarity,y=carat,fill=clarity)) + geom_boxplot() ggplot(data = diamonds,aes(x=clarity,y=carat)) + geom_boxplot()

ggplot(data = diamonds,aes(x=price)) + geom_histogram (fill="khaki3",col="lavenderblush4") ggplot(data = diamonds,aes(x=price,fill=price)) + geom_histogram ()