Facet Plots in ggplot2

How to make Facet Plots in ggplot2 with Plotly.

New to Plotly?

Plotly is a free and open-source graphing library for R. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Basic

library(reshape2)
library(plotly)

p <- ggplot(tips, aes(x=total_bill, y=tip/total_bill)) + geom_point(shape=1)

# Divide by levels of "sex", in the vertical direction
p <- p + facet_grid(sex ~ .)

ggplotly(p)

Horizontal Grid

library(reshape2)
library(plotly)

p <- ggplot(tips, aes(x=total_bill, y=tip/total_bill)) + geom_point(shape=1)

# Divide by levels of "sex", in the horizontal direction
p <- p + facet_grid(. ~ sex)

ggplotly(p)

Free Scale

library(reshape2)
library(plotly)

p <- ggplot(tips, aes(x=total_bill)) + geom_histogram(binwidth=2,colour="white")

# Histogram of total_bill, divided by sex and smoker
p <- p + facet_grid(sex ~ smoker)

ggplotly(p)

Free Y Axis

library(reshape2)
library(plotly)

p <- ggplot(tips, aes(x=total_bill)) + geom_histogram(binwidth=2,colour="white")

# Same as above, with scales="free_y"
p <- p + facet_grid(sex ~ smoker, scales="free_y")

ggplotly(p)

Varied Range

library(reshape2)
library(plotly)

p <- ggplot(tips, aes(x=total_bill)) + geom_histogram(binwidth=2,colour="white")

# With panels that have the same scaling, but different range (and therefore different physical sizes)
p <- p + facet_grid(sex ~ smoker, scales="free", space="free")

ggplotly(p)

Time Series Data

library(plotly)
require(scales)
require(gridExtra)

mymelt <- structure(list(mydate = structure(c(15340, 15340, 15340, 15340, 15340, 15340, 15340, 15340, 15340, 15340, 15340, 15340, 15371, 15371, 15371, 15371, 15371, 15371, 15371, 15371, 15371, 15371, 15371, 15371, 15400, 15400, 15400, 15400, 15400, 15400, 15400, 15400, 15400, 15400, 15400, 15400, 15431, 15431, 15431, 15431, 15431, 15431, 15431, 15431, 15431, 15431, 15431, 15431, 15461, 15461, 15461, 15461, 15461, 15461, 15461, 15461, 15461, 15461, 15461, 15461, 15492, 15492, 15492, 15492, 15492, 15492, 15492, 15492, 15492, 15492, 15492, 15492, 15522, 15522, 15522, 15522, 15522, 15522, 15522, 15522, 15522, 15522, 15522, 15522, 15553, 15553, 15553, 15553, 15553, 15553, 15553, 15553, 15553, 15553, 15553, 15553), class = "Date"), variable = c("b", "bc", "f", "in", "it", "l", "of", "o", "pr", "s", "total", "tr", "b", "bc", "f", "in", "it", "l", "of", "o", "pr", "s", "total", "tr", "b", "bc", "f", "in", "it", "l", "of", "o", "pr", "s", "total", "tr", "b", "bc", "f", "in", "it", "l", "of", "o", "pr", "s", "total", "tr", "b", "bc", "f", "in", "it", "l", "of", "o", "pr", "s", "total", "tr", "b", "bc", "f", "in", "it", "l", "of", "o", "pr", "s", "total", "tr", "b", "bc", "f", "in", "it", "l", "of", "o", "pr", "s", "total", "tr", "b", "bc", "f", "in", "it", "l", "of", "o", "pr", "s", "total", "tr"), value = c(-23, 6.90000000000001, 459.799999999999, -403.6, -56.1, -95, -13.8, 32.6, 121.5, -15.7, 26.2000000000007, 12.5, -25.1, 238.3, 1047.2, -803.2, -151.5, -260.5, -59.6, -93.8, 461.5, -37.7, 26.7999999999993, -288.8, -46.4, 249, 1289.8, -783.2, -188.1, -414.9, -77.7, -61, 928.4, -36.8, 17.4000000000015, -841.7, -46.5, 276.2, 1384.8, -541.1, -71.8999999999999, -433.3, -61.3, -28.3, 494.699999999999, -23.4, -14.5999999999985, -964.5, -46.1, 376.2, 1020.1, -119.4, 56.8000000000001, -447.7, -9.50000000000001, 14.2, -9.20000000000164, 2.5, -42.7999999999993, -880.6, -52.9, 345.5, 892.599999999999, -241.8, 144.3, -428.2, -3.30000000000001, 91.9, -294.800000000002, -5.19999999999999, -42.1999999999971, -490.1, -64.5, 379.7, 679.299999999999, -143.1, 185.9, -419.8, -4.30000000000001, 182.4, -421.900000000002, 1.80000000000001, -59.8999999999978, -435.2, -80.2, 422.2, 645.499999999998, -391.4, 76.6000000000001, -387.4, -1.70000000000001, 211.2, -131.500000000002, -10.6, -40.8999999999978, -393.6), fill = c("#A4D3EE80", "#A478AB80", "#01AEF080", "#8DC73F80", "#F8931D80", "#FFAAAA80", "#8C8C8C", "#D38D5F80", "#23238E80", "#77B9B780", "#C8373780", "#EEDD8280", "#A4D3EE80", "#A478AB80", "#01AEF080", "#8DC73F80", "#F8931D80", "#FFAAAA80", "#8C8C8C", "#D38D5F80", "#23238E80", "#77B9B780", "#C8373780", "#EEDD8280", "#A4D3EE80", "#A478AB80", "#01AEF080", "#8DC73F80", "#F8931D80", "#FFAAAA80", "#8C8C8C", "#D38D5F80", "#23238E80", "#77B9B780", "#C8373780", "#EEDD8280", "#A4D3EE80", "#A478AB80", "#01AEF080", "#8DC73F80", "#F8931D80", "#FFAAAA80", "#8C8C8C", "#D38D5F80", "#23238E80", "#77B9B780", "#C8373780", "#EEDD8280", "#A4D3EE80", "#A478AB80", "#01AEF080", "#8DC73F80", "#F8931D80", "#FFAAAA80", "#8C8C8C", "#D38D5F80", "#23238E80", "#77B9B780", "#C8373780", "#EEDD8280", "#A4D3EE80", "#A478AB80", "#01AEF080", "#8DC73F80", "#F8931D80", "#FFAAAA80", "#8C8C8C", "#D38D5F80", "#23238E80", "#77B9B780", "#C8373780", "#EEDD8280", "#A4D3EE80", "#A478AB80", "#01AEF080", "#8DC73F80", "#F8931D80", "#FFAAAA80", "#8C8C8C", "#D38D5F80", "#23238E80", "#77B9B780", "#C8373780", "#EEDD8280", "#A4D3EE80", "#A478AB80", "#01AEF080", "#8DC73F80", "#F8931D80", "#FFAAAA80", "#8C8C8C", "#D38D5F80", "#23238E80", "#77B9B780", "#C8373780", "#EEDD8280")), .Names = c("mydate", "variable", "value", "fill"), row.names = c(NA, 96L), class = "data.frame")

myvals <- mymelt[mymelt$mydate == mymelt$mydate[nrow(mymelt)],] ## last date in mymelt should always be same as plotenddate as we subset earlier
mymelt <- within(mymelt, variable <- factor(variable, as.character(myvals[order(myvals$value, decreasing = T),]$variable), ordered = TRUE))

p <- ggplot(mymelt, aes(x = mydate, y = value)) +
    geom_line(lwd=0.3) +
    facet_grid(. ~ variable) +
    theme(axis.text.x = element_text(size = 5, angle = 90),
          axis.text.y = element_text(size = 8),
          axis.title.x = element_text(vjust = 0),
          axis.ticks = element_blank(),
          panel.grid.minor = element_blank())

ggplotly(p)

Geom Line

library(plotly)
library(plyr)

date <- rep(as.Date(1:365,origin='2011-1-1'),7)
location <- factor(rep(1:7,365))
product <- rep(letters[1:7], each=365)
value <- c(sample(1:10, size=365, replace=T),sample(1:3, size=365, replace=T),
           sample(10:100, size=365, replace=T), sample(1:50, size=365, replace=T),
           sample(1:20, size=365, replace=T),sample(50:100, size=365, replace=T),
           sample(1:100, size=365, replace=T))
dat<-data.frame(date,location,product,value)

p <- ggplot(dat, aes(x=date, y=value, color=location, group=location)) +
    geom_line()+
    facet_grid(product ~ ., scale = "free_y")

ggplotly(p)

What About Dash?

Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash for R at https://dashr.plot.ly/installation.

Everywhere in this page that you see fig, you can display the same figure in a Dash for R application by passing it to the figure argument of the Graph component from the built-in dashCoreComponents package like this:

library(plotly)

fig <- plot_ly() 
# fig <- fig %>% add_trace( ... )
# fig <- fig %>% layout( ... ) 

library(dash)
library(dashCoreComponents)
library(dashHtmlComponents)

app <- Dash$new()
app$layout(
    htmlDiv(
        list(
            dccGraph(figure=fig) 
        )
     )
)

app$run_server(debug=TRUE, dev_tools_hot_reload=FALSE)