geom_polygon in ggplot2
Examples of geom_polygon in R.
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library(plotly)
packageVersion('plotly')
## [1] '4.5.6.9000'
Basic Ploygon
library(plotly)
ids <- factor(c("1.1", "2.1", "1.2", "2.2", "1.3", "2.3"))
values <- data.frame(
id = ids,
value = c(3, 3.1, 3.1, 3.2, 3.15, 3.5)
)
positions <- data.frame(
id = rep(ids, each = 4),
x = c(2, 1, 1.1, 2.2, 1, 0, 0.3, 1.1, 2.2, 1.1, 1.2, 2.5, 1.1, 0.3,
0.5, 1.2, 2.5, 1.2, 1.3, 2.7, 1.2, 0.5, 0.6, 1.3),
y = c(-0.5, 0, 1, 0.5, 0, 0.5, 1.5, 1, 0.5, 1, 2.1, 1.7, 1, 1.5,
2.2, 2.1, 1.7, 2.1, 3.2, 2.8, 2.1, 2.2, 3.3, 3.2)
)
datapoly <- merge(values, positions, by=c("id"))
p <- ggplot(datapoly, aes(x=x, y=y)) + geom_polygon(aes(fill=value, group=id))
p <- ggplotly(p)
# Create a shareable link to your chart
# Set up API credentials: https://plot.ly/r/getting-started
chart_link = plotly_POST(p, filename="geom_polygon/basic")
chart_link
Inspired by ggplot2 docs
Ellipses
# create data
set.seed(20130226)
n <- 200
x1 <- rnorm(n, mean = 2)
y1 <- 1.5 + 0.4 * x1 + rnorm(n)
x2 <- rnorm(n, mean = -1)
y2 <- 3.5 - 1.2 * x2 + rnorm(n)
class <- rep(c("A", "B"), each = n)
df <- data.frame(x = c(x1, x2), y = c(y1, y2), colour = class)
# get code for "stat_ellipse"
library(devtools)
library(ggplot2)
library(proto) #source_url("https://raw.github.com/JoFrhwld/FAAV/master/r/stat-ellipse.R")
p <- qplot(data = df, x = x, y = y, colour = class) +
stat_ellipse(geom = "polygon", alpha = 1/2, aes(fill = class))
p <- ggplotly(p)
# Create a shareable link to your chart
# Set up API credentials: https://plot.ly/r/getting-started
chart_link = plotly_POST(p, filename="geom_polygon/ellipses")
chart_link
Highlighting
library(plotly)
tmp <- with(mtcars, data.frame(x=c(0, 0, max(wt)*35), y=c(0, max(wt), max(wt))))
p <- ggplot(mtcars, aes(hp, wt)) +
geom_polygon(data=tmp, aes(x, y), fill="#d8161688") +
geom_point()
p <- ggplotly(p)
# Create a shareable link to your chart
# Set up API credentials: https://plot.ly/r/getting-started
chart_link = plotly_POST(p, filename="geom_polygon/highlight")
chart_link
Inspired by Stack Overflow
Vertical Conversion
library(plotly)
library(data.table)
df<-data.table(Product=letters[1:10], minX=1:10, maxX=5:14, minY= 10:1, maxY=14:5)
df.t<-data.table(rbind( df[,list(Product,X=minX,Y=minY)],
df[,list(Product,X=minX,Y=maxY)],
df[,list(Product,X=maxX,Y=minY)],
df[,list(Product,X=maxX,Y=maxY)]))[
order(Product,X,Y)]
p <- ggplot(df,aes(xmin=minX,xmax=maxX,ymin=minY,ymax=maxY,fill=Product))+
geom_rect()
p <- ggplotly(p)
# Create a shareable link to your chart
# Set up API credentials: https://plot.ly/r/getting-started
chart_link = plotly_POST(p, filename="geom_polygon/vertical")
chart_link
Inspired by Stack Overflow
Distributions
library(plotly)
x=seq(-2,2,length=200)
dat <- data.frame(
norm = dnorm(x,mean=0,sd=0.2),
logistic = dlogis(x,location=0,scale=0.2), x = x
)
p <- ggplot(data=dat, aes(x=x)) +
geom_polygon(aes(y=norm), fill="red", alpha=0.6) +
geom_polygon(aes(y=logistic), fill="blue", alpha=0.6) +
xlab("z") + ylab("") +
scale_x_continuous(expand = c(0, 0)) +
scale_y_continuous(expand = c(0, 0))
p <- ggplotly(p)
# Create a shareable link to your chart
# Set up API credentials: https://plot.ly/r/getting-started
chart_link = plotly_POST(p, filename="geom_polygon/distributions")
chart_link
Inspired by Stack Overflow
Convex Hull
library(plotly)
doInstall <- TRUE # Change to FALSE if you don't want packages installed.
toInstall <- c("RColorBrewer")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)
# Generate some data
nn <- 500
myData <- data.frame(X = rnorm(nn),
Y = rnorm(nn))
setK = 6 # How many clusters?
clusterSolution <- kmeans(myData, centers = setK)
myData$whichCluster <- factor(clusterSolution$cluster)
splitData <- split(myData, myData$whichCluster)
appliedData <- lapply(splitData, function(df){
df[chull(df), ] # chull really is useful, even outside of contrived examples.
})
combinedData <- do.call(rbind, appliedData)
zp3 <- ggplot(data = myData,
aes(x = X, y = Y))
zp3 <- zp3 + geom_polygon(data = combinedData, # This is also a nice example of how to plot
aes(x = X, y = Y, fill = whichCluster), # two superimposed geoms
alpha = 1/2) # from different data.frames
zp3 <- zp3 + geom_point(size=1)
zp3 <- zp3 + coord_equal()
zp3 <- zp3 + scale_fill_manual(values = colorRampPalette(rev(brewer.pal(11, "Spectral")))(setK))
p <- ggplotly(zp3)
# Create a shareable link to your chart
# Set up API credentials: https://plot.ly/r/getting-started
chart_link = plotly_POST(p, filename="geom_polygon/convex")
chart_link
Inspired by is.R()
County-Level Boundaries
library(plotly)
library(maps)
county_df <- map_data("county")
state_df <- map_data("state")
# create state boundaries
p <- ggplot(county_df, aes(long, lat, group = group)) +
geom_polygon(colour = alpha("black", 1/2), fill = NA) +
geom_polygon(data = state_df, colour = "black", fill = NA) +
theme_void()
p <- ggplotly(p)
# Create a shareable link to your chart
# Set up API credentials: https://plot.ly/r/getting-started
chart_link = plotly_POST(p, filename="geom_polygon/county-level-boundaries")
chart_link
County-Level Choropleths
library(plotly)
library(maps)
# map data
county_df <- map_data("county")
state_df <- map_data("state")
county_df$subregion <- gsub(" ", "", county_df$subregion)
#election data
df <- read.csv("https://raw.githubusercontent.com/bcdunbar/datasets/master/votes.csv")
df <- subset(df, select = c(Obama, Romney, area_name))
df$area_name <- tolower(df$area_name)
df$area_name <- gsub(" county", "", df$area_name)
df$area_name <- gsub(" ", "", df$area_name)
df$area_name <- gsub("[.]", "", df$area_name)
df$Obama <- df$Obama*100
df$Romney <- df$Romney*100
for (i in 1:length(df[,1])) {
if (df$Obama[i] > df$Romney[i]) {
df$Percent[i] = df$Obama[i]
} else {
df$Percent[i] = -df$Romney[i]
}
}
names(df) <- c("Obama", "Romney", "subregion", "Percent")
# join data
US <- inner_join(county_df, df, by = "subregion")
US <- US[!duplicated(US$order), ]
# colorramp
blue <- colorRampPalette(c("navy","royalblue","lightskyblue"))(200)
red <- colorRampPalette(c("mistyrose", "red2","darkred"))(200)
#plot
p <- ggplot(US, aes(long, lat, group = group)) +
geom_polygon(aes(fill = Percent),
colour = alpha("white", 1/2), size = 0.05) +
geom_polygon(data = state_df, colour = "white", fill = NA) +
ggtitle("2012 US Election") +
scale_fill_gradientn(colours=c(blue,"white", red), limits = c(100, -100)) +
theme_void()
p <- ggplotly(p)
# Create a shareable link to your chart
# Set up API credentials: https://plot.ly/r/getting-started
chart_link = plotly_POST(p, filename="geom_polygon/county-level-choropleth")
chart_link