The dygraphs R library is my favorite tool to plot time series. The chart #316 describes extensively its basic utilisation, notably concerning the required input format. This page aims to describe the chart types that this library offers. Remember you can zoom and hover on every following chart.

Connected scatterplot

Most of the chart types described in this post are called using the dyOptions() function. For connected scatterplots, use drawPoints = TRUE. Note that the gallery offers a whole section on connected scatterplot.

# Library
library(dygraphs)
library(xts)          # To make the convertion data-frame / xts format
 
# Create data 
data <- data.frame(
  time=seq(from=Sys.Date()-40, to=Sys.Date(), by=1 ), 
  value=runif(41)
)

# Double check time is at the date format
str(data$time)

# Switch to XTS format
data <- xts(x = data$value, order.by = data$time)
 
# Default = line plot --> See chart #316
 
# Add points
p <- dygraph(data) %>%
  dyOptions( drawPoints = TRUE, pointSize = 4 )
p

# save the widget
# library(htmlwidgets)
# saveWidget(p, file=paste0( getwd(), "/HtmlWidget/dygraphs317-1.html"))

Area chart

Area chart are built thanks to the fillGraph = TRUE option. See the area chart section of the gallery.

p <- dygraph(data) %>%
  dyOptions( fillGraph=TRUE )
p

# saveWidget(p, file=paste0( getwd(), "/HtmlWidget/dygraphs317-2.html"))

Step chart

The step chart is made using the .. stepPlot option! Use it in conjunction with fillGraph to fill the area below the curve.

p <- dygraph(data) %>%
  dyOptions( stepPlot=TRUE, fillGraph=TRUE)
p

# saveWidget(p, file=paste0( getwd(), "/HtmlWidget/dygraphs317-3.html"))

Lollipop plot

Called using the stemPlot option. See the lollipop plot section of the gallery for more.

p <- dygraph(data) %>%
  dyOptions( stemPlot=TRUE)
p

# saveWidget(p, file=paste0( getwd(), "/HtmlWidget/dygraphs317-4.html"))

Candlestick chart

The candlestick chart represents 4 series and is widely used in finance. dygraphs offers the dyCandlestick() function that allows to build them in minutes.

# Create data (needs 4 data points per date stamp)
trend <- sin(seq(1,41))+runif(41)
data <- data.frame(
  time=seq(from=Sys.Date()-40, to=Sys.Date(), by=1 ), 
  value1=trend, 
  value2=trend+rnorm(41), 
  value3=trend+rnorm(41), 
  value4=trend+rnorm(41) 
)

# switch to xts format
data <- xts(x = data[,-1], order.by = data$time)

# Plot it
p <- dygraph(data) %>%
  dyCandlestick()
p

# saveWidget(p, file=paste0( getwd(), "/HtmlWidget/dygraphs317-5.html"))

Line chart with interval

This is very handy to represent confidence interval around your time series. Don with dySeries() that takes 3 columns as input: trend and upper and lower limits of the confidence interval.

# Create data
trend <- sin(seq(1,41))+runif(41)
data <- data.frame(
  time=seq(from=Sys.Date()-40, to=Sys.Date(), by=1 ), 
  trend=trend, 
  max=trend+abs(rnorm(41)), 
  min=trend-abs(rnorm(41, sd=1))
)

# switch to xts format
data <- xts(x = data[,-1], order.by = data$time)

# Plot
p <- dygraph(data) %>%
  dySeries(c("min", "trend", "max"))
p

# saveWidget(p, file=paste0( getwd(), "/HtmlWidget/dygraphs317-6.html"))