Hey there,

today I’d like to introduce you to a great R package that focuses on interactive time series visualisation. The dygraphs package is an R interface to the Dygraphs Interactive Time Series Charting Library which is implemented in JavaScript. dygraphs provides really nice methods for plotting time-series data interactively in R. These methods include (credits to the RStudio Blog):

• Automatic plotting of xts time-series objects (or other time series objects that are convertible to xts),
• Range selector interface for interactive interactive panning and zooming,
• Interactive series/point highlighting with different visual options,
• Highly configurable axis and series display (including optional 2nd Y-axis),
• Display upper/lower bars (e.g. error bars, prediction intervals) around series,
• Various graph overlays including shaded regions, event lines, and annotations,
• Use at the R console just like conventional R plots (via RStudio Viewer),
• Embeddable within R Markdown documents and Shiny web applications.

I have prepared a short application example using dygraphs to chart discharge data from the river Danube in Austria below. Please note that function read_ehyd() for importing the data set can be found at Reading data from eHYD using R.

library(dygraphs)
library(xts)

# fetch data for three Austrian gauges: Wildungsmauer, Melk and Aschach
url <- c(wm = "http://ehyd.gv.at/eHYD/MessstellenExtraData/owf?id=207373&file=4",
    me = "http://ehyd.gv.at/eHYD/MessstellenExtraData/owf?id=207134&file=4",
    ah = "http://ehyd.gv.at/eHYD/MessstellenExtraData/owf?id=207035&file=4")

discharge <- do.call(cbind, lapply(url, read.ehyd))

# plot w/ dygraph
dygraph(discharge, main = "Discharge of River Danube") %>% 
    dyRangeSelector() %>%
    dySeries("wm", label = "Wildungsmauer") %>%
    dySeries("me", label = "Melk") %>%
    dySeries("ah", label = "Aschach") %>%
    dyHighlight(highlightCircleSize = 5,
        highlightSeriesOpts = list(strokeWidth = 3),
        highlightSeriesBackgroundAlpha = 0.2,
        hideOnMouseOut = FALSE)

# time series with data coverage for all gauges
common.start <- index(head(na.omit(discharge), 1))
dygraph(discharge[index(discharge) >= common.start, ],
    main = "Discharge of River Danube") %>% 
    dyRangeSelector() %>%
    dySeries("wm", label = "Wildungsmauer") %>%
    dySeries("me", label = "Melk") %>%
    dySeries("ah", label = "Aschach") %>%
    dyHighlight(highlightCircleSize = 5,
        highlightSeriesOpts = list(strokeWidth = 3),
        highlightSeriesBackgroundAlpha = 0.2,
        hideOnMouseOut = FALSE)

This is how the resulting plot looks like: