How to make "interactive" time series plots for exploratory data analysis

Question

I have a time series data frame similar to data created below. Measurements of 5 variables are taken on each individual. Individuals have unique ID numbers. Note that in this data set each individual is of the same length (each has 1000 observations), but in my real data set each individual is of has different lengths (teach individual has a different number of observations). For each individual, I want to plot all 5 variables on top of one another (i.e. all on the y axis) and plot them against time (x axis). I want to print each of these plots to an external document of some kind (pdf, or whatever is recommended for this application) with one plot per page, meaning each individual will have its own page with a single plot. I want these time series plots to be "interactive", in that I can move my mouse over a point, and it will tell me what time individual data points are at. My goal in doing this is exploring the association between peaks, valleys, and other regions between the 5 variables. I am not sure if ggplot2 is still the best application for this, but I would still like for the plots to be aesthetically appealing so that it will be easier to see patterns in the data. Also, is pasting these plots to a pdf the most sensible route? Or would I be better off using R notebook or some other application?

ID <- rep(c("A","B","C"), each=1000)
time <- rep(c(1:1000), times = 3)
one <- rnorm(1000)
two <- rnorm(1000)  
three <- rnorm(1000)
four <- rnorm(1000)
five<-rnorm(1000)
data<- data.frame(cbind(ID,time,one,two,three,four,five))

Eugene Chong Eugene Chong · Accepted Answer · 2020-02-04T15:41:58

Try using the plotly package. And since you want it to be interactive, you'll want to export as something like html rather than pdf.

To produce a single faceted plot (note I added stringAsFactors = FALSE to your sample data):

library(tidyverse)
library(plotly)

ID <- rep(c("A","B","C"), each=1000)
time <- rep(c(1:1000), times = 3)
one <- rnorm(1000)
two <- rnorm(1000)  
three <- rnorm(1000)
four <- rnorm(1000)
five<-rnorm(1000)
data<- data.frame(cbind(ID,time,one,two,three,four,five),
                  stringsAsFactors = FALSE)

data_long <- data %>% 
  gather(variable,
         value,
         one:five) %>%
  mutate(time = as.numeric(time),
         value = as.numeric(value))

plot <- data_long %>% 
  ggplot(aes(x = time, 
             y = value, 
             color = variable)) +
  geom_point() +
  facet_wrap(~ID)

interactive_plot <- ggplotly(plot)

htmlwidgets::saveWidget(interactive_plot, "example.html")

If you want to produce and export an interactive plot for every ID programmatically:

walk(unique(data_long$ID),
    ~ htmlwidgets::saveWidget(ggplotly(data_long %>% 
                                filter(ID == .x) %>% 
                                ggplot(aes(x = time, 
                                           y = value, 
                                           color = variable)) +
                                geom_point() +
                                labs(title = paste(.x))),
                              paste("plot_for_ID_", .x, ".html", sep = "")))

Edit: I changed map() to walk() so that the plots are produced without console output (previously just a list with 3 empty elements).

How to make "interactive" time series plots for exploratory data analysis

1 Answers