GTrendsR + ggplot2?

Question

I want to generate a plot of interest over time using GTrendsR and ggplot2

The plot I want (generated with google trends) is this:

Any help will be much appreciated.

Thanks!

---

This is the best I was able to get:

library(ggplot2)
library(devtools)
library(GTrendsR)
usr = "my.email"
psw = "my.password"
ch = gConnect(usr, psw)

location = "all"
query = "MOOCs"
MOOCs_trends = gTrends(ch, geo = location, query = query)
MOOCs<-MOOCs_trends[[1]]
MOOCs$moocs<-as.numeric(as.character(MOOCs$moocs))
MOOCs$Week <- as.character(MOOCs$Week)
MOOCs$start <- as.Date(MOOCs$Week)

ggplot(MOOCs[MOOCs$moocs!=0,], aes(start, moocs)) + 
  geom_line(colour = "blue") + 
  ylab("Trends") + xlab("") + theme_bw()

I think that to match the graph generated by google I would need to aggregate the data to months instead of weeks... not sure how to do that yet

Answer 1

The object returned by gtrendsR is a list, of which the trend element in a data.frame that you would want to plot.

usr = "my.email"
psw = "my.password"
gconnect(usr, psw)

MOOCs_trends = gtrends('MOOCs')

MOOCsDF <- MOOCs_trends$trend

ggplot(data = MOOCsDF) + geom_line(aes(x=start, y=moocs))

This gives:

Now if you want to aggregate by month, I would suggest using the floor_date function from the lubridate package, in combination with dplyr (note that I am using the chain operator %>% which dplyr re-exports from the magrittr package).

usr = "my.email"
psw = "my.password"
gconnect(usr, psw)

MOOCs_trends = gtrends('MOOCs')

MOOCsDF <- MOOCs_trends

MOOCsDF$start <- floor_date(MOOCsDF$start, unit = 'month')

MOOCsDF %>%
  group_by(start) %>%
  summarise(moocs = sum(moocs)) %>%
  ggplot() + geom_line(aes(x=start, y=moocs))

This gives:

Note 1: The query MOOCs was changed to moocs, by gtrendsR, this is reflected in the y variable that you're plotting.

Note 2: some of the cases of functions have changed (e.g. gtrendsR not GTrendsR), I am using current versions.

Answer 2

This will get you most of the way there. The plot doesn't look quite right, but that's more of a function of the data being a bit different. Here's the necessary conversions to numeric and to dates.

MOOCs<-MOOCs_trends[[1]]

library(ggplot2)
library(plyr)
## Convert to string
MOOCs$Week <- as.character(MOOCs$Week)
MOOCs$moocs <- as.numeric(MOOCs$moocs)
# split the string
MOOCs$start <- unlist(llply(strsplit(MOOCs$Week," - "), function(x) return(x[2])))
MOOCs$start <- as.POSIXlt(MOOCs$start)
ggplot(MOOCs,aes(x=start,y=moocs))+geom_point()+geom_path()

Google might do some smoothing, but this will plot the data you have.