Plot LOESS (STL) decomposition using Ggvis - r

Question

I want to be able to plot the three different elements of The Seasonal Trend Decomposition using Loess (STL) with Ggvis.
However, I recive this error:
Error: data_frames can only contain 1d atomic vectors and lists
I am using the nottem data set.
# The Seasonal Trend Decomposition using Loess (STL) with Ggvis
# Load nottem data set
library(datasets)
nottem <- nottem
# Decompose using stl()
nottem.stl = stl(nottem, s.window="periodic")
# Plot decomposition
plot(nottem.stl)
Now, this is the information I am interested in. In order to make this into a plot that I can play around with I transform this into a data frame using the xts-package. So far so good.
# Transform nottem.stl to a data.frame
library(xts)
df.nottem.stl <- as.data.frame(as.xts(nottem.stl$time.series))
# Add date to data.frame
df.nottem.stl$date <- data.frame(time = seq(as.Date("1920-01-01"), by = ("months"), length =240))
# Glimpse data
glimpse(df.nottem.stl)
# Plot simple line of trend
plot(df.nottem.stl$date, df.nottem.stl$trend, type = "o")
This is pretty much the plot I want. However, I want to be able to use it with Shiny and therefore Ggvis is preferable.
# Plot ggvis
df.nottem.stl%>%
ggvis(~date, ~trend)%>%
layer_lines()
This is where I get my error.
Any hints on what might go wrong?

Answer 1

First of all your df.nottem.stl data.frame contains a Date data.frame, so you should be using the date$time column. Then using the layer_paths function instead of the layer_lines will make it work. I always find layer_paths working better than layer_lines:
So this will work:
library(ggvis)
df.nottem.stl%>%
ggvis(~date$time, ~trend)%>%
#for points
layer_points() %>%
#for lines
layer_paths()
Output: