Interactively plotting multiple lines with shiny and ggplot2 - r

Question

I'm creating a shiny application that will have a checkboxGroupInput, where each box checked will add another line to a frequency plot. I'm trying to wrap my head around reshape2 and ggplot2 to understand how to make this possible.
data:
head(testSet)
date store_id product_id count
1 2015-08-15 3 1 8
2 2015-08-15 3 3 1
3 2015-08-17 3 1 7
4 2015-08-17 3 2 3
5 2015-08-17 3 3 1
6 2015-08-18 3 3 2
class level information:
dput(droplevels(head(testSet, 10)))
structure(list(date = structure(c(16662, 16662, 16664,
16664, 16664, 16665, 16665, 16665, 16666, 16666), class = "Date"),
store_id = c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), product_id = c(1L,
3L, 1L, 2L, 3L, 3L, 1L, 2L, 1L, 2L), count = c(8L, 1L, 7L,
3L, 1L, 2L, 18L, 1L, 0L, 2L)), .Names = c("date", "store_id",
"product_id", "count"), row.names = c(NA, 10L), class = "data.frame")
The graph should have an x-axis that corresponds to date, and a y-axis that corresponds to count. I would like to have a checkbox group input where for each box representing a product checked, a line corresponding to product_id will be plotted on the graph. The data is already filtered to store_id.
My first thought was to write a for loop inside of the plot to render a new geom_line() per each returned value of the input$productId vector. -- however after some research it seems that's the wrong way to go about things.
Currently I'm trying to melt() the data down to something useful, and then aes(...group=product_id), but getting errors on whatever I try.
Attempting to melt the data:
meltSet <- melt(testSet, id.vars="product_id", value.name="count", variable.name="date")
head of meltSet
head(meltSet)
product_id date count
1 1 date 16662
2 3 date 16662
3 1 date 16664
4 2 date 16664
5 3 date 16664
6 3 date 16665
tail of meltSet
tail(meltSet)
product_id date count
76 9 count 5
77 1 count 19
78 2 count 1
79 3 count 39
80 8 count 1
81 9 count 4
Plotting:
ggplot(data=meltSet, aes(x=date, y=count, group = product_id, colour = product_id)) + geom_line()
So my axis and values are all wonky, and not what I'm expecting from setting the plot.

Answer 1

If I'm understanding it correctly you don't need any melting, you just need to aggregate your data, summing up count by date and product_id. you can use data.table for this purpose:
testSet = data.table(testSet)
aggrSet = testSet[, .(count=sum(count)), by=.(date, product_id)]
You can do your ggplot stuff on aggrSet. It has three columns now: date, product_id, count.
When you melt like you did you merge two variables with different types into date: date(Date) and store_id(int).