Plotting by group in data.table

Base R solution using matplot and dcast

dt_agg <- dt[ , .(mean = mean(outcome)), by=.(grp,time)]
dt_cast <- dcast(dt_agg, time~grp, value.var="mean")
dt_cast[ , matplot(time, .SD[ , !"time"], type="l", ylab="mean", xlab="")]
# alternative:
dt_cast[ , matplot(time, .SD, type="l", ylab="mean", xlab=""), .SDcols = !"time"]

Result:

There is a way to do this with data.table's by argument as follows:

DT[ , mean(outcome), by = .(grp, time)
    ][ , {plot(NULL, xlim = range(time),
           ylim = range(V1)); .SD}
       ][ , lines(time, V1, col = .GRP), by = grp]

Note that the intermediate {...; .SD} part is necessary to continue chaining. If DT[ , mean(outcome), by = .(grp, time)] were already stored as another data.table, DT_m, then we could just do:

DT_m[ , plot(NULL, xlim = range(time), ylim = range(V1))]
DT_m[ , lines(time, V1, col = .GRP), by = grp]

With output

Much fancier results are possible; for example, if we wanted to specify specific colors for each group:

grp_col <- c(a = "blue", b = "black",
             c = "darkgreen", d = "red")
DT[ , mean(outcome), by = .(grp, time)
    ][ , {plot(NULL, xlim = range(time),
           ylim = range(V1)); .SD}
       ][ , lines(time, V1, col = grp_col[.BY$grp]), by = grp]

---

NOTE

There is a bug in RStudio which will cause this code to fail if the output is sent to the RStudio graphics device. As such this approach only works from R on the command line or from sending the output to an external device (I sent it to png to produce the above).

See data.table issue #1524, this RStudio support ticket, and these SO Qs (1 and 2)

You are very much on the right track. Use ggplot to do this as follows:

(dt_agg <- dt[,.(mean = mean(outcome)),by=list(grp,time)]) # Aggregated data.table
     grp time        mean
  1:   a    1  0.75865672
  2:   a    2  0.07244879
 ---

Now ggplot this aggregated data.table

require(ggplot2)
ggplot(dt_agg, aes(x = time, y = mean, col = grp)) + geom_line()

Result: