Hello,
Is it as simple as this? The code below does not separate the
participant1 and participant2, only the 'delta' variables.
idv <- grep("part", names(DB)[-(3:4)], ignore.case = TRUE, value = TRUE)
dblong <- reshape2::melt(DB[-(3:4)], id.vars = idv)
head(dblong)
ggplot(dblong, aes(x = value, fill = variable)) +
geom_density(aes(alpha = 0.2)) +
scale_alpha_continuous(guide = "none")
I will also repost the data, since you have posted a matrix and this
code needs a data.frame.
DB <-
structure(list(participation1 = c(1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,
1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), participation2 = c(1,
1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1,
0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1,
1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1,
1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1,
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1,
0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1), ParticipantsNOPUN = structure(c(2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA), .Label = c("1", "2"), class = "factor"),
ParticipantsPUN = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 1L,
2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L,
1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L,
2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L,
1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L), .Label = c("1", "2"), class = "factor"),
delta11_L = c(0, -10, -10, 0, 0, 0, -30, 0, 10, 0, 20, 10,
0, 0, 20, 0, 0, -10, 30, 10, 0, 0, 0, 0, 10, 0, 0, 0, 0,
0, 0, 0, 0, -10, 0, 0, 0, 40, -10, 0, 10, 0, 10, 0, -20,
0, 0, 0, 10, -20, 10, -10, 40, -10, -10, 10, 20, 10, 0, 0,
0, 0, 0, 0, -10, 0, 0, 20, 0, 0, 0, 0, 10, 0, 0, 0, 10, 0,
-10, 10, 0, 0, 10, 10, 10, 0, 0, 0, 0, 0, -10, 0, 0, 0, 20,
0, 0, 20, 0, 0, 0, 0, 0, 0, 0, 10, 0, 10, 0, 0, 0, 20, -20,
0, 0, -10, 0, 0, 0, 0, -10, 10, 0, 20, 0, 0, 0, 0, 0, -10,
0, 0, 0, 0, 0, -10, 0, 0, -10, 0, -10, 30, -10, 0, 0, 10,
-10, 0, -10, -10, 0, 10, 0, 0, 0, 0, 0, 0, 0, 0, 10, 0, 0,
10, 10, 0, 0, -20, -10, 0, 0, 0, 0, 0, 0, 10, 30, 40, 30,
30, 30, 30, 20, 20, 40, 20, 20, 10, 20, 30, 20, 40, 20, 30,
20, 30, 20, 20, 30, 20, 40, 10, 20, 10, 30, 30, 30, 30, 10,
30, 30, 20, 10, 40, 30, 40, 40, 30, 20, 10, 10, 20, 20, 30,
40, 40, 40, 40, 0, 20, 20, 40, 10, 20, 20, 10), delta2_L = c(0,
-10, 0, 0, 0, 0, 30, 10, 40, 0, 0, 0, 0, 0, 10, 0, 0, 30,
10, 10, 0, 0, -10, -20, -10, 0, 0, 0, -10, 10, 0, 40, 0,
30, 0, 10, 0, 40, 0, 0, -10, 0, 10, 40, -10, 0, 0, 0, 10,
0, 10, -10, 40, 10, 20, 10, 40, 0, 10, -10, 0, 40, 0, 0,
-10, 0, 0, 20, -10, 0, 10, 0, 30, -10, 0, 0, 0, -10, 40,
10, 10, 0, 10, -10, 0, 10, 0, 10, 0, -20, 20, 0, 0, -20,
20, 0, -30, 20, 0, 0, 20, 10, 0, 20, 30, 0, 0, -10, 10, 10,
0, -10, 40, 10, 0, 10, 0, 0, 20, 10, 20, 30, 0, 40, 30, 0,
20, 40, -10, 0, 0, 0, -10, 0, 20, -10, 0, 0, 10, 0, 0, 20,
-20, -20, 0, 20, 0, 0, 10, 0, -10, -10, 20, -10, 0, 0, 0,
0, 0, 0, 0, -10, 30, 10, 0, 0, 10, 20, 10, -10, 10, 0, 0,
-10, 30, -20, 10, 0, 0, 0, 10, 10, 10, 10, -10, 0, 20, 10,
10, 10, 0, -10, -10, 0, 0, 10, 20, 0, -10, 10, 0, 10, 20,
10, 0, 0, 0, 0, 10, 10, 10, 30, 10, 0, 0, -10, 40, 0, 0,
10, 10, 40, 30, -10, 0, 0, 10, 20, 0, 0, 10, 40, 0, 0, -10,
-20)), row.names = c(NA, -236L), class = "data.frame")
Hope this helps,
Rui Barradas
Às 14:10 de 03/12/19, Francesca escreveu:
Hi
here it is;. THANKS!
dput(DATASET)
structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1,
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1,
1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1,
0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0,
1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1,
1, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1,
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1,
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0,
1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1,
2, 1, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, 2, 2, 2, 2, 2,
1, 2, 1, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2,
2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
1, 2, 1, 2, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 2, 2, 2, 2, 1, 2,
2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 1, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2, 2,
1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0,
-10, -10, 0, 0, 0, -30, 0, 10, 0, 20, 10, 0, 0, 20, 0, 0, -10,
30, 10, 0, 0, 0, 0, 10, 0, 0, 0, 0, 0, 0, 0, 0, -10, 0, 0, 0,
40, -10, 0, 10, 0, 10, 0, -20, 0, 0, 0, 10, -20, 10, -10, 40,
-10, -10, 10, 20, 10, 0, 0, 0, 0, 0, 0, -10, 0, 0, 20, 0, 0,
0, 0, 10, 0, 0, 0, 10, 0, -10, 10, 0, 0, 10, 10, 10, 0, 0, 0,
0, 0, -10, 0, 0, 0, 20, 0, 0, 20, 0, 0, 0, 0, 0, 0, 0, 10, 0,
10, 0, 0, 0, 20, -20, 0, 0, -10, 0, 0, 0, 0, -10, 10, 0, 20,
0, 0, 0, 0, 0, -10, 0, 0, 0, 0, 0, -10, 0, 0, -10, 0, -10, 30,
-10, 0, 0, 10, -10, 0, -10, -10, 0, 10, 0, 0, 0, 0, 0, 0, 0,
0, 10, 0, 0, 10, 10, 0, 0, -20, -10, 0, 0, 0, 0, 0, 0, 10, 30,
40, 30, 30, 30, 30, 20, 20, 40, 20, 20, 10, 20, 30, 20, 40, 20,
30, 20, 30, 20, 20, 30, 20, 40, 10, 20, 10, 30, 30, 30, 30, 10,
30, 30, 20, 10, 40, 30, 40, 40, 30, 20, 10, 10, 20, 20, 30, 40,
40, 40, 40, 0, 20, 20, 40, 10, 20, 20, 10, 0, -10, 0, 0, 0, 0,
30, 10, 40, 0, 0, 0, 0, 0, 10, 0, 0, 30, 10, 10, 0, 0, -10, -20,
-10, 0, 0, 0, -10, 10, 0, 40, 0, 30, 0, 10, 0, 40, 0, 0, -10,
0, 10, 40, -10, 0, 0, 0, 10, 0, 10, -10, 40, 10, 20, 10, 40,
0, 10, -10, 0, 40, 0, 0, -10, 0, 0, 20, -10, 0, 10, 0, 30, -10,
0, 0, 0, -10, 40, 10, 10, 0, 10, -10, 0, 10, 0, 10, 0, -20, 20,
0, 0, -20, 20, 0, -30, 20, 0, 0, 20, 10, 0, 20, 30, 0, 0, -10,
10, 10, 0, -10, 40, 10, 0, 10, 0, 0, 20, 10, 20, 30, 0, 40, 30,
0, 20, 40, -10, 0, 0, 0, -10, 0, 20, -10, 0, 0, 10, 0, 0, 20,
-20, -20, 0, 20, 0, 0, 10, 0, -10, -10, 20, -10, 0, 0, 0, 0,
0, 0, 0, -10, 30, 10, 0, 0, 10, 20, 10, -10, 10, 0, 0, -10, 30,
-20, 10, 0, 0, 0, 10, 10, 10, 10, -10, 0, 20, 10, 10, 10, 0,
-10, -10, 0, 0, 10, 20, 0, -10, 10, 0, 10, 20, 10, 0, 0, 0, 0,
10, 10, 10, 30, 10, 0, 0, -10, 40, 0, 0, 10, 10, 40, 30, -10,
0, 0, 10, 20, 0, 0, 10, 40, 0, 0, -10, -20), .Dim = c(236L, 6L
), .Dimnames = list(NULL, c("participation1", "participation2",
"ParticipantsNOPUN", "ParticipantsPUN", "delta11_L", "delta2_L"
)))
Francesca Pancotto
----------------------------------
Francesca Pancotto, PhD
Associate Professor of Political Economy
Università di Modena e Reggio Emilia
Viale A. Allegri, 9
40121 Reggio Emilia
Office: +39 0522 523264
Web:
https://sites.google.com/view/francescapancotto/home
----------------------------------
Il giorno 3 dic 2019, alle ore 15:03, Rui Barradas
<ruipbarra...@sapo.pt <mailto:ruipbarra...@sapo.pt>> ha scritto:
Hello,
Please post the output of
dput(DB)
in a next e-mail to R-Help, like this it's difficult for us to use the
data you posted.
And yes, I bet you will need the data in long format. It is a frequent
first step to the problem of plotting two or more columns in the same
graph. To say more only with data.
Hope this helps,
Rui Barradas
Às 09:18 de 03/12/19, Francesca escreveu:
Dear Contributors,
I would like to ask help on how to create a plot that is the overlapping
of two other plots.
It is a geom_bar structure, where I want to count the occurrences of two
variables, participation1 and participation2 that I recoded as factors as
ParticipationNOPUN and ParticipationPUN to have nice names in the legend.
The variables to "count" in the two plots are delta11_L and delta2_L
These are my data and code to create the two plots. I would like to put
them in the same plot as superimposed areas so that I see the change
in the
distribution of counts in the two cases.
This is DB:
participation1 participation2 ParticipantsNOPUN ParticipantsPUN delta11_L
delta2_L
[1,] 1 1 2 2
0 0
[2,] 1 1 2 2
-10 -10
[3,] 1 1 2 2
-10 0
[4,] 1 1 2 2
0 0
[5,] 1 1 2 2
0 0
[6,] 1 1 2 2
0 0
[7,] 1 0 2 1
-30 30
[8,] 1 1 2 2
0 10
[9,] 1 0 2 1
10 40
[10,] 1 1 2 2
0 0
[11,] 0 0 1 1
20 0
[12,] 1 1 2 2
10 0
[13,] 1 1 2 2
0 0
[14,] 1 1 2 2
0 0
[15,] 1 1 2 2
20 10
[16,] 1 1 2 2
0 0
[17,] 1 1 2 2
0 0
[18,] 1 1 2 2
-10 30
[19,] 0 0 1 1
30 10
[20,] 1 1 2 2
10 10
[21,] 1 1 2 2
0 0
[22,] 1 1 2 2
0 0
[23,] 1 1 2 2
0 -10
[24,] 1 1 2 2
0 -20
[25,] 1 1 2 2
10 -10
[26,] 1 1 2 2
0 0
[27,] 1 1 2 2
0 0
First PLOT(I need to subset the data to eliminate some NA. NB: the two
dataframes end up not having the same number of rows for this reason):
ggplot(data=subset(DB, !is.na(participation1)), aes(x = delta11_L, fill
=ParticipantsNOPUN))+
geom_bar(position = "dodge")+ theme_bw(base_size = 12) +
labs(x="Delta Contributions (PGG w/out punishment)")+
theme(legend.position = "top",legend.title = element_blank())
+scale_fill_brewer(palette="Set1")
Second PLOT:
ggplot(DB, aes(x = delta2_L, fill =ParticipantsPUN) , aes(x = delta2_L,
fill =ParticipantsPUN))+
geom_bar(position = "dodge")+ theme_bw(base_size = 12) + labs(x="Delta
Contributions (PGG w/punishment)")+
theme(legend.position = "top",legend.title = element_blank())
+scale_fill_brewer(palette="Set1")
is it possible to create a density plot of the two counts data on the
same
plot?
Do I need to create a variable count or long data format?
Thanks
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http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
