Having a dataframe like this:
structure(list(google_before = c(0.26981640312419, 0.302252978236613,
0.27519244423907, 0.278573602172958), amazon_before = c(0.165541492443112,
0.162543532408399, 0.150484069110868, 0.212810080358854), ebay_before = c(0.698096408083222,
0.625412783031095, 0.699099484936941, 0.610794910230257), yahoo_before = c(0.156164414439798,
0.189265950612553, 0.151656203861282, 0.211930979296043), so_before = c(0.384820854982136,
0.364443743167243, 0.352744936715994, 0.397252245652394), google_after = c(0.290892287578753,
0.279948606399405, 0.262591995672118, 0.327138300630022), amazon_after = c(0.170072244074521,
0.190821283262141, 0.136632592108377, 0.185400160041476), ebay_after = c(0.637122860008791,
0.595805110056691, 0.713976579846045, 0.594306130039334), yahoo_after = c(0.154789410213351,
0.185512865305938, 0.136271935262096, 0.18347290001916), so_after = c(0.359935532588727,
0.391256325582968, 0.352913994612688, 0.312475345723399)), row.names = c(NA,
-4L), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x00000000003d1ef0>)
How is it possible to create into one plot the distributions of the ten variables but without filling inside the distribution but only have different color in the line like this:
library(tidyverse)
# Build Poisson distributions
p_dat <- map_df(1:10, ~ tibble(
l = paste(.),
x = 0:20,
y = dpois(0:20, .)
))
# Build Normal distributions
n_dat <- map_df(1:10, ~ tibble(
l = paste(.),
x = seq(0, 20, by = 0.001),
y = dnorm(seq(0, 20, by = 0.001), ., sqrt(.))
))
# Use ggplot2 to plot
ggplot(n_dat, aes(x, y, color = factor(l, levels = 1:10))) +
geom_line() +
geom_point(data = p_dat, aes(x, y, color = factor(l, levels = 1:10))) +
labs(color = "Lambda:") +
theme_minimal()

