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library(tidyverse) | |
set.seed(1000) | |
asdpop_base <- tibble::tibble( | |
time1 = sample(1:100, 100, replace = F), | |
time2 = time1) %>% | |
tidyr::gather(x, y, time1:time2, factor_key = TRUE) | |
asdpop <- asdpop_base %>% | |
mutate(services = as.factor(case_when( | |
x == "time1" & y <= 30 ~ 1, | |
x == "time1" & y > 30 ~ 0, | |
x == "time2" & y <= 60 ~ 1, | |
TRUE ~ 0 | |
))) | |
asdpop | |
library(ggrepel) | |
pos <- position_jitter(width = .25, | |
height = 0, | |
seed = 2018) | |
# trying out direct labels | |
# need to use full dataset (not filtered) b/c of matching up with jittered points | |
labels <- asdpop %>% | |
mutate(callout = as.factor(if_else(y %in% c(20, 77), 1, 0))) | |
dotleg <- ggplot(labels, aes(x, y)) | |
dotleg <- dotleg + geom_jitter(aes(colour = services), | |
position = pos, | |
alpha = .75, size = 2) | |
dotdirect <- dotleg + | |
guides(colour = FALSE) + | |
# add the black outlines- transparent for callout = 0 | |
geom_jitter(aes(alpha = callout), | |
colour = "black", | |
size = 3, shape = 1, | |
position = pos) + | |
scale_alpha_manual(values = c(0, 1), guide = 'none') + | |
# add the labels- transparent for callout = 0 | |
geom_label_repel(aes(alpha = callout, label = services), | |
position = pos) | |
dotdirect |
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