You can use secondary axis via scale_y_continious(sec.axis = dup_axis()). This takes a transformation as an argument. So this is something I would do:
library(tidyverse)
df <- data.frame(
date = Sys.Date() - 0:9,
n = rnorm(10, 200, 10),
p = 210
) %>%
mutate_if(is.numeric,round,0) %>%
mutate(perc = n/p)
df
#> date n p perc
#> 1 2020-06-29 190 210 0.9047619
#> 2 2020-06-28 211 210 1.0047619
#> 3 2020-06-27 182 210 0.8666667
#> 4 2020-06-26 209 210 0.9952381
#> 5 2020-06-25 183 210 0.8714286
#> 6 2020-06-24 218 210 1.0380952
#> 7 2020-06-23 186 210 0.8857143
#> 8 2020-06-22 185 210 0.8809524
#> 9 2020-06-21 200 210 0.9523810
#> 10 2020-06-20 209 210 0.9952381
df %>%
mutate(perc = perc * 200) %>%
ggplot(aes(x = date, y = n)) +
geom_line(aes(y = perc), color = "dodgerblue") +
geom_line() +
scale_y_continuous(
#limits = c(0, 1),
sec.axis = dup_axis(~ . / 2, name = "perc")
) +
theme(
axis.text.y.right = element_text(color = "dodgerblue"),
axis.title.y.right = element_text(color = "dodgerblue")
)

Created on 2020-06-29 by the reprex package (v0.3.0)
EDIT: Maybe some words on the chart itself. There is a reason why Hadley Wickham did not want to have secondary axes in ggplot2 and it is also not very appreciated in the dataviz community in general. As one can see here it can be very hard to interpret. You may want to switch to a 2-plot-solution anyway.