Adjust line in graph in R - r

Question

The graph below generates a scatter plot based on date2. In addition, a horizontal line that refers to the mean is generated. Each day of the week has a different mean as you can see.
Note that in abline I specified h=mean_saturday, as 10/4 is a Saturday. But I didn't want to always have to change this part of the abline to show the right mean line, but my idea is to leave it automatically, that is, when I enter the date 10/4/2021 in the code, the code already recognize that the 10th it's Saturday and inserts the appropriate mean line. Any idea how to do this?
library(dplyr)
library(ggplot2)
library(tidyr)
library(lubridate)
library(tibble)
df <- structure(
list(Id=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),
date1 = c("2021-07-20","2021-07-20","2021-07-20","2021-07-20","2021-07-20",
"2021-07-20","2021-07-20","2021-07-20","2021-07-20","2021-07-20","2021-07-20",
"2021-07-20","2021-07-20","2021-07-20","2021-07-20","2021-07-20","2021-07-20",
"2021-07-20","2021-07-20","2021-07-20","2021-07-20"),
date2 = c("2021-07-01","2021-07-01","2021-07-01","2021-07-01","2021-04-02",
"2021-04-02","2021-04-02","2021-04-02","2021-04-02","2021-04-02","2021-04-03",
"2021-04-03","2021-04-03","2021-04-03","2021-04-03","2021-04-08","2021-04-08",
"2021-04-09","2021-04-09","2021-04-10","2021-04-10"),
Week= c("Thursday","Thursday","Thursday","Thursday","Friday","Friday","Friday","Friday",
"Friday","Friday","Saturday","Saturday","Saturday","Saturday","Saturday","Thursday",
"Thursday","Friday","Friday","Saturday","Saturday"),
D = c("","","Ho","","","","","","Ho","","","","","","","","","","","",""),
DR01 = c(2,1,4,3,3,4,1,6,3,7,2,3,4,6,7,8,4,2,6,2,3)),
class = "data.frame", row.names = c(NA, -21L))
mean_thursday=4
mean_friday=5
mean_saturday=6
scatter_date <- function(dt, dta = df) {
dta %>%
filter(date2 == ymd(dt)) %>%
summarize(across(starts_with("DR"), sum)) %>%
pivot_longer(everything(), names_pattern = "DR(.+)", values_to = "val") %>%
mutate(name = as.numeric(name)) %>%
plot(xlab = "Days", ylab = "Types", xlim = c(0, 7),
ylim = c((min(.$val) %/% 10) * 10, (max(.$val) %/% 10 + 1) * 15))
abline(h=mean_saturday, col='blue')
}
scatter_date("2021-04-10",df)

Answer 1

You could try to convert the input date in your scatter_date function to a date and get the weekday: my_day <- weekdays(as.Date(dt)) add that to a switch statment for your means:
my_mean <- switch(
my_day,
"Saturday" = mean_saturday,
"Friday" = mean_friday,
"Thursday" = mean_thursday,
0) # add here your other days
and replace mean_saturday in abline(h=mean_saturday, col='blue') with my_mean
here the full code:
library(dplyr)
library(ggplot2)
library(tidyr)
library(lubridate)
library(tibble)
df <- structure(
list(Id=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1),
date1 = c("2021-07-20","2021-07-20","2021-07-20","2021-07-20","2021-07-20",
"2021-07-20","2021-07-20","2021-07-20","2021-07-20","2021-07-20","2021-07-20",
"2021-07-20","2021-07-20","2021-07-20","2021-07-20","2021-07-20","2021-07-20",
"2021-07-20","2021-07-20","2021-07-20","2021-07-20"),
date2 = c("2021-07-01","2021-07-01","2021-07-01","2021-07-01","2021-04-02",
"2021-04-02","2021-04-02","2021-04-02","2021-04-02","2021-04-02","2021-04-03",
"2021-04-03","2021-04-03","2021-04-03","2021-04-03","2021-04-08","2021-04-08",
"2021-04-09","2021-04-09","2021-04-10","2021-04-10"),
Week= c("Thursday","Thursday","Thursday","Thursday","Friday","Friday","Friday","Friday",
"Friday","Friday","Saturday","Saturday","Saturday","Saturday","Saturday","Thursday",
"Thursday","Friday","Friday","Saturday","Saturday"),
D = c("","","Ho","","","","","","Ho","","","","","","","","","","","",""),
DR01 = c(2,1,4,3,3,4,1,6,3,7,2,3,4,6,7,8,4,2,6,2,3)),
class = "data.frame", row.names = c(NA, -21L))
mean_thursday=4
mean_friday=5
mean_saturday=6
scatter_date <- function(dt, dta = df) {
my_day <- weekdays(as.Date(dt))
my_mean <- switch(
my_day,
"Saturday" = mean_saturday,
"Friday" = mean_friday,
"Thursday" = mean_thursday,
0) # add here your other days
dta %>%
filter(date2 == ymd(dt)) %>%
summarize(across(starts_with("DR"), sum)) %>%
pivot_longer(everything(), names_pattern = "DR(.+)", values_to = "val") %>%
mutate(name = as.numeric(name)) %>%
plot(xlab = "Days", ylab = "Types", xlim = c(0, 7), main = paste0(my_day, ":", my_mean),
ylim = c((min(.$val) %/% 10) * 10, (max(.$val) %/% 10 + 1) * 15))
abline(h=my_mean, col='blue')
}
# testing the different means
scatter_date("2021-04-10",df)
scatter_date("2021-04-9",df)
scatter_date("2021-04-8",df)

Answer 2

One way would be to define a data.frame containing the mean for the days of interest and then use weekdays to extract the corresponding mean from that table.
Instead of
mean_thursday=4
mean_friday=5
mean_saturday=6
I would go for something like:
mean_df <- data.frame(mean = c(4:6),
day = c('Thursday', 'Friday', 'Saturday'))
and then
abline(h=subset(mean_df, day == weekdays(as.Date(dt)))$mean, col='blue')
which will be the only change in your function.