Hello, I tried to solve this. Below is a reprex of my issue.
reprex1 script
install and load packages
pacman::p_load(rio, here, janitor, tidyverse, reprex, datapasta)
import data
surv_raw ← data.frame(
stringsAsFactors = FALSE,
adm3_name_res = c(NA,“Mountain Rural”,
“Mountain Rural”,“East II”,“West III”),
sex = c(“m”, “f”, “f”, “f”, “f”)
)
clean the surveillance data
surv_clean ← surv_raw %>%
clean_names()
make a horizontal bar plot of cases per district, filled by sex
ggplot(
data = Surv_clean,
mapping = aes(y = adm3_name_res, fill = sex))+
geom_bar()
create a minimal dataset, by reducing surv_raw to 5 rows and 3 columns
#surv_raw %>%
#head(5) %>% # take the top 5 rows only
#select(adm3_name_res, sex) %>% # keep only the relevant columns
#dpasta() # convert to stand-alone R code
reprex_addin()