q1_dat<- import(here::here(“D:/Dashboard for Bulletin Webpage/PHEM Weekly Surveillance Data.csv”))

clean_dat<- q1_dat%>% clean_names()

quarter1_dat <- clean_dat[,-4]

quarter1_data <- quarter1_dat %>% filter(year == 2025)

oromia_reg_data <- quarter1_data %>% filter( region ==“Oromia” & epi_week %in% c(28:41))

glimpse(oromia_reg_data)

summary(oromia_reg_data)

skimr::skim(oromia_reg_data)

vis_miss(oromia_reg_data)

vis_dat(oromia_reg_data)

gg_miss_var(oromia_reg_data)+theme()

as_shadow(oromia_reg_data)

miss_var_summary(oromia_reg_data)

n_miss(oromia_reg_data)

n_distinct(oromia_reg_data$total_malaria_confirmed_and_clinical)

n_complete(oromia_reg_data$t_malaria_out_p_cases)

n_complete_row(oromia_reg_data)

prop_miss(oromia_reg_data)

prop_miss_case(oromia_reg_data)

prop_complete_var(oromia_reg_data)

prop_miss_var(oromia_reg_data)

miss_case_summary(oromia_reg_data)

oromia_reg_data %>% group_by(woreda) %>% miss_var_summary()

miss_case_table(oromia_reg_data)

miss_var_table(oromia_reg_data)

miss_var_which(oromia_reg_data)

miss_var_summary(oromia_reg_data,add_cumsum = TRUE)