Calculating the sum of rows in each column group

gistfile1.txt

## LOAD PACKAGE
library(dplyr)

## INPUT

input <- data.frame(president = c("A1", "A1", "A1", "A1", "A1", "A1", "A1"),
                   vice_president = c("B", "B", "B", "B", "C", "C", "C"),
                   manager = c("D", "D", "E", "E", "F", "G", "H"),
                   staff = c("I", "J", "K", "L", "M", "N", "O"),
                   qty_1 = c(1:7),
                   qty_2 = c(2:8),
                   qty_3 = c(1:7),
                   stringsAsFactors = FALSE)
                   
## PROCESSING
### Group manager

    out_manager <- input %>%
        group_by(president, vice_president, manager) %>%
        summarise_at(vars(qty_1, qty_2, qty_3), funs(sum(., na.rm = TRUE))) %>%
        mutate(manager = paste(manager, "Total", sep = " ")) %>%
        bind_rows(input) %>%
        arrange(president, vice_president, manager)
        
### Group vice-president
    
    out_vice_president <- input %>%
        group_by(president, vice_president) %>%
        summarise_at(vars(qty_1, qty_2, qty_3), funs(sum(., na.rm = TRUE))) %>%
        mutate(vice_president = paste(vice_president, "Total")) %>%
        bind_rows(out_manager) %>%
        arrange(president, vice_president) 

### Group president

    out_president <- input %>%
        group_by(president) %>%
        summarise_at(vars(qty_1, qty_2, qty_3), funs(sum(., na.rm = TRUE))) %>%
        mutate(president = paste(president, "Total")) %>%
        bind_rows(out_vice_president) %>%
        arrange(president) %>%
        mutate_all(funs(replace(., is.na(.), ""))) %>%
        mutate_at(vars(president, vice_president), funs(ifelse(grepl("Total", manager), "", .))) %>%
        mutate(president = ifelse(grepl("Total", vice_president), "", president)) 
        
        
## OUTPUT

    output <- out_president %>%
        select(president, vice_president, manager, 
               staff, qty_1, qty_2, qty_3)

write.csv(output, "output.csv")
        
   

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