The plot below shows the highest and lowest selling products.
Product_Quantity_in_Portugal %>%
select(Quantity, Total_Sales)
group column by
select(Quantity, Total_Sales)
group_by(Total_sales)
Sum the total no of sales using (Sum, average etc)
sunnarise (total=n ()) %>%
####creating a new variable in a new column using mutate
mutate(percent=total/sum(total)) %>%
arrange(desc(total)) %>%
ggplot(aes(x=Quantity, y=total)) +
geom_col()