CODEWITHSUNDEEP
r
Glovemiester
Glovemiester

Reputation: 45

Multiply values by a percentage based on a category

I would like to inflate data for 2020 by a certain percentage based on what category it is. The data goes from 2017-2021 (52 weeks in each) and I have 4 different categories I need to filter by. I have attached a sample of the data

Week Category Qty
202001 Category1 100
202001 Category2 115
202002 Category1 95
202002 Category2 105

Upvotes: 1

Views: 59

Answers (1)

AndrewGB
AndrewGB

Reputation: 16836

If you only have 4 categories, then you can make a series of ifelse statements using case_when.

library(tidyverse)

df %>%
  mutate(inflate = case_when(Category == "Category1" ~ (Qty*0.05)+Qty,
                             Category == "Category2" ~ (Qty*0.25)+Qty,
                             Category == "Category3" ~ (Qty*0.30)+Qty,
                             Category == "Category4" ~ (Qty*0.45)+Qty,
                             TRUE ~ NA_real_))

Output

    Week  Category Qty inflate
1 202001 Category1 100  105.00
2 202001 Category2 115  143.75
3 202002 Category1  95   99.75
4 202002 Category2 105  131.25
5 202002 Category3 105  136.50
6 202002 Category4 105  152.25

Or if you did have a lot of categories, then you could create a dataframe key for the percentages for each category. Then, you could join them together and make the calculation for each row.

df_perc <- data.frame(Category = c("Category1", "Category2", "Category3", "Category4"),
                      Percent = c(0.05, 0.25, 0.30, 0.45))

df %>% 
  left_join(., df_perc, by = "Category") %>% 
  mutate(inflate = (Qty*Percent)+Qty)

Data

df <,- structure(list(Week = c(202001L, 202001L, 202002L, 202002L, 202002L, 
202002L), Category = c("Category1", "Category2", "Category1", 
"Category2", "Category3", "Category4"), Qty = c(100L, 115L, 95L, 
105L, 105L, 105L)), class = "data.frame", row.names = c(NA, -6L
))

Upvotes: 1

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