Make all values of a column equal to a row that has a condition, and multiply by rate in r-CodePudding

I have a dataset like this

Company Year Value
A        22    15
A        23    17
A        24    13
A        25    20
B        22    187
B        23    153
B        24    135
C...ect

I need to make all values, for each company, equal to the value of 2022. Like this:

Company Year Value
A        22    15
A        23    15
A        24    15
A        25    15
B        22    187
B        23    187
B        24    187
C...ect

And then multiply each value by a given rate (eg. 2% for each value) that coumpounds. Like this:

Company Year Value
A        22    15
A        23    15x1,02
A        24    15x1,02^2
A        25    15x1,02^3
B        22    187
B        23    187x1,02
B        24    187x1,02^2
C...ect

Can someone help me please?

CodePudding user response：

df <- data.frame(
  stringsAsFactors = FALSE,
  Company = c("A", "A", "A", "A", "B", "B", "B"),
  Year = c(22L, 23L, 24L, 25L, 22L, 23L, 24L),
  Value = c(15L, 17L, 13L, 20L, 187L, 153L, 135L)
)

library(tidyverse)
df %>% 
  group_by(Company) %>% 
  mutate(Value = first(Value) * 1.02 ^ (row_number() - 1)) %>% 
  ungroup()
#> # A tibble: 7 x 3
#>   Company  Year Value
#>   <chr>   <int> <dbl>
#> 1 A          22  15  
#> 2 A          23  15.3
#> 3 A          24  15.6
#> 4 A          25  15.9
#> 5 B          22 187  
#> 6 B          23 191. 
#> 7 B          24 195.

^{Created on 2022-03-18 by the reprex package (v2.0.1)}

CodePudding user response：

You can do:

library(tidyverse)

df %>% 
  group_by(Company) %>% 
  mutate(Value = Value[Year == "22"]*(1.02^(0:(n()-1))))

  Company Year     Value
1       A   22  15.00000
2       A   23  15.30000
3       A   24  15.60600
4       A   25  15.91812
5       B   22 187.00000
6       B   23 190.74000
7       B   24 194.55480