Generate new variable based on table of conditions - r

Question

I am trying to write a loop in R that creates a new variable based on a table of conditional outcomes.
I have four treatment groups (A, B, C, D). Each treatment group pays a different price at three different time periods (day, dinner, night).
Treatment Group Day Price Dinnertime Price Night Price
A 10 20 7
B 11 25 8
C 12 30 9
D 13 35 10
The time period is recorded as a given "hour" (day is hours 8-17, dinner is from 17-19 and night is from 19-0 and 0-8).
Hour Usage
Person 1 1 0
Person 1 2 0
Person 2 20 5
Person 3 17 6
Based on both treatment group (A, B, C and D) and time of day (night, day, dinnertime), I would like to create a new vector of prices.
Ideally, I would create dummy variables for each of the time periods (day, night and dinner) based on these hourly conditions. However, my data set is pretty large (24 observations per person per day) so I'm looking for a more elegant solution.
In plain language, I want this:
if group==A & time==night, then price=7 --> and this information saved in a new variable "price"
Any advice?
Edit: Question is about the loop with two conditions. Is there a way to refer this directly to the data-frame with the treatment groups and tariffs or do I just need to write it manually?

Answer 1

Assuming that you have some way of including a column for the group each person belongs to in the dataframe with the transactions on it. Then something like this may work for you.
df.pricing <- structure(list(Treatment.Group = c("A", "B", "C", "D"), Day.Price = 10:13,
Dinnertime.Price = c(20L, 25L, 30L, 35L), Night.Price = 7:10),
.Names = c("Treatment.Group", "Day.Price", "Dinnertime.Price", "Night.Price"),
class = "data.frame",
row.names = c(NA, -4L))
df.transactions <- structure(list(Person = c("Person1", "Person1", "Person2", "Person3", "Person4"),
Hour = c(1L, 2L, 20L, 17L, 9L),
Usage = c(0L, 0L, 5L, 6L, 2L)),
.Names = c("Person", "Hour", "Usage"),
class = "data.frame", row.names = c(NA, -5L))
# Add the group that each person belongs to
df.transactions$group <- c("A","A","B","C","D")
# Get the transaction price
df.transactions$price <- apply(df.transactions, 1, function(x){
hour <- as.numeric(x[["Hour"]])
price <- ifelse(hour >= 8 & hour <= 16, df.pricing[df.pricing$Treatment.Group == x[["group"]], "Day.Price"],
ifelse((hour > 16 & hour <= 18), df.pricing[df.pricing$Treatment.Group == x[["group"]], "Dinnertime.Price"],
df.pricing[df.pricing$Treatment.Group == x[["group"]], "Night.Price"]))})