substitute value in dataframe based on conditional - r

Question

I have the following data set
library(dplyr)
df<- data.frame(c("a", "a", "a", "a", "a", "a", "b", "b", "b", "b", "b", "b"),
c(1, 1, 2, 2, 2, 3, 1, 2, 2, 2, 3, 3),
c(25, 75, 20, 40, 60, 50, 20, 10, 20, 30, 40, 60))
colnames(df)<-c("name", "year", "val")
This we summarize by grouping df by name and year and then find the average and number of these entries
asd <- (df %>%
group_by(name,year) %>%
summarize(average = mean(val), `ave_number` = n()))
This gives the following desired output
name year average ave_number
<fctr> <dbl> <dbl> <int>
1 a 1 50 2
2 a 2 40 3
3 a 3 50 1
4 b 1 20 1
5 b 2 20 3
6 b 3 50 2
Now, all entries of asd$average where asd$ave_number<2 I would like to substitute according to the following array based on year
replacer<- data.frame(c(1,2,3),
c(100,200,300))
colnames(replacer)<-c("year", "average")
In other words, I would like to end up with
name year average ave_number
<fctr> <dbl> <dbl> <int>
1 a 1 50 2
2 a 2 40 3
3 a 3 300 1 #substituted
4 b 1 100 1 #substituted
5 b 2 20 3
6 b 3 50 2
Is there a way to achieve this with dplyr? I guess I have to use the %>%-operator, something like this (not working code)
asd %>%
group_by(name, year) %>%
summarize(average = ifelse(n() < 2, #SOMETHING#, mean(val)))

Answer 1

Here's what I would do:
colnames(replacer) <- c("year", "average_replacer") #To avoid duplicate of variable name
asd <- left_join(asd, replacer, by = "year") %>%
mutate(average = ifelse(ave_number < 2, average_replacer, average)) %>%
select(-average_replacer)
name year average ave_number
<fctr> <dbl> <dbl> <int>
1 a 1 50 2
2 a 2 40 3
3 a 3 300 1
4 b 1 100 1
5 b 2 20 3
6 b 3 50 2
Regarding the following:
I guess I have to use the %>%-operator
You don't ever have to use the pipe operator. It is there for convenience because you can string (or "pipe") functions one after another, as you would with a train of thought. It's kind of like having a flow in your code.

Answer 2

You can do this easily by using a named vector of replacement values by year instead of a data frame. If you're set on a data frame, you'd be using joins.
replacer <- setNames(c(100,200,300),c(1,2,3))
asd <- df %>%
group_by(name,year) %>%
summarize(average = mean(val),
ave_number = n()) %>%
mutate(average = if_else(ave_number < 2, replacer[year], average))
Source: local data frame [6 x 4]
Groups: name [2]
name year average ave_number
<fctr> <dbl> <dbl> <int>
1 a 1 50 2
2 a 2 40 3
3 a 3 300 1
4 b 1 100 1
5 b 2 20 3
6 b 3 50 2