Ifelse with different lengths of data frame - r

Question

I have dataset which is panel data that contains the following variables:
1. Country
2. Company
3. Monthly date
4. Revenue
`A <- data.frame(Country=as.factor(rep('A', 138)),
Company = as.factor(c(rep('AAA', 12), rep('BBB', 8), rep('CCC', 72), rep('DDD', 46))),
Date = c(seq(as.Date('2010-01-01'), as.Date('2011-01-01'), by = 'month'),
seq(as.Date('2010-01-01'), as.Date('2010-07-01'), by = 'month'),
seq(as.Date('2010-01-01'), as.Date('2015-12-01'), by = 'month'),
seq(as.Date('2012-03-01'), as.Date('2015-12-01'), by = 'month')),
Revenue= sample(10000:25000, 138)
)
B<- data.frame(Country=as.factor(rep('B', 108)),
Company = as.factor(c(rep('EEE', 36), rep('FFF', 36), rep('GGG', 36))),
Date = c(seq(as.Date('2013-01-01'), as.Date('2015-12-01'), by = 'month'),
seq(as.Date('2013-01-01'), as.Date('2015-12-01'), by = 'month'),
seq(as.Date('2013-01-01'), as.Date('2015-12-01'), by = 'month')),
Revenue = sample(10000:25000, 108)
)`
I want to add other variable to the dataset - Competitor's revenue, which is the total sum of the revenues of all other companies in the own country for the corresponding month.
I wrote the following code:
new_B<-data.frame()
for(i in 1:nlevels(B$Company)){
temp_i<-B[which(B$Company==levels(B$Company)[i]),]
temp_j<-B[which(B$Company!=levels(B$Company)[i]),]
agg_temp<-aggregate(temp_j$Revenue, by = list(temp_j$Date), sum)
temp_i$competitor_value<-ifelse(agg_temp$Group.1 %in% temp_i$Date, agg_temp$x, 0)
new_B<-rbind(new_B, temp_i)
}
I created two temporary data set inside for loop one containing company i only and the other - all other companies. I summed all revenues of other companies by month. Then using ifelse for the same dates I add new variable to temp_i. It works nice for the companies that operated during the same period, but in country A there are companies that operated for different periods and when I try to use my code, I have error that they are not of the same length
new_A<-data.frame()
for(i in 1:nlevels(A$Company)){
temp_i<-A[which(A$Company==levels(A$Company)[i]),]
temp_j<-A[which(A$Company!=levels(A$Company)[i]),]
agg_temp<-aggregate(temp_j$Revenue, by = list(temp_j$Date), sum)
temp_i$competitor_value<-ifelse(agg_temp$Group.1 %in% temp_i$Date, agg_temp$x, 0)
new_A<-rbind(new_A, temp_i)
}
I found similar answer ifelse statements with dataframes of different lengths, but still do not know how to solve my problem.
I would really appreciate help

Answer 1

I suggest a different approach using the dplyr package:
library(dplyr)
A %>%
bind_rows(B) %>%
group_by(month=format(Date, "%Y-%m")) %>%
mutate(revComp = sum(Revenue)) %>%
group_by(Company, add = T) %>%
mutate(revComp = revComp-Revenue)
# Source: local data frame [246 x 6]
# Groups: month, Company [246]
#
# Country Company Date Revenue month revComp
# (chr) (chr) (date) (int) (chr) (int)
# 1 A AAA 2010-01-01 10657 2010-01 30356
# 2 A AAA 2010-02-01 11620 2010-02 22765
# 3 A AAA 2010-03-01 17285 2010-03 33329
# 4 A AAA 2010-04-01 22886 2010-04 33469
# 5 A AAA 2010-05-01 20129 2010-05 39974
# 6 A AAA 2010-06-01 22865 2010-06 26896
# 7 A AAA 2010-07-01 13087 2010-07 29542
# 8 A AAA 2010-08-01 19451 2010-08 14842
# 9 A AAA 2010-09-01 12364 2010-09 15309
# 10 A AAA 2010-10-01 19375 2010-10 14090