How to get all values of a specific column based on a specific value in another column in R?

Question

My format for CSV files are

Camp.CSV

Campaign,AdGroup,Keyword,Status
florida,orlando,floridaorlando,Paused
new york,albany,new yorkalbany,Active

geo_fl.csv

Campaign,Adgroup
florida,orlando
florida,miami
new york,new york
california,san francisco,
california,los angeles

I want to list all the Adgroup in 'geo_fl.csv' based on 'Campaign' in 'Camp.csv' like for florida in 'Camp.csv' it should return the values (orlando,miami) in 'geo_fl.csv'

So far code is as follows -

 # Declare function to check with the presence of the 'campaignname' or not
 campaignname <- function(point1, point2) {
 conditioncheck <- any(point2==point1)
 }
# Declare a function to check the presence of the 'adgroupname' or not

# Read the CSV files for reference
newlistings <- read.csv("/home/chi/Downloads/Camp.csv",header=TRUE)
georeportrecord <- read.csv("/home/chi/Downloads/geo_fl.csv",header=TRUE)
# Store the data of each column in a variable for 'Camp.csv'
Keyword <- newlistings$keyword
campaign <- newlistings$Campaign
adgroup <- newlistings$AdGroup
status <- newlistings$Status
# Store the data of each column in a variable for 'geo_fl.csv'
geoCampaign <- georeportrecord$Campaign
geoAdGroup <- georeportrecord$Adgroup

# getting the values for 'number of rows' in each CSV list
nCGM <- nrow(newlistings)
nAdwords <- nrow(georeportrecord)

Pts2 <- georeportrecord[,c("Campaign")]
CGMGeoList <- NULL
# checking for the presence of the element in the vector
#for(i in campaign){
for(i in 1:nCGM){
Pts1 <- NULL
Pts1$Campaign <- (newlistings$Campaign[i])
# passing the value to the function for 'campaign' presence check
checkcondition <- campaignname(Pts1,Pts2)
if(checkcondition == TRUE){
   ad <- geoAdgroup[which(geoCampaign==i)# Stuck here(returning no result)
 }
 }

Also I have tried

for(i in campaign)
 { if (any(geoCampaign==i) == TRUE){
print(i)
# But also I want to list all adgroup for 'geo_fl.csv' together.

} }

My desired output

 Campaign,AdGroup,Keyword,Status,Campaignpresentingeo_fl,Adgrouppresentingeo_fl
 florida,orlando,floridaorlando,Paused,YES,YES
 new york,albany,new yorkalbany,Active,YES,NO

Condition for the above desired result

 for(i in campaign){
 If(( i present in georeportrecord)==TRUE))#for that particular 'campaign' in 'Camp.csv' check the condition for 'Adgroup' in 'geo_fl.csv'
{ If ((AdGroup[i] present in georeportrecord$Adgroup)==TRUE))#AdGroup for that particular 'campaign' 'i' in 'Camp.csv' is also present as an adgroup in 'geo_fl.csv'
{
output write.csv(florida,orlando,floridaorlando,Paused,YES,YES)
}else{
write.csv(florida,orlando,floridaorlando,Paused,YES,NO)
}
}else{write.csv(florida,orlando,floridaorlando,Paused,NO,NO)
}

Output the data onto a CSV file , just 2 additional columns in Camp.csv which indicates YES and NO How to list the values as specified above so that I can write to another CSV file, Please help me with the following, new to R, Any help is appreciated.

Answer 1

It's unclear what you want your output to look like, but here's a simple way to concatenate all levels of one factor that belonging to each of the levels of another factor:

georeportrecord <- read.csv(text='Campaign,Adgroup
florida,orlando
florida,miami
new york,new york
california,san francisco
california,los angeles', header=TRUE)

newlistings <- read.csv(text='Campaign,AdGroup,Keyword,Status
florida,orlando,floridaorlando,Paused
new york,albany,new yorkalbany,Active', header=TRUE)

out <- aggregate(subset(georeportrecord, 
                        Campaign %in% newlistings$Campaign)$Adgroup, 
                 list(Campaign=subset(georeportrecord, 
                      Campaign %in% newlistings$Campaign)$Campaign), 
                 paste0)

out

  Campaign              x
1  florida orlando, miami
2 new york       new york

Use write.csv to write the data out to a csv (see ?write.csv ).

EDIT: (After clarification of desired output)

The above code returns a concatenated string containing the Adgroups present in each Campaign that exists in newlistings . To present as requested by the OP:

newlistings$Campaignpresentingeo_fl <- 
  newlistings$Campaign %in% georeportrecord$Campaign

newlistings$Adgrouppresentingeo_fl <- 
  apply(newlistings, 1, function(x) x[2] %in% 
          subset(georeportrecord, Campaign==x[1])[, 'Adgroup'])

Answer 2

After required output,

x<-read.csv(text='Campaign,Adgroup
florida,orlando
florida,miami
new york,new york
california,san francisco
california,los angeles', header=T, stringsAsFactors=F)


y=read.csv(text="Campaign,AdGroup,Keyword,Status
florida,orlando,floridaorlando,Paused
new york,albany,new yorkalbany,Active", header=T, stringsAsFactors=F)

Campaigns<-x$Campaign
AdGroups<-interaction(x$Campaign, x$Adgroup)

y$campaignpresence<-ifelse(y$Campaign %in% Campaigns,"YES", "NO")
y$geopresence<-ifelse(interaction(y$Campaign, y$AdGroup) %in% AdGroups,"YES", "NO")

output

 y
  Campaign AdGroup        Keyword Status campaignpresence geopresence
1  florida orlando floridaorlando Paused              YES         YES
2 new york  albany new yorkalbany Active              YES          NO

ignore below, as it answered separate thing

another approach with data.table. I even don't see the need of first table camp.csv provided that you have all your unique campaigns in second table. I just made dummmy data here where x is your campaign and y is your Adgroup

require(data.table)
x<-data.frame(x=sample(1:10, 100, replace=T), y=sample(100:999,100))
y<-data.table(x)
l<-y[,list(y=list(y)),by=x]
l$y<-sapply(l$y, paste, collapse=",")
write.table(l,...)

Be careful with writing as csv because your second column now has comma in it, so tsv may be better