Issue with indexing using two data frames in R - r

Question

I have two data frames Table_1 and Table_2 and I need to add a column "index" to Table_2 where value 1 for matching rows from Table_1 and 0 for others.
Basically, I need to match the "Pol", "CTY" ,"STATE" and "CRP" columns from Table_1 and "STATE", "CTY" , "CRP" and "Pol_No" from Table_2.
I prefer the data.table method.
Table_1:
Pol Cty Avg STATE CRP
85010 23 1123 MO 11
75022 23 1123 MO 11
35014 143 450 MO 11
.
.
Table_2:
STATE CTY CRP Pol_No Plan Price
AL 1 11 150410 90 4563
AL 1 21 45023 90 5402
MO 143 11 85010 90 2522
.
.
Desired output as below.
Table_2:
STATE CTY CRP Pol_No Plan Price Index
AL 1 11 150410 90 4563 0
AL 1 21 45023 90 5402 0
MO 143 11 85010 90 2522 1
.
.
How can I achieve this is R.?
Any help is appreciated.
Thanks.

Answer 1

Here's an entirely data.table solution:
merge(t1,t2,by.x='Pol', by.y='Pol_No', all.y=TRUE)[,c('STATE.y','CTY', 'Cty', 'CRP.y', 'Pol', 'Plan', 'Price')]
#-----
STATE.y CTY Cty CRP.y Pol Plan Price
1: AL 1 NA 21 45023 90 5402
2: MO 143 23 11 85010 90 2522
3: AL 1 NA 11 150410 90 4563
#--------
t3 <- merge(t1,t2,by.x='Pol', by.y='Pol_No', all.y=TRUE)[ ,
c('STATE.y','CTY', 'Cty', 'CRP.y', 'Pol', 'Plan', 'Price')]
t3[ , index := as.numeric(!is.na(Cty))]
t3
#--------
STATE.y CTY Cty CRP.y Pol Plan Price index
1: AL 1 NA 21 45023 90 5402 0
2: MO 143 23 11 85010 90 2522 1
3: AL 1 NA 11 150410 90 4563 0
To get column names right after merge(.. I first looked at:
merge(t1,t2,by.x='Pol', by.y='Pol_No', all.y=TRUE)
Pol Cty Avg STATE.x CRP.x STATE.y CTY CRP.y Plan Price
1: 45023 NA NA <NA> NA AL 1 21 90 5402
2: 85010 23 1123 MO 11 MO 143 11 90 2522
3: 150410 NA NA <NA> NA AL 1 11 90 4563

Answer 2

I think this is a straight-forward multi-column join:
library(dplyr)
t2 %>%
left_join(transmute(t1, CTY=Cty, STATE, Index=1L), by=c("CTY", "STATE")) %>%
mutate(Index = if_else(is.na(Index), 0L, Index))
# STATE CTY CRP Pol_No Plan Price Index
# 1 AL 1 11 150410 90 4563 0
# 2 AL 1 21 45023 90 5402 0
# 3 MO 143 11 85010 90 2522 1
EDIT
I've been trying to learn data.table, thought I'd give this a try. It feels a little clumsy to me, I'm sure there is a way to streamline it.
t1 <- setDT(t1); t2 <- setDT(t2)
For convenience, set the column names to be the same (I'm not sure how to make it happen easily otherwise) ... one is "Cty", the other is "CTY". Make them the same.
colnames(t1)[2] <- "CTY"
Now, the merge.
t1[,.(CTY,STATE,CRP,Index=1),][t2,on=c("CTY","STATE","CRP")]
# CTY STATE CRP Index Pol_No Plan Price
# 1: 1 AL 11 NA 150410 90 4563
# 2: 1 AL 21 NA 45023 90 5402
# 3: 143 MO 11 1 85010 90 2522
Notes:
the first bracket-op is selecting just the three joining columns and assigning the fourth, Index;
the actual join is in the second bracket-op, the first is just a selection
typically data.table ops work in side-effect, but not merges or selections like this, so it returns it without modifying the underlying structure; for this, we'll need to store it (back in t2, perhaps)
It's close ... now just update the Index field, since it's either 1 where the data co-exists or NA otherwise.
t2 <- t1[,.(CTY,STATE,CRP,Index=1),][t2,on=c("CTY","STATE","CRP")]
t2[,Index := as.integer(!is.na(Index)),]
t2
# CTY STATE CRP Index Pol_No Plan Price
# 1: 1 AL 11 0 150410 90 4563
# 2: 1 AL 21 0 45023 90 5402
# 3: 143 MO 11 1 85010 90 2522
Data:
t1 <- read.table(header=TRUE, stringsAsFactors=FALSE, text='
Pol Cty Avg STATE CRP
85010 23 1123 MO 11
75022 23 1123 MO 11
35014 143 450 MO 11')
t2 <- read.table(header=TRUE, stringsAsFactors=FALSE, text='
STATE CTY CRP Pol_No Plan Price
AL 1 11 150410 90 4563
AL 1 21 45023 90 5402
MO 143 11 85010 90 2522')

Answer 3

This is not a nice solution but it works for data.table. You need sqldf which works for dataframes and data tables.
library(data.table)
df1<-data.table(Pol=c(85010,75022,35014),Cty=c(23,23,143), Avg=c(1123,1123,450),STATE=c("MO","MO","MO"), CRP=c(11,11,11))
df2=data.table(STATE=c("AL","AL","MO"),CTY=c(1,1,143),CRP=c(11,21,11),Pol_No=c(150410,45023,85010),Plan=c(90,90,90),Price=c(4563,5402,2522))
library(sqldf)
#left join
df<-sqldf("select df2.STATE,df2.CTY,df2.CRP,df2.Pol_No,df2.Plan,df2.Price,df1.Pol from df2 left join df1 on df1.Pol=df2.Pol_No")
#create index
df$index<-ifelse(is.na(df$Pol),0,1)
#delete extra column
df$Pol<-NULL
> df
STATE CTY CRP Pol_No Plan Price index
1 AL 1 11 150410 90 4563 0
2 AL 1 21 45023 90 5402 0
3 MO 143 11 85010 90 2522 1