How to get maximum value from a column in a data.frame and get ALL records

Question

I have a data.frame and I wish to get the row that contains the maximum value for the given column Total

Txn_date  Cust_no   Acct_no cust_type Credit Debit Total
09DEC2013   17382 601298644         I   1500     0  1500
16DEC2013   17382 601298644         I    500     0   500
17DEC2013   17382 601298644         I      0    60    60
18DEC2013   17382 601298644         I      0   200   200
19DEC2013   17382 601298644         I   1500     0  1500
20DEC2013   17382 601298644         I      0    60    60
20DEC2013   17382 601298644         I      0   103   103
30DEC2013   17382 601298644         I    500     0   500

So, I wrote a simple SQL query, to be parsed using sqldf() as follows :

s1<-paste("SELECT Txn_date, Cust_no,Credit,Debit,Total,max(Total) as 'MaxTxnAmt' FROM sample GROUP BY Cust_no")
sample_t1<-sqldf(s1)

And that gives me

Txn_date Cust_no   Acct_no cust_type Credit Debit Total
09DEC2013   17382 601298644         I   1500     0  1500

I get the exact output as shown above if I am using base - R functions :

sample_t1<-do.call(rbind,
        lapply(split(sample,sample$Cust_no),
               function(data) data[which.max(data$Total),]))

I wish to know, how do I get ALL the rows from the table sample that have the maximum value for the column Total.

Desired output :

Txn_date Cust_no   Acct_no cust_type Credit Debit Total
09DEC2013   17382 601298644         I   1500     0  1500
19DEC2013   17382 601298644         I   1500     0  1500

---

Sample data :

sample <- structure(list(Txn_date = c("09DEC2013", "16DEC2013", "17DEC2013", 
"18DEC2013", "19DEC2013", "20DEC2013", "20DEC2013", "30DEC2013"
), Cust_no = c(17382L, 17382L, 17382L, 17382L, 17382L, 17382L, 
17382L, 17382L), Acct_no = c("601298644", "601298644", "601298644", 
"601298644", "601298644", "601298644", "601298644", "601298644"
), cust_type = c("I", "I", "I", "I", "I", "I", "I", "I"), Credit = c(1500, 
500, 0, 0, 1500, 0, 0, 500), Debit = c(0, 0, 60, 200, 0, 60, 
103, 0), Total = c(1500, 500, 60, 200, 1500, 60, 103, 500)), .Names = c("Txn_date", 
"Cust_no", "Acct_no", "cust_type", "Credit", "Debit", "Total"
), row.names = c(16303L, 29153L, 31174L, 33179L, 35388L, 38750L, 
38751L, 53052L), class = "data.frame")

Answer 1

Try

library(dplyr)
sample %>% 
     group_by(Cust_no) %>%
     filter( Total==max(Total))
#   Txn_date Cust_no   Acct_no cust_type Credit Debit Total
#1 09DEC2013   17382 601298644         I   1500     0  1500
#2 19DEC2013   17382 601298644         I   1500     0  1500

Or

library(data.table)
setDT(sample)[, .SD[Total==max(Total)] ,Cust_no]
#   Cust_no  Txn_date   Acct_no cust_type Credit Debit Total
#1:   17382 09DEC2013 601298644         I   1500     0  1500
#2:   17382 19DEC2013 601298644         I   1500     0  1500

Or

setkey(setDT(sample), Total)[J(max(Total)), .SD,Cust_no]
#   Cust_no  Txn_date   Acct_no cust_type Credit Debit Total
#1:   17382 09DEC2013 601298644         I   1500     0  1500
#2:   17382 19DEC2013 601298644         I   1500     0  1500

Or using base R

sample[with(sample, ave(Total, Cust_no, FUN=max)==Total),]
#   Txn_date Cust_no   Acct_no cust_type Credit Debit Total
#1 09DEC2013   17382 601298644         I   1500     0  1500
#5 19DEC2013   17382 601298644         I   1500     0  1500

Answer 2

1) Correlated Subquery Try this:

sqldf("select * 
       from sample a
       where Total = (select max(Total) 
                      from sample b 
                      where b.Cust_no = a.Cust_no)")

giving:

   Txn_date Cust_no   Acct_no cust_type Credit Debit Total
1 09DEC2013   17382 601298644         I   1500     0  1500
2 19DEC2013   17382 601298644         I   1500     0  1500

2) Join with subquery or this:

sqldf("select * 
       from sample
       join (select Cust_no, max(Total) as 'MaxTxnAmt'
             from sample 
             group by Cust_no)
       using(Cust_no)
       where Total = MaxTxnAmt")

giving:

   Txn_date Cust_no   Acct_no cust_type Credit Debit Total MaxTxnAmt
1 09DEC2013   17382 601298644         I   1500     0  1500      1500
2 19DEC2013   17382 601298644         I   1500     0  1500      1500