r - cor.test ,"not enough finite observations"

Question

I use two different ways to use cor.test, one in my own function, the other uses cor.test directly. When I use cor.test in my own function, it appeared an error, how could it happen?

This was OK

cor.test(x=cust_new$maintain_cust/cust_new$ttl_cust,
         y=cust_new$ttl_cust,alternative="two.sided",
         method="pearson",conf.level=0.95)

The following would give the error :

"not enough finite observations"

cor_result<-function(x,y,data){
  a<-cor.test(x=as.numeric(data$x)/as.numeric(data$y),
              y=as.numeric(data$y),
              alternative="two.sided",method="spearman",
              conf.level=0.95)
  r<-a$estimate
  p<-a$p.value
  c<-data.frame(r=r,p=p)
  return(c)
}

d<-cor_result(x=maintain_cust,y=ttl_cust,data=cust_new)

The following would give the error :

'y' must be a numeric vector"

cor_result<-function(x,y,data){
  a<-cor.test(x=data$x/data$y,y=data$y,
            alternative="two.sided",method="spearman",conf.level=0.95)
  r<-a$estimate
  p<-a$p.value
  c<-data.frame(r=r,p=p)
  return(c)
}

d<-cor_result(x=maintain_cust,y=ttl_cust,data=cust_new)

dput(cust_new),a few sample:

structure(list(data_month = structure(c(16953, 16983, 17014, 
17045, 17075, 17106, 16953, 16983, 17014, 17045), class = "Date"), 
    ttl_cust = c(383L, 580L, 735L, 850L, 952L, 1062L, 2418L, 
    2492L, 2515L, 2550L), maintain_cust = c(179L, 266L, 355L, 
    413L, 448L, 508L, 935L, 1026L, 1091L, 1143L)), row.names = c(NA, 
10L), class = "data.frame", .Names = c("data_month", "ttl_cust", 
"maintain_cust"))

Answer 1

You are not properly passing vector (i.e., dataframe column) into function. Consider passing string literals of data frame columns to be referenced with double brackets (and as.numeric() may not be necessary if columns are numeric types):

cor_result<-function(x, y, data){ 
   a<-cor.test(x=as.numeric(data[[x]])/as.numeric(data[[y]]),y=as.numeric(data[[y]]),
               alternative="two.sided", method="spearman", conf.level=0.95) 
   r<-a$estimate 
   p<-a$p.value 
   c<-data.frame(r=r,p=p) 
   return(c) 
}

d<-cor_result(x="maintain_cust", y="ttl_cust", data=cust_new)

Alternatively without data argument:

cor_result<-function(x, y){ 
   a<-cor.test(x=(x/y),y=y,
               alternative="two.sided", method="spearman", conf.level=0.95) 
   r<-a$estimate 
   p<-a$p.value 
   c<-data.frame(r=r,p=p) 
   return(c) 
}

d<-cor_result(x=cust_new$maintain_cust, y=cust_new$ttl_cust)