First of all, i'm sorry if this question is so basic. I'm trying just to calculate correlation coefficient from three lines of my dataframe :
df=structure(list(Id = 1:3, V1 = c(27L, 40L, 29L), V2 = c(70L,
101L, 48L), V3 = c(68L, 84L, 55L), V4 = c(48L, 80L, 39L), V5 = c(58L,
73L, 38L), V6 = c(80L, 103L, 46L), V7 = c(99L, 115L, 52L), V8 = c(46L,
82L, 58L), V9 = c(26L, 38L, 33L), V10 = c(13L, 17L, 13L)), .Names = c("Id",
"V1", "V2", "V3", "V4", "V5", "V6", "V7", "V8", "V9", "V10"), row.names = c(2L,
5L, 8L), class = "data.frame")
What i'm doing is to convert these lines to vectors numeric
df=df[-1]
g=as.numeric(df[1,])
h=as.numeric(df[2,])
i=as.numeric(df[3,])
and running correlation 2 per 2:
> cor(g,h)
[1] 0.9530113
> cor(g,i)
[1] 0.7557693
> cor(h,i)
[1] 0.8519315
I made search about this but it seems that there is no such function cor(g,h,i)
, instead i Cant run cor(df)
but it will gives me correlation between all the V1:V10
.
In conclusion, is there function that allows me to execute cor(g,h,i)
and return to me the three correlation coefficient (0.9530113 , 0.7557693 , 0.8519315)
or a more optimised method than mine.