I would like to correlate two variables and have the output reported separately for levels of a third variable.

My data are similar to this example:

```
var1 <- c(7, 8, 9, 10, 11, 12)
var2 <- c(18, 17, 16, 15, 14, 13)
categories <- c(1, 2, 3, 1, 2, 3)
```

And I want to correlate var1 with var2 within the categories, such that the results would show the correlation of the values of var1 and var2 for category 1 separately from category 2 and category 3.

In SAS, I would do:

```
PROC CORR DATA=x;
BY CATEGORY
VAR VAR1
WITH VAR2;
RUN;
```

Answer:

You can put your records into a data.frame and then split by the cateogies and then run the correlation for each of the categories.

```
sapply(
split(data.frame(var1, var2), categories),
function(x) cor(x[[1]],x[[2]])
)
```

This can look prettier with the `dplyr`

library

```
library(dplyr)
data.frame(var1=var1, var2=var2, categories=categories) %>%
group_by(categories) %>%
summarize(cor= cor(var1, var2))
```

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