Question

I'm running cor() on a data.framewith all numeric values and I'm getting this as the result:

       price exprice...
price      1      NA
exprice   NA       1
...

So it's either 1 or NA for each value in the resulting table. Why are the NAs showing up instead of valid correlations?

Was it helpful?

Solution

The 1s are because everything is perfectly correlated with itself, and the NAs are because there are NAs in your variables.

You will have to specify how you want R to compute the correlation when there are missing values, because the default is to only compute a coefficient with complete information.

You can change this behavior with the use argument to cor, see ?cor for details.

OTHER TIPS

Tell the correlation to ignore the NAs with use argument, e.g.:

cor(data$price, data$exprice, use = "complete.obs")

NAs also appear if there are attributes with zero variance (with all elements equal); see for instance:

cor(cbind(a=runif(10),b=rep(1,10)))

which returns:

   a  b
a  1 NA
b NA  1
Warning message:
In cor(cbind(a = runif(10), b = rep(1, 10))) :
  the standard deviation is zero

very simple and correct answer

Tell the correlation to ignore the NAs with use argument, e.g.:

cor(data$price, data$exprice, use = "complete.obs")

The NA can actually be due to 2 reasons. One is that there is a NA in your data. Another one is due to there being one of the values being constant. This results in standard deviation being equal to zero and hence the cor function returns NA.

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