why is correlation na in r

Correlation NA in R

In R, the cor function is used to calculate the correlation coefficient between two variables. If there are missing values in the data, the cor function has an argument called use which specifies how to handle missing values. By default, it is set to "everything", which means that if there are any missing values in the data, the result will be NA[3].

When the use argument is set to "everything", the cor function will return NA if there are any missing values in the data. This is because the correlation coefficient cannot be calculated when there are missing values, and R returns NA to indicate that the result is not available [3].

To handle missing values in the data when calculating the correlation coefficient, the use argument can be set to "complete.obs". This will cause the cor function to calculate the correlation coefficient using only complete pairs of observations, excluding any pairs that contain missing values.

In summary, when using the cor function in R, it's important to consider how missing values should be handled by setting the use argument appropriately to ensure the desired behavior for the correlation calculation.