Interpretation of corr function in R and corrplot function in R



My question may look trivial to many but I am really confused over the concept of correlation?

I applied corr function to complete data frame and gets the values b/w (numeric) features as: 1.795702e-03, -3.072601e-03, -6.481803e-04, 8.701917e-04, 9.061027e-05 and so on.


(a) What is the interpretation to corr function output values that varies b/w negative and positive.

(b) Based on the Values of corr function, when should we keep the feature/variables/columns in our data set OR should we delete them.

© how and when to use corrplot function as almost every kernel uses it.

(d) how to interpret corrplot function.

I request to take some time to answer my question. Also if I could get some link to video or tutorial or document related to it

Warm Regards


Hello Manish,
Correlation number implies that if we change one factor we will see a change in the other one, if the Correlation number is positive means that both factors moves positive way, otherwise if corr number is negative when you increase the factor 1 you will see a reduction in factor2.

Usually you may dismiss one factor when the correlation is near zero.


a) positive correlation means there will be a positive change in item B with change in item A and there will be a negative change in item B with change in item A

b) for selection of the data or columns you should use multicollinearity instead of correlation.
c) it is used to check if there is any relation between two variables or not
d) for the last answer this article might help

I hope my answer helps you,