# Correlation of One Variable to All Others in R (Example)

In this R tutorial you’ll learn how to **calculate the correlation of one data frame column to all the others**.

The page contains this:

It’s time to dive into the example…

## Creation of Exemplifying Data

Consider the following example data:

set.seed(6529489) # Create example data data <- data.frame(x1 = rnorm(100), x2 = rnorm(100), x3 = rnorm(100), x4 = rnorm(100)) head(data) # Print head of example data

Table 1 shows that our example data is constructed of the four columns “x1”, “x2”, “x3”, and “x4”.

## Example: Calculate Correlation of One Variable to All Others Using cor() Function

In this example, I’ll demonstrate how to get the Pearson correlation coefficient between a particular data frame variable with all the other variables in this data frame.

To achieve this, we can apply the cor and colnames functions as shown below:

data_cor <- cor(data[ , colnames(data) != "x1"], # Calculate correlations data$x1) data_cor # Print correlation values

As visualized in Table 2, the previous code has managed to construct a correlation matrix for only one of the columns in our data set.

## Video, Further Resources & Summary

If you need more information on the R codes of this article, you might watch the following video on my YouTube channel. I demonstrate the R programming codes of this tutorial in the video:

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In addition, you may read the related articles on Statistics Globe. A selection of articles about topics such as ggplot2, variables, lists, and graphics in R is shown below.

- Correlation Matrix in R
- Calculate Correlation Matrix Only for Numeric Columns
- Remove Highly Correlated Variables from Data Frame
- List All Column Names But One in R
- All R Programming Tutorials

This tutorial has demonstrated how to **compute the correlation of one data frame column to many others** in R. If you have additional questions and/or comments, please let me know in the comments below.

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## 6 Comments. Leave new

Hey thank you for the code, it works fine. I need the significances, too, but cor.mtest doesnt work.Do you have any idea, how to calculate the coefficients and sgnificances?

Hello Vanessa,

You need to convert your data frame to a matrix to use the cor.mtest() function. First, be sure that you install the library:

Then convert your data to a matrix:

After that, you can run the function:

Regards,

Cansu

How can I then plot a corrplot including significant marks (or only circles when significant) for the correlation of x1 with all the other variables (x2, x3 and x4)? resulting in a correlation “vector”

Hello Katharina,

Would a plot like here in the second example help? See the title Use chart.Correlation(): Draw scatter plots.

Best,

Cansu

Is there a way to make this work with cor.test as well? Thanks!

Hello Zach,

I understand that you are intention is to test the correlation between a variable and the others. You can achieve this by using a defined function in the apply() procedure. See the following script.

Best,

Cansu