corr_matrix: Calculates Pearson correlation coefficients for all numeric...
In UBC-MDS/collinearityR_tool: Identify Multicollinearity Issues
Description
Usage
Arguments
Value
Examples
View source: R/collinearityR.R
Description
Calculates Pearson correlation coefficients for all numeric variables.
Rounds the outcome to desired decimals. Outputs a matrix or a dataframe
(longer matrix)
Usage
1
corr_matrix(df, decimals = 2)
Arguments
df
tibble, the input dataframe
decimals
int, the number of decimals
Value
a generic correlation matrix and its longer form that can be passed to other functions in this package.
Examples
1
corr_matrix(tibble::tibble(x = 1:5, y = 2:6))
UBC-MDS/collinearityR_tool documentation built on Feb. 6, 2022, 9:41 p.m.
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Description Usage Arguments Value Examples
View source: R/collinearityR.R
Description
Calculates Pearson correlation coefficients for all numeric variables. Rounds the outcome to desired decimals. Outputs a matrix or a dataframe (longer matrix)
Usage
1 | corr_matrix(df, decimals = 2)
|
Arguments
df |
tibble, the input dataframe |
decimals |
int, the number of decimals |
Value
a generic correlation matrix and its longer form that can be passed to other functions in this package.
Examples
1 | corr_matrix(tibble::tibble(x = 1:5, y = 2:6))
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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