corr_plot: Create correlation plots of CSPP data

Description

corr_plot takes CSPP data from get_cspp_data and returns either a correlation matrix or correlation plot.

Usage

corr_plot(
  data = NULL,
  vars = NULL,
  summarize = TRUE,
  labels = TRUE,
  label_size = 3,
  colors = c("#6D9EC1", "#FFFFFF", "#E46726"),
  cor_matrix = FALSE
)

Value

ggplot2 object or correlation matrix

Arguments

data: A dataframe. If data is generated by get_cspp_data function, the function can automatically parse the dataframe. Otherwise, this function will attempt to make a correlation plot or matrix from all numeric variables within the passed dataframe.
vars: Default is NULL. If left NULL, uses all variables within the passed dataframe. Otherwise, must be a character vector. The dataframe is subset based on variables listed.
summarize: Default is TRUE. If TRUE, and if the variable st is present, the function will create state specific averages for each variable in the dataframe. If FALSE, the function will generate the correlation matrix and plot for all values in the dataset.
labels: Default is TRUE. If TRUE, the correlation plot will include labels for the correlation value. If FALSE, no labels will be present.
label_size: Default is 3. Controls the size of the font for labels.
colors: Specify the colors to be used in the correlation plot. Must include three values in a character vector format. The default values are `c("#6D9EC1", "#FFFFFF", "#E46726")`.
cor_matrix: Default is FALSE. If set to TRUE, instead of returning a ggplot object that is a correlation plot, returns a correlation matrix. This is particularly useful if you want to customize the output with ggcorrplot.

Details

This function is a wrapper that passes a dataframe to the ggcorrplot::ggcorrplot function which generates correlation heat plots.

Examples

Run this code


corr_plot(data = get_cspp_data(), vars = c("pollib_median",
 "innovatescore_boehmkeskinner", "citi6013", "ranney4_control", "h_diffs"),
 cor_matrix = FALSE)