Correlation plot

Description

Plots a correlation matrix of a series of variables.

plot_correlation(
  data,
  var,
  var_label = NULL,
  method = "pearson",
  plot_type = c("circle", "number"),
  scale = 1,
  title = NULL,
  palette = "IDE1",
  print = FALSE
)

Arguments

  • data: Data frame containing equally spaced (daily, weekly, monthly) covariate or disease case observations for one or multiple locations.
  • var: Character vector containing variables in data to include in the correlation matrix.
  • var_label: Optional character vector of the same length as var containing custom names for the variables.
  • method: Correlation computation method. Options include “pearson” (default), “spearman” or “kendall”.
  • plot_type: Character vector of length 2 indicating the type of plot to use in the lower triangular and diagonal (1st element) and the upper triangular (2nd element). Options include “circle”, “number” and “raster”.
  • scale: Circle and number size multiplier, e.g. 1.1 increases the size a 10% while 0.9 decreases it a 10%.
  • title: Optional title of the plot.
  • palette: GHR, RColorBrewer or colorspace palette. Use “-” before the palette name (e.g., “-Reds”) to reverse it.
  • print: Logical. If TRUE, print the correlation matrix.

Returns

A plot of the correlation matrix.

Examples

# Load data
data("dengue_MS")

# Pearson correlation plot
plot_correlation(dengue_MS, 
                 method = "pearson",
                 var = c("dengue_cases","pop_density", 
                         "tmax", "tmin", "pdsi", "urban",
                         "water_network", "water_shortage"),  
                 var_label = c("dengue cases","pop. density", 
                               "max temp", "min temp", "drought index", "urbanization",
                               "water network", "water shortage"),
                 title = "Correlation matrix") 

# Print spearman correlation plot of type 'raster' and 'number' 
# with another palette 
plot_correlation(dengue_MS,
                 method = "spearman",
                 var = c("dengue_cases","pop_density", 
                         "tmax", "tmin", "pdsi", "urban",
                         "water_network", "water_shortage"),  
                 var_label = c("dengue cases","pop. density", 
                               "max temp", "min temp", "drought index", "urbanization",
                               "water network", "water shortage"),
                 plot_type = c("raster", "number"),
                 palette = "-Blue-Red 3")