quickcode (version 1.0.6)

compHist: Compare histograms of two distributions

Description

For comparing histograms of two data distributions. Simply input the two distributions, and it generates a clear and informative histogram that illustrates the differences between the data.

Usage

compHist(
  x1,
  x2,
  title,
  col1 = "red",
  col2 = "yellow",
  xlab = "",
  ylab = "Frequency",
  separate = FALSE
)

Value

return histogram comparison using basic histogram plot

Arguments

x1

NUMERIC. the first distribution

x2

NUMERIC. the second distribution

title

CHARACTER. title of the histogram plot

col1

CHARACTER. color fill for first distribution

col2

CHARACTER. color fill for second distribution

xlab

CHARACTER. label of the x-axis

ylab

CHARACTER. label of the y-axis

separate

LOGICAL. whether to separate the plots

Some recommended color pairs

col1 = 'dodgerblue4' (and) col2 = 'darksalmon'
col1 = 'brown' (and) col2 = 'beige'
col1 = 'pink' (and) col2 = 'royalblue4'
col1 = 'red' (and) col2 = 'yellow'
col1 = 'limegreen' (and) col2 = 'blue'
col1 = 'darkred' (and) col2 = 'aquamarine4'
col1 = 'purple' (and) col2 = 'yellow'

Details

Users have the option to view individual histograms for each distribution before initiating the comparison, allowing for a detailed examination of each dataset's characteristics. This feature ensures a comprehensive understanding of the data and enhances the user's ability to interpret the results of the distribution comparison provided by this function.

Examples

# compare two normal distributions with means that differ a lot
# in this case, the overlap will not be observed
set.seed(123)
compHist(
  x1 = rnorm(1000, mean = 3),
  x2 = rnorm(1000, mean = 10),
  title = "Histogram of Distributions With Means 3 & 10",
  col1 = "yellow", col2 = "violet"
)


# compare two normal distributions with means that are close
# in this case, the overlap between the histograms will be observed
set.seed(123)
compHist(
  x1 = rnorm(1000, mean = 0),
  x2 = rnorm(1000, mean = 2),
  title = "Histogram of rnorm Distributions With Means 0 & 2",
  col1 = "lightslateblue", col2 = "salmon"
)

set.seed(123)
# separate the plots for preview
compHist(
  x1 = rnorm(1000, mean = 0),
  x2 = rnorm(1000, mean = 2),
  title = c("Plot Means 0", "Plot Means 2"),
  col1 = "#F96167", col2 = "#CCF381",
  separate = TRUE
)