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Visualise Population Profile of Survey Data

Source: R/plot_popn.R
plot_popn.Rd

plot_popn creates a visual representation of the population profile using survey data. It can illustrate the distribution of age groups across genders or other categories, and optionally includes average age or other statistics.

Usage

plot_popn(
  data,
  xVar,
  yVar,
  group = NULL,
  weight = NULL,
  meanVar = NULL,
  colours = NULL,
  title = "Population Structure",
  subtitle = NULL,
  xLab = "Population",
  yLab = "Age",
  addLabels = FALSE,
  thresholdLab = 3,
  nudgeLab = 0.2,
  sizeLab = 11,
  faceLab = c("plain", "bold", "italic", "bold.italic")
)

Arguments

data

A data frame containing survey data.

xVar

The gender variable (or a similar categorical variable) for the x-axis.

yVar

The age group variable for the y-axis.

group

An optional variable for additional grouping or comparison.

weight

An optional weighting variable for the analysis.

meanVar

An optional numeric variable to include average values in the plot.

colours

A vector of three colors for male, female, and total. This parameter is optional.

title

The title of the plot; defaults to "Population Structure".

subtitle

The subtitle for the plot, particularly useful in grouped plots; defaults to the question associated with the group variable.

xLab

The title for the x-axis; defaults to "Population (%)".

yLab

The title for the y-axis; defaults to "Age".

addLabels

A logical indicating whether to add percentage labels to the plot; defaults to FALSE.

thresholdLab

A numeric threshold for label placement inside or outside the bars.

nudgeLab

A numeric value to adjust the horizontal position of labels.

sizeLab

The font size for labels.

faceLab

The font style for labels; can be "plain", "bold", "italic", or "bold.italic".

Value

A ggplot2 plot representing the population profile based on the provided survey data.

Examples

if (FALSE) { # \dontrun{
  # Example: Create a population plot with age and gender
  plot_popn(dataset,
            xVar = "gender",
            yVar = "age_categories",
            weight = "wgtvar",
            meanVar = "age")
} # }