In ihmeuw-demographics/demViz: Data Visualization Functions for Demography, Public Health and the Social Sciences

knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)

The demViz package provides simple ggplot2 wrapper functions for common graphs used in demography, public health and the social sciences.

One of the most common plots made when comparing estimates or data for different groupings (by location, sex, age, race, income etc.) is a line graph.

library(demViz)
library(ggplot2)
library(data.table)

# create population projections
thailand_population_estimates <- demCore::ccmpp(
  inputs = demCore::thailand_initial_estimates,
  settings = list(
    years = seq(1960, 1995, 5),
    sexes = c("female", "male"),
    ages = seq(0, 80, 5),
    ages_survival = seq(0, 85, 5),
    ages_asfr = seq(15, 45, 5)
  )
)
thailand_population_estimates[, source_name := "CCMPP Projection"]
thailand_population_estimates[, source_type := "Estimate"]

thailand_population_data <- copy(demCore::thailand_data$population)
thailand_population_data[, source_name := "Census Data"]
thailand_population_data[, source_type := "Data"]

# combine projections with population data
thailand_population <- rbind(
  thailand_population_estimates,
  thailand_population_data,
  use.names = T
)

# add 'age_name' column
hierarchyUtils::gen_name(thailand_population, col_stem = "age")
thailand_population[, age_name := factor(age_name, levels = unique(thailand_population[, age_name]))]

# add column differentiating the data to be plotted as a point
thailand_population[, point := source_type == "Data"]

To demonstrate demViz::plot_line_graph we'll use population projections and population data from the demCore package. This is what the plot input data looks like after some basic prep.

thailand_population

plot_line_graph requires that we specify what column in the input data corresponds to the x-value (x_col) and the y-value (y_col). The point_col argument specifies the data we want to plot as points rather than a line.

The scale_manual argument is a flexible argument that allows the user to specify manual values for different aesthetics like colour or linetype etc. Each aesthetic must have col, legend_title and scale attributes.

plot_line_graph(
  dt = thailand_population,
  plot_title = "Thailand Population Time Series",
  x_col = "year",
  x_axis_title = "Year",
  y_col = "value",
  y_axis_title = "Population",
  y_axis_commas = TRUE,
  point_col = "point",
  scale_manual = list(
    colour = list(
      col = "source_name",
      legend_title = "Source",
      scale = c("Census Data" = "#A55B3B", "CCMPP Projection" = "#4DAF4A")
    )
  )
)

ihmeuw-demographics/demViz documentation built on Feb. 6, 2021, 11:10 p.m.