R: Generate map visualizations (choropleths) of CSPP data

generate_map {cspp}

R Documentation

Generate map visualizations (choropleths) of CSPP data

Description

generate_map takes CSPP data from get_cspp_data and plots the values of numeric variables on the map of the U.S. It can also plot individual states or sets of states.

Arguments

`cspp_data`	Dataframe generated by `get_cspp_data` which must include the variable `state`. If there are multiple years of data per state, by default the most recent year is used in creating the map unless `average_years` is set to `TRUE`. Default is NULL and returns the most recent year's `poptotal` data as an example map.
`var_name`	Specify the variable from the dataset passed to `cspp_data` to plot on the map. If left blank, the first variable that is not "year", "st", "state", "state_fips", or "state_icspr" is used. Default is NULL.
`average_years`	Default is `FALSE`. If `TRUE`, averages over all of the years per state in the dataframe to produce a value to plot on the map. If the type of the variable in `var_name` is not numeric, will reset this parameter to FALSE.
`drop_NA_states`	Choose whether to drop states at the map generating stage which have NA values. Default is `FALSE` and states with missing data will be filled grey. If set to `TRUE`, states will have no fill in the plot. If you're passing a dataframe subset to certain states, set this to TRUE.
`poly_args`	Default is `list(color = "#666666", size = .5)`. Changes the aesthetics of how the states look when plotted. The `fill` of each state can be manually changed through ggplot's `scale_fill_` (see examples). See `geom_polygon` for other options to pass to this argument.

Details

Note: due to complications with plotting Alaska and Hawaii, this package currently does not support plotting these two states.

This function is general in the sense that it will produce a ggplot-style map for any dataframe passed to it with the proper formatting. Any dataframe that has at least three columns, with the first two a numeric 'year' column and a state name as a string, and the final column the value to be plotted, will work with this function.

Value

Returns a ggplot object. See examples for how to work with this object.

Examples


## default map with total population
generate_map()

## pass specific variables
# returns average over all non NA years in the data
generate_map(get_cspp_data(var_category = "demographics"),
             var_name = "pctpopover65")

## add additional ggplot options
generate_map(get_cspp_data(var_category = "demographics"),
             var_name = "pctpopover65",
             poly_args = list(color = "black"),
             drop_NA_states = FALSE) +
 ggplot2::scale_fill_gradient(low = "white", high = "red") +
 ggplot2::theme(legend.position = "none") +
 ggplot2::ggtitle("% Population Over 65")

## plot specific states
# drop_NA_states set to TRUE plots only those states
library(dplyr)
generate_map(get_cspp_data(var_category = "demographics") %>%
               dplyr::filter(st %in% c("NC", "VA", "SC")),
             var_name = "pctpopover65",
             poly_args = list(color = "black"),
             drop_NA_states = TRUE) +
 ggplot2::scale_fill_gradient(low = "white", high = "red") +
 ggplot2::theme(legend.position = "none") +
 ggplot2::ggtitle("% Population Over 65")

## pass specific variables and years
# returns average over set of years provided
library(dplyr)
generate_map(get_cspp_data(var_category = "demographics") %>%
 dplyr::filter(year %in% seq(2001, 2010)))

# returns average over set of years provided
library(dplyr)
generate_map(get_cspp_data(var_category = "demographics") %>%
 dplyr::filter(year %in% seq(2001, 2010)))