cspp (version 0.3.3)

generate_map: 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.

Value

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

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.

See Also

get_cspp_data, get_cites, get_var_info

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)))