Interactive Map - Rooftop Solar

The map below is from a sample (n=500) collected from the states that offer solar rebates and incentives according to sunrun.com. Those states are: Arizona, California, Colorado, Connecticut, Florida, Hawaii, Illinois, Massachusetts, Maryland, Nevada, New Hampshire, New Jersey, New Mexico, New York, Pennsylvania, Rhode Island, South Carolina, Texas, Vermont, and Wisconsin. The data is analyzed in this report.

I used the data from the report to create the map using Kyle Cuilla’s code for creating interactive tooltip tables.

code

#suppress warnings from the rgdal package
options("rgdal_show_exportToProj4_warnings"="none")

#load libraries
library(readr)
library(dplyr)
library(ggplot2)
library(jtools)
library(huxtable)
library(tidyverse)
library(HH)
library(ggsci)
library(gt)
library(gtExtras)
library(usmap)
library(rgdal)
library(maptools)

code

incentive <- read_csv("Pollfish_Survey_Rooftop_Solar_Panels_Incentives_313551447.csv")

incentive_select <- incentive %>% rename(state = "Area",
                                         own = "Do you own your home?",
                                         rooftop = "Do you have rooftop solar installations in your home?",
                                         year_born = "Year Of Birth",
                                         motivation_financial =
                                           "What was your motivation for installing rooftop solar panels in your home? (select all that apply)...16",
                                         motivation_sustainable =
                                           "What was your motivation for installing rooftop solar panels in your home? (select all that apply)...17",
                                         motivation_regulation =
                                           "What was your motivation for installing rooftop solar panels in your home? (select all that apply)...18",
                                         other = "What was your motivation for installing rooftop solar panels in your home? (select all that apply)...19",
                                         reform_agree = "How strongly do you agree with the proposed rooftop solar incentive reforms in your local jurisdiction?",
                                         reform_desire = "Overall, Do you believe that there should be reforms to your utility's current rooftop solar incentives programs?",
                                         trust_utility = "On a scale of 1-5, how much do you trust your local utility to decarbonize while serving the best interests of its customers?",
                                         invest_reward = "How much do you agree with the following statements about solar incentives and net metering? Only people who are investing in rooftop solar panels should be rewarded for their contribution to clean energy generation.",
                                         more_support = "How much do you agree with the following statements about solar incentives and net metering? More support should be provided to those who don’t have access to rooftop solar.",
                                         utility_agree = "How much do you agree that your utility is doing enough to reach decarbonization objectives?",
                                         pay_fee = "How much do you agree with the following statements about solar incentives and net metering? Incentives are too high for rooftop solar panels owners. They should pay a fee for sending power to the grid.") %>%
  dplyr::select(state, City, Gender, Age, year_born, own, rooftop, motivation_financial,
                motivation_sustainable, motivation_regulation, other, reform_agree,
                reform_desire, trust_utility, utility_agree, invest_reward, more_support, pay_fee, Income, Weight)



incentive_select2 <-  incentive_select %>% 
  dplyr::select(state, City, rooftop) %>%
  dplyr::filter(!rooftop %in% c("No")) %>% 
  count(state, rooftop = factor(rooftop)) %>% 
  rename(number = "n")

code

#create table
states_map <- ggplot2::map_data("state")
incentive_select2$state <- tolower(incentive_select2$state)

gt_table <- incentive_select2 %>% 
  dplyr::arrange(state) %>%
  dplyr::select(state, number) %>% 
  gt::gt() %>% 
  gt::cols_width(everything() ~ px(100)) %>%
  gtExtras::gt_theme_espn() %>%
  gt::tab_header(title = "Respondents Who Own Rooftop Solar in Each State") 

gt_table

Respondents Who Own Rooftop Solar in Each State
state	number
arizona	6
california	22
colorado	1
connecticut	2
florida	31
illinois	6
maryland	3
massachusetts	4
nevada	7
new jersey	9
new york	20
pennsylvania	11
rhode island	2
south carolina	2
texas	24
wisconsin	2

code

#create html table
gt_table_html <- gt_table %>%
  gt::as_raw_html()


table_head <- strsplit(as.character(gt_table_html), "<tr><td")[[1]][1]

table_body <- c()
for (i in 2:17) {
  table_body[i - 1] <-
    paste0("<tr><td",
           strsplit(as.character(gt_table_html), "<tr><td")[[1]][i],
           "</tbody></table>")
  html_tables <- paste0(table_head, table_body)
}

incentive_select2 <- incentive_select2 %>%
  dplyr::mutate(tooltip = data.frame(html_tables)) 

incentive_select2 <- incentive_select2[-c(2)]

#create interactive map
gg_map <- ggplot(incentive_select2, aes(map_id = state)) +
  ggiraph::geom_map_interactive(
    aes(
      fill = number,
      data_id = state,
      tooltip = tooltip$html_tables
    ),
    color = "white",
    map = states_map
  ) +
  borders("state") +
  expand_limits(x = states_map$long, y = states_map$lat) +
  ggsci::scale_fill_material("blue",
                             label = scales::comma) +
  labs(fill = "Rooftop Solar") +
  theme_void() +
  theme(legend.title = element_blank(),
        plot.margin=margin(t=10,b=5,l=10,r=10))

ggiraph::girafe(ggobj = gg_map, width_svg = 5, height_svg = 3)