04_mapping.Rmd

---
title: "mapping smart cities"
author: "cm"
date: "2024-01-10"
output: html_document
---

```{r}
options(scipen=16)
library(tidyverse)
```
```{r}
df <- read_csv("data/smart_cities20240110.csv")
```

# how prevalent smart cities, towns, and villages are in the US?

```{r}
# total number of smart cities
sum(df$smart)
```

```{r}
# total number of people in smart cities
df %>% filter(smart == 1) %>% summarise(total_pop=sum(POP20))
```

```{r}
# summarize by state
df %>% group_by(State) %>% summarise(muni_count=n(), smart_count=sum(smart), smart_den=smart_count/muni_count*100) %>% arrange(smart_count)
```

```{r}
# summarize by population
df <- df %>% mutate(pop_size=case_when(POP20>=1000000 ~ 4, POP20<1000000&POP20>=100000 ~3, POP20<100000&POP20>= 10000 ~2, POP20<10000 ~1))
df %>% group_by(pop_size) %>% summarise(muni_count=n(), smart_count=sum(smart), smart_den=round(smart_count/muni_count*100,1))
``` 

```{r}
map_df <- df %>% filter(State!="AK") %>% filter(State!="HI") %>% arrange(smart) # to make smart cities pop up in map
```

```{r}
#mycolor <- c("#596174","#d32d41" )
#mycolor <- c("#1c4e80","#d32d41" )
mycolor <- c("#596174","#ea6a47" )
states <- map_data("state")
```
```{r}
#ggplot() + 
#  theme_void() +
#  geom_polygon(data = states, aes(x=long, y = lat, group = group), linewidth=0.4 ,color ="white",fill = 'gray90')
```
```{r}
ggplot() + 
  geom_polygon(data = states, aes(x=long, y = lat, group = group), linewidth=0.4 ,color ="white",fill = 'gray95') + 
  geom_point(data = map_df %>% filter(smart==1),  aes(x = INTPTLON, y = INTPTLAT, stroke =0,  color=as.factor(smart)), size=2) + 
  theme_void() +
  xlab('') + ylab('') +
  scale_color_manual(name="", values = "salmon")+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(), legend.position = c(0.2, 0.15))+
  guides(color="none", fill="none")
```
```{r}
ggplot() + 
  geom_polygon(data = states, aes(x=long, y = lat, group = group), linewidth=0.4 ,color ="white",fill = 'gray95') + 
  geom_point(data = map_df,  aes(x = INTPTLON, y = INTPTLAT, stroke =0,  color=as.factor(smart)), size=0.8, alpha = 0.7) + 
  geom_path(data = states, aes(x = long, y = lat, group = group), color = "white", size = 0.2) +
  geom_point(data = map_df %>% filter(smart==1),  aes(x = INTPTLON, y = INTPTLAT, stroke =0,  color=as.factor(smart)), size=0.8) +
  theme_void() +
  xlab('') + ylab('') +
  scale_color_manual(name="", labels=c("1"="Smart cities", "0"="Non-smart cities"), values = mycolor)+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(), legend.position = c(0.2, 0.15))+
  guides(color=guide_legend(reverse=T, override.aes = list(size = 5)))
#ggsave("figure/map.png")
```

```{r}
ggplot() + 
  geom_polygon(data = states, aes(x=long, y = lat, group = group), linewidth=0.2, color ="white", fill = 'gray90') + 
  geom_point(data = map_df,  aes(x = INTPTLON, y = INTPTLAT, stroke=0.6, color=as.factor(smart),size=as.factor(pop_size)), alpha = 0.4) + 
  geom_path(data = states, aes(x = long, y = lat, group = group), color = "gray80", size = 0.1) +
  theme_void() +
  xlab('') + ylab('') +
  scale_size_ordinal(name=" Population", range=c(0.5,7), 
                      labels=c("4"="1 million or more" ,"3"= "100,000 to 999,999", "2"="10,000 to 99,999", "1"="Less than 10,000"), )+
  scale_color_manual(name=" ", labels=c("1"="Smart city", "0"="Non-smart city"), values = mycolor)+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(), legend.position = c(0.98 , 0.24))+
  theme(plot.margin = unit(c(1,2,1,1), "cm"))+
  guides(size = guide_legend(reverse=T, override.aes = list(shape=1)), color=guide_legend(reverse=T, override.aes = list(size = 5)))
```
```{r}
mycolor2 <- c("grey75","#ea6a47" )
ggplot() + 
  geom_polygon(data = states, aes(x=long, y = lat, group = group), linewidth=0.4 ,color ="grey",fill = 'white') + 
  geom_point(data = map_df,  aes(x = INTPTLON, y = INTPTLAT, stroke =0,  color=as.factor(smart)), size=0.6, alpha = 0.7) + 
  geom_path(data = states, aes(x = long, y = lat, group = group), color = "white", size = 0.3) +
  geom_point(data = map_df %>% filter(smart==1),  aes(x = INTPTLON, y = INTPTLAT, stroke =0,  color=as.factor(smart)), size=1) +
  theme_void() +
  xlab('') + ylab('') +
  scale_color_manual(name="", labels=c("1"="Smart cities", "0"="Non-smart cities"), values = mycolor2)+
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(), legend.position = c(0.2, 0.15))+
  guides(color=guide_legend(reverse=T, override.aes = list(size = 5)))
#ggsave("figure/map.pdf", dpi=500)
```