Figure4_NO2.R

### Code to plot NO2 mean difference of PE for the years 2019 and 2020

library(readxl)
library(tidyverse)
library(boot)
library(ggthemes)
library(grid)
library(gridExtra)
library(forecast)
library(data.table)
library(cowplot)

df_all_plot <- read.csv('df_box_NO2_2019_2020_Jan_Apr.csv')

df_all_plot$Year = factor(df_all_plot$Year)


state.abb = as.character(unique(df_all_plot$state))



df_no2_summary.2 = data.frame(df_no2_summary)
df_no2_summary.2$Year = as.numeric(as.character(df_no2_summary.2$Year))
df_wide_no2 <- reshape(df_no2_summary.2, direction = "wide", v.names="no2", timevar="Year", idvar="state") 

png("figures/NO2_2019_2020_mean_difference.png", height = 1000, width=1500)
no2.plot <- ggplot(df_no2_summary, aes(x=state, y=no2, colour=Year)) +
  geom_point(size=5)+
  geom_hline(yintercept = 0)+
  geom_segment(aes(x=state, xend=state, y=no2.2019, yend=no2.2020), 
               size=1, data=df_wide_no2, colour="black", linetype="dotted")+
  theme_classic()+
  theme(plot.title = element_text(hjust = 0.5))+
  theme(axis.text.x = element_text(size = 14, angle = 45),
        axis.text.y = element_text(size = 14),
        axis.title = element_text(size = 16),
        legend.title = element_text(size=14), #change legend title font size
        legend.text = element_text(size=14))+
  xlab("State")+
  ylab("NO2 mean difference")

no2.plot
dev.off()