37/replication_package/Do/Figures/Fig9.Rmd

---
title: "Figure 9"
output: pdf_document
---
  
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = F, warning = F, message = F)
```

```{r, include = F, echo = F}
# Importing Packages
rm(list=ls())
gc()
library(tidyverse)
library(extrafont)
library(gtable)
library(ggplot2)
library(gridExtra)
library(grid)
library(cowplot)
library(grDevices)
loadfonts()
```

```{r}
# SPECIFY DIRECTORY OF THE REPLICATION PACKAGE
setwd("C:/Users/Francesco/Dropbox/AMS_Redistribution/Data/Survey_Data/Replication RESTUD sharing") 

# IMPORTING DATASET
datafig_second_gen = read_csv('Out/Figures_data/figure_9_data.csv', show_col_types = FALSE)
```

```{r}
# Function to Export Figures: SPECIFY DIRECTORY OF THE REPLICATION PACKAGE

FigureExporter = function(Figure, Name, WhereFolderDraft = "C:/Users/Francesco/Dropbox/AMS_Redistribution/Data/Survey_Data/Replication RESTUD sharing"){
  figure_name <- Name
  figures_dir <- file.path(WhereFolderDraft, 'Out/Figures')
  fig_path <- file.path(figures_dir, figure_name)
  png(fig_path, width = 4800, height=2700, res = 720, type = c("cairo-png"))
  Figure1 = Figure
  print(Figure1)
}
```



```{r}
#Data Adjustment for cleaning (Left Panel) Function - Without Rescaling

DataAdjustNoResc = function(data){
  data = data[data$t %in% c("Sweden", "Germany", "Italy", "France", "UK", "US"), !(names(data) %in% "n")]
  data$m_perc <- data$m_perc
  data$m_real <- data$m_real
  data <- transform(data,
                    lbound = lb_perc,
                    ubound = ub_perc)
  
  diff <- data %>% 
    mutate(Max = max(m_perc, m_real),
           Min = min(m_perc, m_real),
           Diff = Max / Min - 1) %>% 
    arrange(desc(Diff))
  
  ## Create difference between perception and real
  data$diff <- (data$m_perc - data$m_real)/data$m_real
  data_adj = data
  data_adj
}
```


#Figure 9

```{r}
# Data adjustment: rescaling not needed
datafig_second_gen_adj = DataAdjustNoResc(datafig_second_gen) 

# Function to generate the graph
Left_10_B = function(xlb, xupb, distance_ticks){
  data = datafig_second_gen_adj
  
  p <- ggplot(data, aes(x=t)) +
    ## Plot segment joining and points
    geom_segment(aes(x=t, xend=t, y=m_real, yend=m_perc), size = 0.4, color="black") +
    geom_segment(aes(x=t, xend=t, y=lbound, yend=ubound), size = 2, color = rgb(0.7,0.2,0.1,0.3)) +
    geom_point(aes(x=t, y=m_real_2, colour= 'Act. 1 & 2 Gen.', shape = 'Act. 1 & 2 Gen.'), size=4) +
    geom_point(aes(x=t, y=m_real, colour='Act. 1 Gen.', shape = 'Act. 1 Gen.'), size=4) + 
    geom_point(aes(x=t, y=m_perc, colour='Perceived (mean)', shape = 'Perceived (mean)'), size=3) +
    coord_flip()
  
  ## Add theme, labels, and modify scale
  myshapes <- c("my_b" = "15", "my_d" = "18")
  p1 <- p + 
    scale_y_continuous(limits = c(xlb, xupb), breaks = seq(xlb, xupb, by = distance_ticks)) +
    theme_light() +
    theme(
      ## Control grid
      panel.grid.major = element_line(linetype = 'dashed', color = 'darkgrey'),
      panel.grid.major.y = element_line(linetype = 'solid', color = 'darkgrey'),
      
      ## Control legend
      legend.position = "bottom",
      legend.box = "horizontal",
      legend.justification = c(0.5,0),
      legend.title = element_blank(),
      text = element_text(family = "LM Roman 10", color='black', size=11),
      axis.text = element_text(colour = 'black'),
      axis.text.x = element_text(size=9),
      axis.text.y = element_text(size=9),
      axis.title.x = element_text(size = 9, margin = margin(t=15)),
      axis.ticks.x = element_blank()
    ) +
    scale_colour_manual(name = "", labels = c( "Act. 1 & 2 Gen.", 'Act. 1 Gen.','Perceived (mean)'), 
                        values = c("Act. 1 & 2 Gen." = "#1A476F", 'Act. 1 Gen.' = "#0080FF", 
                                   'Perceived (mean)' = rgb(0.7,0.2,0.1,1))) +
    scale_shape_manual(name = "", labels = c("Act. 1 & 2 Gen.",'Act. 1 Gen.',  'Perceived (mean)'), 
                       values = c( "Act. 1 & 2 Gen." = 20, 'Act. 1 Gen.' = 18, 'Perceived (mean)' = 15)) +
    xlab("") +
    ylab("Share of Immigrants") +
    guides(col = guide_legend(nrow=2,byrow=TRUE))
  p1}
```

```{r}
# Generate Figure
plot_grid(Left_10_B(0, 40, 5), labels=NULL, ncol=2, align='h', axis='b')

# Export
FigureExporter(plot_grid(Left_10_B(0, 40, 5), labels=NULL, ncol=2, align='h', axis='b'), "Figure_9.png")

```