In databrew/sfi:

# Packages
library(sfi)
library(webshot)
library(reshape2)
library(ggplot2)
library(dplyr)
library(plotly)
library(ggiraph)
library(scales)
library(tidyverse)
library(knitr)
library(Hmisc)
library(RColorBrewer)
library(extrafont)
library(kableExtra)
library(grid)

# webshot::install_phantomjs()

loadfonts()
## Global options
options(max.print="75")
opts_chunk$set(echo=FALSE,
            cache=FALSE,
              prompt=FALSE,


              tidy=TRUE,
              comment=NA,
              message=FALSE,
              warning=FALSE,
              dpi = 300,
              # dev = "cairo_pdf",
            fig.width = 7.25,
            fig.height = 4,
              dev = c("png", "cairo_pdf"),
              fig.pos="!h",
              fig.path = 'figures/')
opts_knit$set(width=75)
options(xtable.comment = FALSE)

\newpage

This markdown is for Livermore, Ashley, Riddell, Carlson, Rockmore figures.

Livermore, Ashley, Riddell, Carlson, Rockmore 1 (version 1)

# no scientific notation
  options(scipen = '999')

  # get data 
  data <- all_data$livermore$f1

  # version 11
  g1 <- ggplot(data, 
               aes(x = median_year, 
                   y = friendscr)) +
    geom_smooth(method = 'lm', 
                linetype = 0,
                se = TRUE,
                fill = '#373737',
                alpha = 0.4) +
    geom_point(size = 1.5, 
               alpha = 0.8,
               pch = 16,
               color = 'black') +
    labs(x = '',
         y = 'Friendliness score',
         title = '',
         caption = 'Figure 1: Sentiment Score by Authoring Justice') +
    scale_y_continuous(labels = percent, 
                       limits = c(-0.018, 0.004),
                       breaks=c(-0.018,-0.016,-0.014,-0.012,-0.01, -0.008, 
                                -0.006, -0.004, -0.002, 0, 0.002, 0.004)) +
    theme_sfi(lp = 'none',
              y_axis_title_style = 'bold',
              title_style = 'bold') +
    geom_text(data=subset(data, justice == 'alito'),
              aes(median_year, 
                  friendscr, 
                  label=paste0('Justice ', Hmisc::capitalize(justice))), 
              vjust = 1.5, 
              hjust = 1)  +
    theme(axis.text=element_text(size = 10, hjust = 1))

  g1

Livermore, Ashley, Riddell, Carlson, Rockmore 1 (version 2)

# no scientific notation
  options(scipen = '999')

  # get data 
  data <- all_data$livermore$f1

  # version 11
  g1 <- ggplot(data, 
               aes(x = median_year, 
                   y = friendscr)) +
    geom_smooth(method = 'lm', 
                linetype = 0,
                se = TRUE,
                fill = '#373737',
                alpha = 0.5) +
    geom_point(size = 1, 
               alpha = 1,
               pch = 16,
               color = 'black') +
    labs(x = '',
         y = 'Friendliness score',
         title = '',
         caption = 'Figure 1: Sentiment Score by Authoring Justice') +
    scale_y_continuous(labels = percent, 
                       limits = c(-0.018, 0.004),
                       breaks=c(-0.018,-0.016,-0.014,-0.012,-0.01, -0.008, 
                                -0.006, -0.004, -0.002, 0, 0.002, 0.004)) +
    theme_sfi(lp = 'none',
              y_axis_title_style = 'bold',
              title_style = 'bold') +
    geom_text(data=subset(data, justice == 'alito'),
              aes(median_year, 
                  friendscr, 
                  label=paste0('Justice ', Hmisc::capitalize(justice))), 
              vjust = 1.5, 
              hjust = 1)  +
    theme(axis.text=element_text(size = 10, hjust = 1))

  g1

Livermore, Ashley, Riddell, Carlson, Rockmore 2 (version 1)

 # no scientific notation
  options(scipen = '999')

  # get data
  data <- all_data$livermore$f2

  # melt data by x1
  data <- melt(data, id.vars = 'x1')

  # livermore 3 
  g1 <- ggplot(data,
               aes(variable, value)) +
    geom_jitter(width = 0.2,
                alpha = 0.3,
                size = 1) +
    geom_violin(fill = 'grey',
                alpha = 0.7,
                color = adjustcolor('grey', alpha.f = 0.7)) +
    labs(x = '',
         y = 'Accuracy',
         title = 'Supreme Court vs Appellate court',
         subtitle = 'Figure 2: Prediction of Supreme Court Opinions.',
         caption = 'Mirrored density plot') +
    theme_sfi(lp = 'none',
              y_axis_title_style = 'bold',
              x_axis_title_style = 'bold',
              title_style = 'bold') + 
    theme(axis.text.x=element_text(angle=45, hjust=1))  +
    theme(axis.text=element_text(size = 10, hjust = 1))
  g1

Livermore, Ashley, Riddell, Carlson, Rockmore 2 (version 2)

 # no scientific notation
  options(scipen = '999')

  # get data
  data <- all_data$livermore$f2

  # melt data by x1
  data <- melt(data, id.vars = 'x1')

  # livermore 3 
  g1 <- ggplot(data,
               aes(variable, value)) +
    geom_violin(fill = 'grey', 
                color = 'grey',
                width = 1.2) +
     geom_jitter(width = 0.1,
                alpha = 0.3,
                size = 1) +
    labs(x = '',
         y = 'Accuracy',
         title = 'Supreme Court vs Appellate court',
         subtitle = 'Figure 2: Prediction of Supreme Court Opinions.',
         caption = 'Mirrored density plot') +
    theme_sfi(lp = 'none',
              y_axis_title_style = 'bold',
              x_axis_title_style = 'bold',
              title_style = 'bold') + 
    theme(axis.text.x=element_text(angle=45, hjust=1))  +
    theme(axis.text=element_text(size = 10, hjust = 1))
  g1

Livermore, Ashley, Riddell, Carlson, Rockmore 3 (version 1)

   # no scientific notation
  options(scipen = '999')

  # get data
  data <- all_data$livermore$f3

  # melt data by x1
  data <- melt(data, id.vars = 'x1')

  # livermore 3
  g1 <- ggplot(data,
               aes(variable, value)) +
    geom_jitter(width = 0.25,
                alpha = 0.2,
                size = 1) +
    geom_violin(fill = 'grey',
                color = 'grey') +
    labs(x = '',
         y = 'Accuracy',
         title = 'Supreme Court vs Appellate court (cert. granted)',
         subtitle = 'Figure 3a. Prediction of Supreme Court and Appellate Court Opinions.',
         caption = 'Mirrored density plot') +
    theme_sfi(lp = 'none',
              y_axis_title_style = 'bold',
              x_axis_title_style = 'bold',
              title_style = 'bold') + 
    theme(axis.text.x=element_text(angle=45, hjust=1)) +
    theme(axis.text=element_text(size = 10, hjust = 1))

  g1

Livermore, Ashley, Riddell, Carlson, Rockmore 3 (version 2)

 # no scientific notation
  options(scipen = '999')

  # get data
  data <- all_data$livermore$f3

  # melt data by x1
  data <- melt(data, id.vars = 'x1')

  # livermore 3
  g1 <- ggplot(data,
               aes(variable, value)) +
     geom_violin(fill = 'grey', 
                width = 1.2,
                color = 'grey') +
     geom_jitter(width = 0.1,
                alpha = 0.3,
                size = 1) +
    labs(x = '',
         y = 'Accuracy',
         title = 'Supreme Court vs Appellate court (cert. granted)',
         subtitle = 'Figure 3a. Prediction of Supreme Court and Appellate Court Opinions.',
         caption = 'Mirrored density plot') +
    theme_sfi(lp = 'none',
              y_axis_title_style = 'bold',
              x_axis_title_style = 'bold',
              title_style = 'bold') + 
    theme(axis.text.x=element_text(angle=45, hjust=1)) +
    theme(axis.text=element_text(size = 10, hjust = 1))

  g1

Livermore, Ashley, Riddell, Carlson, Rockmore 4 (version 1)

  # no scientific notation
  options(scipen = '999')

  # get data
  data <- all_data$livermore$f4

  # melt data by x1
  data <- melt(data, id.vars = 'x1')


  # livermore 4
  g1 <- ggplot(data,
               aes(variable, value)) +
    geom_jitter(width = 0.3,
                alpha = 0.2,
                size = 1) +
    geom_violin(fill = 'grey',
                color = 'grey') +
    labs(x = '',
         y = 'Accuracy',
         title = 'Appellate court (cert. grant) vs Appellate court',
         subtitle = 'Figure 3b. Prediction of Supreme Court and Appellate Court Opinions.',
         caption = 'Mirrored density plot') +
    theme_sfi(lp = 'none',
              y_axis_title_style = 'bold',
              x_axis_title_style = 'bold',
              title_style = 'bold') + 
    theme(axis.text.x=element_text(angle=45, hjust=1)) +
    theme(axis.text=element_text(size = 10, hjust = 1))

  g1

Livermore, Ashley, Riddell, Carlson, Rockmore 4 (version 2)

 # no scientific notation
  options(scipen = '999')

  # get data
  data <- all_data$livermore$f4

  # melt data by x1
  data <- melt(data, id.vars = 'x1')


  # livermore 4
  g1 <- ggplot(data,
               aes(variable, value)) +
    geom_violin(fill = 'grey',
                color = 'grey',
                width = 1) +
    geom_jitter(width = 0.2,
                alpha = 0.4,
                size = 1) +
    labs(x = '',
         y = 'Accuracy',
         title = 'Appellate court (cert. grant) vs Appellate court',
         subtitle = 'Figure 3b. Prediction of Supreme Court and Appellate Court Opinions.',
         caption = 'Mirrored density plot') +
    theme_sfi(lp = 'none',
              y_axis_title_style = 'bold',
              x_axis_title_style = 'bold',
              title_style = 'bold') + 
    theme(axis.text.x=element_text(angle=45, hjust=1)) +
    theme(axis.text=element_text(size = 10, hjust = 1))

  g1