In databrew/sfi:

# Packages
library(sfi)
library(webshot)
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$set(echo=FALSE,
            cache=FALSE,
              prompt=FALSE,
              tidy=TRUE,
              comment=NA,
              message=FALSE,
              warning=FALSE,
              dpi = 300,
              # dev = "cairo_pdf",
              dev = c("png", "cairo_pdf"),
              fig.pos="!h",
              fig.path = 'figures/')
opts_knit$set(width=75)
options(xtable.comment = FALSE)

\newpage

This markdown is for Feldman figures.

Feldman 1 (version 1)

# Get data
  data <- all_data$feldman$f1 

  # recode federal
  data$federal <- ifelse(data$federal == '1', 'Federal', 'State')


  #Version  
  g1<- ggplot(data, 
         aes(x = federal, 
             y = clarity_score)) +
    geom_violin(fill = 'darkgrey',
                color = 'darkgrey',
                alpha = 1,
                trim = TRUE,
                scale = 'width') +
     geom_jitter(size = 1,
                color = 'black',
                width = 0.35,
                alpha = 0.4,
                pch = 16) +
    labs(x = '',
         y = 'Clarity Score',
         title = 'Figure 1. Federal and State Clarity Score Distribution',
         caption = paste0('The violin distribution plot represents a mirrored density.',
                          '\n', 'Data points randomly "jittered" on the X axis.')) +
    scale_alpha_continuous(range= c(-0, .5)) +
      theme_sfi(lp = 'none',
                y_axis_title_style = 'bold',
                x_axis_title_style = 'bold',
                title_style = 'bold') +
    theme(axis.text=element_text(size = 10, hjust = 1),
          plot.title = element_text(size = 12, face = "bold"))

  g1

Feldman 1 (version 2)

  # Version 2
  g2<- ggplot(data, 
         aes(x = federal, 
             y = clarity_score)) +
     geom_jitter(size = 2,
                color = 'black',
                width = 0.3,
                alpha = 0.5,
                pch = 16) +
  geom_violin(fill = 'darkgrey',
                color = 'darkgrey',
                alpha = 1) +
    labs(x = '',
         y = 'Clarity Score',
         title = 'Figure 1. Federal and State Clarity Score Distribution',
         caption = paste0('The violin distribution plot represents a mirrored density.',
                          '\n', 'Data points randomly "jittered" on the X axis.')) +
    scale_alpha_continuous(range= c(-0, .5)) +
      theme_sfi(lp = 'none',
                y_axis_title_style = 'bold',
                x_axis_title_style = 'bold',
                title_style = 'bold') +
    theme(axis.text=element_text(size = 10, hjust = 1),
          plot.title = element_text(size = 12, face = "bold"))

  g2

Feldman 2 (version 1)

# Get data
  data <- all_data$feldman$f2 

  # recode federal
  data$federal <- ifelse(data$federal == '1', 'Federal', 'State')


  #Version  
  g3<- ggplot(data, 
         aes(x = federal, 
             y = words)) +
    geom_violin(fill = 'darkgrey',
                color = 'darkgrey',
                alpha = 1,
                trim = TRUE,
                scale = 'width') +
     geom_jitter(size = 1,
                color = 'black',
                width = 0.35,
                alpha = 0.4,
                pch = 16) +
    labs(x = '',
         y = 'Words',
         title = 'Figure 2. Federal and State Court Opinion Word Length',
         caption = paste0('The violin distribution plot represents a mirrored density.',
                          '\n', 'Data points randomly "jittered" on the X axis.', '\n',
                          'Note: 25 opinions over 20,000 words were removed from plot.')) +
      theme_sfi(lp = 'none',
                y_axis_title_style = 'bold',
                x_axis_title_style = 'bold',
                title_style = 'bold')  +
    theme(axis.text=element_text(size = 10, hjust = 1),
          plot.title = element_text(size = 12, face = "bold"))

  g3

Feldman 2 (version 2)

# Get data
  data <- all_data$feldman$f2 

  # recode federal
  data$federal <- ifelse(data$federal == '1', 'Federal', 'State')


  #Version  
  g4<- ggplot(data, 
         aes(x = federal, 
             y = words)) +
     geom_jitter(size = 1.5,
                color = 'black',
                width = 0.35,
                alpha = 0.4,
                pch = 16) +
    geom_violin(fill = 'darkgrey',
                color = adjustcolor('darkgrey', alpha.f = 0.3),
                alpha = 0.5,
                trim = TRUE,
                scale = 'width') +
    labs(x = '',
         y = 'Words',
         title = 'Figure 2. Federal and State Court Opinion Word Length',
         caption = paste0('The violin distribution plot represents a mirrored density.',
                          '\n', 'Data points randomly "jittered" on the X axis.', '\n',
                          'Note: 25 opinions over 20,000 words were removed from plot.')) +
      theme_sfi(lp = 'none',
                y_axis_title_style = 'bold',
                x_axis_title_style = 'bold',
                title_style = 'bold')  +
    theme(axis.text=element_text(size = 10, hjust = 1),
          plot.title = element_text(size = 12, face = "bold"))

  g4