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)
library(googleVis)


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)

Doughnut chart

\newpage

# Get data
data <- all_data$alexander$f4

# Flag the groups
data$group <-
  ifelse(data$key %in% 
           c('Exemption',
             'Color',
             'Race',
             'National origin',
             'Religion',
             'Sex',
             'Retaliation'), 
         'Claim type',
         'National origin')


data$value <- data$value * 100

# subset to claim type 
dat_claim <- data[data$group == 'Claim type',]
# get a color vector
colors  <- make_colors(length(unique(dat_claim$key)), bw = TRUE)

# sort data
dat_claim <- dat_claim[order(dat_claim$value, decreasing = TRUE),]

##------- USING PLOTLY
# remove dark color
# get font object
inside_f <- list(
  family = "CMU Bright",
  size = 45,
  color = 'white'
)

outside_f <- list(
  family = "CMU Bright",
  size = 45,
  color = colors 
)

# text font 
t <- list(
  family = "CMU Bright",
  size = 45,
  color = '#353535'
)


# plot
plot_ly(dat_claim,
        labels = ~key, 
        values = ~round(value),
        type ='pie',
        hole = 0.4,
        textposition = 'outside',
        textinfo = 'percent+label',
        rotation = 90,
        outsidetextfont = outside_f,
        marker = list(colors = colors))  %>%
  config(displayModeBar = F) %>%

  layout(title ='' ,
         font = t,
         showlegend = F,
         annotations = list(
           showarrow = FALSE,
           text = paste0('Claim type', '\n', 'Version 8'),
           font = t), 
         xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
         yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))

\pagebreak

colors <- c('#0D0D0D', '#323232','#595959', '#7F7F7F', '#A5A5A5', '#CCCCCC','#F2F2F2')
# Start the plot
p <- ggplot(dat_claim, aes(key , value, fill = key)) +       
    geom_bar(stat="identity", 
           color = 'grey') +
  scale_fill_manual(name = '',
                    values = colors) +
  ylim(-100,120) +
  theme(
    axis.text = element_blank(),
    axis.title = element_blank(),
    panel.grid = element_blank(),
    plot.margin = unit(rep(-1, 4), "cm")) +
    coord_polar(start = 0) +
  annotate(geom = 'text', 
           x = 6, 
           y = 60, 
           label = paste0('38%', '\n', 'Retaliation'),
           angle = 75) +
  annotate(geom = 'text', 
           x = 7, 
           y = 50, 
           label = paste0('26%', '\n', 'Sex'),
           angle = 30) +
  annotate(geom = 'text', 
           x = 4, 
           y = 45, 
           label = paste0('24%', '\n', 'Race'),
           angle = 180) +
  annotate(geom = 'text', 
           x = 3, 
           y = 35, 
           label = paste0('5%', '\n', 'Exemption'),
           angle = 230) +
  annotate(geom = 'text', 
           x = 2, 
           y = 30,
           label = paste0('5%', '\n', 'National origin'),
           angle = 277) +
  annotate(geom = 'text', 
           x = 5, 
           y = 30, 
           label = paste0('2%', '\n', 'Religion'),
           angle = 130) +
  annotate(geom = 'text', 
           x = 1, 
           y = 23, 
           label = paste0('0%', '\n', 'Color'),
           angle = 340) 

p

\pagebreak

# plot the 1955 to 2014 data

# Get data
data <- all_data$frankenreiter$f5_1

cols <- make_colors(length(unique(data$year)), bw = TRUE)
data$year <- as.numeric(data$year)

ggplot(data,
       aes(x = coord2,
           y = coord1,
           fill = year)) +
  geom_point(size = 4,
             pch = 21,
             alpha = 0.7)  +
  ggrepel::geom_text_repel(data=subset(data, year ==  1960 | year == 1970 | year == 1980 | year == 1990 | year == 2000 | year==  2010),
                           aes(coord2, coord1, label=year), vjust = -1.5, hjust = 2.2) +
  theme_sfi() +
  labs(x = 'Coordinate 2',
       y = 'Coordinate 1',
       title = 'Version 18') +
  scale_fill_gradient(name = '', low = "#0D0D0D", high = "#F2F2F2") +
  theme(legend.position = 'bottom',
        legend.key.size = unit(0.5, 'inch')) 

#

\pagebreak

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

# get data 
data <- all_data$livermore$f1

# version 11
ggplot(data, 
       aes(x = median_year, 
           y = friendscr)) +
  geom_smooth(method = 'lm', 
              linetype = 0,
              se = TRUE,
              fill = '#373737',
              alpha = 0.4) +
  geom_point(size = 4, 
             alpha = 0.8,
             pch = 16,
             color = 'black') +
  labs(x = '',
       y = 'Friendliness score',
       title = 'Version 11',
       caption = 'Standard errors estimated with a linear regression') +
  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() +
  geom_text(data=subset(data, justice == 'alito'),
            aes(median_year, 
                friendscr, 
                label=paste0('Justice ', Hmisc::capitalize(justice))), 
            vjust = 1.5, 
            hjust = 1) 

\pagebreak

# Get data
data <- all_data$feldman$f1 

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

# Version 16
ggplot(data, 
       aes(x = federal, 
           y = clarity_score)) +
  ylim(c(-3, 11)) +
  stat_ydensity(geom="segment", 
                adjust = 20,
                scale = 'area',
                aes(xend=..x..+..scaled../4, 
                    yend=..y.., 
                    alpha=(..scaled../3)^2), 
                size=3, 
                color = '#838383',
                trim=TRUE) +
  stat_ydensity(geom="segment", 
                adjust = 20,
                scale = 'area',
                aes(xend=..x..-..scaled../4, 
                    yend=..y.., 
                    alpha=(..scaled../3)^2), 
                size=3, 
                linetype = 1,
                color = '#838383',

                trim=TRUE) +
  labs(x = '',
       y = 'Clarity Score',
       title = 'Version 16, spherical cloud represents distrubition') +
  scale_alpha_continuous(range= c(-0, .5)) +
  geom_jitter(size = 2,
              color = 'black',
              width = 0.25,
              alpha = 0.25,
              pch = 16) +
  theme_sfi(lp = 'none') 

databrew/sfi documentation built on May 29, 2019, 1:52 a.m.