inst/rmd/old_scripts/plot_examples.R
In databrew/sfi:
library(ggrepel)
library(sfi)
library(ggplot2)
library(dplyr)
library(plotly)
library(ggiraph)
library(ggforce)
library(tidyverse)
library(googleVis)
library(scales)
#####################################################################################################
# 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')
# Get percentage
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 = 25,
color = 'white'
)
outside_f <- list(
family = "CMU Bright",
size = 20,
color = colors
)
# text font
t <- list(
family = "CMU Bright",
size = 25,
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))
##------- USING ggvis
# doughnut chart
gvis_hole <- gvisPieChart(dat_claim,
labelvar = 'key',
numvar = 'value',
options = list(title="",
fontName ='Computer Modern',
slices = 1,
pieSliceText = 'none',
sliceVisibilityThreshold = 0,
pieHole = 0.5,
chartArea = "{left:200, top:100, width:\"100%\",height:\"80%\"}",
colors = "['#0D0D0D', '#323232','#595959', '#7F7F7F', '#A5A5A5', '#CCCCCC','#F2F2F2']",
pieSliceBorderColor = 'white',
legend = "{position: 'labeled'}",
width=700,
height=400))
plot(gvis_hole)
# make one that's 3d
# doughnut chart
gvis_3d <- gvisPieChart(dat_claim,
labelvar = 'key',
numvar = 'value',
options = list(title="",
fontName ='Computer Modern',
pieSliceText = 'none',
sliceVisibilityThreshold = 0,
pieHole = 0.5,
is3D = TRUE,
chartArea = "{left:200, top:100, width:\"100%\",height:\"80%\"}",
colors = "['#0D0D0D', '#323232','#595959', '#7F7F7F', '#A5A5A5', '#CCCCCC','#F2F2F2']",
legend = "{position: 'labeled'}",
width=700,
height=400))
plot(gvis_3d)
# gauge
gvis_g <- gvisGauge(dat_claim,
labelvar = "",
numvar = "",
options = list(title="",
fontName ='Computer Modern',
pieSliceText = 'none',
sliceVisibilityThreshold = 0,
chartArea = "{left:200, top:100, width:\"100%\",height:\"80%\"}",
colors = "['#0D0D0D', '#323232','#595959', '#7F7F7F', '#A5A5A5', '#CCCCCC','#F2F2F2']",
legend = "{position: 'labeled'}",
width=700,
height=400))
plot(gvis_g)
##------- USING base R
dat_claim$ymax <- cumsum(dat_claim$value)
dat_claim$ymin <- c(0, head(dat_claim$ymax, n = -1))
################################################
# basic ring plot
# colors <- c('#A2A2A2', '#3E3E3E', '#606060','#050505','#858585', '#C0C0C0','#E0E0E0')
# colors <- c('#C0C0C0','#A2A2A2','#E0E0E0','#858585', '#606060','#050505','#3E3E3E')
colors <- c('#F2F2F2','#7F7F7F','#A5A5A5','#595959', '#CCCCCC','#0D0D0D', '#323232')
p2 <- ggplot(dat_claim, aes(fill=key,
ymax=ymax,
ymin=ymin,
xmax=3,
xmin=2)) +
geom_rect(colour= 'black', size = 0.01) +
scale_fill_manual(name = '',
values = colors) +
coord_polar(theta="y") +
annotate(geom = 'text',
x = 4,
y = 25,
label = paste0('38%', '\n', 'Retaliation')) +
annotate(geom = 'text',
x = 3.8,
y = 50,
label = paste0('26%', '\n', 'Sex')) +
annotate(geom = 'text',
x = 3.7,
y = 75,
label = paste0('24%', '\n', 'Race')) +
annotate(geom = 'text',
x = 4,
y = 89,
label = paste0('5%', '\n', 'Exemption'),
size = 2.5) +
annotate(geom = 'text',
x = 3.5,
y = 94,
label = paste0('5%', '\n', 'National origin'),
size = 2.5) +
annotate(geom = 'text',
x = 3.5,
y = 99,
label = paste0('2%', '\n', 'Religion'),
size = 2.5) +
xlim(c(0, 5)) +
theme_sfi(lp = 'none') +
theme(panel.grid=element_blank()) +
theme(axis.text=element_blank()) +
theme(axis.ticks=element_blank()) +
labs(title='')
p2
# rose chart
ggplot(data=dat_claim,aes(x=key,y=value, fill = key))+
geom_bar(stat="identity")+
coord_polar()+
scale_fill_brewer(palette='Greys') +
xlab("") +
ylab("") +
theme_sfi(lp = 'none') +
theme(panel.grid=element_blank()) +
theme(axis.text=element_blank()) +
theme(axis.ticks=element_blank()) +
labs(title='')
##$##########################################
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 = 20,
label = paste0('0%', '\n', 'Color'),
angle = 340)
p
#####################################################################################################
# 10 plots as alternatives to pie charts
#####################################################################################################
# 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')
# Get percentage
data$value <- data$value * 100
# subset to claim type
dat_claim <- data[data$group == 'Claim type',]
# candle stick plots ---------------------------------------------------
# version 1 one
ggplot(dat_claim,
aes(key, value)) +
ylim(c(0, 50)) +
geom_segment(aes(x=reorder(key, -value),
xend=key,
y=0,
yend=value),
linetype = 'dashed',
size = 0.5,
alpha = 0.5) +
geom_point(size= 25,
alpha = 1,
color = c('#000000', '#383838', '#565656', '#868686',
'#A2A2A2', '#BFBFBF', '#C2C2C2')) +
geom_text(aes(label = paste0(value, '%')),
size = 6,
color = 'white',
alpha = 0.7) +
labs(x = '',
y = 'Percent',
title = 'Version 1') +
theme_sfi()
# second one ------------------
ggplot(dat_claim,
aes(x=key,
y=value)) +
ylim(c(0, 50)) +
geom_segment(aes(x=reorder(key, -value),
xend=key,
y=0,
yend=value),
linetype = 'dashed',
size = 0.7,
alpha = 0.5) +
geom_point(size= 25,
pch = 21,
fill = '#383838',
stroke = 1,
alpha = 1,
color = 'black') +
geom_text(aes(label = paste0(value, '%')),
size = 6,
color = 'white',
alpha = 1) +
labs(x = '',
y = 'Percent',
title = 'Version 2') +
theme_sfi()
# third one ------------------
ggplot(dat_claim,
aes(x=key,
y=value)) +
ylim(c(-5, 50)) +
geom_segment(aes(x=reorder(key, -value),
xend=key,
y=0,
yend=value),
linetype = 'dashed',
size = 0.7,
alpha = 0.5) +
geom_point(size= 30,
pch = 19,
stroke = 1,
alpha = 1,
color = 'darkgrey') +
geom_text(aes(label = paste0(value, '%')),
size = 6,
color = '#323232',
alpha = 1) +
labs(x = '',
y = 'Percent',
title = 'Version 3') +
theme_sfi()
# fourth one ------------------ size of points based on value
ggplot(dat_claim,
aes(x=key,
y=value)) +
ylim(c(-5, 50)) +
geom_segment(aes(x=reorder(key, -value),
xend=key,
y=0,
yend=value),
linetype = 'dashed',
size = 0.7,
alpha = 0.5) +
geom_point(aes(size = value),
pch = 19,
stroke = 1,
alpha = 1,
color = '#505050') +
geom_text(aes(label = paste0(value, '%'),
color = reorder(key, -value)),
size = 4,
alpha = 1) +
scale_size_area(name = '',
max_size = 30) +
scale_color_manual(name = '',
values= c('white', 'white', 'white', 'white','white','white',' black')) +
labs(x = '',
y = 'Percent',
title = 'Version 4') +
theme_sfi(lp = 'none')
# fifth one all on one line ------------------
ggplot(dat_claim,
aes(x=group,
y=value)) +
ylim(c(-5, 50)) +
geom_segment(aes(x=group,
xend=group,
y=0,
yend=value),
linetype = 1,
size = 0.3,
alpha = 1) +
geom_point(aes(size = value),
pch = 21,
fill = 'darkgrey',
stroke = 1,
alpha = 1,
color = 'black') +
annotate(geom = 'text',
label = paste0('Color', '\n', '0%'),
x = 1.1,
y = 0) +
annotate(geom = 'text',
label = paste0('Religion', '\n', '2%'),
x = .88,
y = 2) +
annotate(geom = 'text',
label = paste0('National origin', '\n', '5%'),
x = 1.1,
y = 7) +
annotate(geom = 'text',
label = paste0('Exemption', '\n', '5%'),
x = .88,
y = 7) +
annotate(geom = 'text',
label = paste0('Race', '\n', '24%'),
x = 1.115,
y = 24) +
annotate(geom = 'text',
label = paste0('Sex', '\n', '26%'),
x = .88,
y = 26) +
annotate(geom = 'text',
label = paste0('Retaliation', '\n', '38%'),
x = 1,
y = 46) +
scale_size_area(name = '',
max_size = 30) +
labs(x = '',
y = 'Percent',
title = 'Version 5') +
theme_sfi(lp = 'none')
######--------------------------------------------------------
# PLOT 1
# get a color vector
colors <- make_colors(length(unique(dat_claim$key)), bw = TRUE)
colors <- c("#595959", "#595959", "#595959", "#595959", "#595959", "#595959", "#595959")
# remove dark color
# get font object
inside_f <- list(
family = "CMU Bright",
size = 25,
color = 'white'
)
outside_f <- list(
family = "CMU Bright",
size = 20,
color = colors
)
# text font
t <- list(
family = "CMU Bright",
size = 25,
color = '#353535'
)
# plot
plot_ly(dat_claim,
labels = ~key,
values = ~value,
type ='pie',
hole = 0.3,
textposition = 'outside',
textinfo = 'percent',
outsidetextfont = outside_f,
marker = list(colors = colors,
line = list(color = '#FFFFFF', width = 2))) %>%
add_trace(dat_claim,
labels = ~key,
values = ~value,
type ='pie',
hole = 0.3,
textposition = 'inside',
textinfo = 'label',
insidetextfont = inside_f,
marker = list(colors = colors,
line = list(color = '#FFFFFF', width = 1))) %>%
config(displayModeBar = F) %>%
layout(title = '' ,
font = list(
family = "CMU Bright",
color = '#353535'),
showlegend = F,
annotations = list(
showarrow = FALSE,
text = paste0('Claim type', '\n', 'Version 6'),
font = t),
xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
######--------------------------------------------------------
# PLOT 2
# get a color vector
colors <- c("#989898", "#989898", "#989898", "#989898", "#989898", "#989898", "#989898")
# remove dark color
# get font object
inside_f <- list(
family = "CMU Bright",
size = 25,
color = 'black'
)
# text font
t <- list(
family = "CMU Bright",
size = 25,
color = '#353535'
)
# plot
plot_ly(dat_claim,
labels = ~key,
values = ~value,
type ='pie',
hole = 0.3,
textposition = 'inside',
textinfo = 'percent+label',
outsidetextfont = outside_f,
marker = list(colors = colors,
line = list(color = '#FFFFFF', width = 2))) %>%
config(displayModeBar = F) %>%
layout(title ='' ,
font = t,
showlegend = F,
annotations = list(
showarrow = FALSE,
text = paste0('Claim type', '\n', 'Version 7'),
font = t),
xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
######--------------------------------------------------------
# PLOT 3
# 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),]
# remove dark color
# get font object
inside_f <- list(
family = "CMU Bright",
size = 25,
color = 'white'
)
outside_f <- list(
family = "CMU Bright",
size = 20,
color = colors
)
# text font
t <- list(
family = "CMU Bright",
size = 30,
color = '#353535'
)
# plot
plot_ly(dat_claim,
labels = ~key,
values = ~value,
type ='pie',
hole = 0.6,
textposition = 'outside',
textinfo = 'percent',
outsidetextfont = outside_f,
marker = list(colors = colors,
line = list(color = '#FFFFFF', width = 3))) %>%
add_trace(dat_claim,
labels = ~key,
values = ~value,
type ='pie',
hole = 0.6,
textposition = 'inside',
textinfo = 'label',
insidetextfont = inside_f,
marker = list(colors = colors,
line = list(color = '#FFFFFF', width = 3))) %>%
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))
####### -------------------- make a nice barplot
# relevel key
dat_claim$key <- as.factor(dat_claim$key)
dat_claim$key <- factor(dat_claim$key, levels = c('Retaliation', 'Sex', 'Race',
'Exemption', 'National origin',
'Religion', 'Color'))
colors <- c('#000000', '#383838', '#565656', '#868686',
'#A2A2A2', '#C2C2C2', '#EAE8E8')
ggplot(dat_claim,
aes(key, value,
fill = key)) +
geom_bar(stat= 'identity',
color = 'grey',
alpha = 0.7) +
ylim(c(0, 40)) +
xlab('Claim type') +
ylab('Percent') +
ggtitle('Version 9') +
geom_text(aes(label = paste0(value, ' %'), vjust = -0.6), alpha = 0.7) +
scale_fill_manual(name = '',
values = c('#000000', '#383838', '#565656', '#868686',
'#A2A2A2', '#C2C2C2', '#EAE8E8')) +
theme_sfi(lp = 'none')
####### -------------------- make a nice barplot
# relevel key
dat_claim$key <- as.factor(dat_claim$key)
dat_claim$key <- factor(dat_claim$key, levels = c('Retaliation', 'Sex', 'Race',
'Exemption', 'National origin',
'Religion', 'Color'))
colors <- c('#000000', '#383838', '#565656', '#868686',
'#A2A2A2', '#C2C2C2', '#EAE8E8')
ggplot(dat_claim,
aes(key, value,
fill = key)) +
geom_bar(stat= 'identity',
color = 'grey',
alpha = 0.7) +
ylim(c(0, 40)) +
xlab('Claim type') +
ylab('Percent') +
ggtitle('Version 10') +
coord_flip() +
geom_text(aes(label = paste0(value, ' %'), hjust = -0.3), alpha = 0.7) +
scale_fill_manual(name = '',
values = c('#000000', '#383838', '#565656', '#868686',
'#A2A2A2', '#C2C2C2', '#EAE8E8')) +
theme_sfi(lp = 'none')
#####################################################################################################
# Create a line chart (points) using specified theme
#####################################################################################################
# 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)
# version 1
ggplot(data,
aes(x = median_year,
y = friendscr)) +
geom_smooth(method = 'lm',
linetype = 1,
size = 5,
se = FALSE,
color = 'grey',
alpha = 0.4) +
geom_point(size = 4,
alpha = 0.8,
pch = 16,
color = 'black') +
labs(x = '',
y = 'Friendliness score',
title = 'Version 12',
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)
# version 3
ggplot(data,
aes(x = median_year,
y = friendscr)) +
geom_smooth(method = 'lm',
linetype = 0,
se = TRUE,
fill = '#373737',
alpha = 0.3) +
geom_point(size = 4,
aes(alpha = -friendscr),
pch = 16,
color = 'black') +
scale_alpha(name = '',
range = c(0.4, 1)) +
labs(x = '',
y = 'Friendliness score',
title = 'Version 13',
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(lp = 'none') +
geom_text(data=subset(data, justice == 'alito'),
aes(median_year,
friendscr,
label=paste0('Justice ', Hmisc::capitalize(justice))),
vjust = 1.5,
hjust = 1)
#####################################################################################################
# Create distributions using specified theme
#####################################################################################################
# Version 14 - this is the original, that they liked, but with slightly larger points, as they suggested.
# Get data
data <- all_data$feldman$f1
# recode federal
data$federal <- ifelse(data$federal == '1', 'Federal', 'State')
ggplot(data,
aes(x = federal,
y = clarity_score)) +
ylim(c(-3, 11)) +
stat_ydensity(geom="segment",
adjust = 20,
scale = 'area',
aes(xend=..x..+..scaled../3.5,
yend=..y..,
alpha=(..scaled../3)^5),
size=3,
color = 'darkgrey',
trim=TRUE) +
stat_ydensity(geom="segment",
adjust = 20,
scale = 'area',
aes(xend=..x..-..scaled../3.5,
yend=..y..,
alpha=(..scaled../3)^5),
size=3,
linetype = 1,
color = 'darkgrey',
trim=TRUE) +
labs(x = '',
y = 'Clarity Score',
title = 'Version 14, spherical cloud represents distrubition') +
scale_alpha_continuous(range= c(-0, .5)) +
geom_jitter(size = 1,
color = 'black',
width = 0.3,
alpha = 0.3,
pch = 16) +
theme_sfi(lp = 'none')
# Version 15
ggplot(data,
aes(x = federal,
y = clarity_score)) +
ylim(c(-3, 11)) +
stat_ydensity(geom="segment",
adjust = 20,
scale = 'area',
aes(xend=..x..+..scaled../5,
yend=..y..,
alpha=(..scaled../3)^1),
size=3,
color = 'darkgrey',
trim=TRUE) +
stat_ydensity(geom="segment",
adjust = 20,
scale = 'area',
aes(xend=..x..-..scaled../5,
yend=..y..,
alpha=(..scaled../3)^1),
size=3,
linetype = 1,
color = 'darkgrey',
trim=TRUE) +
labs(x = '',
y = 'Clarity Score',
title = 'Version 15, spherical cloud represents distrubition') +
scale_alpha_continuous(range= c(-0, .5)) +
geom_jitter(size = 1.5,
color = 'black',
width = 0.2,
alpha = 0.3,
pch = 16) +
theme_sfi(lp = 'none')
# 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')
#####################################################################################################
# make plot for frankenreiter 5 so that each point colored based on time, and each decade is labeled
#####################################################################################################
# Get data
data <- all_data$frankenreiter$f5_1
cols <- make_colors(length(unique(data$year)), bw = TRUE)
# plot the 1955 to 2014 data
ggplot(data,
aes(x = coord2,
y = coord1,
fill = year)) +
geom_point(size = 4,
pch = 21,
alpha = 0.7) +
theme_sfi() +
annotate(geom = 'text',
label = '1955',
x = -0.0755,
y = -0.026) +
annotate("text",
x = -0.0755,
y = -0.023,
label = sprintf('\u2191')) +
annotate(geom = 'text',
label = '1960',
x = -0.043,
y = -0.007) +
annotate(geom = 'text',
label = '1960',
x = -0.043,
y = -0.007) +
annotate(geom = 'text',
label = '1970',
x = -0.041,
y = 0.0084) +
annotate(geom = 'text',
label = '1980',
x = 0.0129,
y = 0.0039) +
labs(x = 'Coordinate 2',
y = 'Coordinate 1',
title = 'Version 17') +
scale_fill_manual(name = '',
values = sort(cols, decreasing = TRUE)) +
theme(legend.position = 'none')
# plot the 1955 to 2014 data
# Get data
data <- all_data$frankenreiter$f5_1
ggplot(data,
aes(x = coord2,
y = coord1,
fill = year)) +
geom_point(size = 4,
pch = 21,
alpha = 0.7) +
ggrepel::geom_text_repel(data=subset(data, year == 1960 | year == 1970 | year == 1980 | year == 1990 | year == 2000 | year== 2010),
aes(coord2, coord1, label=year), vjust = -1.5, hjust = 2.2) +
theme_sfi() +
labs(x = 'Coordinate 2',
y = 'Coordinate 1',
title = 'Version 18') +
scale_fill_manual(name = '',
values = sort(cols)) +
theme(legend.position = 'none')
# plot the 1955 to 2014 data
cols <- make_colors(length(unique(data$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 17') +
scale_fill_gradient(name = '', low = "#0D0D0D", high = "#F2F2F2") +
theme_sfi(lp = 'bottom')
databrew/sfi documentation built on May 29, 2019, 1:52 a.m.
R Package Documentation
Browse R Packages
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library(ggrepel)
library(sfi)
library(ggplot2)
library(dplyr)
library(plotly)
library(ggiraph)
library(ggforce)
library(tidyverse)
library(googleVis)
library(scales)
#####################################################################################################
# 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')
# Get percentage
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 = 25,
color = 'white'
)
outside_f <- list(
family = "CMU Bright",
size = 20,
color = colors
)
# text font
t <- list(
family = "CMU Bright",
size = 25,
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))
##------- USING ggvis
# doughnut chart
gvis_hole <- gvisPieChart(dat_claim,
labelvar = 'key',
numvar = 'value',
options = list(title="",
fontName ='Computer Modern',
slices = 1,
pieSliceText = 'none',
sliceVisibilityThreshold = 0,
pieHole = 0.5,
chartArea = "{left:200, top:100, width:\"100%\",height:\"80%\"}",
colors = "['#0D0D0D', '#323232','#595959', '#7F7F7F', '#A5A5A5', '#CCCCCC','#F2F2F2']",
pieSliceBorderColor = 'white',
legend = "{position: 'labeled'}",
width=700,
height=400))
plot(gvis_hole)
# make one that's 3d
# doughnut chart
gvis_3d <- gvisPieChart(dat_claim,
labelvar = 'key',
numvar = 'value',
options = list(title="",
fontName ='Computer Modern',
pieSliceText = 'none',
sliceVisibilityThreshold = 0,
pieHole = 0.5,
is3D = TRUE,
chartArea = "{left:200, top:100, width:\"100%\",height:\"80%\"}",
colors = "['#0D0D0D', '#323232','#595959', '#7F7F7F', '#A5A5A5', '#CCCCCC','#F2F2F2']",
legend = "{position: 'labeled'}",
width=700,
height=400))
plot(gvis_3d)
# gauge
gvis_g <- gvisGauge(dat_claim,
labelvar = "",
numvar = "",
options = list(title="",
fontName ='Computer Modern',
pieSliceText = 'none',
sliceVisibilityThreshold = 0,
chartArea = "{left:200, top:100, width:\"100%\",height:\"80%\"}",
colors = "['#0D0D0D', '#323232','#595959', '#7F7F7F', '#A5A5A5', '#CCCCCC','#F2F2F2']",
legend = "{position: 'labeled'}",
width=700,
height=400))
plot(gvis_g)
##------- USING base R
dat_claim$ymax <- cumsum(dat_claim$value)
dat_claim$ymin <- c(0, head(dat_claim$ymax, n = -1))
################################################
# basic ring plot
# colors <- c('#A2A2A2', '#3E3E3E', '#606060','#050505','#858585', '#C0C0C0','#E0E0E0')
# colors <- c('#C0C0C0','#A2A2A2','#E0E0E0','#858585', '#606060','#050505','#3E3E3E')
colors <- c('#F2F2F2','#7F7F7F','#A5A5A5','#595959', '#CCCCCC','#0D0D0D', '#323232')
p2 <- ggplot(dat_claim, aes(fill=key,
ymax=ymax,
ymin=ymin,
xmax=3,
xmin=2)) +
geom_rect(colour= 'black', size = 0.01) +
scale_fill_manual(name = '',
values = colors) +
coord_polar(theta="y") +
annotate(geom = 'text',
x = 4,
y = 25,
label = paste0('38%', '\n', 'Retaliation')) +
annotate(geom = 'text',
x = 3.8,
y = 50,
label = paste0('26%', '\n', 'Sex')) +
annotate(geom = 'text',
x = 3.7,
y = 75,
label = paste0('24%', '\n', 'Race')) +
annotate(geom = 'text',
x = 4,
y = 89,
label = paste0('5%', '\n', 'Exemption'),
size = 2.5) +
annotate(geom = 'text',
x = 3.5,
y = 94,
label = paste0('5%', '\n', 'National origin'),
size = 2.5) +
annotate(geom = 'text',
x = 3.5,
y = 99,
label = paste0('2%', '\n', 'Religion'),
size = 2.5) +
xlim(c(0, 5)) +
theme_sfi(lp = 'none') +
theme(panel.grid=element_blank()) +
theme(axis.text=element_blank()) +
theme(axis.ticks=element_blank()) +
labs(title='')
p2
# rose chart
ggplot(data=dat_claim,aes(x=key,y=value, fill = key))+
geom_bar(stat="identity")+
coord_polar()+
scale_fill_brewer(palette='Greys') +
xlab("") +
ylab("") +
theme_sfi(lp = 'none') +
theme(panel.grid=element_blank()) +
theme(axis.text=element_blank()) +
theme(axis.ticks=element_blank()) +
labs(title='')
##$##########################################
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 = 20,
label = paste0('0%', '\n', 'Color'),
angle = 340)
p
#####################################################################################################
# 10 plots as alternatives to pie charts
#####################################################################################################
# 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')
# Get percentage
data$value <- data$value * 100
# subset to claim type
dat_claim <- data[data$group == 'Claim type',]
# candle stick plots ---------------------------------------------------
# version 1 one
ggplot(dat_claim,
aes(key, value)) +
ylim(c(0, 50)) +
geom_segment(aes(x=reorder(key, -value),
xend=key,
y=0,
yend=value),
linetype = 'dashed',
size = 0.5,
alpha = 0.5) +
geom_point(size= 25,
alpha = 1,
color = c('#000000', '#383838', '#565656', '#868686',
'#A2A2A2', '#BFBFBF', '#C2C2C2')) +
geom_text(aes(label = paste0(value, '%')),
size = 6,
color = 'white',
alpha = 0.7) +
labs(x = '',
y = 'Percent',
title = 'Version 1') +
theme_sfi()
# second one ------------------
ggplot(dat_claim,
aes(x=key,
y=value)) +
ylim(c(0, 50)) +
geom_segment(aes(x=reorder(key, -value),
xend=key,
y=0,
yend=value),
linetype = 'dashed',
size = 0.7,
alpha = 0.5) +
geom_point(size= 25,
pch = 21,
fill = '#383838',
stroke = 1,
alpha = 1,
color = 'black') +
geom_text(aes(label = paste0(value, '%')),
size = 6,
color = 'white',
alpha = 1) +
labs(x = '',
y = 'Percent',
title = 'Version 2') +
theme_sfi()
# third one ------------------
ggplot(dat_claim,
aes(x=key,
y=value)) +
ylim(c(-5, 50)) +
geom_segment(aes(x=reorder(key, -value),
xend=key,
y=0,
yend=value),
linetype = 'dashed',
size = 0.7,
alpha = 0.5) +
geom_point(size= 30,
pch = 19,
stroke = 1,
alpha = 1,
color = 'darkgrey') +
geom_text(aes(label = paste0(value, '%')),
size = 6,
color = '#323232',
alpha = 1) +
labs(x = '',
y = 'Percent',
title = 'Version 3') +
theme_sfi()
# fourth one ------------------ size of points based on value
ggplot(dat_claim,
aes(x=key,
y=value)) +
ylim(c(-5, 50)) +
geom_segment(aes(x=reorder(key, -value),
xend=key,
y=0,
yend=value),
linetype = 'dashed',
size = 0.7,
alpha = 0.5) +
geom_point(aes(size = value),
pch = 19,
stroke = 1,
alpha = 1,
color = '#505050') +
geom_text(aes(label = paste0(value, '%'),
color = reorder(key, -value)),
size = 4,
alpha = 1) +
scale_size_area(name = '',
max_size = 30) +
scale_color_manual(name = '',
values= c('white', 'white', 'white', 'white','white','white',' black')) +
labs(x = '',
y = 'Percent',
title = 'Version 4') +
theme_sfi(lp = 'none')
# fifth one all on one line ------------------
ggplot(dat_claim,
aes(x=group,
y=value)) +
ylim(c(-5, 50)) +
geom_segment(aes(x=group,
xend=group,
y=0,
yend=value),
linetype = 1,
size = 0.3,
alpha = 1) +
geom_point(aes(size = value),
pch = 21,
fill = 'darkgrey',
stroke = 1,
alpha = 1,
color = 'black') +
annotate(geom = 'text',
label = paste0('Color', '\n', '0%'),
x = 1.1,
y = 0) +
annotate(geom = 'text',
label = paste0('Religion', '\n', '2%'),
x = .88,
y = 2) +
annotate(geom = 'text',
label = paste0('National origin', '\n', '5%'),
x = 1.1,
y = 7) +
annotate(geom = 'text',
label = paste0('Exemption', '\n', '5%'),
x = .88,
y = 7) +
annotate(geom = 'text',
label = paste0('Race', '\n', '24%'),
x = 1.115,
y = 24) +
annotate(geom = 'text',
label = paste0('Sex', '\n', '26%'),
x = .88,
y = 26) +
annotate(geom = 'text',
label = paste0('Retaliation', '\n', '38%'),
x = 1,
y = 46) +
scale_size_area(name = '',
max_size = 30) +
labs(x = '',
y = 'Percent',
title = 'Version 5') +
theme_sfi(lp = 'none')
######--------------------------------------------------------
# PLOT 1
# get a color vector
colors <- make_colors(length(unique(dat_claim$key)), bw = TRUE)
colors <- c("#595959", "#595959", "#595959", "#595959", "#595959", "#595959", "#595959")
# remove dark color
# get font object
inside_f <- list(
family = "CMU Bright",
size = 25,
color = 'white'
)
outside_f <- list(
family = "CMU Bright",
size = 20,
color = colors
)
# text font
t <- list(
family = "CMU Bright",
size = 25,
color = '#353535'
)
# plot
plot_ly(dat_claim,
labels = ~key,
values = ~value,
type ='pie',
hole = 0.3,
textposition = 'outside',
textinfo = 'percent',
outsidetextfont = outside_f,
marker = list(colors = colors,
line = list(color = '#FFFFFF', width = 2))) %>%
add_trace(dat_claim,
labels = ~key,
values = ~value,
type ='pie',
hole = 0.3,
textposition = 'inside',
textinfo = 'label',
insidetextfont = inside_f,
marker = list(colors = colors,
line = list(color = '#FFFFFF', width = 1))) %>%
config(displayModeBar = F) %>%
layout(title = '' ,
font = list(
family = "CMU Bright",
color = '#353535'),
showlegend = F,
annotations = list(
showarrow = FALSE,
text = paste0('Claim type', '\n', 'Version 6'),
font = t),
xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
######--------------------------------------------------------
# PLOT 2
# get a color vector
colors <- c("#989898", "#989898", "#989898", "#989898", "#989898", "#989898", "#989898")
# remove dark color
# get font object
inside_f <- list(
family = "CMU Bright",
size = 25,
color = 'black'
)
# text font
t <- list(
family = "CMU Bright",
size = 25,
color = '#353535'
)
# plot
plot_ly(dat_claim,
labels = ~key,
values = ~value,
type ='pie',
hole = 0.3,
textposition = 'inside',
textinfo = 'percent+label',
outsidetextfont = outside_f,
marker = list(colors = colors,
line = list(color = '#FFFFFF', width = 2))) %>%
config(displayModeBar = F) %>%
layout(title ='' ,
font = t,
showlegend = F,
annotations = list(
showarrow = FALSE,
text = paste0('Claim type', '\n', 'Version 7'),
font = t),
xaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE),
yaxis = list(showgrid = FALSE, zeroline = FALSE, showticklabels = FALSE))
######--------------------------------------------------------
# PLOT 3
# 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),]
# remove dark color
# get font object
inside_f <- list(
family = "CMU Bright",
size = 25,
color = 'white'
)
outside_f <- list(
family = "CMU Bright",
size = 20,
color = colors
)
# text font
t <- list(
family = "CMU Bright",
size = 30,
color = '#353535'
)
# plot
plot_ly(dat_claim,
labels = ~key,
values = ~value,
type ='pie',
hole = 0.6,
textposition = 'outside',
textinfo = 'percent',
outsidetextfont = outside_f,
marker = list(colors = colors,
line = list(color = '#FFFFFF', width = 3))) %>%
add_trace(dat_claim,
labels = ~key,
values = ~value,
type ='pie',
hole = 0.6,
textposition = 'inside',
textinfo = 'label',
insidetextfont = inside_f,
marker = list(colors = colors,
line = list(color = '#FFFFFF', width = 3))) %>%
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))
####### -------------------- make a nice barplot
# relevel key
dat_claim$key <- as.factor(dat_claim$key)
dat_claim$key <- factor(dat_claim$key, levels = c('Retaliation', 'Sex', 'Race',
'Exemption', 'National origin',
'Religion', 'Color'))
colors <- c('#000000', '#383838', '#565656', '#868686',
'#A2A2A2', '#C2C2C2', '#EAE8E8')
ggplot(dat_claim,
aes(key, value,
fill = key)) +
geom_bar(stat= 'identity',
color = 'grey',
alpha = 0.7) +
ylim(c(0, 40)) +
xlab('Claim type') +
ylab('Percent') +
ggtitle('Version 9') +
geom_text(aes(label = paste0(value, ' %'), vjust = -0.6), alpha = 0.7) +
scale_fill_manual(name = '',
values = c('#000000', '#383838', '#565656', '#868686',
'#A2A2A2', '#C2C2C2', '#EAE8E8')) +
theme_sfi(lp = 'none')
####### -------------------- make a nice barplot
# relevel key
dat_claim$key <- as.factor(dat_claim$key)
dat_claim$key <- factor(dat_claim$key, levels = c('Retaliation', 'Sex', 'Race',
'Exemption', 'National origin',
'Religion', 'Color'))
colors <- c('#000000', '#383838', '#565656', '#868686',
'#A2A2A2', '#C2C2C2', '#EAE8E8')
ggplot(dat_claim,
aes(key, value,
fill = key)) +
geom_bar(stat= 'identity',
color = 'grey',
alpha = 0.7) +
ylim(c(0, 40)) +
xlab('Claim type') +
ylab('Percent') +
ggtitle('Version 10') +
coord_flip() +
geom_text(aes(label = paste0(value, ' %'), hjust = -0.3), alpha = 0.7) +
scale_fill_manual(name = '',
values = c('#000000', '#383838', '#565656', '#868686',
'#A2A2A2', '#C2C2C2', '#EAE8E8')) +
theme_sfi(lp = 'none')
#####################################################################################################
# Create a line chart (points) using specified theme
#####################################################################################################
# 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)
# version 1
ggplot(data,
aes(x = median_year,
y = friendscr)) +
geom_smooth(method = 'lm',
linetype = 1,
size = 5,
se = FALSE,
color = 'grey',
alpha = 0.4) +
geom_point(size = 4,
alpha = 0.8,
pch = 16,
color = 'black') +
labs(x = '',
y = 'Friendliness score',
title = 'Version 12',
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)
# version 3
ggplot(data,
aes(x = median_year,
y = friendscr)) +
geom_smooth(method = 'lm',
linetype = 0,
se = TRUE,
fill = '#373737',
alpha = 0.3) +
geom_point(size = 4,
aes(alpha = -friendscr),
pch = 16,
color = 'black') +
scale_alpha(name = '',
range = c(0.4, 1)) +
labs(x = '',
y = 'Friendliness score',
title = 'Version 13',
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(lp = 'none') +
geom_text(data=subset(data, justice == 'alito'),
aes(median_year,
friendscr,
label=paste0('Justice ', Hmisc::capitalize(justice))),
vjust = 1.5,
hjust = 1)
#####################################################################################################
# Create distributions using specified theme
#####################################################################################################
# Version 14 - this is the original, that they liked, but with slightly larger points, as they suggested.
# Get data
data <- all_data$feldman$f1
# recode federal
data$federal <- ifelse(data$federal == '1', 'Federal', 'State')
ggplot(data,
aes(x = federal,
y = clarity_score)) +
ylim(c(-3, 11)) +
stat_ydensity(geom="segment",
adjust = 20,
scale = 'area',
aes(xend=..x..+..scaled../3.5,
yend=..y..,
alpha=(..scaled../3)^5),
size=3,
color = 'darkgrey',
trim=TRUE) +
stat_ydensity(geom="segment",
adjust = 20,
scale = 'area',
aes(xend=..x..-..scaled../3.5,
yend=..y..,
alpha=(..scaled../3)^5),
size=3,
linetype = 1,
color = 'darkgrey',
trim=TRUE) +
labs(x = '',
y = 'Clarity Score',
title = 'Version 14, spherical cloud represents distrubition') +
scale_alpha_continuous(range= c(-0, .5)) +
geom_jitter(size = 1,
color = 'black',
width = 0.3,
alpha = 0.3,
pch = 16) +
theme_sfi(lp = 'none')
# Version 15
ggplot(data,
aes(x = federal,
y = clarity_score)) +
ylim(c(-3, 11)) +
stat_ydensity(geom="segment",
adjust = 20,
scale = 'area',
aes(xend=..x..+..scaled../5,
yend=..y..,
alpha=(..scaled../3)^1),
size=3,
color = 'darkgrey',
trim=TRUE) +
stat_ydensity(geom="segment",
adjust = 20,
scale = 'area',
aes(xend=..x..-..scaled../5,
yend=..y..,
alpha=(..scaled../3)^1),
size=3,
linetype = 1,
color = 'darkgrey',
trim=TRUE) +
labs(x = '',
y = 'Clarity Score',
title = 'Version 15, spherical cloud represents distrubition') +
scale_alpha_continuous(range= c(-0, .5)) +
geom_jitter(size = 1.5,
color = 'black',
width = 0.2,
alpha = 0.3,
pch = 16) +
theme_sfi(lp = 'none')
# 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')
#####################################################################################################
# make plot for frankenreiter 5 so that each point colored based on time, and each decade is labeled
#####################################################################################################
# Get data
data <- all_data$frankenreiter$f5_1
cols <- make_colors(length(unique(data$year)), bw = TRUE)
# plot the 1955 to 2014 data
ggplot(data,
aes(x = coord2,
y = coord1,
fill = year)) +
geom_point(size = 4,
pch = 21,
alpha = 0.7) +
theme_sfi() +
annotate(geom = 'text',
label = '1955',
x = -0.0755,
y = -0.026) +
annotate("text",
x = -0.0755,
y = -0.023,
label = sprintf('\u2191')) +
annotate(geom = 'text',
label = '1960',
x = -0.043,
y = -0.007) +
annotate(geom = 'text',
label = '1960',
x = -0.043,
y = -0.007) +
annotate(geom = 'text',
label = '1970',
x = -0.041,
y = 0.0084) +
annotate(geom = 'text',
label = '1980',
x = 0.0129,
y = 0.0039) +
labs(x = 'Coordinate 2',
y = 'Coordinate 1',
title = 'Version 17') +
scale_fill_manual(name = '',
values = sort(cols, decreasing = TRUE)) +
theme(legend.position = 'none')
# plot the 1955 to 2014 data
# Get data
data <- all_data$frankenreiter$f5_1
ggplot(data,
aes(x = coord2,
y = coord1,
fill = year)) +
geom_point(size = 4,
pch = 21,
alpha = 0.7) +
ggrepel::geom_text_repel(data=subset(data, year == 1960 | year == 1970 | year == 1980 | year == 1990 | year == 2000 | year== 2010),
aes(coord2, coord1, label=year), vjust = -1.5, hjust = 2.2) +
theme_sfi() +
labs(x = 'Coordinate 2',
y = 'Coordinate 1',
title = 'Version 18') +
scale_fill_manual(name = '',
values = sort(cols)) +
theme(legend.position = 'none')
# plot the 1955 to 2014 data
cols <- make_colors(length(unique(data$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 17') +
scale_fill_gradient(name = '', low = "#0D0D0D", high = "#F2F2F2") +
theme_sfi(lp = 'bottom')
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