ashomah/Tour_de_France_Code

## Tour_de_France_Code

### We have selected a dataset about statistics of the Tour de France results, from 1903 to 2016.
### The dataset has been selected from this list: [Tour de France Dataset](http://www.makeovermonday.co.uk/data/data-sets-2017/).
### All documents of this project can be found on GitHub: [Assignment 01 - GitHub](https://github.com/ashomah/Data-Vizualization-Course/tree/master/Assignment%2001%20-%20R).
### The code can be found on GitHub as a Gist: [Assignment 01 - Gist](https://gist.github.com/ashomah/a4d041e1965c4b41e783228a9c43fc06).

# INSTALL AND LOAD PACKAGES ----

packages_list <- c('ggplot2',
                   'ggalt',
                   'gridExtra',
                   'scales',
                   'grid',
                   'lattice',
                   'ggthemes',
                   'extrafont',
                   'plotly',
                   'plyr',
                   'leaflet',
                   'maps'
                   )

for (i in packages_list){
  if(!i%in%installed.packages()){
    install.packages(i, dependencies = TRUE, repos = "http://cran.us.r-project.org")
    library(i, character.only = TRUE)
    print(paste0(i, ' has been installed'))
  } else {
    print(paste0(i, ' is already installed'))
    library(i, character.only = TRUE)
  }
}


# READ DATASET FROM GIST AND ADD VARIABLES ----

tour_de_france <- read.csv("https://gist.githubusercontent.com/ashomah/e7c6f1e6c519b5eb301b8b51c00071f0/raw/3e4347bd5ab5ee3536870fc87ff498d97b546fc9/Tour_de_France_Dataset",
                           sep = ',',
                           header = TRUE)

# Add Duration
tour_de_france$Start.Date <- as.Date(tour_de_france$Start.Date, format = '%d/%m/%Y')
tour_de_france$End.Date <- as.Date(tour_de_france$End.Date, format = '%d/%m/%Y')
tour_de_france$Duration <- tour_de_france$End.Date - tour_de_france$Start.Date

# Add Distance per Stage
tour_de_france$Distance_per_Stage <- tour_de_france$Total.distance..km. / tour_de_france$Number.of.stages

# Add Withdrawal
tour_de_france$Withdrawal <- tour_de_france$Entrants - tour_de_france$Finishers

# Add Withdrawal Rate
tour_de_france$Withdrawal_Rate <- tour_de_france$Withdrawal / tour_de_france$Entrants

# Add Variable - "group" calling the right color of icon basis "Total distance km" column
tour_de_france$group=cut(as.numeric(tour_de_france$Total.distance..km.), breaks=c(0,4000,6000), labels = c('yellow','red'))

# Create new data-frame for frequency basis race starting point (used in maps)
dist=count(tour_de_france[ ,c("Starting.city.Longitude","Starting.city.Latitude","Starting.city")])


# COLOR PALETTE AND FONTS ----
# We used the colors of the Tour de France logo for our charts.

# Palette 1
color1 = 'black'
color2 = 'white'
color3 = 'gold1'
color4 = 'darkorchid3'
font1 = 'Impact'
font2 = 'Helvetica'

# Color Palette for Frequency Density (basis new df 'dist' and used in map)
pal = colorNumeric(palette = c(color3,color4), domain = dist$freq)

# Icons imported for maps
tdfIcons <- iconList(red = makeIcon("https://github.com/ashomah/Data-Vizualization-Course/blob/master/Assignment%2001%20-%20R/Map%20Icons/red.png?raw=true", iconWidth = 20, iconHeight =20),
                     yellow = makeIcon("https://github.com/ashomah/Data-Vizualization-Course/blob/master/Assignment%2001%20-%20R/Map%20Icons/yellow.png?raw=true", iconWidth = 20, iconHeight =20),
                     green = makeIcon("https://github.com/ashomah/Data-Vizualization-Course/blob/master/Assignment%2001%20-%20R/Map%20Icons/green.png?raw=true", iconWidth = 20, iconHeight =20),
                     blue = makeIcon("https://github.com/ashomah/Data-Vizualization-Course/blob/master/Assignment%2001%20-%20R/Map%20Icons/blue.png?raw=true", iconWidth = 20, iconHeight =20))


# 1. MAPS ----
# These maps aim to visualise the starting co-ordinates of each Tour de France race on the European map.

## Map A : Map basis the location and stats of each TDF event (change markeroptions to change 'Year' shown as title on hover;  popup for changing the stats to be shown on click)
mapA = leaflet(tour_de_france) %>%
  addProviderTiles(providers$CartoDB.DarkMatter) %>%
  addMarkers(lng=tour_de_france[tour_de_france$group=="red", "Starting.city.Longitude"],
             lat=tour_de_france[tour_de_france$group=="red", "Starting.city.Latitude"],
             popup=paste(paste0("Start City =   ", tour_de_france[tour_de_france$group=="red","Starting.city"]),
                         paste0("Start Date = ", tour_de_france[tour_de_france$group=="red","Start.Date"]),
                         paste0("End Date = ", tour_de_france[tour_de_france$group=="red","End.Date"]),
                         paste0("Total Kms = ", tour_de_france[tour_de_france$group=="red","Total.distance..km."]),
                         paste0("Winner = ", tour_de_france[tour_de_france$group=="red","Winner"],
                                " (", tour_de_france[tour_de_france$group=="red","Winner.s.Team"],
                                " | ", tour_de_france[tour_de_france$group=="red","Winner.s.Nationality"], ")"),
                         sep="<br/>"),
             options = markerOptions(interactive = TRUE, title = tour_de_france[tour_de_france$group=="red","Year"], riseOnHover = TRUE),
             icon = tdfIcons$red, group = "Red Icons") %>%
  addMarkers(lng=tour_de_france[tour_de_france$group=="yellow", "Starting.city.Longitude"],
             lat=tour_de_france[tour_de_france$group=="yellow", "Starting.city.Latitude"],
             popup=paste(paste0("Start City = ",tour_de_france[tour_de_france$group=="yellow","Starting.city"]),
                         paste0("Start Date = ",tour_de_france[tour_de_france$group=="yellow","Start.Date"]),
                         paste0("End Date = ",tour_de_france[tour_de_france$group=="yellow","End.Date"]),
                         paste0("Total Kms = ",tour_de_france[tour_de_france$group=="yellow","Total.distance..km."]),
                         paste0("Winner = ",tour_de_france[tour_de_france$group=="yellow","Winner"],
                                " (",tour_de_france[tour_de_france$group=="yellow","Winner.s.Team"],
                                " | ",tour_de_france[tour_de_france$group=="yellow","Winner.s.Nationality"],")"),
                         sep="<br/>"),
             options = markerOptions(interactive = TRUE, title = tour_de_france[tour_de_france$group=="yellow","Year"], riseOnHover = TRUE),
             icon = tdfIcons$yellow, group = "Yellow Icons") %>%
  addLegend(title = "Starting points of Tour de France events (basis Total distance of the event",
            position = "bottomleft",
            labels = c("Total Distance < 4,000 Kms","Total Distance > 4,000 Kms"),
            colors = c("Yellow", "red")) %>%
  addScaleBar(position = "topleft") %>%
  addLayersControl(overlayGroups = c("Red Icons","Yellow Icons"), position = "bottomright", options = layersControlOptions(collapsed = FALSE))
mapA

## Map B : Shows the frequency of start city
mapB = leaflet(dist) %>%
  addProviderTiles(providers$CartoDB.DarkMatter) %>%
  addCircleMarkers(lng=dist[ ,"Starting.city.Longitude"], lat=dist[ ,"Starting.city.Latitude"],
                   radius = 8, fillColor =~ pal(freq), fillOpacity = (20*dist$freq/100),
                   stroke = TRUE, color =~ pal(freq), weight = 2*log(dist$freq),
                   popup = paste(paste0("Start City : ",dist$Starting.city),
                                 paste0("Freq : ",dist$freq),sep = "<br/>")) %>%
  addLegend(title = "Density of starting points for TDF events", position = "bottomleft", pal = pal, labels = c(1,40), bins = 5, values =~ as.numeric(dist$freq))
mapB


# 2. BASIC CHARTS - TIME SERIES ----
# These first charts aim to show the evolution of the race settings overtime.
# The Total Distance has decreased, year after year, while the number of stages has increased, leading the Average Distance per Stage to decrease even more.
# This increased the energy the runners can deploy during a stage, improving the overall race speed.

# Total Distance per Year
plot_total_distance <- ggplot(tour_de_france, aes(x=Year, y=Total.distance..km.)) +
  geom_line(color = color3)+
  theme_minimal()+
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        panel.border = element_blank(),
        axis.title = element_blank(),
        axis.text.y = element_blank(),
        axis.text.x = element_text(color = color2, family = font2),
        axis.ticks = element_blank(),
        plot.background = element_rect(fill = color1, color = color1),
        legend.position = 'None')+
  expand_limits(y = -(max(tour_de_france$Total.distance..km.)-min(tour_de_france$Total.distance..km.))*2/10+min(tour_de_france$Total.distance..km.))+
  annotate('text',
           label = 'Total Distance',
           family = font1,
           color = color3,
           x = max(tour_de_france$Year)-(max(tour_de_france$Year)-min(tour_de_france$Year))/8,
           y = -(max(tour_de_france$Total.distance..km.)-min(tour_de_france$Total.distance..km.))/10+min(tour_de_france$Total.distance..km.),
           size = 4)+
  scale_x_continuous(breaks = c(1903, 1920, 1940, 1960, 1980, 2000, 2016), position = 'top')

# Number of Stages per Year
plot_stages <- ggplot(tour_de_france, aes(x=Year, y=Number.of.stages)) +
  geom_line(color = color3)+
  theme_minimal()+
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        panel.border = element_blank(),
        axis.title = element_blank(),
        axis.text = element_blank(),
        axis.ticks = element_blank(),
        plot.background = element_rect(fill = color1, color = color1),
        legend.position = 'None')+
  expand_limits(y = -(max(tour_de_france$Number.of.stages)-min(tour_de_france$Number.of.stages))*2/10+min(tour_de_france$Number.of.stages))+
  annotate('text',
           label = 'Number of Stages',
           family = font1,
           color = color3,
           x = max(tour_de_france$Year)-(max(tour_de_france$Year)-min(tour_de_france$Year))/8,
           y = -(max(tour_de_france$Number.of.stages)-min(tour_de_france$Number.of.stages))/10+min(tour_de_france$Number.of.stages),
           size = 4)

# Average Distance per Stage per Year
plot_distance_per_stage <- ggplot(tour_de_france, aes(x=Year, y=Distance_per_Stage)) +
  geom_line(color = color3)+
  theme_minimal()+
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        panel.border = element_blank(),
        axis.title = element_blank(),
        axis.text = element_blank(),
        axis.ticks = element_blank(),
        plot.background = element_rect(fill = color1, color = color1),
        legend.position = 'None')+
  expand_limits(y = -(max(tour_de_france$Distance_per_Stage)-min(tour_de_france$Distance_per_Stage))*2/10+min(tour_de_france$Distance_per_Stage))+
  annotate('text',
           label = 'Distance per Stage',
           family = font1,
           color = color3,
           x = max(tour_de_france$Year)-(max(tour_de_france$Year)-min(tour_de_france$Year))/8,
           y = -(max(tour_de_france$Distance_per_Stage)-min(tour_de_france$Distance_per_Stage))/10+min(tour_de_france$Distance_per_Stage),
           size = 4)

# Winner's Average Speed per Year
plot_winner_avg_speed <- ggplot(tour_de_france, aes(x=Year, y=Winner.s.avg.speed)) +
  geom_line(color = color1)+
  theme_minimal()+
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        panel.border = element_blank(),
        axis.title = element_blank(),
        axis.text = element_blank(),
        axis.ticks = element_blank(),
        plot.background = element_rect(fill = color3, color = color3),
        legend.position = 'None')+
  expand_limits(y = -(max(tour_de_france$Winner.s.avg.speed)-min(tour_de_france$Winner.s.avg.speed))*2/10+min(tour_de_france$Winner.s.avg.speed))+
  annotate('text',
           label = 'Winner\'s Average Speed',
           family = font1,
           color = color1,
           x = max(tour_de_france$Year)-(max(tour_de_france$Year)-min(tour_de_france$Year))/8,
           y = -(max(tour_de_france$Winner.s.avg.speed)-min(tour_de_france$Winner.s.avg.speed))/10+min(tour_de_france$Winner.s.avg.speed),
           size = 4)

# Plot
grid.arrange(plot_total_distance,
             plot_stages,
             plot_distance_per_stage,
             plot_winner_avg_speed,
             nrow = 4,
             ncol = 1)


# 3. DUMBBELL CHART ----
# This chart compares the number of Entrants and the number of Finishers over time.

# Dumbbell Chart
ggplot(tour_de_france, aes(x=tour_de_france$Finishers,
                           xend=tour_de_france$Entrants,
                           y=tour_de_france$Year,
                           group=tour_de_france$Year))+
  geom_dumbbell(colour = color2, colour_x = color2, size = 0.2, colour_xend = color3, size_xend = 1, dot_guide=FALSE, size_x = 1)+
  labs(x=NULL, y=NULL)+
  theme_tufte()+
  theme(axis.text.y = element_text(colour = color2, size = 8, family = font2),
        axis.text.x = element_text(colour = color2, size = 8, family = font2),
        axis.ticks = element_blank(),
        plot.title = element_text(color = color3, size = 14),
        plot.background = element_rect(fill= color1)
  )+
  scale_y_continuous(breaks = c(1903, 1920, 1940, 1960, 1980, 2000, 2016))+ coord_flip()

# Titles
spacing <-10
grid.text(unit(0.8, 'npc'), unit(0.165,"npc"), check.overlap = T,just = "left",
          label="Finishers",
          gp=gpar(col=color2, fontsize=16,fontface="bold", fontfamily = font1))
grid.text(unit(0.8, 'npc'), unit(0.2,"npc"), check.overlap = T,just = "left",
          label="Entrants",
          gp=gpar(col=color3, fontsize=16,fontface="bold", fontfamily = font1))


# 4. WAFFLE ----
# This chart shows the proportion of wins for the top 3 countries. Other countries have been groups under the label *Others*.

# Waffle Data Preparation
winners_nationality <- as.character(tour_de_france$Winner.s.Nationality)
winners_nationality[!(winners_nationality %in% c('France', 'Belgium', 'Spain'))] <- 'Others'
nrows <- 10
df <- expand.grid(y = 1:nrows, x = 1:nrows)
categ_table <- round(table(winners_nationality) * ((nrows*nrows)/(length(winners_nationality))))
categ_table <- categ_table[c(2,1,4,3)]
df$category <- factor(rep(names(categ_table), categ_table))

# Plot
ggplot(df, aes(x = x, y = y, fill = category))+
  geom_tile(color = "black", size = 0.5)+
  scale_x_continuous(expand = c(0, 0))+
  scale_y_continuous(expand = c(0, 0), trans = 'reverse')+
  scale_fill_manual(values = c('orange', 'gold1', 'darkorange4', 'darkorange3'),
                    breaks = c('France', 'Belgium', 'Spain', 'Others'),
                    labels = c('France', 'Belgium', 'Spain', 'Others'))+
  theme(title = element_text(),
        legend.position = 'right',
        legend.background = element_rect(fill = 'black'),
        legend.key = element_rect(fill = 'black', color = 'black'),
        legend.box.background = element_rect(fill = 'black', color = 'black'),
        legend.title = element_blank(),
        legend.text = element_text(margin = margin(r = 10), color = 'white', family = font2),
        legend.spacing.x = unit(5,'pt'),
        axis.text = element_blank(),
        axis.title = element_blank(),
        axis.ticks = element_blank(),
        panel.background = element_rect(fill = 'black', color = 'black'),
        plot.background = element_rect(fill = 'black', color = 'black'),
        plot.margin = unit(c(5.5, 5.5, 50, 5.5),'point'))
grid.text(unit(0.68, 'npc'), unit(0.05,"npc"), check.overlap = T, just = "left",
          label=paste(paste(rep(" ",spacing), collapse=''),"Wins per Country"),
          gp=gpar(col=color3, fontsize=16,fontface="bold", fontfamily = font1))


# 5. SMALL MULTIPLE WITH TUFTE THEME  ----
# These charts show on which Years each Nationality has won the competition.

# Data for Grey Background Data
tdf_no_nationality <- tour_de_france[,c('Year', 'Winner.s.avg.speed')]

# Plot
ggplot(tour_de_france, aes(x = Year, y = 1))+
  geom_bar(data = tdf_no_nationality, stat = 'identity', alpha = 0.1, fill = color2,width = 1)+
  geom_bar(stat = 'identity', fill = color3, width = 1)+
  facet_wrap( ~ Winner.s.Nationality, scales = 'free')+
  scale_x_continuous(breaks = c(1903, 2016))+
  theme_tufte(ticks = FALSE, base_size = 15)+
  theme(axis.text.y = element_blank(),
        axis.text.x = element_text(color = color2, family = font2, size = 6),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.title = element_blank(),
        plot.background = element_rect(fill = color1),
        strip.text = element_text(color = color2, family = font2, size = 8),
        panel.spacing = unit(2, 'lines'))
spacing <-10
grid.text(unit(1, 'npc'), unit(0.1,"npc"), check.overlap = T,just = "right",
          label=paste("Wins by Nationality",paste(rep(" ",spacing), collapse='')),
          gp=gpar(col=color3, fontsize=16,fontface="bold", fontfamily = font1))


# 6. TUFTE CHART - BOXPLOTS ----
# This plot shows the distribution of Winner's Average Speed by Nationality.

ggplot(tour_de_france, aes(x = reorder(factor(Winner.s.Nationality), -(Winner.s.avg.speed), median), Winner.s.avg.speed))+
  theme_tufte(base_size = 5, ticks=F)+
  geom_tufteboxplot(outlier.colour = color3, color= color3, size = 1.5, median.type = 'line', whisker.type = 'line', hoffset = 0, width = 3)+
  theme(plot.margin = unit(c(10,10,10,10),'pt'),
        axis.title=element_blank(),
        axis.text = element_text(colour = color2, family = font2, size = 10),
        axis.text.x = element_text(angle = 45, hjust = 1, size = 10),
        plot.background = element_rect(fill = color1))+
  scale_y_continuous(expand = c(0, 0), limits = c(0,44), breaks = seq(0, 50, by = 20))+
  annotate('text', label = "Winner's Average Speed", family = font1, color = color3, x = 12, y = 3, size = 5)

	### We have selected a dataset about statistics of the Tour de France results, from 1903 to 2016.
	### The dataset has been selected from this list: [Tour de France Dataset](http://www.makeovermonday.co.uk/data/data-sets-2017/).
	### All documents of this project can be found on GitHub: [Assignment 01 - GitHub](https://github.com/ashomah/Data-Vizualization-Course/tree/master/Assignment%2001%20-%20R).
	### The code can be found on GitHub as a Gist: [Assignment 01 - Gist](https://gist.github.com/ashomah/a4d041e1965c4b41e783228a9c43fc06).

	# INSTALL AND LOAD PACKAGES ----

	packages_list <- c('ggplot2',
	'ggalt',
	'gridExtra',
	'scales',
	'grid',
	'lattice',
	'ggthemes',
	'extrafont',
	'plotly',
	'plyr',
	'leaflet',
	'maps'
	)

	for (i in packages_list){
	if(!i%in%installed.packages()){
	install.packages(i, dependencies = TRUE, repos = "http://cran.us.r-project.org")
	library(i, character.only = TRUE)
	print(paste0(i, ' has been installed'))
	} else {
	print(paste0(i, ' is already installed'))
	library(i, character.only = TRUE)
	}
	}



	# READ DATASET FROM GIST AND ADD VARIABLES ----

	tour_de_france <- read.csv("https://gist.githubusercontent.com/ashomah/e7c6f1e6c519b5eb301b8b51c00071f0/raw/3e4347bd5ab5ee3536870fc87ff498d97b546fc9/Tour_de_France_Dataset",
	sep = ',',
	header = TRUE)

	# Add Duration
	tour_de_france$Start.Date <- as.Date(tour_de_france$Start.Date, format = '%d/%m/%Y')
	tour_de_france$End.Date <- as.Date(tour_de_france$End.Date, format = '%d/%m/%Y')
	tour_de_france$Duration <- tour_de_france$End.Date - tour_de_france$Start.Date

	# Add Distance per Stage
	tour_de_france$Distance_per_Stage <- tour_de_france$Total.distance..km. / tour_de_france$Number.of.stages

	# Add Withdrawal
	tour_de_france$Withdrawal <- tour_de_france$Entrants - tour_de_france$Finishers

	# Add Withdrawal Rate
	tour_de_france$Withdrawal_Rate <- tour_de_france$Withdrawal / tour_de_france$Entrants

	# Add Variable - "group" calling the right color of icon basis "Total distance km" column
	tour_de_france$group=cut(as.numeric(tour_de_france$Total.distance..km.), breaks=c(0,4000,6000), labels = c('yellow','red'))

	# Create new data-frame for frequency basis race starting point (used in maps)
	dist=count(tour_de_france[ ,c("Starting.city.Longitude","Starting.city.Latitude","Starting.city")])


	# COLOR PALETTE AND FONTS ----
	# We used the colors of the Tour de France logo for our charts.

	# Palette 1
	color1 = 'black'
	color2 = 'white'
	color3 = 'gold1'
	color4 = 'darkorchid3'
	font1 = 'Impact'
	font2 = 'Helvetica'

	# Color Palette for Frequency Density (basis new df 'dist' and used in map)
	pal = colorNumeric(palette = c(color3,color4), domain = dist$freq)

	# Icons imported for maps
	tdfIcons <- iconList(red = makeIcon("https://github.com/ashomah/Data-Vizualization-Course/blob/master/Assignment%2001%20-%20R/Map%20Icons/red.png?raw=true", iconWidth = 20, iconHeight =20),
	yellow = makeIcon("https://github.com/ashomah/Data-Vizualization-Course/blob/master/Assignment%2001%20-%20R/Map%20Icons/yellow.png?raw=true", iconWidth = 20, iconHeight =20),
	green = makeIcon("https://github.com/ashomah/Data-Vizualization-Course/blob/master/Assignment%2001%20-%20R/Map%20Icons/green.png?raw=true", iconWidth = 20, iconHeight =20),
	blue = makeIcon("https://github.com/ashomah/Data-Vizualization-Course/blob/master/Assignment%2001%20-%20R/Map%20Icons/blue.png?raw=true", iconWidth = 20, iconHeight =20))


	# 1. MAPS ----
	# These maps aim to visualise the starting co-ordinates of each Tour de France race on the European map.

	## Map A : Map basis the location and stats of each TDF event (change markeroptions to change 'Year' shown as title on hover; popup for changing the stats to be shown on click)
	mapA = leaflet(tour_de_france) %>%
	addProviderTiles(providers$CartoDB.DarkMatter) %>%
	addMarkers(lng=tour_de_france[tour_de_france$group=="red", "Starting.city.Longitude"],
	lat=tour_de_france[tour_de_france$group=="red", "Starting.city.Latitude"],
	popup=paste(paste0("Start City = ", tour_de_france[tour_de_france$group=="red","Starting.city"]),
	paste0("Start Date = ", tour_de_france[tour_de_france$group=="red","Start.Date"]),
	paste0("End Date = ", tour_de_france[tour_de_france$group=="red","End.Date"]),
	paste0("Total Kms = ", tour_de_france[tour_de_france$group=="red","Total.distance..km."]),
	paste0("Winner = ", tour_de_france[tour_de_france$group=="red","Winner"],
	" (", tour_de_france[tour_de_france$group=="red","Winner.s.Team"],
	" \| ", tour_de_france[tour_de_france$group=="red","Winner.s.Nationality"], ")"),
	sep="<br/>"),
	options = markerOptions(interactive = TRUE, title = tour_de_france[tour_de_france$group=="red","Year"], riseOnHover = TRUE),
	icon = tdfIcons$red, group = "Red Icons") %>%
	addMarkers(lng=tour_de_france[tour_de_france$group=="yellow", "Starting.city.Longitude"],
	lat=tour_de_france[tour_de_france$group=="yellow", "Starting.city.Latitude"],
	popup=paste(paste0("Start City = ",tour_de_france[tour_de_france$group=="yellow","Starting.city"]),
	paste0("Start Date = ",tour_de_france[tour_de_france$group=="yellow","Start.Date"]),
	paste0("End Date = ",tour_de_france[tour_de_france$group=="yellow","End.Date"]),
	paste0("Total Kms = ",tour_de_france[tour_de_france$group=="yellow","Total.distance..km."]),
	paste0("Winner = ",tour_de_france[tour_de_france$group=="yellow","Winner"],
	" (",tour_de_france[tour_de_france$group=="yellow","Winner.s.Team"],
	" \| ",tour_de_france[tour_de_france$group=="yellow","Winner.s.Nationality"],")"),
	sep="<br/>"),
	options = markerOptions(interactive = TRUE, title = tour_de_france[tour_de_france$group=="yellow","Year"], riseOnHover = TRUE),
	icon = tdfIcons$yellow, group = "Yellow Icons") %>%
	addLegend(title = "Starting points of Tour de France events (basis Total distance of the event",
	position = "bottomleft",
	labels = c("Total Distance < 4,000 Kms","Total Distance > 4,000 Kms"),
	colors = c("Yellow", "red")) %>%
	addScaleBar(position = "topleft") %>%
	addLayersControl(overlayGroups = c("Red Icons","Yellow Icons"), position = "bottomright", options = layersControlOptions(collapsed = FALSE))
	mapA

	## Map B : Shows the frequency of start city
	mapB = leaflet(dist) %>%
	addProviderTiles(providers$CartoDB.DarkMatter) %>%
	addCircleMarkers(lng=dist[ ,"Starting.city.Longitude"], lat=dist[ ,"Starting.city.Latitude"],
	radius = 8, fillColor =~ pal(freq), fillOpacity = (20*dist$freq/100),
	stroke = TRUE, color =~ pal(freq), weight = 2*log(dist$freq),
	popup = paste(paste0("Start City : ",dist$Starting.city),
	paste0("Freq : ",dist$freq),sep = "<br/>")) %>%
	addLegend(title = "Density of starting points for TDF events", position = "bottomleft", pal = pal, labels = c(1,40), bins = 5, values =~ as.numeric(dist$freq))
	mapB


	# 2. BASIC CHARTS - TIME SERIES ----
	# These first charts aim to show the evolution of the race settings overtime.
	# The Total Distance has decreased, year after year, while the number of stages has increased, leading the Average Distance per Stage to decrease even more.
	# This increased the energy the runners can deploy during a stage, improving the overall race speed.

	# Total Distance per Year
	plot_total_distance <- ggplot(tour_de_france, aes(x=Year, y=Total.distance..km.)) +
	geom_line(color = color3)+
	theme_minimal()+
	theme(panel.grid.major = element_blank(),
	panel.grid.minor = element_blank(),
	panel.border = element_blank(),
	axis.title = element_blank(),
	axis.text.y = element_blank(),
	axis.text.x = element_text(color = color2, family = font2),
	axis.ticks = element_blank(),
	plot.background = element_rect(fill = color1, color = color1),
	legend.position = 'None')+
	expand_limits(y = -(max(tour_de_france$Total.distance..km.)-min(tour_de_france$Total.distance..km.))*2/10+min(tour_de_france$Total.distance..km.))+
	annotate('text',
	label = 'Total Distance',
	family = font1,
	color = color3,
	x = max(tour_de_france$Year)-(max(tour_de_france$Year)-min(tour_de_france$Year))/8,
	y = -(max(tour_de_france$Total.distance..km.)-min(tour_de_france$Total.distance..km.))/10+min(tour_de_france$Total.distance..km.),
	size = 4)+
	scale_x_continuous(breaks = c(1903, 1920, 1940, 1960, 1980, 2000, 2016), position = 'top')

	# Number of Stages per Year
	plot_stages <- ggplot(tour_de_france, aes(x=Year, y=Number.of.stages)) +
	geom_line(color = color3)+
	theme_minimal()+
	theme(panel.grid.major = element_blank(),
	panel.grid.minor = element_blank(),
	panel.border = element_blank(),
	axis.title = element_blank(),
	axis.text = element_blank(),
	axis.ticks = element_blank(),
	plot.background = element_rect(fill = color1, color = color1),
	legend.position = 'None')+
	expand_limits(y = -(max(tour_de_france$Number.of.stages)-min(tour_de_france$Number.of.stages))*2/10+min(tour_de_france$Number.of.stages))+
	annotate('text',
	label = 'Number of Stages',
	family = font1,
	color = color3,
	x = max(tour_de_france$Year)-(max(tour_de_france$Year)-min(tour_de_france$Year))/8,
	y = -(max(tour_de_france$Number.of.stages)-min(tour_de_france$Number.of.stages))/10+min(tour_de_france$Number.of.stages),
	size = 4)

	# Average Distance per Stage per Year
	plot_distance_per_stage <- ggplot(tour_de_france, aes(x=Year, y=Distance_per_Stage)) +
	geom_line(color = color3)+
	theme_minimal()+
	theme(panel.grid.major = element_blank(),
	panel.grid.minor = element_blank(),
	panel.border = element_blank(),
	axis.title = element_blank(),
	axis.text = element_blank(),
	axis.ticks = element_blank(),
	plot.background = element_rect(fill = color1, color = color1),
	legend.position = 'None')+
	expand_limits(y = -(max(tour_de_france$Distance_per_Stage)-min(tour_de_france$Distance_per_Stage))*2/10+min(tour_de_france$Distance_per_Stage))+
	annotate('text',
	label = 'Distance per Stage',
	family = font1,
	color = color3,
	x = max(tour_de_france$Year)-(max(tour_de_france$Year)-min(tour_de_france$Year))/8,
	y = -(max(tour_de_france$Distance_per_Stage)-min(tour_de_france$Distance_per_Stage))/10+min(tour_de_france$Distance_per_Stage),
	size = 4)

	# Winner's Average Speed per Year
	plot_winner_avg_speed <- ggplot(tour_de_france, aes(x=Year, y=Winner.s.avg.speed)) +
	geom_line(color = color1)+
	theme_minimal()+
	theme(panel.grid.major = element_blank(),
	panel.grid.minor = element_blank(),
	panel.border = element_blank(),
	axis.title = element_blank(),
	axis.text = element_blank(),
	axis.ticks = element_blank(),
	plot.background = element_rect(fill = color3, color = color3),
	legend.position = 'None')+
	expand_limits(y = -(max(tour_de_france$Winner.s.avg.speed)-min(tour_de_france$Winner.s.avg.speed))*2/10+min(tour_de_france$Winner.s.avg.speed))+
	annotate('text',
	label = 'Winner\'s Average Speed',
	family = font1,
	color = color1,
	x = max(tour_de_france$Year)-(max(tour_de_france$Year)-min(tour_de_france$Year))/8,
	y = -(max(tour_de_france$Winner.s.avg.speed)-min(tour_de_france$Winner.s.avg.speed))/10+min(tour_de_france$Winner.s.avg.speed),
	size = 4)

	# Plot
	grid.arrange(plot_total_distance,
	plot_stages,
	plot_distance_per_stage,
	plot_winner_avg_speed,
	nrow = 4,
	ncol = 1)


	# 3. DUMBBELL CHART ----
	# This chart compares the number of Entrants and the number of Finishers over time.

	# Dumbbell Chart
	ggplot(tour_de_france, aes(x=tour_de_france$Finishers,
	xend=tour_de_france$Entrants,
	y=tour_de_france$Year,
	group=tour_de_france$Year))+
	geom_dumbbell(colour = color2, colour_x = color2, size = 0.2, colour_xend = color3, size_xend = 1, dot_guide=FALSE, size_x = 1)+
	labs(x=NULL, y=NULL)+
	theme_tufte()+
	theme(axis.text.y = element_text(colour = color2, size = 8, family = font2),
	axis.text.x = element_text(colour = color2, size = 8, family = font2),
	axis.ticks = element_blank(),
	plot.title = element_text(color = color3, size = 14),
	plot.background = element_rect(fill= color1)
	)+
	scale_y_continuous(breaks = c(1903, 1920, 1940, 1960, 1980, 2000, 2016))+ coord_flip()

	# Titles
	spacing <-10
	grid.text(unit(0.8, 'npc'), unit(0.165,"npc"), check.overlap = T,just = "left",
	label="Finishers",
	gp=gpar(col=color2, fontsize=16,fontface="bold", fontfamily = font1))
	grid.text(unit(0.8, 'npc'), unit(0.2,"npc"), check.overlap = T,just = "left",
	label="Entrants",
	gp=gpar(col=color3, fontsize=16,fontface="bold", fontfamily = font1))


	# 4. WAFFLE ----
	# This chart shows the proportion of wins for the top 3 countries. Other countries have been groups under the label Others.

	# Waffle Data Preparation
	winners_nationality <- as.character(tour_de_france$Winner.s.Nationality)
	winners_nationality[!(winners_nationality %in% c('France', 'Belgium', 'Spain'))] <- 'Others'
	nrows <- 10
	df <- expand.grid(y = 1:nrows, x = 1:nrows)
	categ_table <- round(table(winners_nationality) * ((nrows*nrows)/(length(winners_nationality))))
	categ_table <- categ_table[c(2,1,4,3)]
	df$category <- factor(rep(names(categ_table), categ_table))

	# Plot
	ggplot(df, aes(x = x, y = y, fill = category))+
	geom_tile(color = "black", size = 0.5)+
	scale_x_continuous(expand = c(0, 0))+
	scale_y_continuous(expand = c(0, 0), trans = 'reverse')+
	scale_fill_manual(values = c('orange', 'gold1', 'darkorange4', 'darkorange3'),
	breaks = c('France', 'Belgium', 'Spain', 'Others'),
	labels = c('France', 'Belgium', 'Spain', 'Others'))+
	theme(title = element_text(),
	legend.position = 'right',
	legend.background = element_rect(fill = 'black'),
	legend.key = element_rect(fill = 'black', color = 'black'),
	legend.box.background = element_rect(fill = 'black', color = 'black'),
	legend.title = element_blank(),
	legend.text = element_text(margin = margin(r = 10), color = 'white', family = font2),
	legend.spacing.x = unit(5,'pt'),
	axis.text = element_blank(),
	axis.title = element_blank(),
	axis.ticks = element_blank(),
	panel.background = element_rect(fill = 'black', color = 'black'),
	plot.background = element_rect(fill = 'black', color = 'black'),
	plot.margin = unit(c(5.5, 5.5, 50, 5.5),'point'))
	grid.text(unit(0.68, 'npc'), unit(0.05,"npc"), check.overlap = T, just = "left",
	label=paste(paste(rep(" ",spacing), collapse=''),"Wins per Country"),
	gp=gpar(col=color3, fontsize=16,fontface="bold", fontfamily = font1))


	# 5. SMALL MULTIPLE WITH TUFTE THEME ----
	# These charts show on which Years each Nationality has won the competition.

	# Data for Grey Background Data
	tdf_no_nationality <- tour_de_france[,c('Year', 'Winner.s.avg.speed')]

	# Plot
	ggplot(tour_de_france, aes(x = Year, y = 1))+
	geom_bar(data = tdf_no_nationality, stat = 'identity', alpha = 0.1, fill = color2,width = 1)+
	geom_bar(stat = 'identity', fill = color3, width = 1)+
	facet_wrap( ~ Winner.s.Nationality, scales = 'free')+
	scale_x_continuous(breaks = c(1903, 2016))+
	theme_tufte(ticks = FALSE, base_size = 15)+
	theme(axis.text.y = element_blank(),
	axis.text.x = element_text(color = color2, family = font2, size = 6),
	panel.grid.major = element_blank(),
	panel.grid.minor = element_blank(),
	axis.title = element_blank(),
	plot.background = element_rect(fill = color1),
	strip.text = element_text(color = color2, family = font2, size = 8),
	panel.spacing = unit(2, 'lines'))
	spacing <-10
	grid.text(unit(1, 'npc'), unit(0.1,"npc"), check.overlap = T,just = "right",
	label=paste("Wins by Nationality",paste(rep(" ",spacing), collapse='')),
	gp=gpar(col=color3, fontsize=16,fontface="bold", fontfamily = font1))


	# 6. TUFTE CHART - BOXPLOTS ----
	# This plot shows the distribution of Winner's Average Speed by Nationality.

	ggplot(tour_de_france, aes(x = reorder(factor(Winner.s.Nationality), -(Winner.s.avg.speed), median), Winner.s.avg.speed))+
	theme_tufte(base_size = 5, ticks=F)+
	geom_tufteboxplot(outlier.colour = color3, color= color3, size = 1.5, median.type = 'line', whisker.type = 'line', hoffset = 0, width = 3)+
	theme(plot.margin = unit(c(10,10,10,10),'pt'),
	axis.title=element_blank(),
	axis.text = element_text(colour = color2, family = font2, size = 10),
	axis.text.x = element_text(angle = 45, hjust = 1, size = 10),
	plot.background = element_rect(fill = color1))+
	scale_y_continuous(expand = c(0, 0), limits = c(0,44), breaks = seq(0, 50, by = 20))+
	annotate('text', label = "Winner's Average Speed", family = font1, color = color3, x = 12, y = 3, size = 5)