.Rhistory

geom_line(size = 2) +
gghighlight(max(avg) > 95,  label_key = gamename) +
theme_minimal(base_size = 16) +
labs(title = "The Rise of Farming Simulator", subtitle = 'The Farming Simulator francise has become increasingly popular since 2012' , caption = 'Data from SteamCharts • #TidyTuesday • @Ian_Bellio', x= "Average Number of Players at the Same Time)", y= "")
farming
farming <- ggplot(video_games, aes(date, avg, color = gamename)) +
geom_line(size = 2) +
gghighlight(max(avg) > 95,  label_key = gamename) +
theme_minimal(base_size = 16) +
labs(title = "The Rise of Farming Simulator", subtitle = 'The Farming Simulator francise has become increasingly popular since 2012' , caption = 'Data from SteamCharts • #TidyTuesday • @Ian_Bellio', y= "Average Number of Players at the Same Time)", x= "")
farming
farming <- ggplot(video_games, aes(date, avg, color = gamename)) +
geom_line(size = 2) +
gghighlight(max(avg) > 95,  label_key = gamename) +
theme_minimal(base_size = 16) +
labs(title = "The Rise of Farming Simulator", subtitle = 'The Farming Simulator francise has become increasingly popular since 2012' , caption = 'Data from SteamCharts • #TidyTuesday • @Ian_Bellio', y= "Average Number of Players at the Same Time", x= "")
farming
farming <- ggplot(video_games, aes(date, avg, color = gamename)) +
geom_line(size = 2) +
gghighlight(max(avg) > 95,  label_key = gamename) +
theme_minimal(base_size = 16) +
labs(title = "The Rise of Farming Simulator", subtitle = 'The Farming Simulator francise has become increasingly popular since 2012' , caption = 'Data from SteamCharts • #TidyTuesday • @Ian_Bellio', y= "Average Number of Players at the Same Time", x= "") +
theme(plot.title = element_text(size=24, family = "Source Sans Pro Semibold")) +
theme(text = element_text(size=18, family = "Source Sans Pro"))
farming
farming <- ggplot(video_games, aes(date, avg, color = gamename)) +
geom_line(size = 2) +
gghighlight(max(avg) > 95,  label_key = gamename) +
theme_minimal(base_size = 16) +
labs(title = "The Rise of Farming Simulator", subtitle = 'The Farming Simulator francise has become increasingly popular since 2012' , caption = 'Data from SteamCharts • #TidyTuesday • @Ian_Bellio', y= "Average Number of Players", x= "") +
theme(plot.title = element_text(size=24, family = "Source Sans Pro Semibold")) +
theme(text = element_text(size=18, family = "Source Sans Pro"))
farming
ggsave("FarmingSmulator.png", dpi = 300, width = 11, height = 10, units = "in")
ggsave("FarmingSmulator.png", dpi = 300, width = 8, height = 4.5, units = "in")
farming <- ggplot(video_games, aes(date, avg, color = gamename)) +
geom_line(size = 2) +
gghighlight(max(avg) > 95,  label_key = gamename) +
theme_minimal(base_size = 16) +
labs(title = "The Rise of Farming Simulator", subtitle = 'The Farming Simulator francise has become increasingly popular since 2012' , caption = 'Data from SteamCharts • #TidyTuesday • @Ian_Bellio', y= "Average Number of Players", x= "") +
theme(plot.title = element_text(size=18, family = "Source Sans Pro Semibold")) +
theme(text = element_text(size=14, family = "Source Sans Pro"))
farming
library(tidyverse)
#Data
broadband <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-05-11/broadband.csv')
broadbandzip <- broadband <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-05-11/broadband_zip.csv')
#Data
broadband <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-05-11/broadband.csv')
broadbandzip <-  readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-05-11/broadband_zip.csv')
library(tigris)
install.packages("tigris")
library(leaflet)
trib <- tribal_subdivisions_national()
library(tidyverse)
library(tigris)
library(leaflet)
trib <- tribal_subdivisions_national()
trib <- tribal_subdivisions_national()
leaflet(trib) %>%
trib <- tribal_subdivisions_national()
leaflet(trib) %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(fillColor = "white",
color = "black",
weight = 0.5)
(rappdirs::user_cache_dir("tigris"))
library(tidyverse)
library(tigris)
library(leaflet)
library(sf)
trib <- native_areas()
zipcodes <- zctas(cb = TRUE)
native_area_zips <- st_join(trib, zipcodes)
View(native_area_zips)
broadbandzip <-  readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-05-11/broadband_zip.csv')
View(broadbandzip)
View(native_area_zips)
native_broadband <-  left_join(broadbandzip,native_area_zips, by = c("POSTAL CODE" = "GEOID10"))
native_area_zips <- st_join(trib, zipcodes) %>%
mutate(ZIP = as.numeric(GEOID10))
native_broadband <-  left_join(broadbandzip,native_area_zips, by = c("POSTAL CODE" = "ZIP"))
View(native_broadband)
native_broadband <-  left_join(broadbandzip,native_area_zips, by = c("POSTAL CODE" = "ZIP")) %>%
mutate(indian_country = case_when(is.na(NAME) ~ "Other", TRUE ~ "Native" ))
nativebroadband_plot <- ggplot(data = native_broadband, aes(indian_country, BROADBAND USAGE, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .15), size = 1) +
geom_boxplot(aes(x = as.numeric(oxygen_used) + 1, y = injury_height_ft),outlier.shape = NA, alpha = 0.3, width = .1, colour = "BLACK") +
coord_flip() +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
scale_y_continuous(label=comma) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
library(tidyverse)
library(tigris)
library(leaflet)
library(sf)
nativebroadband_plot <- ggplot(data = native_broadband, aes(indian_country, BROADBAND USAGE, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .15), size = 1) +
geom_boxplot(aes(x = as.numeric(oxygen_used) + 1, y = injury_height_ft),outlier.shape = NA, alpha = 0.3, width = .1, colour = "BLACK") +
coord_flip() +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
scale_y_continuous(label=comma) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
source("https://gist.githubusercontent.com/benmarwick/2a1bb0133ff568cbe28d/raw/fb53bd97121f7f9ce947837ef1a4c65a73bffb3f/geom_flat_violin.R")
nativebroadband_plot <- ggplot(data = native_broadband, aes(indian_country, BROADBAND USAGE, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .15), size = 1) +
geom_boxplot(aes(x = as.numeric(oxygen_used) + 1, y = injury_height_ft),outlier.shape = NA, alpha = 0.3, width = .1, colour = "BLACK") +
coord_flip() +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
scale_y_continuous(label=comma) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(indian_country, BROADBAND USAGE, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .15), size = 1) +
geom_boxplot(aes(x = as.numeric(indian_country) + 1, y = BROADBAND USAGE),outlier.shape = NA, alpha = 0.3, width = .1, colour = "BLACK") +
coord_flip() +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
scale_y_continuous(label=comma) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(indian_country, BROADBAND USAGE, fill = indian_country)) + geom_jitter()
nativebroadband_plot <- ggplot(data = native_broadband, aes(indian_country, "BROADBAND USAGE", fill = indian_country)) + geom_jitter()
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(indian_country, "BROADBAND USAGE", fill = indian_country)) + geom_dotplot()
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(indian_country, BROADBAND USAGE, fill = indian_country)) + geom_dotplot()
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(indian_country, `BROADBAND USAGE`, fill = indian_country)) + geom_dotplot()
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country,y = `BROADBAND USAGE`, fill = indian_country)) + geom_dotplot()
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) + geom_point()
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) + geom_jitter()
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) + geom_violin()
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) + geom_dotplot()
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) + geom_boxplot()
nativebroadband_plot
install.packages('ggbeeswarm')
library(ggbeeswarm)
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) + geom_beeswarm()
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .15), size = 1)
nativebroadband_plot
library(plyr)
install.packages("plyr")
library(plyr)
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .15), size = 1)
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .15), size = 0.5)
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .15), size = 0.2)
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .15), size = 0.2) +
geom_boxplot(aes(x = as.numeric(indian_country) + 1, y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = .1, colour = "BLACK")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .15), size = 0.2) +
geom_boxplot(aes(x = as.numeric(indian_country) + 1, y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 1, colour = "BLACK")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .5), size = 0.2) +
geom_boxplot(aes(x = as.numeric(indian_country) + 1, y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 1, colour = "BLACK")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .3), size = 0.2) +
geom_boxplot(aes(x = as.numeric(indian_country) + 1, y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 1, colour = "BLACK")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .25), size = 0.2) +
geom_boxplot(aes(x = as.numeric(indian_country) + 1, y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 1, colour = "BLACK")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .25), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 1, colour = "BLACK")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .25), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 0.25, colour = "BLACK")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .25), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 0.25, colour = "BLACK") +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
library(breaks)
library(scales)
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0),adjust = 2) +
geom_point(position = position_jitter(width = .25), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 0.25, colour = "BLACK") +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_point(position = position_jitter(width = .25), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 0.25, colour = "BLACK", position = position_nudge(x = .2, y = 0)) +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_point(position = position_jitter(width = .25), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 0.25, colour = "BLACK", position = position_nudge(x = 1, y = 0)) +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_point(position = position_jitter(width = .25), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 0.25, colour = "BLACK", position = position_nudge(x = 0.25, y = 0)) +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country)) +
geom_point(position = position_jitter(width = .25), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 0.25, colour = "BLACK", position = position_nudge(x = 0.5, y = 0)) +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country, color = indian_country)) +
geom_point(position = position_jitter(width = .25), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 0.25, colour = "BLACK", position = position_nudge(x = 0.35, y = 0)) +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, fill = indian_country, color = indian_country)) +
geom_point(position = position_jitter(width = .3), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 0.25, colour = "BLACK") +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .3), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0.3, width = 0.25, colour = "BLACK") +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .3), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.25, colour = "BLACK") +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "BLACK") +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = indian_country) +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`,color = indian_country ),outlier.shape = NA, alpha = 0, width = 0.3) +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = black) +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
library(showtext)
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Acute Mountain Sickness in Himalayan Climbing", subtitle = "Acute Mountain Sickness (AMS) is an altitude-related illness caused by the reduced\n oxyen at altitude. With supplemental oxygen, AMS occured at a median altitude of\n 24,442 ft. Without, AMS occured at a median altitude of 20,997 ft.", x = "Supplemental Oxygen Used", y = "AMS Injury Height (ft)")
nativebroadband_plot
###Data
broadband <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-05-11/broadband.csv')
View(broadband)
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Usage in Indian Country", subtitle = "In the United States, indigenous communities often have limited access or  ", x = "Supplemental Oxygen Used", y = "Percent Broadband Usage")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, indigenous peoples living on tribal lands can have limited access to fast broadband internet. Pricing and lack of broadband infrastructure to rural areas can impact tribal education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, indigenous peoples living on tribal lands can have limited access to\n fast broadband internet. Pricing and lack of broadband infrastructure to rural areas can impact tribal education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, indigenous peoples living on tribal lands can have limited access to\n fast broadband internet. Pricing and lack of broadband infrastructure to rural areas can\n impact tribal education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, indigenous peoples living on tribal lands can have limited access to\n fast broadband internet. Pricing and lack of broadband infrastructure to rural tribal communities  can\n impact  education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, indigenous peoples living on tribal lands can have limited access to\n fast broadband internet. Pricing and lack of broadband infrastructure in tribal communities  can\n impact  education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, zip codes with with tribal lands have lower broadband internet usage when compared with other zip codes. Pricing and lack of broadband infrastructure in tribal communities\n can impact education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage")
nativebroadband_plot
library(ggtext)
native_broadband <-  left_join(broadbandzip,native_area_zips, by = c("POSTAL CODE" = "ZIP")) %>%
mutate(indian_country = case_when(is.na(NAME) ~ "Other", TRUE ~ "Tribal Lands" ))
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, zip codes with with tribal lands have lower broadband internet usage when compared with other zip codes. Pricing and lack of broadband infrastructure in tribal communities\n can impact education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, zip codes with with tribal lands have lower broadband internet usage\n when compared with other zip codes. Pricing and lack of broadband infrastructure in tribal communities can impact education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, zip codes with with tribal lands have lower broadband internet usage\n when compared with other zip codes. Pricing and lack of broadband infrastructure in tribal\n communities can impact education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, zip codes that contain tribal lands have lower broadband internet usage\n when compared with other zip codes. Pricing and lack of broadband infrastructure in tribal\n communities can impact education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, zip codes that contain tribal lands have lower broadband internet\n usage when compared with other zip codes. Pricing and lack of broadband infrastructure in tribal\n communities can impact education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage")
nativebroadband_plot
\n
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, zip codes that contain tribal lands have lower broadband internet\n usage when compared with other zip codes. Pricing and lack of broadband infrastructure\n in tribal communities can impact education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, zip codes that contain tribal lands have lower broadband internet\n usage when compared with other zip codes. Pricing and lack of broadband infrastructure\n in tribal communities can impact education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage", caption = "Data: Microsoft, US Census Bureau | #TidyTuesday | @Ian_Bellio")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, zip codes that contain tribal lands have lower broadband internet\n usage when compared with other zip codes. Pricing and lack of broadband infrastructure\n in tribal communities can impact education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage", caption = "Data: Microsoft, US Census Bureau | #TidyTuesday | @Ian_Bellio")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
scale_x_discrete(position = "top") +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, zip codes that contain tribal lands have lower broadband internet\n usage when compared with other zip codes. Pricing and lack of broadband infrastructure\n in tribal communities can impact education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage", caption = "Data: Microsoft, US Census Bureau | #TidyTuesday | @Ian_Bellio")
nativebroadband_plot
native_broadband$indian_country <- factor(native_broadband$indian_country, levels = c("Tribal Lands", "Other"))
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
scale_x_discrete(position = "top") +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "so")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, zip codes that contain tribal lands have lower broadband internet\n usage when compared with other zip codes. Pricing and lack of broadband infrastructure\n in tribal communities can impact education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage", caption = "Data: Microsoft, US Census Bureau | #TidyTuesday | @Ian_Bellio")
nativebroadband_plot
nativebroadband_plot <- ggplot(data = native_broadband, aes(x = indian_country, y = `BROADBAND USAGE`, color = indian_country)) +
geom_point(position = position_jitter(width = .4), size = 0.2) +
geom_boxplot(aes(x = indian_country , y = `BROADBAND USAGE`),outlier.shape = NA, alpha = 0, width = 0.3, colour = "black") +
scale_y_continuous(label=percent) +
scale_x_discrete(position = "top") +
theme_minimal() +
theme_minimal(base_size = 16, base_family = "roboto") +
theme(plot.title = element_text(size=26, family = "times new roman")) +
theme(legend.position = "none") +
labs(title = "Broadband Internet Use in Indian Country", subtitle = "In the United States, zip codes that contain tribal lands have lower broadband internet\n usage when compared with other zip codes. Pricing and lack of broadband infrastructure\n in tribal communities can impact education, economic development, and quality of life.  ", x = "", y = "Percent Broadband Usage", caption = "Data: Microsoft, US Census Bureau | #TidyTuesday | @Ian_Bellio")
nativebroadband_plot