Disney Marathon Weather in ggplot2
Year | Low | High | StartTemp | StartHumidity | Sky | Wind | |
---|---|---|---|---|---|---|---|
2018 | 41 | 61 | 41 | 82 | Clear | 5 | |
2017 | 34 | 52 | 34 | 79 | Clear | 13 | |
2016 | 55 | 71 | 71 | 90 | Overcast | 8 | |
2015 | 54 | 79 | 54 | 90 | Clear | 4 | |
2014 | 51 | 66 | 63 | 93 | Partly Cloudy | 8 | |
2013 | 60 | 81 | 61 | 94 | Partly Cloudy | 0 | |
2012 | 50 | 77 | 50 | 96 | Clear | 0 | |
2011 | 43 | 64 | 44 | 68 | Clear | 5 | |
2010 | 28 | 44 | 29 | 55 | Clear | 9 | |
2009 | 55 | 79 | 56 | 97 | Clear | 4 |
library(ggplot2) | |
library(reshape2) | |
weather <- read.csv('DisneyMarathonWeather.csv') | |
weather.melt <- melt(weather[,c('Year', 'Low', 'High', 'Wind', 'StartHumidity', 'Sky')], | |
id.vars = c('Year', 'Wind', 'StartHumidity', 'Sky')) | |
ggplot(weather.melt, aes(x = Year)) + | |
geom_ribbon(data = weather, aes(ymin = Low, ymax = High), alpha = 0.3, fill = 'skyblue') + | |
geom_path(aes(y = value, group = variable)) + | |
geom_point(aes(y = value, size = Wind, color = Sky)) + | |
geom_text(aes(y = value, label = paste0(value, '°')), vjust = -1) + | |
scale_x_continuous(breaks = unique(weather.melt$Year)) + | |
scale_size_continuous('Wind (mph)') + | |
ylim(c(25, 85)) + | |
ylab('Temperature (Fahrenheit)') + xlab('') + theme_minimal() + | |
ggtitle('Disney Marathon Weather') | |
ggsave('DisneyMarathonWeather.png', width = 10, height = 4) |
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Here is the resulting plot: