knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/" )
This package allows building horizon plots in ggplot2. You can learn more about the package in vignette("ggHoriPlot")
.
You can install ggHoriPlot
from CRAN via:
install.packages("ggHoriPlot")
You can also install the development version of the package from GitHub with the following command:
#install.packages("devtools") devtools::install_github("rivasiker/ggHoriPlot")
Load the libraries:
library(tidyverse) library(ggHoriPlot) library(ggthemes)
Load the dataset and calculate the cutpoints and origin:
utils::data(climate_CPH) cutpoints <- climate_CPH %>% mutate( outlier = between( AvgTemperature, quantile(AvgTemperature, 0.25, na.rm=T)- 1.5*IQR(AvgTemperature, na.rm=T), quantile(AvgTemperature, 0.75, na.rm=T)+ 1.5*IQR(AvgTemperature, na.rm=T))) %>% filter(outlier) ori <- sum(range(cutpoints$AvgTemperature))/2 sca <- seq(range(cutpoints$AvgTemperature)[1], range(cutpoints$AvgTemperature)[2], length.out = 7)[-4] round(ori, 2) # The origin round(sca, 2) # The horizon scale cutpoints
Build the horizon plots in ggplot2
using geom_horizon()
:
climate_CPH %>% ggplot() + geom_horizon(aes(date_mine, AvgTemperature, fill = ..Cutpoints..), origin = ori, horizonscale = sca) + scale_fill_hcl(palette = 'RdBu', reverse = T) + facet_grid(Year~.) + theme_few() + theme( panel.spacing.y=unit(0, "lines"), strip.text.y = element_text(size = 7, angle = 0, hjust = 0), axis.text.y = element_blank(), axis.title.y = element_blank(), axis.ticks.y = element_blank(), panel.border = element_blank() ) + scale_x_date(expand=c(0,0), date_breaks = "1 month", date_labels = "%b") + xlab('Date') + ggtitle('Average daily temperature in Copenhagen', 'from 1995 to 2019')
You can check out the full functionality of ggHoriPlot
in the following guides:
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