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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")
::install_github("rivasiker/ggHoriPlot") devtools
Load the libraries:
library(tidyverse)
library(ggHoriPlot)
library(ggthemes)
Load the dataset and calculate the cutpoints and origin:
::data(climate_CPH)
utils
<- climate_CPH %>%
cutpoints 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)
<- sum(range(cutpoints$AvgTemperature))/2
ori <- seq(range(cutpoints$AvgTemperature)[1],
sca range(cutpoints$AvgTemperature)[2],
length.out = 7)[-4]
round(ori, 2) # The origin
#> [1] 6.58
round(sca, 2) # The horizon scale cutpoints
#> [1] -12.11 -5.88 0.35 12.81 19.05 25.28
Build the horizon plots in ggplot2
using
geom_horizon()
:
%>% ggplot() +
climate_CPH 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:
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.