ggplot2 Time Series Heatmaps: revisited in the tidyverse
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I revisited my previous post on creating beautiful time series calendar heatmaps in ggplot, moving the code into the tidyverse. Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
To obtain following example:
Simply use the following code:
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# An simple function to turn an xts time series | |
# into a ggplot calendar heatmap | |
require(tidyverse) | |
# The core idea is to transform the data such that one can | |
# plot "Value" as a function of "WeekOfMonth" versus "DayOfWeek" | |
# and facet this Year versus Month | |
xts_heatmap <- function(x){ | |
data.frame(Date=as.Date(index(x)), x[,1]) %>% | |
setNames(c("Date","Value")) %>% | |
dplyr::mutate( | |
Year=lubridate::year(Date), | |
Month=lubridate::month(Date), | |
# I use factors here to get plot ordering in the right order | |
# without worrying about locale | |
MonthTag=factor(Month,levels=as.character(1:12), | |
labels=c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"),ordered=TRUE), | |
# week start on Monday in my world | |
Wday=lubridate::wday(Date,week_start=1), | |
# the rev reverse here is just for the plotting order | |
WdayTag=factor(Wday,levels=rev(1:7),labels=rev(c("Mon","Tue","Wed","Thu","Fri","Sat","Sun")),ordered=TRUE), | |
Week=as.numeric(format(Date,"%W")) | |
) %>% | |
# ok here we group by year and month and then calculate the week of the month | |
# we are currently in | |
dplyr::group_by(Year,Month) %>% | |
dplyr::mutate(Wmonth=1+Week-min(Week)) %>% | |
dplyr::ungroup() %>% | |
ggplot(aes(x=Wmonth, y=WdayTag, fill = Value)) + | |
geom_tile(colour = "white") + | |
facet_grid(Year~MonthTag) + | |
scale_fill_gradient(low="red", high="yellow") + | |
labs(x="Week of Month", y=NULL) | |
} | |
require(quantmod) | |
# Download some Data, e.g. the CBOE VIX | |
quantmod::getSymbols("^VIX",src="yahoo") | |
# lets see | |
xts_heatmap(Cl(VIX)) + labs(title="Heatmap of VIX") | |
# ok |
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