stat_calendar_heatmap: Plots a calendar heatmap

In Ather-Energy/ggTimeSeries: Time Series Visualisations Using the Grammar of Graphics

Description

A calendar heatmap provides context for weeks, and day of week and is a better way to visualise daily data than line charts.

Usage

stat_calendar_heatmap(mapping = NULL, data = NULL, show.legend = NA,
  inherit.aes = TRUE, na.rm = T, bandwidth = NULL, ...)

Arguments

mapping	mapping
data	df
show.legend	logical
inherit.aes	logical
na.rm	logical
bandwidth	bandwidth
...	more functions

Aesthetics

date, fill.

Data Tips

strftime can help extract the value of the year, week of year, and day of week from the date column. You might need to extract the year to facet multiple years as demonstrated in the example. This stat uses the following transformation to obtain the x and y coordinate to be used in the heatmap - data$x = 1 + as.integer(strftime(data$date, "%W")) data$y = as.integer(strftime(data$date, "%w")) data$y[data$y == 0L] = 7 data$y = 8 - data$y

Cosmetic Tips

The minimalist look can be achieved by appending the following chunk of code to the output object: + xlab(NULL) + ylab(NULL) + scale_fill_continuous(low = 'green', high = 'red') + theme( axis.text = element_blank(), axis.ticks = element_blank(), legend.position = 'none', strip.background = element_blank(), panel.background = element_blank(), panel.border = element_blank() )

Also See

ggplot_calendar_heatmap, a polished but less flexible alternative.

Examples

{
library(ggplot2)
DailyData = data.frame(
      DateCol = seq(
         as.Date("1/01/2014", "%d/%m/%Y"),
         as.Date("31/12/2015", "%d/%m/%Y"),
         "days"
      ),
      ValueCol = runif(730)
   )
   DailyData$Year = strftime(DailyData$DateCol, "%Y")
ggplot(
   DailyData,
   aes(
      date = DateCol,
      fill = ValueCol
   )
) +
   stat_calendar_heatmap() +
   facet_wrap(~Year, ncol = 1)}

Ather-Energy/ggTimeSeries documentation built on June 22, 2019, 2:55 a.m.