我们平常的日历也可以当作可视化工具，适用于显示不同时间段，以及活动事件的组织情况。时间段通常以不同单位显示，例如日、周、月和年。今天我们最常用的日历形式是公历，每个月份的月历由7个垂直列组成（代表每周7天），如图所示。
日历图的主要可视化形式有如图6-2-2所示的两种：以年为单位的日历图（见图6-2-2 (a)）和以月为单位的日历图（见图6-2-2 (b)）。日历图的数据结构一般为(Date,Value)，将Value按照Date（日期）在日历上展示，其中Value映射到颜色。
1. ggTimeSeries绘图
R中ggTimeSeries 包[1]的ggplot_calendar_heatmap()函数可以绘制如图6-2-2(a)所示的日历图，但是不能设定日历图每个时间单元的边框格式。
使用stat_calendar_heatmap()函数和ggplot2包的ggplot()函数可以调整日历图每个时间单元的边框格式，具体代码如下所示。其关键是使用as.integer(strftime())日期型处理组合函数获取某天对应所在的年份、月份、周数等数据信息。
代码语言：javascript复制#setwd("D:/R/working_documents1")
library(ggplot2)
library(data.table) # 数据格式依赖
library(ggTimeSeries)
library(RColorBrewer)# 构造随机数据
set.seed(2134)
dat <- data.table(
date = seq(as.Date("2016-01-01"), as.Date("2019-12-31"), "days"),
ValueCol = runif(1461)
)
dat[, ValueCol := ValueCol (strftime(date, "%u") %in% c(6,7)*runif(1)*0.75)
][, ValueCol := ValueCol (abs(as.numeric(strftime(date, "%m")) - 6.5))*runif(1)*0.75
][, ':='(Year = as.integer(strftime(date, "%Y")), # add new column
month = as.integer(strftime(date, "%m")),
week = as.integer(strftime(date, "%W")))] # 添加列
MonthLabels <- dat[, list(meanWkofYr = mean(week)), by = c("month")
][, month := month.abb[month]]ggplot(data = dat, aes(date = date, fill = ValueCol))
stat_calendar_heatmap()
scale_fill_gradientn(colours = rev(brewer.pal(11, "Spectral")))
scale_y_continuous(name = NULL,
breaks = seq(7, 1, -1),
labels = c("Mon", "Tue", "Wed",
"Thu", "Fri", "Sat", "Sun"))
scale_x_continuous(name = NULL,
breaks = MonthLabels$meanWkofYr,
labels = MonthLabels$month,
expand = c(0,0))
facet_wrap(~Year, ncol = 1, strip.position = "right")
theme(panel.background = element_blank(),
panel.border = element_blank(),
strip.background = element_blank(),
strip.text = element_text(size = 13, face = "plain", color = "black"),
axis.line = element_line(colour = "black", size = 0.25),
axis.title = element_text(size = 10, face = "plain", color = "black"),
axis.text = element_text(size = 10, face = "plain", color = "black"))
2.geom_tile()
使用R中ggplot2包的geom_tile()函数，借助facet_wrap()函数分面，就可以绘制如图6-2-2(b)所示的以月为单位的日历图，具体代码如下所示。
代码语言：javascript复制label_mons <- c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul",
"Aug", "Sep", "Oct", "Nov", "Dec")
label_wik <- c("Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun")
dat19 <- dat[Year == 2017, list(date, ValueCol, month, week)
][, ':='(weekday = as.integer(strftime(date, "%u")), # 周数
yearmonth = strftime(date, "%m%Y"), # 月数
day = strftime(date, "%d")) # 天数
][, ':='(monthf = factor(x = month, levels = as.character(1:12),
labels = label_mons, ordered = TRUE),
weekdayf = factor(x = weekday, levels = 1:7,
labels = label_wik, ordered = TRUE),
yearmonthf = factor(x = yearmonth))
][, ':='(monthweek = 1 week - min(week)), by = .(monthf)] # 分组聚合label_mons <- c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul",
"Aug", "Sep", "Oct", "Nov", "Dec")
label_wik <- c("Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun")
dat19 <- dat[Year == 2017, list(date, ValueCol, month, week)
][, ':='(weekday = as.integer(strftime(date, "%u")), # 周数
day = strftime(date, "%d")) # 天数
][, ':='(monthf = factor(x = month, levels = as.character(1:12),
labels = label_mons, ordered = TRUE),
weekdayf = factor(x = weekday, levels = 1:7,
labels = label_wik, ordered = TRUE))
][, ':='(monthweek = 1 week - min(week)), by = .(monthf)] # 分组聚合ggplot(dat19, aes(weekdayf, monthweek, fill = ValueCol))
geom_tile(color = "white")
geom_text(aes(label = day), size = 3)
scale_fill_gradientn(colours = rev(brewer.pal(11, "Spectral")))
facet_wrap(~monthf, nrow = 3)
scale_y_reverse(name = "Week of the month")
xlab("Day")
theme(strip.text = element_text(size = 11, face = "plain", color = "black"),
panel.grid = element_blank())
感谢誉辉优化《R语言数据可视化之美》关于热力日历图的代码
参考：
[1] ggTimeSeries 包的参考网址：http://www.ggplot2-exts.org/ggTimeSeries.html
