如何将上一年和当年的时间序列安排到一个ggplot中？

Question

我的时间序列从2015-01-01开始到Sys.time()

我想制作一个情节，我将两者相互比较：

原因是产生一个总体情节，显示按小时和工作日平均的值，以便比较上一年和当前年份：

library(dplyr)
library(lubridate)
library(ggplot2)
# Some data
start.date <- as.POSIXct('2015-01-01')
end.date <-  Sys.time()
tseq <- seq(start.date, end.date, by = "hours")
data <- sample(1:10,length(tseq),replace = T)
sales<- cumsum(rnorm(length(tseq), mean=data, sd=sqrt(data)))
df<- cbind.data.frame(tseq,sales)
head(df)
# spitting date to days in week
df$week_days<-as.numeric(format(df$tseq, "%w"))
# spitting date to days in hours
df$hours<-as.numeric(format(df$tseq, "%H"))



# subset from 2015-01-01 to Current timestamp - 365 days
my_interval<- Sys.time()-1 -dyears(1)

df_15 <- df %>% filter(tseq < my_interval)

my_plot15=aggregate(sales ~ + hours + week_days, data =df_15, FUN=mean)


ggplot(my_plot15, aes(hours, sales, group=week_days, col=week_days)) + 
  geom_line() +
  geom_point()+
  ylab("Avgvalue")+
  xlab("Hours")+
  ggtitle("Average sales by hour and month 2015") + 
  theme_bw()

# from 2016 to Current timestamp 

# subset from 2015-01-01 to Current timestamp - 365 days

df_16 <- df %>% filter(tseq >= '2016-01-01')

my_plot16=aggregate(sales ~ + hours + week_days, data =df_16, FUN=mean)


ggplot(my_plot16, aes(hours, sales, group=week_days, col=week_days)) + 
  geom_line() +
  geom_point()+
  ylab("Avgvalue")+
  xlab("Hours")+
  ggtitle("Average sales by hour and month 2016") + 
  theme_bw()

如何将它们整理成一个图？

Answer 1

如果您将数据合并到一个数据框中，则可以通过facet_wrap()：

使用分面

my_plot15$year <- 2015
my_plot16$year <- 2016

my_plot <- rbind(my_plot15, my_plot16)

ggplot(my_plot, aes(hours, sales, group=week_days, col=week_days)) + 
  geom_line() +
  geom_point()+
  facet_wrap(~year, ncol=1, scales = "free_y") +
  ylab("Avgvalue")+
  xlab("Hours")+
  ggtitle("Average sales by hour and month 2016") + 
  theme_bw()

Answer 2

给出数据的每小时性质，我建议使用雷达图。请注意，对于实际的连续时间数据，这应该看起来要好得多，因为从第23小时到0会看起来好多了。

大量借鉴here。

coord_radar <- function (theta = "x", start = 0, direction = 1) 
{
    theta <- match.arg(theta, c("x", "y"))
    r <- if (theta == "x") 
        "y"
    else "x"
    ggproto("CordRadar", CoordPolar, theta = theta, r = r, start = start, 
        direction = sign(direction),
        is_linear = function(coord) TRUE)
}

做一些数据准备：

# Get 2016 at the mean of 2015
my_plot16$sales <- my_plot16$sales - mean(my_plot16$sales) + mean(my_plot15$sales)

complete <- bind_rows('2015' = my_plot15, '2016' = my_plot16, .id = 'year')
complete$week_days <- factor(complete$week_days, 
                             labels = c('M', 'Tu', 'W', 'Th', 'F', 'Sa', 'Su'))

简介：

ggplot(complete, aes(x = hours, y = sales, group = year, color = year)) +
  geom_polygon(fill = NA, size = 2, show.legend = FALSE) +
  geom_line(size = 2) +
  facet_wrap(~week_days) +
  coord_radar() +
  theme_minimal()