Question

我想计算ds $ date_fixed和ds $ date_broken之间的平均燃烧时间（燃烧时间$ hours_burned）。我知道我可以使用下面的代码来计算：

ds$average_burninghours <- sapply (interval(ds$date_fixed, ds$date_broken), function(i)                                
                            mean (burning_hours$hours_burned[burning_hours$date%within%i]))

但我想根据位置和位置计算burning_hours。所以，我想添加一些代码看lke：'group_by = c（location，position）'，但我无法做到这一点。有人对此有想法吗？

示例代码：

ds <- data.frame( date_fixed= c("16-3-2015", "19-3-2015", "21-3-2015"), 
                     date_broken = c("18-3-2015", "22-3-2015", "24-3-2015"), 
                     location = c("A", "B", "B"), position = c("1", "2", "2"))

burning_hours <- data.frame(date = c("16-3-2015", "16-3-2015", "17-3-2015", "17-3-2015", 
                          "18-3-2015", "18-3-2015", "19-3-2015", "19-3-2015", "20-3-2015",
                          "20-3-2015", "21-3-2015", "21-3-2015", "22-3-2015", "22-3-2015",
                          "23-3-2015", "23-3-2015", "24-3-2015", "24-3-2015"), 
                           hours_burned= c("10", "11"), location = c("A", "B"), 
                           position = c("1", "2"))

期望的结果：

     date_fixed date_broken location position avg_burninghours
     16-3-2015  18-3-2015    A         1         10
     19-3-2015  22-3-2015    B         2         11
     21-3-2015  24-3-2015    B         2         11

Answer 1

合并两个数据帧，然后合并子集。

library(dplyr)
library(lubridate)

#Cleaning
ds$date_fixed <- dmy(ds$date_fixed)
ds$date_broken <- dmy(ds$date_broken)
burning_hours$date <- dmy(burning_hours$date)
burning_hours$hours_burned <- as.numeric(as.character(burning_hours$hours_burned))

df <- merge(burning_hours,ds,by = c('location','position'))

df %>%
    group_by(date_fixed,date_broken,location,position) %>%
    filter(date >= date_fixed,date <= date_broken) %>%
    summarise(avg_burninghours = mean(hours_burned))

给出了：

  date_fixed date_broken location position avg_burninghours
      (date)      (date)   (fctr)   (fctr)            (dbl)
1 2015-03-16  2015-03-18        A        1               10
2 2015-03-19  2015-03-22        B        2               11
3 2015-03-21  2015-03-24        B        2               11

计算r中每个位置的时间段（来自另一个数据集）的平均值

1 个答案: