algorithm - 在子集中包括for循环

我想计算两艘船装载集装箱的周平均值。一艘船星期天航行，另一艘船星期三航行我有一个带有预订的大excel文件。我将在以下链接中加载此文件的一小部分：https://docs.google.com/spreadsheets/d/1BxHTClTkrQzIzZzG5vXXnvKtV0_az83PGJ2ghBaAQr0/edit?usp=sharing
第一艘船得到的集装箱应在星期一（Mo）、星期二（Di）和星期三（Mi）交付第二艘船应于星期四（Do）、星期五（Fr）、星期六（Sa）和星期日（So）在另一港口交货数据包含了从2017-01-01到2018-07-31的集装箱信息。整整82周我想做一个长度为82的向量，每一个数字都是该周的容器总数例如，向量的第一个数字应该是第一周的星期一、星期二和星期三的集装箱需求所以，我想创建一个向量，每艘船一个，包含关于这艘船上应该装载的集装箱数量的信息。一个82周的向量，看看我们的需求量和平均值是多少周。
有人能帮我吗？

Here is the beginning of my code:

 containers <- "https://docs.google.com/spreadsheets/d/1BxHTClTkrQzIzZzG5vXXnvKtV0_az83PGJ2ghBaAQr0/edit?usp=sharing"

#Containers between Rotterdam and Duisburg
containersRTMDUI <- subset(containers, containers$Laadhaven == "Rotterdam" & containers$Loshaven == "Duisburg")

#I used to do this in subsets, because I could not make a loop
Week1 <- subset(containersRTMDUI, containersRTMDUI$Datum1 >= "2017-01-02" &
containersRTMDUI$Datum1 < "2017-01-09" & containersRTMDUI$Dag1 = "Mo" &
containersRTMDUI$Dag1 = "Di" &containersRTMDUI$Dag1 = "Mi")
Week2 <- subset(etc..)

当然，困难的一点来自这样一个事实：在某些日子里没有需求。

最佳答案

我想我明白了。使用data.table的一种方法：

# read in data as a data.table
    library(data.table)
    dt <- data.table(read.csv("path/to/file", stringsAsFactors = F))

# rename variables to english (
# there are shorter ways to do this, but I like to keep track)
    setnames(dt, old = "ISO",          new = "containter_type")
    setnames(dt, old = "F.E",          new = "full_empty")
    setnames(dt, old = "Gewicht",      new = "weight")
    setnames(dt, old = "Laadhaven",    new = "pickup_port")
    setnames(dt, old = "Laadterminal", new = "pickup_terminal")
    setnames(dt, old = "Loshaven",     new = "dropoff_port")
    setnames(dt, old = "Losterminal",  new = "dropoff_terminal")
    setnames(dt, old = "Datum1",       new = "pickup_date")
    setnames(dt, old = "Dag1",         new = "pickup_dow")
    setnames(dt, old = "Datum2",       new = "dropoff_date")
    setnames(dt, old = "Dag2",         new = "dropoff_dow")

# convert date variable to date-type (instead of factor/string)
    dt[ , pickup_date  := as.Date(pickup_date,  "%d.%m.%Y")]
    dt[ , dropoff_date := as.Date(dropoff_date, "%d.%m.%Y")]

# create a week variable
    dt[ , week := lubridate::week(pickup_date)]

# create a variable (MTW) by day-of-week
# MTW=1 for mon, tues, wed; MTW=0 for thurs, fri, sat, sun
    dt[ , MTW := pickup_dow %in% c("Mo", "Di", "Mi")]

# count the number of rows by week and MTW
    result <- dt[ , .(nrows = .N), by=.(week, MTW)]

# print result
    result

# fill in 0 weeks
    dt2 <- data.table(week = rep(1:7, each=2), MTW = rep(c(T,F), each=7))
    result <- merge(result, dt2, by=c("week", "MTW"), all=T)
    result[is.na(nrows), nrows := 0]

# print updated result
    result