R-使用dplyr mutate分配总数的一部分

我有一套5G移动基础设施用于服务不同邮政编码地区的成本数据：

observation <- c(1:10)
pop.d.rank  <- c(1:10)
cost  <- c(101:110)
all <- data.frame(observation,pop.d.rank,cost) 

---

observation您可以使用
transform

all <- transform(all, 
          capital_allocated.5G = diff(c(0, pmin(cumsum(cost), annual.investment))))
all <- transform(all,
                 capital_percentage.5G = capital_allocated.5G / cost * 100)

此外，如果您删除
group\u by（pop.d.rank）
您可以使用
transform

all <- transform(all, 
          capital_allocated.5G = diff(c(0, pmin(cumsum(cost), annual.investment))))
all <- transform(all,
                 capital_percentage.5G = capital_allocated.5G / cost * 100)

此外，如果删除
groupby（pop.d.rank）

observation <- c(1:10)
pop.d.rank  <- c(1:10)
cost  <- c(101:110)
capital_allocated.5G <- c(101, 102, 103, 104, 90, 0, 0, 0, 0, 0)
capital_percentage.5G <- c(100, 100, 100, 100, 86, 0, 0, 0, 0, 0)
example.output <- data.frame(observation,pop.d.rank,cost, capital_allocated.5G, capital_percentage.5G) 

all <- transform(all, 
          capital_allocated.5G = diff(c(0, pmin(cumsum(cost), annual.investment))))
all <- transform(all,
                 capital_percentage.5G = capital_allocated.5G / cost * 100)

all <- with(all,{
    capital_allocated.5G = diff(c(0, pmin(cumsum(cost), annual.investment)))
    capital_percentage.5G = capital_allocated.5G / cost * 100
    return(cbind(all, capital_allocated.5G,
                 capital_percentage.5G))
})

##   observation pop.d.rank cost capital_allocated.5G capital_percentage.5G
## 1            1          1  101                  101             100.00000
## 2            2          2  102                  102             100.00000
## 3            3          3  103                  103             100.00000
## 4            4          4  104                  104             100.00000
## 5            5          5  105                   90              85.71429
## 6            6          6  106                    0               0.00000
## 7            7          7  107                    0               0.00000
## 8            8          8  108                    0               0.00000
## 9            9          9  109                    0               0.00000
## 10          10         10  110                    0               0.00000