Question

这是我的数据文件。

Location.Name   Item.Description    Sort.In.Date    OrderedQty
HC Overijse     Pro B 731           7/1/2015        2
HC Overijse     Pro B 731           8/3/2015        2
HC Overijse     Pro B 931           8/27/2015       1
HC Overijse     Pro B 933           6/24/2015       2
HC Overijse     Pro B 933           7/22/2015       2
HC Overijse     Pro B 933           7/29/2015       1
HC Overijse     Pro R 731           6/16/2015       2
HC Overijse     Pro R 731           8/3/2015        2
Hannah Thieuw   Pro B 933           7/14/2015       2
Hannah Thieuw   Pro R 731           8/14/2015       2
HC Asse         Pro B 731           6/12/2015       2
HC Asse         Pro B 931           6/12/2015       2
HC Asse         Pro B 933           6/4/2015        2
HC Asse         Pro R 731           6/8/2015        2
HC Asse         Pro R 731           6/10/2015       2
HC Asse         Pro R 731           6/17/2015       2
HC Asse         Pro R 731           7/9/2015        2
HC Asse         Pro R 731           7/27/2015       2
HC Asse         Pro R 732           6/16/2015       2

我的问题是如何计算6/1 / 20105-> 2015年8月31日期间（没有周末）的每日/每周平均订购数量。每个位置和每个产品。所以我必须找到一种方法将零插入数据集来计算平均值。（这将是一个小值）。我还需要展台开发。我使用此代码计算每个订单的平均orderdQty和2个订单之间的时间。

fe <- fe[order(fe$Item.Description,fe$Location.Name,fe$Sort.In.Date), ]
sfe<-dlply(fe, .(fe$Item.Description,fe$Location.Name))

fe$DayBetween <- unlist(sapply(seq_along(sfe), function(x)          diff(as.Date(c(NA, as.Date(sfe[[x]][,3] ,  format="%d/%m/%Y") ))) ))


FilteredExport<-fe
remove(fe)

results<-ddply(FilteredExport, .(Location.Code,Location.Name,Item.Description),summarize,
               N=length(Item.Description), AverageQty = mean(OrderedQty),sdAverageQty=sd(OrderedQty) , AvgTimeBetweenOrder = mean(DayBetween,na.rm=TRUE),sdAvgTimeBetweenOrder=sd(DayBetween,na.rm=TRUE))

以下是我的数据输入：

structure(list(Location.Name = c("HC Overijse", "HC Overijse", 
"HC Overijse", "HC Overijse", "HC Overijse", "HC Overijse", "HC Overijse", 
"HC Overijse", "Hannah Thieuw", "Hannah Thieuw", "HC Asse", "HC Asse", 
"HC Asse", "HC Asse", "HC Asse", "HC Asse", "HC Asse", "HC Asse", 
"HC Asse"), Item.Description = c("Pro B 731", "Pro B 731", "Pro B 931", 
"Pro B 933", "Pro B 933", "Pro B 933", "Pro R 731", "Pro R 731", 
"Pro B 933", "Pro R 731", "Pro B 731", "Pro B 931", "Pro B 933", 
"Pro R 731", "Pro R 731", "Pro R 731", "Pro R 731", "Pro R 731", 
"Pro R 732"), Sort.In.Date = structure(c(16617, 16650, 16674, 
16610, 16638, 16645, 16602, 16650, 16630, 16661, 16598, 16598, 
16590, 16594, 16596, 16603, 16625, 16643, 16602), class = "Date"), 
    OrderedQty = c(2L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L)), .Names = c("Location.Name", 
"Item.Description", "Sort.In.Date", "OrderedQty"), row.names = c(NA, 
-19L), class = "data.frame")

Answer 1

List<State> getNeighbors(State s) {
    List<State> neighbors = new ArrayList<State>();
    for (Brick b : s.bricks) {
         // if you can move the brick up
         // create new state new_state_up as you update 'a'
         // and 'bricks' and simply add it to neighbors.
         // do the same for the rest of the directions
    }
    return neighbors;
}

在每个产品和商店的数据框中插入缺少的日期

1 个答案: