使用data.frame / list作为函数的参数进行映射

Question

简而言之，我有一个较大的函数，该函数创建data.frame，它们是较大data.frame的子集，并以该函数的参数命名。 它正在构建用于原始数据以及Holt-Winters的输出和预测输出的data.frames ...这意味着它正在创建多个data.frames。 下面是一个小示例（尽管这里没有足够的间隔来实际生成ts类data.frame）：

Group <- c("Primary_Group","Primary_Group","Primary_Group","Primary_Group","Primary_Group","Primary_Group","Secondary_Group","Secondary_Group","Secondary_Group","Secondary_Group","Secondary_Group","Secondary_Group","Tertiary_Group","Tertiary_Group","Tertiary_Group","Tertiary_Group","Tertiary_Group","Tertiary_Group")
Day <- c(1,2,3,1,2,3,1,2,3,1,2,3,1,2,3,1,2,3)
Type <- c("A","A","A","B","B","B","A","A","A","B","B","B","A","A","A","B","B","B")
Value <- c(7,3,10,3,9,4,0,9,3,10,1,6,3,4,10,2,3,1)
df <- as.data.frame(cbind(Group,Day,Type,Value))

Fun <- function(Group,Type, A, B, G){
    df <- Data[Data$Group== Group & Data$Type== Type, ]
    assign(paste(Group,Type,"_df",sep = ''), df, envir = parent.frame()) 
    df_holtwinters <- HoltWinters(ts(Data[Data$Group== Group & Data$Type== Type, ], 
                                  frequency = 365), alpha = A, beta = B, gamma = G)
    assign(paste(Group,Type,"_hw",sep = ''), df_holtwinters, envir = parent.frame()) 
}

您会注意到Group和Type是字符，而A，B，G是数字或NULL 。

如果我现在有一个由列表值组成的data.frame，如何最好地循环上述函数（可能使用mapply ）以使用第一行中每一列的值...然后使用第二行中的每一列，等等-创建多个数据框架。

argGroup <- c("Primary_Group","Primary_Group","Secondary_Group","Secondary_Group","Tertiary_Group","Tertiary_Group")
argType <- c("A","B","A","B","A","B")
argA <- c(NA, NA, NA, NA, NA, NA)
argB <- c(0.05, 0.05, NA, NA, NA, NULL)
argG <- c(NA, NA, NA, NA, NA, NA)

argGroup[is.na(argGroup)] <- list(NULL)
argType[is.na(argType)] <- list(NULL)
argA[is.na(argA)] <- list(NULL)
argB[is.na(argB)] <- list(NULL)
argG[is.na(argG)] <- list(NULL)

Arguments <- cbind(argType, argType, argA, argB, argG)

理想情况下，我将获得以下data.frames来生成...

Primary_Group_A_df
Primary_Group_A_hw
Primary_Group_B_df
Primary_Group_B_hw
Secondary_Group_A_df
Secondary_Group_A_hw
Secondary_Group_B_df
Secondary_Group_B_hw
Tertiary_Group_A_df
Tertiary_Group_A_hw
Tertiary_Group_B_df
Tertiary_Group_B_hw

这也将有助于了解如何最佳（最自动化的方式） rbind共同所有的_DF和所有的_hw在一起。

任何帮助将是惊人的，非常感谢。 非常感谢！

Answer 1

您将通过使用as.data.frame(cbind(...))丢失类型信息，只需直接使用data.frame即可：

Data <- data.frame(
  Group = rep(c("Primary_Group", "Secondary_Group", "Tertiary_Group"), each = 6L),
  Day = rep(1L:3L, 6L),
  Type = rep(rep(c("A", "B"), each = 3L), 3L),
  Value = c(7,3,10,3,9,4,0,9,3,10,1,6,3,4,10,2,3,1)
)

之后，我想您可以执行以下操作：

split_data <- split(Data, as.list(Data[, c("Group", "Type")]))
dfs <- do.call(rbind, split_data)

dfs_hw <- lapply(split_data, function(sub_data) {
  Map(argA, argB, argG, f = function(A, B, G) {
    HoltWinters(ts(sub_data, frequency = 365), alpha = A, beta = B, gamma = G)
  })
})

dfs_hw <- do.call(rbind, unlist(dfs_hw, recursive = FALSE))

但是我从HoltWinters收到一个错误，所以我不能肯定地说。 另外，我认为dfs只是再次具有Data ，只是重新排序。

Answer 2

避免用许多类似结构的对象充斥您的全局环境。 考虑使用诸如列表之类的容器来保存许多数据帧。 一种有用的方法是by一个或多个因素（例如“ 组”和“ 类型” ）对数据框进行子集化，以返回数据框列表。 另外，不要按行进行迭代，而是merge参数与数据merge ，以便每个子集传递一次参数。

具体来说，呼吁by两次DF和硬件列表。 但首先，按Group和Type合并df和Arguments数据帧。 一个挑战是NULL无法存储在数据帧中，因此请考虑保存"NULL"字符串并分配临时变量以传递到HW参数中。 不幸的是，这会将整个列转换为字符类型，对于非NULL值，您需要将其转换为as.numeric 。

合并

Group <- c("Primary_Group","Primary_Group","Secondary_Group","Secondary_Group",
           "Tertiary_Group","Tertiary_Group")
Type <- c("A","B","A","B","A","B")
argA <- c("NULL", "NULL", "NULL", "NULL", "NULL", "NULL")
argB <- c(0.05, 0.05, "NULL", "NULL", "NULL", "NULL")
argG <- c("NULL", "NULL", "NULL", "NULL", "NULL", "NULL")

Arguments <- data.frame(Group, Type, argA, argB, argG, stringsAsFactors=FALSE)
df <- merge(df, Arguments, by=c("Group", "Type"))

数据框列表 （具有命名的df元素）

# ORDER FOR NAMING LATER
df <- with(df, df[order(Type, Group),])

# DATAFRAME LIST
df_list <- by(df, df[c("Group", "Type")], identity)
# RENAME LIST
df_list <- setNames(df_list, unique(paste0(df$Group, "_", df$Type, "_df")))

# REFERENCE ELEMENTS
df_list$Primary_Group_A_df
df_list$Secondary_Group_A_df
df_list$Tertiary_Group_A_df
...

硬件列表 （带有命名的硬件元素）

# HW LIST
hw_list <- by(df, df[c("Group", "Type")], function(sub) {
  # CONDITIONALLY ASSIGN TEMP VARIABLES 
  # (BEING SUBSETS: max(arg*)==min(arg*)==mean(arg*)==median(arg*))
  if(!is.na(max(sub$argA)) & max(sub$argA) == "NULL") { tmpA <- NULL } 
  else { tmpA <- max(as.numeric(sub$argA)) }

  if(!is.na(max(sub$argB)) & max(sub$argB) == "NULL") { tmpB <- NULL } 
  else { tmpB <- max(as.numeric(sub$argB)) }

  if(!is.na(max(sub$argG)) & max(sub$argG) == "NULL") { tmpG <- NULL } 
  else { tmpG <- max(as.numeric(sub$argG)) }

  # PASS ARGS ONCE PER SUBSET 
  return(HoltWinters(ts(sub, frequency = 365), alpha=tmpA, beta=tmpB, gamma=tmpG))
})

# RENAME LIST
hw_list <- setNames(hw_list, unique(paste0(df$Group, "_", df$Type, "_hw")))

# REFERENCE ELEMENTS
hw_list$Primary_Group_A_hw
hw_list$Secondary_Group_A_hw
hw_list$Tertiary_Group_A_hw
...

输出 （使用3作为硬件频率以与发布的数据对齐）

> hw_list$Primary_Group_A_hw
Holt-Winters exponential smoothing with trend and additive seasonal component.

Call:
HoltWinters(x = ts(sub[c("Group", "Day", "Type", "Value")], frequency = 3),     alpha = tmpA, beta = tmpB, gamma = tmpG)

Smoothing parameters:
 alpha: 0.2169231
 beta : 0.05
 gamma: 0.1

Coefficients:
          [,1]
a   2.89129621
b   0.08783715
s1  0.54815382
s2 -0.12485260
s3  0.21087038

> hw_list$Secondary_Group_A_hw
Holt-Winters exponential smoothing with trend and additive seasonal component.

Call:
HoltWinters(x = ts(sub[c("Group", "Day", "Type", "Value")], frequency = 3),     alpha = tmpA, beta = tmpB, gamma = tmpG)

Smoothing parameters:
 alpha: 0.752124
 beta : 0
 gamma: 0

Coefficients:
            [,1]
a   3.691664e+00
b   3.333333e-01
s1  3.333333e-01
s2 -1.480388e-16
s3 -3.333333e-01

> hw_list$Tertiary_Group_A_hw
Holt-Winters exponential smoothing with trend and additive seasonal component.

Call:
HoltWinters(x = ts(sub[c("Group", "Day", "Type", "Value")], frequency = 3),     alpha = tmpA, beta = tmpB, gamma = tmpG)

Smoothing parameters:
 alpha: 0.3145406
 beta : 0
 gamma: 0

Coefficients:
            [,1]
a   3.022946e+00
b  -3.333333e-01
s1 -3.333333e-01
s2 -1.480388e-16
s3  3.333333e-01