Question

My data has multiple customers data with different start and end dates along with their sales data.So I did simple exponential smoothing. I applied the following code to apply ses

library(zoo)
library(forecast)

z <- read.zoo(data_set,FUN = function(x) as.Date(x) + seq_along(x) / 10^10 , index = "Date", split = "customer_id")
L <- lapply(as.list(z), function(x) ts(na.omit(x),frequency = 52))
HW <- lapply(L, ses)

Now my output class is list with uneven lengths.Can someone help me how to unnest or unlist the output in to a data frame and get the fitted values,actuals,residuals along with their dates,sales and customer_id. Note : the reson I post my input data rather than data of HW is,the HW data is too large. Can someone help me in R.

Answer 1

我将使用tidyverse软件包来解决此问题。

map(HW, ~ .x %>% 
      as.data.frame %>%             # convert each element of the list to data.frame
      rownames_to_column) %>%       # add row names as columns within each element
  bind_rows(.id = "customer_id")    # bind all elements and add customer ID

我不确定如何将日期和实际销售额与您的输出（HW）相关联。如果您对此进行了解释，我也可能会提供解决该问题的方法。

Answer 2

首先将所有唯一的customer_id放入名为“ k”的变量

 k <- unique(data_set$customer_id)

创建一个空的数据框

   b <- data.frame()

使用for循环提取所有拟合值并存储在'a'中。使用rbind函数将所有拟合值附加到数据框'b'

for(key in k){    
  print(a <- as.data.frame((as.numeric(HW_ses[[key]]$model$fitted))))
  b <- rbind(b,a)     
    }

最后使用列绑定功能将输入数据集附加到数据框'b'

data_set_final <- cbind(data_set,b)

Unnest a ts class

2 个答案: