fragile

install.packages("readxl")
library(readxl)
setwd("E:\\R4D")
data = read_excel("test.xlsx",sheet = 1) #读取数据
data[,3 : 50] <- lapply(data[, 3 : 50], as.numeric) # 转换数据，指定列
warnings() # 知道数据有问题
data = as.data.frame(lapply(data,as.numeric))
options(digits = 16) # 设置加小数点16位数
sum(is.na(data$v1_1_1))
sum(is.na(data))
which(rowSums(is.na(data))==0) # 查看哪一行有缺失值，发现几乎都有
which(colSums(is.na(data))==0) # 查看哪一列有缺失值
data1 <- data[-1883, -2]
dwt <- data[1,] # 权重单独作为一个数据
data1 <- data1[-1, ] # 删掉权重行，构建整洁格式数据
data2 <- transform(data1, 
			w1_1_1 == dwt$v1_1_1)



if(data1$v1_1_1 == 0 & data1$v1_1_2 != 0) {
  data1$v1_1 <- data1$v1_1_2 * (dwt$v1_1_2 / dwt$v1_1_2)
} else if(data1$v1_1_2 == 0 & data1$v1_1_1 != 0) {
  data1$v1_1 <- data1$v1_1_1 * (dwt$v1_1_1 / dwt$v1_1_1)
} else {
  data1$v1_1 <- (data1$v1_1_1 * (dwt$v1_1_1 / dwt$v1_1_1 +  dwt$v1_1_2)) +(data1$v1_1_2 * (dwt$v1_1_2 / dwt$v1_1_1 +  dwt$v1_1_2))
}