循环清理 table，其中观察值存储为列

Question

我有一个 table，它按以下方式在 x 列中存储观察结果，在 y 列中存储变量名称。

我正在尝试编写一个 R 循环来创建一个矩阵，其中每个观察值是一行，每个变量是一列。

问题是并不是所有的观测值都有所有的变量。

原始数据：

x	y
Apple	Fruit
Austria	Origin
Summer	Season
Orange	Fruit
Spain	Origin
Pear	Fruit
Tomato	Fruit
Italy	Origin
Summer	Season

期望输出：

Fruit	Origin	Season
Apple	Austria	Summer
Orange	Spain
Pear
Tomato	Italy	Summer

我目前的思路（伪R代码）：

df_old <- data.frame( x = c( "Apple", "Austria", "Summer", "Orange", "Spain", "Pear", "Tomato", "Italy", "Summer" ),
                      y = c( "Fruit", "Origin", "Season", "Fruit", "Origin", "Fruit", "Fruit", "Origin", "Season" ) )

df_new <- data.frame( matrix( ncol = 3, nrow = 0 ) )
colnames( df_new ) <- c( "Fruit", "Origin", "Season")

for ( i in seq_along( df_old ) ) {
  if ( y == "Fruit" ) {
    # add new row
    df_new$Fruit <- df_old$x
  } else if ( y == "Origin" ) {
    df_new$Origin <- df_old$x
  } else ( y == "Season" ) {
    df_new$Season <- df_old$x
  }
}

感谢您的帮助。

Answer 1

这是一个基于您使用 for-loop 给出的想法的解决方案。

df_old <- data.frame( x = c( "Apple", "Austria", "Summer", "Orange", "Spain", "Pear", "Tomato", "Italy", "Summer" ),
                          y = c( "Fruit", "Origin", "Season", "Fruit", "Origin", "Fruit", "Fruit", "Origin", "Season" ) ,stringsAsFactors=F)
    
    
df_new <- as.data.frame(matrix(NA, nrow=sum(df_old$y == "Fruit"), ncol=length(unique(df_old$y))))
names(df_new) <- c("Fruit", "Origin", "Season")


j <- 0
for (i in 1:(nrow(df_old))){
  print(df_old$y[i])
  if (df_old$y[i] == "Fruit") { j <- j + 1 ; df_new$Fruit[j] <-  df_old$x[i]
    print("new colum")
    if ((df_old$y[i+1] == "Origin")){ df_new$Origin[j] <-  df_old$x[i+1] }
    print("add origin")
    if ((df_old$y[i+1] == "Season") |  (df_old$y[i+2] == "Season")){
      df_new$Season[j] <-  df_old$x[c(i+1,i+2)][df_old$y[c(i+1,i+2)] == "Season"]
      print("add Season")
    }
  }
}

循环清理 table，其中观察值存储为列

Loop to clean up table where observations are stored as column

r

data-cleaning