好的，所以我有这个data.frame：
A B C 1 yellow purple <NA> 2 <NA> <NA> yellow 3 orange yellow <NA> 4 orange <NA> brown 5 <NA> brown purple 6 yellow purple pink 7 purple green pink 8 yellow pink green 9 purple orange <NA> 10 purple <NA> brown
我有兴趣从第一列中获取所有缺失的值，并用其他列中的值替换它们，例如，以第2、4、5和10行为例。
A B C 1 yellow purple <NA> 2 yellow <NA> <NA> 3 orange yellow <NA> 4 orange brown <NA> 5 brown purple <NA> 6 yellow purple pink 7 purple green pink 8 yellow pink green 9 purple orange <NA> 10 purple brown <NA>
我的想法是循环遍历各列以获取缺少值的行，并用右侧列中的值替换它们，但这也可能存在缺陷，因为如果有4列，而第2和3列中有两个值，那该怎么办？不适用 有谁知道可能有效的算法？
我们可以遍历行并连接非NA元素和NA元素，然后将其分配回数据集
df[] <- t(apply(df, 1, function(x) c(x[!is.na(x)], x[is.na(x)]))) df # A B C #1 yellow purple <NA> #2 yellow <NA> <NA> #3 orange yellow <NA> #4 orange brown <NA> #5 brown purple <NA> #6 yellow purple pink #7 purple green pink #8 yellow pink green #9 purple orange <NA> #10 purple brown <NA>
df <- structure(list(A = c("yellow", NA, "orange", "orange", NA, "yellow", "purple", "yellow", "purple", "purple"), B = c("purple", NA, "yellow", NA, "brown", "purple", "green", "pink", "orange", NA ), C = c(NA, "yellow", NA, "brown", "purple", "pink", "pink", "green", NA, "brown")), .Names = c("A", "B", "C"), row.names = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10"), class = "data.frame")
