这是一些玩具数据
x <- c("Bird","Bird","Tiger","Bird","Fish","grey","blue","orange","green","yellow","10","5","7","12","5","10","10","8","12","2","10","20","10","18","3")
m <- matrix(x,byrow = F,ncol = 5,nrow= 5)
m <- as.data.frame(m)
colnames(m) <- c("Animal","colour","length","height","weight")
y <- c("Tiger","Bird","Bird","colour","length","colour","orange","10","green","orange/black","12","light green")
new.m <- matrix(y,byrow=F,ncol=4,nrow = 3)
new.m <- as.data.frame(new.m)
colnames(new.m) <- c("Animal","attribute","value","new value")
如何使用数据框m有效地更新new.m中的值。最终结果应如下所示：
z <- c("Bird","Bird","Tiger","Bird","Fish","grey","blue","orange/black"," light green","yellow","12","5","7","12","5","10","10","8","12","2","10","20","10","18","3")
update.m <- matrix(z,byrow = F,ncol = 5,nrow= 5)
update.m <- as.data.frame(update.m)
colnames(update.m) <- c("Animal","colour","length","height","weight")
对于new.m中的固定行，我可以轻松实现此目的。但这可以通过综合而非基于行的方式来完成吗？
答案 0 :(得分：3)
通过基础R的一个想法。我们首先创建一个矩阵，其中包含我们需要更新值的列。我们使用match来更新值。 nomath条目生成NA，我们replace包含原始值并将其放回原始数据框中。
m3 <- sapply(m[c(2:3)], function(i) new.m$`new value`[match(i, new.m$value)])
m[c(2:3)] <- replace(m3, is.na(m3), m[c(2,3)][which(is.na(m3), arr.ind = TRUE)])
m
# Animal colour length height weight
#1 Bird grey 12 10 10
#2 Bird blue 5 10 20
#3 Tiger orange/black 7 8 10
#4 Bird light green 12 12 18
#5 Fish yellow 5 2 3