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as.numeric vs.chr_R - Fatal编程技术网
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as.numeric vs.chr

r

as.numeric vs.chr,r,R,我有以下代码 fig4 <- data.frame(chads=NA,age=NA,treatment=NA,mean=NA,lower=NA,upper=NA) fig4$chads <- as.factor(fig4$chads) levels(fig4$chads) <- c(0,1,2,3,4,5,6) fig4$age <- as.factor(fig4$age) levels(fig4$age ) <- c("u80","o80") fig4$treat

我有以下代码

fig4 <- data.frame(chads=NA,age=NA,treatment=NA,mean=NA,lower=NA,upper=NA)
fig4$chads <- as.factor(fig4$chads)
levels(fig4$chads) <- c(0,1,2,3,4,5,6)
fig4$age <- as.factor(fig4$age)
levels(fig4$age ) <- c("u80","o80")
fig4$treatment <- as.factor(fig4$treatment)
levels(fig4$treatment) <- c("OAC","OAP")
fig4$mean <- as.numeric(fig4$mean)
fig4$lower <- as.numeric(fig4$lower)
fig4$upper <- as.numeric(fig4$upper)

> str(fig4)
'data.frame':   1 obs. of  6 variables:
 $ chads    : Factor w/ 7 levels "0","1","2","3",..: NA
 $ age      : Factor w/ 2 levels "u80","o80": NA
 $ treatment: Factor w/ 2 levels "OAC","OAP": NA
 $ mean     : num NA
 $ lower    : num NA
 $ upper    : num NA
为什么数字向量会变成字符向量？

原因与矩阵相同——向量和矩阵只能包含一种类型。当你将角色强制加入混音时，你就得到了角色

使用data.frame保存不同类型的“列”，然后对单个列进行子集处理。

出于相同的原因，矩阵将保存向量和矩阵只能保存一种类型。当你将角色强制加入混音时，你就得到了角色

使用data.frame保存不同类型的“列”，然后对单个列进行子集。列表可以保存多种类型的对象，因此，为避免新数据转换为字符，可以执行以下操作：

fig4[nrow(fig4) + 1, ] <- list(6,"o80","OAC",0.1,0.02,0.25)

fig4[nrow（fig4）+1，]列表可以保存多种类型的对象，因此为了避免新数据转换为字符，您可以执行以下操作：


fig4[nrow(fig4) + 1, ] <- list(6,"o80","OAC",0.1,0.02,0.25)



fig4[nrow（fig4）+1，]

fig4[nrow(fig4) + 1, ] <- list(6,"o80","OAC",0.1,0.02,0.25)