将函数应用于多个数据集

Question

*当变量(Age、Age2和Mspline(为矢量格式时，以下函数有效

Age<-c(2,2.1,2.2,3.4,3.5,4.2,4.7,4.8,5,5.6,NA, 5.9, NA)
Age2<-seq(2,20,0.25)    
Mspline<-rnorm(73)
res <- lapply(1:length(Age), (x){
lwr_ind <- max(which(Age2 <= Age[x]))
upr_ind <- min(which(Age2 >= Age[x]))
data.frame(Age = Age[x], 
Mspline = Mspline[lwr_ind] + ((Age[x]-Age2[lwr_ind])/0.25)*(Mspline[lwr_ind] - Mspline[upr_ind]))
})
res <- do.call(rbind, res)

我想知道当我们有两个数据集df1和df2，Age、Age2和Mspline是两个数据集中的变量时，我们如何修改上面的函数：*

Age<-c(2,2.1,2.2,3.4,3.5,4.2,4.7,4.8,5,5.6,NA, 5.9, NA)
R<-c(2,2.1,2.2,3.4,3.5,4.2,4.7,4.8,5,5.6,NA, 5.9, NA)
df1<-data.frame(Age,R)
# Second data:
Age2<-seq(2,20,0.25)    
Mspline<-rnorm(73)
df2<-data.frame(Age2, Mspline)

Answer 1

# with vector input data...
set.seed(1234)
Age <- c(2, 2.1, 2.2, 3.4, 3.5, 4.2, 4.7, 4.8, 5, 5.6, NA, 5.9, NA)
Age2 <- seq(2, 20, 0.25)    
Mspline <- rnorm(73)
res <- lapply(1:length(Age), (x){
lwr_ind <- max(which(Age2 <= Age[ x ]))
upr_ind <- min(which(Age2 >= Age[ x ]))
data.frame(Age = Age[ x ], 
Mspline = Mspline[ lwr_ind ] + 
((Age[ x ] - Age2[ lwr_ind ]) / 0.25) * 
(Mspline[ lwr_ind ] - Mspline[ upr_ind ]))
})
res1 <- do.call(rbind, res)
# with data.frame input data...
Age <- c(2, 2.1, 2.2, 3.4, 3.5, 4.2, 4.7, 4.8, 5, 5.6, NA, 5.9, NA)
R <- rnorm(13)
df1 <- data.frame(Age, R)
Age2 <- seq(2,20,0.25)
df2 <- data.frame(Age2, Mspline)
res2 <- lapply(1:nrow(df1), (x){
age <- df1[ x, 'Age' ]
age2 <- df2[ , 'Age2' ]
R <- df1[ x, 'R' ]
lwr_ind <- max(which(age2 <= age))
upr_ind <- min(which(age2 >= age))
data.frame(Age = age, 
Mspline = df2[ lwr_ind, 'Mspline' ] + 
((age - df2[ lwr_ind, 'Age2' ]) / 0.25) * 
(df2[ lwr_ind, 'Mspline' ] - df2[ upr_ind, 'Mspline' ]),
R)
})
res2 <- do.call(rbind, res2)
identical(res1, res2[ , 1:2 ])

[1] TRUE