如何对R中的for循环进行矢量化
我正在尝试清理这段代码,想知道是否有人对如何在R中不使用循环运行这段代码有任何建议。我有一个名为data的数据集,包含100个变量和200000个观察值。我想做的是将每个观测值乘以一个特定的标量来扩展数据集,然后将数据组合在一起。最后,我需要一个包含800000个观察值(我要创建四个类别)和101个变量的数据集。这是我写的一个循环,它可以做到这一点,但是它效率很低,我想要更快、更高效的东西如何对R中的for循环进行矢量化,r,for-loop,vectorization,R,For Loop,Vectorization,我正在尝试清理这段代码,想知道是否有人对如何在R中不使用循环运行这段代码有任何建议。我有一个名为data的数据集,包含100个变量和200000个观察值。我想做的是将每个观测值乘以一个特定的标量来扩展数据集,然后将数据组合在一起。最后,我需要一个包含800000个观察值(我要创建四个类别)和101个变量的数据集。这是我写的一个循环,它可以做到这一点,但是它效率很低,我想要更快、更高效的东西 datanew <- c() for (i in 1:51){ for (k in 1:6){
datanew <- c()
for (i in 1:51){
for (k in 1:6){
for (m in 1:4){
sub <- subset(data,data$var1==i & data$var2==k)
sub[,4:(ncol(sub)-1)] <- filingstat0711[i,k,m]*sub[,4:(ncol(sub)-1)]
sub$newvar <- m
datanew <- rbind(datanew,sub)
}
}
}
datanew您可以尝试以下方法。请注意,我们将前两个for循环替换为对mappy
的调用,将第三个for循环替换为对lappy的调用。
另外,我们正在创建两个向量,我们将组合它们进行向量化乘法
# create a table of the i-k index combinations using `expand.grid`
ixk <- expand.grid(i=1:51, k=1:6)
# Take a look at what expand.grid does
head(ixk, 60)
# create two vectors for multiplying against our dataframe subset
multpVec <- c(rep(c(0, 1), times=c(4, ncol(mydf)-4-1)), 0)
invVec <- !multpVec
# example of how we will use the vectors
(multpVec * filingstat0711[1, 2, 1] + invVec)
# Instead of for loops, we can use mapply.
newdf <-
mapply(function(i, k)
# The function that you are `mapply`ing is:
# rbingd'ing a list of dataframes, which were subsetted by matching var1 & var2
# and then multiplying by a value in filingstat
do.call(rbind,
# iterating over m
lapply(1:4, function(m)
# the cbind is for adding the newvar=m, at the end of the subtable
cbind(
# we transpose twice: first the subset to multiply our vector.
# Then the result, to get back our orignal form
t( t(subset(mydf, var1==i & mydf$var2==k)) *
(multpVec * filingstat0711[i,k,m] + invVec)),
# this is an argument to cbind
"newvar"=m)
)),
# the two lists you are passing as arguments are the columns of the expanded grid
ixk$i, ixk$k, SIMPLIFY=FALSE
)
# flatten the data frame
newdf <- do.call(rbind, newdf)
#使用“expand.grid”创建i-k索引组合表`
ixk请帮助我们帮助您,(1)发布一些样本数据,(2)用文字说明您希望在这里完成的工作。还请注意,您不需要引用您正在子集
中设置的data.frame。
# create a table of the i-k index combinations using `expand.grid`
ixk <- expand.grid(i=1:51, k=1:6)
# Take a look at what expand.grid does
head(ixk, 60)
# create two vectors for multiplying against our dataframe subset
multpVec <- c(rep(c(0, 1), times=c(4, ncol(mydf)-4-1)), 0)
invVec <- !multpVec
# example of how we will use the vectors
(multpVec * filingstat0711[1, 2, 1] + invVec)
# Instead of for loops, we can use mapply.
newdf <-
mapply(function(i, k)
# The function that you are `mapply`ing is:
# rbingd'ing a list of dataframes, which were subsetted by matching var1 & var2
# and then multiplying by a value in filingstat
do.call(rbind,
# iterating over m
lapply(1:4, function(m)
# the cbind is for adding the newvar=m, at the end of the subtable
cbind(
# we transpose twice: first the subset to multiply our vector.
# Then the result, to get back our orignal form
t( t(subset(mydf, var1==i & mydf$var2==k)) *
(multpVec * filingstat0711[i,k,m] + invVec)),
# this is an argument to cbind
"newvar"=m)
)),
# the two lists you are passing as arguments are the columns of the expanded grid
ixk$i, ixk$k, SIMPLIFY=FALSE
)
# flatten the data frame
newdf <- do.call(rbind, newdf)