R循环通过列中的代码列表
我有一个很大的数据集，我需要根据区域列将其拆分为多个数据集，然后为每个区域执行一些代码集，并获得每个区域的输出数据。我试图使用for循环来实现这一点，但它似乎不起作用。如何才能做到这一点。下面是我正在尝试的代码-R循环通过列中的代码列表,r,for-loop,split,data.table,R,For Loop,Split,Data.table,我有一个很大的数据集，我需要根据区域列将其拆分为多个数据集，然后为每个区域执行一些代码集，并获得每个区域的输出数据。我试图使用for循环来实现这一点，但它似乎不起作用。如何才能做到这一点。下面是我正在尝试的代码- for (a in c('10','11','14','20','30','40','50','61','64')) { paste0("data3_add_area",a) <- data3_add[AREACODE == a,] paste0("in_add_area
for (a in c('10','11','14','20','30','40','50','61','64'))
{
paste0("data3_add_area",a) <- data3_add[AREACODE == a,]
paste0("in_add_area",a) <- in_add[AREA_CODE == a,]
source1 <- paste0("data3_add_area",a)$name
source2 <- paste0("in_add_area",a)$name
.....
paste0("match_",a) <- output
}
for（c中的a（'10'，'11'，'14'，'20'，'30'，'40'，'50'，'61'，'64'））
{
paste0（“data3_add_area”，a）这是一个完整的脚本，我稍微更改了输入集，以演示距离矩阵包含多行和一列的情况：
library("stringdist")
library("data.table")
Address1 <- c("786, GALI NO 5, XYZ","rambo, 45, strret 4, atlast, pqr","23/4, 23RD FLOOR, STREET 2, ABC-E, PQR","45-B, GALI NO5, XYZ","HECTIC, 99 STREET, PQR")
AREACODE <- c('10','10','14','20','30')
Year1 <- c(2001:2005)
Address2 <- c("abc, pqr, xyz","786, GALI NO 4 XYZ","45B, GALI NO 5, XYZ","del, 546, strret2, towards east, pqr","23/4, STREET 2, PQR","abc, pqr, xyz","786, GALI NO 4 XYZ","45B, GALI NO 5, XYZ","del, 546, strret2, towards east, pqr","23/4, STREET 2, PQR")
Year2 <- c(2001:2010)
AREA_CODE <- c('10','10','10','20','30','40','50','61','64', '99')
data1 <- data.table(Address1, Year1, AREACODE)
data2 <- data.table(Address2, Year2, AREA_CODE)
data2[, unique_id := sprintf("%06d", 1:nrow(data2))]
methods <- c('osa','lv','dl','hamming','lcs','qgram','cosine','jaccard','jw')
# split data.table into list of data.tables by area code
sdata1 <- split(data1, data1$AREACODE)
sdata2 <- split(data2, data2$AREA_CODE)
# find the unique codes
codes <- union(names(sdata1), names(sdata2))
dist_calc <- function(x, y, methods) {
distance_methods <- list()
# calculate distance for each method
for(m in seq_along(methods)) {
output <- matrix(NA, ncol = length(x), nrow = length(y))
for(i in seq_along(x)) {
for(j in seq_along(y)) {
# calculate the matrix of distances for each pairing
output[j, i] <- stringdist(tolower(x[i]), tolower(y[j]), method = methods[m])
}
}
# store the output matrix in a named list element
distance_methods[[methods[m]]] <- output
}
# return a list of lists, with each leaf element being a matrix
return(distance_methods)
}
# iterate over codes, use names to retain codes and do not simplify -- return a list
distances <- sapply(codes, function(code) {
x <- sdata1[[code]]$Address1
y <- sdata2[[code]]$Address2
# do not compute if the code is not present in either one, the other or both
if (is.null(x) | is.null(y))
return(NULL)
# calculate all the distances
dist_mats <- dist_calc(x, y, methods)
# calculate the minimum value and indicie for each method
method_mins <- sapply(methods, function(meth) {
min_col <- apply(dist_mats[[meth]], 1, which.min)
min_val <- apply(dist_mats[[meth]], 1, min)
# list the minimum match value, the string, the matching string
data.table(name = y, match_name = x[min_col], adist = min_val)
}, USE.NAMES = TRUE, simplify = FALSE)
# combine into a single data.table
rbindlist(method_mins, idcol = "method")
}, USE.NAMES = TRUE, simplify = FALSE)
all_distances <- rbindlist(Filter(function(x) !is.null(x), distances), idcol = "AREACODE")
# AREACODE method name match_name adist
# 1: 10 osa abc, pqr, xyz 786, GALI NO 5, XYZ 12.00000000
# 2: 10 osa 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 2.00000000
# 3: 10 osa 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 3.00000000
# 4: 10 lv abc, pqr, xyz 786, GALI NO 5, XYZ 12.00000000
# 5: 10 lv 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 2.00000000
# 6: 10 lv 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 3.00000000
# 7: 10 dl abc, pqr, xyz 786, GALI NO 5, XYZ 12.00000000
# 8: 10 dl 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 2.00000000
# 9: 10 dl 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 3.00000000
#10: 10 hamming abc, pqr, xyz 786, GALI NO 5, XYZ Inf
#11: 10 hamming 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ Inf
#12: 10 hamming 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 3.00000000
#13: 10 lcs abc, pqr, xyz 786, GALI NO 5, XYZ 18.00000000
#14: 10 lcs 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 3.00000000
#15: 10 lcs 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 6.00000000
#16: 10 qgram abc, pqr, xyz 786, GALI NO 5, XYZ 16.00000000
#17: 10 qgram 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 3.00000000
#18: 10 qgram 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 6.00000000
#19: 10 cosine abc, pqr, xyz rambo, 45, strret 4, atlast, pqr 0.31400566
#20: 10 cosine 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 0.04653741
#21: 10 cosine 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 0.08784068
#22: 10 jaccard abc, pqr, xyz rambo, 45, strret 4, atlast, pqr 0.63157895
#23: 10 jaccard 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 0.12500000
#24: 10 jaccard 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 0.29411765
#25: 10 jw abc, pqr, xyz 786, GALI NO 5, XYZ 0.42535425
#26: 10 jw 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 0.05360624
#27: 10 jw 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 0.10526316
#28: 20 osa del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 29.00000000
#29: 20 lv del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 29.00000000
#30: 20 dl del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 29.00000000
#31: 20 hamming del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ Inf
#32: 20 lcs del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 41.00000000
#33: 20 qgram del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 35.00000000
#34: 20 cosine del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 0.46394373
#35: 20 jaccard del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 0.72000000
#36: 20 jw del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 0.54863548
#37: 30 osa 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 11.00000000
#38: 30 lv 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 11.00000000
#39: 30 dl 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 11.00000000
#40: 30 hamming 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR Inf
#41: 30 lcs 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 15.00000000
#42: 30 qgram 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 13.00000000
#43: 30 cosine 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 0.21927994
#44: 30 jaccard 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 0.50000000
#45: 30 jw 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 0.31607428
# AREACODE method name match_name adist
库（“stringdist”）
库（“数据表”）
地址1您能提供一些可复制的数据吗？dput（head（data2\u add，20））
例如，可能是添加中的。可能您正在寻找split
，它可以根据某个向量的值将data.frame拆分为data.frames列表。myList@Frank，感谢您指出。我已经更新了示例代码。感谢您的解决方案。这很有趣，但在same复制并非如我所想的那么简单。是否有必要将这些区域列为列表？如果您能让我知道为什么我们需要使用两个[[]]？我已经为每个区域添加了我想要复制的代码。您能建议我需要添加[[]]的地方吗获取每个区域的输出。很抱歉，我一直在尝试复制，但得到一些错误，例如-$运算符对原子向量无效。您可以使用问题查看何时使用[
以及何时使用[[
感谢您复制代码。我尝试运行您的代码，但在代码的最后一行出现错误，“rbindlist（distance，idcol=“AREACODE”）：试图在set_STRING_ELT中设置索引5/5”，我在网上搜索了这个错误，看到帖子要求更新data.table，我更新了同样的，仍然是这个错误。你知道是什么导致了这个错误吗？我在data.table 1.10.4，r 3.2.5，Win 10中看到了同样的错误。rbindlist（Filter（function（x）！is.null（x），distance），idcol=“AREACODE”）
工作得很好，我想，尽管@user1412tanks@Frank，看起来我使用的是一个过时的包版本，其中null
s被悄悄删除，感谢您的关注。
#install.packages('stringdist')
library(stringdist)
distance.methods<-c('osa','lv','dl','hamming','lcs','qgram','cosine','jaccard','jw')
dist.methods<-list()
for(m in 1:length(distance.methods))
{
dist.name.enh<-matrix(NA, ncol = length(source2.devices$name),nrow = length(source1.devices$name))
for(i in 1:length(source2.devices$name)) {
for(j in 1:length(source1.devices$name)) {
dist.name.enh[j,i]<-stringdist(tolower(source2.devices[i,]$name),tolower(source1.devices[j,]$name),method = distance.methods[m])
#adist.enhance(source2.devices[i,]$name,source1.devices[j,]$name)
}
}
dist.methods[[distance.methods[m]]]<-dist.name.enh
}
match.s1.s2.enh<-NULL
for(m in 1:length(dist.methods))
{
dist.matrix<-as.matrix(dist.methods[[distance.methods[m]]])
min.name.enh<-apply(dist.matrix, 1, base::min)
for(i in 1:nrow(dist.matrix))
{
s2.i<-match(min.name.enh[i],dist.matrix[i,])
s1.i<-i
match.s1.s2.enh<-rbind(data.frame(s2.i=s2.i,s1.i=s1.i,s2name=source2.devices[s2.i,]$name, s1name=source1.devices[s1.i,]$name, adist=min.name.enh[i],method=distance.methods[m]),match.s1.s2.enh)
}
}
# Let's have a look at the results
library(reshape2)
matched.names.matrix<-dcast(match.s1.s2.enh,s2.i+s1.i+s2name+s1name~method, value.var = "adist")
View(matched.names.matrix)
library("stringdist")
library("data.table")
Address1 <- c("786, GALI NO 5, XYZ","rambo, 45, strret 4, atlast, pqr","23/4, 23RD FLOOR, STREET 2, ABC-E, PQR","45-B, GALI NO5, XYZ","HECTIC, 99 STREET, PQR")
AREACODE <- c('10','10','14','20','30')
Year1 <- c(2001:2005)
Address2 <- c("abc, pqr, xyz","786, GALI NO 4 XYZ","45B, GALI NO 5, XYZ","del, 546, strret2, towards east, pqr","23/4, STREET 2, PQR","abc, pqr, xyz","786, GALI NO 4 XYZ","45B, GALI NO 5, XYZ","del, 546, strret2, towards east, pqr","23/4, STREET 2, PQR")
Year2 <- c(2001:2010)
AREA_CODE <- c('10','10','10','20','30','40','50','61','64', '99')
data1 <- data.table(Address1, Year1, AREACODE)
data2 <- data.table(Address2, Year2, AREA_CODE)
data2[, unique_id := sprintf("%06d", 1:nrow(data2))]
methods <- c('osa','lv','dl','hamming','lcs','qgram','cosine','jaccard','jw')
# split data.table into list of data.tables by area code
sdata1 <- split(data1, data1$AREACODE)
sdata2 <- split(data2, data2$AREA_CODE)
# find the unique codes
codes <- union(names(sdata1), names(sdata2))
dist_calc <- function(x, y, methods) {
distance_methods <- list()
# calculate distance for each method
for(m in seq_along(methods)) {
output <- matrix(NA, ncol = length(x), nrow = length(y))
for(i in seq_along(x)) {
for(j in seq_along(y)) {
# calculate the matrix of distances for each pairing
output[j, i] <- stringdist(tolower(x[i]), tolower(y[j]), method = methods[m])
}
}
# store the output matrix in a named list element
distance_methods[[methods[m]]] <- output
}
# return a list of lists, with each leaf element being a matrix
return(distance_methods)
}
# iterate over codes, use names to retain codes and do not simplify -- return a list
distances <- sapply(codes, function(code) {
x <- sdata1[[code]]$Address1
y <- sdata2[[code]]$Address2
# do not compute if the code is not present in either one, the other or both
if (is.null(x) | is.null(y))
return(NULL)
# calculate all the distances
dist_mats <- dist_calc(x, y, methods)
# calculate the minimum value and indicie for each method
method_mins <- sapply(methods, function(meth) {
min_col <- apply(dist_mats[[meth]], 1, which.min)
min_val <- apply(dist_mats[[meth]], 1, min)
# list the minimum match value, the string, the matching string
data.table(name = y, match_name = x[min_col], adist = min_val)
}, USE.NAMES = TRUE, simplify = FALSE)
# combine into a single data.table
rbindlist(method_mins, idcol = "method")
}, USE.NAMES = TRUE, simplify = FALSE)
all_distances <- rbindlist(Filter(function(x) !is.null(x), distances), idcol = "AREACODE")
# AREACODE method name match_name adist
# 1: 10 osa abc, pqr, xyz 786, GALI NO 5, XYZ 12.00000000
# 2: 10 osa 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 2.00000000
# 3: 10 osa 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 3.00000000
# 4: 10 lv abc, pqr, xyz 786, GALI NO 5, XYZ 12.00000000
# 5: 10 lv 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 2.00000000
# 6: 10 lv 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 3.00000000
# 7: 10 dl abc, pqr, xyz 786, GALI NO 5, XYZ 12.00000000
# 8: 10 dl 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 2.00000000
# 9: 10 dl 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 3.00000000
#10: 10 hamming abc, pqr, xyz 786, GALI NO 5, XYZ Inf
#11: 10 hamming 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ Inf
#12: 10 hamming 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 3.00000000
#13: 10 lcs abc, pqr, xyz 786, GALI NO 5, XYZ 18.00000000
#14: 10 lcs 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 3.00000000
#15: 10 lcs 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 6.00000000
#16: 10 qgram abc, pqr, xyz 786, GALI NO 5, XYZ 16.00000000
#17: 10 qgram 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 3.00000000
#18: 10 qgram 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 6.00000000
#19: 10 cosine abc, pqr, xyz rambo, 45, strret 4, atlast, pqr 0.31400566
#20: 10 cosine 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 0.04653741
#21: 10 cosine 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 0.08784068
#22: 10 jaccard abc, pqr, xyz rambo, 45, strret 4, atlast, pqr 0.63157895
#23: 10 jaccard 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 0.12500000
#24: 10 jaccard 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 0.29411765
#25: 10 jw abc, pqr, xyz 786, GALI NO 5, XYZ 0.42535425
#26: 10 jw 786, GALI NO 4 XYZ 786, GALI NO 5, XYZ 0.05360624
#27: 10 jw 45B, GALI NO 5, XYZ 786, GALI NO 5, XYZ 0.10526316
#28: 20 osa del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 29.00000000
#29: 20 lv del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 29.00000000
#30: 20 dl del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 29.00000000
#31: 20 hamming del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ Inf
#32: 20 lcs del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 41.00000000
#33: 20 qgram del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 35.00000000
#34: 20 cosine del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 0.46394373
#35: 20 jaccard del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 0.72000000
#36: 20 jw del, 546, strret2, towards east, pqr 45-B, GALI NO5, XYZ 0.54863548
#37: 30 osa 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 11.00000000
#38: 30 lv 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 11.00000000
#39: 30 dl 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 11.00000000
#40: 30 hamming 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR Inf
#41: 30 lcs 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 15.00000000
#42: 30 qgram 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 13.00000000
#43: 30 cosine 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 0.21927994
#44: 30 jaccard 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 0.50000000
#45: 30 jw 23/4, STREET 2, PQR HECTIC, 99 STREET, PQR 0.31607428
# AREACODE method name match_name adist