こんにちは、管理が難しい状況です。次のような data.frame があります。
General_name a b c d m n
そして、次のような別の data.frame :
First_names_list a=34;b=4 Second_names_list d=2;m=98;n=32 Third_names_list c=1;d=12;m=0.1
最初の data.frame の各要素を、2 番目の data.frame[,2] の = の前の各要素と一致させて、最終的に次のテーブルを取得する必要があります。
Names a b c d m n First_names_list 34 4 NA NA NA NA Second_names_list NA NA NA 2 98 32 Third_names_list NA NA 1 12 0.1 NA
なにか提案を？私には難しすぎるようです。
一番
E.
dcast「reshape2」とconcat.split私の「splitstackshape」パッケージから使用する1つのアプローチを次に示します。
library(splitstackshape)
## The following can also be done in 2 steps. The basic idea is to split
## the values into a semi-long form for `dcast` to be able to use. So,
## I've split first on the semicolon, and made the data into a long form
## at the same time, then I've split on =, but kept it wide that time.
out <- concat.split(concat.split.multiple(df, "V2", ";", "long"),
"V2", "=", drop = TRUE)
out
# V1 time V2_1 V2_2
# 1 First_names_list 1 a 34.0
# 2 Second_names_list 1 d 2.0
# 3 Third_names_list 1 c 1.0
# 4 First_names_list 2 b 4.0
# 5 Second_names_list 2 m 98.0
# 6 Third_names_list 2 d 12.0
# 7 First_names_list 3 <NA> NA
# 8 Second_names_list 3 n 32.0
# 9 Third_names_list 3 m 0.1
library(reshape2)
dcast(out[complete.cases(out), ], V1 ~ V2_1, value.var="V2_2")
# V1 a b c d m n
# 1 First_names_list 34 4 NA NA NA NA
# 2 Second_names_list NA NA NA 2 98.0 32
# 3 Third_names_list NA NA 1 12 0.1 NA
のより新しいバージョンを使用した別のオプションを次に示しますdata.table。この概念は、上記のアプローチと非常によく似ています。
library(data.table)
library(reshape2)
packageVersion("data.table")
# [1] ‘1.8.11’
dt <- data.table(df)
S1 <- dt[, list(X = unlist(strsplit(as.character(V2), ";"))), by = V1]
S1[, c("A", "B") := do.call(rbind.data.frame, strsplit(X, "="))]
S1
# V1 X A B
# 1: First_names_list a=34 a 34
# 2: First_names_list b=4 b 4
# 3: Second_names_list d=2 d 2
# 4: Second_names_list m=98 m 98
# 5: Second_names_list n=32 n 32
# 6: Third_names_list c=1 c 1
# 7: Third_names_list d=12 d 12
# 8: Third_names_list m=0.1 m 0.1
dcast.data.table(S1, V1 ~ A, value.var="B")
# V1 a b c d m n
# 1: First_names_list 34 4 NA NA NA NA
# 2: Second_names_list NA NA NA 2 98 32
# 3: Third_names_list NA NA 1 12 0.1 NA
上記のオプションは両方とも、次のものから始めることを前提としています。
df <- structure(list(V1 = c("First_names_list", "Second_names_list",
"Third_names_list"), V2 = c("a=34;b=4", "d=2;m=98;n=32",
"c=1;d=12;m=0.1")), .Names = c("V1", "V2"), class = "data.frame",
row.names = c(NA, -3L))
applyapply内で使用するソリューションは次のとおりです。
#Data frame 1
df1 <- read.table(text=
"General_name
a
b
c
d
m
n", header=T, as.is=T)
#Data frame 2
df2 <- read.table(text=
"col1 col2
First_names_list a=34;b=4
Second_names_list d=2;m=98;n=32
Third_names_list c=1;d=12;m=0.1", header=T, as.is=T)
#make lists for each row, sep by ";"
df2split <- strsplit(df2$col2,split=";")
#result
t(
sapply(seq(1:nrow(df2)),function(c){
x <- df2split[[c]]
sapply(df1$General_name,function(n){
t <- gsub(paste0(n,"="),"",x[grepl(n,x)])
ifelse(length(t)==0,NA,as.numeric(t))
})
})
)
これは少し回りくどい方法だと思うので、より良い解決策も楽しみにしています。しかし、これは機能します。
library(data.table)
library(reshape2)
#creating datasets
dt <- data.table(read.csv(textConnection('
"First_names_list","a=34;b=4"
"Second_names_list","d=2;m=98;n=32"
"Third_names_list","c=1;d=12;m=0.1"
'),header = FALSE))
General_name = c('a','b','c','d','m','n')
TotalBreakup <- data.table(
V1 = General_name
)
# Fixing datatypes
TotalBreakup <- TotalBreakup[,lapply(.SD,as.character)]
dt <- dt[,lapply(.SD,as.character)]
# looping through each row and calculating breakdown
for(i in 1:nrow(dt))
{
# the next two statements are the workhorse of this code. Run each part of these statements step by step to see
dtlist <- strsplit(unlist(strsplit(dt[i,V2],";")),"=")
breakup <- data.table(
t(
matrix(
unlist(
strsplit(
unlist(
strsplit(
dt[i,V2],
";"
)
),
"="
)
),
nrow = 2
)
)
)
# fixing datatypes again
breakup <- breakup[,lapply(.SD,as.character)]
#appending to master dataset
TotalBreakup <- merge(TotalBreakup, breakup, by = "V1", all.x = TRUE)
}
#formatting results
setnames(TotalBreakup,c("Names",dt[,V1]))
TotalBreakup <- acast(melt(TotalBreakup,id.vars = "Names"),variable~Names)
出力 -
> TotalBreakup
a b c d m n
First_names_list "34" "4" NA NA NA NA
Second_names_list NA NA NA "2" "98" "32"
Third_names_list NA NA "1" "12" "0.1" NA
方法はこれです：
#the second dataframe you provided
DF2 <- read.table(text = '
First_names_list a=34;b=4
Second_names_list d=2;m=98;n=32
Third_names_list c=1;d=12;m=0.1
', header = F, stringsAsFactors = F)
#empty dataframe
DF <- structure(list(a = c(NA, NA, NA), b = c(NA, NA, NA), c = c(NA,
NA, NA), d = c(NA, NA, NA), m = c(NA, NA, NA), n = c(NA, NA,
NA)), .Names = c("a", "b", "c", "d", "m", "n"), row.names = c("First_names_list",
"Second_names_list", "Third_names_list"), class = "data.frame")
DF
# a b c d m n
#First_names_list NA NA NA NA NA NA
#Second_names_list NA NA NA NA NA NA
#Third_names_list NA NA NA NA NA NA
#fill the dataframe
myls <- strsplit(DF2$V2, split = ";")
for(i in 1:length(myls))
{
sapply(myls[[i]],
function(x) { res <- unlist(strsplit(x, "=")) ; DF[i,res[1]] <<- res[2] })
}
DF
# a b c d m n
#First_names_list 34 4 <NA> <NA> <NA> <NA>
#Second_names_list <NA> <NA> <NA> 2 98 32
#Third_names_list <NA> <NA> 1 12 0.1 <NA>