https://github.com/Rdatatable/data.table/wiki/Convenience-features-of-fread

• read.table() 대신 사용가능
• Text파일을 읽어들이는데 많이 사용됨.
  Xlsx파일은 readxl::read_xlsx를 사용
• 빠르고
• character를 factor로 자동변환하진 않는다.

fread ( input= 파일명 or URL,
header= “auto”, sep=”auto” ,
stringsAsFactors=FALSE,
drop= NULL, select=NULL , colClasses=NULL
)

fread(input, file, text, cmd, sep="auto/,/delimiter설정", sep2="auto", dec=".", quote="\\"",
   nrows=Inf, header="auto/T/F",
   na.strings=getOption("datatable.na.strings","NA"),  # due to change to ""; see NEWS
   stringsAsFactors=FALSE, verbose=getOption("datatable.verbose", FALSE),
   skip="__auto__", select=NULL, drop=NULL, 
   colClasses=NULL, # character number Date POSIXct ....
   integer64=getOption("datatable.integer64", "integer64"),
   col.names,
   check.names=FALSE, encoding="unknown",
   strip.white=TRUE, fill=FALSE, blank.lines.skip=FALSE,
   key=NULL, index=NULL,
   showProgress=getOption("datatable.showProgress", interactive()),
   data.table=getOption("datatable.fread.datatable", TRUE),
   nThread=getDTthreads(verbose),
   logical01=getOption("datatable.logical01", FALSE),  # due to change to TRUE; see NEWS
   keepLeadingZeros = getOption("datatable.keepLeadingZeros", FALSE),
   yaml=FALSE, autostart=NA, tmpdir=tempdir(), tz=""
)

data = "
A,B,C,D
1,3,5,7
2,4,6,8
"
dd <- data %>% fread()
#   A B C D
#1: 1 3 5 7
#2: 2 4 6 8

dd %>% str
#Classes ‘data.table’ and 'data.frame':\t2 obs. of  4 variables:
# $ A: int  1 2
# $ B: int  3 4
# $ C: int  5 6
# $ D: int  7 8
# - attr(*, ".internal.selfref")= 

colClasses

character–>datetime 변경하고 싶을때, colClasses=c(“날짜시간으로바꾸고싶은문자변수명”=”POSIXct”)
“Date”,”integer”,”numeric”, “character”

dd <- data %>% fread(colClasses=c(B="character",C="character",D="character"))
     #fread(data, colClasses=list(character=c("B","C","D")))
     #fread(data, colClasses=list(character=2:4)) 
dd %>% str

Classes ‘data.table’ and 'data.frame':\t2 obs. of  4 variables:
 $ A: int  1 2
 $ B: chr  "3" "4"
 $ C: chr  "5" "6"
 $ D: chr  "7" "8"
 - attr(*, ".internal.selfref")=

https://www.r-bloggers.com/2013/09/using-colclasses-to-load-data-more-quickly-in-r/

sampleData <- read.csv("huge-file.csv", header = TRUE, nrows = 5)
classes <- sapply(sampleData, class)
largeData <- read.csv("huge-file.csv", header = TRUE, colClasses = classes)
str(largeData)

drop/select

data %>% fread(drop=c("B","C"))      # same but less typing, easier to read
data %>% fread(drop=2:3)             # same using column numbers
data %>% fread(colClasses=c("B"="NULL","C"="NULL")) # as read.csv
data %>% fread(colClasses=list(NULL=c("B","C")))    # same

data %>% fread(select=c("A","D"))    # less typing, easier to read
data %>% fread(select=c(1,4))        # same using column numbers
#   A D
#1: 1 7
#2: 2 8

https://stackoverrun.com/ko/q/5099655

data = "A,B,C,D\
1,3,5,7\
2,4,6,8\
"
data %>% fread()
#    A B C D
# 1: 1 3 5 7
# 2: 2 4 6 8
data %>% fread() %>% str()
# Classes ‘data.table’ and 'data.frame':\t2 obs. of  4 variables:
#  $ A: int  1 2
#  $ B: int  3 4
#  $ C: int  5 6
#  $ D: int  7 8
#  - attr(*, ".internal.selfref")= 

### colClasses  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~  
data %>% fread(colClasses=c(B="character",C="character",D="character")) %>% str()
# Classes ‘data.table’ and 'data.frame':\t2 obs. of  4 variables:
#  $ A: int  1 2
#  $ B: chr  "3" "4"
#  $ C: chr  "5" "6"
#  $ D: chr  "7" "8"
#  - attr(*, ".internal.selfref")= 
data %>% fread(colClasses=list(character=c("B","C","D")))  # same above, saves typing
data %>% fread(colClasses=list(character=2:4))             # same above, using column numbers

### drop  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
data %>% fread(colClasses=c("B"="NULL","C"="NULL"))   # as read.csv
#    A D
# 1: 1 7
# 2: 2 8
data %>% fread(colClasses=list(NULL=c("B","C")))      # same
data %>% fread(drop=c("B","C"))      # same but less typing, easier to read
data %>% fread(drop=2:3)             # same using column numbers

### select  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# (in read.csv you need to work out which to drop)
data %>% fread(select=c("A","D"))    # less typing, easier to read
data %>% fread(select=c(1,4))        # same using column numbers

ex

library(tidyverse)
library(data.table)

files <- list.files(path="./data", pattern = "[t].+csv", full.names=TRUE)
dd <- sapply(files, function(x){fread(input=x, sep = ",", header = T, encoding = 'UTF-8')})
# for(i in 1:length(dd)){
#     names(dd[[1]][,8]) <- "rename"
# }
dd <- rbindlist(dd)
dd <- dd[!duplicated(dd)]
#identical(unique(dd), dd[!duplicated(dd)])

fwrite(x = d1, sep = ",", file = "aaa.csv", quote = T, row.names = F )