

Email : calvin.riswandi@student.matanauniversity.ac.id
RPubs : https://rpubs.com/Calvinriswandy/
Jurusan : Statistika
Address : ARA Center, Matana University Tower
Jl. CBD Barat Kav, RT.1, Curug Sangereng, Kelapa Dua, Tangerang, Banten 15810.
Import/Eksport CSV
Terdapat beberapa cara untuk menginput data, berikut adalah cara menginput data dengan menggunakan format CSV
# pengaturan directory
print(getwd())
## [1] "C:/Users/5/Documents/Data"
## [1] "C:/Users/5/Documents/Data"
setwd(getwd())
# Import data
df1 <-read.csv("Input/input1.csv",sep = ",") # Import data 1 format CSV
df2 <-read.csv("Input/input2.csv",sep = ",") # Import data 2 format CSV
# eksport data
write.csv(df1,"Output/output1.csv", row.names = FALSE) # eksport data 1 format CSV
write.csv(df2,"Output/output2.csv", row.names = FALSE) # eksport data 2 format CSV
Import/eksport Excel
Microsoft Excel adalah program spreadsheet yang paling banyak orang gunakan untuk menyimpan data dengan format .xls atau .xlsx. Berikut adalah langkah-langkah untuk menginput data tersebut masuk ke Rstudio. Caranya sebagai berikut:
#install.packages(c("readxl", "writexl"))
pacman::p_load(readxl, writexl)
# Import data
df3 <-read_excel("Input/input4.xls",sheet= 1) # Import data format XLS
df4 <-read_excel("Input/input3.xlsx",sheet="DuplicateX") # Import data format XLSX (excel 2003<)
# eksport data
write_xlsx(df3,"Output/output3.xls") # eksport data format XLS
write_xlsx(df4,"Output/output4.xlsx") # eksport data format XLS
Import/Eksport TXT dan RDS
Kita ketahui bahwa format yang paling umum digunakan untuk Import/Eksport data adalah file CSV dan XLS. Tetapi, untuk ukuran data CSV dan XLS lebih besar. Jadi untuk mengatasi permasalahan ini, maka kita menggunakan data berformat TXT atau file biner R (RDS). Berikut cara untuk menginput data berformat TXT dan Biner:
# Import data
df5 <- read.table("Input/input5.txt") # Import data format TXT (notepad)
df6 <- source("Input/input6.rdmpd") # Import data format TXT (rdmpd)
df7 <- readRDS("Input/input7.rds") # Import data format binary RDS
df8 <- readRDS("Input/input8.ascii") # Import data format binart ASCII
# eksport data
write.table(df5,"Output/output5.txt") # eksport data format TXT (notepad)
dump("df6","Output/output6.rdmpd") # eksport data format TXT (rdmpd)
saveRDS(df7,"Output/output7.rds") # eksport data format binary RDS
saveRDS(df8,"Output/output8.ascii", ascii= TRUE) # eksport data format binart ASCII
Import/Eksport XML
XML adalah kumpulan file dan data di World Wide Web atau yang biasa kita kenal sebagai WWW. XML singkatan dari eXtensible Markup Language. Berikut cara untuk menginput data berformat XML:
library("XML") # memasukan library "XML"
library("kulife") # memasukan library "kulife"
library("methods") # memasukan library "methods"
df9 <- xmlParse("Input/input9.xml") # Import data format xml
xml_df <- xmlToDataFrame(df9) # mengkonversi menjadi dataframe
write.xml(xml_df, "Output/output9.xml") # eksport data format xml
Import/Eksport JSON
File JSON adalah file yang digunakan untuk menyimpan data sebagai teks dalam format yang daapat dibaca manusia. JSON adalah singkatan dari JavaScript Object Nation. Berikut cara untuk menginput data berformat JSON:
library("jsonlite") # memasukan library "jsonlite"
df10 <-fromJSON("Input/Input10.json") # Import data format json
json_df <- as.data.frame(df10) # mengkonversi menjadi dataframe
write_json(json_df, "Output/output10.json") # eksport data format json
Import/Eksport dari web
banyak webside yang menyediakan data untuk digunakan penggunanya. di R kita bisa mengekstrak data spesifik dari situs web tersebut secara terprogram.
CSV
Sebagai contohnya:
# web_csv <- read.csv() # Tinggal di isi link .CSV
XLSX
library(rio)
install_formats()
## [1] TRUE
# web_xlsx <- rio::import() # Tinggal di isi link .XLSX
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