Algoritma & Struktur Data

Tugas Algoritma dan Struktur Data pertemuan ke-10


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Impor/ekspor CSV

Directory

print (getwd())
## [1] "C:/Users/HP/OneDrive/Documents/tugas algo 5"
getwd()
## [1] "C:/Users/HP/OneDrive/Documents/tugas algo 5"
setwd(getwd())

Impor file CSV

data1 <- read.csv("C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\input\\input1.csv", sep = ";")
data2 <- read.csv("C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\input\\input2.csv",sep = ",")
data1
data2

ekspor data dalam bentuk Output

write.csv(data1,"C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\output\\output1.csv", row.names = FALSE)
write.csv(data2,"C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\output\\output2.csv", row.names = FALSE)

Impor/ekspor Excel

Directory

# install.packages(c("readxl","writexl")) # install packages readxl and writexl
pacman::p_load(readxl, writexl)         # install pacman

Impor data Excel

data3 <- read_excel("C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\input\\input3.xlsx")             # impor data xlsx
data4 <- read_excel("C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\input\\input4.xlsx", sheet=1)    # impor data xlsx 
data3
data4

Ekspor data dalam bentuk output

write_xlsx(data3,"C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\output\\output3.xlsx")
write_xlsx(data4,"C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\output\\output4.xlsx")

Impor/ekspor TXT and RDS

Directory

getwd()
## [1] "C:/Users/HP/OneDrive/Documents/tugas algo 5"
setwd(getwd())

impor

data5 <- read.table("C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\input\\input5.txt")
data6 <- source("C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\input\\input6.Rdmpd")
data7 <- readRDS("C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\input\\input7.rds")
data8 <- readRDS("C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\input\\input8.ascii")

# memanggil data 5-8 
data5
data6
## $value
##    id    name salary start_date      dept
## 1   1  Julian  623,3   1/1/2022        DS
## 2   2 Vanessa  515,2  9/23/2022        DS
## 3   3  Jeffry    611 11/15/2022        BA
## 4   4   Angel    729  5/11/2022        DA
## 5   5   Nikki 843,25  3/27/2022        DS
## 6   6  Ardifo    578  5/21/2022 Actuaries
## 7   7   Irene  722,5  7/30/2022 Actuaries
## 8   8   Kefas  632,8  6/17/2022        CA
## 9   9  Sherly  632,8  7/30/2022        DE
## 10 10   Bakti   <NA>   9/3/2018  Lecturer
## 
## $visible
## [1] FALSE
data7
data8

ekspor

write.table(data5,"C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\output\\output5.txt")
dump("data6", "C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\output\\output6.Rdmpd")
saveRDS(data7, "C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\output\\output7.rds")
saveRDS(data8, "C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\output\\output8.ascii", ascii = TRUE)

ekspor/impor XML

Directory

# install.packages("XML")
library("XML")
library("methods")

impor XML

data9 <- xmlParse(file= "C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\input\\input9.xml")
print(data9)
## <?xml version="1.0"?>
## <RECORDS>
##   <EMPLOYEE>
##     <id>1</id>
##     <name>Julian</name>
##     <salary>623.3</salary>
##     <start_date>1/1/2022</start_date>
##     <dept>DS</dept>
##   </EMPLOYEE>
##   <EMPLOYEE>
##     <id>2</id>
##     <name>Vanessa</name>
##     <salary>515.2</salary>
##     <start_date>9/23/2022</start_date>
##     <dept>DS</dept>
##   </EMPLOYEE>
##   <EMPLOYEE>
##     <id>3</id>
##     <name>Jeffry</name>
##     <salary>611</salary>
##     <start_date>11/15/2022</start_date>
##     <dept>BA</dept>
##   </EMPLOYEE>
##   <EMPLOYEE>
##     <id>4</id>
##     <name>Angel</name>
##     <salary>729</salary>
##     <start_date>5/11/2022</start_date>
##     <dept>BA</dept>
##   </EMPLOYEE>
##   <EMPLOYEE>
##     <id>5</id>
##     <name>Nikki</name>
##     <salary>843.25</salary>
##     <start_date>3/27/2022</start_date>
##     <dept>DS</dept>
##   </EMPLOYEE>
##   <EMPLOYEE>
##     <id>6</id>
##     <name>Ardifo</name>
##     <salary>578</salary>
##     <start_date>5/21/2022</start_date>
##     <dept>Actuaries</dept>
##   </EMPLOYEE>
##   <EMPLOYEE>
##     <id>7</id>
##     <name>Irene</name>
##     <salary>722.5</salary>
##     <start_date>7/30/2022</start_date>
##     <dept>Actuaries</dept>
##   </EMPLOYEE>
##   <EMPLOYEE>
##     <id>8</id>
##     <name>Kefas</name>
##     <salary>632.8</salary>
##     <start_date>6/17/2022</start_date>
##     <dept>CA</dept>
##   </EMPLOYEE>
##   <EMPLOYEE>
##     <id>9</id>
##     <name>Sherly</name>
##     <salary>632.8</salary>
##     <start_date>7/30/2022</start_date>
##     <dept>DE</dept>
##   </EMPLOYEE>
##   <EMPLOYEE>
##     <id>10</id>
##     <name>Bakti</name>
##     <salary>NA</salary>
##     <start_date>9/03/2018</start_date>
##     <dept>Lecturer</dept>
##   </EMPLOYEE>
## </RECORDS>
##

mengubah XML menjadi dataframe

Mengubahkan XML menjadi dataframe memudahkan dalam melihat secara rapi dan terinci.

data9_df <- xmlToDataFrame(data9)
data9_df

impor XML

write.csv(data9_df, "C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\output\\output9.xml")

Impor/ ekspor JSON

Directory

# install.packages("jsonlite")
library(jsonlite)

Impor JSON

data10 <- fromJSON("C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\input\\input10.json")
data10
## $id
##  [1] "1"  "2"  "3"  "4"  "5"  "6"  "7"  "8"  "9"  "10"
## 
## $name
##  [1] "Julian"  "Vanessa" "Jeffry"  "Angel"   "Nikki"   "Ardifo"  "Irene"  
##  [8] "Kefas"   "Sherly"  "Bakti"  
## 
## $salary
##  [1] "623.3"  "515.2"  "611"    "729"    "843.25" "578"    "722.5"  "632.8" 
##  [9] "632.8"  "NA"    
## 
## $start_date
##  [1] "1/1/2022"   "9/23/2022"  "11/15/2022" "5/11/2022"  "3/27/2022" 
##  [6] "5/21/2022"  "7/30/2022"  "6/17/2022"  "7/30/2022"  "9/3/2018"  
## 
## $dept
##  [1] "DS"        "DS"        "BA"        "DA"        "DS"        "Actuaries"
##  [7] "Actuaries" "CA"        "DE"        "Lecturer"

ubah JSON menjadi dataframe ‘as.data.frame()’

data10_json_df <- as.data.frame(data10)
data10_json_df

Ekspor JSON

write_json(data10_json_df, "C:\\Users\\HP\\OneDrive\\Documents\\tugas algo 5\\output\\output10.json")