Analisis dengan satu tabel mengacu pada proses memanipulasi dan menganalisis data yang terdapat dalam satu tabel tunggal menggunakan paket dplyr dalam bahasa pemrograman R. Paket dplyr adalah salah satu paket yang populer dalam R untuk memanipulasi dan menyederhanakan operasi pada data frame.
library(dplyr)
## Warning: package 'dplyr' was built under R version 4.2.2
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
membuat data frame
data_frame = data.frame(companies = c("Mobile Legend","Free Fire","xiaomi","TCS",
"Legenda Selular","BERMAIN DENGAN API","TCS","Siaomi",
"Doritos","Siaomi"),
people = c(100,NA,532,454,234,554,223,122,432,453),
rating = c(4,3,5,NA,5,3,NA,4,5,2))
print("Original Data frame")
## [1] "Original Data frame"
Cetak data frame
print(data_frame)
## companies people rating
## 1 Mobile Legend 100 4
## 2 Free Fire NA 3
## 3 xiaomi 532 5
## 4 TCS 454 NA
## 5 Legenda Selular 234 5
## 6 BERMAIN DENGAN API 554 3
## 7 TCS 223 NA
## 8 Siaomi 122 4
## 9 Doritos 432 5
## 10 Siaomi 453 2
print("Extracting companies vector from data frame")
## [1] "Extracting companies vector from data frame"
print("Companies vector")
## [1] "Companies vector"
data_frame %>%
pull(companies)
## [1] "Mobile Legend" "Free Fire" "xiaomi"
## [4] "TCS" "Legenda Selular" "BERMAIN DENGAN API"
## [7] "TCS" "Siaomi" "Doritos"
## [10] "Siaomi"
print("Renaming rating column")
## [1] "Renaming rating column"
data_frame %>%
rename(feedback_rating = rating)
## companies people feedback_rating
## 1 Mobile Legend 100 4
## 2 Free Fire NA 3
## 3 xiaomi 532 5
## 4 TCS 454 NA
## 5 Legenda Selular 234 5
## 6 BERMAIN DENGAN API 554 3
## 7 TCS 223 NA
## 8 Siaomi 122 4
## 9 Doritos 432 5
## 10 Siaomi 453 2
print("Arranging data frame by rating column")
## [1] "Arranging data frame by rating column"
data_frame %>%
arrange(rating)
## companies people rating
## 1 Siaomi 453 2
## 2 Free Fire NA 3
## 3 BERMAIN DENGAN API 554 3
## 4 Mobile Legend 100 4
## 5 Siaomi 122 4
## 6 xiaomi 532 5
## 7 Legenda Selular 234 5
## 8 Doritos 432 5
## 9 TCS 454 NA
## 10 TCS 223 NA
print("Arranging data frame by rating column")
## [1] "Arranging data frame by rating column"
data_frame %>%
filter(!is.na(people))
## companies people rating
## 1 Mobile Legend 100 4
## 2 xiaomi 532 5
## 3 TCS 454 NA
## 4 Legenda Selular 234 5
## 5 BERMAIN DENGAN API 554 3
## 6 TCS 223 NA
## 7 Siaomi 122 4
## 8 Doritos 432 5
## 9 Siaomi 453 2
data_frame %>%
summarize(num_rows = n(),most_bellas = max(companies))
## num_rows most_bellas
## 1 10 xiaomi
Pada analisi data menggunakan library dplyr, Bisa melakukan berbagai tugas seperti berikut
1.Pemilihan kolom 2.Pemfilteran Baris 3.Pengelompokkan data