Masukkan ini di bagian paling atas file .Rmd Anda
data("starwars")starwars## # A tibble: 87 × 14
## name height mass hair_color skin_color eye_color birth_year sex gender
## <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr>
## 1 Luke Sk… 172 77 blond fair blue 19 male mascu…
## 2 C-3PO 167 75 <NA> gold yellow 112 none mascu…
## 3 R2-D2 96 32 <NA> white, bl… red 33 none mascu…
## 4 Darth V… 202 136 none white yellow 41.9 male mascu…
## 5 Leia Or… 150 49 brown light brown 19 fema… femin…
## 6 Owen La… 178 120 brown, gr… light blue 52 male mascu…
## 7 Beru Wh… 165 75 brown light blue 47 fema… femin…
## 8 R5-D4 97 32 <NA> white, red red NA none mascu…
## 9 Biggs D… 183 84 black light brown 24 male mascu…
## 10 Obi-Wan… 182 77 auburn, w… fair blue-gray 57 male mascu…
## # ℹ 77 more rows
## # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,
## # vehicles <list>, starships <list>head(starwars)## # A tibble: 6 × 14
## name height mass hair_color skin_color eye_color birth_year sex gender
## <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr>
## 1 Luke Sky… 172 77 blond fair blue 19 male mascu…
## 2 C-3PO 167 75 <NA> gold yellow 112 none mascu…
## 3 R2-D2 96 32 <NA> white, bl… red 33 none mascu…
## 4 Darth Va… 202 136 none white yellow 41.9 male mascu…
## 5 Leia Org… 150 49 brown light brown 19 fema… femin…
## 6 Owen Lars 178 120 brown, gr… light blue 52 male mascu…
## # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,
## # vehicles <list>, starships <list>(starwars)## # A tibble: 87 × 14
## name height mass hair_color skin_color eye_color birth_year sex gender
## <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr>
## 1 Luke Sk… 172 77 blond fair blue 19 male mascu…
## 2 C-3PO 167 75 <NA> gold yellow 112 none mascu…
## 3 R2-D2 96 32 <NA> white, bl… red 33 none mascu…
## 4 Darth V… 202 136 none white yellow 41.9 male mascu…
## 5 Leia Or… 150 49 brown light brown 19 fema… femin…
## 6 Owen La… 178 120 brown, gr… light blue 52 male mascu…
## 7 Beru Wh… 165 75 brown light blue 47 fema… femin…
## 8 R5-D4 97 32 <NA> white, red red NA none mascu…
## 9 Biggs D… 183 84 black light brown 24 male mascu…
## 10 Obi-Wan… 182 77 auburn, w… fair blue-gray 57 male mascu…
## # ℹ 77 more rows
## # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,
## # vehicles <list>, starships <list>##Pendeteksian Missing Values##
starwars## # A tibble: 87 × 14
## name height mass hair_color skin_color eye_color birth_year sex gender
## <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr>
## 1 Luke Sk… 172 77 blond fair blue 19 male mascu…
## 2 C-3PO 167 75 <NA> gold yellow 112 none mascu…
## 3 R2-D2 96 32 <NA> white, bl… red 33 none mascu…
## 4 Darth V… 202 136 none white yellow 41.9 male mascu…
## 5 Leia Or… 150 49 brown light brown 19 fema… femin…
## 6 Owen La… 178 120 brown, gr… light blue 52 male mascu…
## 7 Beru Wh… 165 75 brown light blue 47 fema… femin…
## 8 R5-D4 97 32 <NA> white, red red NA none mascu…
## 9 Biggs D… 183 84 black light brown 24 male mascu…
## 10 Obi-Wan… 182 77 auburn, w… fair blue-gray 57 male mascu…
## # ℹ 77 more rows
## # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,
## # vehicles <list>, starships <list>is.na(starwars)## name height mass hair_color skin_color eye_color birth_year sex
## [1,] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
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## gender homeworld species films vehicles starships
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## [87,] FALSE TRUE FALSE FALSE FALSE FALSEcolSums (is.na(starwars))## name height mass hair_color skin_color eye_color birth_year
## 0 6 28 5 0 0 44
## sex gender homeworld species films vehicles starships
## 4 4 10 4 0 0 0#visualisasi
aggr(starwars, numbers = TRUE, prop = FALSE)
#Melakukan imputasi Missing Values
starwars$mass[is.na(starwars$mass)] <- median(starwars$mass, na.rm = TRUE)
starwars$birth_year[is.na(starwars$birth_year)] <- median(starwars$birth_year, na.rm = TRUE)
colSums(is.na(starwars))## name height mass hair_color skin_color eye_color birth_year
## 0 6 0 5 0 0 0
## sex gender homeworld species films vehicles starships
## 4 4 10 4 0 0 0summary (starwars)## name height mass hair_color
## Length:87 Min. : 66.0 Min. : 15.00 Length:87
## Class :character 1st Qu.:167.0 1st Qu.: 75.00 Class :character
## Mode :character Median :180.0 Median : 79.00 Mode :character
## Mean :174.6 Mean : 91.42
## 3rd Qu.:191.0 3rd Qu.: 80.00
## Max. :264.0 Max. :1358.00
## NA's :6
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## Length:87 Length:87 Min. : 8.00 Length:87
## Class :character Class :character 1st Qu.: 52.00 Class :character
## Mode :character Mode :character Median : 52.00 Mode :character
## Mean : 69.58
## 3rd Qu.: 52.00
## Max. :896.00
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## Length:87 Length:87 Length:87
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## 5 -none- character
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## 4 -none- character
## 5 -none- character
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## 2 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## vehicles.Length vehicles.Class vehicles.Mode
## 2 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 1 -none- character
## 0 -none- character
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## starships.Length starships.Class starships.Mode
## 2 -none- character
## 0 -none- character
## 0 -none- character
## 1 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 1 -none- character
## 5 -none- character
## 3 -none- character
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## 0 -none- character#Deteksi dan Penanganan data yang Outlier
# 1. Menghitung Q1 dan Q3 dengan benar (Gunakan TITIK bukan KOMA)
Q1 <- quantile(airquality$Ozone, 0.25, na.rm = TRUE)
Q3 <- quantile(airquality$Ozone, 0.75, na.rm = TRUE)
IQR_Ozone <- Q3 - Q1
batas_bawah <- Q1 - 1.5 * IQR_Ozone
batas_atas <- Q3 + 1.5 * IQR_Ozone
outlier <- airquality$Ozone[airquality$Ozone < batas_bawah | airquality$Ozone > batas_atas]
print(outlier)## [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
## [20] NA NA NA NA NA NA NA 135 NA NA NA NA NA NA NA NA NA 168 NA
## [39] NAsum (outlier)## [1] NA# Visualisasi boxplot untuk kolom mass di starwars
boxplot(starwars$mass,
main = "Boxplot Berat Badan (Star Wars)",
col = "darkgreen",
ylab = "Mass (Berat)",
na.rm = TRUE)
#deteksi dan haps duplikasi
sum(duplicated (starwars))## [1] 0#cek finalisasi data
summary(starwars)## name height mass hair_color
## Length:87 Min. : 66.0 Min. : 15.00 Length:87
## Class :character 1st Qu.:167.0 1st Qu.: 75.00 Class :character
## Mode :character Median :180.0 Median : 79.00 Mode :character
## Mean :174.6 Mean : 91.42
## 3rd Qu.:191.0 3rd Qu.: 80.00
## Max. :264.0 Max. :1358.00
## NA's :6
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## skin_color eye_color birth_year sex
## Length:87 Length:87 Min. : 8.00 Length:87
## Class :character Class :character 1st Qu.: 52.00 Class :character
## Mode :character Mode :character Median : 52.00 Mode :character
## Mean : 69.58
## 3rd Qu.: 52.00
## Max. :896.00
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## gender homeworld species
## Length:87 Length:87 Length:87
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## films.Length films.Class films.Mode
## 5 -none- character
## 6 -none- character
## 7 -none- character
## 4 -none- character
## 5 -none- character
## 3 -none- character
## 3 -none- character
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## 3 -none- character
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## 1 -none- character
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## 1 -none- character
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## 2 -none- character
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## 1 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 3 -none- character
## 1 -none- character
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## 2 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 2 -none- character
## 1 -none- character
## 1 -none- character
## 2 -none- character
## 1 -none- character
## 1 -none- character
## 3 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 3 -none- character
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## 3 -none- character
## 2 -none- character
## 2 -none- character
## 2 -none- character
## 1 -none- character
## 3 -none- character
## 2 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 2 -none- character
## 2 -none- character
## 1 -none- character
## 1 -none- character
## 2 -none- character
## 2 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 2 -none- character
## 1 -none- character
## 1 -none- character
## 2 -none- character
## 1 -none- character
## 1 -none- character
## 2 -none- character
## 2 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## 1 -none- character
## vehicles.Length vehicles.Class vehicles.Mode
## 2 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 1 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 1 -none- character
## 2 -none- character
## 0 -none- character
## 1 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 1 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 1 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 1 -none- character
## 0 -none- character
## 0 -none- character
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## 0 -none- character
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## 0 -none- character
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## 1 -none- character
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## 0 -none- character
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## 1 -none- character
## 0 -none- character
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## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## starships.Length starships.Class starships.Mode
## 2 -none- character
## 0 -none- character
## 0 -none- character
## 1 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 0 -none- character
## 1 -none- character
## 5 -none- character
## 3 -none- character
## 0 -none- character
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## 0 -none- character
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## 0 -none- character
## 0 -none- character
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## 1 -none- character
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## 0 -none- character
## 0 -none- character
## 1 -none- character
## 0 -none- character
## 0 -none- character#kesimpulan setelah dilakukannya hal seperti diatas, dataset starwars telah bersih dari missingvalues, data duplikat, dan outlier. setelah ini data siap digunakan untuk analisis lanjutan