library(dplyr)
##
## 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
library(tidyr)
## Warning: package 'tidyr' was built under R version 4.5.2
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.5.2
# NO 10
data1 <- datasets::ChickWeight
data1
## weight Time Chick Diet
## 1 42 0 1 1
## 2 51 2 1 1
## 3 59 4 1 1
## 4 64 6 1 1
## 5 76 8 1 1
## 6 93 10 1 1
## 7 106 12 1 1
## 8 125 14 1 1
## 9 149 16 1 1
## 10 171 18 1 1
## 11 199 20 1 1
## 12 205 21 1 1
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## 14 49 2 2 1
## 15 58 4 2 1
## 16 72 6 2 1
## 17 84 8 2 1
## 18 103 10 2 1
## 19 122 12 2 1
## 20 138 14 2 1
## 21 162 16 2 1
## 22 187 18 2 1
## 23 209 20 2 1
## 24 215 21 2 1
## 25 43 0 3 1
## 26 39 2 3 1
## 27 55 4 3 1
## 28 67 6 3 1
## 29 84 8 3 1
## 30 99 10 3 1
## 31 115 12 3 1
## 32 138 14 3 1
## 33 163 16 3 1
## 34 187 18 3 1
## 35 198 20 3 1
## 36 202 21 3 1
## 37 42 0 4 1
## 38 49 2 4 1
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## 40 67 6 4 1
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## 42 87 10 4 1
## 43 102 12 4 1
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## 522 82 6 46 4
## 523 101 8 46 4
## 524 120 10 46 4
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## 549 154 12 48 4
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## 551 222 16 48 4
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## 553 303 20 48 4
## 554 322 21 48 4
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## 556 53 2 49 4
## 557 64 4 49 4
## 558 85 6 49 4
## 559 108 8 49 4
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## 563 184 16 49 4
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## 565 233 20 49 4
## 566 237 21 49 4
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## 568 54 2 50 4
## 569 67 4 50 4
## 570 84 6 50 4
## 571 105 8 50 4
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## 577 264 20 50 4
## 578 264 21 50 4
# Menggunakan data bawaan R
data(ChickWeight)
# Membuat Line Chart
ggplot(data = ChickWeight, aes(x = Time, y = weight, color = Diet, group = Chick)) +
geom_line(alpha = 0.5) +
geom_point(size = 0.5) +
labs(title = "Tren Berat Anak Ayam Berdasarkan Waktu",
x = "Waktu (Hari)",
y = "Berat (gram)") +
theme_minimal()
# NO 11
# Load the dataset
data(diamonds)
data
## function (..., list = character(), package = NULL, lib.loc = NULL,
## verbose = getOption("verbose"), envir = .GlobalEnv, overwrite = TRUE)
## {
## fileExt <- function(x) {
## db <- grepl("\\.[^.]+\\.(gz|bz2|xz)$", x)
## ans <- sub(".*\\.", "", x)
## ans[db] <- sub(".*\\.([^.]+\\.)(gz|bz2|xz)$", "\\1\\2",
## x[db])
## ans
## }
## my_read_table <- function(...) {
## lcc <- Sys.getlocale("LC_COLLATE")
## on.exit(Sys.setlocale("LC_COLLATE", lcc))
## Sys.setlocale("LC_COLLATE", "C")
## read.table(...)
## }
## stopifnot(is.character(list))
## names <- c(as.character(substitute(list(...))[-1L]), list)
## if (!is.null(package)) {
## if (!is.character(package))
## stop("'package' must be a character vector or NULL")
## }
## paths <- find.package(package, lib.loc, verbose = verbose)
## if (is.null(lib.loc))
## paths <- c(path.package(package, TRUE), if (!length(package)) getwd(),
## paths)
## paths <- unique(normalizePath(paths[file.exists(paths)]))
## paths <- paths[dir.exists(file.path(paths, "data"))]
## dataExts <- tools:::.make_file_exts("data")
## if (length(names) == 0L) {
## db <- matrix(character(), nrow = 0L, ncol = 4L)
## for (path in paths) {
## entries <- NULL
## packageName <- if (file_test("-f", file.path(path,
## "DESCRIPTION")))
## basename(path)
## else "."
## if (file_test("-f", INDEX <- file.path(path, "Meta",
## "data.rds"))) {
## entries <- readRDS(INDEX)
## }
## else {
## dataDir <- file.path(path, "data")
## entries <- tools::list_files_with_type(dataDir,
## "data")
## if (length(entries)) {
## entries <- unique(tools::file_path_sans_ext(basename(entries)))
## entries <- cbind(entries, "")
## }
## }
## if (NROW(entries)) {
## if (is.matrix(entries) && ncol(entries) == 2L)
## db <- rbind(db, cbind(packageName, dirname(path),
## entries))
## else warning(gettextf("data index for package %s is invalid and will be ignored",
## sQuote(packageName)), domain = NA, call. = FALSE)
## }
## }
## colnames(db) <- c("Package", "LibPath", "Item", "Title")
## footer <- if (missing(package))
## paste0("Use ", sQuote(paste("data(package =", ".packages(all.available = TRUE))")),
## "\n", "to list the data sets in all *available* packages.")
## else NULL
## y <- list(title = "Data sets", header = NULL, results = db,
## footer = footer)
## class(y) <- "packageIQR"
## return(y)
## }
## paths <- file.path(paths, "data")
## for (name in names) {
## found <- FALSE
## for (p in paths) {
## tmp_env <- if (overwrite)
## envir
## else new.env()
## if (file_test("-f", file.path(p, "Rdata.rds"))) {
## rds <- readRDS(file.path(p, "Rdata.rds"))
## if (name %in% names(rds)) {
## found <- TRUE
## if (verbose)
## message(sprintf("name=%s:\t found in Rdata.rds",
## name), domain = NA)
## objs <- rds[[name]]
## lazyLoad(file.path(p, "Rdata"), envir = tmp_env,
## filter = function(x) x %in% objs)
## break
## }
## else if (verbose)
## message(sprintf("name=%s:\t NOT found in names() of Rdata.rds, i.e.,\n\t%s\n",
## name, paste(names(rds), collapse = ",")),
## domain = NA)
## }
## files <- list.files(p, full.names = TRUE)
## files <- files[grep(name, files, fixed = TRUE)]
## if (length(files) > 1L) {
## o <- match(fileExt(files), dataExts, nomatch = 100L)
## paths0 <- dirname(files)
## paths0 <- factor(paths0, levels = unique(paths0))
## files <- files[order(paths0, o)]
## }
## if (length(files)) {
## for (file in files) {
## if (verbose)
## message("name=", name, ":\t file= ...", .Platform$file.sep,
## basename(file), "::\t", appendLF = FALSE,
## domain = NA)
## ext <- fileExt(file)
## if (basename(file) != paste0(name, ".", ext))
## found <- FALSE
## else {
## found <- TRUE
## switch(ext, R = , r = {
## library("utils")
## sys.source(file, chdir = TRUE, envir = tmp_env)
## }, RData = , rdata = , rda = load(file, envir = tmp_env),
## TXT = , txt = , tab = , tab.gz = , tab.bz2 = ,
## tab.xz = , txt.gz = , txt.bz2 = , txt.xz = assign(name,
## my_read_table(file, header = TRUE, as.is = FALSE),
## envir = tmp_env), CSV = , csv = , csv.gz = ,
## csv.bz2 = , csv.xz = assign(name, my_read_table(file,
## header = TRUE, sep = ";", as.is = FALSE),
## envir = tmp_env), found <- FALSE)
## }
## if (found)
## break
## }
## if (verbose)
## message(if (!found)
## "*NOT* ", "found", domain = NA)
## }
## if (found)
## break
## }
## if (!found) {
## warning(gettextf("data set %s not found", sQuote(name)),
## domain = NA)
## }
## else if (!overwrite) {
## for (o in ls(envir = tmp_env, all.names = TRUE)) {
## if (exists(o, envir = envir, inherits = FALSE))
## warning(gettextf("an object named %s already exists and will not be overwritten",
## sQuote(o)))
## else assign(o, get(o, envir = tmp_env, inherits = FALSE),
## envir = envir)
## }
## rm(tmp_env)
## }
## }
## invisible(names)
## }
## <bytecode: 0x0000021dd9145f58>
## <environment: namespace:utils>
# Membuat Boxplot
ggplot(data = diamonds, aes(x = cut, y = price, fill = cut)) +
geom_boxplot() +
labs(title = "Distribusi Harga Berlian berdasarkan Potongan (Cut)",
x = "Kualitas Potongan (Cut)",
y = "Harga (Price in USD)") +
theme_minimal()
# NO 14
# Load the dataset
data1 <- datasets::airquality
# Mengganti missing values dengan median di setiap kolom
airquality$Ozone[is.na(airquality$Ozone)] <- median(airquality$Ozone, na.rm = TRUE)
airquality
## Ozone Solar.R Wind Temp Month Day
## 1 41.0 190 7.4 67 5 1
## 2 36.0 118 8.0 72 5 2
## 3 12.0 149 12.6 74 5 3
## 4 18.0 313 11.5 62 5 4
## 5 31.5 NA 14.3 56 5 5
## 6 28.0 NA 14.9 66 5 6
## 7 23.0 299 8.6 65 5 7
## 8 19.0 99 13.8 59 5 8
## 9 8.0 19 20.1 61 5 9
## 10 31.5 194 8.6 69 5 10
## 11 7.0 NA 6.9 74 5 11
## 12 16.0 256 9.7 69 5 12
## 13 11.0 290 9.2 66 5 13
## 14 14.0 274 10.9 68 5 14
## 15 18.0 65 13.2 58 5 15
## 16 14.0 334 11.5 64 5 16
## 17 34.0 307 12.0 66 5 17
## 18 6.0 78 18.4 57 5 18
## 19 30.0 322 11.5 68 5 19
## 20 11.0 44 9.7 62 5 20
## 21 1.0 8 9.7 59 5 21
## 22 11.0 320 16.6 73 5 22
## 23 4.0 25 9.7 61 5 23
## 24 32.0 92 12.0 61 5 24
## 25 31.5 66 16.6 57 5 25
## 26 31.5 266 14.9 58 5 26
## 27 31.5 NA 8.0 57 5 27
## 28 23.0 13 12.0 67 5 28
## 29 45.0 252 14.9 81 5 29
## 30 115.0 223 5.7 79 5 30
## 31 37.0 279 7.4 76 5 31
## 32 31.5 286 8.6 78 6 1
## 33 31.5 287 9.7 74 6 2
## 34 31.5 242 16.1 67 6 3
## 35 31.5 186 9.2 84 6 4
## 36 31.5 220 8.6 85 6 5
## 37 31.5 264 14.3 79 6 6
## 38 29.0 127 9.7 82 6 7
## 39 31.5 273 6.9 87 6 8
## 40 71.0 291 13.8 90 6 9
## 41 39.0 323 11.5 87 6 10
## 42 31.5 259 10.9 93 6 11
## 43 31.5 250 9.2 92 6 12
## 44 23.0 148 8.0 82 6 13
## 45 31.5 332 13.8 80 6 14
## 46 31.5 322 11.5 79 6 15
## 47 21.0 191 14.9 77 6 16
## 48 37.0 284 20.7 72 6 17
## 49 20.0 37 9.2 65 6 18
## 50 12.0 120 11.5 73 6 19
## 51 13.0 137 10.3 76 6 20
## 52 31.5 150 6.3 77 6 21
## 53 31.5 59 1.7 76 6 22
## 54 31.5 91 4.6 76 6 23
## 55 31.5 250 6.3 76 6 24
## 56 31.5 135 8.0 75 6 25
## 57 31.5 127 8.0 78 6 26
## 58 31.5 47 10.3 73 6 27
## 59 31.5 98 11.5 80 6 28
## 60 31.5 31 14.9 77 6 29
## 61 31.5 138 8.0 83 6 30
## 62 135.0 269 4.1 84 7 1
## 63 49.0 248 9.2 85 7 2
## 64 32.0 236 9.2 81 7 3
## 65 31.5 101 10.9 84 7 4
## 66 64.0 175 4.6 83 7 5
## 67 40.0 314 10.9 83 7 6
## 68 77.0 276 5.1 88 7 7
## 69 97.0 267 6.3 92 7 8
## 70 97.0 272 5.7 92 7 9
## 71 85.0 175 7.4 89 7 10
## 72 31.5 139 8.6 82 7 11
## 73 10.0 264 14.3 73 7 12
## 74 27.0 175 14.9 81 7 13
## 75 31.5 291 14.9 91 7 14
## 76 7.0 48 14.3 80 7 15
## 77 48.0 260 6.9 81 7 16
## 78 35.0 274 10.3 82 7 17
## 79 61.0 285 6.3 84 7 18
## 80 79.0 187 5.1 87 7 19
## 81 63.0 220 11.5 85 7 20
## 82 16.0 7 6.9 74 7 21
## 83 31.5 258 9.7 81 7 22
## 84 31.5 295 11.5 82 7 23
## 85 80.0 294 8.6 86 7 24
## 86 108.0 223 8.0 85 7 25
## 87 20.0 81 8.6 82 7 26
## 88 52.0 82 12.0 86 7 27
## 89 82.0 213 7.4 88 7 28
## 90 50.0 275 7.4 86 7 29
## 91 64.0 253 7.4 83 7 30
## 92 59.0 254 9.2 81 7 31
## 93 39.0 83 6.9 81 8 1
## 94 9.0 24 13.8 81 8 2
## 95 16.0 77 7.4 82 8 3
## 96 78.0 NA 6.9 86 8 4
## 97 35.0 NA 7.4 85 8 5
## 98 66.0 NA 4.6 87 8 6
## 99 122.0 255 4.0 89 8 7
## 100 89.0 229 10.3 90 8 8
## 101 110.0 207 8.0 90 8 9
## 102 31.5 222 8.6 92 8 10
## 103 31.5 137 11.5 86 8 11
## 104 44.0 192 11.5 86 8 12
## 105 28.0 273 11.5 82 8 13
## 106 65.0 157 9.7 80 8 14
## 107 31.5 64 11.5 79 8 15
## 108 22.0 71 10.3 77 8 16
## 109 59.0 51 6.3 79 8 17
## 110 23.0 115 7.4 76 8 18
## 111 31.0 244 10.9 78 8 19
## 112 44.0 190 10.3 78 8 20
## 113 21.0 259 15.5 77 8 21
## 114 9.0 36 14.3 72 8 22
## 115 31.5 255 12.6 75 8 23
## 116 45.0 212 9.7 79 8 24
## 117 168.0 238 3.4 81 8 25
## 118 73.0 215 8.0 86 8 26
## 119 31.5 153 5.7 88 8 27
## 120 76.0 203 9.7 97 8 28
## 121 118.0 225 2.3 94 8 29
## 122 84.0 237 6.3 96 8 30
## 123 85.0 188 6.3 94 8 31
## 124 96.0 167 6.9 91 9 1
## 125 78.0 197 5.1 92 9 2
## 126 73.0 183 2.8 93 9 3
## 127 91.0 189 4.6 93 9 4
## 128 47.0 95 7.4 87 9 5
## 129 32.0 92 15.5 84 9 6
## 130 20.0 252 10.9 80 9 7
## 131 23.0 220 10.3 78 9 8
## 132 21.0 230 10.9 75 9 9
## 133 24.0 259 9.7 73 9 10
## 134 44.0 236 14.9 81 9 11
## 135 21.0 259 15.5 76 9 12
## 136 28.0 238 6.3 77 9 13
## 137 9.0 24 10.9 71 9 14
## 138 13.0 112 11.5 71 9 15
## 139 46.0 237 6.9 78 9 16
## 140 18.0 224 13.8 67 9 17
## 141 13.0 27 10.3 76 9 18
## 142 24.0 238 10.3 68 9 19
## 143 16.0 201 8.0 82 9 20
## 144 13.0 238 12.6 64 9 21
## 145 23.0 14 9.2 71 9 22
## 146 36.0 139 10.3 81 9 23
## 147 7.0 49 10.3 69 9 24
## 148 14.0 20 16.6 63 9 25
## 149 30.0 193 6.9 70 9 26
## 150 31.5 145 13.2 77 9 27
## 151 14.0 191 14.3 75 9 28
## 152 18.0 131 8.0 76 9 29
## 153 20.0 223 11.5 68 9 30
colSums(is.na(airquality))
## Ozone Solar.R Wind Temp Month Day
## 0 7 0 0 0 0
# NO 15
# Load the dataset
data1 <- datasets::mtcars
# Melihat data 6 baris pertama
head(mtcars)
## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
# Menghitung korelasi antara mpg dan cyl
cor(mtcars$mpg, mtcars$cyl)
## [1] -0.852162
# NO 18
# Load the dataset
plot(mtcars$wt, mtcars$mpg,
main = "Scatterplot MPG vs WT",
xlab = "Weight (1000 lbs)",
ylab = "Miles per Gallon",
pch = 19, col = "blue")
# NO 21
data(diamonds)
data
## function (..., list = character(), package = NULL, lib.loc = NULL,
## verbose = getOption("verbose"), envir = .GlobalEnv, overwrite = TRUE)
## {
## fileExt <- function(x) {
## db <- grepl("\\.[^.]+\\.(gz|bz2|xz)$", x)
## ans <- sub(".*\\.", "", x)
## ans[db] <- sub(".*\\.([^.]+\\.)(gz|bz2|xz)$", "\\1\\2",
## x[db])
## ans
## }
## my_read_table <- function(...) {
## lcc <- Sys.getlocale("LC_COLLATE")
## on.exit(Sys.setlocale("LC_COLLATE", lcc))
## Sys.setlocale("LC_COLLATE", "C")
## read.table(...)
## }
## stopifnot(is.character(list))
## names <- c(as.character(substitute(list(...))[-1L]), list)
## if (!is.null(package)) {
## if (!is.character(package))
## stop("'package' must be a character vector or NULL")
## }
## paths <- find.package(package, lib.loc, verbose = verbose)
## if (is.null(lib.loc))
## paths <- c(path.package(package, TRUE), if (!length(package)) getwd(),
## paths)
## paths <- unique(normalizePath(paths[file.exists(paths)]))
## paths <- paths[dir.exists(file.path(paths, "data"))]
## dataExts <- tools:::.make_file_exts("data")
## if (length(names) == 0L) {
## db <- matrix(character(), nrow = 0L, ncol = 4L)
## for (path in paths) {
## entries <- NULL
## packageName <- if (file_test("-f", file.path(path,
## "DESCRIPTION")))
## basename(path)
## else "."
## if (file_test("-f", INDEX <- file.path(path, "Meta",
## "data.rds"))) {
## entries <- readRDS(INDEX)
## }
## else {
## dataDir <- file.path(path, "data")
## entries <- tools::list_files_with_type(dataDir,
## "data")
## if (length(entries)) {
## entries <- unique(tools::file_path_sans_ext(basename(entries)))
## entries <- cbind(entries, "")
## }
## }
## if (NROW(entries)) {
## if (is.matrix(entries) && ncol(entries) == 2L)
## db <- rbind(db, cbind(packageName, dirname(path),
## entries))
## else warning(gettextf("data index for package %s is invalid and will be ignored",
## sQuote(packageName)), domain = NA, call. = FALSE)
## }
## }
## colnames(db) <- c("Package", "LibPath", "Item", "Title")
## footer <- if (missing(package))
## paste0("Use ", sQuote(paste("data(package =", ".packages(all.available = TRUE))")),
## "\n", "to list the data sets in all *available* packages.")
## else NULL
## y <- list(title = "Data sets", header = NULL, results = db,
## footer = footer)
## class(y) <- "packageIQR"
## return(y)
## }
## paths <- file.path(paths, "data")
## for (name in names) {
## found <- FALSE
## for (p in paths) {
## tmp_env <- if (overwrite)
## envir
## else new.env()
## if (file_test("-f", file.path(p, "Rdata.rds"))) {
## rds <- readRDS(file.path(p, "Rdata.rds"))
## if (name %in% names(rds)) {
## found <- TRUE
## if (verbose)
## message(sprintf("name=%s:\t found in Rdata.rds",
## name), domain = NA)
## objs <- rds[[name]]
## lazyLoad(file.path(p, "Rdata"), envir = tmp_env,
## filter = function(x) x %in% objs)
## break
## }
## else if (verbose)
## message(sprintf("name=%s:\t NOT found in names() of Rdata.rds, i.e.,\n\t%s\n",
## name, paste(names(rds), collapse = ",")),
## domain = NA)
## }
## files <- list.files(p, full.names = TRUE)
## files <- files[grep(name, files, fixed = TRUE)]
## if (length(files) > 1L) {
## o <- match(fileExt(files), dataExts, nomatch = 100L)
## paths0 <- dirname(files)
## paths0 <- factor(paths0, levels = unique(paths0))
## files <- files[order(paths0, o)]
## }
## if (length(files)) {
## for (file in files) {
## if (verbose)
## message("name=", name, ":\t file= ...", .Platform$file.sep,
## basename(file), "::\t", appendLF = FALSE,
## domain = NA)
## ext <- fileExt(file)
## if (basename(file) != paste0(name, ".", ext))
## found <- FALSE
## else {
## found <- TRUE
## switch(ext, R = , r = {
## library("utils")
## sys.source(file, chdir = TRUE, envir = tmp_env)
## }, RData = , rdata = , rda = load(file, envir = tmp_env),
## TXT = , txt = , tab = , tab.gz = , tab.bz2 = ,
## tab.xz = , txt.gz = , txt.bz2 = , txt.xz = assign(name,
## my_read_table(file, header = TRUE, as.is = FALSE),
## envir = tmp_env), CSV = , csv = , csv.gz = ,
## csv.bz2 = , csv.xz = assign(name, my_read_table(file,
## header = TRUE, sep = ";", as.is = FALSE),
## envir = tmp_env), found <- FALSE)
## }
## if (found)
## break
## }
## if (verbose)
## message(if (!found)
## "*NOT* ", "found", domain = NA)
## }
## if (found)
## break
## }
## if (!found) {
## warning(gettextf("data set %s not found", sQuote(name)),
## domain = NA)
## }
## else if (!overwrite) {
## for (o in ls(envir = tmp_env, all.names = TRUE)) {
## if (exists(o, envir = envir, inherits = FALSE))
## warning(gettextf("an object named %s already exists and will not be overwritten",
## sQuote(o)))
## else assign(o, get(o, envir = tmp_env, inherits = FALSE),
## envir = envir)
## }
## rm(tmp_env)
## }
## }
## invisible(names)
## }
## <bytecode: 0x0000021dd9145f58>
## <environment: namespace:utils>
library(ggplot2)
str(diamonds$cut)
## Ord.factor w/ 5 levels "Fair"<"Good"<..: 5 4 2 4 2 3 3 3 1 3 ...
# NO 22
# Memuat data (opsional, faithful sudah ada di base R)
data(faithful)
# Menghitung korelasi Pearson (default)
cor(faithful$eruptions, faithful$waiting)
## [1] 0.9008112
# NO 25
# Memuat dataset Titanic bawaan R
data("Titanic")
# Mengubahnya menjadi dataframe agar bisa menggunakan sintaks $
titanic <- as.data.frame(Titanic)
# Melihat tabel hitungan (0: tidak selamat, 1: selamat)
table(titanic$Survived)
##
## No Yes
## 16 16
# Total jumlah yang selamat saja (menjumlahkan angka 1)
sum(titanic$Survived == 1)
## [1] 0
# NO 28
str(mtcars)
## 'data.frame': 32 obs. of 11 variables:
## $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
## $ cyl : num 6 6 4 6 8 6 8 4 4 6 ...
## $ disp: num 160 160 108 258 360 ...
## $ hp : num 110 110 93 110 175 105 245 62 95 123 ...
## $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
## $ wt : num 2.62 2.88 2.32 3.21 3.44 ...
## $ qsec: num 16.5 17 18.6 19.4 17 ...
## $ vs : num 0 0 1 1 0 1 0 1 1 1 ...
## $ am : num 1 1 1 0 0 0 0 0 0 0 ...
## $ gear: num 4 4 4 3 3 3 3 4 4 4 ...
## $ carb: num 4 4 1 1 2 1 4 2 2 4 ...
# NO 29
data(iris)
head(iris) # Melihat 6 baris pertama
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
boxplot(Sepal.Length ~ Species, data = iris,
main = "Perbedaan Sepal.Length berdasarkan Spesies",
xlab = "Spesies",
ylab = "Sepal Length (cm)",
col = c("red", "green", "blue"))
