A day in the library: Introduction to R

Oleh:Dasapta Erwin Irawan@dasaptaerwin

ITB Central Library26 Mei 2015

Pendahuluan

Siapa saya?

I Dosen KK Geologi Terapan, FITB, ITBI Mengajar di: Prodi S1 Teknik Geologi dan S2 Teknik Air TanahI Media sosial: @dasaptaerwin, +Dasapta Erwin Irawan

Lisensi dokumen

Dengan menyebutkan penulis dan dokumen ini dalam DaftarPustaka, anda boleh:

memperbanyak, menyebarkan, memodifikasi sebagian atau seluruhdokumen ini,

untuk kegiatan non-komersial.

Sumber

Beberapa bagian dari paparan ini diadaptasi dari:

I Slide Coursera RD.Peng: R.D. Peng on GithubI Slide Coursera Data Specialization oleh J.T. Leek: Data

SpecializationI Slide tutorial Kevin Markham: Kevin Markham on GithubI Website Quick R TutorialI Website R Introduction to StatisticsI Website saya R from DummiesI dll

Data

I Data yang disertakan dalam tutorial ini adalahBandungData.csv.

I Berisi data kualitas air (major element) air S. Cikapundung danair tanah di bantaran sungainya.

Apakah R?

Apakah R?

I Alfabet ke-18

Apakah R?

I R adalah bahasa pemrograman (statistik) yang dikembangkandari Bahasa S.

I S ditulis pada tahun 1976 (saya lahir) oleh John Chambers dkkdi Bell Labs.

I S awalnya ditulis sebagai library statistik Bahasa Fortran.I S pada tahun 1988 mulai ditulis ulang dengan Bahasa C++,

hingga kemudian menjadi R yang kita kenal sekarang.

Mengapa R?

I Free dan Lightweight: free as breathing yang diperlukanhanya koneksi internet, ukuran installer R base < 70 MB, RStudio < 60 MB. (Bandingkan dengan SPSS, Matlab)(Bandingkan dengan SPSS, Matlab)

I Cross platform: R tersedia untuk Linux, Mac, dan (tentunya)Windows. (Sebagian besar Windows only)

I Peran komunitas open source: sangat aktif, mailing lists, RStack Overflow, Youtube, dll.

Mengapa R cocok untuk engineer?

I Reproducibility: semua yang ditulis dengan R bisa diulangoleh orang lain untuk diperbaiki dan dikembangkan. Karenabasisnya open source, maka semangat saling berbagi diantarapemakai R sangat tinggi.

I Terstruktur: basis command line, memang sulit pada awalnya,tapi membuat analisis lebih terstruktur, tiap langkah dapatdidokumentasikan dengan memberi komentar dll.

I Visualisasi: R dapat menghasilkan grafis yang sangat bagusdan plot yang fully-customizeable. Banyak output grafik yangtidak dapat dibuat dengan piranti lunak spreadsheetkonvensional.

Mengapa R cocok untuk non-programmer?

I Mudah: sudah banyak tutorial dilengkapi codenya di internet,tinggal mengetik how to .... in R.

I Sederhana: syntax penulisan kode sederhana, berbasis obyek.I Pengembangan intensif: R dapat dikembangkan melalui >

4000 R packages, bahkan untuk web-authoring, web-scraping,analisis spasial, dll.

Memulai R

Karakter R

I case sensitiveI command lineI what you mean is what you get

Karakter R 2

I R base telah memiliki perbendaharaan fungsi yang sangat kayaI Beberapa package juga telah dimasukkan ke dalam R baseI Pengembangan package tujuannya untuk:I memudahkan dan menyingkat kode, misal: dari 10 baris

menjadi tiga baris sajaI meningkatkan kualitas grafis

Karakter R 3

Jadi jangan heran kalau anda telah fasih menjalankan satu proses,kemudian dengan perkembangan baru, baris kode anda menjaditidak optimal (terlalu panjang).

Komponen R

Sebelum ke tahap instalasi, kita kenali dulu komponen R yangterdiri dari:

I R base atau R coreI R IDEI R packages

R base atau R core

I Inti dari R, full functionality.I Jendela script, console, proses, dan output terpisah.I Unduh installer dari Server CRAN. Mirrors di Indonesia:I Mirror BPPTI Mirror Uni Jember

R IDE (Integrated Development Environment)

I Ada R Studio atau R Commander.I Jendela script, console, proses, dan output menyatu.I Unduh installer dari Website RStudio

Jendela R base

Jendela R Studio

R packages

I Pengembangan dari fungsi-fungsi R base dikemas sebagai Rpackages.

I Saat ini ada lebih dari 4000 packages di sini yang telahterklasifikasi klik menu Task Views, diantaranya:

I SpasialI TimeseriesI LingkunganI bahkan Medis

R packages 2

I Beberapa packages yang sangat fungsional dari pengembangindividu dapat dimasukkan ke dalam fungsi dasar R base versiberikutnya, misal: utils, stats, datasets, graphics,grDevices, grid, methods, tools, parallel, compiler, splines,tcltk, stats4.

R packages 3

I Beberapa packages yang sering saya pakai, diantaranya:cluster, foreign, mgcv, rpart, spatial, dll.

I Beberapa package yang dikembangkan oleh ahli biologi danlingkungan, dapat diunduh dari Website Bioconductor Project

I Atau dari individu langsung via repo Github. Perlumenginstalasi devtools package

R packages 4

Package harus diunduh dan diinstalasi terlebih dahulu denganperintah:

install.packages("packageName")

Kemudian package harus dimuat ke memory dengan perintah:

library(packageName)

atau

require(packageName)

InstalasiSekarang mulailah “pekerjaan kotor kita”, yaitu menginstalasi R kedalam PC atau laptop kita. Untuk itu coba perhatikan beberapa halberikut ini:

I Spesifikasi komputer/laptop: Tidak ada spesifikasi khususuntuk R, tetapi prinsip utamanya adalah makin besar data yanganda gunakan, makin kompleks analisis yang anda lakukan,akan memerlukan spesifikasi prosesor dan RAM yang makinbesar. Jadi ini akan sangat bergantung kepada kebutuhan anda.Untuk keperluan pembelajaran gunakan saja komputer yanganda miliki sekarang.

I Sistem operasi (OS): Seperti yang telah saya sampaikansebelumnya, R berjalan di semua OS: Linux (bisa Ubuntu,Fedora dll), Mac OS, dan tentunya Windows. Jangan kuatir,yang manapun OS yang anda pakai, spesifikasi R nya akansama persis.

Instalasi 2

I Apa saja yang perlu anda unduh dan install:I R base: Inti dari R.I Kunjungi Situs R ProjectI Pilih mirror server. Pilih server yang ada di Indonesia. Klik

CRAN mirror di dalam kotak “Getting Started”. Cari server diIndonesia. Ada dua, silahkan anda pilih:

I Server BPPTI Server Universitas JemberI Setelah server CRAN-BPPT terbuka, klik versi R sesuai dengan

OS yang anda miliki.

Instalasi 3

I R Studio: lingkungan pemrograman.I Kunjungi Situs R StudioI Klik menu Products > RStudio > klik tombol Download

RStudio Desktop. Secara otomatis R Studio akan membacaOS yang anda pakai dan proses pengunduhan akan segeradimulai.

Instalasi 4

Atau anda bisa langsung buka halamanhttp://www.rstudio.com/products/rstudio/download/,Pilih versi RStudio.

I Pilihan installer yang ada per tanggal 04 September 2014adalah:

I RStudio 0.98.1049 - Windows XP/Vista/7/8 ukuran file 48.2MB tanggal update 2014-09-02

I RStudio 0.98.1049 - Mac OS X 10.6+ (64-bit) ukuran file 37.8MB tanggal update 2014-09-02

I RStudio 0.98.1049 - Debian 6+/Ubuntu 10.04+ (32-bit)ukuran file 56.3 MB tanggal update 2014-09-02

Instalasi 5

I RStudio 0.98.1049 - Debian 6+/Ubuntu 10.04+ (64-bit)ukuran file 58 MB tanggal update 2014-09-02

I RStudio 0.98.1049 - Fedora 13+/openSUSE 11.4+ (32-bit)ukuran file 56.6 MB tanggal update 2014-09-02

I RStudio 0.98.1049 - Fedora 13+/openSUSE 11.4+ (64-bit)ukuran file 57.9 MB tanggal update 2014-09-02

Instalasi 6

Setelah proses pengunduhan selesai, jalankan file programinstalasinya:

I Untuk Linux: jalankan file xRstudioxx.deb dan ikutiperintahnya

I Untuk Mac OSX: jalankan file xRstudioxx.dmg dan ikutiperintahnya

I Untuk Windows: jalankan file xRstudioxx.exe dan ikutiperintahnya

Bekerja dengan R

Format data

I format database:I kasus/sampel dalam barisI variable/parameter/pengukuran dalam kolomI tanpa judul tabel dan aksesori lainnya

Format data 2

I dulu data harus format text/ASCII bukan binary (xls, xlsx, dll),misal:

I txtI csv (comma separated values)I dengan fungsi dasar R

Format data 3

I sekarang dengan fungsi dari package tambahan, sepertiforeign, read.table, readxl, R dapat meng-importberbagai format file text maupun binary, misal:

I xls, xlsx (Ms Office)I sav (SPPS)I dta (Stata)I odt (LibreOffice)

Format data 4

Memuat data ke dalam R

data <- read.csv("BandungData.csv", header = TRUE)attach(data)

## The following object is masked from package:datasets:#### CO2

Dimensi data

dim(data)

## [1] 295 34

Jenis datastr(data)

## 'data.frame': 295 obs. of 34 variables:## $ no : int 16 22 263 17 12 18 13 19 14 20 ...## $ code : int 116 122 8 117 112 118 113 119 114 120 ...## $ year : int 1997 1997 1997 1997 1997 1997 1997 1997 1997 1997 ...## $ type : Factor w/ 2 levels "groundwater",..: 1 1 2 1 1 1 1 1 1 1 ...## $ x : num 785175 785168 799275 785175 785181 ...## $ y : num 10752836 10752843 10753680 10752840 10752843 ...## $ distx : num 6897 6904 0 6897 6891 ...## $ elv : int 1338 1336 1336 1320 1300 1247 1240 1230 1228 1225 ...## $ aq : Factor w/ 3 levels "breccias","clay",..: 3 3 3 3 3 3 3 3 3 3 ...## $ zone : Factor w/ 2 levels "eff","inf": 1 1 1 1 1 1 1 1 1 1 ...## $ ec : num 71.9 71.9 77 71.9 71.9 71.9 71.9 71.9 71.9 71.9 ...## $ ph : num 6.89 6.89 6.39 6.89 6.89 ...## $ hard : num 11 11 26.4 11 11 11 11 11 11 11 ...## $ tds : num 58.7 58.7 50 58.7 58.7 ...## $ temp : num 21 21 16.1 21 21 ...## $ eh : num 30 24 -0.45 34 35 32 30 23 24 21 ...## $ Q : num 1 1 NA 1 1 1 1 1 1 1 ...## $ Ca : num 1.8 1.8 9.44 1.8 1.8 1.8 1.8 1.8 1.8 1.8 ...## $ Mg : num 1.7 1.7 0.72 1.7 1.7 1.7 1.7 1.7 1.7 1.7 ...## $ Fe : num 0.08 0.08 0.216 0.08 0.08 0.08 0.08 0.08 0.08 0.08 ...## $ Mn : num 0.22 0.22 0 0.22 0.22 0.22 0.22 0.22 0.22 0.22 ...## $ K : num 1.7 1.7 0.8 1.7 1.7 1.7 1.7 1.7 1.7 1.7 ...## $ Na : num 5 5 3.2 5 5 5 5 5 5 5 ...## $ CO3 : num 7 6 0 6 5.8 6.8 6.7 8 8 8.2 ...## $ HCO3 : num 8 7.8 31.4 6.7 7 ...## $ CO2 : num 36.3 36.3 7.28 36.3 36.3 36.3 36.3 36.3 36.3 36.3 ...## $ Cl : num 4.8 4.8 5.52 4.8 4.8 4.8 4.8 4.8 4.8 4.8 ...## $ SO4 : num 0.6 0.6 0 0.6 0.6 0.6 0.6 0.6 0.6 0.6 ...## $ NO2 : num 0 0 0.04 0 0 0 0 0 0 0 ...## $ NO3 : num 4.7 4.7 2.24 4.7 4.7 4.7 4.7 4.7 4.7 4.7 ...## $ SiO2 : num 23 23 37.8 23 23 ...## $ cumrain: num 38.5 38.5 38.5 38.5 38.5 38.5 38.5 38.5 38.5 38.5 ...## $ lag1 : num 32.4 32.4 32.4 32.4 32.4 32.4 32.4 32.4 32.4 32.4 ...## $ lag1.1 : logi NA NA NA NA NA NA ...

Beberapa contoh visualisasi dan analisis denganfungsi dasar R

Scatter plot

plot(tds, temp,xlab = "tds (ppm)",ylab = "temp (^oC)",bg = "lightblue",col = "black",cex = 1.1,pch = 21,frame = FALSE)

abline(lm(tds~temp), col="red") # regression line (y~x)lines(lowess(tds,temp), col="blue") # lowess line (x,y)

Note: semua yang diketik di belakang simbol # tidak dieksekusi olehR, disebut comment. Biasa digunakan untuk memberi penjelasanbaris atau kelompok baris kode.

Scatter plot 2

0 200 400 600 800 1000 1200

1520

2530

35

tds (ppm)

tem

p (C

)

Mengapa garis regresi tidak diagonal?

Histogram

hist(tds, col="red")

Histogram of tds

tds

Fre

quen

cy

0 200 400 600 800 1000 1200

020

4060

80

Multiple Histogram 2par(mfrow=c(1,3))hist(tds, col="red")hist(ph, col="green")hist(hard, col="blue")

Histogram of tds

tds

Fre

quen

cy

0 400 1000

020

4060

80

Histogram of ph

ph

Fre

quen

cy

5 6 7 8 9

020

4060

8010

0

Histogram of hard

hard

Fre

quen

cy0 40 80

050

100

150

Multiple Histogram 3par(mfrow=c(2,2))hist(tds, col="cyan")hist(ph, col="magenta")hist(hard, col="yellow")hist(eh, col="blue")

Histogram of tds

tds

Fre

quen

cy

0 200 600 1000

060

Histogram of ph

phF

requ

ency

5 6 7 8 9

060

Histogram of hard

hard

Fre

quen

cy

0 20 40 60 80

015

0

Histogram of eh

eh

Fre

quen

cy

−100 −50 0 50

080

Analisis regresi

Berikut contoh perintah untuk mengetahui koef dan interceptpersamaan regresi.

fit <- lm(tds ~ temp, data = data)coef(fit)

Analisis regresi 2

fit <- lm(data$tds ~ data$temp, data = data)coef(fit)

## (Intercept) data$temp## -650.96402 37.93123

Pairs analysisUntuk memvisualisasikan matriks korelasi.

group1 <- data[,c("x", "y", "elv", "aq", "ec", "ph","hard", "tds", "temp", "eh", "Q")]

pairs(group1,labels=colnames(group1),main="Physical parameter",pch=21, bg=c("red", "blue")[unclass(data$type)],upper.panel=NULL)

legend(x=0.6, y=0.8, levels(data$type),pt.bg=c("red", blue"),pch=21,bty="n",ncol=2,horiz=F)

Pairs analysis 2

700 900 1100 1300

700

1000 elv

56

78

ph

040

80

hard

040

010

00

tds

1525

35

temp

700 900 1100 1300

04

8

5 6 7 8 0 20 40 60 80 0 400 800 1200 15 20 25 30 35 0 2 4 6 8 10

04

8

Q

Physical parameter

groundwater river

Multiple linear regression

Misal:

I Apakah tds merupakan fungsi linear dari unsur Ca, Mg, dan Fe?I atau tds adalah fungsi dari unsur HCO3, CO3, SO4, Cl?

Multiple linear regression 2fit <- lm(tds ~ Ca + Mg + Fe, data=data)summary(fit)

#### Call:## lm(formula = tds ~ Ca + Mg + Fe, data = data)#### Residuals:## Min 1Q Median 3Q Max## -352.11 -57.96 -29.36 36.98 835.27#### Coefficients:## Estimate Std. Error t value Pr(>|t|)## (Intercept) 77.7128 12.3875 6.273 1.28e-09 ***## Ca 2.8913 0.4657 6.209 1.84e-09 ***## Mg 11.2824 1.2024 9.384 < 2e-16 ***## Fe -43.5776 33.5691 -1.298 0.195## ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1#### Residual standard error: 120.8 on 291 degrees of freedom## Multiple R-squared: 0.543, Adjusted R-squared: 0.5383## F-statistic: 115.3 on 3 and 291 DF, p-value: < 2.2e-16

Multiple linear regression 3fit2 <- lm(tds ~ HCO3 + CO3 + SO4 + Cl, data=data)summary(fit2)

#### Call:## lm(formula = tds ~ HCO3 + CO3 + SO4 + Cl, data = data)#### Residuals:## Min 1Q Median 3Q Max## -369.64 -37.61 -23.53 24.36 688.83#### Coefficients:## Estimate Std. Error t value Pr(>|t|)## (Intercept) 55.08578 10.67173 5.162 4.55e-07 ***## HCO3 0.77447 0.06993 11.075 < 2e-16 ***## CO3 1.13775 0.73530 1.547 0.123## SO4 1.47805 0.25607 5.772 2.01e-08 ***## Cl 2.41691 0.29699 8.138 1.19e-14 ***## ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1#### Residual standard error: 97.88 on 290 degrees of freedom## Multiple R-squared: 0.701, Adjusted R-squared: 0.6969## F-statistic: 170 on 4 and 290 DF, p-value: < 2.2e-16

Multiple linear regression 4

anova(fit, fit2)

## Analysis of Variance Table#### Model 1: tds ~ Ca + Mg + Fe## Model 2: tds ~ HCO3 + CO3 + SO4 + Cl## Res.Df RSS Df Sum of Sq F Pr(>F)## 1 291 4246450## 2 290 2778559 1 1467891 153.2 < 2.2e-16 ***## ---## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

PCA

# Prepare Datamydata <- data[,c("elv", "ph",

"hard", "tds", "temp", "Q")]

mydata <- na.omit(mydata) # listwise deletion of missingmydata <- scale(mydata)

# run PCAfit <- princomp(mydata, cor=TRUE)

PCA 2

summary(fit) # print variance accounted for

## Importance of components:## Comp.1 Comp.2 Comp.3 Comp.4 Comp.5## Standard deviation 1.3597606 1.1297573 0.9700609 0.8708904 0.8527924## Proportion of Variance 0.3081582 0.2127253 0.1568364 0.1264083 0.1212091## Cumulative Proportion 0.3081582 0.5208834 0.6777198 0.8041281 0.9253373## Comp.6## Standard deviation 0.66931040## Proportion of Variance 0.07466273## Cumulative Proportion 1.00000000

PCA 3loadings(fit) # pc loadings

#### Loadings:## Comp.1 Comp.2 Comp.3 Comp.4 Comp.5 Comp.6## elv 0.488 -0.133 0.800 0.132 -0.294## ph -0.111 0.687 0.709## hard 0.250 0.368 -0.791 -0.395 0.141## tds -0.605 -0.206 0.130 -0.153 -0.737## temp -0.561 -0.101 0.558 -0.111 0.589## Q -0.598 -0.568 -0.159 0.537#### Comp.1 Comp.2 Comp.3 Comp.4 Comp.5 Comp.6## SS loadings 1.000 1.000 1.000 1.000 1.000 1.000## Proportion Var 0.167 0.167 0.167 0.167 0.167 0.167## Cumulative Var 0.167 0.333 0.500 0.667 0.833 1.000

PCA 4

plot(fit,type="lines") # scree plot

fit

Var

ianc

es

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

Comp.1 Comp.2 Comp.3 Comp.4 Comp.5 Comp.6

PCA 5fit$scores # the principal components

## Comp.1 Comp.2 Comp.3 Comp.4 Comp.5## 1 2.555170709 4.137174e-01 -0.401835894 0.692409628 0.378888717## 2 2.550748586 4.149192e-01 -0.401556057 0.685160307 0.377692454## 4 2.515371607 4.245332e-01 -0.399317361 0.627165736 0.368122347## 5 2.471150383 4.365508e-01 -0.396518992 0.554672522 0.356159713## 6 2.353964139 4.683973e-01 -0.389103312 0.362565505 0.324458733## 7 2.338486711 4.726035e-01 -0.388123883 0.337192881 0.320271811## 8 2.316376099 4.786123e-01 -0.386724698 0.300946274 0.314290494## 9 2.311953977 4.798140e-01 -0.386444861 0.293696952 0.313094230## 10 2.305320793 4.816167e-01 -0.386025106 0.282822970 0.311299835## 11 2.250044263 4.966386e-01 -0.382527144 0.192206453 0.296346543## 12 2.227933651 5.026474e-01 -0.381127959 0.155959846 0.290365226## 13 1.867410026 -2.616254e-01 -0.089218290 0.321085216 -0.257670279## 14 1.645181935 -7.239144e-01 1.219284576 0.021630346 -0.182046889## 16 1.105647572 -1.059011e+00 1.265951112 0.539519751 -0.446562492## 17 0.351155766 -1.836384e+00 0.960274284 -0.048751818 0.158178575## 18 1.465595962 -6.196960e-01 0.299890164 -0.304720998 -1.177913472## 19 -0.506573219 -1.511914e+00 0.026146169 0.417734514 -0.462104409## 20 0.164865384 -7.847679e-01 0.991985755 -0.004910367 -0.720360407## 21 0.604547067 -3.336723e-01 0.941685813 -0.028105997 -0.228600111## 22 -0.316973177 -8.740355e-01 0.706829110 -0.050780072 -1.198143500## 23 0.112829795 -1.087316e-01 1.113450746 -0.236811961 -0.189360571## 26 -0.422571088 -9.552581e-01 0.281569891 -0.716878176 0.117034146## 27 0.183249922 -5.443714e-01 1.454311490 -0.671865073 0.519144083## 28 0.173662027 -3.950843e-01 -0.266312917 -0.736196403 0.213648207## 30 -0.849718165 1.602827e-01 0.123351495 -0.140031646 -0.092586720## 31 -1.041995227 -5.897139e-01 0.963761177 -0.431737527 -0.135459601## 32 -0.493401113 -7.164377e-01 0.572893886 -0.427216979 -0.628634028## 33 -0.548678826 3.305960e-01 0.752028654 -0.195261029 0.092833351## 34 -0.597390943 7.297445e-01 0.389409525 -0.311898460 0.053622524## 35 -1.037871003 -3.012907e-01 -0.290095619 -0.158146149 0.291398886## 36 -0.569574093 7.840560e-01 0.506503125 -0.267664057 -0.089589587## 37 -0.858506126 -4.987261e+00 -4.102522220 -1.635829589 1.628323847## 38 -0.188062864 -1.090072e-01 0.665698772 -0.432650914 0.175386493## 39 -0.140616531 -2.636812e+00 -1.201290312 -0.997872596 0.716545447## 40 -0.017171285 1.279101e+00 -0.715900878 -0.409506693 -0.389396937## 41 -0.540991634 -8.031882e-01 0.836564968 -0.652820891 -0.510649344## 42 1.127365472 -1.675026e+00 0.414883265 -1.554880662 -1.957106903## 43 -0.278374427 3.543304e-01 -0.843816716 -0.412079451 -1.244577519## 44 -1.346496992 -4.068094e-01 -0.414212423 -0.189233327 -0.002247759## 45 0.009278339 1.365973e-01 -0.692082508 -0.758408638 -1.722412419## 46 -0.132488469 1.203855e+00 -1.245603597 -0.462077198 -1.469215271## 47 -0.691031627 4.197883e-01 0.410091548 -0.449287311 0.425443618## 49 -1.001105077 5.869796e-01 0.625065488 -0.373528736 -0.134504628## 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1.799130053## 117 -1.030864573 1.044349e+00 -0.451623784 -0.675792817 1.869080318## 119 2.555170709 4.137174e-01 -0.401835894 0.692409628 0.378888717## 120 2.550748586 4.149192e-01 -0.401556057 0.685160307 0.377692454## 122 1.291904294 1.154642e+00 0.988405119 1.485026738 2.029273960## 123 2.471150383 4.365508e-01 -0.396518992 0.554672522 0.356159713## 124 1.859654871 -7.821996e-01 1.205712484 0.373222433 -0.124028114## 125 0.540571105 -9.237173e-02 1.437758400 1.412676091 1.670729657## 126 0.022876147 6.351798e-01 0.538254336 1.462636384 0.806749789## 127 2.311953977 4.798140e-01 -0.386444861 0.293696952 0.313094230## 128 2.305320793 4.816167e-01 -0.386025106 0.282822970 0.311299835## 129 2.250044263 4.966386e-01 -0.382527144 0.192206453 0.296346543## 130 2.227933651 5.026474e-01 -0.381127959 0.155959846 0.290365226## 131 1.124146449 -4.748787e-01 0.908804971 0.823689265 -0.088039162## 132 2.139491203 5.266825e-01 -0.375531220 0.010973418 0.266439958## 134 1.767912272 -2.345858e-01 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0.337192881 0.320271811## 185 0.046192081 -1.662134e+00 -0.008833450 1.323899686 -0.312571485## 186 -0.008882295 5.346316e-01 0.127193981 1.594500397 0.290718259## 187 -0.020782851 -5.776948e-01 -0.354458118 1.509197768 0.566539467## 188 0.431875294 -1.067575e+00 0.775000839 0.942029812 -0.247471397## 189 -0.373630064 -6.711959e-01 -0.475776552 1.405617377 0.260930188## 190 0.336960999 5.376958e-01 0.449136551 1.218446825 0.155644409## 191 1.645181935 -7.239144e-01 1.219284576 0.021630346 -0.182046889## 193 1.767912272 -2.345858e-01 -0.082921959 0.157975485 -0.284586206## 194 -0.250464296 -5.152503e+00 -4.140999801 -0.639047900 1.792810064## 195 1.785721411 6.228231e-01 -0.353144265 -0.568972292 0.170738886## 196 1.763610799 6.288319e-01 -0.351745080 -0.605218899 0.164757569## 197 0.164865384 -7.847679e-01 0.991985755 -0.004910367 -0.720360407## 198 -0.226708775 2.936038e-01 0.380708669 0.311891434 0.551051275## 199 0.338024206 -5.864329e-01 1.444517196 -0.418138825 0.561013302## 200 0.088319786 -1.841170e-01 0.648208963 0.020431672 0.250152955## 203 -0.377060811 -4.559756e-02 -0.262525538 -0.270324137 -0.010753884## 204 1.409841007 7.249724e-01 -0.329358124 -1.185164609 0.069056498## 205 -1.028389020 2.528648e-01 0.531490852 -0.152533675 0.419483135## 207 0.090250743 -8.830798e-01 1.193501400 -0.842189765 -0.875434730## 208 -0.107450613 -2.645825e+00 -1.203389089 -0.943502686 0.725517422## 209 1.299287947 7.550163e-01 -0.322362200 -1.366397643 0.039149913## 210 -0.548678826 3.305960e-01 0.752028654 -0.195261029 0.092833351## 211 0.064554869 1.215753e-01 -0.695580470 -0.667792121 -1.707459126## 212 1.288232641 7.580207e-01 -0.321662608 -1.384520947 0.036159255## 213 -0.964313214 8.308599e-01 -1.547632118 0.180612143 -1.722440239## 214 -1.075161145 -5.807007e-01 0.965859955 -0.486107437 -0.144431576## 215 -0.306898411 -5.498025e-01 0.572498402 -0.575807742 -1.549445651## 216 -0.504456419 -7.134333e-01 0.573593478 -0.445340283 -0.631624686## 217 1.127365472 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0.982262170 -1.079257597 -0.402058303## 234 1.033960603 8.271217e-01 -0.305571983 -1.801356926 -0.032625891## 235 0.041165954 1.338976e-01 -0.552462971 -1.254784663 -1.993785797## 237 1.836317421 2.124058e-02 -1.316716381 1.973376992 -1.742649993## 238 0.961811964 2.143884e-01 -0.635177559 2.431681727 -0.662221171## 240 1.070218894 -6.638544e-01 -0.815469289 2.166268061 -1.068576904## 241 1.768408313 -7.988054e-01 -1.568017545 1.694558644 -2.051897671## 242 -1.624745643 -5.221140e+00 -1.909706327 1.219480034 4.418056728## 243 -0.035043858 -6.213305e-01 -1.632690351 2.046425661 -1.373253171## 244 1.193519440 -4.126863e-01 -0.856018567 1.660087465 -1.647477697## 245 0.029532268 -2.502195e-01 1.001427997 1.965821739 0.021001563## 246 -0.738436690 -1.196834e+00 1.193939075 2.033024108 0.190006611## 247 -0.089900659 7.734689e-02 0.676020650 1.811198725 0.393321672## 248 -0.426664529 -2.396249e-01 0.527490634 1.667572898 1.852093891## 249 0.050765298 -1.105483e+00 -0.039201736 1.511310953 0.303943069## 250 0.146804598 2.682502e-01 -0.935358229 1.621216419 -0.781232511## 252 -0.903661148 -7.480867e-01 -0.457464240 1.552637319 0.153790377## 253 0.149278627 -4.660009e-01 -1.620188397 1.085096676 -0.777367046## 254 -0.250263710 -1.186830e-01 -1.447342208 0.827199547 -0.330280941## 255 -0.989263739 -5.506926e-01 0.358489975 1.121894452 -0.288646161## 256 -0.929300461 -9.598681e-01 0.171382012 0.816583575 0.342117777## 257 -1.849914785 -7.384507e-01 0.462693030 0.808710752 0.791382525## 258 -0.305640415 -6.348247e-01 0.717120045 0.399982347 -0.471234240## 259 -0.814185051 2.392578e-01 -0.743561161 0.776632141 0.703180424## 262 -0.664268586 -4.134790e-01 0.918250373 0.196241660 -0.460382373## 263 -1.009199692 -1.310091e-01 0.137810428 0.394432804 -0.278509574## 264 -1.719578084 -9.518523e-05 0.146651225 0.538868884 -0.856541279## 266 -1.181174376 -3.351984e-01 0.903128361 0.304939424 -0.434794794## 267 -3.746683288 -9.872953e-01 0.564161560 3.059945329 -1.135764295## 268 -1.055117206 -3.506738e-01 1.472839703 0.160813045 0.122637791## 269 -1.751676699 -2.460210e-02 -0.699606573 0.390342105 0.223404682## 270 -2.969280408 -2.396189e-01 -0.141247808 0.595318332 -0.876021365## 271 -1.265595157 -5.474094e-02 -0.186727486 0.344348426 -0.591229695## 272 -1.169388587 -9.193807e-01 0.363566793 -0.014445947 0.310492222## 273 -1.864228083 2.282846e-01 0.142490685 0.598912030 -0.615766069## 274 -1.296719215 9.358620e-01 -0.087983852 0.234135643 -0.096019749## 275 -1.949614079 1.481898e+00 -0.236986954 0.455653518 0.064193184## 276 -1.935556120 1.335589e+00 -0.626664383 0.383180653 -0.253025287## 277 -1.739392595 -9.054334e-02 -0.037176775 0.366394729 -0.522231516## 278 -2.588469447 7.670844e-01 -0.774082317 0.668810888 -1.043419496## 279 -1.866835054 -9.593011e-01 -3.881629701 0.039501442 -0.177438970## 280 -0.431317463 5.961279e-01 -0.853422015 0.208361040 -0.512940518## 281 -2.762732401 -9.127031e-01 1.723470351 0.432824938 0.310070984## 282 -2.064018066 1.448035e+00 -1.796007295 0.351382775 -0.703330209## 283 -2.612498257 1.191128e+00 -1.672857266 0.760587179 -1.505304469## 285 -1.867163784 3.995817e-01 0.427844526 0.081572623 0.417023786## 286 -3.945507625 -6.895154e-01 0.137368153 0.468044448 0.123102781## 287 -3.142142913 3.215645e-01 0.002718618 0.454305062 -0.511639157## 288 -3.373923712 -8.218203e-02 -0.772323498 0.426982222 -0.106842827## 289 -3.441950172 2.519565e-01 0.626615882 0.683708998 -0.253322560## 290 -1.336716136 -4.262046e-01 0.469795570 0.022070134 -1.163683415## 292 -1.305447954 5.873989e-01 -0.843544180 0.039246176 -1.359563642## 293 -0.989813893 3.847176e-03 -0.717885547 -0.076810710 -1.870002053## 294 -1.411000643 -1.019845e+00 0.688024610 -0.198551977 -0.926975002## Comp.6## 1 -0.4956718034## 2 -0.4930099214## 4 -0.4717148659## 5 -0.4450960464## 6 -0.3745561749## 7 -0.3652395881## 8 -0.3519301783## 9 -0.3492682964## 10 -0.3452754735## 11 -0.3120019491## 12 -0.2986925394## 13 -0.1484011345## 14 -0.8422221873## 16 0.0079826706## 17 -0.8039338806## 18 0.0415514519## 19 -0.3596672774## 20 -0.3239172471## 21 0.3659770403## 22 -0.6222313666## 23 -0.3497513638## 26 -1.0134597152## 27 0.1417873412## 28 0.3897629624## 30 0.0382133328## 31 -0.8446559664## 32 0.1099919498## 33 0.5134215909## 34 0.0014363643## 35 0.3321762436## 36 0.0669250750## 37 -0.2769641962## 38 0.7569344917## 39 0.8771380289## 40 0.4457545230## 41 -0.3647031531## 42 -0.2618613697## 43 0.2057497118## 44 -0.1050252336## 45 -0.2376567972## 46 0.0239976211## 47 0.3166293992## 49 -0.1875912868## 50 -0.0616092269## 51 -0.1884065008## 52 0.3376937325## 53 0.2723524706## 54 0.2668740754## 56 0.5731378550## 57 -0.4451052254## 58 0.6230292211## 60 -0.4956718034## 61 -0.2661911698## 63 0.0182622518## 64 -0.6451283455## 65 -0.3745561749## 66 -0.0333052516## 67 -0.3519301783## 68 -0.3492682964## 69 -0.1731330294## 70 -0.5775229589## 71 -0.7490336556## 72 -1.4726343508## 73 -0.2454549005## 75 -0.9237185682## 76 0.5111292614## 77 -0.0325043448## 78 -0.1695056545## 79 0.0340427038## 80 0.1080985006## 81 0.3510467922## 82 0.7205325365## 85 -0.1600261315## 86 0.3240829108## 87 0.1817155704## 89 -0.7117392153## 90 -0.2884801891## 91 -0.8313465567## 92 -0.4598565680## 93 0.2669573740## 94 0.2669573740## 95 0.2669573740## 96 0.2669573740## 97 -0.0910025769## 98 0.3321762436## 99 -0.3231552079## 100 0.1898824212## 101 -0.2703094913## 102 0.4430006014## 103 -0.3513937434## 104 -3.0921419860## 105 0.0914509717## 106 -0.0009514101## 108 1.0400416848## 109 0.2506446997## 110 -0.2986091320## 111 -0.7422939101## 112 0.0267178042## 113 -0.6070793506## 115 -0.2559455616## 116 -1.3512276985## 117 0.8270298352## 119 -0.4956718034## 120 -0.4930099214## 122 0.1030715123## 123 -0.4450960464## 124 -0.9713234616## 125 0.2468977439## 126 -0.9449545515## 127 -0.3492682964## 128 -0.3452754735## 129 -0.3120019491## 130 -0.2986925394## 131 0.0532059117## 132 -0.2454549005## 134 -0.0885087907## 135 -0.4570113444## 136 -0.0325043448## 137 0.3320735304## 138 -0.3064296385## 139 0.3403896477## 140 0.1005897524## 141 0.1005897524## 144 0.2545020076## 145 0.5332841446## 146 -0.2166572665## 148 -0.4578892277## 149 0.4212037515## 150 0.4871214208## 151 0.7630317502## 152 -0.5531698357## 153 0.1392135623## 154 0.6508334813## 155 0.4948696894## 156 1.0893204229## 157 0.4050370083## 158 0.3732243651## 159 0.4535532516## 160 1.1086936683## 161 -1.1015918419## 162 -1.2783679559## 163 0.3600608686## 164 -0.6296049701## 165 -0.0384476969## 167 0.4724957473## 168 1.0613532278## 169 -0.4837584073## 170 0.5669761768## 171 0.4852779840## 172 0.8722021875## 174 0.7887227194## 175 0.9971122317## 176 0.4831665932## 178 -0.3395926907## 179 -0.2661911698## 181 -0.4717148659## 182 -0.7213293237## 183 -0.8248972911## 184 -0.3652395881## 185 -0.6924025207## 186 -0.7510366509## 187 -0.2800566039## 188 -0.9503171812## 189 -0.6906392617## 190 -0.4787607239## 191 -0.8422221873## 193 -0.0885087907## 194 -0.6429729637## 195 -0.0325043448## 196 -0.0191949351## 197 -0.3239172471## 198 0.0371317949## 199 0.0486214731## 200 0.5905668701## 203 -0.1326299370## 204 0.1937556205## 205 -0.3015364835## 207 -0.3057554401## 208 0.8571739143## 209 0.2603026692## 210 0.5134215909## 211 -0.2709303216## 212 0.2669573740## 213 0.0929856216## 214 -0.8246918519## 215 -0.3967000647## 216 0.1166466547## 217 -0.2618613697## 218 0.2578372741## 219 0.0080910692## 220 -0.4179609985## 221 0.2869214886## 222 -0.4225902207## 223 -0.2142101062## 224 0.2323685313## 226 0.3268497178## 227 0.4142149243## 228 -0.8470920936## 229 0.5256109813## 230 0.1446886107## 231 0.3933967665## 233 0.7519499224## 234 0.4200155859## 235 -0.2831971113## 237 1.1186172295## 238 1.2715226422## 240 1.2085122912## 241 1.0904884916## 242 -0.0823982134## 243 0.2101996910## 244 1.0542554482## 245 0.4652481787## 246 -0.0981718442## 247 0.3314323476## 248 0.3494260891## 249 0.7031981123## 250 0.5341460964## 252 -0.2603214844## 253 1.1807481100## 254 0.6121066020## 255 0.3651995614## 256 0.7384158108## 257 -0.7411059676## 258 0.8417923948## 259 1.3094450403## 262 0.5007650591## 263 0.6580456607## 264 0.0143693809## 266 0.6873273045## 267 3.9432575488## 268 0.8561418482## 269 0.4813773934## 270 -1.3925931184## 271 0.8035139131## 272 0.7239508266## 273 0.3288790563## 274 0.2165995597## 275 -0.4236152608## 276 -0.5560205665## 277 0.1850469576## 278 -0.9458576434## 279 0.1887032451## 280 1.8620126244## 281 -0.4653556091## 282 -0.6776296168## 283 -0.5774567268## 285 -0.0337422208## 286 -1.8894925868## 287 -1.2427198693## 288 -1.1793564227## 289 -0.9569509715## 290 1.1149712997## 292 1.1147264820## 293 1.3438663740## 294 1.0507774250

PCA 6biplot(fit)

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Cluster analysis

# Ward Hierarchical Clusteringd <- dist(as.matrix(mydata), method="euclidean") # distance matrixfit <- hclust(d, method="complete", members=NULL)

Cluster analysis 2plot(fit) # display dendogram

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hclust (*, "complete")d

Hei

ght

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Penutup

Workshop selanjutnya

I tematik: basic stats, multivariate stats, plotting, exploratorydata analysis

I sharing session dari pengguna: kasus, data, kode

Slide dan kode

I Slide:I format pdf tersedia di SlideShareI format ioslide tersedia di RpubsI Kode: tersedia di Github

Media sosial

I Facebook Group Indonesia R UserI Me on Twitter: @dasaptaerwinI Me on G+: +Dasapta Erwin IrawanI Me on ResearchGate:

www.researchgate.net/profile/dasapta_irawanI I used Ubuntu 14.04 and R Markdown

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