EDA dan DATA PREPROCESSING
Zakiah Intan Maula
1/14/2022
Exploratory Data Analysis
Mengakses library pada R
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, unionlibrary(plotly)## Loading required package: ggplot2##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layoutMembaca dan mengimpor data titanic ke R
dataset_a <- read.csv(file.choose(), header = T)
dataset_a## PassengerId Survived Pclass
## 1 1 0 3
## 2 2 1 1
## 3 3 1 3
## 4 4 1 1
## 5 5 0 3
## 6 6 0 3
## 7 7 0 1
## 8 8 0 3
## 9 9 1 3
## 10 10 1 2
## 11 11 1 3
## 12 12 1 1
## 13 13 0 3
## 14 14 0 3
## 15 15 0 3
## 16 16 1 2
## 17 17 0 3
## 18 18 1 2
## 19 19 0 3
## 20 20 1 3
## 21 21 0 2
## 22 22 1 2
## 23 23 1 3
## 24 24 1 1
## 25 25 0 3
## 26 26 1 3
## 27 27 0 3
## 28 28 0 1
## 29 29 1 3
## 30 30 0 3
## 31 31 0 1
## 32 32 1 1
## 33 33 1 3
## 34 34 0 2
## 35 35 0 1
## 36 36 0 1
## 37 37 1 3
## 38 38 0 3
## 39 39 0 3
## 40 40 1 3
## 41 41 0 3
## 42 42 0 2
## 43 43 0 3
## 44 44 1 2
## 45 45 1 3
## 46 46 0 3
## 47 47 0 3
## 48 48 1 3
## 49 49 0 3
## 50 50 0 3
## 51 51 0 3
## 52 52 0 3
## 53 53 1 1
## 54 54 1 2
## 55 55 0 1
## 56 56 1 1
## 57 57 1 2
## 58 58 0 3
## 59 59 1 2
## 60 60 0 3
## 61 61 0 3
## 62 62 1 1
## 63 63 0 1
## 64 64 0 3
## 65 65 0 1
## 66 66 1 3
## 67 67 1 2
## 68 68 0 3
## 69 69 1 3
## 70 70 0 3
## 71 71 0 2
## 72 72 0 3
## 73 73 0 2
## 74 74 0 3
## 75 75 1 3
## 76 76 0 3
## 77 77 0 3
## 78 78 0 3
## 79 79 1 2
## 80 80 1 3
## 81 81 0 3
## 82 82 1 3
## 83 83 1 3
## 84 84 0 1
## 85 85 1 2
## 86 86 1 3
## 87 87 0 3
## 88 88 0 3
## 89 89 1 1
## 90 90 0 3
## 91 91 0 3
## 92 92 0 3
## 93 93 0 1
## 94 94 0 3
## 95 95 0 3
## 96 96 0 3
## 97 97 0 1
## 98 98 1 1
## 99 99 1 2
## 100 100 0 2
## 101 101 0 3
## 102 102 0 3
## 103 103 0 1
## 104 104 0 3
## 105 105 0 3
## 106 106 0 3
## 107 107 1 3
## 108 108 1 3
## 109 109 0 3
## 110 110 1 3
## 111 111 0 1
## 112 112 0 3
## 113 113 0 3
## 114 114 0 3
## 115 115 0 3
## 116 116 0 3
## 117 117 0 3
## 118 118 0 2
## 119 119 0 1
## 120 120 0 3
## 121 121 0 2
## 122 122 0 3
## 123 123 0 2
## 124 124 1 2
## 125 125 0 1
## 126 126 1 3
## 127 127 0 3
## 128 128 1 3
## 129 129 1 3
## 130 130 0 3
## 131 131 0 3
## 132 132 0 3
## 133 133 0 3
## 134 134 1 2
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## 136 136 0 2
## 137 137 1 1
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## 139 139 0 3
## 140 140 0 1
## 141 141 0 3
## 142 142 1 3
## 143 143 1 3
## 144 144 0 3
## 145 145 0 2
## 146 146 0 2
## 147 147 1 3
## 148 148 0 3
## 149 149 0 2
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## 151 151 0 2
## 152 152 1 1
## 153 153 0 3
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## 155 155 0 3
## 156 156 0 1
## 157 157 1 3
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## 162 162 1 2
## 163 163 0 3
## 164 164 0 3
## 165 165 0 3
## 166 166 1 3
## 167 167 1 1
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## 169 169 0 1
## 170 170 0 3
## 171 171 0 1
## 172 172 0 3
## 173 173 1 3
## 174 174 0 3
## 175 175 0 1
## 176 176 0 3
## 177 177 0 3
## 178 178 0 1
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## 180 180 0 3
## 181 181 0 3
## 182 182 0 2
## 183 183 0 3
## 184 184 1 2
## 185 185 1 3
## 186 186 0 1
## 187 187 1 3
## 188 188 1 1
## 189 189 0 3
## 190 190 0 3
## 191 191 1 2
## 192 192 0 2
## 193 193 1 3
## 194 194 1 2
## 195 195 1 1
## 196 196 1 1
## 197 197 0 3
## 198 198 0 3
## 199 199 1 3
## 200 200 0 2
## 201 201 0 3
## 202 202 0 3
## 203 203 0 3
## 204 204 0 3
## 205 205 1 3
## 206 206 0 3
## 207 207 0 3
## 208 208 1 3
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## 210 210 1 1
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## Name
## 1 Braund, Mr. Owen Harris
## 2 Cumings, Mrs. John Bradley (Florence Briggs Thayer)
## 3 Heikkinen, Miss. Laina
## 4 Futrelle, Mrs. Jacques Heath (Lily May Peel)
## 5 Allen, Mr. William Henry
## 6 Moran, Mr. James
## 7 McCarthy, Mr. Timothy J
## 8 Palsson, Master. Gosta Leonard
## 9 Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)
## 10 Nasser, Mrs. Nicholas (Adele Achem)
## 11 Sandstrom, Miss. Marguerite Rut
## 12 Bonnell, Miss. Elizabeth
## 13 Saundercock, Mr. William Henry
## 14 Andersson, Mr. Anders Johan
## 15 Vestrom, Miss. Hulda Amanda Adolfina
## 16 Hewlett, Mrs. (Mary D Kingcome)
## 17 Rice, Master. Eugene
## 18 Williams, Mr. Charles Eugene
## 19 Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)
## 20 Masselmani, Mrs. Fatima
## 21 Fynney, Mr. Joseph J
## 22 Beesley, Mr. Lawrence
## 23 McGowan, Miss. Anna "Annie"
## 24 Sloper, Mr. William Thompson
## 25 Palsson, Miss. Torborg Danira
## 26 Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)
## 27 Emir, Mr. Farred Chehab
## 28 Fortune, Mr. Charles Alexander
## 29 O'Dwyer, Miss. Ellen "Nellie"
## 30 Todoroff, Mr. Lalio
## 31 Uruchurtu, Don. Manuel E
## 32 Spencer, Mrs. William Augustus (Marie Eugenie)
## 33 Glynn, Miss. Mary Agatha
## 34 Wheadon, Mr. Edward H
## 35 Meyer, Mr. Edgar Joseph
## 36 Holverson, Mr. Alexander Oskar
## 37 Mamee, Mr. Hanna
## 38 Cann, Mr. Ernest Charles
## 39 Vander Planke, Miss. Augusta Maria
## 40 Nicola-Yarred, Miss. Jamila
## 41 Ahlin, Mrs. Johan (Johanna Persdotter Larsson)
## 42 Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott)
## 43 Kraeff, Mr. Theodor
## 44 Laroche, Miss. Simonne Marie Anne Andree
## 45 Devaney, Miss. Margaret Delia
## 46 Rogers, Mr. William John
## 47 Lennon, Mr. Denis
## 48 O'Driscoll, Miss. Bridget
## 49 Samaan, Mr. Youssef
## 50 Arnold-Franchi, Mrs. Josef (Josefine Franchi)
## 51 Panula, Master. Juha Niilo
## 52 Nosworthy, Mr. Richard Cater
## 53 Harper, Mrs. Henry Sleeper (Myna Haxtun)
## 54 Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson)
## 55 Ostby, Mr. Engelhart Cornelius
## 56 Woolner, Mr. Hugh
## 57 Rugg, Miss. Emily
## 58 Novel, Mr. Mansouer
## 59 West, Miss. Constance Mirium
## 60 Goodwin, Master. William Frederick
## 61 Sirayanian, Mr. Orsen
## 62 Icard, Miss. Amelie
## 63 Harris, Mr. Henry Birkhardt
## 64 Skoog, Master. Harald
## 65 Stewart, Mr. Albert A
## 66 Moubarek, Master. Gerios
## 67 Nye, Mrs. (Elizabeth Ramell)
## 68 Crease, Mr. Ernest James
## 69 Andersson, Miss. Erna Alexandra
## 70 Kink, Mr. Vincenz
## 71 Jenkin, Mr. Stephen Curnow
## 72 Goodwin, Miss. Lillian Amy
## 73 Hood, Mr. Ambrose Jr
## 74 Chronopoulos, Mr. Apostolos
## 75 Bing, Mr. Lee
## 76 Moen, Mr. Sigurd Hansen
## 77 Staneff, Mr. Ivan
## 78 Moutal, Mr. Rahamin Haim
## 79 Caldwell, Master. Alden Gates
## 80 Dowdell, Miss. Elizabeth
## 81 Waelens, Mr. Achille
## 82 Sheerlinck, Mr. Jan Baptist
## 83 McDermott, Miss. Brigdet Delia
## 84 Carrau, Mr. Francisco M
## 85 Ilett, Miss. Bertha
## 86 Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson)
## 87 Ford, Mr. William Neal
## 88 Slocovski, Mr. Selman Francis
## 89 Fortune, Miss. Mabel Helen
## 90 Celotti, Mr. Francesco
## 91 Christmann, Mr. Emil
## 92 Andreasson, Mr. Paul Edvin
## 93 Chaffee, Mr. Herbert Fuller
## 94 Dean, Mr. Bertram Frank
## 95 Coxon, Mr. Daniel
## 96 Shorney, Mr. Charles Joseph
## 97 Goldschmidt, Mr. George B
## 98 Greenfield, Mr. William Bertram
## 99 Doling, Mrs. John T (Ada Julia Bone)
## 100 Kantor, Mr. Sinai
## 101 Petranec, Miss. Matilda
## 102 Petroff, Mr. Pastcho ("Pentcho")
## 103 White, Mr. Richard Frasar
## 104 Johansson, Mr. Gustaf Joel
## 105 Gustafsson, Mr. Anders Vilhelm
## 106 Mionoff, Mr. Stoytcho
## 107 Salkjelsvik, Miss. Anna Kristine
## 108 Moss, Mr. Albert Johan
## 109 Rekic, Mr. Tido
## 110 Moran, Miss. Bertha
## 111 Porter, Mr. Walter Chamberlain
## 112 Zabour, Miss. Hileni
## 113 Barton, Mr. David John
## 114 Jussila, Miss. Katriina
## 115 Attalah, Miss. Malake
## 116 Pekoniemi, Mr. Edvard
## 117 Connors, Mr. Patrick
## 118 Turpin, Mr. William John Robert
## 119 Baxter, Mr. Quigg Edmond
## 120 Andersson, Miss. Ellis Anna Maria
## 121 Hickman, Mr. Stanley George
## 122 Moore, Mr. Leonard Charles
## 123 Nasser, Mr. Nicholas
## 124 Webber, Miss. Susan
## 125 White, Mr. Percival Wayland
## 126 Nicola-Yarred, Master. Elias
## 127 McMahon, Mr. Martin
## 128 Madsen, Mr. Fridtjof Arne
## 129 Peter, Miss. Anna
## 130 Ekstrom, Mr. Johan
## 131 Drazenoic, Mr. Jozef
## 132 Coelho, Mr. Domingos Fernandeo
## 133 Robins, Mrs. Alexander A (Grace Charity Laury)
## 134 Weisz, Mrs. Leopold (Mathilde Francoise Pede)
## 135 Sobey, Mr. Samuel James Hayden
## 136 Richard, Mr. Emile
## 137 Newsom, Miss. Helen Monypeny
## 138 Futrelle, Mr. Jacques Heath
## 139 Osen, Mr. Olaf Elon
## 140 Giglio, Mr. Victor
## 141 Boulos, Mrs. Joseph (Sultana)
## 142 Nysten, Miss. Anna Sofia
## 143 Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck)
## 144 Burke, Mr. Jeremiah
## 145 Andrew, Mr. Edgardo Samuel
## 146 Nicholls, Mr. Joseph Charles
## 147 Andersson, Mr. August Edvard ("Wennerstrom")
## 148 Ford, Miss. Robina Maggie "Ruby"
## 149 Navratil, Mr. Michel ("Louis M Hoffman")
## 150 Byles, Rev. Thomas Roussel Davids
## 151 Bateman, Rev. Robert James
## 152 Pears, Mrs. Thomas (Edith Wearne)
## 153 Meo, Mr. Alfonzo
## 154 van Billiard, Mr. Austin Blyler
## 155 Olsen, Mr. Ole Martin
## 156 Williams, Mr. Charles Duane
## 157 Gilnagh, Miss. Katherine "Katie"
## 158 Corn, Mr. Harry
## 159 Smiljanic, Mr. Mile
## 160 Sage, Master. Thomas Henry
## 161 Cribb, Mr. John Hatfield
## 162 Watt, Mrs. James (Elizabeth "Bessie" Inglis Milne)
## 163 Bengtsson, Mr. John Viktor
## 164 Calic, Mr. Jovo
## 165 Panula, Master. Eino Viljami
## 166 Goldsmith, Master. Frank John William "Frankie"
## 167 Chibnall, Mrs. (Edith Martha Bowerman)
## 168 Skoog, Mrs. William (Anna Bernhardina Karlsson)
## 169 Baumann, Mr. John D
## 170 Ling, Mr. Lee
## 171 Van der hoef, Mr. Wyckoff
## 172 Rice, Master. Arthur
## 173 Johnson, Miss. Eleanor Ileen
## 174 Sivola, Mr. Antti Wilhelm
## 175 Smith, Mr. James Clinch
## 176 Klasen, Mr. Klas Albin
## 177 Lefebre, Master. Henry Forbes
## 178 Isham, Miss. Ann Elizabeth
## 179 Hale, Mr. Reginald
## 180 Leonard, Mr. Lionel
## 181 Sage, Miss. Constance Gladys
## 182 Pernot, Mr. Rene
## 183 Asplund, Master. Clarence Gustaf Hugo
## 184 Becker, Master. Richard F
## 185 Kink-Heilmann, Miss. Luise Gretchen
## 186 Rood, Mr. Hugh Roscoe
## 187 O'Brien, Mrs. Thomas (Johanna "Hannah" Godfrey)
## 188 Romaine, Mr. Charles Hallace ("Mr C Rolmane")
## 189 Bourke, Mr. John
## 190 Turcin, Mr. Stjepan
## 191 Pinsky, Mrs. (Rosa)
## 192 Carbines, Mr. William
## 193 Andersen-Jensen, Miss. Carla Christine Nielsine
## 194 Navratil, Master. Michel M
## 195 Brown, Mrs. James Joseph (Margaret Tobin)
## 196 Lurette, Miss. Elise
## 197 Mernagh, Mr. Robert
## 198 Olsen, Mr. Karl Siegwart Andreas
## 199 Madigan, Miss. Margaret "Maggie"
## 200 Yrois, Miss. Henriette ("Mrs Harbeck")
## 201 Vande Walle, Mr. Nestor Cyriel
## 202 Sage, Mr. Frederick
## 203 Johanson, Mr. Jakob Alfred
## 204 Youseff, Mr. Gerious
## 205 Cohen, Mr. Gurshon "Gus"
## 206 Strom, Miss. Telma Matilda
## 207 Backstrom, Mr. Karl Alfred
## 208 Albimona, Mr. Nassef Cassem
## 209 Carr, Miss. Helen "Ellen"
## 210 Blank, Mr. Henry
## 211 Ali, Mr. Ahmed
## 212 Cameron, Miss. Clear Annie
## 213 Perkin, Mr. John Henry
## 214 Givard, Mr. Hans Kristensen
## 215 Kiernan, Mr. Philip
## 216 Newell, Miss. Madeleine
## 217 Honkanen, Miss. Eliina
## 218 Jacobsohn, Mr. Sidney Samuel
## 219 Bazzani, Miss. Albina
## 220 Harris, Mr. Walter
## 221 Sunderland, Mr. Victor Francis
## 222 Bracken, Mr. James H
## 223 Green, Mr. George Henry
## 224 Nenkoff, Mr. Christo
## 225 Hoyt, Mr. Frederick Maxfield
## 226 Berglund, Mr. Karl Ivar Sven
## 227 Mellors, Mr. William John
## 228 Lovell, Mr. John Hall ("Henry")
## 229 Fahlstrom, Mr. Arne Jonas
## 230 Lefebre, Miss. Mathilde
## 231 Harris, Mrs. Henry Birkhardt (Irene Wallach)
## 232 Larsson, Mr. Bengt Edvin
## 233 Sjostedt, Mr. Ernst Adolf
## 234 Asplund, Miss. Lillian Gertrud
## 235 Leyson, Mr. Robert William Norman
## 236 Harknett, Miss. Alice Phoebe
## 237 Hold, Mr. Stephen
## 238 Collyer, Miss. Marjorie "Lottie"
## 239 Pengelly, Mr. Frederick William
## 240 Hunt, Mr. George Henry
## 241 Zabour, Miss. Thamine
## 242 Murphy, Miss. Katherine "Kate"
## 243 Coleridge, Mr. Reginald Charles
## 244 Maenpaa, Mr. Matti Alexanteri
## 245 Attalah, Mr. Sleiman
## 246 Minahan, Dr. William Edward
## 247 Lindahl, Miss. Agda Thorilda Viktoria
## 248 Hamalainen, Mrs. William (Anna)
## 249 Beckwith, Mr. Richard Leonard
## 250 Carter, Rev. Ernest Courtenay
## 251 Reed, Mr. James George
## 252 Strom, Mrs. Wilhelm (Elna Matilda Persson)
## 253 Stead, Mr. William Thomas
## 254 Lobb, Mr. William Arthur
## 255 Rosblom, Mrs. Viktor (Helena Wilhelmina)
## 256 Touma, Mrs. Darwis (Hanne Youssef Razi)
## 257 Thorne, Mrs. Gertrude Maybelle
## 258 Cherry, Miss. Gladys
## 259 Ward, Miss. Anna
## 260 Parrish, Mrs. (Lutie Davis)
## 261 Smith, Mr. Thomas
## 262 Asplund, Master. Edvin Rojj Felix
## 263 Taussig, Mr. Emil
## 264 Harrison, Mr. William
## 265 Henry, Miss. Delia
## 266 Reeves, Mr. David
## 267 Panula, Mr. Ernesti Arvid
## 268 Persson, Mr. Ernst Ulrik
## 269 Graham, Mrs. William Thompson (Edith Junkins)
## 270 Bissette, Miss. Amelia
## 271 Cairns, Mr. Alexander
## 272 Tornquist, Mr. William Henry
## 273 Mellinger, Mrs. (Elizabeth Anne Maidment)
## 274 Natsch, Mr. Charles H
## 275 Healy, Miss. Hanora "Nora"
## 276 Andrews, Miss. Kornelia Theodosia
## 277 Lindblom, Miss. Augusta Charlotta
## 278 Parkes, Mr. Francis "Frank"
## 279 Rice, Master. Eric
## 280 Abbott, Mrs. Stanton (Rosa Hunt)
## 281 Duane, Mr. Frank
## 282 Olsson, Mr. Nils Johan Goransson
## 283 de Pelsmaeker, Mr. Alfons
## 284 Dorking, Mr. Edward Arthur
## 285 Smith, Mr. Richard William
## 286 Stankovic, Mr. Ivan
## 287 de Mulder, Mr. Theodore
## 288 Naidenoff, Mr. Penko
## 289 Hosono, Mr. Masabumi
## 290 Connolly, Miss. Kate
## 291 Barber, Miss. Ellen "Nellie"
## 292 Bishop, Mrs. Dickinson H (Helen Walton)
## 293 Levy, Mr. Rene Jacques
## 294 Haas, Miss. Aloisia
## 295 Mineff, Mr. Ivan
## 296 Lewy, Mr. Ervin G
## 297 Hanna, Mr. Mansour
## 298 Allison, Miss. Helen Loraine
## 299 Saalfeld, Mr. Adolphe
## 300 Baxter, Mrs. James (Helene DeLaudeniere Chaput)
## 301 Kelly, Miss. Anna Katherine "Annie Kate"
## 302 McCoy, Mr. Bernard
## 303 Johnson, Mr. William Cahoone Jr
## 304 Keane, Miss. Nora A
## 305 Williams, Mr. Howard Hugh "Harry"
## 306 Allison, Master. Hudson Trevor
## 307 Fleming, Miss. Margaret
## 308 Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo)
## 309 Abelson, Mr. Samuel
## 310 Francatelli, Miss. Laura Mabel
## 311 Hays, Miss. Margaret Bechstein
## 312 Ryerson, Miss. Emily Borie
## 313 Lahtinen, Mrs. William (Anna Sylfven)
## 314 Hendekovic, Mr. Ignjac
## 315 Hart, Mr. Benjamin
## 316 Nilsson, Miss. Helmina Josefina
## 317 Kantor, Mrs. Sinai (Miriam Sternin)
## 318 Moraweck, Dr. Ernest
## 319 Wick, Miss. Mary Natalie
## 320 Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone)
## 321 Dennis, Mr. Samuel
## 322 Danoff, Mr. Yoto
## 323 Slayter, Miss. Hilda Mary
## 324 Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh)
## 325 Sage, Mr. George John Jr
## 326 Young, Miss. Marie Grice
## 327 Nysveen, Mr. Johan Hansen
## 328 Ball, Mrs. (Ada E Hall)
## 329 Goldsmith, Mrs. Frank John (Emily Alice Brown)
## 330 Hippach, Miss. Jean Gertrude
## 331 McCoy, Miss. Agnes
## 332 Partner, Mr. Austen
## 333 Graham, Mr. George Edward
## 334 Vander Planke, Mr. Leo Edmondus
## 335 Frauenthal, Mrs. Henry William (Clara Heinsheimer)
## 336 Denkoff, Mr. Mitto
## 337 Pears, Mr. Thomas Clinton
## 338 Burns, Miss. Elizabeth Margaret
## 339 Dahl, Mr. Karl Edwart
## 340 Blackwell, Mr. Stephen Weart
## 341 Navratil, Master. Edmond Roger
## 342 Fortune, Miss. Alice Elizabeth
## 343 Collander, Mr. Erik Gustaf
## 344 Sedgwick, Mr. Charles Frederick Waddington
## 345 Fox, Mr. Stanley Hubert
## 346 Brown, Miss. Amelia "Mildred"
## 347 Smith, Miss. Marion Elsie
## 348 Davison, Mrs. Thomas Henry (Mary E Finck)
## 349 Coutts, Master. William Loch "William"
## 350 Dimic, Mr. Jovan
## 351 Odahl, Mr. Nils Martin
## 352 Williams-Lambert, Mr. Fletcher Fellows
## 353 Elias, Mr. Tannous
## 354 Arnold-Franchi, Mr. Josef
## 355 Yousif, Mr. Wazli
## 356 Vanden Steen, Mr. Leo Peter
## 357 Bowerman, Miss. Elsie Edith
## 358 Funk, Miss. Annie Clemmer
## 359 McGovern, Miss. Mary
## 360 Mockler, Miss. Helen Mary "Ellie"
## 361 Skoog, Mr. Wilhelm
## 362 del Carlo, Mr. Sebastiano
## 363 Barbara, Mrs. (Catherine David)
## 364 Asim, Mr. Adola
## 365 O'Brien, Mr. Thomas
## 366 Adahl, Mr. Mauritz Nils Martin
## 367 Warren, Mrs. Frank Manley (Anna Sophia Atkinson)
## 368 Moussa, Mrs. (Mantoura Boulos)
## 369 Jermyn, Miss. Annie
## 370 Aubart, Mme. Leontine Pauline
## 371 Harder, Mr. George Achilles
## 372 Wiklund, Mr. Jakob Alfred
## 373 Beavan, Mr. William Thomas
## 374 Ringhini, Mr. Sante
## 375 Palsson, Miss. Stina Viola
## 376 Meyer, Mrs. Edgar Joseph (Leila Saks)
## 377 Landergren, Miss. Aurora Adelia
## 378 Widener, Mr. Harry Elkins
## 379 Betros, Mr. Tannous
## 380 Gustafsson, Mr. Karl Gideon
## 381 Bidois, Miss. Rosalie
## 382 Nakid, Miss. Maria ("Mary")
## 383 Tikkanen, Mr. Juho
## 384 Holverson, Mrs. Alexander Oskar (Mary Aline Towner)
## 385 Plotcharsky, Mr. Vasil
## 386 Davies, Mr. Charles Henry
## 387 Goodwin, Master. Sidney Leonard
## 388 Buss, Miss. Kate
## 389 Sadlier, Mr. Matthew
## 390 Lehmann, Miss. Bertha
## 391 Carter, Mr. William Ernest
## 392 Jansson, Mr. Carl Olof
## 393 Gustafsson, Mr. Johan Birger
## 394 Newell, Miss. Marjorie
## 395 Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengtsson)
## 396 Johansson, Mr. Erik
## 397 Olsson, Miss. Elina
## 398 McKane, Mr. Peter David
## 399 Pain, Dr. Alfred
## 400 Trout, Mrs. William H (Jessie L)
## 401 Niskanen, Mr. Juha
## 402 Adams, Mr. John
## 403 Jussila, Miss. Mari Aina
## 404 Hakkarainen, Mr. Pekka Pietari
## 405 Oreskovic, Miss. Marija
## 406 Gale, Mr. Shadrach
## 407 Widegren, Mr. Carl/Charles Peter
## 408 Richards, Master. William Rowe
## 409 Birkeland, Mr. Hans Martin Monsen
## 410 Lefebre, Miss. Ida
## 411 Sdycoff, Mr. Todor
## 412 Hart, Mr. Henry
## 413 Minahan, Miss. Daisy E
## 414 Cunningham, Mr. Alfred Fleming
## 415 Sundman, Mr. Johan Julian
## 416 Meek, Mrs. Thomas (Annie Louise Rowley)
## 417 Drew, Mrs. James Vivian (Lulu Thorne Christian)
## 418 Silven, Miss. Lyyli Karoliina
## 419 Matthews, Mr. William John
## 420 Van Impe, Miss. Catharina
## 421 Gheorgheff, Mr. Stanio
## 422 Charters, Mr. David
## 423 Zimmerman, Mr. Leo
## 424 Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren)
## 425 Rosblom, Mr. Viktor Richard
## 426 Wiseman, Mr. Phillippe
## 427 Clarke, Mrs. Charles V (Ada Maria Winfield)
## 428 Phillips, Miss. Kate Florence ("Mrs Kate Louise Phillips Marshall")
## 429 Flynn, Mr. James
## 430 Pickard, Mr. Berk (Berk Trembisky)
## 431 Bjornstrom-Steffansson, Mr. Mauritz Hakan
## 432 Thorneycroft, Mrs. Percival (Florence Kate White)
## 433 Louch, Mrs. Charles Alexander (Alice Adelaide Slow)
## 434 Kallio, Mr. Nikolai Erland
## 435 Silvey, Mr. William Baird
## 436 Carter, Miss. Lucile Polk
## 437 Ford, Miss. Doolina Margaret "Daisy"
## 438 Richards, Mrs. Sidney (Emily Hocking)
## 439 Fortune, Mr. Mark
## 440 Kvillner, Mr. Johan Henrik Johannesson
## 441 Hart, Mrs. Benjamin (Esther Ada Bloomfield)
## 442 Hampe, Mr. Leon
## 443 Petterson, Mr. Johan Emil
## 444 Reynaldo, Ms. Encarnacion
## 445 Johannesen-Bratthammer, Mr. Bernt
## 446 Dodge, Master. Washington
## 447 Mellinger, Miss. Madeleine Violet
## 448 Seward, Mr. Frederic Kimber
## 449 Baclini, Miss. Marie Catherine
## 450 Peuchen, Major. Arthur Godfrey
## 451 West, Mr. Edwy Arthur
## 452 Hagland, Mr. Ingvald Olai Olsen
## 453 Foreman, Mr. Benjamin Laventall
## 454 Goldenberg, Mr. Samuel L
## 455 Peduzzi, Mr. Joseph
## 456 Jalsevac, Mr. Ivan
## 457 Millet, Mr. Francis Davis
## 458 Kenyon, Mrs. Frederick R (Marion)
## 459 Toomey, Miss. Ellen
## 460 O'Connor, Mr. Maurice
## 461 Anderson, Mr. Harry
## 462 Morley, Mr. William
## 463 Gee, Mr. Arthur H
## 464 Milling, Mr. Jacob Christian
## 465 Maisner, Mr. Simon
## 466 Goncalves, Mr. Manuel Estanslas
## 467 Campbell, Mr. William
## 468 Smart, Mr. John Montgomery
## 469 Scanlan, Mr. James
## 470 Baclini, Miss. Helene Barbara
## 471 Keefe, Mr. Arthur
## 472 Cacic, Mr. Luka
## 473 West, Mrs. Edwy Arthur (Ada Mary Worth)
## 474 Jerwan, Mrs. Amin S (Marie Marthe Thuillard)
## 475 Strandberg, Miss. Ida Sofia
## 476 Clifford, Mr. George Quincy
## 477 Renouf, Mr. Peter Henry
## 478 Braund, Mr. Lewis Richard
## 479 Karlsson, Mr. Nils August
## 480 Hirvonen, Miss. Hildur E
## 481 Goodwin, Master. Harold Victor
## 482 Frost, Mr. Anthony Wood "Archie"
## 483 Rouse, Mr. Richard Henry
## 484 Turkula, Mrs. (Hedwig)
## 485 Bishop, Mr. Dickinson H
## 486 Lefebre, Miss. Jeannie
## 487 Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby)
## 488 Kent, Mr. Edward Austin
## 489 Somerton, Mr. Francis William
## 490 Coutts, Master. Eden Leslie "Neville"
## 491 Hagland, Mr. Konrad Mathias Reiersen
## 492 Windelov, Mr. Einar
## 493 Molson, Mr. Harry Markland
## 494 Artagaveytia, Mr. Ramon
## 495 Stanley, Mr. Edward Roland
## 496 Yousseff, Mr. Gerious
## 497 Eustis, Miss. Elizabeth Mussey
## 498 Shellard, Mr. Frederick William
## 499 Allison, Mrs. Hudson J C (Bessie Waldo Daniels)
## 500 Svensson, Mr. Olof
## 501 Calic, Mr. Petar
## 502 Canavan, Miss. Mary
## 503 O'Sullivan, Miss. Bridget Mary
## 504 Laitinen, Miss. Kristina Sofia
## 505 Maioni, Miss. Roberta
## 506 Penasco y Castellana, Mr. Victor de Satode
## 507 Quick, Mrs. Frederick Charles (Jane Richards)
## 508 Bradley, Mr. George ("George Arthur Brayton")
## 509 Olsen, Mr. Henry Margido
## 510 Lang, Mr. Fang
## 511 Daly, Mr. Eugene Patrick
## 512 Webber, Mr. James
## 513 McGough, Mr. James Robert
## 514 Rothschild, Mrs. Martin (Elizabeth L. Barrett)
## 515 Coleff, Mr. Satio
## 516 Walker, Mr. William Anderson
## 517 Lemore, Mrs. (Amelia Milley)
## 518 Ryan, Mr. Patrick
## 519 Angle, Mrs. William A (Florence "Mary" Agnes Hughes)
## 520 Pavlovic, Mr. Stefo
## 521 Perreault, Miss. Anne
## 522 Vovk, Mr. Janko
## 523 Lahoud, Mr. Sarkis
## 524 Hippach, Mrs. Louis Albert (Ida Sophia Fischer)
## 525 Kassem, Mr. Fared
## 526 Farrell, Mr. James
## 527 Ridsdale, Miss. Lucy
## 528 Farthing, Mr. John
## 529 Salonen, Mr. Johan Werner
## 530 Hocking, Mr. Richard George
## 531 Quick, Miss. Phyllis May
## 532 Toufik, Mr. Nakli
## 533 Elias, Mr. Joseph Jr
## 534 Peter, Mrs. Catherine (Catherine Rizk)
## 535 Cacic, Miss. Marija
## 536 Hart, Miss. Eva Miriam
## 537 Butt, Major. Archibald Willingham
## 538 LeRoy, Miss. Bertha
## 539 Risien, Mr. Samuel Beard
## 540 Frolicher, Miss. Hedwig Margaritha
## 541 Crosby, Miss. Harriet R
## 542 Andersson, Miss. Ingeborg Constanzia
## 543 Andersson, Miss. Sigrid Elisabeth
## 544 Beane, Mr. Edward
## 545 Douglas, Mr. Walter Donald
## 546 Nicholson, Mr. Arthur Ernest
## 547 Beane, Mrs. Edward (Ethel Clarke)
## 548 Padro y Manent, Mr. Julian
## 549 Goldsmith, Mr. Frank John
## 550 Davies, Master. John Morgan Jr
## 551 Thayer, Mr. John Borland Jr
## 552 Sharp, Mr. Percival James R
## 553 O'Brien, Mr. Timothy
## 554 Leeni, Mr. Fahim ("Philip Zenni")
## 555 Ohman, Miss. Velin
## 556 Wright, Mr. George
## 557 Duff Gordon, Lady. (Lucille Christiana Sutherland) ("Mrs Morgan")
## 558 Robbins, Mr. Victor
## 559 Taussig, Mrs. Emil (Tillie Mandelbaum)
## 560 de Messemaeker, Mrs. Guillaume Joseph (Emma)
## 561 Morrow, Mr. Thomas Rowan
## 562 Sivic, Mr. Husein
## 563 Norman, Mr. Robert Douglas
## 564 Simmons, Mr. John
## 565 Meanwell, Miss. (Marion Ogden)
## 566 Davies, Mr. Alfred J
## 567 Stoytcheff, Mr. Ilia
## 568 Palsson, Mrs. Nils (Alma Cornelia Berglund)
## 569 Doharr, Mr. Tannous
## 570 Jonsson, Mr. Carl
## 571 Harris, Mr. George
## 572 Appleton, Mrs. Edward Dale (Charlotte Lamson)
## 573 Flynn, Mr. John Irwin ("Irving")
## 574 Kelly, Miss. Mary
## 575 Rush, Mr. Alfred George John
## 576 Patchett, Mr. George
## 577 Garside, Miss. Ethel
## 578 Silvey, Mrs. William Baird (Alice Munger)
## 579 Caram, Mrs. Joseph (Maria Elias)
## 580 Jussila, Mr. Eiriik
## 581 Christy, Miss. Julie Rachel
## 582 Thayer, Mrs. John Borland (Marian Longstreth Morris)
## 583 Downton, Mr. William James
## 584 Ross, Mr. John Hugo
## 585 Paulner, Mr. Uscher
## 586 Taussig, Miss. Ruth
## 587 Jarvis, Mr. John Denzil
## 588 Frolicher-Stehli, Mr. Maxmillian
## 589 Gilinski, Mr. Eliezer
## 590 Murdlin, Mr. Joseph
## 591 Rintamaki, Mr. Matti
## 592 Stephenson, Mrs. Walter Bertram (Martha Eustis)
## 593 Elsbury, Mr. William James
## 594 Bourke, Miss. Mary
## 595 Chapman, Mr. John Henry
## 596 Van Impe, Mr. Jean Baptiste
## 597 Leitch, Miss. Jessie Wills
## 598 Johnson, Mr. Alfred
## 599 Boulos, Mr. Hanna
## 600 Duff Gordon, Sir. Cosmo Edmund ("Mr Morgan")
## 601 Jacobsohn, Mrs. Sidney Samuel (Amy Frances Christy)
## 602 Slabenoff, Mr. Petco
## 603 Harrington, Mr. Charles H
## 604 Torber, Mr. Ernst William
## 605 Homer, Mr. Harry ("Mr E Haven")
## 606 Lindell, Mr. Edvard Bengtsson
## 607 Karaic, Mr. Milan
## 608 Daniel, Mr. Robert Williams
## 609 Laroche, Mrs. Joseph (Juliette Marie Louise Lafargue)
## 610 Shutes, Miss. Elizabeth W
## 611 Andersson, Mrs. Anders Johan (Alfrida Konstantia Brogren)
## 612 Jardin, Mr. Jose Neto
## 613 Murphy, Miss. Margaret Jane
## 614 Horgan, Mr. John
## 615 Brocklebank, Mr. William Alfred
## 616 Herman, Miss. Alice
## 617 Danbom, Mr. Ernst Gilbert
## 618 Lobb, Mrs. William Arthur (Cordelia K Stanlick)
## 619 Becker, Miss. Marion Louise
## 620 Gavey, Mr. Lawrence
## 621 Yasbeck, Mr. Antoni
## 622 Kimball, Mr. Edwin Nelson Jr
## 623 Nakid, Mr. Sahid
## 624 Hansen, Mr. Henry Damsgaard
## 625 Bowen, Mr. David John "Dai"
## 626 Sutton, Mr. Frederick
## 627 Kirkland, Rev. Charles Leonard
## 628 Longley, Miss. Gretchen Fiske
## 629 Bostandyeff, Mr. Guentcho
## 630 O'Connell, Mr. Patrick D
## 631 Barkworth, Mr. Algernon Henry Wilson
## 632 Lundahl, Mr. Johan Svensson
## 633 Stahelin-Maeglin, Dr. Max
## 634 Parr, Mr. William Henry Marsh
## 635 Skoog, Miss. Mabel
## 636 Davis, Miss. Mary
## 637 Leinonen, Mr. Antti Gustaf
## 638 Collyer, Mr. Harvey
## 639 Panula, Mrs. Juha (Maria Emilia Ojala)
## 640 Thorneycroft, Mr. Percival
## 641 Jensen, Mr. Hans Peder
## 642 Sagesser, Mlle. Emma
## 643 Skoog, Miss. Margit Elizabeth
## 644 Foo, Mr. Choong
## 645 Baclini, Miss. Eugenie
## 646 Harper, Mr. Henry Sleeper
## 647 Cor, Mr. Liudevit
## 648 Simonius-Blumer, Col. Oberst Alfons
## 649 Willey, Mr. Edward
## 650 Stanley, Miss. Amy Zillah Elsie
## 651 Mitkoff, Mr. Mito
## 652 Doling, Miss. Elsie
## 653 Kalvik, Mr. Johannes Halvorsen
## 654 O'Leary, Miss. Hanora "Norah"
## 655 Hegarty, Miss. Hanora "Nora"
## 656 Hickman, Mr. Leonard Mark
## 657 Radeff, Mr. Alexander
## 658 Bourke, Mrs. John (Catherine)
## 659 Eitemiller, Mr. George Floyd
## 660 Newell, Mr. Arthur Webster
## 661 Frauenthal, Dr. Henry William
## 662 Badt, Mr. Mohamed
## 663 Colley, Mr. Edward Pomeroy
## 664 Coleff, Mr. Peju
## 665 Lindqvist, Mr. Eino William
## 666 Hickman, Mr. Lewis
## 667 Butler, Mr. Reginald Fenton
## 668 Rommetvedt, Mr. Knud Paust
## 669 Cook, Mr. Jacob
## 670 Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright)
## 671 Brown, Mrs. Thomas William Solomon (Elizabeth Catherine Ford)
## 672 Davidson, Mr. Thornton
## 673 Mitchell, Mr. Henry Michael
## 674 Wilhelms, Mr. Charles
## 675 Watson, Mr. Ennis Hastings
## 676 Edvardsson, Mr. Gustaf Hjalmar
## 677 Sawyer, Mr. Frederick Charles
## 678 Turja, Miss. Anna Sofia
## 679 Goodwin, Mrs. Frederick (Augusta Tyler)
## 680 Cardeza, Mr. Thomas Drake Martinez
## 681 Peters, Miss. Katie
## 682 Hassab, Mr. Hammad
## 683 Olsvigen, Mr. Thor Anderson
## 684 Goodwin, Mr. Charles Edward
## 685 Brown, Mr. Thomas William Solomon
## 686 Laroche, Mr. Joseph Philippe Lemercier
## 687 Panula, Mr. Jaako Arnold
## 688 Dakic, Mr. Branko
## 689 Fischer, Mr. Eberhard Thelander
## 690 Madill, Miss. Georgette Alexandra
## 691 Dick, Mr. Albert Adrian
## 692 Karun, Miss. Manca
## 693 Lam, Mr. Ali
## 694 Saad, Mr. Khalil
## 695 Weir, Col. John
## 696 Chapman, Mr. Charles Henry
## 697 Kelly, Mr. James
## 698 Mullens, Miss. Katherine "Katie"
## 699 Thayer, Mr. John Borland
## 700 Humblen, Mr. Adolf Mathias Nicolai Olsen
## 701 Astor, Mrs. John Jacob (Madeleine Talmadge Force)
## 702 Silverthorne, Mr. Spencer Victor
## 703 Barbara, Miss. Saiide
## 704 Gallagher, Mr. Martin
## 705 Hansen, Mr. Henrik Juul
## 706 Morley, Mr. Henry Samuel ("Mr Henry Marshall")
## 707 Kelly, Mrs. Florence "Fannie"
## 708 Calderhead, Mr. Edward Pennington
## 709 Cleaver, Miss. Alice
## 710 Moubarek, Master. Halim Gonios ("William George")
## 711 Mayne, Mlle. Berthe Antonine ("Mrs de Villiers")
## 712 Klaber, Mr. Herman
## 713 Taylor, Mr. Elmer Zebley
## 714 Larsson, Mr. August Viktor
## 715 Greenberg, Mr. Samuel
## 716 Soholt, Mr. Peter Andreas Lauritz Andersen
## 717 Endres, Miss. Caroline Louise
## 718 Troutt, Miss. Edwina Celia "Winnie"
## 719 McEvoy, Mr. Michael
## 720 Johnson, Mr. Malkolm Joackim
## 721 Harper, Miss. Annie Jessie "Nina"
## 722 Jensen, Mr. Svend Lauritz
## 723 Gillespie, Mr. William Henry
## 724 Hodges, Mr. Henry Price
## 725 Chambers, Mr. Norman Campbell
## 726 Oreskovic, Mr. Luka
## 727 Renouf, Mrs. Peter Henry (Lillian Jefferys)
## 728 Mannion, Miss. Margareth
## 729 Bryhl, Mr. Kurt Arnold Gottfrid
## 730 Ilmakangas, Miss. Pieta Sofia
## 731 Allen, Miss. Elisabeth Walton
## 732 Hassan, Mr. Houssein G N
## 733 Knight, Mr. Robert J
## 734 Berriman, Mr. William John
## 735 Troupiansky, Mr. Moses Aaron
## 736 Williams, Mr. Leslie
## 737 Ford, Mrs. Edward (Margaret Ann Watson)
## 738 Lesurer, Mr. Gustave J
## 739 Ivanoff, Mr. Kanio
## 740 Nankoff, Mr. Minko
## 741 Hawksford, Mr. Walter James
## 742 Cavendish, Mr. Tyrell William
## 743 Ryerson, Miss. Susan Parker "Suzette"
## 744 McNamee, Mr. Neal
## 745 Stranden, Mr. Juho
## 746 Crosby, Capt. Edward Gifford
## 747 Abbott, Mr. Rossmore Edward
## 748 Sinkkonen, Miss. Anna
## 749 Marvin, Mr. Daniel Warner
## 750 Connaghton, Mr. Michael
## 751 Wells, Miss. Joan
## 752 Moor, Master. Meier
## 753 Vande Velde, Mr. Johannes Joseph
## 754 Jonkoff, Mr. Lalio
## 755 Herman, Mrs. Samuel (Jane Laver)
## 756 Hamalainen, Master. Viljo
## 757 Carlsson, Mr. August Sigfrid
## 758 Bailey, Mr. Percy Andrew
## 759 Theobald, Mr. Thomas Leonard
## 760 Rothes, the Countess. of (Lucy Noel Martha Dyer-Edwards)
## 761 Garfirth, Mr. John
## 762 Nirva, Mr. Iisakki Antino Aijo
## 763 Barah, Mr. Hanna Assi
## 764 Carter, Mrs. William Ernest (Lucile Polk)
## 765 Eklund, Mr. Hans Linus
## 766 Hogeboom, Mrs. John C (Anna Andrews)
## 767 Brewe, Dr. Arthur Jackson
## 768 Mangan, Miss. Mary
## 769 Moran, Mr. Daniel J
## 770 Gronnestad, Mr. Daniel Danielsen
## 771 Lievens, Mr. Rene Aime
## 772 Jensen, Mr. Niels Peder
## 773 Mack, Mrs. (Mary)
## 774 Elias, Mr. Dibo
## 775 Hocking, Mrs. Elizabeth (Eliza Needs)
## 776 Myhrman, Mr. Pehr Fabian Oliver Malkolm
## 777 Tobin, Mr. Roger
## 778 Emanuel, Miss. Virginia Ethel
## 779 Kilgannon, Mr. Thomas J
## 780 Robert, Mrs. Edward Scott (Elisabeth Walton McMillan)
## 781 Ayoub, Miss. Banoura
## 782 Dick, Mrs. Albert Adrian (Vera Gillespie)
## 783 Long, Mr. Milton Clyde
## 784 Johnston, Mr. Andrew G
## 785 Ali, Mr. William
## 786 Harmer, Mr. Abraham (David Lishin)
## 787 Sjoblom, Miss. Anna Sofia
## 788 Rice, Master. George Hugh
## 789 Dean, Master. Bertram Vere
## 790 Guggenheim, Mr. Benjamin
## 791 Keane, Mr. Andrew "Andy"
## 792 Gaskell, Mr. Alfred
## 793 Sage, Miss. Stella Anna
## 794 Hoyt, Mr. William Fisher
## 795 Dantcheff, Mr. Ristiu
## 796 Otter, Mr. Richard
## 797 Leader, Dr. Alice (Farnham)
## 798 Osman, Mrs. Mara
## 799 Ibrahim Shawah, Mr. Yousseff
## 800 Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert)
## 801 Ponesell, Mr. Martin
## 802 Collyer, Mrs. Harvey (Charlotte Annie Tate)
## 803 Carter, Master. William Thornton II
## 804 Thomas, Master. Assad Alexander
## 805 Hedman, Mr. Oskar Arvid
## 806 Johansson, Mr. Karl Johan
## 807 Andrews, Mr. Thomas Jr
## 808 Pettersson, Miss. Ellen Natalia
## 809 Meyer, Mr. August
## 810 Chambers, Mrs. Norman Campbell (Bertha Griggs)
## 811 Alexander, Mr. William
## 812 Lester, Mr. James
## 813 Slemen, Mr. Richard James
## 814 Andersson, Miss. Ebba Iris Alfrida
## 815 Tomlin, Mr. Ernest Portage
## 816 Fry, Mr. Richard
## 817 Heininen, Miss. Wendla Maria
## 818 Mallet, Mr. Albert
## 819 Holm, Mr. John Fredrik Alexander
## 820 Skoog, Master. Karl Thorsten
## 821 Hays, Mrs. Charles Melville (Clara Jennings Gregg)
## 822 Lulic, Mr. Nikola
## 823 Reuchlin, Jonkheer. John George
## 824 Moor, Mrs. (Beila)
## 825 Panula, Master. Urho Abraham
## 826 Flynn, Mr. John
## 827 Lam, Mr. Len
## 828 Mallet, Master. Andre
## 829 McCormack, Mr. Thomas Joseph
## 830 Stone, Mrs. George Nelson (Martha Evelyn)
## 831 Yasbeck, Mrs. Antoni (Selini Alexander)
## 832 Richards, Master. George Sibley
## 833 Saad, Mr. Amin
## 834 Augustsson, Mr. Albert
## 835 Allum, Mr. Owen George
## 836 Compton, Miss. Sara Rebecca
## 837 Pasic, Mr. Jakob
## 838 Sirota, Mr. Maurice
## 839 Chip, Mr. Chang
## 840 Marechal, Mr. Pierre
## 841 Alhomaki, Mr. Ilmari Rudolf
## 842 Mudd, Mr. Thomas Charles
## 843 Serepeca, Miss. Augusta
## 844 Lemberopolous, Mr. Peter L
## 845 Culumovic, Mr. Jeso
## 846 Abbing, Mr. Anthony
## 847 Sage, Mr. Douglas Bullen
## 848 Markoff, Mr. Marin
## 849 Harper, Rev. John
## 850 Goldenberg, Mrs. Samuel L (Edwiga Grabowska)
## 851 Andersson, Master. Sigvard Harald Elias
## 852 Svensson, Mr. Johan
## 853 Boulos, Miss. Nourelain
## 854 Lines, Miss. Mary Conover
## 855 Carter, Mrs. Ernest Courtenay (Lilian Hughes)
## 856 Aks, Mrs. Sam (Leah Rosen)
## 857 Wick, Mrs. George Dennick (Mary Hitchcock)
## 858 Daly, Mr. Peter Denis
## 859 Baclini, Mrs. Solomon (Latifa Qurban)
## 860 Razi, Mr. Raihed
## 861 Hansen, Mr. Claus Peter
## 862 Giles, Mr. Frederick Edward
## 863 Swift, Mrs. Frederick Joel (Margaret Welles Barron)
## 864 Sage, Miss. Dorothy Edith "Dolly"
## 865 Gill, Mr. John William
## 866 Bystrom, Mrs. (Karolina)
## 867 Duran y More, Miss. Asuncion
## 868 Roebling, Mr. Washington Augustus II
## 869 van Melkebeke, Mr. Philemon
## 870 Johnson, Master. Harold Theodor
## 871 Balkic, Mr. Cerin
## 872 Beckwith, Mrs. Richard Leonard (Sallie Monypeny)
## 873 Carlsson, Mr. Frans Olof
## 874 Vander Cruyssen, Mr. Victor
## 875 Abelson, Mrs. Samuel (Hannah Wizosky)
## 876 Najib, Miss. Adele Kiamie "Jane"
## 877 Gustafsson, Mr. Alfred Ossian
## 878 Petroff, Mr. Nedelio
## 879 Laleff, Mr. Kristo
## 880 Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)
## 881 Shelley, Mrs. William (Imanita Parrish Hall)
## 882 Markun, Mr. Johann
## 883 Dahlberg, Miss. Gerda Ulrika
## 884 Banfield, Mr. Frederick James
## 885 Sutehall, Mr. Henry Jr
## 886 Rice, Mrs. William (Margaret Norton)
## 887 Montvila, Rev. Juozas
## 888 Graham, Miss. Margaret Edith
## 889 Johnston, Miss. Catherine Helen "Carrie"
## 890 Behr, Mr. Karl Howell
## 891 Dooley, Mr. Patrick
## Sex Age SibSp Parch Ticket Fare Cabin
## 1 male 22.00 1 0 A/5 21171 7.25
## 2 female 38.00 1 0 PC 17599 712.833 C85
## 3 female 26.00 0 0 STON/O2. 3101282 7.925
## 4 female 35.00 1 0 113803 53.1 C123
## 5 male 35.00 0 0 373450 08.05
## 6 male NA 0 0 330877 8.4583
## 7 male 54.00 0 0 17463 518.625 E46
## 8 male 2.00 3 1 349909 21.075
## 9 female 27.00 0 2 347742 11.1333
## 10 female 14.00 1 0 237736 300.708
## 11 female 4.00 1 1 PP 9549 16.7 G6
## 12 female 58.00 0 0 113783 26.55 C103
## 13 male 20.00 0 0 A/5. 2151 08.05
## 14 male 39.00 1 5 347082 31.275
## 15 female 14.00 0 0 350406 7.8542
## 16 female 55.00 0 0 248706 16.0
## 17 male 2.00 4 1 382652 29.125
## 18 male NA 0 0 244373 13.0
## 19 female 31.00 1 0 345763 18.0
## 20 female NA 0 0 2649 7.225
## 21 male 35.00 0 0 239865 26.0
## 22 male 34.00 0 0 248698 13.0 D56
## 23 female 15.00 0 0 330923 8.0292
## 24 male 28.00 0 0 113788 35.5 A6
## 25 female 8.00 3 1 349909 21.075
## 26 female 38.00 1 5 347077 313.875
## 27 male NA 0 0 2631 7.225
## 28 male 19.00 3 2 19950 263.0 C23 C25 C27
## 29 female NA 0 0 330959 7.8792
## 30 male NA 0 0 349216 7.8958
## 31 male 40.00 0 0 PC 17601 277.208
## 32 female NA 1 0 PC 17569 1.465.208 B78
## 33 female NA 0 0 335677 7.75
## 34 male 66.00 0 0 C.A. 24579 10.5
## 35 male 28.00 1 0 PC 17604 821.708
## 36 male 42.00 1 0 113789 52.0
## 37 male NA 0 0 2677 7.2292
## 38 male 21.00 0 0 A./5. 2152 08.05
## 39 female 18.00 2 0 345764 18.0
## 40 female 14.00 1 0 2651 11.2417
## 41 female 40.00 1 0 7546 9.475
## 42 female 27.00 1 0 11668 21.0
## 43 male NA 0 0 349253 7.8958
## 44 female 3.00 1 2 SC/Paris 2123 415.792
## 45 female 19.00 0 0 330958 7.8792
## 46 male NA 0 0 S.C./A.4. 23567 08.05
## 47 male NA 1 0 370371 15.5
## 48 female NA 0 0 14311 7.75
## 49 male NA 2 0 2662 216.792
## 50 female 18.00 1 0 349237 17.8
## 51 male 7.00 4 1 3101295 396.875
## 52 male 21.00 0 0 A/4. 39886 7.8
## 53 female 49.00 1 0 PC 17572 767.292 D33
## 54 female 29.00 1 0 2926 26.0
## 55 male 65.00 0 1 113509 619.792 B30
## 56 male NA 0 0 19947 35.5 C52
## 57 female 21.00 0 0 C.A. 31026 10.5
## 58 male 28.50 0 0 2697 7.2292
## 59 female 5.00 1 2 C.A. 34651 27.75
## 60 male 11.00 5 2 CA 2144 46.9
## 61 male 22.00 0 0 2669 7.2292
## 62 female 38.00 0 0 113572 80.0 B28
## 63 male 45.00 1 0 36973 83.475 C83
## 64 male 4.00 3 2 347088 27.9
## 65 male NA 0 0 PC 17605 277.208
## 66 male NA 1 1 2661 152.458
## 67 female 29.00 0 0 C.A. 29395 10.5 F33
## 68 male 19.00 0 0 S.P. 3464 8.1583
## 69 female 17.00 4 2 3101281 7.925
## 70 male 26.00 2 0 315151 8.6625
## 71 male 32.00 0 0 C.A. 33111 10.5
## 72 female 16.00 5 2 CA 2144 46.9
## 73 male 21.00 0 0 S.O.C. 14879 73.5
## 74 male 26.00 1 0 2680 144.542
## 75 male 32.00 0 0 1601 564.958
## 76 male 25.00 0 0 348123 7.65 F G73
## 77 male NA 0 0 349208 7.8958
## 78 male NA 0 0 374746 08.05
## 79 male 0.83 0 2 248738 29.0
## 80 female 30.00 0 0 364516 12.475
## 81 male 22.00 0 0 345767 9.0
## 82 male 29.00 0 0 345779 9.5
## 83 female NA 0 0 330932 7.7875
## 84 male 28.00 0 0 113059 47.1
## 85 female 17.00 0 0 SO/C 14885 10.5
## 86 female 33.00 3 0 3101278 15.85
## 87 male 16.00 1 3 W./C. 6608 34.375
## 88 male NA 0 0 SOTON/OQ 392086 08.05
## 89 female 23.00 3 2 19950 263.0 C23 C25 C27
## 90 male 24.00 0 0 343275 08.05
## 91 male 29.00 0 0 343276 08.05
## 92 male 20.00 0 0 347466 7.8542
## 93 male 46.00 1 0 W.E.P. 5734 61.175 E31
## 94 male 26.00 1 2 C.A. 2315 20.575
## 95 male 59.00 0 0 364500 7.25
## 96 male NA 0 0 374910 08.05
## 97 male 71.00 0 0 PC 17754 346.542 A5
## 98 male 23.00 0 1 PC 17759 633.583 D10 D12
## 99 female 34.00 0 1 231919 23.0
## 100 male 34.00 1 0 244367 26.0
## 101 female 28.00 0 0 349245 7.8958
## 102 male NA 0 0 349215 7.8958
## 103 male 21.00 0 1 35281 772.875 D26
## 104 male 33.00 0 0 7540 8.6542
## 105 male 37.00 2 0 3101276 7.925
## 106 male 28.00 0 0 349207 7.8958
## 107 female 21.00 0 0 343120 7.65
## 108 male NA 0 0 312991 7.775
## 109 male 38.00 0 0 349249 7.8958
## 110 female NA 1 0 371110 24.15
## 111 male 47.00 0 0 110465 52.0 C110
## 112 female 14.50 1 0 2665 144.542
## 113 male 22.00 0 0 324669 08.05
## 114 female 20.00 1 0 4136 9.825
## 115 female 17.00 0 0 2627 144.583
## 116 male 21.00 0 0 STON/O 2. 3101294 7.925
## 117 male 70.50 0 0 370369 7.75
## 118 male 29.00 1 0 11668 21.0
## 119 male 24.00 0 1 PC 17558 2.475.208 B58 B60
## 120 female 2.00 4 2 347082 31.275
## 121 male 21.00 2 0 S.O.C. 14879 73.5
## 122 male NA 0 0 A4. 54510 08.05
## 123 male 32.50 1 0 237736 300.708
## 124 female 32.50 0 0 27267 13.0 E101
## 125 male 54.00 0 1 35281 772.875 D26
## 126 male 12.00 1 0 2651 11.2417
## 127 male NA 0 0 370372 7.75
## 128 male 24.00 0 0 C 17369 7.1417
## 129 female NA 1 1 2668 223.583 F E69
## 130 male 45.00 0 0 347061 6.975
## 131 male 33.00 0 0 349241 7.8958
## 132 male 20.00 0 0 SOTON/O.Q. 3101307 07.05
## 133 female 47.00 1 0 A/5. 3337 14.5
## 134 female 29.00 1 0 228414 26.0
## 135 male 25.00 0 0 C.A. 29178 13.0
## 136 male 23.00 0 0 SC/PARIS 2133 150.458
## 137 female 19.00 0 2 11752 262.833 D47
## 138 male 37.00 1 0 113803 53.1 C123
## 139 male 16.00 0 0 7534 9.2167
## 140 male 24.00 0 0 PC 17593 79.2 B86
## 141 female NA 0 2 2678 152.458
## 142 female 22.00 0 0 347081 7.75
## 143 female 24.00 1 0 STON/O2. 3101279 15.85
## 144 male 19.00 0 0 365222 6.75
## 145 male 18.00 0 0 231945 11.5
## 146 male 19.00 1 1 C.A. 33112 36.75
## 147 male 27.00 0 0 350043 7.7958
## 148 female 9.00 2 2 W./C. 6608 34.375
## 149 male 36.50 0 2 230080 26.0 F2
## 150 male 42.00 0 0 244310 13.0
## 151 male 51.00 0 0 S.O.P. 1166 12.525
## 152 female 22.00 1 0 113776 66.6 C2
## 153 male 55.50 0 0 A.5. 11206 08.05
## 154 male 40.50 0 2 A/5. 851 14.5
## 155 male NA 0 0 Fa 265302 7.3125
## 156 male 51.00 0 1 PC 17597 613.792
## 157 female 16.00 0 0 35851 7.7333
## 158 male 30.00 0 0 SOTON/OQ 392090 08.05
## 159 male NA 0 0 315037 8.6625
## 160 male NA 8 2 CA. 2343 69.55
## 161 male 44.00 0 1 371362 16.1
## 162 female 40.00 0 0 C.A. 33595 15.75
## 163 male 26.00 0 0 347068 7.775
## 164 male 17.00 0 0 315093 8.6625
## 165 male 1.00 4 1 3101295 396.875
## 166 male 9.00 0 2 363291 20.525
## 167 female NA 0 1 113505 55.0 E33
## 168 female 45.00 1 4 347088 27.9
## 169 male NA 0 0 PC 17318 25.925
## 170 male 28.00 0 0 1601 564.958
## 171 male 61.00 0 0 111240 33.5 B19
## 172 male 4.00 4 1 382652 29.125
## 173 female 1.00 1 1 347742 11.1333
## 174 male 21.00 0 0 STON/O 2. 3101280 7.925
## 175 male 56.00 0 0 17764 306.958 A7
## 176 male 18.00 1 1 350404 7.8542
## 177 male NA 3 1 4133 254.667
## 178 female 50.00 0 0 PC 17595 287.125 C49
## 179 male 30.00 0 0 250653 13.0
## 180 male 36.00 0 0 LINE 0.0
## 181 female NA 8 2 CA. 2343 69.55
## 182 male NA 0 0 SC/PARIS 2131 15.05
## 183 male 9.00 4 2 347077 313.875
## 184 male 1.00 2 1 230136 39.0 F4
## 185 female 4.00 0 2 315153 22.025
## 186 male NA 0 0 113767 50.0 A32
## 187 female NA 1 0 370365 15.5
## 188 male 45.00 0 0 111428 26.55
## 189 male 40.00 1 1 364849 15.5
## 190 male 36.00 0 0 349247 7.8958
## 191 female 32.00 0 0 234604 13.0
## 192 male 19.00 0 0 28424 13.0
## 193 female 19.00 1 0 350046 7.8542
## 194 male 3.00 1 1 230080 26.0 F2
## 195 female 44.00 0 0 PC 17610 277.208 B4
## 196 female 58.00 0 0 PC 17569 1.465.208 B80
## 197 male NA 0 0 368703 7.75
## 198 male 42.00 0 1 4579 8.4042
## 199 female NA 0 0 370370 7.75
## 200 female 24.00 0 0 248747 13.0
## 201 male 28.00 0 0 345770 9.5
## 202 male NA 8 2 CA. 2343 69.55
## 203 male 34.00 0 0 3101264 6.4958
## 204 male 45.50 0 0 2628 7.225
## 205 male 18.00 0 0 A/5 3540 08.05
## 206 female 2.00 0 1 347054 10.4625 G6
## 207 male 32.00 1 0 3101278 15.85
## 208 male 26.00 0 0 2699 187.875
## 209 female 16.00 0 0 367231 7.75
## 210 male 40.00 0 0 112277 31.0 A31
## 211 male 24.00 0 0 SOTON/O.Q. 3101311 07.05
## 212 female 35.00 0 0 F.C.C. 13528 21.0
## 213 male 22.00 0 0 A/5 21174 7.25
## 214 male 30.00 0 0 250646 13.0
## 215 male NA 1 0 367229 7.75
## 216 female 31.00 1 0 35273 113.275 D36
## 217 female 27.00 0 0 STON/O2. 3101283 7.925
## 218 male 42.00 1 0 243847 27.0
## 219 female 32.00 0 0 11813 762.917 D15
## 220 male 30.00 0 0 W/C 14208 10.5
## 221 male 16.00 0 0 SOTON/OQ 392089 08.05
## 222 male 27.00 0 0 220367 13.0
## 223 male 51.00 0 0 21440 08.05
## 224 male NA 0 0 349234 7.8958
## 225 male 38.00 1 0 19943 90.0 C93
## 226 male 22.00 0 0 PP 4348 9.35
## 227 male 19.00 0 0 SW/PP 751 10.5
## 228 male 20.50 0 0 A/5 21173 7.25
## 229 male 18.00 0 0 236171 13.0
## 230 female NA 3 1 4133 254.667
## 231 female 35.00 1 0 36973 83.475 C83
## 232 male 29.00 0 0 347067 7.775
## 233 male 59.00 0 0 237442 13.5
## 234 female 5.00 4 2 347077 313.875
## 235 male 24.00 0 0 C.A. 29566 10.5
## 236 female NA 0 0 W./C. 6609 7.55
## 237 male 44.00 1 0 26707 26.0
## 238 female 8.00 0 2 C.A. 31921 26.25
## 239 male 19.00 0 0 28665 10.5
## 240 male 33.00 0 0 SCO/W 1585 12.275
## 241 female NA 1 0 2665 144.542
## 242 female NA 1 0 367230 15.5
## 243 male 29.00 0 0 W./C. 14263 10.5
## 244 male 22.00 0 0 STON/O 2. 3101275 7.125
## 245 male 30.00 0 0 2694 7.225
## 246 male 44.00 2 0 19928 90.0 C78
## 247 female 25.00 0 0 347071 7.775
## 248 female 24.00 0 2 250649 14.5
## 249 male 37.00 1 1 11751 525.542 D35
## 250 male 54.00 1 0 244252 26.0
## 251 male NA 0 0 362316 7.25
## 252 female 29.00 1 1 347054 10.4625 G6
## 253 male 62.00 0 0 113514 26.55 C87
## 254 male 30.00 1 0 A/5. 3336 16.1
## 255 female 41.00 0 2 370129 202.125
## 256 female 29.00 0 2 2650 152.458
## 257 female NA 0 0 PC 17585 79.2
## 258 female 30.00 0 0 110152 86.5 B77
## 259 female 35.00 0 0 PC 17755 5.123.292
## 260 female 50.00 0 1 230433 26.0
## 261 male NA 0 0 384461 7.75
## 262 male 3.00 4 2 347077 313.875
## 263 male 52.00 1 1 110413 79.65 E67
## 264 male 40.00 0 0 112059 0.0 B94
## 265 female NA 0 0 382649 7.75
## 266 male 36.00 0 0 C.A. 17248 10.5
## 267 male 16.00 4 1 3101295 396.875
## 268 male 25.00 1 0 347083 7.775
## 269 female 58.00 0 1 PC 17582 1.534.625 C125
## 270 female 35.00 0 0 PC 17760 1.356.333 C99
## 271 male NA 0 0 113798 31.0
## 272 male 25.00 0 0 LINE 0.0
## 273 female 41.00 0 1 250644 19.5
## 274 male 37.00 0 1 PC 17596 29.7 C118
## 275 female NA 0 0 370375 7.75
## 276 female 63.00 1 0 13502 779.583 D7
## 277 female 45.00 0 0 347073 7.75
## 278 male NA 0 0 239853 0.0
## 279 male 7.00 4 1 382652 29.125
## 280 female 35.00 1 1 C.A. 2673 20.25
## 281 male 65.00 0 0 336439 7.75
## 282 male 28.00 0 0 347464 7.8542
## 283 male 16.00 0 0 345778 9.5
## 284 male 19.00 0 0 A/5. 10482 08.05
## 285 male NA 0 0 113056 26.0 A19
## 286 male 33.00 0 0 349239 8.6625
## 287 male 30.00 0 0 345774 9.5
## 288 male 22.00 0 0 349206 7.8958
## 289 male 42.00 0 0 237798 13.0
## 290 female 22.00 0 0 370373 7.75
## 291 female 26.00 0 0 19877 78.85
## 292 female 19.00 1 0 11967 910.792 B49
## 293 male 36.00 0 0 SC/Paris 2163 12.875 D
## 294 female 24.00 0 0 349236 8.85
## 295 male 24.00 0 0 349233 7.8958
## 296 male NA 0 0 PC 17612 277.208
## 297 male 23.50 0 0 2693 7.2292
## 298 female 2.00 1 2 113781 151.55 C22 C26
## 299 male NA 0 0 19988 30.5 C106
## 300 female 50.00 0 1 PC 17558 2.475.208 B58 B60
## 301 female NA 0 0 9234 7.75
## 302 male NA 2 0 367226 23.25
## 303 male 19.00 0 0 LINE 0.0
## 304 female NA 0 0 226593 12.35 E101
## 305 male NA 0 0 A/5 2466 08.05
## 306 male 0.92 1 2 113781 151.55 C22 C26
## 307 female NA 0 0 17421 1.108.833
## 308 female 17.00 1 0 PC 17758 108.9 C65
## 309 male 30.00 1 0 P/PP 3381 24.0
## 310 female 30.00 0 0 PC 17485 569.292 E36
## 311 female 24.00 0 0 11767 831.583 C54
## 312 female 18.00 2 2 PC 17608 262.375 B57 B59 B63 B66
## 313 female 26.00 1 1 250651 26.0
## 314 male 28.00 0 0 349243 7.8958
## 315 male 43.00 1 1 F.C.C. 13529 26.25
## 316 female 26.00 0 0 347470 7.8542
## 317 female 24.00 1 0 244367 26.0
## 318 male 54.00 0 0 29011 14.0
## 319 female 31.00 0 2 36928 1.648.667 C7
## 320 female 40.00 1 1 16966 134.5 E34
## 321 male 22.00 0 0 A/5 21172 7.25
## 322 male 27.00 0 0 349219 7.8958
## 323 female 30.00 0 0 234818 12.35
## 324 female 22.00 1 1 248738 29.0
## 325 male NA 8 2 CA. 2343 69.55
## 326 female 36.00 0 0 PC 17760 1.356.333 C32
## 327 male 61.00 0 0 345364 6.2375
## 328 female 36.00 0 0 28551 13.0 D
## 329 female 31.00 1 1 363291 20.525
## 330 female 16.00 0 1 111361 579.792 B18
## 331 female NA 2 0 367226 23.25
## 332 male 45.50 0 0 113043 28.5 C124
## 333 male 38.00 0 1 PC 17582 1.534.625 C91
## 334 male 16.00 2 0 345764 18.0
## 335 female NA 1 0 PC 17611 133.65
## 336 male NA 0 0 349225 7.8958
## 337 male 29.00 1 0 113776 66.6 C2
## 338 female 41.00 0 0 16966 134.5 E40
## 339 male 45.00 0 0 7598 08.05
## 340 male 45.00 0 0 113784 35.5 T
## 341 male 2.00 1 1 230080 26.0 F2
## 342 female 24.00 3 2 19950 263.0 C23 C25 C27
## 343 male 28.00 0 0 248740 13.0
## 344 male 25.00 0 0 244361 13.0
## 345 male 36.00 0 0 229236 13.0
## 346 female 24.00 0 0 248733 13.0 F33
## 347 female 40.00 0 0 31418 13.0
## 348 female NA 1 0 386525 16.1
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## 350 male 42.00 0 0 315088 8.6625
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## 352 male NA 0 0 113510 35.0 C128
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## 355 male NA 0 0 2647 7.225
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## 359 female NA 0 0 330931 7.8792
## 360 female NA 0 0 330980 7.8792
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## 362 male 29.00 1 0 SC/PARIS 2167 277.208
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## 364 male 35.00 0 0 SOTON/O.Q. 3101310 07.05
## 365 male NA 1 0 370365 15.5
## 366 male 30.00 0 0 C 7076 7.25
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## 368 female NA 0 0 2626 7.2292
## 369 female NA 0 0 14313 7.75
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## 373 male 19.00 0 0 323951 08.05
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## 376 female NA 1 0 PC 17604 821.708
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## 378 male 27.00 0 2 113503 211.5 C82
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## 380 male 19.00 0 0 347069 7.775
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## 382 female 1.00 0 2 2653 157.417
## 383 male 32.00 0 0 STON/O 2. 3101293 7.925
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## 385 male NA 0 0 349227 7.8958
## 386 male 18.00 0 0 S.O.C. 14879 73.5
## 387 male 1.00 5 2 CA 2144 46.9
## 388 female 36.00 0 0 27849 13.0
## 389 male NA 0 0 367655 7.7292
## 390 female 17.00 0 0 SC 1748 12.0
## 391 male 36.00 1 2 113760 120.0 B96 B98
## 392 male 21.00 0 0 350034 7.7958
## 393 male 28.00 2 0 3101277 7.925
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## 395 female 24.00 0 2 PP 9549 16.7 G6
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## 399 male 23.00 0 0 244278 10.5
## 400 female 28.00 0 0 240929 12.65
## 401 male 39.00 0 0 STON/O 2. 3101289 7.925
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## 407 male 51.00 0 0 347064 7.75
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## 410 female NA 3 1 4133 254.667
## 411 male NA 0 0 349222 7.8958
## 412 male NA 0 0 394140 6.8583
## 413 female 33.00 1 0 19928 90.0 C78
## 414 male NA 0 0 239853 0.0
## 415 male 44.00 0 0 STON/O 2. 3101269 7.925
## 416 female NA 0 0 343095 08.05
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## 418 female 18.00 0 2 250652 13.0
## 419 male 30.00 0 0 28228 13.0
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## 421 male NA 0 0 349254 7.8958
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## 423 male 29.00 0 0 315082 7.875
## 424 female 28.00 1 1 347080 14.4
## 425 male 18.00 1 1 370129 202.125
## 426 male NA 0 0 A/4. 34244 7.25
## 427 female 28.00 1 0 2003 26.0
## 428 female 19.00 0 0 250655 26.0
## 429 male NA 0 0 364851 7.75
## 430 male 32.00 0 0 SOTON/O.Q. 392078 08.05 E10
## 431 male 28.00 0 0 110564 26.55 C52
## 432 female NA 1 0 376564 16.1
## 433 female 42.00 1 0 SC/AH 3085 26.0
## 434 male 17.00 0 0 STON/O 2. 3101274 7.125
## 435 male 50.00 1 0 13507 55.9 E44
## 436 female 14.00 1 2 113760 120.0 B96 B98
## 437 female 21.00 2 2 W./C. 6608 34.375
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## 439 male 64.00 1 4 19950 263.0 C23 C25 C27
## 440 male 31.00 0 0 C.A. 18723 10.5
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## 442 male 20.00 0 0 345769 9.5
## 443 male 25.00 1 0 347076 7.775
## 444 female 28.00 0 0 230434 13.0
## 445 male NA 0 0 65306 8.1125
## 446 male 4.00 0 2 33638 818.583 A34
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## 449 female 5.00 2 1 2666 192.583
## 450 male 52.00 0 0 113786 30.5 C104
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## 452 male NA 1 0 65303 199.667
## 453 male 30.00 0 0 113051 27.75 C111
## 454 male 49.00 1 0 17453 891.042 C92
## 455 male NA 0 0 A/5 2817 08.05
## 456 male 29.00 0 0 349240 7.8958
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## 458 female NA 1 0 17464 518.625 D21
## 459 female 50.00 0 0 F.C.C. 13531 10.5
## 460 male NA 0 0 371060 7.75
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## 462 male 34.00 0 0 364506 08.05
## 463 male 47.00 0 0 111320 38.5 E63
## 464 male 48.00 0 0 234360 13.0
## 465 male NA 0 0 A/S 2816 08.05
## 466 male 38.00 0 0 SOTON/O.Q. 3101306 07.05
## 467 male NA 0 0 239853 0.0
## 468 male 56.00 0 0 113792 26.55
## 469 male NA 0 0 36209 7.725
## 470 female 0.75 2 1 2666 192.583
## 471 male NA 0 0 323592 7.25
## 472 male 38.00 0 0 315089 8.6625
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## 474 female 23.00 0 0 SC/AH Basle 541 137.917 D
## 475 female 22.00 0 0 7553 9.8375
## 476 male NA 0 0 110465 52.0 A14
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## 478 male 29.00 1 0 3460 7.0458
## 479 male 22.00 0 0 350060 7.5208
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## 482 male NA 0 0 239854 0.0
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## 485 male 25.00 1 0 11967 910.792 B49
## 486 female NA 3 1 4133 254.667
## 487 female 35.00 1 0 19943 90.0 C93
## 488 male 58.00 0 0 11771 29.7 B37
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## 491 male NA 1 0 65304 199.667
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## 493 male 55.00 0 0 113787 30.5 C30
## 494 male 71.00 0 0 PC 17609 495.042
## 495 male 21.00 0 0 A/4 45380 08.05
## 496 male NA 0 0 2627 144.583
## 497 female 54.00 1 0 36947 782.667 D20
## 498 male NA 0 0 C.A. 6212 15.1
## 499 female 25.00 1 2 113781 151.55 C22 C26
## 500 male 24.00 0 0 350035 7.7958
## 501 male 17.00 0 0 315086 8.6625
## 502 female 21.00 0 0 364846 7.75
## 503 female NA 0 0 330909 7.6292
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## 505 female 16.00 0 0 110152 86.5 B79
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## 508 male NA 0 0 111427 26.55
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## 512 male NA 0 0 SOTON/OQ 3101316 08.05
## 513 male 36.00 0 0 PC 17473 262.875 E25
## 514 female 54.00 1 0 PC 17603 59.4
## 515 male 24.00 0 0 349209 7.4958
## 516 male 47.00 0 0 36967 340.208 D46
## 517 female 34.00 0 0 C.A. 34260 10.5 F33
## 518 male NA 0 0 371110 24.15
## 519 female 36.00 1 0 226875 26.0
## 520 male 32.00 0 0 349242 7.8958
## 521 female 30.00 0 0 12749 93.5 B73
## 522 male 22.00 0 0 349252 7.8958
## 523 male NA 0 0 2624 7.225
## 524 female 44.00 0 1 111361 579.792 B18
## 525 male NA 0 0 2700 7.2292
## 526 male 40.50 0 0 367232 7.75
## 527 female 50.00 0 0 W./C. 14258 10.5
## 528 male NA 0 0 PC 17483 2.217.792 C95
## 529 male 39.00 0 0 3101296 7.925
## 530 male 23.00 2 1 29104 11.5
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## 532 male NA 0 0 2641 7.2292
## 533 male 17.00 1 1 2690 7.2292
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## 536 female 7.00 0 2 F.C.C. 13529 26.25
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## 539 male NA 0 0 364498 14.5
## 540 female 22.00 0 2 13568 49.5 B39
## 541 female 36.00 0 2 WE/P 5735 71.0 B22
## 542 female 9.00 4 2 347082 31.275
## 543 female 11.00 4 2 347082 31.275
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## 545 male 50.00 1 0 PC 17761 106.425 C86
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## 547 female 19.00 1 0 2908 26.0
## 548 male NA 0 0 SC/PARIS 2146 138.625
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## 550 male 8.00 1 1 C.A. 33112 36.75
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## 553 male NA 0 0 330979 7.8292
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## 555 female 22.00 0 0 347085 7.775
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## 558 male NA 0 0 PC 17757 227.525
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## 561 male NA 0 0 372622 7.75
## 562 male 40.00 0 0 349251 7.8958
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## 564 male NA 0 0 SOTON/OQ 392082 08.05
## 565 female NA 0 0 SOTON/O.Q. 392087 08.05
## 566 male 24.00 2 0 A/4 48871 24.15
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## 568 female 29.00 0 4 349909 21.075
## 569 male NA 0 0 2686 7.2292
## 570 male 32.00 0 0 350417 7.8542
## 571 male 62.00 0 0 S.W./PP 752 10.5
## 572 female 53.00 2 0 11769 514.792 C101
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## 574 female NA 0 0 14312 7.75
## 575 male 16.00 0 0 A/4. 20589 08.05
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## 577 female 34.00 0 0 243880 13.0
## 578 female 39.00 1 0 13507 55.9 E44
## 579 female NA 1 0 2689 144.583
## 580 male 32.00 0 0 STON/O 2. 3101286 7.925
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## 582 female 39.00 1 1 17421 1.108.833 C68
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## 589 male 22.00 0 0 14973 08.05
## 590 male NA 0 0 A./5. 3235 08.05
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## 593 male 47.00 0 0 A/5 3902 7.25
## 594 female NA 0 2 364848 7.75
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## 597 female NA 0 0 248727 33.0
## 598 male 49.00 0 0 LINE 0.0
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## 602 male NA 0 0 349214 7.8958
## 603 male NA 0 0 113796 42.4
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## 611 female 39.00 1 5 347082 31.275
## 612 male NA 0 0 SOTON/O.Q. 3101305 07.05
## 613 female NA 1 0 367230 15.5
## 614 male NA 0 0 370377 7.75
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## 618 female 26.00 1 0 A/5. 3336 16.1
## 619 female 4.00 2 1 230136 39.0 F4
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## 622 male 42.00 1 0 11753 525.542 D19
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## 628 female 21.00 0 0 13502 779.583 D9
## 629 male 26.00 0 0 349224 7.8958
## 630 male NA 0 0 334912 7.7333
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## 634 male NA 0 0 112052 0.0
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## 636 female 28.00 0 0 237668 13.0
## 637 male 32.00 0 0 STON/O 2. 3101292 7.925
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## 640 male NA 1 0 376564 16.1
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## 643 female 2.00 3 2 347088 27.9
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## 645 female 0.75 2 1 2666 192.583
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## 647 male 19.00 0 0 349231 7.8958
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## 650 female 23.00 0 0 CA. 2314 7.55
## 651 male NA 0 0 349221 7.8958
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## 654 female NA 0 0 330919 7.8292
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## 657 male NA 0 0 349223 7.8958
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## 659 male 23.00 0 0 29751 13.0
## 660 male 58.00 0 2 35273 113.275 D48
## 661 male 50.00 2 0 PC 17611 133.65
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## 665 male 20.00 1 0 STON/O 2. 3101285 7.925
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## 668 male NA 0 0 312993 7.775
## 669 male 43.00 0 0 A/5 3536 08.05
## 670 female NA 1 0 19996 52.0 C126
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## 672 male 31.00 1 0 F.C. 12750 52.0 B71
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## 675 male NA 0 0 239856 0.0
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## 680 male 36.00 0 1 PC 17755 5.123.292 B51 B53 B55
## 681 female NA 0 0 330935 8.1375
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## 683 male 20.00 0 0 6563 9.225
## 684 male 14.00 5 2 CA 2144 46.9
## 685 male 60.00 1 1 29750 39.0
## 686 male 25.00 1 2 SC/Paris 2123 415.792
## 687 male 14.00 4 1 3101295 396.875
## 688 male 19.00 0 0 349228 10.1708
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## 690 female 15.00 0 1 24160 2.113.375 B5
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## 692 female 4.00 0 1 349256 134.167
## 693 male NA 0 0 1601 564.958
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## 697 male 44.00 0 0 363592 08.05
## 698 female NA 0 0 35852 7.7333
## 699 male 49.00 1 1 17421 1.108.833 C68
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## 704 male 25.00 0 0 36864 7.7417
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## 709 female 22.00 0 0 113781 151.55
## 710 male NA 1 1 2661 152.458
## 711 female 24.00 0 0 PC 17482 495.042 C90
## 712 male NA 0 0 113028 26.55 C124
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## 715 male 52.00 0 0 250647 13.0
## 716 male 19.00 0 0 348124 7.65 F G73
## 717 female 38.00 0 0 PC 17757 227.525 C45
## 718 female 27.00 0 0 34218 10.5 E101
## 719 male NA 0 0 36568 15.5
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## 722 male 17.00 1 0 350048 7.0542
## 723 male 34.00 0 0 12233 13.0
## 724 male 50.00 0 0 250643 13.0
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## 727 female 30.00 3 0 31027 21.0
## 728 female NA 0 0 36866 7.7375
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## 730 female 25.00 1 0 STON/O2. 3101271 7.925
## 731 female 29.00 0 0 24160 2.113.375 B5
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## 733 male NA 0 0 239855 0.0
## 734 male 23.00 0 0 28425 13.0
## 735 male 23.00 0 0 233639 13.0
## 736 male 28.50 0 0 54636 16.1
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## 738 male 35.00 0 0 PC 17755 5.123.292 B101
## 739 male NA 0 0 349201 7.8958
## 740 male NA 0 0 349218 7.8958
## 741 male NA 0 0 16988 30.0 D45
## 742 male 36.00 1 0 19877 78.85 C46
## 743 female 21.00 2 2 PC 17608 262.375 B57 B59 B63 B66
## 744 male 24.00 1 0 376566 16.1
## 745 male 31.00 0 0 STON/O 2. 3101288 7.925
## 746 male 70.00 1 1 WE/P 5735 71.0 B22
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## 752 male 6.00 0 1 392096 12.475 E121
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## 754 male 23.00 0 0 349204 7.8958
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## 756 male 0.67 1 1 250649 14.5
## 757 male 28.00 0 0 350042 7.7958
## 758 male 18.00 0 0 29108 11.5
## 759 male 34.00 0 0 363294 08.05
## 760 female 33.00 0 0 110152 86.5 B77
## 761 male NA 0 0 358585 14.5
## 762 male 41.00 0 0 SOTON/O2 3101272 7.125
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## 764 female 36.00 1 2 113760 120.0 B96 B98
## 765 male 16.00 0 0 347074 7.775
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## 767 male NA 0 0 112379 39.6
## 768 female 30.50 0 0 364850 7.75
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## 770 male 32.00 0 0 8471 8.3625
## 771 male 24.00 0 0 345781 9.5
## 772 male 48.00 0 0 350047 7.8542
## 773 female 57.00 0 0 S.O./P.P. 3 10.5 E77
## 774 male NA 0 0 2674 7.225
## 775 female 54.00 1 3 29105 23.0
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## 777 male NA 0 0 383121 7.75 F38
## 778 female 5.00 0 0 364516 12.475
## 779 male NA 0 0 36865 7.7375
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## 782 female 17.00 1 0 17474 57.0 B20
## 783 male 29.00 0 0 113501 30.0 D6
## 784 male NA 1 2 W./C. 6607 23.45
## 785 male 25.00 0 0 SOTON/O.Q. 3101312 07.05
## 786 male 25.00 0 0 374887 7.25
## 787 female 18.00 0 0 3101265 7.4958
## 788 male 8.00 4 1 382652 29.125
## 789 male 1.00 1 2 C.A. 2315 20.575
## 790 male 46.00 0 0 PC 17593 79.2 B82 B84
## 791 male NA 0 0 12460 7.75
## 792 male 16.00 0 0 239865 26.0
## 793 female NA 8 2 CA. 2343 69.55
## 794 male NA 0 0 PC 17600 306.958
## 795 male 25.00 0 0 349203 7.8958
## 796 male 39.00 0 0 28213 13.0
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## 798 female 31.00 0 0 349244 8.6833
## 799 male 30.00 0 0 2685 7.2292
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## 803 male 11.00 1 2 113760 120.0 B96 B98
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## 805 male 27.00 0 0 347089 6.975
## 806 male 31.00 0 0 347063 7.775
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## 808 female 18.00 0 0 347087 7.775
## 809 male 39.00 0 0 248723 13.0
## 810 female 33.00 1 0 113806 53.1 E8
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## 812 male 39.00 0 0 A/4 48871 24.15
## 813 male 35.00 0 0 28206 10.5
## 814 female 6.00 4 2 347082 31.275
## 815 male 30.50 0 0 364499 08.05
## 816 male NA 0 0 112058 0.0 B102
## 817 female 23.00 0 0 STON/O2. 3101290 7.925
## 818 male 31.00 1 1 S.C./PARIS 2079 370.042
## 819 male 43.00 0 0 C 7075 6.45
## 820 male 10.00 3 2 347088 27.9
## 821 female 52.00 1 1 12749 93.5 B69
## 822 male 27.00 0 0 315098 8.6625
## 823 male 38.00 0 0 19972 0.0
## 824 female 27.00 0 1 392096 12.475 E121
## 825 male 2.00 4 1 3101295 396.875
## 826 male NA 0 0 368323 6.95
## 827 male NA 0 0 1601 564.958
## 828 male 1.00 0 2 S.C./PARIS 2079 370.042
## 829 male NA 0 0 367228 7.75
## 830 female 62.00 0 0 113572 80.0 B28
## 831 female 15.00 1 0 2659 144.542
## 832 male 0.83 1 1 29106 18.75
## 833 male NA 0 0 2671 7.2292
## 834 male 23.00 0 0 347468 7.8542
## 835 male 18.00 0 0 2223 8.3
## 836 female 39.00 1 1 PC 17756 831.583 E49
## 837 male 21.00 0 0 315097 8.6625
## 838 male NA 0 0 392092 08.05
## 839 male 32.00 0 0 1601 564.958
## 840 male NA 0 0 11774 29.7 C47
## 841 male 20.00 0 0 SOTON/O2 3101287 7.925
## 842 male 16.00 0 0 S.O./P.P. 3 10.5
## 843 female 30.00 0 0 113798 31.0
## 844 male 34.50 0 0 2683 6.4375
## 845 male 17.00 0 0 315090 8.6625
## 846 male 42.00 0 0 C.A. 5547 7.55
## 847 male NA 8 2 CA. 2343 69.55
## 848 male 35.00 0 0 349213 7.8958
## 849 male 28.00 0 1 248727 33.0
## 850 female NA 1 0 17453 891.042 C92
## 851 male 4.00 4 2 347082 31.275
## 852 male 74.00 0 0 347060 7.775
## 853 female 9.00 1 1 2678 152.458
## 854 female 16.00 0 1 PC 17592 39.4 D28
## 855 female 44.00 1 0 244252 26.0
## 856 female 18.00 0 1 392091 9.35
## 857 female 45.00 1 1 36928 1.648.667
## 858 male 51.00 0 0 113055 26.55 E17
## 859 female 24.00 0 3 2666 192.583
## 860 male NA 0 0 2629 7.2292
## 861 male 41.00 2 0 350026 141.083
## 862 male 21.00 1 0 28134 11.5
## 863 female 48.00 0 0 17466 259.292 D17
## 864 female NA 8 2 CA. 2343 69.55
## 865 male 24.00 0 0 233866 13.0
## 866 female 42.00 0 0 236852 13.0
## 867 female 27.00 1 0 SC/PARIS 2149 138.583
## 868 male 31.00 0 0 PC 17590 504.958 A24
## 869 male NA 0 0 345777 9.5
## 870 male 4.00 1 1 347742 11.1333
## 871 male 26.00 0 0 349248 7.8958
## 872 female 47.00 1 1 11751 525.542 D35
## 873 male 33.00 0 0 695 5.0 B51 B53 B55
## 874 male 47.00 0 0 345765 9.0
## 875 female 28.00 1 0 P/PP 3381 24.0
## 876 female 15.00 0 0 2667 7.225
## 877 male 20.00 0 0 7534 9.8458
## 878 male 19.00 0 0 349212 7.8958
## 879 male NA 0 0 349217 7.8958
## 880 female 56.00 0 1 11767 831.583 C50
## 881 female 25.00 0 1 230433 26.0
## 882 male 33.00 0 0 349257 7.8958
## 883 female 22.00 0 0 7552 10.5167
## 884 male 28.00 0 0 C.A./SOTON 34068 10.5
## 885 male 25.00 0 0 SOTON/OQ 392076 07.05
## 886 female 39.00 0 5 382652 29.125
## 887 male 27.00 0 0 211536 13.0
## 888 female 19.00 0 0 112053 30.0 B42
## 889 female NA 1 2 W./C. 6607 23.45
## 890 male 26.00 0 0 111369 30.0 C148
## 891 male 32.00 0 0 370376 7.75
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## 891 QDimensi Data
dim(dataset_a)## [1] 891 12Variabel pada Dataset
colnames(dataset_a)## [1] "PassengerId" "Survived" "Pclass" "Name" "Sex"
## [6] "Age" "SibSp" "Parch" "Ticket" "Fare"
## [11] "Cabin" "Embarked"str(dataset_a)## 'data.frame': 891 obs. of 12 variables:
## $ PassengerId: int 1 2 3 4 5 6 7 8 9 10 ...
## $ Survived : int 0 1 1 1 0 0 0 0 1 1 ...
## $ Pclass : int 3 1 3 1 3 3 1 3 3 2 ...
## $ Name : chr "Braund, Mr. Owen Harris" "Cumings, Mrs. John Bradley (Florence Briggs Thayer)" "Heikkinen, Miss. Laina" "Futrelle, Mrs. Jacques Heath (Lily May Peel)" ...
## $ Sex : chr "male" "female" "female" "female" ...
## $ Age : num 22 38 26 35 35 NA 54 2 27 14 ...
## $ SibSp : int 1 1 0 1 0 0 0 3 0 1 ...
## $ Parch : int 0 0 0 0 0 0 0 1 2 0 ...
## $ Ticket : chr "A/5 21171" "PC 17599" "STON/O2. 3101282" "113803" ...
## $ Fare : chr "7.25" "712.833" "7.925" "53.1" ...
## $ Cabin : chr "" "C85" "" "C123" ...
## $ Embarked : chr "S" "C" "S" "S" ...Melihat Statistik Data
summary(dataset_a)## PassengerId Survived Pclass Name
## Min. : 1.0 Min. :0.0000 Min. :1.000 Length:891
## 1st Qu.:223.5 1st Qu.:0.0000 1st Qu.:2.000 Class :character
## Median :446.0 Median :0.0000 Median :3.000 Mode :character
## Mean :446.0 Mean :0.3838 Mean :2.309
## 3rd Qu.:668.5 3rd Qu.:1.0000 3rd Qu.:3.000
## Max. :891.0 Max. :1.0000 Max. :3.000
##
## Sex Age SibSp Parch
## Length:891 Min. : 0.42 Min. :0.000 Min. :0.0000
## Class :character 1st Qu.:20.12 1st Qu.:0.000 1st Qu.:0.0000
## Mode :character Median :28.00 Median :0.000 Median :0.0000
## Mean :29.70 Mean :0.523 Mean :0.3816
## 3rd Qu.:38.00 3rd Qu.:1.000 3rd Qu.:0.0000
## Max. :80.00 Max. :8.000 Max. :6.0000
## NA's :177
## Ticket Fare Cabin Embarked
## Length:891 Length:891 Length:891 Length:891
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## Dengan menggunakan perintah summary() kita dapat sekaligus menemukan missing datanya. Missing data tersebut dapat dilihat pada bagian NA’S. Di dataset ini, missing data hanya terdapat pada variabel Age sebanyak 177 data.
sum(is.na(dataset_a)) # Mengecek ulang missing value## [1] 177Mengecek Outlier
# LIST OUTLIER SECARA NUMERIK
boxplot(dataset_a$PassengerId, plot = FALSE)$out## numeric(0)boxplot(dataset_a$Survived, plot = FALSE)$out## numeric(0)boxplot(dataset_a$Age, plot = FALSE)$out## [1] 66.0 71.0 70.5 71.0 80.0 70.0 70.0 74.0boxplot(dataset_a$Pclass, plot = FALSE)$out## numeric(0)boxplot(dataset_a$SibSp, plot = FALSE)$out## [1] 3 4 3 3 4 5 3 4 5 3 3 4 8 4 4 3 8 4 8 3 4 4 4 4 8 3 3 5 3 5 3 4 4 3 3 5 4 3
## [39] 4 8 4 3 4 8 4 8boxplot(dataset_a$Parch, plot = FALSE)$out## [1] 1 2 1 5 1 1 5 2 2 1 1 2 2 2 1 2 2 2 3 2 2 1 1 1 1 2 1 1 2 2 1 2 2 2 1 2 1
## [38] 1 2 1 4 1 1 1 1 2 2 1 2 1 1 1 2 1 1 2 2 2 1 1 2 2 1 2 1 1 1 1 1 1 1 2 1 2
## [75] 2 1 1 2 1 1 2 1 1 1 1 2 1 1 1 4 1 1 2 2 2 2 2 1 1 1 2 2 1 1 2 2 3 4 1 2 1
## [112] 1 2 1 2 1 2 1 1 2 2 1 1 1 1 2 2 2 2 2 2 1 1 2 1 4 1 1 2 1 2 1 1 2 5 2 1 1
## [149] 1 2 1 5 2 1 1 1 2 1 6 1 2 1 2 1 1 1 1 1 1 1 3 2 1 1 1 1 2 1 2 3 1 2 1 2 2
## [186] 1 1 2 1 2 1 2 1 1 1 2 1 1 2 1 2 1 1 1 1 3 2 1 1 1 1 5 2# GRAFIK DATASET
dataset <- read.csv(file.choose(), header = T) # mengakses dataset yang sudah di filter menggunakan MySQL
boxplot(dataset)
Dari boxplot diatas, dapat dilihat bahwa kolom numerik yang memiliki outlier atau pencilan yaitu kolom Age, Parch, dan SibSp
Melihat Korelasi Data
library(psych)##
## Attaching package: 'psych'## The following objects are masked from 'package:ggplot2':
##
## %+%, alphadataset <- read.csv(file.choose(), header = T) # mengakses dataset yang sudah di filter menggunakan MySQL
corPlot(dataset,
cex = 1) # Mengubah ukuran teks 
Plot Distribusi Data Numerik
qqnorm(dataset$Age)
qqline(dataset$Age) # Melihat secara visual apakah data berdistribusi normal atau tidak
qqnorm(dataset$PassengerId)
qqline(dataset$PassengerId)
qqnorm(dataset$Parch)
qqline(dataset$Parch)
qqnorm(dataset$Survived)
qqline(dataset$Survived)
qqnorm(dataset$Pclass)
qqline(dataset$Pclass)
qqnorm(dataset$SibSp)
qqline(dataset$SibSp)
# Apabila data cenderung berada pada garis berarti data berdistribusi normal
# Namun apabila sebagian besar berada di bawah garis, maka data tidak berdistribusi normalData Preprocessing
Seleksi Kolom
Seleksi kolom ini untuk menghapus data atau kolom yang tidak diperlukan, yaitu kolom name dan ticket.
dataset <- dataset[, -4] # Menghapus kolom ke-4 pada tabel dataset, yaitu kolom name
dataset < dataset[, -9] # Menghapus kolom ke-9 pada tabel dataset, yaitu kolom ticket## Age PassengerId Parch SibSp Survived
## [1,] FALSE FALSE FALSE FALSE FALSE
## [2,] FALSE FALSE FALSE FALSE FALSE
## [3,] FALSE FALSE FALSE FALSE FALSE
## [4,] FALSE FALSE FALSE FALSE FALSE
## [5,] FALSE FALSE FALSE FALSE FALSE
## [6,] NA FALSE FALSE FALSE FALSE
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## [27,] NA FALSE FALSE FALSE FALSE
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## [718,] FALSE FALSE FALSE FALSE FALSE
## [719,] NA FALSE FALSE FALSE FALSE
## [720,] FALSE FALSE FALSE FALSE FALSE
## [721,] FALSE FALSE FALSE FALSE FALSE
## [722,] FALSE FALSE FALSE FALSE FALSE
## [723,] FALSE FALSE FALSE FALSE FALSE
## [724,] FALSE FALSE FALSE FALSE FALSE
## [725,] FALSE FALSE FALSE FALSE FALSE
## [726,] FALSE FALSE FALSE FALSE FALSE
## [727,] FALSE FALSE FALSE FALSE FALSE
## [728,] NA FALSE FALSE FALSE FALSE
## [729,] FALSE FALSE FALSE FALSE FALSE
## [730,] FALSE FALSE FALSE FALSE FALSE
## [731,] FALSE FALSE FALSE FALSE FALSE
## [732,] FALSE FALSE FALSE FALSE FALSE
## [733,] NA FALSE FALSE FALSE FALSE
## [734,] FALSE FALSE FALSE FALSE FALSE
## [735,] FALSE FALSE FALSE FALSE FALSE
## [736,] FALSE FALSE FALSE FALSE FALSE
## [737,] FALSE FALSE FALSE FALSE FALSE
## [738,] FALSE FALSE FALSE FALSE FALSE
## [739,] NA FALSE FALSE FALSE FALSE
## [740,] NA FALSE FALSE FALSE FALSE
## [741,] NA FALSE FALSE FALSE FALSE
## [742,] FALSE FALSE FALSE FALSE FALSE
## [743,] FALSE FALSE FALSE FALSE FALSE
## [744,] FALSE FALSE FALSE FALSE FALSE
## [745,] FALSE FALSE FALSE FALSE FALSE
## [746,] FALSE FALSE FALSE FALSE FALSE
## [747,] FALSE FALSE FALSE FALSE FALSE
## [748,] FALSE FALSE FALSE FALSE FALSE
## [749,] FALSE FALSE FALSE FALSE FALSE
## [750,] FALSE FALSE FALSE FALSE FALSE
## [751,] FALSE FALSE FALSE FALSE FALSE
## [752,] FALSE FALSE FALSE FALSE FALSE
## [753,] FALSE FALSE FALSE FALSE FALSE
## [754,] FALSE FALSE FALSE FALSE FALSE
## [755,] FALSE FALSE FALSE FALSE FALSE
## [756,] FALSE FALSE FALSE FALSE FALSE
## [757,] FALSE FALSE FALSE FALSE FALSE
## [758,] FALSE FALSE FALSE FALSE FALSE
## [759,] FALSE FALSE FALSE FALSE FALSE
## [760,] FALSE FALSE FALSE FALSE FALSE
## [761,] NA FALSE FALSE FALSE FALSE
## [762,] FALSE FALSE FALSE FALSE FALSE
## [763,] FALSE FALSE FALSE FALSE FALSE
## [764,] FALSE FALSE FALSE FALSE FALSE
## [765,] FALSE FALSE FALSE FALSE FALSE
## [766,] FALSE FALSE FALSE FALSE FALSE
## [767,] NA FALSE FALSE FALSE FALSE
## [768,] FALSE FALSE FALSE FALSE FALSE
## [769,] NA FALSE FALSE FALSE FALSE
## [770,] FALSE FALSE FALSE FALSE FALSE
## [771,] FALSE FALSE FALSE FALSE FALSE
## [772,] FALSE FALSE FALSE FALSE FALSE
## [773,] FALSE FALSE FALSE FALSE FALSE
## [774,] NA FALSE FALSE FALSE FALSE
## [775,] FALSE FALSE FALSE FALSE FALSE
## [776,] FALSE FALSE FALSE FALSE FALSE
## [777,] NA FALSE FALSE FALSE FALSE
## [778,] FALSE FALSE FALSE FALSE FALSE
## [779,] NA FALSE FALSE FALSE FALSE
## [780,] FALSE FALSE FALSE FALSE FALSE
## [781,] FALSE FALSE FALSE FALSE FALSE
## [782,] FALSE FALSE FALSE FALSE FALSE
## [783,] FALSE FALSE FALSE FALSE FALSE
## [784,] NA FALSE FALSE FALSE FALSE
## [785,] FALSE FALSE FALSE FALSE FALSE
## [786,] FALSE FALSE FALSE FALSE FALSE
## [787,] FALSE FALSE FALSE FALSE FALSE
## [788,] FALSE FALSE FALSE FALSE FALSE
## [789,] FALSE FALSE FALSE FALSE FALSE
## [790,] FALSE FALSE FALSE FALSE FALSE
## [791,] NA FALSE FALSE FALSE FALSE
## [792,] FALSE FALSE FALSE FALSE FALSE
## [793,] NA FALSE FALSE FALSE FALSE
## [794,] NA FALSE FALSE FALSE FALSE
## [795,] FALSE FALSE FALSE FALSE FALSE
## [796,] FALSE FALSE FALSE FALSE FALSE
## [797,] FALSE FALSE FALSE FALSE FALSE
## [798,] FALSE FALSE FALSE FALSE FALSE
## [799,] FALSE FALSE FALSE FALSE FALSE
## [800,] FALSE FALSE FALSE FALSE FALSE
## [801,] FALSE FALSE FALSE FALSE FALSE
## [802,] FALSE FALSE FALSE FALSE FALSE
## [803,] FALSE FALSE FALSE FALSE FALSE
## [804,] FALSE FALSE FALSE FALSE FALSE
## [805,] FALSE FALSE FALSE FALSE FALSE
## [806,] FALSE FALSE FALSE FALSE FALSE
## [807,] FALSE FALSE FALSE FALSE FALSE
## [808,] FALSE FALSE FALSE FALSE FALSE
## [809,] FALSE FALSE FALSE FALSE FALSE
## [810,] FALSE FALSE FALSE FALSE FALSE
## [811,] FALSE FALSE FALSE FALSE FALSE
## [812,] FALSE FALSE FALSE FALSE FALSE
## [813,] FALSE FALSE FALSE FALSE FALSE
## [814,] FALSE FALSE FALSE FALSE FALSE
## [815,] FALSE FALSE FALSE FALSE FALSE
## [816,] NA FALSE FALSE FALSE FALSE
## [817,] FALSE FALSE FALSE FALSE FALSE
## [818,] FALSE FALSE FALSE FALSE FALSE
## [819,] FALSE FALSE FALSE FALSE FALSE
## [820,] FALSE FALSE FALSE FALSE FALSE
## [821,] FALSE FALSE FALSE FALSE FALSE
## [822,] FALSE FALSE FALSE FALSE FALSE
## [823,] FALSE FALSE FALSE FALSE FALSE
## [824,] FALSE FALSE FALSE FALSE FALSE
## [825,] FALSE FALSE FALSE FALSE FALSE
## [826,] NA FALSE FALSE FALSE FALSE
## [827,] NA FALSE FALSE FALSE FALSE
## [828,] FALSE FALSE FALSE FALSE FALSE
## [829,] NA FALSE FALSE FALSE FALSE
## [830,] FALSE FALSE FALSE FALSE FALSE
## [831,] FALSE FALSE FALSE FALSE FALSE
## [832,] FALSE FALSE FALSE FALSE FALSE
## [833,] NA FALSE FALSE FALSE FALSE
## [834,] FALSE FALSE FALSE FALSE FALSE
## [835,] FALSE FALSE FALSE FALSE FALSE
## [836,] FALSE FALSE FALSE FALSE FALSE
## [837,] FALSE FALSE FALSE FALSE FALSE
## [838,] NA FALSE FALSE FALSE FALSE
## [839,] FALSE FALSE FALSE FALSE FALSE
## [840,] NA FALSE FALSE FALSE FALSE
## [841,] FALSE FALSE FALSE FALSE FALSE
## [842,] FALSE FALSE FALSE FALSE FALSE
## [843,] FALSE FALSE FALSE FALSE FALSE
## [844,] FALSE FALSE FALSE FALSE FALSE
## [845,] FALSE FALSE FALSE FALSE FALSE
## [846,] FALSE FALSE FALSE FALSE FALSE
## [847,] NA FALSE FALSE FALSE FALSE
## [848,] FALSE FALSE FALSE FALSE FALSE
## [849,] FALSE FALSE FALSE FALSE FALSE
## [850,] NA FALSE FALSE FALSE FALSE
## [851,] FALSE FALSE FALSE FALSE FALSE
## [852,] FALSE FALSE FALSE FALSE FALSE
## [853,] FALSE FALSE FALSE FALSE FALSE
## [854,] FALSE FALSE FALSE FALSE FALSE
## [855,] FALSE FALSE FALSE FALSE FALSE
## [856,] FALSE FALSE FALSE FALSE FALSE
## [857,] FALSE FALSE FALSE FALSE FALSE
## [858,] FALSE FALSE FALSE FALSE FALSE
## [859,] FALSE FALSE FALSE FALSE FALSE
## [860,] NA FALSE FALSE FALSE FALSE
## [861,] FALSE FALSE FALSE FALSE FALSE
## [862,] FALSE FALSE FALSE FALSE FALSE
## [863,] FALSE FALSE FALSE FALSE FALSE
## [864,] NA FALSE FALSE FALSE FALSE
## [865,] FALSE FALSE FALSE FALSE FALSE
## [866,] FALSE FALSE FALSE FALSE FALSE
## [867,] FALSE FALSE FALSE FALSE FALSE
## [868,] FALSE FALSE FALSE FALSE FALSE
## [869,] NA FALSE FALSE FALSE FALSE
## [870,] FALSE FALSE FALSE FALSE FALSE
## [871,] FALSE FALSE FALSE FALSE FALSE
## [872,] FALSE FALSE FALSE FALSE FALSE
## [873,] FALSE FALSE FALSE FALSE FALSE
## [874,] FALSE FALSE FALSE FALSE FALSE
## [875,] FALSE FALSE FALSE FALSE FALSE
## [876,] FALSE FALSE FALSE FALSE FALSE
## [877,] FALSE FALSE FALSE FALSE FALSE
## [878,] FALSE FALSE FALSE FALSE FALSE
## [879,] NA FALSE FALSE FALSE FALSE
## [880,] FALSE FALSE FALSE FALSE FALSE
## [881,] FALSE FALSE FALSE FALSE FALSE
## [882,] FALSE FALSE FALSE FALSE FALSE
## [883,] FALSE FALSE FALSE FALSE FALSE
## [884,] FALSE FALSE FALSE FALSE FALSE
## [885,] FALSE FALSE FALSE FALSE FALSE
## [886,] FALSE FALSE FALSE FALSE FALSE
## [887,] FALSE FALSE FALSE FALSE FALSE
## [888,] FALSE FALSE FALSE FALSE FALSE
## [889,] NA FALSE FALSE FALSE FALSE
## [890,] FALSE FALSE FALSE FALSE FALSE
## [891,] FALSE FALSE FALSE FALSE FALSEdataset## Age PassengerId Parch SibSp Survived
## 1 22.00 1 0 1 0
## 2 38.00 2 0 1 1
## 3 26.00 3 0 0 1
## 4 35.00 4 0 1 1
## 5 35.00 5 0 0 0
## 6 NA 6 0 0 0
## 7 54.00 7 0 0 0
## 8 2.00 8 1 3 0
## 9 27.00 9 2 0 1
## 10 14.00 10 0 1 1
## 11 4.00 11 1 1 1
## 12 58.00 12 0 0 1
## 13 20.00 13 0 0 0
## 14 39.00 14 5 1 0
## 15 14.00 15 0 0 0
## 16 55.00 16 0 0 1
## 17 2.00 17 1 4 0
## 18 NA 18 0 0 1
## 19 31.00 19 0 1 0
## 20 NA 20 0 0 1
## 21 35.00 21 0 0 0
## 22 34.00 22 0 0 1
## 23 15.00 23 0 0 1
## 24 28.00 24 0 0 1
## 25 8.00 25 1 3 0
## 26 38.00 26 5 1 1
## 27 NA 27 0 0 0
## 28 19.00 28 2 3 0
## 29 NA 29 0 0 1
## 30 NA 30 0 0 0
## 31 40.00 31 0 0 0
## 32 NA 32 0 1 1
## 33 NA 33 0 0 1
## 34 66.00 34 0 0 0
## 35 28.00 35 0 1 0
## 36 42.00 36 0 1 0
## 37 NA 37 0 0 1
## 38 21.00 38 0 0 0
## 39 18.00 39 0 2 0
## 40 14.00 40 0 1 1
## 41 40.00 41 0 1 0
## 42 27.00 42 0 1 0
## 43 NA 43 0 0 0
## 44 3.00 44 2 1 1
## 45 19.00 45 0 0 1
## 46 NA 46 0 0 0
## 47 NA 47 0 1 0
## 48 NA 48 0 0 1
## 49 NA 49 0 2 0
## 50 18.00 50 0 1 0
## 51 7.00 51 1 4 0
## 52 21.00 52 0 0 0
## 53 49.00 53 0 1 1
## 54 29.00 54 0 1 1
## 55 65.00 55 1 0 0
## 56 NA 56 0 0 1
## 57 21.00 57 0 0 1
## 58 28.50 58 0 0 0
## 59 5.00 59 2 1 1
## 60 11.00 60 2 5 0
## 61 22.00 61 0 0 0
## 62 38.00 62 0 0 1
## 63 45.00 63 0 1 0
## 64 4.00 64 2 3 0
## 65 NA 65 0 0 0
## 66 NA 66 1 1 1
## 67 29.00 67 0 0 1
## 68 19.00 68 0 0 0
## 69 17.00 69 2 4 1
## 70 26.00 70 0 2 0
## 71 32.00 71 0 0 0
## 72 16.00 72 2 5 0
## 73 21.00 73 0 0 0
## 74 26.00 74 0 1 0
## 75 32.00 75 0 0 1
## 76 25.00 76 0 0 0
## 77 NA 77 0 0 0
## 78 NA 78 0 0 0
## 79 0.83 79 2 0 1
## 80 30.00 80 0 0 1
## 81 22.00 81 0 0 0
## 82 29.00 82 0 0 1
## 83 NA 83 0 0 1
## 84 28.00 84 0 0 0
## 85 17.00 85 0 0 1
## 86 33.00 86 0 3 1
## 87 16.00 87 3 1 0
## 88 NA 88 0 0 0
## 89 23.00 89 2 3 1
## 90 24.00 90 0 0 0
## 91 29.00 91 0 0 0
## 92 20.00 92 0 0 0
## 93 46.00 93 0 1 0
## 94 26.00 94 2 1 0
## 95 59.00 95 0 0 0
## 96 NA 96 0 0 0
## 97 71.00 97 0 0 0
## 98 23.00 98 1 0 1
## 99 34.00 99 1 0 1
## 100 34.00 100 0 1 0
## 101 28.00 101 0 0 0
## 102 NA 102 0 0 0
## 103 21.00 103 1 0 0
## 104 33.00 104 0 0 0
## 105 37.00 105 0 2 0
## 106 28.00 106 0 0 0
## 107 21.00 107 0 0 1
## 108 NA 108 0 0 1
## 109 38.00 109 0 0 0
## 110 NA 110 0 1 1
## 111 47.00 111 0 0 0
## 112 14.50 112 0 1 0
## 113 22.00 113 0 0 0
## 114 20.00 114 0 1 0
## 115 17.00 115 0 0 0
## 116 21.00 116 0 0 0
## 117 70.50 117 0 0 0
## 118 29.00 118 0 1 0
## 119 24.00 119 1 0 0
## 120 2.00 120 2 4 0
## 121 21.00 121 0 2 0
## 122 NA 122 0 0 0
## 123 32.50 123 0 1 0
## 124 32.50 124 0 0 1
## 125 54.00 125 1 0 0
## 126 12.00 126 0 1 1
## 127 NA 127 0 0 0
## 128 24.00 128 0 0 1
## 129 NA 129 1 1 1
## 130 45.00 130 0 0 0
## 131 33.00 131 0 0 0
## 132 20.00 132 0 0 0
## 133 47.00 133 0 1 0
## 134 29.00 134 0 1 1
## 135 25.00 135 0 0 0
## 136 23.00 136 0 0 0
## 137 19.00 137 2 0 1
## 138 37.00 138 0 1 0
## 139 16.00 139 0 0 0
## 140 24.00 140 0 0 0
## 141 NA 141 2 0 0
## 142 22.00 142 0 0 1
## 143 24.00 143 0 1 1
## 144 19.00 144 0 0 0
## 145 18.00 145 0 0 0
## 146 19.00 146 1 1 0
## 147 27.00 147 0 0 1
## 148 9.00 148 2 2 0
## 149 36.50 149 2 0 0
## 150 42.00 150 0 0 0
## 151 51.00 151 0 0 0
## 152 22.00 152 0 1 1
## 153 55.50 153 0 0 0
## 154 40.50 154 2 0 0
## 155 NA 155 0 0 0
## 156 51.00 156 1 0 0
## 157 16.00 157 0 0 1
## 158 30.00 158 0 0 0
## 159 NA 159 0 0 0
## 160 NA 160 2 8 0
## 161 44.00 161 1 0 0
## 162 40.00 162 0 0 1
## 163 26.00 163 0 0 0
## 164 17.00 164 0 0 0
## 165 1.00 165 1 4 0
## 166 9.00 166 2 0 1
## 167 NA 167 1 0 1
## 168 45.00 168 4 1 0
## 169 NA 169 0 0 0
## 170 28.00 170 0 0 0
## 171 61.00 171 0 0 0
## 172 4.00 172 1 4 0
## 173 1.00 173 1 1 1
## 174 21.00 174 0 0 0
## 175 56.00 175 0 0 0
## 176 18.00 176 1 1 0
## 177 NA 177 1 3 0
## 178 50.00 178 0 0 0
## 179 30.00 179 0 0 0
## 180 36.00 180 0 0 0
## 181 NA 181 2 8 0
## 182 NA 182 0 0 0
## 183 9.00 183 2 4 0
## 184 1.00 184 1 2 1
## 185 4.00 185 2 0 1
## 186 NA 186 0 0 0
## 187 NA 187 0 1 1
## 188 45.00 188 0 0 1
## 189 40.00 189 1 1 0
## 190 36.00 190 0 0 0
## 191 32.00 191 0 0 1
## 192 19.00 192 0 0 0
## 193 19.00 193 0 1 1
## 194 3.00 194 1 1 1
## 195 44.00 195 0 0 1
## 196 58.00 196 0 0 1
## 197 NA 197 0 0 0
## 198 42.00 198 1 0 0
## 199 NA 199 0 0 1
## 200 24.00 200 0 0 0
## 201 28.00 201 0 0 0
## 202 NA 202 2 8 0
## 203 34.00 203 0 0 0
## 204 45.50 204 0 0 0
## 205 18.00 205 0 0 1
## 206 2.00 206 1 0 0
## 207 32.00 207 0 1 0
## 208 26.00 208 0 0 1
## 209 16.00 209 0 0 1
## 210 40.00 210 0 0 1
## 211 24.00 211 0 0 0
## 212 35.00 212 0 0 1
## 213 22.00 213 0 0 0
## 214 30.00 214 0 0 0
## 215 NA 215 0 1 0
## 216 31.00 216 0 1 1
## 217 27.00 217 0 0 1
## 218 42.00 218 0 1 0
## 219 32.00 219 0 0 1
## 220 30.00 220 0 0 0
## 221 16.00 221 0 0 1
## 222 27.00 222 0 0 0
## 223 51.00 223 0 0 0
## 224 NA 224 0 0 0
## 225 38.00 225 0 1 1
## 226 22.00 226 0 0 0
## 227 19.00 227 0 0 1
## 228 20.50 228 0 0 0
## 229 18.00 229 0 0 0
## 230 NA 230 1 3 0
## 231 35.00 231 0 1 1
## 232 29.00 232 0 0 0
## 233 59.00 233 0 0 0
## 234 5.00 234 2 4 1
## 235 24.00 235 0 0 0
## 236 NA 236 0 0 0
## 237 44.00 237 0 1 0
## 238 8.00 238 2 0 1
## 239 19.00 239 0 0 0
## 240 33.00 240 0 0 0
## 241 NA 241 0 1 0
## 242 NA 242 0 1 1
## 243 29.00 243 0 0 0
## 244 22.00 244 0 0 0
## 245 30.00 245 0 0 0
## 246 44.00 246 0 2 0
## 247 25.00 247 0 0 0
## 248 24.00 248 2 0 1
## 249 37.00 249 1 1 1
## 250 54.00 250 0 1 0
## 251 NA 251 0 0 0
## 252 29.00 252 1 1 0
## 253 62.00 253 0 0 0
## 254 30.00 254 0 1 0
## 255 41.00 255 2 0 0
## 256 29.00 256 2 0 1
## 257 NA 257 0 0 1
## 258 30.00 258 0 0 1
## 259 35.00 259 0 0 1
## 260 50.00 260 1 0 1
## 261 NA 261 0 0 0
## 262 3.00 262 2 4 1
## 263 52.00 263 1 1 0
## 264 40.00 264 0 0 0
## 265 NA 265 0 0 0
## 266 36.00 266 0 0 0
## 267 16.00 267 1 4 0
## 268 25.00 268 0 1 1
## 269 58.00 269 1 0 1
## 270 35.00 270 0 0 1
## 271 NA 271 0 0 0
## 272 25.00 272 0 0 1
## 273 41.00 273 1 0 1
## 274 37.00 274 1 0 0
## 275 NA 275 0 0 1
## 276 63.00 276 0 1 1
## 277 45.00 277 0 0 0
## 278 NA 278 0 0 0
## 279 7.00 279 1 4 0
## 280 35.00 280 1 1 1
## 281 65.00 281 0 0 0
## 282 28.00 282 0 0 0
## 283 16.00 283 0 0 0
## 284 19.00 284 0 0 1
## 285 NA 285 0 0 0
## 286 33.00 286 0 0 0
## 287 30.00 287 0 0 1
## 288 22.00 288 0 0 0
## 289 42.00 289 0 0 1
## 290 22.00 290 0 0 1
## 291 26.00 291 0 0 1
## 292 19.00 292 0 1 1
## 293 36.00 293 0 0 0
## 294 24.00 294 0 0 0
## 295 24.00 295 0 0 0
## 296 NA 296 0 0 0
## 297 23.50 297 0 0 0
## 298 2.00 298 2 1 0
## 299 NA 299 0 0 1
## 300 50.00 300 1 0 1
## 301 NA 301 0 0 1
## 302 NA 302 0 2 1
## 303 19.00 303 0 0 0
## 304 NA 304 0 0 1
## 305 NA 305 0 0 0
## 306 0.92 306 2 1 1
## 307 NA 307 0 0 1
## 308 17.00 308 0 1 1
## 309 30.00 309 0 1 0
## 310 30.00 310 0 0 1
## 311 24.00 311 0 0 1
## 312 18.00 312 2 2 1
## 313 26.00 313 1 1 0
## 314 28.00 314 0 0 0
## 315 43.00 315 1 1 0
## 316 26.00 316 0 0 1
## 317 24.00 317 0 1 1
## 318 54.00 318 0 0 0
## 319 31.00 319 2 0 1
## 320 40.00 320 1 1 1
## 321 22.00 321 0 0 0
## 322 27.00 322 0 0 0
## 323 30.00 323 0 0 1
## 324 22.00 324 1 1 1
## 325 NA 325 2 8 0
## 326 36.00 326 0 0 1
## 327 61.00 327 0 0 0
## 328 36.00 328 0 0 1
## 329 31.00 329 1 1 1
## 330 16.00 330 1 0 1
## 331 NA 331 0 2 1
## 332 45.50 332 0 0 0
## 333 38.00 333 1 0 0
## 334 16.00 334 0 2 0
## 335 NA 335 0 1 1
## 336 NA 336 0 0 0
## 337 29.00 337 0 1 0
## 338 41.00 338 0 0 1
## 339 45.00 339 0 0 1
## 340 45.00 340 0 0 0
## 341 2.00 341 1 1 1
## 342 24.00 342 2 3 1
## 343 28.00 343 0 0 0
## 344 25.00 344 0 0 0
## 345 36.00 345 0 0 0
## 346 24.00 346 0 0 1
## 347 40.00 347 0 0 1
## 348 NA 348 0 1 1
## 349 3.00 349 1 1 1
## 350 42.00 350 0 0 0
## 351 23.00 351 0 0 0
## 352 NA 352 0 0 0
## 353 15.00 353 1 1 0
## 354 25.00 354 0 1 0
## 355 NA 355 0 0 0
## 356 28.00 356 0 0 0
## 357 22.00 357 1 0 1
## 358 38.00 358 0 0 0
## 359 NA 359 0 0 1
## 360 NA 360 0 0 1
## 361 40.00 361 4 1 0
## 362 29.00 362 0 1 0
## 363 45.00 363 1 0 0
## 364 35.00 364 0 0 0
## 365 NA 365 0 1 0
## 366 30.00 366 0 0 0
## 367 60.00 367 0 1 1
## 368 NA 368 0 0 1
## 369 NA 369 0 0 1
## 370 24.00 370 0 0 1
## 371 25.00 371 0 1 1
## 372 18.00 372 0 1 0
## 373 19.00 373 0 0 0
## 374 22.00 374 0 0 0
## 375 3.00 375 1 3 0
## 376 NA 376 0 1 1
## 377 22.00 377 0 0 1
## 378 27.00 378 2 0 0
## 379 20.00 379 0 0 0
## 380 19.00 380 0 0 0
## 381 42.00 381 0 0 1
## 382 1.00 382 2 0 1
## 383 32.00 383 0 0 0
## 384 35.00 384 0 1 1
## 385 NA 385 0 0 0
## 386 18.00 386 0 0 0
## 387 1.00 387 2 5 0
## 388 36.00 388 0 0 1
## 389 NA 389 0 0 0
## 390 17.00 390 0 0 1
## 391 36.00 391 2 1 1
## 392 21.00 392 0 0 1
## 393 28.00 393 0 2 0
## 394 23.00 394 0 1 1
## 395 24.00 395 2 0 1
## 396 22.00 396 0 0 0
## 397 31.00 397 0 0 0
## 398 46.00 398 0 0 0
## 399 23.00 399 0 0 0
## 400 28.00 400 0 0 1
## 401 39.00 401 0 0 1
## 402 26.00 402 0 0 0
## 403 21.00 403 0 1 0
## 404 28.00 404 0 1 0
## 405 20.00 405 0 0 0
## 406 34.00 406 0 1 0
## 407 51.00 407 0 0 0
## 408 3.00 408 1 1 1
## 409 21.00 409 0 0 0
## 410 NA 410 1 3 0
## 411 NA 411 0 0 0
## 412 NA 412 0 0 0
## 413 33.00 413 0 1 1
## 414 NA 414 0 0 0
## 415 44.00 415 0 0 1
## 416 NA 416 0 0 0
## 417 34.00 417 1 1 1
## 418 18.00 418 2 0 1
## 419 30.00 419 0 0 0
## 420 10.00 420 2 0 0
## 421 NA 421 0 0 0
## 422 21.00 422 0 0 0
## 423 29.00 423 0 0 0
## 424 28.00 424 1 1 0
## 425 18.00 425 1 1 0
## 426 NA 426 0 0 0
## 427 28.00 427 0 1 1
## 428 19.00 428 0 0 1
## 429 NA 429 0 0 0
## 430 32.00 430 0 0 1
## 431 28.00 431 0 0 1
## 432 NA 432 0 1 1
## 433 42.00 433 0 1 1
## 434 17.00 434 0 0 0
## 435 50.00 435 0 1 0
## 436 14.00 436 2 1 1
## 437 21.00 437 2 2 0
## 438 24.00 438 3 2 1
## 439 64.00 439 4 1 0
## 440 31.00 440 0 0 0
## 441 45.00 441 1 1 1
## 442 20.00 442 0 0 0
## 443 25.00 443 0 1 0
## 444 28.00 444 0 0 1
## 445 NA 445 0 0 1
## 446 4.00 446 2 0 1
## 447 13.00 447 1 0 1
## 448 34.00 448 0 0 1
## 449 5.00 449 1 2 1
## 450 52.00 450 0 0 1
## 451 36.00 451 2 1 0
## 452 NA 452 0 1 0
## 453 30.00 453 0 0 0
## 454 49.00 454 0 1 1
## 455 NA 455 0 0 0
## 456 29.00 456 0 0 1
## 457 65.00 457 0 0 0
## 458 NA 458 0 1 1
## 459 50.00 459 0 0 1
## 460 NA 460 0 0 0
## 461 48.00 461 0 0 1
## 462 34.00 462 0 0 0
## 463 47.00 463 0 0 0
## 464 48.00 464 0 0 0
## 465 NA 465 0 0 0
## 466 38.00 466 0 0 0
## 467 NA 467 0 0 0
## 468 56.00 468 0 0 0
## 469 NA 469 0 0 0
## 470 0.75 470 1 2 1
## 471 NA 471 0 0 0
## 472 38.00 472 0 0 0
## 473 33.00 473 2 1 1
## 474 23.00 474 0 0 1
## 475 22.00 475 0 0 0
## 476 NA 476 0 0 0
## 477 34.00 477 0 1 0
## 478 29.00 478 0 1 0
## 479 22.00 479 0 0 0
## 480 2.00 480 1 0 1
## 481 9.00 481 2 5 0
## 482 NA 482 0 0 0
## 483 50.00 483 0 0 0
## 484 63.00 484 0 0 1
## 485 25.00 485 0 1 1
## 486 NA 486 1 3 0
## 487 35.00 487 0 1 1
## 488 58.00 488 0 0 0
## 489 30.00 489 0 0 0
## 490 9.00 490 1 1 1
## 491 NA 491 0 1 0
## 492 21.00 492 0 0 0
## 493 55.00 493 0 0 0
## 494 71.00 494 0 0 0
## 495 21.00 495 0 0 0
## 496 NA 496 0 0 0
## 497 54.00 497 0 1 1
## 498 NA 498 0 0 0
## 499 25.00 499 2 1 0
## 500 24.00 500 0 0 0
## 501 17.00 501 0 0 0
## 502 21.00 502 0 0 0
## 503 NA 503 0 0 0
## 504 37.00 504 0 0 0
## 505 16.00 505 0 0 1
## 506 18.00 506 0 1 0
## 507 33.00 507 2 0 1
## 508 NA 508 0 0 1
## 509 28.00 509 0 0 0
## 510 26.00 510 0 0 1
## 511 29.00 511 0 0 1
## 512 NA 512 0 0 0
## 513 36.00 513 0 0 1
## 514 54.00 514 0 1 1
## 515 24.00 515 0 0 0
## 516 47.00 516 0 0 0
## 517 34.00 517 0 0 1
## 518 NA 518 0 0 0
## 519 36.00 519 0 1 1
## 520 32.00 520 0 0 0
## 521 30.00 521 0 0 1
## 522 22.00 522 0 0 0
## 523 NA 523 0 0 0
## 524 44.00 524 1 0 1
## 525 NA 525 0 0 0
## 526 40.50 526 0 0 0
## 527 50.00 527 0 0 1
## 528 NA 528 0 0 0
## 529 39.00 529 0 0 0
## 530 23.00 530 1 2 0
## 531 2.00 531 1 1 1
## 532 NA 532 0 0 0
## 533 17.00 533 1 1 0
## 534 NA 534 2 0 1
## 535 30.00 535 0 0 0
## 536 7.00 536 2 0 1
## 537 45.00 537 0 0 0
## 538 30.00 538 0 0 1
## 539 NA 539 0 0 0
## 540 22.00 540 2 0 1
## 541 36.00 541 2 0 1
## 542 9.00 542 2 4 0
## 543 11.00 543 2 4 0
## 544 32.00 544 0 1 1
## 545 50.00 545 0 1 0
## 546 64.00 546 0 0 0
## 547 19.00 547 0 1 1
## 548 NA 548 0 0 1
## 549 33.00 549 1 1 0
## 550 8.00 550 1 1 1
## 551 17.00 551 2 0 1
## 552 27.00 552 0 0 0
## 553 NA 553 0 0 0
## 554 22.00 554 0 0 1
## 555 22.00 555 0 0 1
## 556 62.00 556 0 0 0
## 557 48.00 557 0 1 1
## 558 NA 558 0 0 0
## 559 39.00 559 1 1 1
## 560 36.00 560 0 1 1
## 561 NA 561 0 0 0
## 562 40.00 562 0 0 0
## 563 28.00 563 0 0 0
## 564 NA 564 0 0 0
## 565 NA 565 0 0 0
## 566 24.00 566 0 2 0
## 567 19.00 567 0 0 0
## 568 29.00 568 4 0 0
## 569 NA 569 0 0 0
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## 826 NA 826 0 0 0
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## 828 1.00 828 2 0 1
## 829 NA 829 0 0 1
## 830 62.00 830 0 0 1
## 831 15.00 831 0 1 1
## 832 0.83 832 1 1 1
## 833 NA 833 0 0 0
## 834 23.00 834 0 0 0
## 835 18.00 835 0 0 0
## 836 39.00 836 1 1 1
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## 840 NA 840 0 0 1
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## 843 30.00 843 0 0 1
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## 846 42.00 846 0 0 0
## 847 NA 847 2 8 0
## 848 35.00 848 0 0 0
## 849 28.00 849 1 0 0
## 850 NA 850 0 1 1
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## 852 74.00 852 0 0 0
## 853 9.00 853 1 1 0
## 854 16.00 854 1 0 1
## 855 44.00 855 0 1 0
## 856 18.00 856 1 0 1
## 857 45.00 857 1 1 1
## 858 51.00 858 0 0 1
## 859 24.00 859 3 0 1
## 860 NA 860 0 0 0
## 861 41.00 861 0 2 0
## 862 21.00 862 0 1 0
## 863 48.00 863 0 0 1
## 864 NA 864 2 8 0
## 865 24.00 865 0 0 0
## 866 42.00 866 0 0 1
## 867 27.00 867 0 1 1
## 868 31.00 868 0 0 0
## 869 NA 869 0 0 0
## 870 4.00 870 1 1 1
## 871 26.00 871 0 0 0
## 872 47.00 872 1 1 1
## 873 33.00 873 0 0 0
## 874 47.00 874 0 0 0
## 875 28.00 875 0 1 1
## 876 15.00 876 0 0 1
## 877 20.00 877 0 0 0
## 878 19.00 878 0 0 0
## 879 NA 879 0 0 0
## 880 56.00 880 1 0 1
## 881 25.00 881 1 0 1
## 882 33.00 882 0 0 0
## 883 22.00 883 0 0 0
## 884 28.00 884 0 0 0
## 885 25.00 885 0 0 0
## 886 39.00 886 5 0 0
## 887 27.00 887 0 0 0
## 888 19.00 888 0 0 1
## 889 NA 889 2 1 0
## 890 26.00 890 0 0 1
## 891 32.00 891 0 0 0Mengisi NaN
Pada analisis data sebelumnya, kita menemukan bahwa pada kolom age terdapat data missing. Untuk itu, sekarang kita akan mengganti data missing sehingga tidak ada lagi NaN pada kolom age.
dataset$Age = ifelse(is.na(dataset$Age),
ave(dataset$Age, FUN = function(x) mean(x, na.rm = TRUE)),
dataset$Age)
# Mengganti NaN pada kolom age dengan rata-rata nilai atau mean untuk kolom tersebut
# Sehingga proses penggantian nilai ini tidak memengaruhi kesimpulan analisis data secara keseluruhan
dataset## Age PassengerId Parch SibSp Survived
## 1 22.00000 1 0 1 0
## 2 38.00000 2 0 1 1
## 3 26.00000 3 0 0 1
## 4 35.00000 4 0 1 1
## 5 35.00000 5 0 0 0
## 6 29.69912 6 0 0 0
## 7 54.00000 7 0 0 0
## 8 2.00000 8 1 3 0
## 9 27.00000 9 2 0 1
## 10 14.00000 10 0 1 1
## 11 4.00000 11 1 1 1
## 12 58.00000 12 0 0 1
## 13 20.00000 13 0 0 0
## 14 39.00000 14 5 1 0
## 15 14.00000 15 0 0 0
## 16 55.00000 16 0 0 1
## 17 2.00000 17 1 4 0
## 18 29.69912 18 0 0 1
## 19 31.00000 19 0 1 0
## 20 29.69912 20 0 0 1
## 21 35.00000 21 0 0 0
## 22 34.00000 22 0 0 1
## 23 15.00000 23 0 0 1
## 24 28.00000 24 0 0 1
## 25 8.00000 25 1 3 0
## 26 38.00000 26 5 1 1
## 27 29.69912 27 0 0 0
## 28 19.00000 28 2 3 0
## 29 29.69912 29 0 0 1
## 30 29.69912 30 0 0 0
## 31 40.00000 31 0 0 0
## 32 29.69912 32 0 1 1
## 33 29.69912 33 0 0 1
## 34 66.00000 34 0 0 0
## 35 28.00000 35 0 1 0
## 36 42.00000 36 0 1 0
## 37 29.69912 37 0 0 1
## 38 21.00000 38 0 0 0
## 39 18.00000 39 0 2 0
## 40 14.00000 40 0 1 1
## 41 40.00000 41 0 1 0
## 42 27.00000 42 0 1 0
## 43 29.69912 43 0 0 0
## 44 3.00000 44 2 1 1
## 45 19.00000 45 0 0 1
## 46 29.69912 46 0 0 0
## 47 29.69912 47 0 1 0
## 48 29.69912 48 0 0 1
## 49 29.69912 49 0 2 0
## 50 18.00000 50 0 1 0
## 51 7.00000 51 1 4 0
## 52 21.00000 52 0 0 0
## 53 49.00000 53 0 1 1
## 54 29.00000 54 0 1 1
## 55 65.00000 55 1 0 0
## 56 29.69912 56 0 0 1
## 57 21.00000 57 0 0 1
## 58 28.50000 58 0 0 0
## 59 5.00000 59 2 1 1
## 60 11.00000 60 2 5 0
## 61 22.00000 61 0 0 0
## 62 38.00000 62 0 0 1
## 63 45.00000 63 0 1 0
## 64 4.00000 64 2 3 0
## 65 29.69912 65 0 0 0
## 66 29.69912 66 1 1 1
## 67 29.00000 67 0 0 1
## 68 19.00000 68 0 0 0
## 69 17.00000 69 2 4 1
## 70 26.00000 70 0 2 0
## 71 32.00000 71 0 0 0
## 72 16.00000 72 2 5 0
## 73 21.00000 73 0 0 0
## 74 26.00000 74 0 1 0
## 75 32.00000 75 0 0 1
## 76 25.00000 76 0 0 0
## 77 29.69912 77 0 0 0
## 78 29.69912 78 0 0 0
## 79 0.83000 79 2 0 1
## 80 30.00000 80 0 0 1
## 81 22.00000 81 0 0 0
## 82 29.00000 82 0 0 1
## 83 29.69912 83 0 0 1
## 84 28.00000 84 0 0 0
## 85 17.00000 85 0 0 1
## 86 33.00000 86 0 3 1
## 87 16.00000 87 3 1 0
## 88 29.69912 88 0 0 0
## 89 23.00000 89 2 3 1
## 90 24.00000 90 0 0 0
## 91 29.00000 91 0 0 0
## 92 20.00000 92 0 0 0
## 93 46.00000 93 0 1 0
## 94 26.00000 94 2 1 0
## 95 59.00000 95 0 0 0
## 96 29.69912 96 0 0 0
## 97 71.00000 97 0 0 0
## 98 23.00000 98 1 0 1
## 99 34.00000 99 1 0 1
## 100 34.00000 100 0 1 0
## 101 28.00000 101 0 0 0
## 102 29.69912 102 0 0 0
## 103 21.00000 103 1 0 0
## 104 33.00000 104 0 0 0
## 105 37.00000 105 0 2 0
## 106 28.00000 106 0 0 0
## 107 21.00000 107 0 0 1
## 108 29.69912 108 0 0 1
## 109 38.00000 109 0 0 0
## 110 29.69912 110 0 1 1
## 111 47.00000 111 0 0 0
## 112 14.50000 112 0 1 0
## 113 22.00000 113 0 0 0
## 114 20.00000 114 0 1 0
## 115 17.00000 115 0 0 0
## 116 21.00000 116 0 0 0
## 117 70.50000 117 0 0 0
## 118 29.00000 118 0 1 0
## 119 24.00000 119 1 0 0
## 120 2.00000 120 2 4 0
## 121 21.00000 121 0 2 0
## 122 29.69912 122 0 0 0
## 123 32.50000 123 0 1 0
## 124 32.50000 124 0 0 1
## 125 54.00000 125 1 0 0
## 126 12.00000 126 0 1 1
## 127 29.69912 127 0 0 0
## 128 24.00000 128 0 0 1
## 129 29.69912 129 1 1 1
## 130 45.00000 130 0 0 0
## 131 33.00000 131 0 0 0
## 132 20.00000 132 0 0 0
## 133 47.00000 133 0 1 0
## 134 29.00000 134 0 1 1
## 135 25.00000 135 0 0 0
## 136 23.00000 136 0 0 0
## 137 19.00000 137 2 0 1
## 138 37.00000 138 0 1 0
## 139 16.00000 139 0 0 0
## 140 24.00000 140 0 0 0
## 141 29.69912 141 2 0 0
## 142 22.00000 142 0 0 1
## 143 24.00000 143 0 1 1
## 144 19.00000 144 0 0 0
## 145 18.00000 145 0 0 0
## 146 19.00000 146 1 1 0
## 147 27.00000 147 0 0 1
## 148 9.00000 148 2 2 0
## 149 36.50000 149 2 0 0
## 150 42.00000 150 0 0 0
## 151 51.00000 151 0 0 0
## 152 22.00000 152 0 1 1
## 153 55.50000 153 0 0 0
## 154 40.50000 154 2 0 0
## 155 29.69912 155 0 0 0
## 156 51.00000 156 1 0 0
## 157 16.00000 157 0 0 1
## 158 30.00000 158 0 0 0
## 159 29.69912 159 0 0 0
## 160 29.69912 160 2 8 0
## 161 44.00000 161 1 0 0
## 162 40.00000 162 0 0 1
## 163 26.00000 163 0 0 0
## 164 17.00000 164 0 0 0
## 165 1.00000 165 1 4 0
## 166 9.00000 166 2 0 1
## 167 29.69912 167 1 0 1
## 168 45.00000 168 4 1 0
## 169 29.69912 169 0 0 0
## 170 28.00000 170 0 0 0
## 171 61.00000 171 0 0 0
## 172 4.00000 172 1 4 0
## 173 1.00000 173 1 1 1
## 174 21.00000 174 0 0 0
## 175 56.00000 175 0 0 0
## 176 18.00000 176 1 1 0
## 177 29.69912 177 1 3 0
## 178 50.00000 178 0 0 0
## 179 30.00000 179 0 0 0
## 180 36.00000 180 0 0 0
## 181 29.69912 181 2 8 0
## 182 29.69912 182 0 0 0
## 183 9.00000 183 2 4 0
## 184 1.00000 184 1 2 1
## 185 4.00000 185 2 0 1
## 186 29.69912 186 0 0 0
## 187 29.69912 187 0 1 1
## 188 45.00000 188 0 0 1
## 189 40.00000 189 1 1 0
## 190 36.00000 190 0 0 0
## 191 32.00000 191 0 0 1
## 192 19.00000 192 0 0 0
## 193 19.00000 193 0 1 1
## 194 3.00000 194 1 1 1
## 195 44.00000 195 0 0 1
## 196 58.00000 196 0 0 1
## 197 29.69912 197 0 0 0
## 198 42.00000 198 1 0 0
## 199 29.69912 199 0 0 1
## 200 24.00000 200 0 0 0
## 201 28.00000 201 0 0 0
## 202 29.69912 202 2 8 0
## 203 34.00000 203 0 0 0
## 204 45.50000 204 0 0 0
## 205 18.00000 205 0 0 1
## 206 2.00000 206 1 0 0
## 207 32.00000 207 0 1 0
## 208 26.00000 208 0 0 1
## 209 16.00000 209 0 0 1
## 210 40.00000 210 0 0 1
## 211 24.00000 211 0 0 0
## 212 35.00000 212 0 0 1
## 213 22.00000 213 0 0 0
## 214 30.00000 214 0 0 0
## 215 29.69912 215 0 1 0
## 216 31.00000 216 0 1 1
## 217 27.00000 217 0 0 1
## 218 42.00000 218 0 1 0
## 219 32.00000 219 0 0 1
## 220 30.00000 220 0 0 0
## 221 16.00000 221 0 0 1
## 222 27.00000 222 0 0 0
## 223 51.00000 223 0 0 0
## 224 29.69912 224 0 0 0
## 225 38.00000 225 0 1 1
## 226 22.00000 226 0 0 0
## 227 19.00000 227 0 0 1
## 228 20.50000 228 0 0 0
## 229 18.00000 229 0 0 0
## 230 29.69912 230 1 3 0
## 231 35.00000 231 0 1 1
## 232 29.00000 232 0 0 0
## 233 59.00000 233 0 0 0
## 234 5.00000 234 2 4 1
## 235 24.00000 235 0 0 0
## 236 29.69912 236 0 0 0
## 237 44.00000 237 0 1 0
## 238 8.00000 238 2 0 1
## 239 19.00000 239 0 0 0
## 240 33.00000 240 0 0 0
## 241 29.69912 241 0 1 0
## 242 29.69912 242 0 1 1
## 243 29.00000 243 0 0 0
## 244 22.00000 244 0 0 0
## 245 30.00000 245 0 0 0
## 246 44.00000 246 0 2 0
## 247 25.00000 247 0 0 0
## 248 24.00000 248 2 0 1
## 249 37.00000 249 1 1 1
## 250 54.00000 250 0 1 0
## 251 29.69912 251 0 0 0
## 252 29.00000 252 1 1 0
## 253 62.00000 253 0 0 0
## 254 30.00000 254 0 1 0
## 255 41.00000 255 2 0 0
## 256 29.00000 256 2 0 1
## 257 29.69912 257 0 0 1
## 258 30.00000 258 0 0 1
## 259 35.00000 259 0 0 1
## 260 50.00000 260 1 0 1
## 261 29.69912 261 0 0 0
## 262 3.00000 262 2 4 1
## 263 52.00000 263 1 1 0
## 264 40.00000 264 0 0 0
## 265 29.69912 265 0 0 0
## 266 36.00000 266 0 0 0
## 267 16.00000 267 1 4 0
## 268 25.00000 268 0 1 1
## 269 58.00000 269 1 0 1
## 270 35.00000 270 0 0 1
## 271 29.69912 271 0 0 0
## 272 25.00000 272 0 0 1
## 273 41.00000 273 1 0 1
## 274 37.00000 274 1 0 0
## 275 29.69912 275 0 0 1
## 276 63.00000 276 0 1 1
## 277 45.00000 277 0 0 0
## 278 29.69912 278 0 0 0
## 279 7.00000 279 1 4 0
## 280 35.00000 280 1 1 1
## 281 65.00000 281 0 0 0
## 282 28.00000 282 0 0 0
## 283 16.00000 283 0 0 0
## 284 19.00000 284 0 0 1
## 285 29.69912 285 0 0 0
## 286 33.00000 286 0 0 0
## 287 30.00000 287 0 0 1
## 288 22.00000 288 0 0 0
## 289 42.00000 289 0 0 1
## 290 22.00000 290 0 0 1
## 291 26.00000 291 0 0 1
## 292 19.00000 292 0 1 1
## 293 36.00000 293 0 0 0
## 294 24.00000 294 0 0 0
## 295 24.00000 295 0 0 0
## 296 29.69912 296 0 0 0
## 297 23.50000 297 0 0 0
## 298 2.00000 298 2 1 0
## 299 29.69912 299 0 0 1
## 300 50.00000 300 1 0 1
## 301 29.69912 301 0 0 1
## 302 29.69912 302 0 2 1
## 303 19.00000 303 0 0 0
## 304 29.69912 304 0 0 1
## 305 29.69912 305 0 0 0
## 306 0.92000 306 2 1 1
## 307 29.69912 307 0 0 1
## 308 17.00000 308 0 1 1
## 309 30.00000 309 0 1 0
## 310 30.00000 310 0 0 1
## 311 24.00000 311 0 0 1
## 312 18.00000 312 2 2 1
## 313 26.00000 313 1 1 0
## 314 28.00000 314 0 0 0
## 315 43.00000 315 1 1 0
## 316 26.00000 316 0 0 1
## 317 24.00000 317 0 1 1
## 318 54.00000 318 0 0 0
## 319 31.00000 319 2 0 1
## 320 40.00000 320 1 1 1
## 321 22.00000 321 0 0 0
## 322 27.00000 322 0 0 0
## 323 30.00000 323 0 0 1
## 324 22.00000 324 1 1 1
## 325 29.69912 325 2 8 0
## 326 36.00000 326 0 0 1
## 327 61.00000 327 0 0 0
## 328 36.00000 328 0 0 1
## 329 31.00000 329 1 1 1
## 330 16.00000 330 1 0 1
## 331 29.69912 331 0 2 1
## 332 45.50000 332 0 0 0
## 333 38.00000 333 1 0 0
## 334 16.00000 334 0 2 0
## 335 29.69912 335 0 1 1
## 336 29.69912 336 0 0 0
## 337 29.00000 337 0 1 0
## 338 41.00000 338 0 0 1
## 339 45.00000 339 0 0 1
## 340 45.00000 340 0 0 0
## 341 2.00000 341 1 1 1
## 342 24.00000 342 2 3 1
## 343 28.00000 343 0 0 0
## 344 25.00000 344 0 0 0
## 345 36.00000 345 0 0 0
## 346 24.00000 346 0 0 1
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## 348 29.69912 348 0 1 1
## 349 3.00000 349 1 1 1
## 350 42.00000 350 0 0 0
## 351 23.00000 351 0 0 0
## 352 29.69912 352 0 0 0
## 353 15.00000 353 1 1 0
## 354 25.00000 354 0 1 0
## 355 29.69912 355 0 0 0
## 356 28.00000 356 0 0 0
## 357 22.00000 357 1 0 1
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## 889 29.69912 889 2 1 0
## 890 26.00000 890 0 0 1
## 891 32.00000 891 0 0 0sum(is.na(dataset)) # Mengecek apakah masih ada missing data atau tidak## [1] 0Menghapus Outlier
Q = quantile(dataset$Age, probs = c(.25, .75), na.rm = FALSE) # Mencari kuartil ke-1(kuartil bawah) dan ke-3(kuartil atas) dari kolom age
IQR <- IQR(dataset$Age) # Mencari jangkauan interkuartil dari kolom age
Q # Menampilkan nilai kuartil ke-1 dan ke-3## 25% 75%
## 22 35IQR # Menampilkan nilai jangkauan interkuartil## [1] 13batas_atas <- Q[2] + 1.5*IQR
batas_bawah <- Q[1] - 1.5*IQR
dataset <- subset(dataset, dataset$Age > 22 & dataset$Age < 35) # Menghapus outlier pada kolom age
dataset## Age PassengerId Parch SibSp Survived
## 3 26.00000 3 0 0 1
## 6 29.69912 6 0 0 0
## 9 27.00000 9 2 0 1
## 18 29.69912 18 0 0 1
## 19 31.00000 19 0 1 0
## 20 29.69912 20 0 0 1
## 22 34.00000 22 0 0 1
## 24 28.00000 24 0 0 1
## 27 29.69912 27 0 0 0
## 29 29.69912 29 0 0 1
## 30 29.69912 30 0 0 0
## 32 29.69912 32 0 1 1
## 33 29.69912 33 0 0 1
## 35 28.00000 35 0 1 0
## 37 29.69912 37 0 0 1
## 42 27.00000 42 0 1 0
## 43 29.69912 43 0 0 0
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## 54 29.00000 54 0 1 1
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## 58 28.50000 58 0 0 0
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## 66 29.69912 66 1 1 1
## 67 29.00000 67 0 0 1
## 70 26.00000 70 0 2 0
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## 891 32.00000 891 0 0 0Q = quantile(dataset$Parch, probs = c(.25, .75), na.rm = FALSE) # Mencari kuartil ke-1(kuartil bawah) dan ke-3(kuartil atas) dari kolom parch
IQR <- IQR(dataset$Parch) # Mencari jangkauan interkuartil dari kolom parch
Q # Menampilkan nilai kuartil ke-1 dan ke-3## 25% 75%
## 0 0IQR # Menampilkan nilai jangkauan interkuartil## [1] 0batas_atas <- Q[2] + 1.5*IQR
batas_bawah <- Q[1] - 1.5*IQR
dataset <- subset(dataset, dataset$Parch > 0 & dataset$Parch < 0) # Menghapus outlier pada kolom parchQ = quantile(dataset$SibSp, probs = c(.25, .75), na.rm = FALSE) # Mencari kuartil ke-1(kuartil bawah) dan ke-3(kuartil atas) dari kolom SibSp
IQR <- IQR(dataset$SibSp) # Mencari jangkauan interkuartil dari kolom SibSp
Q # Menampilkan nilai kuartil ke-1 dan ke-3## 25% 75%
## NA NAIQR # Menampilkan nilai jangkauan interkuartil## [1] NAbatas_atas <- Q[2] + 1.5*IQR
batas_bawah <- Q[1] - 1.5*IQR
dataset <- subset(dataset, dataset$SibSp > 0 & dataset$SibSp < 1) # Menghapus outlier pada kolom SIbSpNormalisasi Data
normal_data <- distinct(dataset)Membagi data menjadi data training dan data testing
library(dplyr)
set.seed(123)
label <- sample(x = 2, size=(nrow(dataset)), replace= TRUE, prob=c(0.8,0.2)) # Membagi dataset menjadi dua bagian
train <- dataset[label == 1,]
test <- dataset[label == 2,]size <- floor(0.75 * nrow(dataset))
set.seed(123)
training <- sample(seq_len(nrow(dataset)), size = size)
trainingset <- dataset[training,]
testset <- dataset[-training,]