EDA Danych dotyczących Titanica¶

O Danych¶

Dane o pasażerach Titanica

Zbiór danych zawiera informacje o pasażerach RMS Titanic, który zatonął 15 kwietnia 1912 roku po zderzeniu z górą lodową. Dane obejmują takie atrybuty jak klasa podróży, wiek, płeć, liczba rodzeństwa/małżonków na pokładzie, liczba rodziców/dzieci na pokładzie, cena biletu oraz miejsce zaokrętowania.

Zbiór zawiera także informację o tym, czy pasażer przeżył katastrofę.

Titanic przewoził ponad 2,200 osób, z czego ponad 1,500 zginęło, co czyni tę katastrofę jedną z najbardziej tragicznych w historii morskiej.

Kolumny:

  • pclass - Klasa biletu
  • survived - Czy pasażer przeżył katastrofę
  • name - Imię i nazwisko pasażera
  • sex - Płeć pasażera
  • age - Wiek pasażera
  • sibsp - Liczba rodzeństwa/małżonków na pokładzie
  • parch - Liczba rodziców/dzieci na pokładzie
  • ticket - Numer biletu
  • fare - Cena biletu
  • cabin - Numer kabiny
  • embarked - Port, w którym pasażer wszedł na pokład (C = Cherbourg, Q = Queenstown, S = Southampton)
  • boat - Numer łodzi ratunkowej
  • body - Numer ciała (jeśli pasażer nie przeżył i ciało zostało odnalezione)
  • home.dest - Miejsce docelowe
pclass survived name sex age sibsp parch ticket fare cabin embarked boat body home.dest
0 1.0 1.0 Allen, Miss. Elisabeth Walton female 29.0000 0.0 0.0 24160 211.3375 B5 S 2 NaN St Louis, MO
1 1.0 1.0 Allison, Master. Hudson Trevor male 0.9167 1.0 2.0 113781 151.5500 C22 C26 S 11 NaN Montreal, PQ / Chesterville, ON
2 1.0 0.0 Allison, Miss. Helen Loraine female 2.0000 1.0 2.0 113781 151.5500 C22 C26 S NaN NaN Montreal, PQ / Chesterville, ON
3 1.0 0.0 Allison, Mr. Hudson Joshua Creighton male 30.0000 1.0 2.0 113781 151.5500 C22 C26 S NaN 135.0 Montreal, PQ / Chesterville, ON
4 1.0 0.0 Allison, Mrs. Hudson J C (Bessie Waldo Daniels) female 25.0000 1.0 2.0 113781 151.5500 C22 C26 S NaN NaN Montreal, PQ / Chesterville, ON
... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
1305 3.0 0.0 Zabour, Miss. Thamine female NaN 1.0 0.0 2665 14.4542 NaN C NaN NaN NaN
1306 3.0 0.0 Zakarian, Mr. Mapriededer male 26.5000 0.0 0.0 2656 7.2250 NaN C NaN 304.0 NaN
1307 3.0 0.0 Zakarian, Mr. Ortin male 27.0000 0.0 0.0 2670 7.2250 NaN C NaN NaN NaN
1308 3.0 0.0 Zimmerman, Mr. Leo male 29.0000 0.0 0.0 315082 7.8750 NaN S NaN NaN NaN
1309 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN

1310 rows × 14 columns

Podstawowe informacje o Data Frame Titanic¶

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1310 entries, 0 to 1309
Data columns (total 14 columns):
 #   Column     Non-Null Count  Dtype  
---  ------     --------------  -----  
 0   pclass     1309 non-null   float64
 1   survived   1309 non-null   float64
 2   name       1309 non-null   object 
 3   sex        1309 non-null   object 
 4   age        1046 non-null   float64
 5   sibsp      1309 non-null   float64
 6   parch      1309 non-null   float64
 7   ticket     1309 non-null   object 
 8   fare       1308 non-null   float64
 9   cabin      295 non-null    object 
 10  embarked   1307 non-null   object 
 11  boat       486 non-null    object 
 12  body       121 non-null    float64
 13  home.dest  745 non-null    object 
dtypes: float64(7), object(7)
memory usage: 143.4+ KB

pclass          1
survived        1
name            1
sex             1
age           264
sibsp           1
parch           1
ticket          1
fare            2
cabin        1015
embarked        3
boat          824
body         1189
home.dest     565
dtype: int64
pclass          3
survived        2
name         1307
sex             2
age            98
sibsp           7
parch           8
ticket        929
fare          281
cabin         186
embarked        3
boat           27
body          121
home.dest     369
dtype: int64
pclass survived age sibsp parch fare body
count 1309.000000 1309.000000 1046.000000 1309.000000 1309.000000 1308.000000 121.000000
mean 2.294882 0.381971 29.881135 0.498854 0.385027 33.295479 160.809917
std 0.837836 0.486055 14.413500 1.041658 0.865560 51.758668 97.696922
min 1.000000 0.000000 0.166700 0.000000 0.000000 0.000000 1.000000
25% 2.000000 0.000000 21.000000 0.000000 0.000000 7.895800 72.000000
50% 3.000000 0.000000 28.000000 0.000000 0.000000 14.454200 155.000000
75% 3.000000 1.000000 39.000000 1.000000 0.000000 31.275000 256.000000
max 3.000000 1.000000 80.000000 8.000000 9.000000 512.329200 328.000000
pclass survived name sex age sibsp parch ticket fare cabin embarked boat body home.dest
1191 3.0 0.0 Saundercock, Mr. William Henry male 20.0 0.0 0.0 A/5. 2151 8.0500 NaN S NaN NaN NaN
894 3.0 1.0 Johnson, Master. Harold Theodor male 4.0 1.0 1.0 347742 11.1333 NaN S 15 NaN NaN
749 3.0 0.0 Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria ... female 28.0 1.0 1.0 347080 14.4000 NaN S NaN NaN Stanton, IA
511 2.0 0.0 Myles, Mr. Thomas Francis male 62.0 0.0 0.0 240276 9.6875 NaN Q NaN NaN Cambridge, MA
168 1.0 1.0 Icard, Miss. Amelie female 38.0 0.0 0.0 113572 80.0000 B28 NaN 6 NaN NaN
811 3.0 0.0 Ford, Mrs. Edward (Margaret Ann Watson) female 48.0 1.0 3.0 W./C. 6608 34.3750 NaN S NaN NaN Rotherfield, Sussex, England Essex Co, MA
766 3.0 0.0 Delalic, Mr. Redjo male 25.0 0.0 0.0 349250 7.8958 NaN S NaN NaN NaN
198 1.0 1.0 Marvin, Mrs. Daniel Warner (Mary Graham Carmic... female 18.0 1.0 0.0 113773 53.1000 D30 S 10 NaN New York, NY
452 2.0 1.0 Hold, Mrs. Stephen (Annie Margaret Hill) female 29.0 1.0 0.0 26707 26.0000 NaN S 10 NaN England / Sacramento, CA
1254 3.0 1.0 Tornquist, Mr. William Henry male 25.0 0.0 0.0 LINE 0.0000 NaN S 15 NaN NaN
781 3.0 0.0 Drazenoic, Mr. Jozef male 33.0 0.0 0.0 349241 7.8958 NaN C NaN 51.0 Austria Niagara Falls, NY
797 3.0 0.0 Farrell, Mr. James male 40.5 0.0 0.0 367232 7.7500 NaN Q NaN 68.0 Aughnacliff, Co Longford, Ireland New York, NY
1110 3.0 0.0 Pavlovic, Mr. Stefo male 32.0 0.0 0.0 349242 7.8958 NaN S NaN NaN NaN
21 1.0 1.0 Beckwith, Mrs. Richard Leonard (Sallie Monypeny) female 47.0 1.0 1.0 11751 52.5542 D35 S 5 NaN New York, NY
418 2.0 0.0 Gilbert, Mr. William male 47.0 0.0 0.0 C.A. 30769 10.5000 NaN S NaN NaN Cornwall
24 1.0 1.0 Bird, Miss. Ellen female 29.0 0.0 0.0 PC 17483 221.7792 C97 S 8 NaN NaN
123 1.0 1.0 Frolicher-Stehli, Mr. Maxmillian male 60.0 1.0 1.0 13567 79.2000 B41 C 5 NaN Zurich, Switzerland
466 2.0 0.0 Kantor, Mr. Sinai male 34.0 1.0 0.0 244367 26.0000 NaN S NaN 283.0 Moscow / Bronx, NY
907 3.0 0.0 Jussila, Miss. Katriina female 20.0 1.0 0.0 4136 9.8250 NaN S NaN NaN NaN
1180 3.0 0.0 Sage, Mrs. John (Annie Bullen) female NaN 1.0 9.0 CA. 2343 69.5500 NaN S NaN NaN NaN
280 1.0 1.0 Stengel, Mr. Charles Emil Henry male 54.0 1.0 0.0 11778 55.4417 C116 C 1 NaN Newark, NJ
66 1.0 1.0 Chaudanson, Miss. Victorine female 36.0 0.0 0.0 PC 17608 262.3750 B61 C 4 NaN NaN
19 1.0 0.0 Beattie, Mr. Thomson male 36.0 0.0 0.0 13050 75.2417 C6 C A NaN Winnipeg, MN
527 2.0 0.0 Parker, Mr. Clifford Richard male 28.0 0.0 0.0 SC 14888 10.5000 NaN S NaN NaN St Andrews, Guernsey
403 2.0 0.0 Eitemiller, Mr. George Floyd male 23.0 0.0 0.0 29751 13.0000 NaN S NaN NaN England / Detroit, MI
pclass survived name sex age sibsp parch ticket fare cabin embarked boat body home.dest
0 1.0 1.0 Allen, Miss. Elisabeth Walton female 29.0000 0.0 0.0 24160 211.3375 B5 S 2 NaN St Louis, MO
1 1.0 1.0 Allison, Master. Hudson Trevor male 0.9167 1.0 2.0 113781 151.5500 C22 C26 S 11 NaN Montreal, PQ / Chesterville, ON
2 1.0 0.0 Allison, Miss. Helen Loraine female 2.0000 1.0 2.0 113781 151.5500 C22 C26 S NaN NaN Montreal, PQ / Chesterville, ON
3 1.0 0.0 Allison, Mr. Hudson Joshua Creighton male 30.0000 1.0 2.0 113781 151.5500 C22 C26 S NaN 135.0 Montreal, PQ / Chesterville, ON
4 1.0 0.0 Allison, Mrs. Hudson J C (Bessie Waldo Daniels) female 25.0000 1.0 2.0 113781 151.5500 C22 C26 S NaN NaN Montreal, PQ / Chesterville, ON
5 1.0 1.0 Anderson, Mr. Harry male 48.0000 0.0 0.0 19952 26.5500 E12 S 3 NaN New York, NY
6 1.0 1.0 Andrews, Miss. Kornelia Theodosia female 63.0000 1.0 0.0 13502 77.9583 D7 S 10 NaN Hudson, NY
7 1.0 0.0 Andrews, Mr. Thomas Jr male 39.0000 0.0 0.0 112050 0.0000 A36 S NaN NaN Belfast, NI
8 1.0 1.0 Appleton, Mrs. Edward Dale (Charlotte Lamson) female 53.0000 2.0 0.0 11769 51.4792 C101 S D NaN Bayside, Queens, NY
9 1.0 0.0 Artagaveytia, Mr. Ramon male 71.0000 0.0 0.0 PC 17609 49.5042 NaN C NaN 22.0 Montevideo, Uruguay
10 1.0 0.0 Astor, Col. John Jacob male 47.0000 1.0 0.0 PC 17757 227.5250 C62 C64 C NaN 124.0 New York, NY
11 1.0 1.0 Astor, Mrs. John Jacob (Madeleine Talmadge Force) female 18.0000 1.0 0.0 PC 17757 227.5250 C62 C64 C 4 NaN New York, NY
12 1.0 1.0 Aubart, Mme. Leontine Pauline female 24.0000 0.0 0.0 PC 17477 69.3000 B35 C 9 NaN Paris, France
13 1.0 1.0 Barber, Miss. Ellen "Nellie" female 26.0000 0.0 0.0 19877 78.8500 NaN S 6 NaN NaN
14 1.0 1.0 Barkworth, Mr. Algernon Henry Wilson male 80.0000 0.0 0.0 27042 30.0000 A23 S B NaN Hessle, Yorks
15 1.0 0.0 Baumann, Mr. John D male NaN 0.0 0.0 PC 17318 25.9250 NaN S NaN NaN New York, NY
16 1.0 0.0 Baxter, Mr. Quigg Edmond male 24.0000 0.0 1.0 PC 17558 247.5208 B58 B60 C NaN NaN Montreal, PQ
17 1.0 1.0 Baxter, Mrs. James (Helene DeLaudeniere Chaput) female 50.0000 0.0 1.0 PC 17558 247.5208 B58 B60 C 6 NaN Montreal, PQ
18 1.0 1.0 Bazzani, Miss. Albina female 32.0000 0.0 0.0 11813 76.2917 D15 C 8 NaN NaN
19 1.0 0.0 Beattie, Mr. Thomson male 36.0000 0.0 0.0 13050 75.2417 C6 C A NaN Winnipeg, MN
pclass survived name sex age sibsp parch ticket fare cabin embarked boat body home.dest
1285 3.0 0.0 Wenzel, Mr. Linhart male 32.5 0.0 0.0 345775 9.5000 NaN S NaN 298.0 NaN
1286 3.0 1.0 Whabee, Mrs. George Joseph (Shawneene Abi-Saab) female 38.0 0.0 0.0 2688 7.2292 NaN C C NaN NaN
1287 3.0 0.0 Widegren, Mr. Carl/Charles Peter male 51.0 0.0 0.0 347064 7.7500 NaN S NaN NaN NaN
1288 3.0 0.0 Wiklund, Mr. Jakob Alfred male 18.0 1.0 0.0 3101267 6.4958 NaN S NaN 314.0 NaN
1289 3.0 0.0 Wiklund, Mr. Karl Johan male 21.0 1.0 0.0 3101266 6.4958 NaN S NaN NaN NaN
1290 3.0 1.0 Wilkes, Mrs. James (Ellen Needs) female 47.0 1.0 0.0 363272 7.0000 NaN S NaN NaN NaN
1291 3.0 0.0 Willer, Mr. Aaron ("Abi Weller") male NaN 0.0 0.0 3410 8.7125 NaN S NaN NaN NaN
1292 3.0 0.0 Willey, Mr. Edward male NaN 0.0 0.0 S.O./P.P. 751 7.5500 NaN S NaN NaN NaN
1293 3.0 0.0 Williams, Mr. Howard Hugh "Harry" male NaN 0.0 0.0 A/5 2466 8.0500 NaN S NaN NaN NaN
1294 3.0 0.0 Williams, Mr. Leslie male 28.5 0.0 0.0 54636 16.1000 NaN S NaN 14.0 NaN
1295 3.0 0.0 Windelov, Mr. Einar male 21.0 0.0 0.0 SOTON/OQ 3101317 7.2500 NaN S NaN NaN NaN
1296 3.0 0.0 Wirz, Mr. Albert male 27.0 0.0 0.0 315154 8.6625 NaN S NaN 131.0 NaN
1297 3.0 0.0 Wiseman, Mr. Phillippe male NaN 0.0 0.0 A/4. 34244 7.2500 NaN S NaN NaN NaN
1298 3.0 0.0 Wittevrongel, Mr. Camille male 36.0 0.0 0.0 345771 9.5000 NaN S NaN NaN NaN
1299 3.0 0.0 Yasbeck, Mr. Antoni male 27.0 1.0 0.0 2659 14.4542 NaN C C NaN NaN
1300 3.0 1.0 Yasbeck, Mrs. Antoni (Selini Alexander) female 15.0 1.0 0.0 2659 14.4542 NaN C NaN NaN NaN
1301 3.0 0.0 Youseff, Mr. Gerious male 45.5 0.0 0.0 2628 7.2250 NaN C NaN 312.0 NaN
1302 3.0 0.0 Yousif, Mr. Wazli male NaN 0.0 0.0 2647 7.2250 NaN C NaN NaN NaN
1303 3.0 0.0 Yousseff, Mr. Gerious male NaN 0.0 0.0 2627 14.4583 NaN C NaN NaN NaN
1304 3.0 0.0 Zabour, Miss. Hileni female 14.5 1.0 0.0 2665 14.4542 NaN C NaN 328.0 NaN
1305 3.0 0.0 Zabour, Miss. Thamine female NaN 1.0 0.0 2665 14.4542 NaN C NaN NaN NaN
1306 3.0 0.0 Zakarian, Mr. Mapriededer male 26.5 0.0 0.0 2656 7.2250 NaN C NaN 304.0 NaN
1307 3.0 0.0 Zakarian, Mr. Ortin male 27.0 0.0 0.0 2670 7.2250 NaN C NaN NaN NaN
1308 3.0 0.0 Zimmerman, Mr. Leo male 29.0 0.0 0.0 315082 7.8750 NaN S NaN NaN NaN
1309 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN

Obserwacje¶

  1. Najwięcej brakujących elementów dateframe znajduje się w kolumnie body
  2. Najwięcej unikatowych wartości jest w Name, jest spowodowane połączeniem Imienia oraz nazwiska w jednej kolumnie
  3. Średni wiek na wszystkicj uczestników to 29,88 lat
  4. Ostatni rekord z dateframe nic nie wniesie do anilizy zostastanie usunięt na brak danych wkażdej kolumnie
  5. Średnia cena biletów bez uwzględnia rodzaju wykupionej klasy to 33,30

Analiza dataframe po różnych kryteriach¶

0.0    809
1.0    500
Name: survived, dtype: int64
male      843
female    466
Name: sex, dtype: int64

Obserwacje¶

  1. Z podanych danych na 1309 osób płynących Titanic'iem przeżyło 500 osób
  2. Mężczyzn było prawie 2x więcej
pclass survived age sibsp parch fare body
count 466.000000 466.000000 388.000000 466.000000 466.000000 466.000000 8.000000
mean 2.154506 0.727468 28.687071 0.652361 0.633047 46.198097 166.625000
std 0.866181 0.445741 14.576995 1.101009 1.049579 63.292599 138.110657
min 1.000000 0.000000 0.166700 0.000000 0.000000 6.750000 7.000000
25% 1.000000 0.000000 19.000000 0.000000 0.000000 10.504175 52.750000
50% 2.000000 1.000000 27.000000 0.000000 0.000000 23.000000 133.500000
75% 3.000000 1.000000 38.000000 1.000000 1.000000 55.331275 306.000000
max 3.000000 1.000000 76.000000 8.000000 9.000000 512.329200 328.000000

Obserwacje¶

  1. Średnia wieku paseżerek Titanic'a to 29 lat
  2. Najstarsza miała 76lat
  3. Cena bieletów dla wszytkich kobiet średnio wynosiła 46,20
  4. Standardowe odhylenie dla cen biletów jest znacznie wyższe niż średnia
pclass survived age sibsp parch fare body
count 843.000000 843.000000 658.000000 843.000000 843.000000 842.000000 113.000000
mean 2.372479 0.190985 30.585233 0.413998 0.247924 26.154601 160.398230
std 0.811908 0.393310 14.280571 0.997928 0.708938 42.486877 95.035289
min 1.000000 0.000000 0.333300 0.000000 0.000000 0.000000 1.000000
25% 2.000000 0.000000 21.000000 0.000000 0.000000 7.876050 79.000000
50% 3.000000 0.000000 28.000000 0.000000 0.000000 11.887500 155.000000
75% 3.000000 0.000000 39.000000 1.000000 0.000000 26.550000 255.000000
max 3.000000 1.000000 80.000000 8.000000 9.000000 512.329200 322.000000

Obserwacje¶

  1. Średnia wieku dla mężczyzn jest około 2 lata większa niż u kobiet
  2. Ceny biletów dla Panów były 20 tańsze
  3. Odchylenie standardowe dla ceny również jest większe tak jak u kobiet
  4. Najdroższe bilety były po 512,33
3.0    709
1.0    323
2.0    277
Name: pclass, dtype: int64

Obserwacje¶

  1. Najwięcej pasażerów było 3 klassy
pclass survived name sex age sibsp parch ticket fare cabin embarked boat body home.dest
0 1.0 1.0 Allen, Miss. Elisabeth Walton female 29.000000 0.0 0.0 24160 211.3375 B5 S 2 NaN St Louis, MO
1 1.0 1.0 Allison, Master. Hudson Trevor male 0.916700 1.0 2.0 113781 151.5500 C22 C26 S 11 NaN Montreal, PQ / Chesterville, ON
2 1.0 0.0 Allison, Miss. Helen Loraine female 2.000000 1.0 2.0 113781 151.5500 C22 C26 S NaN NaN Montreal, PQ / Chesterville, ON
3 1.0 0.0 Allison, Mr. Hudson Joshua Creighton male 30.000000 1.0 2.0 113781 151.5500 C22 C26 S NaN 135.0 Montreal, PQ / Chesterville, ON
4 1.0 0.0 Allison, Mrs. Hudson J C (Bessie Waldo Daniels) female 25.000000 1.0 2.0 113781 151.5500 C22 C26 S NaN NaN Montreal, PQ / Chesterville, ON
... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
1305 3.0 0.0 Zabour, Miss. Thamine female 29.881135 1.0 0.0 2665 14.4542 NaN C NaN NaN NaN
1306 3.0 0.0 Zakarian, Mr. Mapriededer male 26.500000 0.0 0.0 2656 7.2250 NaN C NaN 304.0 NaN
1307 3.0 0.0 Zakarian, Mr. Ortin male 27.000000 0.0 0.0 2670 7.2250 NaN C NaN NaN NaN
1308 3.0 0.0 Zimmerman, Mr. Leo male 29.000000 0.0 0.0 315082 7.8750 NaN S NaN NaN NaN
1309 NaN NaN NaN NaN 29.881135 NaN NaN NaN NaN NaN NaN NaN NaN NaN

1310 rows × 14 columns

0       False
1       False
2       False
3       False
4       False
        ...  
1305    False
1306    False
1307    False
1308    False
1309    False
Length: 1310, dtype: bool
pclass survived name sex age sibsp parch ticket fare cabin embarked boat body home.dest
1294 3.0 0.0 Williams, Mr. Leslie male 28.500000 0.0 0.0 54636 16.1000 NaN S NaN 14.0 NaN
1295 3.0 0.0 Windelov, Mr. Einar male 21.000000 0.0 0.0 SOTON/OQ 3101317 7.2500 NaN S NaN NaN NaN
1296 3.0 0.0 Wirz, Mr. Albert male 27.000000 0.0 0.0 315154 8.6625 NaN S NaN 131.0 NaN
1297 3.0 0.0 Wiseman, Mr. Phillippe male 29.881135 0.0 0.0 A/4. 34244 7.2500 NaN S NaN NaN NaN
1298 3.0 0.0 Wittevrongel, Mr. Camille male 36.000000 0.0 0.0 345771 9.5000 NaN S NaN NaN NaN
1299 3.0 0.0 Yasbeck, Mr. Antoni male 27.000000 1.0 0.0 2659 14.4542 NaN C C NaN NaN
1300 3.0 1.0 Yasbeck, Mrs. Antoni (Selini Alexander) female 15.000000 1.0 0.0 2659 14.4542 NaN C NaN NaN NaN
1301 3.0 0.0 Youseff, Mr. Gerious male 45.500000 0.0 0.0 2628 7.2250 NaN C NaN 312.0 NaN
1302 3.0 0.0 Yousif, Mr. Wazli male 29.881135 0.0 0.0 2647 7.2250 NaN C NaN NaN NaN
1303 3.0 0.0 Yousseff, Mr. Gerious male 29.881135 0.0 0.0 2627 14.4583 NaN C NaN NaN NaN
1304 3.0 0.0 Zabour, Miss. Hileni female 14.500000 1.0 0.0 2665 14.4542 NaN C NaN 328.0 NaN
1305 3.0 0.0 Zabour, Miss. Thamine female 29.881135 1.0 0.0 2665 14.4542 NaN C NaN NaN NaN
1306 3.0 0.0 Zakarian, Mr. Mapriededer male 26.500000 0.0 0.0 2656 7.2250 NaN C NaN 304.0 NaN
1307 3.0 0.0 Zakarian, Mr. Ortin male 27.000000 0.0 0.0 2670 7.2250 NaN C NaN NaN NaN
1308 3.0 0.0 Zimmerman, Mr. Leo male 29.000000 0.0 0.0 315082 7.8750 NaN S NaN NaN NaN
pclass survived age sibsp parch fare body
count 1309.000000 1309.000000 1309.000000 1309.000000 1309.000000 1308.000000 121.000000
mean 2.294882 0.381971 29.881135 0.498854 0.385027 33.295479 160.809917
std 0.837836 0.486055 12.883199 1.041658 0.865560 51.758668 97.696922
min 1.000000 0.000000 0.166700 0.000000 0.000000 0.000000 1.000000
25% 2.000000 0.000000 22.000000 0.000000 0.000000 7.895800 72.000000
50% 3.000000 0.000000 29.881135 0.000000 0.000000 14.454200 155.000000
75% 3.000000 1.000000 35.000000 1.000000 0.000000 31.275000 256.000000
max 3.000000 1.000000 80.000000 8.000000 9.000000 512.329200 328.000000
pclass survived age sibsp parch fare body
count 466.000000 466.000000 466.000000 466.000000 466.000000 466.000000 8.000000
mean 2.154506 0.727468 28.886935 0.652361 0.633047 46.198097 166.625000
std 0.866181 0.445741 13.305812 1.101009 1.049579 63.292599 138.110657
min 1.000000 0.000000 0.166700 0.000000 0.000000 6.750000 7.000000
25% 1.000000 0.000000 21.000000 0.000000 0.000000 10.504175 52.750000
50% 2.000000 1.000000 29.881135 0.000000 0.000000 23.000000 133.500000
75% 3.000000 1.000000 35.000000 1.000000 1.000000 55.331275 306.000000
max 3.000000 1.000000 76.000000 8.000000 9.000000 512.329200 328.000000
pclass survived age sibsp parch fare body
count 843.000000 843.000000 843.000000 843.000000 843.000000 842.000000 113.000000
mean 2.372479 0.190985 30.430716 0.413998 0.247924 26.154601 160.398230
std 0.811908 0.393310 12.617933 0.997928 0.708938 42.486877 95.035289
min 1.000000 0.000000 0.333300 0.000000 0.000000 0.000000 1.000000
25% 2.000000 0.000000 24.000000 0.000000 0.000000 7.876050 79.000000
50% 3.000000 0.000000 29.881135 0.000000 0.000000 11.887500 155.000000
75% 3.000000 0.000000 35.000000 1.000000 0.000000 26.550000 255.000000
max 3.000000 1.000000 80.000000 8.000000 9.000000 512.329200 322.000000

Obserwacje¶

  1. Po podstawieniu średniej zamiast brakujących wartości średnia u mężczyzn w wieku zmieniła się z 30.585233 na 30,430716
  2. Odchylenie standardowe spadło około 2 laTA
  3. U płuci pięknej średnia się zwiększyła o 0,2lata
<Axes: title={'center': 'Liczba osób podzielone na płucie'}, xlabel='Płucie', ylabel='Liczba osób'>
No description has been provided for this image

Obserwacje¶

  1. Na Tytanicu płynęło 2x więcej mężczyzn, niż kobiet
C:\Users\spaid\AppData\Local\Temp\ipykernel_19804\498816730.py:4: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.
  correlation_matrix = df2.corr()
No description has been provided for this image

Obserwacja¶

  1. Zewzględu dwukrotnie większą ilość mężczyzna zależności kolaracja nie zachodzi idealnie
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Obeserwacje¶

  1. Z powyższego wykresu więcej mężczyzn przyżyło zatonięcie Tytanica, pradopodobnie jest to spowodawane zasadami ilością ich na statku
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Obeserwacje¶

  1. Najwięcekj osób było w wieku z przedziału 24-32
  2. Na statku było bardzo mało osón powyżej 65 roku życia
  3. Na Tytanicu również płyneły dzieci w wieku od kliku tygodni życia do 18 roku
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Obserwacje¶

  1. Najwięcej przeżyło katastrofę Tytanica w wieku 30-36 lat
  2. Najwiękasz ilość osób które zgineła to osyby około 30lat
  3. Dzieci z przedziału 0-7 lat mają większą ilość śmierci
Text(0, 0.5, 'Wartości')
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Obserwacje¶

  1. Jak widać na wykres bardzo dużo odstających wartości może zniekształcić anilizę

Wnioski¶

  1. Na początku dateframe zawieram bardzo dużo brakujących danych co spowodowało spłycenie analizy i zniekształce ogólnej oceny
  2. Przyżywalność osób płynących na Tytanicu była zależna od wykupionej klasy oraz wieku Jest to spowodowane Hierachią społeczną, a następnie kolejnością ratowania (płeć, dzieci itd)
  3. Na Tytanicu przeżyło więcej mężczyzn, aczkowliek jest spowodowane znacznie większą ilością płynących osób płci męskiej