{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Zadanie domowe - EDA Danych dotyczących Titanica\n", "\n", "* Twoim zadaniem jest wykonanie analizy danych zawartych w załączonym pliku CSV (`26__titanic.csv`).\n", "* Plik znajduje się pod video. Pamiętaj, żeby wrzucić plik do tego samego folderu, w którym znajduje się ten notebook.\n", "* Wykorzystaj nowo nabytą wiedzę z biblioteki `Pandas`\n", "* Jeżeli jest taka konieczność posiłkuj się [code explainerem](https://codeexplainer.imprv.ai/) lub / i [data chatterem](https://datachatter.imprv.ai/) (który również te dane ma dostępne).\n", "* Prześlij na discordzie notebook z rozwiązaniem (`#modul-4-zad2`)\n", "* Pamiętaj:\n", "\n", "1. Nie spiesz się\n", "2. Potraktuj zadanie domowe jak prawdziwy projekt\n", "3. Dodawaj opisy, obserwacje, wnioski\n", "4. Dodaj wizualizacje\n", "5. Dodaj konkluzję i wnioski końcowe\n", "\n", "Powodzenia!!! I mega zabawy!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Dane o pasażerach Titanica\n", "\n", "Zbiór danych zawiera informacje o pasażerach RMS Titanic, który zatonął 15 kwietnia 1912 roku po zderzeniu z górą\n", "lodową. Dane obejmują takie atrybuty jak klasa podróży, wiek, płeć, liczba rodzeństwa/małżonków na pokładzie,\n", "liczba rodziców/dzieci na pokładzie, cena biletu oraz miejsce zaokrętowania.\n", "\n", "Zbiór zawiera także informację o tym, czy pasażer przeżył katastrofę.\n", "\n", "Titanic przewoził ponad 2,200 osób, z czego ponad 1,500 zginęło, co czyni tę katastrofę jedną z najbardziej\n", "tragicznych w historii morskiej.\n", "\n", "Kolumny:\n", "\n", "* **pclass** - Klasa biletu\n", "* **survived** - Czy pasażer przeżył katastrofę\n", "* **name** - Imię i nazwisko pasażera\n", "* **sex** - Płeć pasażera\n", "* **age** - Wiek pasażera\n", "* **sibsp** - Liczba ro## O Danych\n", "dzeństwa/małżonków na pokładzie\n", "* **parch** - Liczba rodziców/dzieci na pokładzie\n", "* **ticket** - Numer biletu\n", "* **fare** - Cena biletu\n", "* **cabin** - Numer kabiny\n", "* **embarked** - Port, w którym pasażer wszedł na pokład (C = Cherbourg, Q = Queenstown, S = Southampton)\n", "* **boat** - Numer łodzi ratunkowej\n", "* **body** - Numer ciała (jeśli pasażer nie przeżył i ciało zostało odnalezione)\n", "* **home.dest** - Miejsce docelowe" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1. Kształt ogólny danych" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Zbiór składa się z 1310 wierszy i 14 kolumn.\n" ] } ], "source": [ "import pandas as pd\n", "df = pd.read_csv('26__titanic.csv', sep = \",\")\n", "x, y = df.shape\n", "print(f\"Zbiór składa się z {x} wierszy i {y} kolumn.\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1.1. Badania zmiennych i transformacje zbioru danych" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 'name'" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
7253.01.0Connolly, Miss. Katefemale22.00.00.03703737.7500NaNQ13NaNIreland
7263.00.0Connolly, Miss. Katefemale30.00.00.03309727.6292NaNQNaNNaNIreland
9243.00.0Kelly, Mr. Jamesmale34.50.00.03309117.8292NaNQNaN70.0NaN
9253.00.0Kelly, Mr. Jamesmale44.00.00.03635928.0500NaNSNaNNaNNaN
\n", "
" ], "text/plain": [ " pclass survived name sex age sibsp parch \\\n", "725 3.0 1.0 Connolly, Miss. Kate female 22.0 0.0 0.0 \n", "726 3.0 0.0 Connolly, Miss. Kate female 30.0 0.0 0.0 \n", "924 3.0 0.0 Kelly, Mr. James male 34.5 0.0 0.0 \n", "925 3.0 0.0 Kelly, Mr. James male 44.0 0.0 0.0 \n", "\n", " ticket fare cabin embarked boat body home.dest \n", "725 370373 7.7500 NaN Q 13 NaN Ireland \n", "726 330972 7.6292 NaN Q NaN NaN Ireland \n", "924 330911 7.8292 NaN Q NaN 70.0 NaN \n", "925 363592 8.0500 NaN S NaN NaN NaN " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Wyświetlanie wierszy z duplikowanymi wartościami w kolumnie 'name'\n", "duplikaty_nazwisk = df[df.duplicated(subset=['name'], keep=False)]\n", "duplikaty_nazwisk" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- wiersze duplikują nazwiska. Usunięcie wierszy 726 i 925, bo najwiecej NaN. \n", "- Miss. przeżyła na łodzi. Ciało Mrs. odnaleziono." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
9243.00.0Kelly, Mr. Jamesmale34.50.00.03309117.8292NaNQNaN70.0NaN
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" ], "text/plain": [ " pclass survived name sex age sibsp parch ticket \\\n", "924 3.0 0.0 Kelly, Mr. James male 34.5 0.0 0.0 330911 \n", "\n", " fare cabin embarked boat body home.dest \n", "924 7.8292 NaN Q NaN 70.0 NaN " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# usunięcie wierszy 726 i 925\n", "df = df.drop([726,925])\n", "# sprawdzenie kontrolne\n", "nazwisko_Kelly = df[df['name'] == 'Kelly, Mr. James']\n", "nazwisko_Kelly" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Nie było całych wierszy zduplikowanych do usunięcia.\n" ] }, { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
01.01.0Allen, Miss. Elisabeth Waltonfemale29.00000.00.024160211.3375B5S2NaNSt Louis, MO
11.01.0Allison, Master. Hudson Trevormale0.91671.02.0113781151.5500C22 C26S11NaNMontreal, PQ / Chesterville, ON
21.00.0Allison, Miss. Helen Lorainefemale2.00001.02.0113781151.5500C22 C26SNaNNaNMontreal, PQ / Chesterville, ON
31.00.0Allison, Mr. Hudson Joshua Creightonmale30.00001.02.0113781151.5500C22 C26SNaN135.0Montreal, PQ / Chesterville, ON
41.00.0Allison, Mrs. Hudson J C (Bessie Waldo Daniels)female25.00001.02.0113781151.5500C22 C26SNaNNaNMontreal, PQ / Chesterville, ON
.............................................
13053.00.0Zabour, Miss. ThaminefemaleNaN1.00.0266514.4542NaNCNaNNaNNaN
13063.00.0Zakarian, Mr. Mapriededermale26.50000.00.026567.2250NaNCNaN304.0NaN
13073.00.0Zakarian, Mr. Ortinmale27.00000.00.026707.2250NaNCNaNNaNNaN
13083.00.0Zimmerman, Mr. Leomale29.00000.00.03150827.8750NaNSNaNNaNNaN
1309NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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1308 rows × 14 columns

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" ], "text/plain": [ " pclass survived name \\\n", "0 1.0 1.0 Allen, Miss. Elisabeth Walton \n", "1 1.0 1.0 Allison, Master. Hudson Trevor \n", "2 1.0 0.0 Allison, Miss. Helen Loraine \n", "3 1.0 0.0 Allison, Mr. Hudson Joshua Creighton \n", "4 1.0 0.0 Allison, Mrs. Hudson J C (Bessie Waldo Daniels) \n", "... ... ... ... \n", "1305 3.0 0.0 Zabour, Miss. Thamine \n", "1306 3.0 0.0 Zakarian, Mr. Mapriededer \n", "1307 3.0 0.0 Zakarian, Mr. Ortin \n", "1308 3.0 0.0 Zimmerman, Mr. Leo \n", "1309 NaN NaN NaN \n", "\n", " sex age sibsp parch ticket fare cabin embarked boat \\\n", "0 female 29.0000 0.0 0.0 24160 211.3375 B5 S 2 \n", "1 male 0.9167 1.0 2.0 113781 151.5500 C22 C26 S 11 \n", "2 female 2.0000 1.0 2.0 113781 151.5500 C22 C26 S NaN \n", "3 male 30.0000 1.0 2.0 113781 151.5500 C22 C26 S NaN \n", "4 female 25.0000 1.0 2.0 113781 151.5500 C22 C26 S NaN \n", "... ... ... ... ... ... ... ... ... ... \n", "1305 female NaN 1.0 0.0 2665 14.4542 NaN C NaN \n", "1306 male 26.5000 0.0 0.0 2656 7.2250 NaN C NaN \n", "1307 male 27.0000 0.0 0.0 2670 7.2250 NaN C NaN \n", "1308 male 29.0000 0.0 0.0 315082 7.8750 NaN S NaN \n", "1309 NaN NaN NaN NaN NaN NaN NaN NaN NaN \n", "\n", " body home.dest \n", "0 NaN St Louis, MO \n", "1 NaN Montreal, PQ / Chesterville, ON \n", "2 NaN Montreal, PQ / Chesterville, ON \n", "3 135.0 Montreal, PQ / Chesterville, ON \n", "4 NaN Montreal, PQ / Chesterville, ON \n", "... ... ... \n", "1305 NaN NaN \n", "1306 304.0 NaN \n", "1307 NaN NaN \n", "1308 NaN NaN \n", "1309 NaN NaN \n", "\n", "[1308 rows x 14 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Wyszukanie całych zduplikowanych wierszy i ich usunięcie (oryginalny df nie ulega zmianie)\n", "df2 = df.copy()\n", "df2 = df.drop_duplicates()\n", "# Liczba wierszy DF przed usunięciem duplikatów\n", "przed = len(df)\n", "# Liczba wierszy po usunięciu duplikatów\n", "po = len(df2)\n", "# Sprawdzenie, czy liczba wierszy się zmieniła\n", "if przed > po:\n", " print(\"Zduplikowane wiersze zostały usunięte.\")\n", "else:\n", " print(\"Nie było całych wierszy zduplikowanych do usunięcia.\")\n", "df2" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
01.01.0Allen, Miss. Elisabeth Waltonfemale29.00000.00.024160211.3375B5S2NaNSt Louis, MO
11.01.0Allison, Master. Hudson Trevormale0.91671.02.0113781151.5500C22 C26S11NaNMontreal, PQ / Chesterville, ON
21.00.0Allison, Miss. Helen Lorainefemale2.00001.02.0113781151.5500C22 C26SNaNNaNMontreal, PQ / Chesterville, ON
31.00.0Allison, Mr. Hudson Joshua Creightonmale30.00001.02.0113781151.5500C22 C26SNaN135.0Montreal, PQ / Chesterville, ON
41.00.0Allison, Mrs. Hudson J C (Bessie Waldo Daniels)female25.00001.02.0113781151.5500C22 C26SNaNNaNMontreal, PQ / Chesterville, ON
.............................................
13043.00.0Zabour, Miss. Hilenifemale14.50001.00.0266514.4542NaNCNaN328.0NaN
13053.00.0Zabour, Miss. ThaminefemaleNaN1.00.0266514.4542NaNCNaNNaNNaN
13063.00.0Zakarian, Mr. Mapriededermale26.50000.00.026567.2250NaNCNaN304.0NaN
13073.00.0Zakarian, Mr. Ortinmale27.00000.00.026707.2250NaNCNaNNaNNaN
13083.00.0Zimmerman, Mr. Leomale29.00000.00.03150827.8750NaNSNaNNaNNaN
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1307 rows × 14 columns

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" ], "text/plain": [ " pclass survived name \\\n", "0 1.0 1.0 Allen, Miss. Elisabeth Walton \n", "1 1.0 1.0 Allison, Master. Hudson Trevor \n", "2 1.0 0.0 Allison, Miss. Helen Loraine \n", "3 1.0 0.0 Allison, Mr. Hudson Joshua Creighton \n", "4 1.0 0.0 Allison, Mrs. Hudson J C (Bessie Waldo Daniels) \n", "... ... ... ... \n", "1304 3.0 0.0 Zabour, Miss. Hileni \n", "1305 3.0 0.0 Zabour, Miss. Thamine \n", "1306 3.0 0.0 Zakarian, Mr. Mapriededer \n", "1307 3.0 0.0 Zakarian, Mr. Ortin \n", "1308 3.0 0.0 Zimmerman, Mr. Leo \n", "\n", " sex age sibsp parch ticket fare cabin embarked boat \\\n", "0 female 29.0000 0.0 0.0 24160 211.3375 B5 S 2 \n", "1 male 0.9167 1.0 2.0 113781 151.5500 C22 C26 S 11 \n", "2 female 2.0000 1.0 2.0 113781 151.5500 C22 C26 S NaN \n", "3 male 30.0000 1.0 2.0 113781 151.5500 C22 C26 S NaN \n", "4 female 25.0000 1.0 2.0 113781 151.5500 C22 C26 S NaN \n", "... ... ... ... ... ... ... ... ... ... \n", "1304 female 14.5000 1.0 0.0 2665 14.4542 NaN C NaN \n", "1305 female NaN 1.0 0.0 2665 14.4542 NaN C NaN \n", "1306 male 26.5000 0.0 0.0 2656 7.2250 NaN C NaN \n", "1307 male 27.0000 0.0 0.0 2670 7.2250 NaN C NaN \n", "1308 male 29.0000 0.0 0.0 315082 7.8750 NaN S NaN \n", "\n", " body home.dest \n", "0 NaN St Louis, MO \n", "1 NaN Montreal, PQ / Chesterville, ON \n", "2 NaN Montreal, PQ / Chesterville, ON \n", "3 135.0 Montreal, PQ / Chesterville, ON \n", "4 NaN Montreal, PQ / Chesterville, ON \n", "... ... ... \n", "1304 328.0 NaN \n", "1305 NaN NaN \n", "1306 304.0 NaN \n", "1307 NaN NaN \n", "1308 NaN NaN \n", "\n", "[1307 rows x 14 columns]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# usunięcie ostatniego wiersza wartości NaN\n", "df = df.drop(1309)\n", "df" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Zbiór zawiera brakujące wartości:\n", "pclass 0\n", "survived 0\n", "name 0\n", "sex 0\n", "age 263\n", "sibsp 0\n", "parch 0\n", "ticket 0\n", "fare 1\n", "cabin 1012\n", "embarked 2\n", "boat 821\n", "body 1186\n", "home.dest 563\n", "dtype: int64\n" ] } ], "source": [ "# ile wartości brakuje w każdej kolumnie?\n", "liczba_brakow = df.isna().sum()\n", "zdanie = (f\"Zbiór zawiera brakujące wartości:\\n{liczba_brakow}\")\n", "print(zdanie)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.20122417750573834" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Procent brakujacych wartosci do wszystkich w kalumnie 'age'\n", "sumaBrakow = df['age'].isna().sum()\n", "liczbaElementow = len(df['age'])\n", "czescProcentowa = sumaBrakow / liczbaElementow\n", "czescProcentowa" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Procentowy udział NaN: \n", "pclass 0%\n", "survived 0%\n", "name 0%\n", "sex 0%\n", "age 20%\n", "sibsp 0%\n", "parch 0%\n", "ticket 0%\n", "fare 0%\n", "cabin 77%\n", "embarked 0%\n", "boat 63%\n", "body 91%\n", "home.dest 43%\n", "dtype: object.\n", "\n" ] } ], "source": [ "# ile wartości brakuje w każdej kolumnie procentowo?\n", "# Średnia True i dodanie znaku % (2f = sformatowane do dwóch miejsc po przecinku)\n", "braki_srednia_logiczna = df.isna().mean() * 100\n", "braki_procent = braki_srednia_logiczna.apply(lambda x: f'{x:.0f}%')\n", "print(f'Procentowy udział NaN: \\n{braki_procent}.\\n')" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "pclass float64\n", "survived float64\n", "name object\n", "sex object\n", "age float64\n", "sibsp float64\n", "parch float64\n", "ticket object\n", "fare float64\n", "cabin object\n", "embarked object\n", "boat object\n", "body float64\n", "home.dest object\n", "dtype: object\n" ] } ], "source": [ "# Typy kolumn\n", "print(df.dtypes)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 'sex'" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Ilosc kobiet w kolumnie sex:\n", "465\n", "Liczba mężczyzn: 842\n", "suma powyższa liczb kobiet i mężczyzn 1307\n", "liczba wszystkich elementow w kolumnie sex: 1307\n" ] } ], "source": [ "# mapowanie object na numeryczne\n", "df['sex'] = df['sex'].replace({'male': 0, 'female': 1})\n", "\n", "# sprawdzenie kontrolne\n", "liczbaKobiet = df['sex'].sum()\n", "print(f'Ilosc kobiet w kolumnie sex:\\n{liczbaKobiet}')\n", "\n", "liczbaMezczyzn = (df['sex'] == 0).sum()\n", "print(\"Liczba mężczyzn:\", liczbaMezczyzn)\n", "\n", "# suma\n", "s = liczbaKobiet + liczbaMezczyzn\n", "print(\"suma powyższa liczb kobiet i mężczyzn\", s)\n", "\n", "#\n", "liczbaElementowSex = len(df['sex'])\n", "print(\"liczba wszystkich elementow w kolumnie sex:\", liczbaElementowSex)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Liczba wierszy bez Mr.: 85\n" ] } ], "source": [ "# licz wiersze, gdzie kolumna 'name' nie zawiera \"Mr.\" ale kolumna 'sex' wynosi 0.\n", "ZeroAleNieMr = df[(df['sex'] == 0) & ~df['name'].str.contains('Mr.', na=False)]\n", "a = len(ZeroAleNieMr)\n", "print(\"Liczba wierszy bez Mr.:\", a)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 'cabin'" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "C23 C25 C27 6\n", "G6 5\n", "B57 B59 B63 B66 5\n", "F4 4\n", "F33 4\n", " ..\n", "C132 1\n", "E60 1\n", "B52 B54 B56 1\n", "C49 1\n", "F38 1\n", "Name: cabin, Length: 186, dtype: int64" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Wylistowanie wartości\n", "ilosc = df['cabin'].value_counts()\n", "ilosc" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski: \n", "- Zastanawia to dlaczego cabina ma wartość 'C23 C25 C27'? Czy jest w tym jakiś sens?" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['A10', 'A11', 'A14', 'A16', 'A18', 'A19', 'A20', 'A21', 'A23', 'A24', 'A26', 'A29', 'A31', 'A32', 'A34', 'A36', 'A5', 'A6', 'A7', 'A9', 'B10', 'B101', 'B102', 'B11', 'B18', 'B19', 'B20', 'B22', 'B24', 'B26', 'B28', 'B3', 'B30', 'B35', 'B36', 'B37', 'B38', 'B39', 'B4', 'B41', 'B42', 'B45', 'B49', 'B5', 'B50', 'B51 B53 B55', 'B52 B54 B56', 'B57 B59 B63 B66', 'B58 B60', 'B61', 'B69', 'B71', 'B73', 'B77', 'B78', 'B79', 'B80', 'B82 B84', 'B86', 'B94', 'B96 B98', 'C101', 'C103', 'C104', 'C105', 'C106', 'C110', 'C111', 'C116', 'C118', 'C123', 'C124', 'C125', 'C126', 'C128', 'C130', 'C132', 'C148', 'C2', 'C22 C26', 'C23 C25 C27', 'C28', 'C30', 'C31', 'C32', 'C39', 'C45', 'C46', 'C47', 'C49', 'C50', 'C51', 'C52', 'C53', 'C54', 'C55 C57', 'C6', 'C62 C64', 'C65', 'C68', 'C7', 'C70', 'C78', 'C80', 'C82', 'C83', 'C85', 'C86', 'C87', 'C89', 'C90', 'C91', 'C92', 'C93', 'C95', 'C97', 'C99', 'D', 'D10 D12', 'D11', 'D15', 'D17', 'D19', 'D20', 'D21', 'D22', 'D26', 'D28', 'D30', 'D33', 'D34', 'D35', 'D36', 'D37', 'D38', 'D40', 'D43', 'D45', 'D46', 'D47', 'D48', 'D49', 'D50', 'D56', 'D6', 'D7', 'D9', 'E10', 'E101', 'E12', 'E121', 'E17', 'E24', 'E25', 'E31', 'E33', 'E34', 'E36', 'E38', 'E39 E41', 'E40', 'E44', 'E45', 'E46', 'E49', 'E50', 'E52', 'E58', 'E60', 'E63', 'E67', 'E68', 'E77', 'E8', 'F', 'F E46', 'F E57', 'F E69', 'F G63', 'F G73', 'F2', 'F33', 'F38', 'F4', 'G6', 'T', 'nan']\n" ] } ], "source": [ "# wylistowanie wszystkich wartosci w celu sprawdzenia błędów, powtarzających się ciągów znaków.\n", "lista_cabin = df['cabin'].unique()\n", "# Posortowanie wartości w porządku alfabetycznym pozwoli na usunięcie błędów. Ale sorted() nie może mieć NaN.\n", "df['cabin'] = df['cabin'].fillna('Unknown')\n", "lista_cabin_sorted = sorted([str(item) for item in lista_cabin])\n", "print(lista_cabin_sorted)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- Jest 10 wartości z numerami wielu kabin np.: 'B51 B53 B55' lub 'B57 B59 B63 B66' itd, które można skrócić." ] }, { "cell_type": "raw", "metadata": {}, "source": [ "zastap_cabin = {\n", " 'B51 B53 B55':'B51',\n", " 'B52 B54 B56':'B52',\n", " 'B57 B59 B63 B66':'B57',\n", " 'B58 B60':'B58',\n", " 'B82 B84':'B82',\n", " 'C22 C26':'C22',\n", " 'C23 C25 C27':'C23',\n", " 'C55 C57':'C55',\n", " 'C62 C64':'C62',\n", " 'D10 D12':'D10'\n", "}\n", "df['cabin'] = df['cabin'].replace(zastap_cabin)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 'sibsp' i 'parch'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "- Kluczem jest kodowanie: \n", "- sibsp - Liczba rodzeństwa/małżonków na pokładzie, parch - Liczba rodziców/dzieci na pokładzie.\n", "- Zobaczmy kto był w kabinach " ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.0 889\n", "1.0 319\n", "2.0 42\n", "4.0 22\n", "3.0 20\n", "8.0 9\n", "5.0 6\n", "Name: sibsp, dtype: int64\n" ] } ], "source": [ "kolumna = 'sibsp'\n", "liczba_wystepowania_sibsp = df[kolumna].value_counts()\n", "print(liczba_wystepowania_sibsp)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
491.01.0Cardeza, Mr. Thomas Drake Martinez036.00.01.0PC 17755512.3292B51 B53 B55C3NaNAustria-Hungary / Germantown, Philadelphia, PA
501.01.0Cardeza, Mrs. James Warburton Martinez (Charlo...158.00.01.0PC 17755512.3292B51 B53 B55C3NaNGermantown, Philadelphia, PA
511.00.0Carlsson, Mr. Frans Olof033.00.00.06955.0000B51 B53 B55SNaNNaNNew York, NY
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" ], "text/plain": [ " pclass survived name sex \\\n", "49 1.0 1.0 Cardeza, Mr. Thomas Drake Martinez 0 \n", "50 1.0 1.0 Cardeza, Mrs. James Warburton Martinez (Charlo... 1 \n", "51 1.0 0.0 Carlsson, Mr. Frans Olof 0 \n", "\n", " age sibsp parch ticket fare cabin embarked boat body \\\n", "49 36.0 0.0 1.0 PC 17755 512.3292 B51 B53 B55 C 3 NaN \n", "50 58.0 0.0 1.0 PC 17755 512.3292 B51 B53 B55 C 3 NaN \n", "51 33.0 0.0 0.0 695 5.0000 B51 B53 B55 S NaN NaN \n", "\n", " home.dest \n", "49 Austria-Hungary / Germantown, Philadelphia, PA \n", "50 Germantown, Philadelphia, PA \n", "51 New York, NY " ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Przykładowo co zawierają kolumny, dla cabin==B51'\n", "wybrana_cabin = df[df['cabin'].str.contains('B51')]\n", "# Wyświetlenie wartości w innych kolumnach dla wybranej kabiny\n", "wybrana_cabin" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### wnioski: \n", "- 3 osoby wykupiły 3 kabiny.\n", "- Cardeza, Mr. Thomas (age 36) płynął bez rodzeństwa i z jednym rodzicem, bo sibsp Liczba rodzeństwa/- na pokładzie 0, parch Liczba rodziców/- na pokładzie 1\n", "- Cardeza, Mrs. James (age 58) płynęła z jednym dzieckiem, bo ibsp Liczba rodzeństwa/małżonków na pokładzie 0, parch Liczba -/dzieci na pokładzie 1\n", "- Carlsson, Mr. Frans Olof (age 33) podróżował bez rodzeństwa i bez rodziców, bo sibsp - Liczba rodzeństwa/małżonków na pokładzie 0, parch - Liczba rodziców/dzieci na pokładzie = 0\n", "- Panowie byli pewnie przyjaciółmi. Ten ostatni płacił śmieszne pieniądze za bilet w 1. klasie." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
1701.01.0Ismay, Mr. Joseph Bruce049.00.00.01120580.0B52 B54 B56SCNaNLiverpool
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" ], "text/plain": [ " pclass survived name sex age sibsp parch \\\n", "170 1.0 1.0 Ismay, Mr. Joseph Bruce 0 49.0 0.0 0.0 \n", "\n", " ticket fare cabin embarked boat body home.dest \n", "170 112058 0.0 B52 B54 B56 S C NaN Liverpool " ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Przykładowo co zawierają kolumny, dla cabin==B52'\n", "wybrana_cabin = df[df['cabin'].str.contains('B52', na=False)]\n", "# Wyświetlenie wartości w innych kolumnach dla wybranej kabiny\n", "wybrana_cabin" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- Z kolei tutaj jedna osoba zajmowałaby kilka kabin?! I zapłacił 0 $ !!" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
2491.01.0Ryerson, Master. John Borie013.02.02.0PC 17608262.375B57 B59 B63 B66C4NaNHaverford, PA / Cooperstown, NY
2501.01.0Ryerson, Miss. Emily Borie118.02.02.0PC 17608262.375B57 B59 B63 B66C4NaNHaverford, PA / Cooperstown, NY
2511.01.0Ryerson, Miss. Susan Parker \"Suzette\"121.02.02.0PC 17608262.375B57 B59 B63 B66C4NaNHaverford, PA / Cooperstown, NY
2521.00.0Ryerson, Mr. Arthur Larned061.01.03.0PC 17608262.375B57 B59 B63 B66CNaNNaNHaverford, PA / Cooperstown, NY
2531.01.0Ryerson, Mrs. Arthur Larned (Emily Maria Borie)148.01.03.0PC 17608262.375B57 B59 B63 B66C4NaNHaverford, PA / Cooperstown, NY
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" ], "text/plain": [ " pclass survived name sex \\\n", "249 1.0 1.0 Ryerson, Master. John Borie 0 \n", "250 1.0 1.0 Ryerson, Miss. Emily Borie 1 \n", "251 1.0 1.0 Ryerson, Miss. Susan Parker \"Suzette\" 1 \n", "252 1.0 0.0 Ryerson, Mr. Arthur Larned 0 \n", "253 1.0 1.0 Ryerson, Mrs. Arthur Larned (Emily Maria Borie) 1 \n", "\n", " age sibsp parch ticket fare cabin embarked boat \\\n", "249 13.0 2.0 2.0 PC 17608 262.375 B57 B59 B63 B66 C 4 \n", "250 18.0 2.0 2.0 PC 17608 262.375 B57 B59 B63 B66 C 4 \n", "251 21.0 2.0 2.0 PC 17608 262.375 B57 B59 B63 B66 C 4 \n", "252 61.0 1.0 3.0 PC 17608 262.375 B57 B59 B63 B66 C NaN \n", "253 48.0 1.0 3.0 PC 17608 262.375 B57 B59 B63 B66 C 4 \n", "\n", " body home.dest \n", "249 NaN Haverford, PA / Cooperstown, NY \n", "250 NaN Haverford, PA / Cooperstown, NY \n", "251 NaN Haverford, PA / Cooperstown, NY \n", "252 NaN Haverford, PA / Cooperstown, NY \n", "253 NaN Haverford, PA / Cooperstown, NY " ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Przykładowo co zawierają kolumny, dla cabin==B57'\n", "wybrana_cabin = df[df['cabin'].str.contains('B57')]\n", "# Wyświetlenie wartości w innych kolumnach dla wybranej kabiny\n", "wybrana_cabin" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- 5 osobowa rodzina zamówiła aż 4 kabiny.\n", "- Dla dzieci: Liczba rodzeństwa/- na pokładzie 2. Liczba rodziców/- na pokładzie 2.\n", "- Dla rodziców: Liczba -/małżonków na pokładzie 1. Liczba -/dzieci na pokładzie 3 " ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
161.00.0Baxter, Mr. Quigg Edmond024.00.01.0PC 17558247.5208B58 B60CNaNNaNMontreal, PQ
171.01.0Baxter, Mrs. James (Helene DeLaudeniere Chaput)150.00.01.0PC 17558247.5208B58 B60C6NaNMontreal, PQ
971.01.0Douglas, Mrs. Frederick Charles (Mary Helene B...127.01.01.0PC 17558247.5208B58 B60C6NaNMontreal, PQ
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" ], "text/plain": [ " pclass survived name sex \\\n", "16 1.0 0.0 Baxter, Mr. Quigg Edmond 0 \n", "17 1.0 1.0 Baxter, Mrs. James (Helene DeLaudeniere Chaput) 1 \n", "97 1.0 1.0 Douglas, Mrs. Frederick Charles (Mary Helene B... 1 \n", "\n", " age sibsp parch ticket fare cabin embarked boat body \\\n", "16 24.0 0.0 1.0 PC 17558 247.5208 B58 B60 C NaN NaN \n", "17 50.0 0.0 1.0 PC 17558 247.5208 B58 B60 C 6 NaN \n", "97 27.0 1.0 1.0 PC 17558 247.5208 B58 B60 C 6 NaN \n", "\n", " home.dest \n", "16 Montreal, PQ \n", "17 Montreal, PQ \n", "97 Montreal, PQ " ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Przykładowo co zawierają kolumny, dla cabin==B58'\n", "wybrana_cabin = df[df['cabin'].str.contains('B58', na=False)]\n", "# Wyświetlenie wartości w innych kolumnach dla wybranej kabiny\n", "wybrana_cabin" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['Baxter, Mr. Quigg Edmond', 'Baxter, Mrs. James (Helene DeLaudeniere Chaput)', 'Douglas, Mrs. Frederick Charles (Mary Helene Baxter)']\n" ] } ], "source": [ "# wypisz pełne nazwiska dla cabin==B58'\n", "name_cabin58 = df[df['cabin'] == 'B58 B60']['name'].tolist()\n", "print(name_cabin58)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- 2 kabiny zajmowały 3 osoby: \n", "- Pan Mr. age 24. Liczba rodzeństwa/małżonków na pokładzie 0. Liczba rodziców/ - na pokładzie 1. Jest synem Mrs. age 50.\n", "- Pani Mrs. age 50. Liczba rodzeństwa/małżonków na pokładzie 0. Liczba rodziców/dzieci na pokładzie 1 \n", "- Pani Mrs. Douglas z domu Baxter age 27. Liczba rodzeństwa/ - na pokładzie 1. Liczba rodziców/ - na pokładzie 1. Jest zamężna i ma jedno rodzenstwo i jednego rodzica w innej kabinie. Ale Mrs. Baxter z domu Chaput nie jest jej rodzicem. Tu jest jakiś błąd. Także komórka poniżej nie przyniesie odpowiedzi." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
961.00.0Douglas, Mr. Walter Donald050.01.00.0PC 17761106.4250C86CNaN62.0Deephaven, MN / Cedar Rapids, IA
971.01.0Douglas, Mrs. Frederick Charles (Mary Helene B...127.01.01.0PC 17558247.5208B58 B60C6NaNMontreal, PQ
981.01.0Douglas, Mrs. Walter Donald (Mahala Dutton)148.01.00.0PC 17761106.4250C86C2NaNDeephaven, MN / Cedar Rapids, IA
2731.01.0Spedden, Master. Robert Douglas06.00.02.016966134.5000E34C3NaNTuxedo Park, NY
5192.00.0Norman, Mr. Robert Douglas028.00.00.021862913.5000UnknownSNaN287.0Glasgow
11763.00.0Sage, Mr. Douglas Bullen0NaN8.02.0CA. 234369.5500UnknownSNaNNaNNaN
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" ], "text/plain": [ " pclass survived name \\\n", "96 1.0 0.0 Douglas, Mr. Walter Donald \n", "97 1.0 1.0 Douglas, Mrs. Frederick Charles (Mary Helene B... \n", "98 1.0 1.0 Douglas, Mrs. Walter Donald (Mahala Dutton) \n", "273 1.0 1.0 Spedden, Master. Robert Douglas \n", "519 2.0 0.0 Norman, Mr. Robert Douglas \n", "1176 3.0 0.0 Sage, Mr. Douglas Bullen \n", "\n", " sex age sibsp parch ticket fare cabin embarked boat \\\n", "96 0 50.0 1.0 0.0 PC 17761 106.4250 C86 C NaN \n", "97 1 27.0 1.0 1.0 PC 17558 247.5208 B58 B60 C 6 \n", "98 1 48.0 1.0 0.0 PC 17761 106.4250 C86 C 2 \n", "273 0 6.0 0.0 2.0 16966 134.5000 E34 C 3 \n", "519 0 28.0 0.0 0.0 218629 13.5000 Unknown S NaN \n", "1176 0 NaN 8.0 2.0 CA. 2343 69.5500 Unknown S NaN \n", "\n", " body home.dest \n", "96 62.0 Deephaven, MN / Cedar Rapids, IA \n", "97 NaN Montreal, PQ \n", "98 NaN Deephaven, MN / Cedar Rapids, IA \n", "273 NaN Tuxedo Park, NY \n", "519 287.0 Glasgow \n", "1176 NaN NaN " ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Czy możliwe, że w innej kabinie podróżowało jej rodzeństwo i rodzic?\n", "name_Douglas = df[df['name'].str.contains('Douglas')]\n", "name_Douglas" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
1421.00.0Guggenheim, Mr. Benjamin046.00.00.0PC 1759379.2B82 B84CNaNNaNNew York, NY
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" ], "text/plain": [ " pclass survived name sex age sibsp parch \\\n", "142 1.0 0.0 Guggenheim, Mr. Benjamin 0 46.0 0.0 0.0 \n", "\n", " ticket fare cabin embarked boat body home.dest \n", "142 PC 17593 79.2 B82 B84 C NaN NaN New York, NY " ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Przykładowo co zawierają kolumny, dla cabin==B82'\n", "wybrana_cabin = df[df['cabin'].str.contains('B82', na=False)]\n", "# Wyświetlenie wartości w innych kolumnach dla wybranej kabiny\n", "wybrana_cabin" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- Z kolei tutaj jedna osoba zajmowała 2 kabiny." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
11.01.0Allison, Master. Hudson Trevor00.91671.02.0113781151.55C22 C26S11NaNMontreal, PQ / Chesterville, ON
21.00.0Allison, Miss. Helen Loraine12.00001.02.0113781151.55C22 C26SNaNNaNMontreal, PQ / Chesterville, ON
31.00.0Allison, Mr. Hudson Joshua Creighton030.00001.02.0113781151.55C22 C26SNaN135.0Montreal, PQ / Chesterville, ON
41.00.0Allison, Mrs. Hudson J C (Bessie Waldo Daniels)125.00001.02.0113781151.55C22 C26SNaNNaNMontreal, PQ / Chesterville, ON
\n", "
" ], "text/plain": [ " pclass survived name sex \\\n", "1 1.0 1.0 Allison, Master. Hudson Trevor 0 \n", "2 1.0 0.0 Allison, Miss. Helen Loraine 1 \n", "3 1.0 0.0 Allison, Mr. Hudson Joshua Creighton 0 \n", "4 1.0 0.0 Allison, Mrs. Hudson J C (Bessie Waldo Daniels) 1 \n", "\n", " age sibsp parch ticket fare cabin embarked boat body \\\n", "1 0.9167 1.0 2.0 113781 151.55 C22 C26 S 11 NaN \n", "2 2.0000 1.0 2.0 113781 151.55 C22 C26 S NaN NaN \n", "3 30.0000 1.0 2.0 113781 151.55 C22 C26 S NaN 135.0 \n", "4 25.0000 1.0 2.0 113781 151.55 C22 C26 S NaN NaN \n", "\n", " home.dest \n", "1 Montreal, PQ / Chesterville, ON \n", "2 Montreal, PQ / Chesterville, ON \n", "3 Montreal, PQ / Chesterville, ON \n", "4 Montreal, PQ / Chesterville, ON " ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Przykładowo co zawierają kolumny, dla cabin==C22'\n", "wybrana_cabin = df[df['cabin'].str.contains('C22', na=False)]\n", "# Wyświetlenie wartości w innych kolumnach dla wybranej kabiny\n", "wybrana_cabin" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- kabiny zajmowały małżonkowie z dwójką małych dzieci\n", "- Mr. age 30. Liczba - /małżonków na pokładzie 1. Liczba - /dzieci na pokładzie 2.\n", "- Mrs. age 25. Liczba - /małżonków na pokładzie 1. Liczba - /dzieci na pokładzie 2 \n", "- Dla dzieci: Liczba rodzeństwa/- na pokładzie 1. Liczba rodziców/- na pokładzie 2." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
1111.01.0Fortune, Miss. Alice Elizabeth124.03.02.019950263.0C23 C25 C27S10NaNWinnipeg, MB
1121.01.0Fortune, Miss. Ethel Flora128.03.02.019950263.0C23 C25 C27S10NaNWinnipeg, MB
1131.01.0Fortune, Miss. Mabel Helen123.03.02.019950263.0C23 C25 C27S10NaNWinnipeg, MB
1141.00.0Fortune, Mr. Charles Alexander019.03.02.019950263.0C23 C25 C27SNaNNaNWinnipeg, MB
1151.00.0Fortune, Mr. Mark064.01.04.019950263.0C23 C25 C27SNaNNaNWinnipeg, MB
1161.01.0Fortune, Mrs. Mark (Mary McDougald)160.01.04.019950263.0C23 C25 C27S10NaNWinnipeg, MB
\n", "
" ], "text/plain": [ " pclass survived name sex age sibsp \\\n", "111 1.0 1.0 Fortune, Miss. Alice Elizabeth 1 24.0 3.0 \n", "112 1.0 1.0 Fortune, Miss. Ethel Flora 1 28.0 3.0 \n", "113 1.0 1.0 Fortune, Miss. Mabel Helen 1 23.0 3.0 \n", "114 1.0 0.0 Fortune, Mr. Charles Alexander 0 19.0 3.0 \n", "115 1.0 0.0 Fortune, Mr. Mark 0 64.0 1.0 \n", "116 1.0 1.0 Fortune, Mrs. Mark (Mary McDougald) 1 60.0 1.0 \n", "\n", " parch ticket fare cabin embarked boat body home.dest \n", "111 2.0 19950 263.0 C23 C25 C27 S 10 NaN Winnipeg, MB \n", "112 2.0 19950 263.0 C23 C25 C27 S 10 NaN Winnipeg, MB \n", "113 2.0 19950 263.0 C23 C25 C27 S 10 NaN Winnipeg, MB \n", "114 2.0 19950 263.0 C23 C25 C27 S NaN NaN Winnipeg, MB \n", "115 4.0 19950 263.0 C23 C25 C27 S NaN NaN Winnipeg, MB \n", "116 4.0 19950 263.0 C23 C25 C27 S 10 NaN Winnipeg, MB " ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Przykładowo co zawierają kolumny, dla cabin==C23'\n", "wybrana_cabin = df[df['cabin'].str.contains('C23', na=False)]\n", "# Wyświetlenie wartości w innych kolumnach dla wybranej kabiny\n", "wybrana_cabin" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- 3 kabiny zajmowały 6 osob: \n", "- Pan Mr. age 64. Liczba -/małżonków na pokładzie 1. Liczba -/ dzieci na pokładzie 4.\n", "- Pani Mrs. age 60. Liczba -/małżonków na pokładzie 1. Liczba /dzieci na pokładzie 4 \n", "- Ich dzieci: Liczba rodzeństwa/ - na pokładzie 3. Liczba rodziców/ - na pokładzie 2." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
2851.00.0Straus, Mr. Isidor067.01.00.0PC 17483221.7792C55 C57SNaN96.0New York, NY
2861.00.0Straus, Mrs. Isidor (Rosalie Ida Blun)163.01.00.0PC 17483221.7792C55 C57SNaNNaNNew York, NY
\n", "
" ], "text/plain": [ " pclass survived name sex age \\\n", "285 1.0 0.0 Straus, Mr. Isidor 0 67.0 \n", "286 1.0 0.0 Straus, Mrs. Isidor (Rosalie Ida Blun) 1 63.0 \n", "\n", " sibsp parch ticket fare cabin embarked boat body \\\n", "285 1.0 0.0 PC 17483 221.7792 C55 C57 S NaN 96.0 \n", "286 1.0 0.0 PC 17483 221.7792 C55 C57 S NaN NaN \n", "\n", " home.dest \n", "285 New York, NY \n", "286 New York, NY " ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Przykładowo co zawierają kolumny, dla cabin==C55'\n", "wybrana_cabin = df[df['cabin'].str.contains('C55', na=False)]\n", "# Wyświetlenie wartości w innych kolumnach dla wybranej kabiny\n", "wybrana_cabin" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- 2 kabiny zajmowały 2 osoby: \n", "- Oboje: Liczba -/małżonków na pokładzie 1. Liczba -/ dzieci na pokładzie 0." ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
101.00.0Astor, Col. John Jacob047.01.00.0PC 17757227.525C62 C64CNaN124.0New York, NY
111.01.0Astor, Mrs. John Jacob (Madeleine Talmadge Force)118.01.00.0PC 17757227.525C62 C64C4NaNNew York, NY
\n", "
" ], "text/plain": [ " pclass survived name sex \\\n", "10 1.0 0.0 Astor, Col. John Jacob 0 \n", "11 1.0 1.0 Astor, Mrs. John Jacob (Madeleine Talmadge Force) 1 \n", "\n", " age sibsp parch ticket fare cabin embarked boat body \\\n", "10 47.0 1.0 0.0 PC 17757 227.525 C62 C64 C NaN 124.0 \n", "11 18.0 1.0 0.0 PC 17757 227.525 C62 C64 C 4 NaN \n", "\n", " home.dest \n", "10 New York, NY \n", "11 New York, NY " ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Przykładowo co zawierają kolumny, dla cabin==C62'\n", "wybrana_cabin = df[df['cabin'].str.contains('C62', na=False)]\n", "# Wyświetlenie wartości w innych kolumnach dla wybranej kabiny\n", "wybrana_cabin" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- Małżeństwo age 47 i 18.\n", "Liczba rodze-/małżonków na pokładzie 1. Liczba rodziców/dzieci na pokładzie 0" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
1401.01.0Greenfield, Mr. William Bertram023.00.01.0PC 1775963.3583D10 D12C7NaNNew York, NY
1411.01.0Greenfield, Mrs. Leo David (Blanche Strouse)145.00.01.0PC 1775963.3583D10 D12C7NaNNew York, NY
\n", "
" ], "text/plain": [ " pclass survived name sex \\\n", "140 1.0 1.0 Greenfield, Mr. William Bertram 0 \n", "141 1.0 1.0 Greenfield, Mrs. Leo David (Blanche Strouse) 1 \n", "\n", " age sibsp parch ticket fare cabin embarked boat body \\\n", "140 23.0 0.0 1.0 PC 17759 63.3583 D10 D12 C 7 NaN \n", "141 45.0 0.0 1.0 PC 17759 63.3583 D10 D12 C 7 NaN \n", "\n", " home.dest \n", "140 New York, NY \n", "141 New York, NY " ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Przykładowo co zawierają kolumny, dla cabin==D10'\n", "wybrana_cabin = df[df['cabin'].str.contains('D10', na=False)]\n", "# Wyświetlenie wartości w innych kolumnach dla wybranej kabiny\n", "wybrana_cabin" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- Mama z synem\n", "Liczba rodzeństwa/małżonków na pokładzie 0. Liczba rodziców/dzieci na pokładzie 1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 'parch'" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.0 1000\n", "1.0 170\n", "2.0 113\n", "3.0 8\n", "4.0 6\n", "5.0 6\n", "6.0 2\n", "9.0 2\n", "Name: parch, dtype: int64\n" ] } ], "source": [ "# liczba_rodziców_albo_dzieci_na_pokładzie\n", "kolumna = 'parch'\n", "# Liczba występowania poszczególnych wartości unikalnych\n", "liczba_wystepowania_parch = df[kolumna].value_counts()\n", "print(liczba_wystepowania_parch)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski\n", "- Większość osób (1000) podróżowała bez osób spokrewnionych. Z jednym rodzicem albo jednym dzieckiem jest 170 rekordów. Z dwójką dzieci lub dwojgiem rodziców jest 113 wpisów." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Liczba osób należących do rodzin: 519\n" ] }, { "data": { "text/plain": [ "array(['Allison, Master. Hudson Trevor', 'Allison, Miss. Helen Loraine',\n", " 'Allison, Mr. Hudson Joshua Creighton',\n", " 'Allison, Mrs. Hudson J C (Bessie Waldo Daniels)',\n", " 'Andrews, Miss. Kornelia Theodosia',\n", " 'Appleton, Mrs. Edward Dale (Charlotte Lamson)',\n", " 'Astor, Col. John Jacob',\n", " 'Astor, Mrs. John Jacob (Madeleine Talmadge Force)',\n", " 'Baxter, Mr. Quigg Edmond',\n", " 'Baxter, Mrs. James (Helene DeLaudeniere Chaput)',\n", " 'Beckwith, Mr. Richard Leonard',\n", " 'Beckwith, Mrs. Richard Leonard (Sallie Monypeny)',\n", " 'Bishop, Mr. Dickinson H',\n", " 'Bishop, Mrs. Dickinson H (Helen Walton)',\n", " 'Bowerman, Miss. Elsie Edith',\n", " 'Brown, Mrs. John Murray (Caroline Lane Lamson)',\n", " 'Cardeza, Mr. Thomas Drake Martinez',\n", " 'Cardeza, Mrs. James Warburton Martinez (Charlotte Wardle Drake)',\n", " 'Carter, Master. William Thornton II', 'Carter, Miss. Lucile Polk',\n", " 'Carter, Mr. William Ernest',\n", " 'Carter, Mrs. William Ernest (Lucile Polk)',\n", " 'Cavendish, Mr. Tyrell William',\n", " 'Cavendish, Mrs. Tyrell William (Julia Florence Siegel)',\n", " 'Chaffee, Mr. Herbert Fuller',\n", " 'Chaffee, Mrs. Herbert Fuller (Carrie Constance Toogood)',\n", " 'Chambers, Mr. Norman Campbell',\n", " 'Chambers, Mrs. Norman Campbell (Bertha Griggs)',\n", " 'Chibnall, Mrs. (Edith Martha Bowerman)',\n", " 'Clark, Mr. Walter Miller',\n", " 'Clark, Mrs. Walter Miller (Virginia McDowell)',\n", " 'Compton, Miss. Sara Rebecca', 'Compton, Mr. Alexander Taylor Jr',\n", " 'Compton, Mrs. Alexander Taylor (Mary Eliza Ingersoll)',\n", " 'Cornell, Mrs. Robert Clifford (Malvina Helen Lamson)',\n", " 'Crosby, Capt. Edward Gifford', 'Crosby, Miss. Harriet R',\n", " 'Crosby, Mrs. Edward Gifford (Catherine Elizabeth Halstead)',\n", " 'Cumings, Mr. John Bradley',\n", " 'Cumings, Mrs. John Bradley (Florence Briggs Thayer)',\n", " 'Davidson, Mr. Thornton', 'Davidson, Mrs. Thornton (Orian Hays)',\n", " 'Dick, Mr. Albert Adrian',\n", " 'Dick, Mrs. Albert Adrian (Vera Gillespie)',\n", " 'Dodge, Dr. Washington', 'Dodge, Master. Washington',\n", " 'Dodge, Mrs. Washington (Ruth Vidaver)',\n", " 'Douglas, Mr. Walter Donald',\n", " 'Douglas, Mrs. Frederick Charles (Mary Helene Baxter)',\n", " 'Douglas, Mrs. Walter Donald (Mahala Dutton)',\n", " 'Duff Gordon, Lady. (Lucille Christiana Sutherland) (\"Mrs Morgan\")',\n", " 'Duff Gordon, Sir. Cosmo Edmund (\"Mr Morgan\")',\n", " 'Earnshaw, Mrs. Boulton (Olive Potter)',\n", " 'Eustis, Miss. Elizabeth Mussey', 'Fortune, Miss. Alice Elizabeth',\n", " 'Fortune, Miss. Ethel Flora', 'Fortune, Miss. Mabel Helen',\n", " 'Fortune, Mr. Charles Alexander', 'Fortune, Mr. Mark',\n", " 'Fortune, Mrs. Mark (Mary McDougald)',\n", " 'Frauenthal, Dr. Henry William', 'Frauenthal, Mr. Isaac Gerald',\n", " 'Frauenthal, Mrs. Henry William (Clara Heinsheimer)',\n", " 'Frolicher, Miss. Hedwig Margaritha',\n", " 'Frolicher-Stehli, Mr. Maxmillian',\n", " 'Frolicher-Stehli, Mrs. Maxmillian (Margaretha Emerentia Stehli)',\n", " 'Futrelle, Mr. Jacques Heath',\n", " 'Futrelle, Mrs. Jacques Heath (Lily May Peel)',\n", " 'Gibson, Miss. Dorothy Winifred',\n", " 'Gibson, Mrs. Leonard (Pauline C Boeson)',\n", " 'Goldenberg, Mr. Samuel L',\n", " 'Goldenberg, Mrs. Samuel L (Edwiga Grabowska)',\n", " 'Graham, Mr. George Edward',\n", " 'Graham, Mrs. William Thompson (Edith Junkins)',\n", " 'Greenfield, Mr. William Bertram',\n", " 'Greenfield, Mrs. Leo David (Blanche Strouse)',\n", " 'Harder, Mr. George Achilles',\n", " 'Harder, Mrs. George Achilles (Dorothy Annan)',\n", " 'Harper, Mr. Henry Sleeper',\n", " 'Harper, Mrs. Henry Sleeper (Myna Haxtun)',\n", " 'Harris, Mr. Henry Birkhardt',\n", " 'Harris, Mrs. Henry Birkhardt (Irene Wallach)',\n", " 'Hays, Mr. Charles Melville',\n", " 'Hays, Mrs. Charles Melville (Clara Jennings Gregg)',\n", " 'Hippach, Miss. Jean Gertrude',\n", " 'Hippach, Mrs. Louis Albert (Ida Sophia Fischer)',\n", " 'Hogeboom, Mrs. John C (Anna Andrews)',\n", " 'Holverson, Mr. Alexander Oskar',\n", " 'Holverson, Mrs. Alexander Oskar (Mary Aline Towner)',\n", " 'Hoyt, Mr. Frederick Maxfield',\n", " 'Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby)',\n", " 'Kenyon, Mr. Frederick R', 'Kenyon, Mrs. Frederick R (Marion)',\n", " 'Kimball, Mr. Edwin Nelson Jr',\n", " 'Kimball, Mrs. Edwin Nelson Jr (Gertrude Parsons)',\n", " 'Lines, Miss. Mary Conover',\n", " 'Lines, Mrs. Ernest H (Elizabeth Lindsey James)',\n", " 'Madill, Miss. Georgette Alexandra', 'Marvin, Mr. Daniel Warner',\n", " 'Marvin, Mrs. Daniel Warner (Mary Graham Carmichael Farquarson)',\n", " 'Meyer, Mr. Edgar Joseph', 'Meyer, Mrs. Edgar Joseph (Leila Saks)',\n", " 'Minahan, Dr. William Edward', 'Minahan, Miss. Daisy E',\n", " 'Minahan, Mrs. William Edward (Lillian E Thorpe)',\n", " 'Mock, Mr. Philipp Edmund', 'Natsch, Mr. Charles H',\n", " 'Newell, Miss. Madeleine', 'Newell, Miss. Marjorie',\n", " 'Newell, Mr. Arthur Webster', 'Newsom, Miss. Helen Monypeny',\n", " 'Ostby, Miss. Helene Ragnhild', 'Ostby, Mr. Engelhart Cornelius',\n", " 'Pears, Mr. Thomas Clinton', 'Pears, Mrs. Thomas (Edith Wearne)',\n", " 'Penasco y Castellana, Mr. Victor de Satode',\n", " 'Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo)',\n", " 'Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)',\n", " 'Robert, Mrs. Edward Scott (Elisabeth Walton McMillan)',\n", " 'Rothschild, Mr. Martin',\n", " 'Rothschild, Mrs. Martin (Elizabeth L. Barrett)',\n", " 'Ryerson, Master. John Borie', 'Ryerson, Miss. Emily Borie',\n", " 'Ryerson, Miss. Susan Parker \"Suzette\"',\n", " 'Ryerson, Mr. Arthur Larned',\n", " 'Ryerson, Mrs. Arthur Larned (Emily Maria Borie)',\n", " 'Schabert, Mrs. Paul (Emma Mock)', 'Silvey, Mr. William Baird',\n", " 'Silvey, Mrs. William Baird (Alice Munger)',\n", " 'Smith, Mr. Lucien Philip',\n", " 'Smith, Mrs. Lucien Philip (Mary Eloise Hughes)',\n", " 'Snyder, Mr. John Pillsbury',\n", " 'Snyder, Mrs. John Pillsbury (Nelle Stevenson)',\n", " 'Spedden, Master. Robert Douglas', 'Spedden, Mr. Frederic Oakley',\n", " 'Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone)',\n", " 'Spencer, Mr. William Augustus',\n", " 'Spencer, Mrs. William Augustus (Marie Eugenie)',\n", " 'Stengel, Mr. Charles Emil Henry',\n", " 'Stengel, Mrs. Charles Emil Henry (Annie May Morris)',\n", " 'Stephenson, Mrs. Walter Bertram (Martha Eustis)',\n", " 'Straus, Mr. Isidor', 'Straus, Mrs. Isidor (Rosalie Ida Blun)',\n", " 'Taussig, Miss. Ruth', 'Taussig, Mr. Emil',\n", " 'Taussig, Mrs. Emil (Tillie Mandelbaum)',\n", " 'Taylor, Mr. Elmer Zebley',\n", " 'Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright)',\n", " 'Thayer, Mr. John Borland', 'Thayer, Mr. John Borland Jr',\n", " 'Thayer, Mrs. John Borland (Marian Longstreth Morris)',\n", " 'Warren, Mr. Frank Manley',\n", " 'Warren, Mrs. Frank Manley (Anna Sophia Atkinson)',\n", " 'White, Mr. Percival Wayland', 'White, Mr. Richard Frasar',\n", " 'Wick, Miss. Mary Natalie', 'Wick, Mr. George Dennick',\n", " 'Wick, Mrs. George Dennick (Mary Hitchcock)',\n", " 'Widener, Mr. George Dunton', 'Widener, Mr. Harry Elkins',\n", " 'Widener, Mrs. George Dunton (Eleanor Elkins)',\n", " 'Williams, Mr. Charles Duane', 'Williams, Mr. Richard Norris II',\n", " 'Abelson, Mr. Samuel', 'Abelson, Mrs. Samuel (Hannah Wizosky)',\n", " 'Angle, Mr. William A',\n", " 'Angle, Mrs. William A (Florence \"Mary\" Agnes Hughes)',\n", " 'Beane, Mr. Edward', 'Beane, Mrs. Edward (Ethel Clarke)',\n", " 'Becker, Master. Richard F', 'Becker, Miss. Marion Louise',\n", " 'Becker, Miss. Ruth Elizabeth',\n", " 'Becker, Mrs. Allen Oliver (Nellie E Baumgardner)',\n", " 'Brown, Miss. Edith Eileen', 'Brown, Mr. Thomas William Solomon',\n", " 'Brown, Mrs. Thomas William Solomon (Elizabeth Catherine Ford)',\n", " 'Bryhl, Miss. Dagmar Jenny Ingeborg ',\n", " 'Bryhl, Mr. Kurt Arnold Gottfrid', 'Caldwell, Master. Alden Gates',\n", " 'Caldwell, Mr. Albert Francis',\n", " 'Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh)',\n", " 'Carter, Mrs. Ernest Courtenay (Lilian Hughes)',\n", " 'Carter, Rev. Ernest Courtenay', 'Chapman, Mr. John Henry',\n", " 'Chapman, Mrs. John Henry (Sara Elizabeth Lawry)',\n", " 'Christy, Miss. Julie Rachel', 'Christy, Mrs. (Alice Frances)',\n", " 'Clarke, Mr. Charles Valentine',\n", " 'Clarke, Mrs. Charles V (Ada Maria Winfield)',\n", " 'Collyer, Miss. Marjorie \"Lottie\"', 'Collyer, Mr. Harvey',\n", " 'Collyer, Mrs. Harvey (Charlotte Annie Tate)',\n", " 'Davies, Master. John Morgan Jr',\n", " 'Davies, Mrs. John Morgan (Elizabeth Agnes Mary White) ',\n", " 'del Carlo, Mr. Sebastiano',\n", " 'del Carlo, Mrs. Sebastiano (Argenia Genovesi)',\n", " 'Doling, Miss. Elsie', 'Doling, Mrs. John T (Ada Julia Bone)',\n", " 'Drew, Master. Marshall Brines', 'Drew, Mr. James Vivian',\n", " 'Drew, Mrs. James Vivian (Lulu Thorne Christian)',\n", " 'Duran y More, Miss. Asuncion', 'Duran y More, Miss. Florentina',\n", " 'Faunthorpe, Mr. Harry',\n", " 'Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson)',\n", " 'Gale, Mr. Harry', 'Gale, Mr. Shadrach', 'Giles, Mr. Edgar',\n", " 'Giles, Mr. Frederick Edward', 'Hamalainen, Master. Viljo',\n", " 'Hamalainen, Mrs. William (Anna)',\n", " 'Harper, Miss. Annie Jessie \"Nina\"', 'Harper, Rev. John',\n", " 'Hart, Miss. Eva Miriam', 'Hart, Mr. Benjamin',\n", " 'Hart, Mrs. Benjamin (Esther Ada Bloomfield)',\n", " 'Herman, Miss. Alice', 'Herman, Miss. Kate', 'Herman, Mr. Samuel',\n", " 'Herman, Mrs. Samuel (Jane Laver)', 'Hickman, Mr. Leonard Mark',\n", " 'Hickman, Mr. Lewis', 'Hickman, Mr. Stanley George',\n", " 'Hiltunen, Miss. Marta', 'Hocking, Miss. Ellen \"Nellie\"',\n", " 'Hocking, Mr. Richard George',\n", " 'Hocking, Mrs. Elizabeth (Eliza Needs)', 'Hold, Mr. Stephen',\n", " 'Hold, Mrs. Stephen (Annie Margaret Hill)', 'Howard, Mr. Benjamin',\n", " 'Howard, Mrs. Benjamin (Ellen Truelove Arman)',\n", " 'Jacobsohn, Mr. Sidney Samuel',\n", " 'Jacobsohn, Mrs. Sidney Samuel (Amy Frances Christy)',\n", " 'Jefferys, Mr. Clifford Thomas', 'Jefferys, Mr. Ernest Wilfred',\n", " 'Kantor, Mr. Sinai', 'Kantor, Mrs. Sinai (Miriam Sternin)',\n", " 'Lahtinen, Mrs. William (Anna Sylfven)', 'Lahtinen, Rev. William',\n", " 'Laroche, Miss. Louise',\n", " 'Laroche, Miss. Simonne Marie Anne Andree',\n", " 'Laroche, Mr. Joseph Philippe Lemercier',\n", " 'Laroche, Mrs. Joseph (Juliette Marie Louise Lafargue)',\n", " 'Louch, Mr. Charles Alexander',\n", " 'Louch, Mrs. Charles Alexander (Alice Adelaide Slow)',\n", " 'Mallet, Master. Andre', 'Mallet, Mr. Albert',\n", " 'Mallet, Mrs. Albert (Antoinette Magnin)',\n", " 'Mellinger, Miss. Madeleine Violet',\n", " 'Mellinger, Mrs. (Elizabeth Anne Maidment)',\n", " 'Nasser, Mr. Nicholas', 'Nasser, Mrs. Nicholas (Adele Achem)',\n", " 'Navratil, Master. Edmond Roger', 'Navratil, Master. Michel M',\n", " 'Navratil, Mr. Michel (\"Louis M Hoffman\")',\n", " 'Nicholls, Mr. Joseph Charles', 'Parrish, Mrs. (Lutie Davis)',\n", " 'Phillips, Miss. Alice Frances Louisa',\n", " 'Phillips, Mr. Escott Robert', 'Quick, Miss. Phyllis May',\n", " 'Quick, Miss. Winifred Vera',\n", " 'Quick, Mrs. Frederick Charles (Jane Richards)',\n", " 'Renouf, Mr. Peter Henry',\n", " 'Renouf, Mrs. Peter Henry (Lillian Jefferys)',\n", " 'Richards, Master. George Sibley',\n", " 'Richards, Master. William Rowe',\n", " 'Richards, Mrs. Sidney (Emily Hocking)',\n", " 'Shelley, Mrs. William (Imanita Parrish Hall)',\n", " 'Silven, Miss. Lyyli Karoliina', 'Turpin, Mr. William John Robert',\n", " 'Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott)',\n", " 'Ware, Mr. John James', 'Ware, Mr. William Jeffery',\n", " 'Weisz, Mr. Leopold',\n", " 'Weisz, Mrs. Leopold (Mathilde Francoise Pede)',\n", " 'Wells, Master. Ralph Lester', 'Wells, Miss. Joan',\n", " 'Wells, Mrs. Arthur Henry (\"Addie\" Dart Trevaskis)',\n", " 'West, Miss. Barbara J', 'West, Miss. Constance Mirium',\n", " 'West, Mr. Edwy Arthur', 'West, Mrs. Edwy Arthur (Ada Mary Worth)',\n", " 'Abbott, Master. Eugene Joseph', 'Abbott, Mr. Rossmore Edward',\n", " 'Abbott, Mrs. Stanton (Rosa Hunt)',\n", " 'Ahlin, Mrs. Johan (Johanna Persdotter Larsson)',\n", " 'Aks, Master. Philip Frank', 'Aks, Mrs. Sam (Leah Rosen)',\n", " 'Andersen-Jensen, Miss. Carla Christine Nielsine',\n", " 'Andersson, Master. Sigvard Harald Elias',\n", " 'Andersson, Miss. Ebba Iris Alfrida',\n", " 'Andersson, Miss. Ellis Anna Maria',\n", " 'Andersson, Miss. Erna Alexandra',\n", " 'Andersson, Miss. Ida Augusta Margareta',\n", " 'Andersson, Miss. Ingeborg Constanzia',\n", " 'Andersson, Miss. Sigrid Elisabeth', 'Andersson, Mr. Anders Johan',\n", " 'Andersson, Mrs. Anders Johan (Alfrida Konstantia Brogren)',\n", " 'Arnold-Franchi, Mr. Josef',\n", " 'Arnold-Franchi, Mrs. Josef (Josefine Franchi)',\n", " 'Asplund, Master. Carl Edgar',\n", " 'Asplund, Master. Clarence Gustaf Hugo',\n", " 'Asplund, Master. Edvin Rojj Felix',\n", " 'Asplund, Master. Filip Oscar', 'Asplund, Miss. Lillian Gertrud',\n", " 'Asplund, Mr. Carl Oscar Vilhelm Gustafsson',\n", " 'Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)',\n", " 'Backstrom, Mr. Karl Alfred',\n", " 'Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson)',\n", " 'Baclini, Miss. Eugenie', 'Baclini, Miss. Helene Barbara',\n", " 'Baclini, Miss. Marie Catherine',\n", " 'Baclini, Mrs. Solomon (Latifa Qurban)', 'Barbara, Miss. Saiide',\n", " 'Barbara, Mrs. (Catherine David)', 'Boulos, Master. Akar',\n", " 'Boulos, Miss. Nourelain', 'Boulos, Mrs. Joseph (Sultana)',\n", " 'Bourke, Miss. Mary', 'Bourke, Mr. John',\n", " 'Bourke, Mrs. John (Catherine)', 'Braund, Mr. Lewis Richard',\n", " 'Braund, Mr. Owen Harris', 'Caram, Mr. Joseph',\n", " 'Caram, Mrs. Joseph (Maria Elias)', 'Chronopoulos, Mr. Apostolos',\n", " 'Chronopoulos, Mr. Demetrios',\n", " 'Coutts, Master. Eden Leslie \"Neville\"',\n", " 'Coutts, Master. William Loch \"William\"',\n", " 'Coutts, Mrs. William (Winnie \"Minnie\" Treanor)',\n", " 'Cribb, Miss. Laura Alice', 'Cribb, Mr. John Hatfield',\n", " 'Danbom, Master. Gilbert Sigvard Emanuel',\n", " 'Danbom, Mr. Ernst Gilbert',\n", " 'Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren)',\n", " 'Davies, Mr. Alfred J', 'Davies, Mr. John Samuel',\n", " 'Davies, Mr. Joseph', 'Davison, Mr. Thomas Henry',\n", " 'Davison, Mrs. Thomas Henry (Mary E Finck)',\n", " 'de Messemaeker, Mr. Guillaume Joseph',\n", " 'de Messemaeker, Mrs. Guillaume Joseph (Emma)',\n", " 'Dean, Master. Bertram Vere',\n", " 'Dean, Miss. Elizabeth Gladys \"Millvina\"',\n", " 'Dean, Mr. Bertram Frank',\n", " 'Dean, Mrs. Bertram (Eva Georgetta Light)',\n", " 'Dyker, Mr. Adolf Fredrik',\n", " 'Dyker, Mrs. Adolf Fredrik (Anna Elisabeth Judith Andersson)',\n", " 'Elias, Mr. Joseph', 'Elias, Mr. Joseph Jr', 'Elias, Mr. Tannous',\n", " 'Ford, Miss. Doolina Margaret \"Daisy\"',\n", " 'Ford, Miss. Robina Maggie \"Ruby\"', 'Ford, Mr. Edward Watson',\n", " 'Ford, Mr. William Neal',\n", " 'Ford, Mrs. Edward (Margaret Ann Watson)',\n", " 'Goldsmith, Master. Frank John William \"Frankie\"',\n", " 'Goldsmith, Mr. Frank John',\n", " 'Goldsmith, Mrs. Frank John (Emily Alice Brown)',\n", " 'Goodwin, Master. Harold Victor',\n", " 'Goodwin, Master. Sidney Leonard',\n", " 'Goodwin, Master. William Frederick',\n", " 'Goodwin, Miss. Jessie Allis', 'Goodwin, Miss. Lillian Amy',\n", " 'Goodwin, Mr. Charles Edward', 'Goodwin, Mr. Charles Frederick',\n", " 'Goodwin, Mrs. Frederick (Augusta Tyler)',\n", " 'Gustafsson, Mr. Anders Vilhelm', 'Gustafsson, Mr. Johan Birger',\n", " 'Hagland, Mr. Ingvald Olai Olsen',\n", " 'Hagland, Mr. Konrad Mathias Reiersen',\n", " 'Hakkarainen, Mr. Pekka Pietari',\n", " 'Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck)',\n", " 'Hansen, Mr. Claus Peter', 'Hansen, Mr. Henrik Juul',\n", " 'Hansen, Mrs. Claus Peter (Jennie L Howard)',\n", " 'Hirvonen, Miss. Hildur E',\n", " 'Hirvonen, Mrs. Alexander (Helga E Lindqvist)',\n", " 'Ilmakangas, Miss. Ida Livija', 'Ilmakangas, Miss. Pieta Sofia',\n", " 'Jensen, Mr. Svend Lauritz', 'Johnson, Master. Harold Theodor',\n", " 'Johnson, Miss. Eleanor Ileen',\n", " 'Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)',\n", " 'Johnston, Master. William Arthur \"Willie\"',\n", " 'Johnston, Miss. Catherine Helen \"Carrie\"',\n", " 'Johnston, Mr. Andrew G',\n", " 'Johnston, Mrs. Andrew G (Elizabeth \"Lily\" Watson)',\n", " 'Jussila, Miss. Katriina', 'Jussila, Miss. Mari Aina',\n", " 'Karun, Miss. Manca', 'Karun, Mr. Franz', 'Khalil, Mr. Betros',\n", " 'Khalil, Mrs. Betros (Zahie \"Maria\" Elias)', 'Kiernan, Mr. John',\n", " 'Kiernan, Mr. Philip', 'Kink, Miss. Maria', 'Kink, Mr. Vincenz',\n", " 'Kink-Heilmann, Miss. Luise Gretchen', 'Kink-Heilmann, Mr. Anton',\n", " 'Kink-Heilmann, Mrs. Anton (Luise Heilmann)',\n", " 'Klasen, Miss. Gertrud Emilia', 'Klasen, Mr. Klas Albin',\n", " 'Klasen, Mrs. (Hulda Kristina Eugenia Lofqvist)',\n", " 'Lefebre, Master. Henry Forbes', 'Lefebre, Miss. Ida',\n", " 'Lefebre, Miss. Jeannie', 'Lefebre, Miss. Mathilde',\n", " 'Lefebre, Mrs. Frank (Frances)', 'Lennon, Miss. Mary',\n", " 'Lennon, Mr. Denis', 'Lindell, Mr. Edvard Bengtsson',\n", " 'Lindell, Mrs. Edvard Bengtsson (Elin Gerda Persson)',\n", " 'Lindqvist, Mr. Eino William', 'Lobb, Mr. William Arthur',\n", " 'Lobb, Mrs. William Arthur (Cordelia K Stanlick)',\n", " 'McCoy, Miss. Agnes', 'McCoy, Miss. Alicia', 'McCoy, Mr. Bernard',\n", " 'McNamee, Mr. Neal', \"McNamee, Mrs. Neal (Eileen O'Leary)\",\n", " 'Moor, Master. Meier', 'Moor, Mrs. (Beila)', 'Moran, Miss. Bertha',\n", " 'Moran, Mr. Daniel J', 'Moubarek, Master. Gerios',\n", " 'Moubarek, Master. Halim Gonios (\"William George\")',\n", " 'Moubarek, Mrs. George (Omine \"Amenia\" Alexander)',\n", " 'Murphy, Miss. Katherine \"Kate\"', 'Murphy, Miss. Margaret Jane',\n", " 'Nakid, Miss. Maria (\"Mary\")', 'Nakid, Mr. Sahid',\n", " 'Nakid, Mrs. Said (Waika \"Mary\" Mowad)',\n", " 'Nicola-Yarred, Master. Elias', 'Nicola-Yarred, Miss. Jamila',\n", " \"O'Brien, Mr. Thomas\",\n", " 'O\\'Brien, Mrs. Thomas (Johanna \"Hannah\" Godfrey)',\n", " 'Olsen, Master. Artur Karl', 'Olsen, Mr. Karl Siegwart Andreas',\n", " 'Palsson, Master. Gosta Leonard', 'Palsson, Master. Paul Folke',\n", " 'Palsson, Miss. Stina Viola', 'Palsson, Miss. Torborg Danira',\n", " 'Palsson, Mrs. Nils (Alma Cornelia Berglund)',\n", " 'Panula, Master. Eino Viljami', 'Panula, Master. Juha Niilo',\n", " 'Panula, Master. Urho Abraham', 'Panula, Mr. Ernesti Arvid',\n", " 'Panula, Mr. Jaako Arnold',\n", " 'Panula, Mrs. Juha (Maria Emilia Ojala)',\n", " 'Peacock, Master. Alfred Edward', 'Peacock, Miss. Treasteall',\n", " 'Peacock, Mrs. Benjamin (Edith Nile)', 'Persson, Mr. Ernst Ulrik',\n", " 'Peter, Master. Michael J', 'Peter, Miss. Anna',\n", " 'Peter, Mrs. Catherine (Catherine Rizk)',\n", " 'Petterson, Mr. Johan Emil', 'Rice, Master. Albert',\n", " 'Rice, Master. Arthur', 'Rice, Master. Eric',\n", " 'Rice, Master. Eugene', 'Rice, Master. George Hugh',\n", " 'Rice, Mrs. William (Margaret Norton)', 'Robins, Mr. Alexander A',\n", " 'Robins, Mrs. Alexander A (Grace Charity Laury)',\n", " 'Rosblom, Miss. Salli Helena', 'Rosblom, Mr. Viktor Richard',\n", " 'Rosblom, Mrs. Viktor (Helena Wilhelmina)',\n", " 'Sage, Master. Thomas Henry', 'Sage, Master. William Henry',\n", " 'Sage, Miss. Ada', 'Sage, Miss. Constance Gladys',\n", " 'Sage, Miss. Dorothy Edith \"Dolly\"', 'Sage, Miss. Stella Anna',\n", " 'Sage, Mr. Douglas Bullen', 'Sage, Mr. Frederick',\n", " 'Sage, Mr. George John Jr', 'Sage, Mr. John George',\n", " 'Sage, Mrs. John (Annie Bullen)', 'Samaan, Mr. Elias',\n", " 'Samaan, Mr. Hanna', 'Samaan, Mr. Youssef',\n", " 'Sandstrom, Miss. Beatrice Irene',\n", " 'Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengtsson)',\n", " 'Sandstrom, Miss. Marguerite Rut', 'Skoog, Master. Harald',\n", " 'Skoog, Master. Karl Thorsten', 'Skoog, Miss. Mabel',\n", " 'Skoog, Miss. Margit Elizabeth', 'Skoog, Mr. Wilhelm',\n", " 'Skoog, Mrs. William (Anna Bernhardina Karlsson)',\n", " 'Strom, Miss. Telma Matilda',\n", " 'Strom, Mrs. Wilhelm (Elna Matilda Persson)',\n", " 'Thomas, Master. Assad Alexander', 'Thomas, Mr. Charles P',\n", " 'Thomas, Mrs. Alexander (Thamine \"Thelma\")',\n", " 'Thorneycroft, Mr. Percival',\n", " 'Thorneycroft, Mrs. Percival (Florence Kate White)',\n", " 'Touma, Master. Georges Youssef', 'Touma, Miss. Maria Youssef',\n", " 'Touma, Mrs. Darwis (Hanne Youssef Razi)',\n", " 'van Billiard, Master. James William',\n", " 'van Billiard, Master. Walter John',\n", " 'van Billiard, Mr. Austin Blyler', 'Van Impe, Miss. Catharina',\n", " 'Van Impe, Mr. Jean Baptiste',\n", " 'Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert)',\n", " 'Vander Planke, Miss. Augusta Maria', 'Vander Planke, Mr. Julius',\n", " 'Vander Planke, Mr. Leo Edmondus',\n", " 'Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)',\n", " 'Wiklund, Mr. Jakob Alfred', 'Wiklund, Mr. Karl Johan',\n", " 'Wilkes, Mrs. James (Ellen Needs)', 'Yasbeck, Mr. Antoni',\n", " 'Yasbeck, Mrs. Antoni (Selini Alexander)', 'Zabour, Miss. Hileni',\n", " 'Zabour, Miss. Thamine'], dtype=object)" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# liczba osób spokrewnionych: wiersze, w których pasażerowie mają członków rodziny na pokładzie\n", "rodziny = df[(df['sibsp'] > 0) | (df['parch'] > 0)]\n", "\n", "# usuniecie duplikatow nazwisk, aby każde nazwisko występowało tylko raz\n", "unique_names = rodziny.drop_duplicates(subset='name')\n", "\n", "# Zliczenie nazwisk rodzin\n", "liczba_rodzin = unique_names['name'].nunique()\n", "print(\"Liczba osób należących do rodzin:\", liczba_rodzin)\n", "lista_rodzin = unique_names['name'].unique()\n", "lista_rodzin" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Liczba unikalnych nazwisk: 209\n" ] } ], "source": [ "rodziny = df[(df['sibsp'] > 0) | (df['parch'] > 0)].copy()\n", "# Tworzenie kopii kolumny 'name' - 'surname', gdzie zapisane są tylko części nazwisk przed przecinkiem\n", "\n", "rodziny['surname'] = rodziny['name'].str.split(',', expand=True)[0].str.strip()\n", "# Zliczanie unikalnych nazwisk\n", "unique_surnames_count = rodziny['surname'].nunique()\n", "print(\"Liczba unikalnych nazwisk:\", unique_surnames_count)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 'boat'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Według Wikipedii na „Titanicu” było 20 szalup." ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['2' '11' nan '3' '10' 'D' '4' '9' '6' 'B' '8' 'A' '5' '7' 'C' '14' '5 9'\n", " '13' '1' '15' '5 7' '8 10' '12' '16' '13 15 B' 'C D' '15 16' '13 15']\n", "Liczba unikalnych wartości w kolumnie 'boat': 27\n" ] } ], "source": [ "df2 = df.copy()\n", "ilość_łodzi = df2['boat'].unique()\n", "print(ilość_łodzi)\n", "# Liczba unikalnych wartości w kolumnie 'boat'\n", "liczba_unikalnych = df2['boat'].nunique()\n", "print(\"Liczba unikalnych wartości w kolumnie 'boat':\", liczba_unikalnych)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Kolumna ma jednak 27 oznaczen dla szalup.\n", "Podmiana oznaczenia szalup (zastąpienie błędnego oznaczenia, przez zignorowanie ciągu znaków za spacją)" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['2' '11' nan '3' '10' 'D' '4' '9' '6' 'B' '8' 'A' '5' '7' 'C' '14' '13'\n", " '1' '15' '12' '16']\n", "Liczba unikalnych wartości w kolumnie 'boat': 20\n" ] } ], "source": [ "# Podmiana oznaczenia szalup (zastąpienie błędnego oznaczenia, przez zignorowanie ciągu znaków za spacją)\n", "# Zastąpienie wartości przy użyciu słownika\n", "zastap_boat = {'5 7':'5',\n", " '5 9':'5',\n", " '8 10':'8',\n", " '13 15': '13',\n", " '13 15 B': '13',\n", " '15 16':'15',\n", " 'C D':'C'\n", " }\n", "\n", "df2['boat'] = df2['boat'].replace(zastap_boat)\n", "# wylistowanie kontrolne\n", "ilość_łodzi = df2['boat'].unique()\n", "print(ilość_łodzi)\n", "# Liczba unikalnych wartości w kolumnie 'boat'\n", "liczba_unikalnych = df2['boat'].nunique()\n", "print(\"Liczba unikalnych wartości w kolumnie 'boat':\", liczba_unikalnych)" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Liczba osób w każdej szalupie:\n" ] }, { "data": { "text/plain": [ "boat\n", "1 5\n", "10 29\n", "11 25\n", "12 19\n", "13 42\n", "14 33\n", "15 38\n", "16 23\n", "2 13\n", "3 26\n", "4 31\n", "5 30\n", "6 20\n", "7 23\n", "8 24\n", "9 25\n", "A 11\n", "B 9\n", "C 40\n", "D 20\n", "dtype: int64" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Zapełnienie rozbitkami pro szalupę\n", "# Zliczanie liczby osób w każdej szalupie\n", "liczba_osob_w_szalupach = df2.groupby('boat').size()\n", "# Wyświetlanie wyników\n", "print('Liczba osób w każdej szalupie:')\n", "liczba_osob_w_szalupach" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Całkowita liczba osób we wszystkich szalupach: 486\n" ] } ], "source": [ "calkowita_liczba_osob = liczba_osob_w_szalupach.sum()\n", "# Wyświetlanie wyniku\n", "print(f'Całkowita liczba osób we wszystkich szalupach: {calkowita_liczba_osob}')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- Porównując surrvived = 500, w szalupach uratowało się 486 rozbitków." ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Najwiecej osób w szalupie: 42\n" ] } ], "source": [ "najwiecej_osób_w_szalupie = max(liczba_osob_w_szalupach)\n", "print(\"Najwiecej osób w szalupie:\", najwiecej_osób_w_szalupie)" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Najmniej osób w szalupie: 5\n" ] } ], "source": [ "najmniej_osób_w_szalupie = min(liczba_osob_w_szalupach)\n", "print(\"Najmniej osób w szalupie:\", najmniej_osób_w_szalupie)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- Najmniejsza liczba rozbitków w szalupie wyniosła 1, największa 39." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 'age'" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "# Czy wartości w kolumnie 'age' są normalne dla wieku ludzkiego?" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Minimalna wartość wieku: 0.1667\n", "Maksymalna wartość wieku: 80.0\n" ] } ], "source": [ "# Wartosci min i max dla kolumny 'age'\n", "min_age = df2['age'].min()\n", "max_age = df2['age'].max()\n", "\n", "print(f\"Minimalna wartość wieku: {min_age}\")\n", "print(f\"Maksymalna wartość wieku: {max_age}\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- wartości są naturalne dla wieku ludzi " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 'embarked'" ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['S' 'C' nan 'Q']\n" ] } ], "source": [ "miejsceWsiadania = df2['embarked'].unique()\n", "print(miejsceWsiadania)" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": [ "# Mapowanie object na wartości numeryczne\n", "df2['embarked'] = df2['embarked'].map({'C': 1, 'Q': 2, 'S': 3})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 'body'" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "121" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Liczba odnalezionych ciał\n", "liczba_ciał = df['body'].count()\n", "liczba_ciał" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Liczba odnalezionych ciał w kolejności rosnącej: [1.0, 4.0, 7.0, 9.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 22.0, 32.0, 35.0, 37.0, 38.0, 43.0, 45.0, 46.0, 47.0, 50.0, 51.0, 52.0, 53.0, 58.0, 61.0, 62.0, 67.0, 68.0, 69.0, 70.0, 72.0, 75.0, 79.0, 80.0, 81.0, 89.0, 96.0, 97.0, 98.0, 101.0, 103.0, 108.0, 109.0, 110.0, 119.0, 120.0, 121.0, 122.0, 124.0, 126.0, 130.0, 131.0, 133.0, 135.0, 142.0, 143.0, 147.0, 148.0, 149.0, 153.0, 155.0, 156.0, 165.0, 166.0, 169.0, 171.0, 172.0, 173.0, 174.0, 175.0, 176.0, 181.0, 187.0, 188.0, 189.0, 190.0, 196.0, 197.0, 201.0, 206.0, 207.0, 208.0, 209.0, 230.0, 232.0, 234.0, 236.0, 245.0, 249.0, 255.0, 256.0, 258.0, 259.0, 260.0, 261.0, 263.0, 269.0, 271.0, 275.0, 283.0, 284.0, 285.0, 286.0, 287.0, 292.0, 293.0, 294.0, 295.0, 297.0, 298.0, 299.0, 304.0, 305.0, 306.0, 307.0, 309.0, 312.0, 314.0, 322.0, 327.0, 328.0]\n" ] } ], "source": [ "# Przekształcenie kolumny 'body' na listę i usunięcie wartości NaN\n", "liczba_cial = df['body'].dropna().tolist()\n", "# Sortowanie listy w kolejności rosnącej\n", "liczba_cial.sort()\n", "# Wypisanie posortowanej listy\n", "print(\"Liczba odnalezionych ciał w kolejności rosnącej:\", liczba_cial)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- Pomimo najwyższej liczby 328, nie oznacza to, że było 328 odnalezionych ciał. Posortowanie w kolejności rosnącej pokazuje brakujące numery." ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: [pclass, survived, name, sex, age, sibsp, parch, ticket, fare, cabin, embarked, boat, body, home.dest]\n", "Index: []" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Sprawdzenie kolumn na sprzeczności, że jest numer ciała, a osoba przeżyła\n", "# Sprawdzenie wierszy, gdzie 'survived' == 1.0 oraz 'body' nie jest NaN\n", "pary_sprzeczne = df2[(df2['survived'] == 1.0) & (df2['body'].notna())]\n", "# Wyświetlenie wierszy sprzecznych\n", "pary_sprzeczne" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- Dane w kolumnie body nie stoją w sprzeczności z kolumną survived." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 'survived'" ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "liczba_ofiar: 807\n" ] } ], "source": [ "# Liczba pasażerów, którzy nie przeżyli\n", "liczba_ofiar = df2[df2['survived'] == 0].shape[0]\n", "print(\"liczba_ofiar:\", liczba_ofiar)" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "liczba_ocalonych: 500.0\n" ] } ], "source": [ "# Liczba pasażerów, którzy przeżyli\n", "liczba_ocalonych = df2['survived'].sum()\n", "print(\"liczba_ocalonych:\", liczba_ocalonych)" ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "liczba_pasażerów, którzy przeżyli w katastrofie:\n" ] }, { "data": { "text/plain": [ "500" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "print(f'liczba_pasażerów, którzy przeżyli w katastrofie:')\n", "szczęściarze = df2[df2['survived']>0]\n", "liczba_szczęściarzy = szczęściarze['survived'].count()\n", "liczba_szczęściarzy" ] }, { "cell_type": "code", "execution_count": 47, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Klasy biletów, które posiadali pasażerowie, którzy przeżyli:\n" ] }, { "data": { "text/plain": [ "pclass\n", "1.0 200\n", "2.0 119\n", "3.0 181\n", "Name: survived, dtype: int64" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# jaką klasę biletu posiadali szczęściarze\n", "print('Klasy biletów, które posiadali pasażerowie, którzy przeżyli:')\n", "bilety_szczęściarzy = szczęściarze.groupby('pclass')['survived'].count()\n", "bilety_szczęściarzy" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 'ticket'" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Bilet: CA. 2343, zliczeń: 11\n", "Bilet: 1601, zliczeń: 8\n", "Bilet: CA 2144, zliczeń: 8\n", "Bilet: PC 17608, zliczeń: 7\n", "Bilet: 347077, zliczeń: 7\n", "Bilet: 347082, zliczeń: 7\n", "Bilet: 3101295, zliczeń: 7\n", "Bilet: S.O.C. 14879, zliczeń: 7\n", "Bilet: 113781, zliczeń: 6\n", "Bilet: 19950, zliczeń: 6\n", "Bilet: 382652, zliczeń: 6\n", "Bilet: 347088, zliczeń: 6\n", "Bilet: PC 17757, zliczeń: 5\n", "Bilet: 349909, zliczeń: 5\n", "Bilet: 16966, zliczeń: 5\n", "Bilet: 4133, zliczeń: 5\n", "Bilet: 220845, zliczeń: 5\n", "Bilet: 113503, zliczeń: 5\n", "Bilet: W./C. 6608, zliczeń: 5\n" ] } ], "source": [ "# Wylistowanie wartości\n", "powtórzenia = df['ticket'].value_counts()\n", "powtórzenia\n", "for ticket, count in powtórzenia.items():\n", " if count >= 5:\n", " print(f'Bilet: {ticket}, zliczeń: {count}')" ] }, { "cell_type": "code", "execution_count": 50, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
11703.00.0Sage, Master. Thomas Henry0NaN8.02.0CA. 234369.55UnknownSNaNNaNNaN
11713.00.0Sage, Master. William Henry014.58.02.0CA. 234369.55UnknownSNaN67.0NaN
11723.00.0Sage, Miss. Ada1NaN8.02.0CA. 234369.55UnknownSNaNNaNNaN
11733.00.0Sage, Miss. Constance Gladys1NaN8.02.0CA. 234369.55UnknownSNaNNaNNaN
11743.00.0Sage, Miss. Dorothy Edith \"Dolly\"1NaN8.02.0CA. 234369.55UnknownSNaNNaNNaN
11753.00.0Sage, Miss. Stella Anna1NaN8.02.0CA. 234369.55UnknownSNaNNaNNaN
11763.00.0Sage, Mr. Douglas Bullen0NaN8.02.0CA. 234369.55UnknownSNaNNaNNaN
11773.00.0Sage, Mr. Frederick0NaN8.02.0CA. 234369.55UnknownSNaNNaNNaN
11783.00.0Sage, Mr. George John Jr0NaN8.02.0CA. 234369.55UnknownSNaNNaNNaN
11793.00.0Sage, Mr. John George0NaN1.09.0CA. 234369.55UnknownSNaNNaNNaN
11803.00.0Sage, Mrs. John (Annie Bullen)1NaN1.09.0CA. 234369.55UnknownSNaNNaNNaN
\n", "
" ], "text/plain": [ " pclass survived name sex age sibsp \\\n", "1170 3.0 0.0 Sage, Master. Thomas Henry 0 NaN 8.0 \n", "1171 3.0 0.0 Sage, Master. William Henry 0 14.5 8.0 \n", "1172 3.0 0.0 Sage, Miss. Ada 1 NaN 8.0 \n", "1173 3.0 0.0 Sage, Miss. Constance Gladys 1 NaN 8.0 \n", "1174 3.0 0.0 Sage, Miss. Dorothy Edith \"Dolly\" 1 NaN 8.0 \n", "1175 3.0 0.0 Sage, Miss. Stella Anna 1 NaN 8.0 \n", "1176 3.0 0.0 Sage, Mr. Douglas Bullen 0 NaN 8.0 \n", "1177 3.0 0.0 Sage, Mr. Frederick 0 NaN 8.0 \n", "1178 3.0 0.0 Sage, Mr. George John Jr 0 NaN 8.0 \n", "1179 3.0 0.0 Sage, Mr. John George 0 NaN 1.0 \n", "1180 3.0 0.0 Sage, Mrs. John (Annie Bullen) 1 NaN 1.0 \n", "\n", " parch ticket fare cabin embarked boat body home.dest \n", "1170 2.0 CA. 2343 69.55 Unknown S NaN NaN NaN \n", "1171 2.0 CA. 2343 69.55 Unknown S NaN 67.0 NaN \n", "1172 2.0 CA. 2343 69.55 Unknown S NaN NaN NaN \n", "1173 2.0 CA. 2343 69.55 Unknown S NaN NaN NaN \n", "1174 2.0 CA. 2343 69.55 Unknown S NaN NaN NaN \n", "1175 2.0 CA. 2343 69.55 Unknown S NaN NaN NaN \n", "1176 2.0 CA. 2343 69.55 Unknown S NaN NaN NaN \n", "1177 2.0 CA. 2343 69.55 Unknown S NaN NaN NaN \n", "1178 2.0 CA. 2343 69.55 Unknown S NaN NaN NaN \n", "1179 9.0 CA. 2343 69.55 Unknown S NaN NaN NaN \n", "1180 9.0 CA. 2343 69.55 Unknown S NaN NaN NaN " ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Filtrowanie DataFrame dla ticket == 'CA. 2343' i wybranie pierwszych 10 wierszy\n", "filtered_df = df[df['ticket'] == 'CA. 2343']\n", "filtered_df.head(11)" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Bilet: CA. 2343\n", " zliczenia powtórzeń: 11\n", " średnia cena biletu: 69.55\n", " klasa biletu: 3.0\n", "------------------------------\n", "Bilet: 1601\n", " zliczenia powtórzeń: 8\n", " średnia cena biletu: 56.4958\n", " klasa biletu: 3.0\n", "------------------------------\n", "Bilet: CA 2144\n", " zliczenia powtórzeń: 8\n", " średnia cena biletu: 46.9\n", " klasa biletu: 3.0\n", "------------------------------\n", "Bilet: PC 17608\n", " zliczenia powtórzeń: 7\n", " średnia cena biletu: 262.375\n", " klasa biletu: 1.0\n", "------------------------------\n", "Bilet: 347077\n", " zliczenia powtórzeń: 7\n", " średnia cena biletu: 31.3875\n", " klasa biletu: 3.0\n", "------------------------------\n", "Bilet: 347082\n", " zliczenia powtórzeń: 7\n", " średnia cena biletu: 31.275\n", " klasa biletu: 3.0\n", "------------------------------\n", "Bilet: 3101295\n", " zliczenia powtórzeń: 7\n", " średnia cena biletu: 39.6875\n", " klasa biletu: 3.0\n", "------------------------------\n", "Bilet: S.O.C. 14879\n", " zliczenia powtórzeń: 7\n", " średnia cena biletu: 73.5\n", " klasa biletu: 2.0\n", "------------------------------\n", "Bilet: 113781\n", " zliczenia powtórzeń: 6\n", " średnia cena biletu: 151.55\n", " klasa biletu: 1.0\n", "------------------------------\n", "Bilet: 19950\n", " zliczenia powtórzeń: 6\n", " średnia cena biletu: 263.0\n", " klasa biletu: 1.0\n", "------------------------------\n", "Bilet: 382652\n", " zliczenia powtórzeń: 6\n", " średnia cena biletu: 29.125\n", " klasa biletu: 3.0\n", "------------------------------\n", "Bilet: 347088\n", " zliczenia powtórzeń: 6\n", " średnia cena biletu: 27.899999999999995\n", " klasa biletu: 3.0\n", "------------------------------\n", "Bilet: PC 17757\n", " zliczenia powtórzeń: 5\n", " średnia cena biletu: 227.525\n", " klasa biletu: 1.0\n", "------------------------------\n", "Bilet: 349909\n", " zliczenia powtórzeń: 5\n", " średnia cena biletu: 21.075\n", " klasa biletu: 3.0\n", "------------------------------\n", "Bilet: 16966\n", " zliczenia powtórzeń: 5\n", " średnia cena biletu: 134.5\n", " klasa biletu: 1.0\n", "------------------------------\n", "Bilet: 4133\n", " zliczenia powtórzeń: 5\n", " średnia cena biletu: 25.4667\n", " klasa biletu: 3.0\n", "------------------------------\n", "Bilet: 220845\n", " zliczenia powtórzeń: 5\n", " średnia cena biletu: 65.0\n", " klasa biletu: 2.0\n", "------------------------------\n", "Bilet: 113503\n", " zliczenia powtórzeń: 5\n", " średnia cena biletu: 211.5\n", " klasa biletu: 1.0\n", "------------------------------\n", "Bilet: W./C. 6608\n", " zliczenia powtórzeń: 5\n", " średnia cena biletu: 34.375\n", " klasa biletu: 3.0\n", "------------------------------\n" ] } ], "source": [ "grouped_by_ticket = df.groupby('ticket').agg({'fare': 'mean', 'pclass': 'first'})\n", "\n", "# Iteracja po wynikach dla każdego biletu\n", "for ticket, count in powtórzenia.items():\n", " if count >= 5:\n", " if ticket in grouped_by_ticket.index:\n", " data = grouped_by_ticket.loc[ticket]\n", " print(f\"Bilet: {ticket}\")\n", " print(f\" zliczenia powtórzeń: {count}\")\n", " print(f\" średnia cena biletu: {data['fare']}\")\n", " print(f\" klasa biletu: {data['pclass']}\")\n", " \n", " print(\"-\" * 30)" ] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Bilet: CA 2144, zliczeń: 8\n", " średnia cena biletu: 46.9\n", " klasa biletu: 3.0\n", " minimalny wiek: 1.0\n", " maksymalny wiek: 43.0\n" ] }, { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
8253.00.0Goodwin, Master. Harold Victor09.05.02.0CA 214446.9UnknownSNaNNaNWiltshire, England Niagara Falls, NY
8263.00.0Goodwin, Master. Sidney Leonard01.05.02.0CA 214446.9UnknownSNaNNaNWiltshire, England Niagara Falls, NY
8273.00.0Goodwin, Master. William Frederick011.05.02.0CA 214446.9UnknownSNaNNaNWiltshire, England Niagara Falls, NY
8283.00.0Goodwin, Miss. Jessie Allis110.05.02.0CA 214446.9UnknownSNaNNaNWiltshire, England Niagara Falls, NY
8293.00.0Goodwin, Miss. Lillian Amy116.05.02.0CA 214446.9UnknownSNaNNaNWiltshire, England Niagara Falls, NY
8303.00.0Goodwin, Mr. Charles Edward014.05.02.0CA 214446.9UnknownSNaNNaNWiltshire, England Niagara Falls, NY
8313.00.0Goodwin, Mr. Charles Frederick040.01.06.0CA 214446.9UnknownSNaNNaNWiltshire, England Niagara Falls, NY
8323.00.0Goodwin, Mrs. Frederick (Augusta Tyler)143.01.06.0CA 214446.9UnknownSNaNNaNWiltshire, England Niagara Falls, NY
\n", "
" ], "text/plain": [ " pclass survived name sex age \\\n", "825 3.0 0.0 Goodwin, Master. Harold Victor 0 9.0 \n", "826 3.0 0.0 Goodwin, Master. Sidney Leonard 0 1.0 \n", "827 3.0 0.0 Goodwin, Master. William Frederick 0 11.0 \n", "828 3.0 0.0 Goodwin, Miss. Jessie Allis 1 10.0 \n", "829 3.0 0.0 Goodwin, Miss. Lillian Amy 1 16.0 \n", "830 3.0 0.0 Goodwin, Mr. Charles Edward 0 14.0 \n", "831 3.0 0.0 Goodwin, Mr. Charles Frederick 0 40.0 \n", "832 3.0 0.0 Goodwin, Mrs. Frederick (Augusta Tyler) 1 43.0 \n", "\n", " sibsp parch ticket fare cabin embarked boat body \\\n", "825 5.0 2.0 CA 2144 46.9 Unknown S NaN NaN \n", "826 5.0 2.0 CA 2144 46.9 Unknown S NaN NaN \n", "827 5.0 2.0 CA 2144 46.9 Unknown S NaN NaN \n", "828 5.0 2.0 CA 2144 46.9 Unknown S NaN NaN \n", "829 5.0 2.0 CA 2144 46.9 Unknown S NaN NaN \n", "830 5.0 2.0 CA 2144 46.9 Unknown S NaN NaN \n", "831 1.0 6.0 CA 2144 46.9 Unknown S NaN NaN \n", "832 1.0 6.0 CA 2144 46.9 Unknown S NaN NaN \n", "\n", " home.dest \n", "825 Wiltshire, England Niagara Falls, NY \n", "826 Wiltshire, England Niagara Falls, NY \n", "827 Wiltshire, England Niagara Falls, NY \n", "828 Wiltshire, England Niagara Falls, NY \n", "829 Wiltshire, England Niagara Falls, NY \n", "830 Wiltshire, England Niagara Falls, NY \n", "831 Wiltshire, England Niagara Falls, NY \n", "832 Wiltshire, England Niagara Falls, NY " ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Wyświetlenie tylko danych dla biletu 'CA 2144'\n", "t = 'CA 2144'\n", "for ticket, count in powtórzenia.items():\n", " if ticket == t:\n", " print(f\"Bilet: {ticket}, zliczeń: {count}\")\n", " data = grouped_by_ticket.loc[ticket]\n", " print(f\" średnia cena biletu: {data['fare']}\")\n", " print(f\" klasa biletu: {data['pclass']}\")\n", " \n", "filtered_df = df[df['ticket'] == t]\n", "# Wypisanie minimalnej i maksymalnej wartości dla kolumny 'age'\n", "min_age = filtered_df['age'].min()\n", "max_age = filtered_df['age'].max()\n", "\n", "print(f\" minimalny wiek: {min_age}\")\n", "print(f\" maksymalny wiek: {max_age}\")\n", "filtered_df.head(10)" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Bilet: CA. 2343, zliczeń: 11\n", " Średnia cena: 69.55\n", " Klasa: 3.0\n", "------------------------------\n", "Bilet: 1601, zliczeń: 8\n", " Średnia cena: 56.4958\n", " Klasa: 3.0\n", "------------------------------\n", "Bilet: CA 2144, zliczeń: 8\n", " Średnia cena: 46.9\n", " Klasa: 3.0\n", "------------------------------\n", "Bilet: PC 17608, zliczeń: 7\n", " Średnia cena: 262.375\n", " Klasa: 1.0\n", "------------------------------\n", "Bilet: 347077, zliczeń: 7\n", " Średnia cena: 31.3875\n", " Klasa: 3.0\n", "------------------------------\n", "Bilet: 347082, zliczeń: 7\n", " Średnia cena: 31.275\n", " Klasa: 3.0\n", "------------------------------\n", "Bilet: 3101295, zliczeń: 7\n", " Średnia cena: 39.6875\n", " Klasa: 3.0\n", "------------------------------\n", "Bilet: S.O.C. 14879, zliczeń: 7\n", " Średnia cena: 73.5\n", " Klasa: 2.0\n", "------------------------------\n", "Bilet: 113781, zliczeń: 6\n", " Średnia cena: 151.55\n", " Klasa: 1.0\n", "------------------------------\n", "Bilet: 19950, zliczeń: 6\n", " Średnia cena: 263.0\n", " Klasa: 1.0\n", "------------------------------\n", "Bilet: 382652, zliczeń: 6\n", " Średnia cena: 29.125\n", " Klasa: 3.0\n", "------------------------------\n", "Bilet: 347088, zliczeń: 6\n", " Średnia cena: 27.899999999999995\n", " Klasa: 3.0\n", "------------------------------\n", "Bilet: PC 17757, zliczeń: 5\n", " Średnia cena: 227.525\n", " Klasa: 1.0\n", "------------------------------\n", "Bilet: 349909, zliczeń: 5\n", " Średnia cena: 21.075\n", " Klasa: 3.0\n", "------------------------------\n", "Bilet: 16966, zliczeń: 5\n", " Średnia cena: 134.5\n", " Klasa: 1.0\n", "------------------------------\n", "Bilet: 4133, zliczeń: 5\n", " Średnia cena: 25.4667\n", " Klasa: 3.0\n", "------------------------------\n", "Bilet: 220845, zliczeń: 5\n", " Średnia cena: 65.0\n", " Klasa: 2.0\n", "------------------------------\n", "Bilet: 113503, zliczeń: 5\n", " Średnia cena: 211.5\n", " Klasa: 1.0\n", "------------------------------\n", "Bilet: W./C. 6608, zliczeń: 5\n", " Średnia cena: 34.375\n", " Klasa: 3.0\n", "------------------------------\n" ] } ], "source": [ "# Iterowanie po zliczeniach biletów i wyświetlanie wyników z dodatkowymi informacjami\n", "for ticket, count in powtórzenia.items():\n", " if count >= 5:\n", " print(f\"Bilet: {ticket}, zliczeń: {count}\")\n", " data = grouped_by_ticket.loc[ticket]\n", " print(f\" Średnia cena: {data['fare']}\")\n", " print(f\" Klasa: {data['pclass']}\")\n", " \n", " print(\"-\" * 30)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 'fare'" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclassfare
minmedianmaxmeanstd
01.00.060.0000512.329287.50899280.447178
12.00.015.045873.500021.17919613.607122
23.00.08.050069.550013.31836511.506956
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" ], "text/plain": [ " pclass fare \n", " min median max mean std\n", "0 1.0 0.0 60.0000 512.3292 87.508992 80.447178\n", "1 2.0 0.0 15.0458 73.5000 21.179196 13.607122\n", "2 3.0 0.0 8.0500 69.5500 13.318365 11.506956" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# cena biletu vs. klasa\n", "df2.groupby('pclass', as_index=False).agg(\n", " {\n", " 'fare': ['min','median','max', 'mean','std']\n", " }\n", " )" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Liczba wierszy z ceną za bilet równą 0 dollars: 17\n" ] }, { "data": { "text/html": [ "
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pclasssurvivednamesexagesibspparchticketfarecabinembarkedboatbodyhome.dest
71.00.0Andrews, Mr. Thomas Jr039.00.00.01120500.0A36SNaNNaNBelfast, NI
701.00.0Chisholm, Mr. Roderick Robert Crispin0NaN0.00.01120510.0UnknownSNaNNaNLiverpool, England / Belfast
1251.00.0Fry, Mr. Richard0NaN0.00.01120580.0B102SNaNNaNNaN
1501.00.0Harrison, Mr. William040.00.00.01120590.0B94SNaN110.0NaN
1701.01.0Ismay, Mr. Joseph Bruce049.00.00.01120580.0B52 B54 B56SCNaNLiverpool
2231.00.0Parr, Mr. William Henry Marsh0NaN0.00.01120520.0UnknownSNaNNaNBelfast
2341.00.0Reuchlin, Jonkheer. John George038.00.00.0199720.0UnknownSNaNNaNRotterdam, Netherlands
3632.00.0Campbell, Mr. William0NaN0.00.02398530.0UnknownSNaNNaNBelfast
3842.00.0Cunningham, Mr. Alfred Fleming0NaN0.00.02398530.0UnknownSNaNNaNBelfast
4102.00.0Frost, Mr. Anthony Wood \"Archie\"0NaN0.00.02398540.0UnknownSNaNNaNBelfast
4732.00.0Knight, Mr. Robert J0NaN0.00.02398550.0UnknownSNaNNaNBelfast
5282.00.0Parkes, Mr. Francis \"Frank\"0NaN0.00.02398530.0UnknownSNaNNaNBelfast
5812.00.0Watson, Mr. Ennis Hastings0NaN0.00.02398560.0UnknownSNaNNaNBelfast
8963.00.0Johnson, Mr. Alfred049.00.00.0LINE0.0UnknownSNaNNaNNaN
8983.00.0Johnson, Mr. William Cahoone Jr019.00.00.0LINE0.0UnknownSNaNNaNNaN
9633.00.0Leonard, Mr. Lionel036.00.00.0LINE0.0UnknownSNaNNaNNaN
12543.01.0Tornquist, Mr. William Henry025.00.00.0LINE0.0UnknownS15NaNNaN
\n", "
" ], "text/plain": [ " pclass survived name sex age \\\n", "7 1.0 0.0 Andrews, Mr. Thomas Jr 0 39.0 \n", "70 1.0 0.0 Chisholm, Mr. Roderick Robert Crispin 0 NaN \n", "125 1.0 0.0 Fry, Mr. Richard 0 NaN \n", "150 1.0 0.0 Harrison, Mr. William 0 40.0 \n", "170 1.0 1.0 Ismay, Mr. Joseph Bruce 0 49.0 \n", "223 1.0 0.0 Parr, Mr. William Henry Marsh 0 NaN \n", "234 1.0 0.0 Reuchlin, Jonkheer. John George 0 38.0 \n", "363 2.0 0.0 Campbell, Mr. William 0 NaN \n", "384 2.0 0.0 Cunningham, Mr. Alfred Fleming 0 NaN \n", "410 2.0 0.0 Frost, Mr. Anthony Wood \"Archie\" 0 NaN \n", "473 2.0 0.0 Knight, Mr. Robert J 0 NaN \n", "528 2.0 0.0 Parkes, Mr. Francis \"Frank\" 0 NaN \n", "581 2.0 0.0 Watson, Mr. Ennis Hastings 0 NaN \n", "896 3.0 0.0 Johnson, Mr. Alfred 0 49.0 \n", "898 3.0 0.0 Johnson, Mr. William Cahoone Jr 0 19.0 \n", "963 3.0 0.0 Leonard, Mr. Lionel 0 36.0 \n", "1254 3.0 1.0 Tornquist, Mr. William Henry 0 25.0 \n", "\n", " sibsp parch ticket fare cabin embarked boat body \\\n", "7 0.0 0.0 112050 0.0 A36 S NaN NaN \n", "70 0.0 0.0 112051 0.0 Unknown S NaN NaN \n", "125 0.0 0.0 112058 0.0 B102 S NaN NaN \n", "150 0.0 0.0 112059 0.0 B94 S NaN 110.0 \n", "170 0.0 0.0 112058 0.0 B52 B54 B56 S C NaN \n", "223 0.0 0.0 112052 0.0 Unknown S NaN NaN \n", "234 0.0 0.0 19972 0.0 Unknown S NaN NaN \n", "363 0.0 0.0 239853 0.0 Unknown S NaN NaN \n", "384 0.0 0.0 239853 0.0 Unknown S NaN NaN \n", "410 0.0 0.0 239854 0.0 Unknown S NaN NaN \n", "473 0.0 0.0 239855 0.0 Unknown S NaN NaN \n", "528 0.0 0.0 239853 0.0 Unknown S NaN NaN \n", "581 0.0 0.0 239856 0.0 Unknown S NaN NaN \n", "896 0.0 0.0 LINE 0.0 Unknown S NaN NaN \n", "898 0.0 0.0 LINE 0.0 Unknown S NaN NaN \n", "963 0.0 0.0 LINE 0.0 Unknown S NaN NaN \n", "1254 0.0 0.0 LINE 0.0 Unknown S 15 NaN \n", "\n", " home.dest \n", "7 Belfast, NI \n", "70 Liverpool, England / Belfast \n", "125 NaN \n", "150 NaN \n", "170 Liverpool \n", "223 Belfast \n", "234 Rotterdam, Netherlands \n", "363 Belfast \n", "384 Belfast \n", "410 Belfast \n", "473 Belfast \n", "528 Belfast \n", "581 Belfast \n", "896 NaN \n", "898 NaN \n", "963 NaN \n", "1254 NaN " ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Ile znajdziemy wierszy z opłatą == 0 ?\n", "# Filtrujemy wiersze, gdzie wartość w kolumnie 'fare' wynosi 0\n", "fare_zero = df[df['fare'] == 0]\n", "\n", "# Liczenie liczby wierszy w kolumnie 'fare'\n", "number_of_fare_zero = fare_zero['fare'].count()\n", "print(f\"Liczba wierszy z ceną za bilet równą 0 dollars: {number_of_fare_zero}\")\n", "fare_zero" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Opis statystyczny" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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pclasssurvivedsexagesibspparchfareembarkedbody
count1307.0000001307.0000001307.0000001044.0000001307.0000001307.0000001306.0000001305.000000121.000000
mean2.2938030.3825550.35577729.8674970.4996170.38561633.3344622.492720160.809917
std0.8380220.4861970.47893114.4206801.0422730.86609251.7887120.81501597.696922
min1.0000000.0000000.0000000.1667000.0000000.0000000.0000001.0000001.000000
25%2.0000000.0000000.00000021.0000000.0000000.0000007.8958002.00000072.000000
50%3.0000000.0000000.00000028.0000000.0000000.00000014.4542003.000000155.000000
75%3.0000001.0000001.00000039.0000001.0000000.00000031.2750003.000000256.000000
max3.0000001.0000001.00000080.0000008.0000009.000000512.3292003.000000328.000000
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" ], "text/plain": [ " pclass survived sex age sibsp \\\n", "count 1307.000000 1307.000000 1307.000000 1044.000000 1307.000000 \n", "mean 2.293803 0.382555 0.355777 29.867497 0.499617 \n", "std 0.838022 0.486197 0.478931 14.420680 1.042273 \n", "min 1.000000 0.000000 0.000000 0.166700 0.000000 \n", "25% 2.000000 0.000000 0.000000 21.000000 0.000000 \n", "50% 3.000000 0.000000 0.000000 28.000000 0.000000 \n", "75% 3.000000 1.000000 1.000000 39.000000 1.000000 \n", "max 3.000000 1.000000 1.000000 80.000000 8.000000 \n", "\n", " parch fare embarked body \n", "count 1307.000000 1306.000000 1305.000000 121.000000 \n", "mean 0.385616 33.334462 2.492720 160.809917 \n", "std 0.866092 51.788712 0.815015 97.696922 \n", "min 0.000000 0.000000 1.000000 1.000000 \n", "25% 0.000000 7.895800 2.000000 72.000000 \n", "50% 0.000000 14.454200 3.000000 155.000000 \n", "75% 0.000000 31.275000 3.000000 256.000000 \n", "max 9.000000 512.329200 3.000000 328.000000 " ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df2.describe()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1.1.1. Podsumowanie wstępnej analizy i transformacji zbioru danych" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Zbiór pierwotnie składa się z 1310 wierszy i 14 kolumn.\n", "Elementy zbioru, które zostały usunięte:\n", "- ostatni wiersz 1309 ze zbioru składa się wyłącznie z wartości NaN\n", "- te wiersze, które duplikują nazwiska i mają najwięcej kolumn z NaN. Usunięcie wierszy 726 i 925.\n", "Ostatecznie pozostało 1307 rekordów.\n", "\n", "Najwięcej brakujących wartości NaN jest w kolumnach: \n", "- age 20%\n", "- cabin 77%\n", "- boat 63%\n", "- body 91%\n", "- home.dest 43%\n", "\n", "Zbadano jaki jest powód brakujących wartości NaN:\n", "- kolumna 'age' zawiera 623 NaN. Po sprawdzeniu nie znalazłem wartości anormalnych lub błędnych. Wartości w kolumnie 'age' są naturalne dla wieku ludzi. Nie zastępowałem Nan innymi wartościami.\n", "- kolumna 'body' zawiera 1186 NaN, co jest prawidłowe i zgodne z obliczoną liczbą 121 znalezionych ciał na 1307 pasażerów. Kolumna body ma 121 numerów ciał. Pomimo najwyższej liczby 328, nie oznacza to, że było 328 odnalezionych ciał. Posortowanie w kolejności rosnącej pokazało brakujące numery. Poza tym sprawdziłem, że dane w kolumnie body nie stoją w sprzeczności z kolumną survived.\n", "- kolumna 'boat'. Według Wikipedii na „Titanicu” było 20 szalup. Rozwiązaniem było zastąpienie błędnego oznaczenia, przez przyjęcie pierwszego znaku i zignorowanie ciągu dalszych znaków za spacją.\n", "- kolumna 'cabin' Skrócono długie ciągi znaków typu 'B57 B59 B63 B66'.\n", "- kolumny 'embarked' i 'sex' zmapowano objekty na wartości numeryczne ({'C': 1, 'Q': 2, 'S': 3} oraz {'male': 0, 'female': 1}).\n", "\n", "\n", "- Ilosc kobiet 465 ,Liczba mężczyzn 842 (w tym Liczba wierszy mężczyzn bez tytułu Mr. z przodu nazwiska: 85)\n", "- Przeanalizowano wszystkie kabiny z długim oznaczeniem wskazującym na zajmowanie wielu kabin względem sibsp i parch. Przypisane były nie tylko do wielu osób np. rodzin, ale też do osób samotnie podróżujących.\n", "- Kolumna parch pokazała, że większość osób (1000) podróżowała bez osób spokrewnionych. Z jednym rodzicem albo jednym dzieckiem jest 170 osób. Z dwójką dzieci lub dwojgiem rodziców jest 113 wpisów. Liczba osób należących do rodzin: 519. Liczba unikalnych nazwisk (bez powtórzeń): 209.\n", "- Przyporządkowanie osób do cabin: Całkowita liczba osób we wszystkich szalupach: 486. Najwiecej osób w szalupie: 39. Najmniej osób w szalupie: 1\n", "- Liczba wierszy z ceną za bilet równą 0 dollars: 17" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1.2. Wizualizacja" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import seaborn as sns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Wykres wartości NaN" ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Wykres brakow NaN powyżej 20% w wybranych kolumnach\n", "braki_powyzej_20 = braki_srednia_logiczna[braki_srednia_logiczna > 20]\n", "# Wykres słupkowy tylko dla kolumn z NaN powyżej 20%\n", "plt.figure(figsize=(8, 6))\n", "plt.bar(braki_powyzej_20.index, braki_powyzej_20.values, color='skyblue')\n", "\n", "plt.title('Procent najwięcej brakujących wartości (NaN) > 20%', fontsize=14)\n", "plt.xlabel('Kolumna', fontsize=12)\n", "plt.ylabel('Procent NaN', fontsize=12)\n", "\n", "# Wyświetlenie wykresu\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Macierz korelacji" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "correlation_matrix = df2[['pclass','survived','sex','age','sibsp','parch','fare','embarked','body']].corr()\n", "plt.figure(figsize=(8, 6))\n", "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt='.2f', square=True)\n", "plt.title('Macierz korelacji')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "Macierz korelacji jest bazą dla wykonania wykresów:\n", "- pclass vs. survived/age/fare/embarked/sex\n", "- survived vs. sex/fare/embarked\n", "- sex vs. sibsp/parch/fare\n", "- age vs. sibsp/parch/fare\n", "- sibsp vs. parch/fare/body\n", "- parch vs. fare\n", "- fare vs. embarked" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### pclass vs. survived - histogram dla ofiar" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Przygotowanie wykresu\n", "plt.figure(figsize=(10, 6))\n", "sns.histplot(df2['pclass'][df2['survived'] == 0].dropna(), bins=3, discrete=True)\n", "\n", "plt.title('Histogram dla pclass ofiar katastrofy')\n", "plt.xlabel('pclass')\n", "plt.ylabel('Ilość osób')\n", "\n", "# Ustalenie podziałek na osi x\n", "plt.xticks([1, 2, 3])\n", "\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- Najwięcej ofiar kupiło bilet klasy 3, najmniej - klasy 1." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### pclass vs. survived - histogram dla szczęściarzy" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10,6))\n", "sns.histplot(df2['pclass'][df2['survived'] == 1].dropna())\n", "plt.title('Histogram dla pclass szczęściarzy')\n", "plt.xlabel('pclass')\n", "plt.ylabel('Ilość osób')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- Najwięcej szczęściarzy kupiło bilet klasy 1 i 3, najmniej szczęściarzy kupiło bilety w klasie\n", "- W klasach pclass 1,2,3 było uratowanych odpowiednio: 200,119,181" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### pclass vs. liczba pasażerów - histogram" ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# ile pasażerów do klasy biletu\n", "policz = df2['pclass'].value_counts()\n", "policz.plot(kind='bar')\n", "plt.title('Liczba pasażerów według klasy')\n", "plt.xlabel('Klasa biletu')\n", "plt.ylabel('Liczba pasażerów')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski\n", "- Najwięcej pasażerów podróżowało z biletem klasy 3, potem 1 i 2." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### survived vs. age - histogram dla uratowanych" ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Ilość osób')" ] }, "execution_count": 70, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# wykres w jakim wieku byli szczęśliwcy\n", "# Wydobycie kolumny z wiekiem\n", "szczęściarze = df2[df2['survived'] == 1]\n", "wiek_szczęściarzy = szczęściarze['age']\n", "\n", "# Tworzenie wykresu słupkowego dla wieku\n", "plt.figure(figsize=(10,6))\n", "wiek_szczęściarzy.value_counts().sort_index().plot(kind='bar')\n", "\n", "# Ustawienia osi i tytuł wykresu\n", "plt.title('Wiek szczęściarzy')\n", "plt.xlabel('Wiek')\n", "plt.ylabel('Ilość osób')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski\n", "- Najwyższe słupki na wykresie pozwalają odczytać, że katastrofę Titanica najwięcej przeżyło osób w sile wieku tj. 24, 22, 30 latków." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### survived vs. age - histogram dla ofiar" ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10,6))\n", "sns.histplot(df2[df2['survived'] == 0]['age'].dropna(), bins=20, kde=False)\n", "plt.title('Histogram dla wieku ofiar katastrofy')\n", "plt.xlabel('Wiek')\n", "plt.ylabel('Ilość osób')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### survived vs. age - box chart" ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df2['survived'] = df2['survived'].replace({0: 'Nie', 1: 'Tak'})\n", "sns.boxplot(df2, x='survived', y='age')\n", "plt.title('Rozkład wieku pasażerów według przeżycia')\n", "plt.xlabel('Przeżycie (Tak-przeżyli, Nie- zginęli)')\n", "plt.ylabel('Wiek')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski\n", "- Rozkład wartosci dla wieku pasażerów, którzy zginęli jest identyczny z rozkładem dla wieku tych co przeżyli." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### survived: pie chart in percent" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df2['survived'] = df2['survived'].replace({0: 'Nie', 1: 'Tak'})\n", "df2['survived'].value_counts().plot(kind='pie', autopct='%1.1f%%', labels=['Zginęli', 'Przeżyli'])\n", "plt.title('Procent pasażerów, którzy przeżyli')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski\n", "- W katastrofie zginęło 62 %, przeżyło 38% pasażerów." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### survived vs. sex - pie chart" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df2['sex'] = df2['sex'].replace({0: 'mężczyźni', 1: 'kobiety'})\n", "survived_sex = df2.groupby(['sex', 'survived']).size().unstack()\n", "fig, axes = plt.subplots(1, 2, figsize=(12, 6))\n", "\n", "for i, sex in enumerate(survived_sex.index):\n", " axes[i].pie(survived_sex.loc[sex], labels=['Nie przeżył', 'Przeżył'], autopct='%1.1f%%', startangle=90)\n", " axes[i].set_title(f'Płeć: {sex}')\n", "\n", "plt.suptitle('Przeżycie względem płci')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- Katastrofę przeżyło więcej kobiet, najmnniej szans mieli meżczyźni. Powodem było, że pierwszeństwo do szalup miały kobiety i dzieci." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### age: box chart" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 75, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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/59lsNt+2r3K73XK5XH4LAAAYuAJ628Xr9WrSpElatmyZJOnSSy9VQ0OD1q1bp7lz5/ZogIqKCi1durRHzwUAAP1PQGc+UlJSdPHFF/utu+iii3T06FFJUnJysiTJ4XD47eNwOHzbvqq8vFxOp9O3tLS0BDISAADoZwKKjyuuuEKNjY1+6z744AONHTtW0pcXnyYnJ6umpsa33eVyae/evcrNze32mLGxsbJYLH4LAAAYuAJ626W0tFRTp07VsmXLdP311+utt97Sk08+qSeffFKSFBERoYULF+qhhx7S+eefr4yMDC1evFipqakqLCwMxfwAAKCfCSg+Lr/8cr300ksqLy/Xgw8+qIyMDK1Zs0Y333yzb5977rlH7e3tuu2229Ta2qpp06Zpx44diouLC/rwAACg/4no6urqCvcQ/5vL5ZLVapXT6eQtGGCAafjYqWse363tC6Yp+1xruMcBEESBvH7z3S4AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGBRQfv/71rxUREeG3ZGVl+bZ3dHSopKRESUlJSkxMVHFxsRwOR9CHBgAA/VfAZz4uueQSHT9+3Lfs3r3bt620tFTbtm3Tli1btGvXLh07dkxFRUVBHRgAAPRv0QE/ITpaycnJX1vvdDq1YcMGbdq0STNmzJAkbdy4URdddJH27NmjKVOm9H5aAADQ7wV85qOpqUmpqak677zzdPPNN+vo0aOSpPr6ep0+fVr5+fm+fbOysjRmzBjV1dV94/HcbrdcLpffAgAABq6A4mPy5Ml66qmntGPHDq1du1bNzc3Ky8tTW1ub7Ha7YmJiNGzYML/n2Gw22e32bzxmRUWFrFarb0lLS+vRLwIAAPqHgN52mTlzpu/P48eP1+TJkzV27Fi98MILio+P79EA5eXlKisr8z12uVwECAAAA1ivPmo7bNgwXXDBBTp06JCSk5PV2dmp1tZWv30cDke314icERsbK4vF4rcAAICBq1fxcerUKR0+fFgpKSmaOHGihgwZopqaGt/2xsZGHT16VLm5ub0eFAAADAwBve1y1113adasWRo7dqyOHTumBx54QFFRUZozZ46sVqvmz5+vsrIyjRgxQhaLRQsWLFBubi6fdAEAAD4BxcdHH32kOXPm6NNPP9XIkSM1bdo07dmzRyNHjpQkrV69WpGRkSouLpbb7VZBQYGqqqpCMjgAAOifAoqPzZs3f+v2uLg4VVZWqrKysldDAQCAgYvvdgEAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRvYqP3/72t4qIiNDChQt96zo6OlRSUqKkpCQlJiaquLhYDoejt3MCAIABosfxsW/fPj3xxBMaP3683/rS0lJt27ZNW7Zs0a5du3Ts2DEVFRX1elAAADAw9Cg+Tp06pZtvvlnr16/X8OHDfeudTqc2bNigVatWacaMGZo4caI2btyoN998U3v27Ana0AAAoP/qUXyUlJToxz/+sfLz8/3W19fX6/Tp037rs7KyNGbMGNXV1XV7LLfbLZfL5bcAAICBKzrQJ2zevFlvv/229u3b97VtdrtdMTExGjZsmN96m80mu93e7fEqKiq0dOnSQMcAAAD9VEBnPlpaWvSrX/1Kzz33nOLi4oIyQHl5uZxOp29paWkJynEBAEDfFFB81NfX68SJE7rssssUHR2t6Oho7dq1S4899piio6Nls9nU2dmp1tZWv+c5HA4lJyd3e8zY2FhZLBa/BQAADFwBve3ywx/+UAcPHvRbN2/ePGVlZenee+9VWlqahgwZopqaGhUXF0uSGhsbdfToUeXm5gZvagBnpflku9rdX4R7DJ9DJ075/bcvSYiNVsY5CeEeAxgUAoqPoUOHKjs7229dQkKCkpKSfOvnz5+vsrIyjRgxQhaLRQsWLFBubq6mTJkSvKkBfKfmk+2avvL1cI/RrYXPHwj3CN167a4rCRDAgIAvOP0uq1evVmRkpIqLi+V2u1VQUKCqqqpg/xgA3+HMGY81N0xQ5qjEME/zpY7THn302ecaPTxecUOiwj2Oz6ETp7Tw+QN96iwRMJD1Oj5ef/11v8dxcXGqrKxUZWVlbw8NIAgyRyUq+1xruMfwmZQe7gkAhBvf7QIAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYRXwAAACjiA8AAGAU8QEAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYRXwAAACjiA8AAGAU8QEAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYRXwAAACjiA8AAGAU8QEAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYRXwAAACjAoqPtWvXavz48bJYLLJYLMrNzdUrr7zi297R0aGSkhIlJSUpMTFRxcXFcjgcQR8aAAD0XwHFx+jRo/Xb3/5W9fX12r9/v2bMmKFrr71W//3f/y1JKi0t1bZt27Rlyxbt2rVLx44dU1FRUUgGBwAA/VN0IDvPmjXL7/HDDz+stWvXas+ePRo9erQ2bNigTZs2acaMGZKkjRs36qKLLtKePXs0ZcqU4E0NAAD6rR5f8+HxeLR582a1t7crNzdX9fX1On36tPLz8337ZGVlacyYMaqrq/vG47jdbrlcLr8FAAAMXAHHx8GDB5WYmKjY2Fjdfvvteumll3TxxRfLbrcrJiZGw4YN89vfZrPJbrd/4/EqKipktVp9S1paWsC/BAAA6D8Cjo8LL7xQBw4c0N69e/WLX/xCc+fO1bvvvtvjAcrLy+V0On1LS0tLj48FAAD6voCu+ZCkmJgYZWZmSpImTpyoffv26Xe/+51uuOEGdXZ2qrW11e/sh8PhUHJy8jceLzY2VrGxsYFPDgAA+qVe3+fD6/XK7XZr4sSJGjJkiGpqanzbGhsbdfToUeXm5vb2xwAAgAEioDMf5eXlmjlzpsaMGaO2tjZt2rRJr7/+unbu3Cmr1ar58+errKxMI0aMkMVi0YIFC5Sbm8snXQAAgE9A8XHixAn95Cc/0fHjx2W1WjV+/Hjt3LlTV111lSRp9erVioyMVHFxsdxutwoKClRVVRWSwQEAQP8UUHxs2LDhW7fHxcWpsrJSlZWVvRoKAAAMXAFfcAqgf3B7OhQZ97GaXY2KjEsM9zh9WrPrlCLjPpbb0yHJGu5xgAGP+AAGqGPtHyoh43Eteivck/QPCRnSsfYJmihbuEcBBjziAxigUhPGqr15gX53wwSNG8WZj29z+MQp/er5A0qdPjbcowCDAvEBDFCxUXHydpyrDMuFujiJtxK+jbfDKW/HJ4qNigv3KMCg0Ov7fAAAAASC+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADCK+AAAAEZFh3sAAKHx+WmPJKnhY2eYJ/kfHac9+uizzzV6eLzihkSFexyfQydOhXsEYFAJKD4qKipUXV2t999/X/Hx8Zo6daqWL1+uCy+80LdPR0eH7rzzTm3evFlut1sFBQWqqqqSzWYL+vAAvtnh//+Cel/1wTBP0n8kxPLvMcCEgP5P27Vrl0pKSnT55Zfriy++0KJFi3T11Vfr3XffVUJCgiSptLRUL7/8srZs2SKr1ao77rhDRUVFeuONN0LyCwDo3tWXJEuSxo1KVHwfOctw6MQpLXz+gNbcMEGZoxLDPY6fhNhoZZyTEO4xgEEhoqurq6unT/7kk080atQo7dq1S//4j/8op9OpkSNHatOmTZo9e7Yk6f3339dFF12kuro6TZky5TuP6XK5ZLVa5XQ6ZbFYejoagD6o4WOnrnl8t7YvmKbsc63hHgdAEAXy+t2rC06dzi/fSx4xYoQkqb6+XqdPn1Z+fr5vn6ysLI0ZM0Z1dXXdHsPtdsvlcvktAABg4OpxfHi9Xi1cuFBXXHGFsrOzJUl2u10xMTEaNmyY3742m012u73b41RUVMhqtfqWtLS0no4EAAD6gR7HR0lJiRoaGrR58+ZeDVBeXi6n0+lbWlpaenU8AADQt/Xo0u477rhD27dv15///GeNHj3atz45OVmdnZ1qbW31O/vhcDiUnJzc7bFiY2MVGxvbkzEAAEA/FNCZj66uLt1xxx166aWX9Kc//UkZGRl+2ydOnKghQ4aopqbGt66xsVFHjx5Vbm5ucCYGAAD9WkBnPkpKSrRp0yb9x3/8h4YOHeq7jsNqtSo+Pl5Wq1Xz589XWVmZRowYIYvFogULFig3N/esPukCAAAGvoDiY+3atZKkK6+80m/9xo0b9dOf/lSStHr1akVGRqq4uNjvJmMAAABSgPFxNrcEiYuLU2VlpSorK3s8FAAAGLj4YjkAAGAU8QEAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYRXwAAACjiA8AAGAU8QEAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYRXwAAACjiA8AAGAU8QEAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYRXwAAACjiA8AAGAU8QEAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYFXB8/PnPf9asWbOUmpqqiIgIbd261W97V1eXlixZopSUFMXHxys/P19NTU3BmhcAAPRzAcdHe3u7vve976mysrLb7StWrNBjjz2mdevWae/evUpISFBBQYE6Ojp6PSwAAOj/ogN9wsyZMzVz5sxut3V1dWnNmjW6//77de2110qSnnnmGdlsNm3dulU33nhj76YFAAD9XlCv+Whubpbdbld+fr5vndVq1eTJk1VXV9ftc9xut1wul98CAAAGrqDGh91ulyTZbDa/9TabzbftqyoqKmS1Wn1LWlpaMEcCAAB9TNg/7VJeXi6n0+lbWlpawj0SAAAIoaDGR3JysiTJ4XD4rXc4HL5tXxUbGyuLxeK3AACAgSuo8ZGRkaHk5GTV1NT41rlcLu3du1e5ubnB/FEAAKCfCvjTLqdOndKhQ4d8j5ubm3XgwAGNGDFCY8aM0cKFC/XQQw/p/PPPV0ZGhhYvXqzU1FQVFhYGc24AANBPBRwf+/fv1/Tp032Py8rKJElz587VU089pXvuuUft7e267bbb1NraqmnTpmnHjh2Ki4sL3tQAAKDfCjg+rrzySnV1dX3j9oiICD344IN68MEHezUYAAAYmML+aRcAADC4EB8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUcQHAAAwivgAAABGER8AAMAo4gMAABhFfAAAAKOIDwAAYBTxAQAAjCI+AACAUSGLj8rKSqWnpysuLk6TJ0/WW2+9FaofBQAA+pGQxMfzzz+vsrIyPfDAA3r77bf1ve99TwUFBTpx4kQofhwAAOhHokNx0FWrVulnP/uZ5s2bJ0lat26dXn75Zf37v/+77rvvvlD8SAAh9HmnR4c/OdXr4xw6ccrvv8EwbmSi4mOignY8AKEX9Pjo7OxUfX29ysvLfesiIyOVn5+vurq6r+3vdrvldrt9j10uV7BHAtBLhz85pWse3x204y18/kDQjrV9wTRln2sN2vEAhF7Q4+PkyZPyeDyy2Wx+6202m95///2v7V9RUaGlS5cGewwAQTRuZKK2L5jW6+N0nPboo88+1+jh8YobEpyzFeNGJgblOADMCcnbLoEoLy9XWVmZ77HL5VJaWloYJwLwVfExUUE7uzApPSiHAdCPBT0+zjnnHEVFRcnhcPitdzgcSk5O/tr+sbGxio2NDfYYAACgjwr6p11iYmI0ceJE1dTU+NZ5vV7V1NQoNzc32D8OAAD0MyF526WsrExz587VpEmT9P3vf19r1qxRe3u779MvAABg8ApJfNxwww365JNPtGTJEtntdk2YMEE7duz42kWoAABg8Ino6urqCvcQ/5vL5ZLVapXT6ZTFYgn3OAAA4CwE8vrNd7sAAACjiA8AAGAU8QEAAIwiPgAAgFHEBwAAMIr4AAAARhEfAADAKOIDAAAYFfZvtf2qM/c8c7lcYZ4EAACcrTOv22dz79I+Fx9tbW2SpLS0tDBPAgAAAtXW1iar1fqt+/S526t7vV4dO3ZMQ4cOVURERLjHARBELpdLaWlpamlp4esTgAGmq6tLbW1tSk1NVWTkt1/V0efiA8DAxXc3AZC44BQAABhGfAAAAKOIDwDGxMbG6oEHHlBsbGy4RwEQRlzzAQAAjOLMBwAAMIr4AAAARhEfAADAKOIDAAAYRXwAAACjiA8AAGAU8QGg13bs2KFp06Zp2LBhSkpK0jXXXKPDhw/7tr/55puaMGGC4uLiNGnSJG3dulURERE6cOCAb5+GhgbNnDlTiYmJstlsuuWWW3Ty5Mkw/DYAQo34ANBr7e3tKisr0/79+1VTU6PIyEj90z/9k7xer1wul2bNmqWcnBy9/fbb+s1vfqN7773X7/mtra2aMWOGLr30Uu3fv187duyQw+HQ9ddfH6bfCEAocZMxAEF38uRJjRw5UgcPHtTu3bt1//3366OPPlJcXJwk6fe//71+9rOf6S9/+YsmTJighx56SLW1tdq5c6fvGB999JHS0tLU2NioCy64IFy/CoAQ4MwHgF5ramrSnDlzdN5558lisSg9PV2SdPToUTU2Nmr8+PG+8JCk73//+37Pf+edd/Taa68pMTHRt2RlZUmS39s3AAaG6HAPAKD/mzVrlsaOHav169crNTVVXq9X2dnZ6uzsPKvnnzp1SrNmzdLy5cu/ti0lJSXY4wIIM+IDQK98+umnamxs1Pr165WXlydJ2r17t2/7hRdeqGeffVZut9v3hXL79u3zO8Zll12mP/7xj0pPT1d0NH8tAQMdb7sA6JXhw4crKSlJTz75pA4dOqQ//elPKisr822/6aab5PV6ddttt+m9997Tzp07tXLlSklSRESEJKmkpER/+9vfNGfOHO3bt0+HDx/Wzp07NW/ePHk8nrD8XgBCh/gA0CuRkZHavHmz6uvrlZ2drdLSUj3yyCO+7RaLRdu2bdOBAwc0YcIE/eu//quWLFkiSb7rQFJTU/XGG2/I4/Ho6quvVk5OjhYuXKhhw4YpMpK/poCBhk+7ADDuueee07x58+R0OhUfHx/ucQAYxpurAELumWee0Xnnnadzzz1X77zzju69915df/31hAcwSBEfAELObrdryZIlstvtSklJ0XXXXaeHH3443GMBCBPedgEAAEZxJRcAADCK+AAAAEYRHwAAwCjiAwAAGEV8AAAAo4gPAABgFPEBAACMIj4AAIBRxAcAADDq/wEZg2YhkzwprQAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df2['age'].plot(kind='box')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### age vs. sex: box chart" ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 76, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.boxplot(x='sex', y='age', data=df2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### WNioski:\n", "- Wiek ofiar i uratowanych z poddziałem na płeć ma bardzo podobny rozkład." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### age: histogram" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df2['age'].hist(bins=11)\n", "plt.xlabel('age') \n", "plt.ylabel('częstość wystąpienia') \n", "plt.title('Histogram dla Wieku')\n", "plt.grid(False)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek\n", "- Największa ilość pasażerów była w wieku od 20 do 30." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### age vs. pclass box chart" ] }, { "cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Tworzenie czytelnego wykresu z trzema osiami obok siebie\n", "fig, axes = plt.subplots(1, 3, figsize=(15, 5))\n", "\n", "df3 = df2[['pclass', 'age']]\n", "# tworzenie wykresu pudełkowego dla klasy 1\n", "filtrowanie_1 = df3[df3['pclass'] == 1.0]\n", "filtrowanie_1[['age']].boxplot(ax=axes[0])\n", "axes[0].set_title('Box Plot dla 1. klasy')\n", "axes[0].set_xlabel('')\n", "axes[0].set_ylabel('Wiek')\n", "# tworzenie wykresu pudełkowego dla klasy 2\n", "filtrowanie_2 = df3[df3['pclass'] == 2.0]\n", "filtrowanie_2[['age']].boxplot(ax=axes[1])\n", "axes[1].set_title('Box Plot dla 2. klasy')\n", "axes[1].set_xlabel('')\n", "# tworzenie wykresu pudełkowego dla klasy 3\n", "filtrowanie_3 = df3[df3['pclass'] == 3.0]\n", "filtrowanie_3[['age']].boxplot(ax=axes[2])\n", "axes[2].set_title('Box Plot dla 3. klasy')\n", "axes[2].set_xlabel('')\n", "# Ustawienia odstępów między wykresami\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### age vs. pclass - inny Wykres pudełkowy" ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.boxplot(df2, x='pclass', y='age')\n", "plt.title('Rozkład wieku według klasy')\n", "plt.xlabel('klasa biletu')\n", "plt.ylabel('cena')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek\n", "- Mediana i wartość Max. dla wieku pokazują, że najlepszą 1. klasę wybierali starsi pasażerowie. Pojedyncze starsze osoby wybierały też klasy niższe 2 i 3. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### sibsp: bar chart dla liczby osób podróżujących bez towarzystwa bliskich*" ] }, { "cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [], "source": [ "# Sprawdzenie typu danych w kolumnie \n", "df2['sibsp'].dtype\n", "# Zamiana kolumny 'sibsp' z float na integer bez zaokrąglania\n", "df2['sibsp'] = df2['sibsp'].astype(int)" ] }, { "cell_type": "code", "execution_count": 132, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Ustawienie stylu Seaborn\n", "sns.set(style=\"whitegrid\")\n", "\n", "# Wykres słupkowy\n", "plt.figure(figsize=(10, 6))\n", "\n", "# Zliczanie wystąpień liczby rodziców dzieci\n", "sns.countplot(data=df2, x='sibsp', palette='viridis', hue=x)\n", "\n", "plt.title('Wykres słupkowy: Liczba rodzeństwa/małżonków na pokładzie')\n", "plt.xlabel('Liczba rodzeństwa/małżonków na pokładzie')\n", "plt.ylabel('Liczba pasażerów')\n", "plt.xticks(rotation=45) # Umożliwienie rotacji etykiet, jeśli to konieczne\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek\n", "- Najwięcej pasażerów było bez osób towarzyszących typu rodzeństwo czy małżonek. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### parch: bar chart dla liczby osób podróżujących bez towarzystwa bliskich*" ] }, { "cell_type": "code", "execution_count": 135, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Sprawdzenie typu danych w kolumnie \n", "df2['parch'].dtype\n", "# Zamiana kolumny 'parch' z float na integer bez zaokrąglania\n", "df2['parch'] = df2['parch'].astype(int)\n", "# Ustawienie stylu Seaborn\n", "sns.set(style=\"whitegrid\")\n", "\n", "# Wykres słupkowy\n", "plt.figure(figsize=(10, 6))\n", "\n", "# Zliczanie wystąpień liczby rodziców dzieci\n", "sns.countplot(data=df2, x='parch', palette='viridis', hue=x)\n", "\n", "plt.title('Wykres słupkowy: Liczba rodziców/dzieci na pokładzie')\n", "plt.xlabel('Liczba rodziców/dzieci na pokładzie')\n", "plt.ylabel('Liczba pasażerów')\n", "plt.xticks(rotation=45) # Umożliwienie rotacji etykiet, jeśli to konieczne\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek\n", "- Najwięcej pasażerów było bez osób towarzyszących typu rodzice / dzieci. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### parch: liczba rodzin wśród wszystkich pasażerów" ] }, { "cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "liczba osob z rodzina: 307\n", "Liczba osób bez rodziny: 1000\n" ] }, { "data": { "image/png": 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aiMdcrlmzZiE8PBxTpkwRHytBELBkyRIAwJAhQ9CsWTO0b98e27Ztg7q6OmJiYnD69GmsW7cOr1+/FuuNjIwU68mlpKT0ySHIwr5+Ll++DCsrK2hoaIivSW1tbbRu3Vp8X/m347AaFSh3bL0wE109PT3x119/YcuWLdDV1c2zvmbNmnK3c0/PJiUlAQAOHToEb29vvHjxAtWqVUOTJk2goaFRqDo/vr/cenP7Pn/+PJYuXYoHDx6gUqVKMDExgZaWFgCIc6d8fHywfv16/Pbbbzh+/DiUlJTQtm1bLFq0CHXq1EFaWho8PT1x8OBBZGVl4euvv0aLFi2goqIi9pErOjoa7u7u6NatGyZNmiQuz308Fy5ciIULF+bZj/j4eLnblSpVEn/O3ZdatWrJtVFRUYGOjg7evn0LAOjUqRMWLVqE9PR0XLp0CVZWVrCysoKPjw+eP3+O8+fPw9zcvMDT469evcLEiRPRoEGDfGvNT+5jKq354+cd+PBaEAQBKSkpSEpKQrVq1fKEnI/3EwBycnLg5uaG+Ph47N27V+7xyc/HwyW595E7r0WR57QoPt6Hj1+XAMQhko99/Foo6Pj62MePTVJSEnR0dKCsrJxvjW/fvhXr0tHR+ex+5Dp69CjWr18Pd3d3tG3btsCaPj6elZSU5B5ne3t7rF+/HidOnECbNm1w6dIleHl5Fdjvx8/zx/3eunULCxcuxK1bt6CpqYlGjRqJw1kFPc8fP9ZKSkrQ0dFBUlKSeDx/6jV+584duWVxcXFo2rSpOO+rUqVKePv2LR49eiTXLicnB97e3ti+fTvev38PfX19mJubQ11dXWyj6HNV2NfPmzdv8Ouvv+LXX3/Ns660LngoawxHVKAqVaoA+DBZuUGDBuLy58+f4/Hjx2jVqhVUVVWxbds27Ny5E4sWLRLPtHxM+gsBgDhhskaNGoiMjIS7uzscHR0xZswY8eBduXJlnsm7+UlMTJS7/erVK7Hvx48fw9nZGV27dsWGDRtQt25dyGQybN++HefPnxe3qVy5MmbOnImZM2fiwYMHOH36NNauXYuFCxdi48aNWLJkCY4fPw5fX1+0bdtWDAK58yNyvX79GpMmTcLXX3+d58xG7uM5a9YsWFlZ5dmPqlWrfnIfc9e9fPkSderUEZdnZmYiMTFRfJPs1KkTMjIyEBkZifDwcHh4eMDMzAxaWlqIiIjAuXPnCpw7lJGRAWdnZ3ECr/RNWRFVq1aVmxib6+XLlwA+vLHr6OggMTER2dnZcr+4P570CgCrVq3C+fPnsWHDBtSrV69INUkV9jktqs+95nPPTHl5eaF+/fp5tpX+wi3M8VWQqlWr5vs454aw3OcC+N/xkyu/5+LmzZv48ccf0bt3b4wePbpINX2sbt26sLKywm+//YY3b95AW1sbXbt2/aI+U1JSMHbsWPHCjQYNGkBJSQlnz57F8ePHC9z+4/eW7OxsJCYmonr16qhWrRoAfPI1/nFwCQgIgKamJvr16wcfHx94eHhAW1sb69atg6mpqdhu48aNCAkJwcKFC9G9e3fxzJV0fl1u3wkJCXLzlvJ7rhR5/VSuXBlt27bFqFGj8qxTUflvxAYOq1GBzM3NoaqqKg5B5QoKCoKbmxuUlZVx8eJFLFu2DIMGDcKgQYM+2deZM2fkbh89ehT6+vqoV68erl27hpycHEyZMkUMRtnZ2eJp3M9dOQR8uPpL6vjx49DU1ETz5s1x+/ZtpKenY/z48TAwMBDDSm4wEgQBz549Q6dOnXDs2DEAQIMGDTBu3Di0bdtWvJrk6tWrsLa2RteuXcVfordv38br16/F+rKysjB16lS8e/cOgYGBef56b9CgAWrUqIGnT5/CzMxM/Kerq4vVq1fn+UtTKjdMHT16NM/jmJ2djVatWgH48JejqakpQkND8fr1a1hZWUFVVRWtWrXC7t278ejRozzDJh9bsGABbt++DT8/vy+6ZN3S0hJ//PGH3OTd7OxsHD16FGZmZlBTU4ONjQ2ysrLknsOMjIw8w0r79+9HUFAQXF1d0bFjxyLXJFWY5/RL5Peaz31dNm/eHKqqqoiLi5N7LaioqMDb21u86q6wx1dBrKyskJWVJb7Gc+UOL7Vq1Qr169eHvr5+njYfH/9xcXFwdnZGgwYNxCGh4tK/f39cvHgRR44cQc+ePYsczHM9ePAAb968wfDhw9GoUSMoKX341Zd71WJBz/O5c+fkht5Onz6NrKws2NjYwNDQELVq1crzQaxPnjzB9evX8wSRmjVrwtjYGCNHjsT27dtx48YNKCkp5Tmbd/XqVTRq1Aj29vZiMIqLi8O9e/fEetu0aQMABT5Xir5+rKysEBMTgyZNmoivyWbNmiEkJKREP56kPPlvREDKIzY2FiEhIXmWGxkZ5Tk1Xr16dQwfPhwhISFQU1ODlZUVbty4gR07dmDWrFl4+vQppk2bhnr16mHgwIG4ceOG3Glq6QeLbd26FZUqVYKpqSmOHj2K8+fPY+XKlZDJZOKVVYsWLYK9vT2SkpKwfft2REdHAwDev38vN2/lY7/99htq1KiBTp06ISIiAtu3b4erqyu0tLTQtGlTqKioYNWqVRg9ejQyMjKwb98+8RfX+/fvYWxsDD09PSxevBgpKSkwMDDA7du3cfbsWTg5OQH4EBR/++037NixAw0bNkR0dDTWrVsHmUwmzm9YtmwZIiIiMH/+fCQlJeH69etijdra2mjUqBFcXV0xf/58KCsro0uXLkhOTsbatWvFU+6f0qhRI9jZ2cHPzw+pqamwtLREVFQUAgICYG1tLTdnJ/fjDHLfvIEPc6q8vLzw1VdfwcTE5JP3ExISgn379mH06NHQ1NSU2wc1NTW5v3ALMnnyZJw7dw7Dhw/H+PHjxbOMT548Eees2djYoH379vDw8MCrV69Qp04dbNmyBa9fvxaH/q5fv4558+aJH2vw8etMkZqkzMzMcOzYsc8+p1/ixIkT0NXVRdu2bfHnn39i165dmDp1qvhaHjt2LNasWYOUlBRYW1sjLi4Oa9asgUwmg4mJCR4/flzg8fW540KqY8eOsLa2hoeHB+Li4mBiYoKIiAj8/PPPsLOzE4/VGTNmYPr06fDw8ECPHj1w/fp17NixQ+wn96xiSkoKFi9eLPcLG/jyz4D69ttv4enpiZs3b+a5Sq4oDA0Noa2tjfXr10NFRQUqKio4fvw49u7dCwAFPs8vXrzAxIkTMXz4cLx48QLe3t7o0KEDrK2tAQBubm6YM2cOpk+fjj59+iAxMREBAQGoWrVqvmdfgA/HxW+//QYPDw/s27cPqqqqcuvNzc2xdu1abNy4ERYWFnj06BE2bNiAjIwMsd569eph0KBB8PHxQVZWFpo0aYKDBw/i7t27Yj+Fef18bNKkSRg8eDCcnJwwZMgQqKurY9euXTh16hT8/PwK8YhXfAxH/1GPHz/GsmXL8izv379/vvMGZs6ciRo1amDnzp3YtGkTvv76a8ybNw+DBw/Gvn37kJSUhKSkJNjb2+fZdsuWLeLPixcvxqZNm+Dr64u6devC29tbnFxsbW2N+fPnIzg4GMeOHUPNmjVhbW2NgIAAODs74+rVq5+dQDx16lRERERg165d0NfXx/z58zFkyBAAH95EVq9ejYCAAEycOBFVq1aFhYUFtm7dCkdHR0RGRoqf0ePt7Y01a9YgMTER+vr6mDx5sjgnZPbs2cjMzISvry8yMjLw9ddfY+LEiYiJicHvv/+O7Oxs8a+2RYsW5anRysoKW7duxYABA1CpUiVs2rQJu3btgpaWFlq2bAkvL68CJ7QuWbIE9erVQ1hYGH7++WfUrl1b/HiE3L+Igf+FI+nQXe6beUETsU+fPg3gw9nBoKAguXV16tTB77///tntpRo3bozQ0FB4e3tjzpw5YhDesmULWrduLbYLCAiAl5cX/Pz8kJ6ejp49e2LgwIFiLefPn0dmZiYiIiLyHRLMbacod3d3ZGVlic9p3bp1MXnyZPz+++84ceJEniEoRc2dOxdHjx5FSEgIatWqhR9//FFuYvu0adNQq1YthIaGYtOmTahatSpsbGzg5uaGypUr4+TJkwUeX7nPa0FkMhk2bNgAPz8/hISE4PXr1/j666/h5uYm90u8d+/eUFJSwtq1a3Hw4EEYGRlh0aJFcHNzA/BhGO7WrVsA8p8vNXnyZEyZMkWhx0lKXV0dbdq0wYMHD8Q/mr5E5cqVsXbtWqxcuRJTp05FpUqV0KRJE2zbtg3jxo1DZGTkZ7+mplevXqhSpQqmTZsGLS0t2NnZwdXVVVzfr18/VKpUCRs2bICzszO0tbXRoUMH8aMN8qOpqYn58+fDyckJGzduhLOzs9z63I8E2LJlCwIDA6Gvr48ffvhBfA6Tk5NRpUoVLFiwADVr1sS2bduQlJSEDh06YMKECfD19QXwYdJ2Yd+fc5mYmGD79u3w8fHBrFmzIAgCjIyMEBgYKF5Y8m8nE4pjxiFRGXr69Cm++eYbLFu2rMDPfSEqjBcvXmD8+PH4+eef+SnYZSAtLQ2dOnXCpEmTMGLEiDKtxdbWFlZWVli+fHmZ1kGli2eOiIg+8ttvvyE5ORlxcXFQUVHJ90okKn7Pnj3D/v37cfHiRchksnzPdBCVBk7IJiL6SMeOHaGuro5Ro0bh77//Luty/jOUlJSwdetWxMbGwsfHp9BzqYiKG4fViIiIiCR45oiIiIhIguGIiIiISILhiIiIiEiCV6sVwbVr1yAIQp4P7SIiIqLyKzMzEzKZLM8XIH+M4agIBEEoli+kJCIiotJT2N/dDEdFkHvGyMzMrIwrISIiosLK/WT3gnDOEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZFEuQpHGzZsgKOjo9yyqKgoODg4wMLCAra2ttiyZYvc+pycHPj5+aFDhw6wsLDAuHHj8OTJE4X6ICIiIspVbsLR9u3b4evrK7csMTERo0aNgoGBAcLCwuDs7AwvLy+EhYWJbdauXYvQ0FB4enpi586dyMnJwdixY5GRkVHoPoiIiIhylfkXz8bFxWHBggUIDw9H/fr15dbt3r0bqqqqWLRoEVRUVNCwYUM8evQIGzduhL29PTIyMhAUFIQZM2agc+fOAAAfHx906NABJ06cQO/evQvsg4iIiEiqzM8c/d///R9UVVVx6NAhNG/eXG5dZGQkrKysoKLyvwzXpk0b/PPPP0hISEB0dDTevXsHGxsbcX2VKlVgamqKK1euFKoPIiIiIqkyP3Nka2sLW1vbfNfFxsbCyMhIblnt2rUBAC9evEBsbCwAQF9fP0+b3HUF9VGzZs0i1S0IAt6/f1+kbQtLJpOVaP9EFZUgCGVdAhFVQIIgFOp3a5mHo89JS0uDmpqa3DJ1dXUAQHp6OlJTUwEg3zZJSUmF6qOoMjMzERUVVeTtC6KqqgpT06ZQUVEusfsgqoiysrJx587/ITMzs6xLIaIK6ONMkJ9yHY40NDTEidW5cgONlpYWNDQ0AAAZGRniz7ltNDU1C9VHUamqqqJRo0ZF3r4gMpkMKirKCNxxAc/ik0rsfogqkjq1q8J5SDs0btyYZ4+ISGExMTGFaleuw5Genh7i4+PlluXe1tXVRVZWlrjMwMBAro2xsXGh+igqmUz2ReGqsJ7FJ+GfZ4klfj9EFUnuHz9ERIoo7HSVMp+Q/TmWlpa4evUqsrOzxWWXL1+GoaEhatSoARMTE2hrayM8PFxcn5ycjDt37sDS0rJQfRARERFJletwZG9vj5SUFMydOxcxMTHYt28fQkJC4OTkBODDuKGDgwO8vLxw+vRpREdHw9XVFXp6eujevXuh+iAiIiKSKtfDajVq1MCmTZuwZMkS2NnZoVatWpg1axbs7OzENi4uLsjKyoKHhwfS0tJgaWmJzZs3Q1VVtdB9EBEREeWSCZzVqLBbt24BAMzMzEr8vn5c8yvnHBH9f/Xr6GDp1J5lXQYRVVCF/f1drofViIiIiEobwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRBMMRERERkQTDEREREZEEwxERERGRRIUIR1lZWVizZg26dOmCFi1aYNiwYbh+/bq4PioqCg4ODrCwsICtrS22bNkit31OTg78/PzQoUMHWFhYYNy4cXjy5Ekp7wURERFVBBUiHK1btw579uyBp6cnDhw4AENDQ4wdOxbx8fFITEzEqFGjYGBggLCwMDg7O8PLywthYWHi9mvXrkVoaCg8PT2xc+dO5OTkYOzYscjIyCjDvSIiIqLyqEKEo1OnTqF3795o37496tWrh9mzZ+Pt27e4fv06du/eDVVVVSxatAgNGzaEvb09Ro4ciY0bNwIAMjIyEBQUBBcXF3Tu3BkmJibw8fFBbGwsTpw4UcZ7RkREROVNhQhHNWrUwB9//IGnT58iOzsbu3btgpqaGkxMTBAZGQkrKyuoqKiI7du0aYN//vkHCQkJiI6Oxrt372BjYyOur1KlCkxNTXHlypWy2B0iIiIqx1QKblL25s6di6lTp+Kbb76BsrIylJSU4O/vDwMDA8TGxsLIyEiufe3atQEAL168QGxsLABAX18/T5vcdUUhCALev39f5O0LIpPJoKmpWWL9E1VkqampEAShrMsgogpGEATIZLIC21WIcBQTE4PKlSsjMDAQurq62LNnD2bMmIFt27YhLS0Nampqcu3V1dUBAOnp6UhNTQWAfNskJSUVuabMzExERUUVefuCaGpqwtTUtMT6J6rIHj58KB7bRESK+DgP5Kfch6MXL15g+vTpCAkJQevWrQEAZmZmiImJgb+/PzQ0NPJMrE5PTwcAaGlpQUNDA8CHuUe5P+e2+ZIzM6qqqmjUqFGRty9IYZIt0X+VoaEhzxwRkcJiYmIK1a7ch6MbN24gMzMTZmZmcsubN2+Oc+fO4auvvkJ8fLzcutzburq6yMrKEpcZGBjItTE2Ni5yXTKZDFpaWkXenoiKjkPORFQUhT3xUO4nZOvp6QEA7t69K7f83r17qF+/PiwtLXH16lVkZ2eL6y5fvgxDQ0PUqFEDJiYm0NbWRnh4uLg+OTkZd+7cgaWlZensBBEREVUY5T4cmZubo1WrVnB3d8fly5fxzz//wNfXF5cuXcL48eNhb2+PlJQUzJ07FzExMdi3bx9CQkLg5OQE4MPYooODA7y8vHD69GlER0fD1dUVenp66N69exnvHREREZU35X5YTUlJCevWrYOvry/mzJmDpKQkGBkZISQkBM2bNwcAbNq0CUuWLIGdnR1q1aqFWbNmwc7OTuzDxcUFWVlZ8PDwQFpaGiwtLbF582aoqqqW1W4RERFROSUTOKtRYbdu3QKAPPOgSsKPa37FP88SS/x+iCqC+nV0sHRqz7Iug4gqqML+/i73w2pEREREpYnhiIiIiEiC4YiIiIhIguGIiIiISILhiIiIiEiC4YiIiIhIguGIiIiISILhiIiIiEiC4YiIiIhIguGIiIiISILhiIiIiEiC4YiIiIhIguGIiIiISILhiIiIiEiC4YiIiIhIguGIiIiISILhiIiIiEiC4YiIiIhIguGIiIiISILhiIiIiEiC4YiIiIhIguGIiIiISILhiIiIiEiC4YiIiIhIQuFwlJWVVRJ1EBEREZULKopuYG1tjXbt2sHW1hYdO3ZE9erVS6IuIiIiojKhcDiaMmUKzp8/jwULFiArKwtmZmbo0qULunTpAiMjo5KokYiIiKjUKByORo4ciZEjRyI9PR2XL1/G+fPnsW/fPvj6+kJfXx9dunTBvHnzSqJWIiIiohJX5AnZ6urq6NSpE8aOHYuJEyeiZcuWeP78OUJDQ4uzPiIiIqJSpfCZoydPniAyMhIRERG4cuUKnj17Bi0tLbRs2RIzZsyAtbV1SdRJREREVCoUDkfdunWDTCZD06ZNMXDgQFhaWsLMzAwqKgp3RURERFTuKJxo+vXrh8uXL+P27dt4//49nj9/jtjYWFhZWaFGjRolUSMRERFRqVE4HC1duhTAh+G1S5cu4dKlS/D09ERiYiIMDQ1hbW2NBQsWFHuhRERERKWhyGNhdevWRd26ddG3b19ERkYiNDQUp06dwsOHDxmOiIiIqMIqUji6ffs2Ll68iEuXLuHatWvIyMhAkyZN4OzsjE6dOhV3jURERESlpkifkJ2cnAwtLS20a9cO8+bNQ6dOnVCzZs2SqI+IiIioVCkcjuzs7NCpUye0bt0aqqqqJVETERERUZlROBzNnj0bAHDu3DlEREQgOTkZOjo6aNWqFTp27FjsBRIRERGVJoXDUUZGBiZNmoQ///wTysrK0NHRQWJiIjZu3Ig2bdpgw4YNUFNTK4laiYiIiEpcob4+5NdffxV/9vf3x9WrV7Fy5UrcvHkTf/75J27cuIFly5bh+vXrWLduXYkVS0RERFTSChWO3Nzc4O/vDwA4cuQIJk+ejD59+kBZWRkAoKKigr59+2Ly5Mk4fPhwyVVLREREVMIKFY7mz5+Pffv24eHDh3j9+jVMTU3zbWdqaoq4uLhiLZCIiIioNBUqHA0dOhTHjx9HnTp1YGBggKtXr+bb7sqVK9DX1y/WAomIiIhKU6EnZOdOsh48eDCWL18ODQ0N9OrVCzVr1kRCQgKOHDmCn3/+GZMnTy6xYomIiIhKmsJXqw0ZMgR37tyBl5cXVq9eLS4XBAF2dnYYP358sRZIREREVJoUDkfv3r3DkiVLMHr0aERERCApKQlVq1aFlZUVGjZsWBI1EhEREZUahcNRz549MWfOHPTs2ZNhiIiIiP51CjUhWyojIwM6OjolUQsRERFRmVP4zNHw4cPh6+sLDQ0NmJiYQFNTsyTqIiIiIioTCoejgwcP4vnz5xg6dGi+62UyGe7cufPFhRERERGVBYXDUZ8+fUqiDiIiIqJyQeFwxM8xIiIion8zhcNRrrNnz+LixYt4+fIlXF1dERUVhaZNm6JOnTrFWR8RERFRqVI4HKWmpsLZ2RkXL16EtrY23r17hzFjxmDHjh24c+cOtm3bhsaNG5dErUREREQlTuFL+b29vfF///d/CAkJweXLlyEIAgBgxYoV0NXVxZo1a4q9SCIiIqLSonA4+u233+Dm5oY2bdpAJpOJy2vXro2JEyd+8ktpiYiIiCoChcNRcnLyJ+cVVa1aFe/fv//iooiIiIjKisLhqHHjxjh8+HC+637//XfONyIiIqIKTeFwNHHiRBw8eBBOTk7Ys2cPZDIZrly5Ak9PT+zYsQNjx44tiTpx4MAB9OzZE2ZmZujVqxd+++03cd3Tp0/h5OSEli1bon379vD19UV2drbc9tu3b8c333wDc3NzDB06lB9USURERPlSOBx17doVq1atwt27d/HTTz9BEAQsX74cx44dw08//YQePXoUe5EHDx7E3LlzMWzYMBw9ehS9e/eGm5sbrl27hszMTIwZMwYAsHPnTvz000/YsWMHAgMDxe3379+PlStXYurUqdi3bx++/vprjBo1Cq9fvy72WomIiKhiK9LnHH3//ff4/vvv8eDBA7x58wZVqlRBgwYNoKSkcNYqkCAIWLNmDYYPH45hw4YB+HD2KjIyEhEREXj27BmeP3+O3bt3o2rVqjAyMsKrV6+wcuVKTJgwAWpqali/fj0cHBzET/deunQpunbtij179sDJyanYayYiIqKKS+E0ExAQgIcPHwIAGjRogJYtW6JRo0ZQUlLC/fv3MXz48GIt8OHDh3j27Bm+//57ueWbN2+Gk5MTIiMj0bRpU1StWlVc16ZNG6SkpCAqKgqvXr3CP//8AxsbG3G9iooKWrdujStXrhRrrURERFTxKXzmKCAgACEhIfDy8kLnzp3l1qWkpBR74MgNYu/fv8eYMWNw584dfP3115g4cSJsbW0RGxsLPT09uW1q164NAHjx4gVUVD7sor6+fp420dHRRa5LEIQSvTJPJpNBU1OzxPonqshSU1PFz1gjIiosQRDkPoboU4o0rFanTh1MmjQJLi4umDBhQlG6KLSUlBQAgLu7OyZPnowZM2bg+PHjmDRpEoKDg5GWloYqVarIbaOurg4ASE9PR2pqKgBATU0tT5v09PQi15WZmYmoqKgib18QTU1NmJqallj/RBXZw4cPxWObiEgRH+eB/BQqHA0fPhx6enpYuXIlAGDRokU4d+4c1qxZg6ioKCxfvrzEznKoqqoCAMaMGQM7OzsAQJMmTXDnzh0EBwdDQ0MDGRkZctvkhh4tLS1oaGgAQL5tvqRmVVVVNGrUqMjbF6QwyZbov8rQ0JBnjohIYTExMYVqV6hwFBERgXr16om3ZTIZpkyZAmNjY7i7u2Pw4MEIDAyEsrJy0ar9DF1dXQCAkZGR3PJGjRrhzJkzsLKywr179+TWxcfHi9vmDqfFx8ejYcOGcm1y+y4KmUwGLS2tIm9PREXHIWciKorCnngo1ITs6OhoHD9+PM/y7t27Y8eOHXj79i369++PmzdvKlZlITRt2hSVKlXCjRs35Jbfu3cPBgYGsLS0xJ07d8ThNwC4fPkyKlWqBBMTE9SoUQOGhoYIDw8X12dlZSEyMhKWlpbFXi8RERFVbF987b2JiQnCwsLQuHFjLFq0qDhqkqOhoYGxY8ciMDAQR44cwePHj7Fu3TpcuHABo0aNQteuXVGrVi1MmzYN0dHROHXqFLy9vTF69GhxXHH06NEIDg7G/v37ERMTgx9//BFpaWno379/sddLREREFZvCE7InT56cZzhKR0cHISEhWLp0Kf74449iKy7XpEmToKmpCR8fH8TFxaFhw4bw9/eHtbU1AGDTpk1YuHAhBg4ciKpVq2Lo0KGYNGmSuP3AgQPx9u1b+Pr64s2bN2jWrBmCg4NRvXr1Yq+ViIiIKjaZUMyzGgt7mVxFduvWLQCAmZlZid/Xj2t+xT/PEkv8fogqgvp1dLB0as+yLoOIKqjC/v4u0qX8v/76KyIiIpCRkSFeMZL7uT/Xr1/HuXPnitItERERUZkr0odABgQEoHLlysjKyoKqqipUVFTw+vVrKCkpYcCAASVRJxEREVGpUHhC9v79+9G3b19ERERg5MiR6NKlCy5evIi9e/eiWrVqaNy4cUnUSURERFQqFA5HcXFx+P777yGTydCkSRNcu3YNANCsWTNMmDABe/bsKfYiiYiIiEqLwuFIS0tLnHBdr149PH36FGlpaQA+fHL106dPi7dCIiIiolKkcDgyMzPDgQMHAHz4CH9lZWVcunQJAHD//v1CfWcJERERUXml8ITsCRMmYNSoUUhOTsb69evRp08fuLu7w9raGn/++Se6du1aEnUSERERlQqFw5GlpSX27t2Lu3fvAgDmz58PJSUl/PXXX+jRowdmz55d7EUSERERlZYifc6RiYkJTExMAADq6urw9PQs1qKIiIiIykqRvlstIiIC169fBwA8f/4cEyZMwPfff4/AwMDirI2IiIio1Ckcjg4cOIARI0bg5MmTAD4Mq4WHh6NevXpYv349Nm7cWOxFEhEREZUWhcNRSEgI7OzsMHPmTLx8+RIXL17E5MmTERAQAFdXV4SFhZVEnURERESlQuFw9ODBA/Tt2xcAcPbsWQiCgG+++QbAh8v8X7x4UawFEhEREZUmhcNRlSpVkJKSAgA4f/48vvrqK9SvXx8A8PjxY+jo6BRrgURERESlSeGr1aytrREQEICYmBicPn0ao0aNAgAcP34ca9asQfv27Yu9SCIiIqLSovCZo7lz50JHRwcBAQGwsbGBk5MTAGDZsmX46quvMH369GIvkoiIiKi0KHzmqHr16ti8eXOe5aGhofjqq6+KpSgiIiKislKkD4EEgFevXiEjIwOCIAAAcnJy8PfffyMyMhJDhgwptgKJiIiISpPC4Sg6OhozZszA/fv3810vk8kYjoiIiKjCUjgcrVy5EklJSXB3d8cff/wBNTU1dOnSBefOncO5c+ewZcuWkqiTiIiIqFQoPCH7xo0bmDp1KkaOHImePXsiNTUVQ4cOxfr169G1a1ds3bq1JOokIiIiKhUKh6OMjAzxc43q16+P6OhocV2/fv3E71wjIiIiqogUDkdfffUVnjx5AuBDOEpJScHTp08BAGpqakhKSireComIiIhKkcLhqHv37li9ejWOHz8OXV1dNGjQAL6+vrh79y6CgoJQt27dkqiTiIiIqFQoHI4mT56Mli1bYu/evQCAOXPm4OTJk+jbty8uX76MKVOmFHuRRERERKVF4avV1NXV4efnh8zMTABAhw4dcOTIEdy+fRtNmzaFgYFBsRdJREREVFqK/CGQGRkZiIiIQFJSEqpXr44uXbpAQ0OjOGsjIiIiKnUKhyNBEODt7Y1ffvkFmZmZ4idka2pqwtnZGWPHji32IomIiIhKi8LhaN26ddi8eTMcHBzQvXt31KhRA69evcKxY8fg4+ODKlWqYODAgSVRKxEREVGJUzgc7dmzB05OTpg6daq4zNDQEK1bt4aWlhaCg4MZjoiIiKjCUvhqtcTERLRq1SrfddbW1njx4sUXF0VERERUVhQOR23atMGhQ4fyXXf27NlPBiciIiKiikDhYbU+ffpg4cKFGDNmDPr06QNdXV0kJibi1KlTOHbsGKZOnYoDBw6I7fv27VuM5RIRERGVLIXDkZubGwDgwoULuHDhQp713t7e4s8ymYzhiIiIiCoUhcPR6dOnS6IOIiIionJB4XBUp06dkqiDiIiIqFxQeEI2ERER0b8ZwxERERGRBMMRERERkQTDEREREZFEsYaj9+/f49y5c8XZJREREVGpUvhqtWfPnuGnn35CREQEMjIy8m0TFRX1xYURERERlQWFw9GyZcvw119/YcCAAfjrr7+gqakJCwsLXLhwAffu3YO/v39J1ElERERUKhQeVrty5QpcXV3h4eGBfv36QV1dHTNnzkRYWBgsLS35IZFERERUoSkcjt69ewdjY2MAQIMGDXDnzh0AgLKyMoYOHYrLly8Xb4VEREREpUjhcFS7dm0kJCQAAOrVq4ekpCS8fPkSAFCtWjW8evWqeCskIiIiKkUKh6NOnTrB19cX165dQ506daCnp4egoCCkpKQgLCwMurq6JVEnERERUalQOBy5uLigSpUqWLNmDQDA1dUVv/zyCywtLXH48GGMGjWq2IskIiIiKi0KX62mo6ODPXv2ID4+HgDQp08ffPXVV7h+/TrMzc1hZWVV7EUSERERlRaFw1Gu2rVr4/79+0hOTkbt2rUxduzY4qyLiIiIqEwUKRxt3boVGzZskJt8ra+vDzc3N/Tu3bvYiiMiIiIqbQqHo23btmHJkiXo2rUrunXrhho1aiAhIQFHjhzBzJkzoaysjO+++64kaiUiIiIqcQqHoy1btsDBwQEeHh5yy/v27Yu5c+ciICCA4YiIiIgqLIWvVouNjYWtrW2+63r37o0nT558cVFEREREZUXhcGRmZoZLly7lu+7OnTvip2cTERERVUSFGla7cuWK+HOvXr2wbNkypKam4rvvvkOtWrXw5s0bnD17Flu3bsXixYtLrFgiIiKiklaocOTo6AiZTCbeFgQB27Ztw/bt2+WWAcDUqVMRFRVVzGUSERERlY5ChaMtW7aUdB1ERERE5UKhwlFhP/U6JSWFZ42IiIioQlN4QnaTJk0wf/58ZGVl5Vl3//59DB8+vFgKy8/Dhw/RokUL7Nu3T1wWFRUFBwcHWFhYwNbWNs9ZrpycHPj5+aFDhw6wsLDAuHHjeEUdERERfZLC4UgQBOzduxeOjo5ISEgoiZrylZmZiRkzZuD9+/fissTERIwaNQoGBgYICwuDs7MzvLy8EBYWJrZZu3YtQkND4enpiZ07dyInJwdjx45FRkZGqdVOREREFYfC4QgAPD09kZCQgH79+uHGjRvFXVO+/P39oa2tLbds9+7dUFVVxaJFi9CwYUPY29tj5MiR2LhxIwAgIyMDQUFBcHFxQefOnWFiYgIfHx/ExsbixIkTpVI3ERERVSxF+m61xo0bY+/evZgyZQocHR0xb948DBgwQO6KtuJ05coV7Nq1CwcOHEDnzp3F5ZGRkbCysoKKyv92o02bNtiwYQMSEhLw/PlzvHv3DjY2NuL6KlWqwNTUFFeuXPmi74ETBEHuLFZxk8lk0NTULLH+iSqy1NRU8QpZIqLCEgShUFmlSOEIAKpWrYrg4GAsWrQI8+fPx507d9C/f/+idvdJycnJmDVrFjw8PKCvry+3LjY2FkZGRnLLateuDQB48eIFYmNjASDPdrVr1xbXFVVmZmaJTj7X1NSEqalpifVPVJE9fPgQqampZV0GEVVAampqBbYpcjgCAGVlZSxcuBCNGzfG8uXL5T4ssrj89NNPaNGiBb7//vs869LS0vLspLq6OgAgPT1dfPPMr01SUtIX1aWqqopGjRp9UR+fU1Jn4Yj+DQwNDXnmiIgUFhMTU6h2XxSOcjk4OKBBgwaYNm1acXQnOnDgACIjI3H48OF812toaOSZWJ2eng4A0NLSgoaGBoAPc49yf85t86VDVjKZDFpaWl/UBxEVDYeciagoCnviQeFwFB0dnWdZdnY22rZti7CwMERGRira5SeFhYXh1atXcvOMAGDBggX49ddfoaenh/j4eLl1ubd1dXXFjxuIj4+HgYGBXBt+BxwRERHlp0hnjjZu3IjIyEjxqrDIyEhMnz4dEyZMgIODQ7EV5+XlhbS0NLll3bt3h4uLC/r06YODBw9i586dyM7OhrKyMgDg8uXLMDQ0RI0aNVC5cmVoa2sjPDxcDEfJycm4c+dOsdZJRERE/x4KX8ofFBQEX19f1K9fX1xmYGCAHj16YPny5dizZ0+xFaerq4t69erJ/QOAGjVqQFdXF/b29khJScHcuXMRExODffv2ISQkBE5OTgA+zDVycHCAl5cXTp8+jejoaLi6ukJPTw/du3cvtjqJiIjo30PhM0c7d+7EtGnTMH78eHGZvr4+PDw8ULNmTYSEhGDAgAHFWuSn1KhRA5s2bcKSJUtgZ2eHWrVqYdasWbCzsxPbuLi4ICsrCx4eHkhLS4OlpSU2b94MVVXVUqmRiIiIKhaFw1FcXBzMzMzyXde8eXOsW7fui4v6nLt378rdNjc3x65duz7ZXllZGTNnzsTMmTNLtC4iIiL6d1B4WK1OnTq4dOlSvuuuXLkCPT29Ly6KiIiIqKwofOZo4MCBWLVqFTIzM9G1a1fUqFEDr1+/xh9//IHg4GBMnz69JOokIiIiKhUKh6ORI0ciLi4OW7duRUhIiLhcWVkZI0aMwKhRo4qzPiIiIqJSVaRL+d3d3TFp0iRcu3YNSUlJqFKlCszNzaGjo1Pc9RERERGVqiJ/QnblypXRsWPH4qyFiIiIqMwVKhx98803CAwMhImJCWxtbT/78dsymQynTp0qtgKJiIiISlOhwpGVlRUqVaok/swvRSUiIqJ/q0KFo2XLlok/L1++vMSKISIiIiprCn/O0edcunQJ8+bNK84uiYiIiEpVsYaje/fuYe/evcXZJREREVGpKtZwRERERFTRMRwRERERSTAcEREREUkwHBERERFJFOpS/uHDhxeqs9jY2C8qhoiIiKisFSocCYJQqM50dXWhq6v7RQURERERlaVChaOtW7eWdB1ERERE5QLnHBERERFJMBwRERERSTAcEREREUkwHBERERFJMBwRERERSTAcEREREUkwHBERERFJMBwRERERSTAcERGVgZycwn3zANF/SXk5Lgr1CdlERFS8lJRkCNxxAc/ik8q6FKJyoU7tqnAe0q6sywDAcEREVGaexSfhn2eJZV0GEX2Ew2pEREREEgxHRERERBIMR0REREQSDEdEREREEgxHRERERBIMR0REREQSDEdEREREEgxHRERERBIMR0REREQSDEdEREREEgxHRERERBIMR0REREQSDEdEREREEgxHRERERBIMR0REREQSDEdEREREEgxHRERERBIMR0REREQSDEdEREREEgxHRERERBIMR0REREQSDEdEREREEgxHRERERBIMR0REREQSDEdEREREEgxHRERERBIMR0REREQSDEdEREREEgxHRERERBIMR0REREQSFSIcvXnzBvPnz0fHjh3RsmVLDBkyBJGRkeL6S5cuoV+/fmjevDl69OiBo0ePym2fnp6OhQsXwsbGBi1atMD06dPx+vXr0t4NIiIiqgAqRDhyc3PDtWvX4O3tjbCwMDRp0gRjxozBgwcPcP/+fTg5OaFDhw7Yt28fBgwYgFmzZuHSpUvi9j/99BP+/PNP+Pv745dffsGDBw/g4uJShntERERE5ZVKWRdQkEePHuHChQsIDQ1Fq1atAADz5s3D+fPncfjwYbx69QrGxsZwdXUFADRs2BB37tzBpk2bYGNjg7i4OBw4cADr169H69atAQDe3t7o0aMHrl27hhYtWpTZvhEREVH5U+7PHOno6GDjxo0wMzMTl8lkMshkMiQnJyMyMhI2NjZy27Rp0wZXr16FIAi4evWquCyXoaEhdHV1ceXKldLZCSIiIqowyv2ZoypVqqBTp05yy44fP45Hjx7hxx9/xP79+6Gnpye3vnbt2khNTUViYiLi4uKgo6MDdXX1PG1iY2OLXJcgCHj//n2Rty+ITCaDpqZmifVPVJGlpqZCEISyLqPIeHwTfVpJHt+CIEAmkxXYrtyHo4/99ddfmDNnDrp3747OnTsjLS0Nampqcm1yb2dkZCA1NTXPegBQV1dHenp6kevIzMxEVFRUkbcviKamJkxNTUusf6KK7OHDh0hNTS3rMoqMxzfRp5X08Z1fJvhYhQpHp06dwowZM9CyZUt4eXkB+BByMjIy5Nrl3tbU1ISGhkae9cCHK9i+5C83VVVVNGrUqMjbF6QwyZbov8rQ0LDCnzkiovyV5PEdExNTqHYVJhxt27YNS5YsQY8ePbBixQox+enr6yM+Pl6ubXx8PLS0tFC5cmXo6enhzZs3yMjIkEuL8fHx0NXVLXI9MpkMWlpaRd6eiIqOQ1JE/14leXwX9g+Tcj8hGwBCQ0Ph6emJYcOGwdvbWy7ktG7dGhEREXLtL1++jJYtW0JJSQmtWrVCTk6OODEb+HDKLi4uDpaWlqW2D0RERFQxlPtw9PDhQyxduhTdunWDk5MTEhIS8PLlS7x8+RJv376Fo6Mjbt68CS8vL9y/fx9BQUE4duwYxo4dCwDQ1dVFr1694OHhgfDwcNy8eRNubm6wsrKChYVF2e4cERERlTvlfljt+PHjyMzMxMmTJ3Hy5Em5dXZ2dli+fDnWrl2LVatW4ZdffsHXX3+NVatWyV3e7+npiaVLl2Ly5MkAgI4dO8LDw6NU94OIiIgqhnIfjiZMmIAJEyZ8tk3Hjh3RsWPHT67X0tLC4sWLsXjx4uIuj4iIiP5lyv2wGhEREVFpYjgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKSYDgiIiIikmA4IiIiIpJgOCIiIiKS+M+Eo5ycHPj5+aFDhw6wsLDAuHHj8OTJk7Iui4iIiMqZ/0w4Wrt2LUJDQ+Hp6YmdO3ciJycHY8eORUZGRlmXRkREROXIfyIcZWRkICgoCC4uLujcuTNMTEzg4+OD2NhYnDhxoqzLIyIionLkPxGOoqOj8e7dO9jY2IjLqlSpAlNTU1y5cqUMKyMiIqLyRqWsCygNsbGxAAB9fX255bVr1xbXKSIzMxOCIODmzZvFUt+nyGQy9LKqheycGiV6P0QVhbKSEm7dugVBEMq6lC/G45tIXmkc35mZmZDJZAW2+0+Eo9TUVACAmpqa3HJ1dXUkJSUp3F/uA1uYB/hLVdHWKPH7IKpoSuPYKw08vonyKsnjWyaTMRzl0tD48AaUkZEh/gwA6enp0NTUVLi/Fi1aFFttREREVL78J+Yc5Q6nxcfHyy2Pj4+Hrq5uWZRERERE5dR/IhyZmJhAW1sb4eHh4rLk5GTcuXMHlpaWZVgZERERlTf/iWE1NTU1ODg4wMvLC9WrV0edOnWwatUq6OnpoXv37mVdHhEREZUj/4lwBAAuLi7IysqCh4cH0tLSYGlpic2bN0NVVbWsSyMiIqJyRCb8G66JJSIiIiom/4k5R0RERESFxXBEREREJMFwRERERCTBcEREREQkwXBEREREJMFwRERERCTBcEREREQk8Z/5EEgq/2xtbfHs2TPxtqqqKurUqYMBAwZg7NixZVhZ4Tk6OqJOnTpYvnx5gW1nz56NZ8+eYevWraVQGVH59fTpU3zzzTefXG9lZVXix4mtrS3s7OwwZcqUAtsqcpxTxcRwROXK6NGjMXr0aABAWloabt68CQ8PD2hqamLYsGFlXF3xmjt3LrKzs8u6DKIyp6+vjz///DPP8uPHj8PT0xPdunUrg6o+zd/fH8rKymVdBpUghiMqV7S0tFCrVi3xdt26dREeHo6wsLB/XTiqXLlyWZdAVC4oKyvLHfcAcOfOHaxatQo9evTA8OHDy6iy/FWrVq2sS6ASxjlHVO5paGjI3RYEAT///DO++eYbNG/eHD/88AMOHTokrnd0dISxsXGef46Ojvn2v2/fPnTr1g2LFy9Gq1atMGnSJADA/fv3MWHCBFhbW6NVq1ZwcXGRG/bLyMjA0qVLYWNjg1atWmHVqlXIyckpdB2zZ88Wfw4PD4epqSnOnj2L3r17o1mzZujRowdOnToFADh16hRMTEzk7h8ABg0ahBUrVhT1oSUql96+fYupU6dCX18fS5Ys+WQ7f39/ODg4wNXVFS1btoSnpycA4Nq1axg+fDhatWoFa2trzJkzB4mJiXL9u7u7o3Xr1mjTpg2Cg4Pl+rW1tc332J0zZw6AD8f27NmzAfzv/SP3/2bNmqFfv364evWq2N/z58/h6uoKGxsbNG3aFB07dszzfkHlC8MRlWs3b97EkSNHMGDAAHGZj48PduzYgXnz5uHw4cMYPnw4fvrpJ2zfvh3AhzfMP//8U/w3d+5cqKioYOLEiZ+8n8ePHyM+Ph4HDhyAq6srnj17hkGDBkFNTQ2//PILgoKC8PLlSzg4OCAlJQUAsHjxYvz6669Yvnw5du7cidjYWERGRop9KlpHdnY2Vq1ahblz5+LIkSMwMjKCu7s73r17h86dO6N69eo4ePCg2P7hw4e4fv067O3tv+gxJipv5syZg5cvX8Lf3x/a2tqfbXvlyhXUrFkTBw8ehKOjI27evAlHR0c0btwYu3fvxpo1a3Djxg2MGTNGHMaeNm0abt68ifXr1yM4OBhnzpyR+8Nj7969csfu6NGjUalSJYwcOTLfGl68eIGdO3di1apV2L9/PzQ1NTF79mzkfnXpxIkT8fbtWwQHB+PYsWMYPXo0Nm3ahN9//714HjAqfgJROdGlSxehadOmgoWFhWBhYSE0bdpUMDIyEgYMGCC8fftWEARBePfunWBmZiacPHlSbts1a9YIXbp0ydPntWvXBDMzMyE0NPST9xsWFiYYGRkJUVFR4rKVK1cKHTp0ENLT08Vl8fHxgpmZmbBt2zbh7du3QtOmTYXdu3eL69PS0oS2bdsK7u7uharD3d1dcHBwEARBEC5fviwYGRnJ7VdUVJRgZGQk/PXXX4IgCMLy5cuF7t27i+u9vb0Fe3v7T+4XUUUUFBQkGBkZCQcPHiywrZ+fn2BkZCQkJyeLy6ZOnSr069dPrl3usXTmzBnh/v37gpGRkXDx4kVx/cuXL4VmzZoJfn5+ee7jxIkTgqmpqfDHH3+IyxwcHMTjPPf9486dO+L6kydPCkZGRkJcXJyQmpoqbN68WXj+/Llcv23bthUCAgIK3EcqG5xzROXK4MGDxaGmrKwsPHr0CD4+Phg2bBj27NmDmJgYpKenY/r06VBS+t+Jz6ysLGRkZCAtLU0chnv69CkmTZqEQYMGYciQIQXed/369cWf7927h2bNmkFNTU1cVqtWLRgaGuLevXt4+PAhMjMzYWZmJq5XV1eHqalpnn4VqaNBgwbiz7l/MWdmZgIA7O3tERQUhBs3bsDc3ByHDh3CuHHjCtwvoori2rVrWL16NYYOHYo+ffoUapsaNWrIzd+7d+8e2rVrJ9fGxMQElStXxt27d5GamgoAcsduzZo1Ubdu3Tx937p1CzNnzsTMmTPRuXPnz9bRsGFD8efcejIzM6GhoQEHBwccO3YMN2/exKNHj3D37l0kJCRwWK0cYziicqVq1aqoV6+eeLthw4aoWrUqhg4diosXL0JHRwcA4OvrKxckcuWGmbdv38LJyQlNmzYV5wYURDq3Sfj/p8M/lpOTA1VVVchksnzbqajIH1KK1iENYx/X0qhRIzRv3hyHDh1CWloaEhIS0Lt37wL7JKoIXr9+jWnTpsHExESc21MY+c1JzI8gCHLH7sfB5ONj98WLF5g4cSL69OnzyeE0qU8du+/fv4eDgwPS0tLQo0cP2NnZwdzc/F93gcm/DeccUbmX+2aXk5ODBg0aQEVFBc+fP0e9evXEf2fPnsXmzZuhpKSErKwsTJ06FTKZDD4+PkW65NbY2Bi3bt1CRkaGuCwhIQGPHj1Cw4YNYWhoCHV1dfz111/i+qysLERHR8vd/tI6PmZvb49Tp07h2LFj6Nq1K6pUqfLFfRKVNUEQMHPmTKSlpcHPzy/foFFYxsbGcpOhASA6OhopKSlo2LAhmjRpAgByx25ycjIeP34s3k5JSYGTkxMaNmyI+fPnF7kWAPjzzz/xf//3f9iyZQtcXFzQs2dPaGtr49WrV58MclT2eOaIypX379/j5cuXAD68YT5+/BhLly5F7dq1YWNjA01NTQwePBhr1qyBtrY2WrZsifDwcKxatQpOTk4AgEWLFiEqKgrBwcFIS0sTT6MDyHO58KcMGTIEO3bswMyZMzFx4kRkZGRgxYoV0NHRQa9evVCpUiU4ODjAz88PtWrVQsOGDREUFIS4uDixj+Ko42O9evXCsmXLsG/fPvj7+xepD6LyZsOGDbhw4QJWrFgBVVVV8T0gl7KyMqpXr16ovkaNGoWhQ4fC09MTQ4cORUJCAjw9PWFqagobGxuoqqqiR48eWLRoEdTU1FCzZk14e3uLfwhlZ2fD1dUV6enpWLx4Md68eSOGGEXqyKWnpwcAOHToEL799lu8ePEC3t7eyMzMlPvji8oXhiMqV4KCghAUFAQAUFJSQrVq1dC6dWt4eXlBU1MTwIcrWXR0dLBmzRrEx8dDX18fLi4u4qdo79q1CwDwww8/5On/7t27harj66+/xrZt27Bq1SrxqrV27dph1apV4tma6dOnQ11dHYsWLcK7d+/w3XffwdbWVuyjOOr4mLa2Nrp27YqIiIg88yqIKqoLFy5AEATMmjUr3/V16tQp9JVdzZs3x6ZNm+Dr64u+ffuKx8z06dOhqqoKAFixYgVWrFgBV1dX5OTkYNCgQXj9+jWAD8Np586dAwB07dq1yHXkMjc3x5w5cxASEgJfX1/o6uqiZ8+eUFdXx+nTpzFjxgyF+qPSIRN4Xo+oQnF0dETLli3h6upa1qUQURG8ffsWw4cPx4YNG1C7du2yLofywTNHRBXEqVOnEBUVhevXr2PlypVlXQ4RFdGFCxeQkpICmUyGjIyML5pjRSWDE7KJKohNmzZh27Zt8PT0hL6+flmXQ0RFZGFhARUVFfTq1UtuniKVHxxWIyIiIpLgmSMiIiIiCYYjIiIiIgmGIyIiIiIJhiMiIiIiCYYjIip1Rb0OhNePEFFpYDgiomJx7949uLq6ol27dmjWrBnat2+PadOmyX3fHABcvXoV48ePV7j/06dPw93dvbjKLVWOjo5wdHQsdHt/f38YGxuXYEVE9Dn8EEgi+mJ///03Bg0aBAsLC3h4eKBGjRqIjY3Ftm3bMHDgQGzZsgUWFhYAgD179uD+/fsK30dISEjxFl2ODRgwAB06dCjrMoj+sxiOiOiLBQcHQ0dHBz///DNUVP73ttK1a1f06NEDa9euxcaNG8uwwopFT09P/MJSIip9HFYjoi+WkJAAQRCQk5Mjt1xLSws//vgjvvvuOwDA7NmzsX//fjx79gzGxsbYt28fAODp06eYNWsW2rdvj6ZNm8LGxgazZs1CYmIigA/DUhEREYiIiICxsTHCw8Oxb98+GBsb4+nTp3L3aWtri9mzZ4u3L1y4gIEDB6JFixawtLTExIkTP3vm6unTpzA2NkZwcDB69OiB5s2bIywsDABw69YtjBkzBtbW1mjZsiUmTJiAv//+W27758+fY/LkyWjVqhXatWuH4OBgufXh4eEwNjbO91/u0NvHw2qOjo6YO3cuNm7ciM6dO8PMzAyDBw/GzZs3AXw4c2dsbCx+2XGuFy9eoEmTJjh06NAn95eI8uKZIyL6Yp07d8bZs2cxePBg2Nvbo02bNmjQoAFkMhl69Oghtps0aRJev36NO3fuICAgAAYGBkhNTcXw4cOho6ODBQsWoHLlyrh27RoCAgKgoaGBRYsWYcGCBZg5cyYAYMGCBWjUqBGePXtWYF1PnjzBpEmTYG9vDzc3NyQnJ8Pb2xvjx4/HyZMnoaT06b8P/f39MXfuXGhra6N58+a4fPkyxo4dC2trayxduhTp6enYsGEDBg8ejN27d6Nhw4Z4//49HBwcoKKiAk9PTygpKcHPzw+PHz9GixYtAABNmzbNE2KOHDmCrVu3on///p+s5/jx42jYsCE8PDwgCAJWrFiBKVOm4Pfff0fjxo3RvHlzHDx4EIMGDRK3OXDgALS0tNC9e/cCHysi+h+GIyL6YkOHDsXLly+xefNmLFq0CACgo6OD9u3bY/jw4TA3NwcAGBgYoHr16lBTUxPnIEVFRUFPTw8rVqxA3bp1AQBt2rTBjRs3EBERAQBo1KgRtLW1AUDcrjBu3ryJtLQ0ODk5QVdXF8CHIavTp0/j/fv3Yp/5+e6772Bvby/enjJlCurVq4eNGzdCWVkZANC+fXt069YNfn5+WLNmDfbv34/nz5/jyJEjaNSoEQCgefPm6Natm9iPtra23D7cuHEDu3fvxsiRI/HDDz98sp6srCxs3rxZrPndu3dwd3dHVFQUmjVrBnt7eyxYsABPnjwRH8cDBw6gV69e0NDQKPRjRkQcViOiYjJ16lScP38eq1evRv/+/aGtrY3Dhw+LE7I/pUmTJggNDUWdOnXwzz//4OzZs9i8eTMePHiAjIyML6qpefPmUFdXR//+/bFkyRKcP38eJiYmcHV1/Wwwyq0r1/v373Hr1i189913YjACgCpVqqBLly5iiIuMjISBgYEYjABAX1//k4EuNjYWzs7OaNGiBWbNmvXZeqQBEYAY9lJTUwFADEEHDx4EAPz111/4559/YGdn99l+iSgvhiMiKjZVq1ZF7969sWTJEpw6dQr79+9Hw4YNsWrVKnH+UH6Cg4NhY2ODb7/9Fj/++CMiIiKgqan5xfV8/fXX2LZtG5o3b469e/di7NixaNeuHXx8fAr8zCQtLS3x57dv30IQBNSsWTNPu5o1a+Lt27cAgKSkJOjo6ORpU6tWrTzLUlNTMWnSJKipqcHX11cudOXn48cjd0gwd56XtrY2evToIc4vOnDgAAwNDcXhPCIqPIYjIvoicXFxaN++Pfbs2ZNnnampKVxdXZGRkYEnT57ku/3hw4exfPlyjBs3DpcuXcKFCxewYcMG1K9f/7P3K5PJACDPJPB3797J3TY3N0dAQADCw8MREhKCdu3aYf369Th27Fih97Fy5cqQyWRISEjIs+7ly5eoVq0agA9Difm1efPmjdxtQRAwe/ZsPHjwAIGBgfkGqqKwt7fHo0ePcPPmTRw/fhz9+vUrln6J/msYjojoi9SsWRMqKioIDQ1Fenp6nvUPHjyAuro66tWrBwB5JkFfvXoVVapUwdixY1G9enUAHwLO1atX5YLPx9vlDjHFxsaKy+7fvy8XREJCQtClSxdkZGRATU0NNjY28PT0BPDhqrLC0tLSQrNmzfDbb78hOztbXP727VucOXMGrVq1AvBhrtTTp09x69Ytsc3r169x/fp1uf4CAgJw7NgxLF68WG747ktZWlqifv36WLVqFd6+ffvZOUxE9GkMR0T0RZSVlfHTTz/h3r17sLe3x44dOxAREYGzZ89i6dKlWLNmDSZPnoyqVasC+DBPJyEhAWfPnkV8fDzMzc2RnJyM5cuXIzw8HIcPH8awYcOQkJAgzqfJ3e7hw4e4dOkSkpKSYG1tDQ0NDSxfvhxnz57Fr7/+CmdnZ/EsDvAhrLx8+RLOzs44e/Ys/vzzT8yZMwdqamro0qWLQvs5ffp0PHz4EOPHj8fp06dx7NgxjBgxAhkZGXB2dgYA/PDDDzAyMsLkyZNx4MABnDp1CuPGjZMLeSdOnEBgYCB69+6NBg0a4MaNG7h+/br470vZ29sjIiIC7dq1E+clEZFieLUaEX2xzp07Y/fu3di8eTPWr1+P169fQ01NDaampvDx8ZG7lLxfv344e/YsnJ2d4eLignHjxuHp06cICwtDaGgodHV10alTJwwdOhTz5s3D/fv30bBhQwwbNgy3b9/GuHHjsGzZMnz//ffw9/fH6tWr4ezsjDp16oihJJeJiQnWr1+PwMBAuLm5ITs7G82aNUNQUBAaNGig0D7a2NggODgYfn5+cHNzg5qaGlq3bo0VK1agcePGAAA1NTX88ssvWLp0KZYsWQKZTIaBAweibt26ePXqFQDg999/hyAIOHLkCI4cOZLnfu7evVuEZ+B/OnXqhNWrV3NIjegLyAR+kyMR0b/Gxo0bERISgjNnzkBNTa2syyGqkHjmiIjoX2D//v24d+8eQkNDxavgiKhoGI6IiP4FoqOjsXPnTnTr1g2jR48u63KIKjQOqxERERFJ8Go1IiIiIgmGIyIiIiIJhiMiIiIiCYYjIiIiIgmGIyIiIiIJhiMiIiIiCYYjIiIiIgmGIyIiIiKJ/we7e6gY5evwfQAAAABJRU5ErkJggg==", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Tworzenie nowej kolumny 'maRodzine' dla pasażerów, którzy mają rodzinę na pokładzie\n", "df2['maRodzine'] = df2['parch'] > 0\n", "print(f\"liczba osob z rodzina: {df2['maRodzine'].sum()}\")\n", "liczba_bez_rodziny = (~df2['maRodzine']).sum()\n", "print(f\"Liczba osób bez rodziny: {liczba_bez_rodziny}\")\n", "\n", "# Tworzenie wykresu słupkowego\n", "sns.countplot(x='maRodzine', data=df2)\n", "plt.xticks([0, 1], ['Bez rodziny', 'Z rodziną'])\n", "plt.title(\"Liczba pasażerów z rodziną i bez rodziny na pokładzie\")\n", "plt.xlabel(\"Status rodziny\")\n", "plt.ylabel(\"Liczba pasażerów\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek\n", "- Najwięcej pasazerów było bez rodzin. liczba osob z rodzina: 307\n", "Liczba osób bez rodziny: 1000" ] }, { "cell_type": "code", "execution_count": 138, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Liczba ocalonych pasażerów bez rodziny: 336\n", "Liczba ocalonych pasażerów z jednym krewnym: 100\n", "Liczba ocalonych pasażerów z dwojgiem krewnych: 57\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Filtrowanie danych dla pasażerów, którzy przeżyli\n", "survived_data = df[df['survived'] == 1]\n", "# Filtrowanie danych dla pasażerów, którzy przeżyli i nie mieli rodziny na pokładzie\n", "survived_no_family = survived_data[survived_data['parch'] == 0] \n", "# Filtrowanie danych dla pasażerów, którzy przeżyli i mieli jednego krewnego\n", "survived_family1 = survived_data[survived_data['parch'] == 1]\n", "# Filtrowanie danych dla pasażerów, którzy przeżyli i mieli dwojga krewnych\n", "survived_family2 = survived_data[survived_data['parch'] == 2]\n", "\n", "# Wypisanie liczby ocalonych pasażerów bez rodziny\n", "print(f\"Liczba ocalonych pasażerów bez rodziny: {len(survived_no_family)}\")\n", "print(f\"Liczba ocalonych pasażerów z jednym krewnym: {len(survived_family1)}\")\n", "print(f\"Liczba ocalonych pasażerów z dwojgiem krewnych: {len(survived_family2)}\")\n", "# Wykres\n", "plt.figure(figsize=(10, 6))\n", "sns.countplot(data=survived_data, x='parch', palette='viridis', hue=x)\n", "plt.title('Liczba pasażerów, którzy przeżyli, posortowane wg liczby krewnych na pokładzie (parch)')\n", "plt.xlabel('Liczba krewnych na pokładzie (parch)')\n", "plt.ylabel('Liczba ocalonych')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- około 336 ocalonych nie miało krewnych na pokładzie. 100 ocalonych było z jednym rodzicem albo z jednym dzieckiem na Titaniku. Kolejne 57 osób, które przeżyły miało dwoje rodziców lub dwójkę dzieci. " ] }, { "cell_type": "code", "execution_count": 137, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Liczba ofiar bez rodziny: 664\n", "Liczba ofiar z jednym krewnym: 70\n", "Liczba ofiar z dwojgiem krewnych: 56\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Filtrowanie danych dla pasażerów, którzy zgineli\n", "survived_data = df[df['survived'] == 0]\n", "# Filtrowanie danych dla pasażerów, którzy zgineli i nie mieli rodziny na pokładzie\n", "survived_no_family = survived_data[survived_data['parch'] == 0]\n", "# Filtrowanie danych dla pasażerów, którzy zgineli i mieli krewnych == 1\n", "survived_family1 = survived_data[survived_data['parch'] == 1]\n", "# Filtrowanie danych dla pasażerów, którzy zgineli i mieli krewnych == 2\n", "survived_family2 = survived_data[survived_data['parch'] == 2]\n", "# Wypisanie liczby ofiar bez rodziny i z jednym krewnym\n", "print(f\"Liczba ofiar bez rodziny: {len(survived_no_family)}\")\n", "print(f\"Liczba ofiar z jednym krewnym: {len(survived_family1)}\")\n", "print(f\"Liczba ofiar z dwojgiem krewnych: {len(survived_family2)}\")\n", "# Wykres\n", "plt.figure(figsize=(10, 6))\n", "sns.countplot(data=survived_data, x='parch', palette='viridis', hue=x)\n", "plt.title('Liczba pasażerów, którzy zginęli, posortowane wg liczby krewnych na pokładzie (parch)')\n", "plt.xlabel('Liczba krewnych na pokładzie (parch)')\n", "plt.ylabel('Liczba ofiar')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- około 664 ofiar nie miało krewnych na pokładzie. Około 80 ofiar było z rodzicem albo z jednym dzieckiem na Titaniku. Dalsze 50 osób miało dwoje rodziców lub dwójkę dzieci." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### fare: histogram" ] }, { "cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df2['fare'].hist(bins=10)\n", "plt.xlabel('fare') \n", "plt.ylabel('częstość wystąpienia') \n", "plt.title('Histogram dla fare')\n", "plt.grid(False)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- Najwięcej sprzedano biletów w cenie do 50 dollars. 20% biletów kosztowało do 100 dollars." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### fare: boxplot" ] }, { "cell_type": "code", "execution_count": 87, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.boxplot(x='fare', data=df2)\n", "plt.title(\"Rozkład cen biletów ('fare')\")\n", "plt.xlabel(\"Cena biletu (fare)\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- Wartość odstająca mocno, ogranicza odczytanie cen. Rozkłady cen najlepiej odczytać z tabeli statystycznego opisu." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### fare vs. pclass - box chart" ] }, { "cell_type": "code", "execution_count": 88, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.boxplot(df2, x='pclass', y='fare')\n", "plt.title('Rozkład ceny według klasy')\n", "plt.xlabel('klasa biletu')\n", "plt.ylabel('cena')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski:\n", "- Ceny dla 1. klasy są najwyższe i mają największy rozrzut. Za najdroższy bilet zapłacono 1000 % średniej ceny (50 $) w tej klasie.\n", "- Generalnie im większy numer dla klasy biletu tym niższa cena biletu" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### fare vs. pclass: Inny wykres pudełkowy" ] }, { "cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Tworzenie nowego wykresu z trzema osiami obok siebie\n", "fig, axes = plt.subplots(1, 3, figsize=(15, 5))\n", "\n", "df3 = df2[['pclass', 'survived', 'age', 'sibsp', 'parch', 'fare', 'body']]\n", "# tworzenie wykresu pudełkowego dla klasy 1\n", "filtrowanie_1 = df3[df3['pclass'] == 1.0]\n", "filtrowanie_1[['fare']].boxplot(ax=axes[0])\n", "axes[0].set_title('Box Plot dla 1. klasy')\n", "axes[0].set_xlabel('')\n", "axes[0].set_ylabel('Wartość')\n", "# tworzenie wykresu pudełkowego dla klasy 2\n", "filtrowanie_2 = df3[df3['pclass'] == 2.0]\n", "filtrowanie_2[['fare']].boxplot(ax=axes[1])\n", "axes[1].set_title('Box Plot dla 2. klasy')\n", "axes[1].set_xlabel('Fare')\n", "# tworzenie wykresu pudełkowego dla klasy 3\n", "filtrowanie_3 = df3[df3['pclass'] == 3.0]\n", "filtrowanie_3[['fare']].boxplot(ax=axes[2])\n", "axes[2].set_title('Box Plot dla 3. klasy')\n", "axes[2].set_xlabel('Fare')\n", "# Ustawienia odstępów między wykresami\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wnioski\n", "- dla 1. klasy 50 % cen biletów nie jest droższa niż 60 dollars. 75% cen mieści się w zakresie do 105 dollars. Maksymalna cena do 220 dollars. Pojawiły się 4 wartości odstające w zakresie 230-520 dollars.\n", "- dla 2. klasy 50 % cen biletów nie jest droższa niż 18 dollars. 75% cen mieści się w zakresie do 27 dollars. Maksymalna cena do 42 dollars. Pojawiły się 2 wartości odstające w zakresie 66 i 75 dollars.\n", "- dla 3. klasy 50 % cen biletów nie jest droższa niż 8 dollars. 75% cen mieści się w zakresie do 17 dollars. Maksymalna cena do 27 dollars. Pojawiły się 8 wartości odstające w zakresie 29-69 dollars." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### embarked vs. fare" ] }, { "cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Oblicz średnią opłatę dla każdego portu zaokrętowania\n", "embarked_fare = df2.groupby('embarked')['fare'].mean()\n", "\n", "# Ustawienie rozmiaru wykresu\n", "plt.figure(figsize=(8, 6))\n", "\n", "# Tworzenie wykresu słupkowego\n", "embarked_fare.plot(kind='bar', color='lightgreen')\n", "\n", "# Dodanie etykiet i tytułu\n", "plt.title(\"Średnia opłata zaokrętowania (fare) w zależności od portu (embarked)\")\n", "plt.xlabel(\"Port zaokrętowania (embarked)\")\n", "plt.ylabel(\"Średnia opłata (fare)\")\n", "\n", "# Wyświetlenie wykresu\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- Porty dalej oddalone od NY mają średnie ceny wyższe. Od najdalszego: C = Cherbourg, S = Southampton, Q = Queenstown" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### embarked: histogram ilości pasażerów wg portu wsiadania" ] }, { "cell_type": "code", "execution_count": 129, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(8, 6))\n", "sns.countplot(data=df, x='embarked', palette='muted', hue=x)\n", "plt.title('Liczba pasażerów według portu wsiadania')\n", "plt.xlabel('Port wsiadania')\n", "plt.ylabel('Liczba pasażerów')\n", "plt.xticks(ticks=[0, 1, 2], labels=['Southampton', 'Cherbourg', 'Queenstown'])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- Najwięcej osób 900 zaczęło podróż z Cherbourg, potem Queenstown 300, Southampton 100 w kolejności malejącej." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### **embarked vs. survived" ] }, { "cell_type": "code", "execution_count": 130, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", "# Filtrowanie danych dla pasażerów, którzy przeżyli\n", "survived_data = df2[df2['survived'] == 'Tak']\n", "\n", "# Usunięcie wierszy z brakującymi wartościami w kolumnie 'embarked'\n", "survived_data = survived_data.dropna(subset=['embarked'])\n", "\n", "# Tworzenie wykresu słupkowego liczby przeżyłych pasażerów w zależności od portu zaokrętowania\n", "plt.figure(figsize=(8, 6))\n", "sns.countplot(data=survived_data, x='embarked', palette='viridis', hue=x)\n", "plt.title('Liczba ocalałych pasażerów według portu zaokrętowania')\n", "plt.xlabel('Port zaokrętowania (embarked)')\n", "plt.ylabel('Liczba ocalałych')\n", "plt.xticks(ticks=[0, 1, 2], labels=['Cherbourg', 'Queenstown', 'Southampton'])\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 131, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Filtrowanie danych dla pasażerów, którzy zginęli\n", "survived_data = df2[df2['survived'] == 'Nie']\n", "\n", "# Tworzenie wykresu słupkowego liczby przeżyłych pasażerów w zależności od portu zaokrętowania\n", "plt.figure(figsize=(8, 6))\n", "sns.countplot(data=survived_data, x='embarked', palette='viridis', hue=x)\n", "plt.title('Liczba ofiar według portu zaokrętowania')\n", "plt.xlabel('Port zaokrętowania (embarked)')\n", "plt.ylabel('Liczba ofiar')\n", "plt.xticks(ticks=[0, 1, 2], labels=['Cherbourg', 'Queenstown', 'Southampton'])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- Procentowo najmniej ofiar dla S." ] }, { "cell_type": "code", "execution_count": 106, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Filtrowanie danych dla pasażerów, którzy przeżyli\n", "survived_data = df2[df2['survived'] == 'Tak']\n", "\n", "# Obliczanie liczby przeżyłych pasażerów dla każdego portu\n", "embarked_counts = survived_data['embarked'].value_counts()\n", "\n", "# Tworzenie wykresu kołowego\n", "plt.figure(figsize=(8, 8))\n", "plt.pie(embarked_counts, labels=embarked_counts.index, autopct='%1.1f%%', startangle=90, colors=['#ff9999', '#66b3ff', '#99ff99'])\n", "plt.title(\"Procentowy udział pasażerów, którzy przeżyli, według portu zaokrętowania\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- Najwięcej ocalałych wsiadających w porcie S. Najmniej z Q." ] }, { "cell_type": "code", "execution_count": 108, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Filtrowanie danych dla pasażerów, którzy nie przeżyli\n", "not_survived_data = df2[df2['survived'] == 'Nie']\n", "\n", "# Obliczanie liczby nieprzeżyłych pasażerów dla każdego portu\n", "embarked_counts = not_survived_data['embarked'].value_counts()\n", "\n", "# Tworzenie wykresu kołowego\n", "plt.figure(figsize=(8, 8))\n", "plt.pie(embarked_counts, labels=embarked_counts.index, autopct='%1.1f%%', startangle=90, colors=['#ff6666', '#66ccff', '#99ffcc'])\n", "plt.title(\"Procentowy udział pasażerów, którzy nie przeżyli, według portu zaokrętowania\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- Najwięcej ofiar wsiadających w porcie S. Najmniej z Q." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### boat: ilość rozbitków pro szalupę - bar chart" ] }, { "cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Zliczanie liczby osób w każdej szalupie\n", "liczba_osob_w_szalupach = df2.groupby('boat').size().sort_values()\n", "# Tworzenie wykresu\n", "liczba_osob_w_szalupach.plot(kind='bar', color='blue')\n", "# Dodanie tytułu i etykiet\n", "plt.title('Liczba osób w każdej szalupie')\n", "plt.xlabel('Szalupy')\n", "plt.ylabel('Liczba osób')\n", "\n", "# Wyświetlenie wykresu\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- Można ustawić szalupy w taki sposób, że pokażą prawie liniowy rozkład liczby rozbitków na szalupę. Min. 5 osób, max.42." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### *boat: porównanie liczby szalup do liczby uratowanych" ] }, { "cell_type": "code", "execution_count": 119, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Liczba szalup: 20\n", "Liczba uratowanych: 500\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Obliczanie liczby szalup ratunkowych\n", "ilosc_szalup = df2['boat'].nunique()\n", "print(f\"Liczba szalup: {ilosc_szalup}\")\n", "# Obliczanie liczby uratowanych pasażerów (survived = 'Tak')\n", "ilosc_uratowanych = df2[df2['survived'] == 'Tak'].shape[0]\n", "print(f\"Liczba uratowanych: {ilosc_uratowanych}\")\n", "# Tworzenie wykresu porównawczego\n", "labels = ['Liczba szalup ratunkowych', 'Liczba uratowanych pasażerów']\n", "values = [ilosc_szalup, ilosc_uratowanych]\n", "\n", "plt.figure(figsize=(8, 6))\n", "plt.bar(labels, values, color=['#1f77b4', '#ff7f0e'])\n", "plt.title('Porównanie liczby szalup ratunkowych do liczby uratowanych pasażerów')\n", "plt.ylabel('Liczba')\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### *body" ] }, { "cell_type": "code", "execution_count": 121, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "liczba_cial: 121\n", "liczba_ofiar: 807\n", "liczba_cial_nieodnalezionych: 686\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Liczba pasażerów, których ciała zostały odnalezione\n", "liczba_cial = df2['body'].notnull().sum()\n", "print(f\"liczba_cial: {liczba_cial}\")\n", "\n", "# Liczba pasażerów, którzy nie przeżyli\n", "liczba_ofiar = df2[df2['survived'] == 'Nie'].shape[0]\n", "print(\"liczba_ofiar:\", liczba_ofiar)\n", "\n", "# Liczba ciał nieodnalezionych\n", "liczba_cial_nieodnalezionych = liczba_ofiar - liczba_cial\n", "print('liczba_cial_nieodnalezionych: ', liczba_cial_nieodnalezionych)\n", "# Przygotowanie danych do wykresu\n", "labels = ['Ciała odnalezione', 'Ciała nieodnalezione']\n", "values = [liczba_cial, liczba_cial_nieodnalezionych]\n", "\n", "# Tworzenie wykresu słupkowego\n", "plt.figure(figsize=(8, 6))\n", "plt.bar(labels, values, color=['#2ca02c', '#d62728'])\n", "plt.title('Liczba odnalezionych i nieodnalezionych ciał pasażerów')\n", "plt.ylabel('Liczba ciał')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- Liczba ciał odnalezionych 121 i 686 nieodnalezionych." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### *home.dest: histogram" ] }, { "cell_type": "code", "execution_count": 122, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Zliczanie liczby pasażerów z każdego miejsca docelowego\n", "home_dest_counts = df2['home.dest'].value_counts()\n", "\n", "# Tworzenie wykresu kołowego\n", "plt.figure(figsize=(8, 8))\n", "home_dest_counts[:10].plot(kind='pie', autopct='%1.1f%%', startangle=90, colors=plt.cm.Paired.colors)\n", "plt.title('Udział pasażerów według miejsca pochodzenia (top 10)')\n", "plt.ylabel('') # Usunięcie etykiety Y dla estetyki\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Wniosek:\n", "- Najwięcej pasażerów pochodziło z NY 44%, London 10%, Montreal 7%, Paryż 6%. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1.3. Podsumowanie\n", "1. W punkcie 1.1.1. podsumowano wstępną analizę i oczyszczanie oraz transformacje danych, któych celem było przygotowanie do wizulizowania i poprawnego wyciągania wniosków. \n", "1. Podstawą dla wizualizacji jest Macierz korelacji. Współczynniki wskazały na zależności do wykonania wykresów:\n", "pclass vs. survived/age/fare/embarked/sex\n", "survived vs. sex/fare/embarked\n", "sex vs. sibsp/parch/fare\n", "age vs. sibsp/parch/fare\n", "sibsp vs. parch/fare/body\n", "parch vs. fare\n", "fare vs. embarked\n", "\n", "Poniżej zebrano wszystkie wnioski z pojedynczych wykresów.\n", "- Statkiem podróżowało 1307 pasażerów. Ilość kobiet 465 , Liczba mężczyzn 842 (w tym liczba wierszy mężczyzn bez tytułu Mr. z przodu nazwiska: 85.\n", "- W katastrofie zginęło 62 %, przeżyło 38% pasażerów.\n", "- Pasażerowie Titanica podróżowali z biletem klasy 3, 1, 2 odpowiednio w kolejności malejącej liczby pasażerów. Najwięcej ofiar posiadało bilet klasy 3, najmniej ofiar - klasy 1. Najwięcej uratowanych miało bilet klasy 1 i 3, najmniej - bilety w klasie 2.\n", "- W klasach 1, 2, 3 uratowanych było odpowiednio: 200,119,181 osób.\n", "- Największa ilość pasażerów była w wieku od 20 do 30 lat.\n", "- Katastrofę Titanica przeżyło najwięcej osób w młodym wieku tj. 24, 22, 30 latków (według histogramu).\n", "- Rozkład wieku pasażerów, którzy zginęli jest identyczny z rozkładem dla tych co przeżyli.\n", "- Katastrofę przeżyło więcej kobiet. Najmniejsze szanse mieli mężczyźni. Przypuszczam, że powodem było pierwszeństwo do szalup dla kobiet i dzieci.\n", "- Rozkład wieku ofiar i uratowanych z poddziałem na płeć jest wręcz identyczny.\n", "- Mediana i wartość Max. dla wieku pokazują, że najlepszą 1. klasę wybierali starsi pasażerowie. Pojedyncze starsze osoby wybierały też klasy niższe 2 i 3.\n", "- Kolumna parch pokazała, że większość osób (1000) podróżowała bez osób spokrewnionych. 307 podróżowało z krewnymi. Z jednym rodzicem albo jednym dzieckiem jest 170 osób. Z dwójką dzieci lub dwojgiem rodziców jest 113 wpisów. Liczba osób należących do rodzin: 519. Liczba unikalnych nazwisk (bez powtórzeń): 209.\n", "- Przeanalizowano wszystkie kabiny z długim oznaczeniem wskazującym na zajmowanie wielu kabin względem sibsp i parch. Przypisane były nie tylko do wielu osób np. rodzin, ale też do osób samotnie podróżujących.\n", "- 336 uratowanych nie miało krewnych na pokładzie. Około 100 ocalonych było z jednym rodzicem albo z jednym dzieckiem na pokładzie Titanica. Kolejne 57 osób, które przeżyły miało dwoje rodziców lub dwójkę dzieci.\n", "- 664 ofiary nie miały krewnych na pokładzie. 70 ofiar było z rodzicem albo z jednym dzieckiem. Dalsze 56 osób miało dwoje rodziców lub dwójkę dzieci.\n", "- Najwięcej sprzedano biletów w cenie do 50 dollars. 20% biletów kosztowało do 100 dollars.\n", "- Liczba wierszy z ceną za bilet 0 dollars: 17\n", "- Ceny dla 1. klasy są najwyższe i mają największy rozrzut. Za najdroższy bilet zapłacono 1000 % średniej ceny (50 $) w tej klasie.\n", "- Generalnie im większy numer klasy biletu tym niższa cena biletu.\n", "- Dla 1. klasy 50 % biletów ma cenę nie wyższą niż 60 dollars. 75% cen mieści się w zakresie do 105 dollars. Maksymalna cena wynosi do 220 dollars. Pojawiły się 4 wartości odstające w zakresie 230-520 dollars.\n", "- Dla 2. klasy 50 % cen biletów nie jest droższa niż 18 dollars. 75% cen mieści się w zakresie do 27 dollars. Maksymalna cena do 42 dollars. Pojawiły się 2 wartości odstające w zakresie 66 i 75 dollars.\n", "- Dla 3. klasy 50 % cen biletów nie jest droższa niż 8 dollars. 75% cen mieści się w zakresie do 17 dollars. Maksymalna cena do 27 dollars. Pojawiły się 8 wartości odstające w zakresie 29-69 dollars.\n", "- Porty dalej oddalone od NY mają ceny średnie wyższe. Od najdalszego: C = Cherbourg, S = Southampton, Q = Queenstown\n", "- Najwięcej osób zaczęło podróż z Cherbourg 900, potem Queenstown 300, Southampton 100 w kolejności malejącej.\n", "- Procentowo najmniej ofiar dla Southampton.\n", "- Najwięcej ocalałych wsiadających w porcie Southampton. Najmniej z Queenstown.\n", "- Najwięcej ofiar wsiadających w porcie Southampton. Najmniej z Queenstown.\n", "- Można ustawić szalupy w taki sposób, że pokażą prawie liniowy rozkład liczby rozbitków pro szalupę. Najwięcej osób w szalupie: 39. Najmniej osób w szalupie: 1.\n", "- Całkowita liczba osób we wszystkich szalupach: 486. Liczba uratowanych w katastrofie: 500. A więc nie wszystkich uratowały tylko szalupy.\n", "- Liczba ciał odnalezionych 121 i 686 nieodnalezionych. Suma 807 ofiar.\n", "- Najwięcej pasażerów pochodziło z NY 44%, London 10%, Montreal 7%, Paryż 6% i innych." ] }, { "cell_type": "markdown", "metadata": {}, "source": [] } ], "metadata": { "kernelspec": { "display_name": "od_zera_do_ai", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.9" } }, "nbformat": 4, "nbformat_minor": 4 }