From bb84846b3322d02b42ab9cdc1b2e2a399402b2d0 Mon Sep 17 00:00:00 2001
From: Louise <louicosta.silva@gmail.com>
Date: Thu, 23 Nov 2023 21:02:13 -0300
Subject: [PATCH] :memo: Entrega de atividade de casa

---
 exercicios/para-casa/ativcasa-s12.ipynb | 451 ++++++++++++
 exercicios/para-casa/titanic.csv        | 892 ++++++++++++++++++++++++
 2 files changed, 1343 insertions(+)
 create mode 100644 exercicios/para-casa/ativcasa-s12.ipynb
 create mode 100644 exercicios/para-casa/titanic.csv

diff --git a/exercicios/para-casa/ativcasa-s12.ipynb b/exercicios/para-casa/ativcasa-s12.ipynb
new file mode 100644
index 0000000..077b815
--- /dev/null
+++ b/exercicios/para-casa/ativcasa-s12.ipynb
@@ -0,0 +1,451 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "from mpl_toolkits import mplot3d"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <iframe\n",
+       "            width=\"200\"\n",
+       "            height=\"200\"\n",
+       "            src=\"https://giphy.com/embed/uhB0n3Eac8ybe\"\n",
+       "            frameborder=\"0\"\n",
+       "            allowfullscreen\n",
+       "            \n",
+       "        ></iframe>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.IFrame at 0x1f720fe3ad0>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from IPython.display import IFrame\n",
+    "iframe_url = \"https://giphy.com/embed/uhB0n3Eac8ybe\"\n",
+    "IFrame(src=iframe_url, width=200, height=200)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PassengerId</th>\n",
+       "      <th>Survived</th>\n",
+       "      <th>Pclass</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Sex</th>\n",
+       "      <th>Age</th>\n",
+       "      <th>SibSp</th>\n",
+       "      <th>Parch</th>\n",
+       "      <th>Ticket</th>\n",
+       "      <th>Fare</th>\n",
+       "      <th>Cabin</th>\n",
+       "      <th>Embarked</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Braund, Mr. Owen Harris</td>\n",
+       "      <td>male</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>A/5 21171</td>\n",
+       "      <td>7.2500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
+       "      <td>female</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>PC 17599</td>\n",
+       "      <td>71.2833</td>\n",
+       "      <td>C85</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Heikkinen, Miss. Laina</td>\n",
+       "      <td>female</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>STON/O2. 3101282</td>\n",
+       "      <td>7.9250</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
+       "      <td>female</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>113803</td>\n",
+       "      <td>53.1000</td>\n",
+       "      <td>C123</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Allen, Mr. William Henry</td>\n",
+       "      <td>male</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>373450</td>\n",
+       "      <td>8.0500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>886</th>\n",
+       "      <td>887</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Montvila, Rev. Juozas</td>\n",
+       "      <td>male</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>211536</td>\n",
+       "      <td>13.0000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>887</th>\n",
+       "      <td>888</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Graham, Miss. Margaret Edith</td>\n",
+       "      <td>female</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>112053</td>\n",
+       "      <td>30.0000</td>\n",
+       "      <td>B42</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>888</th>\n",
+       "      <td>889</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
+       "      <td>female</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>W./C. 6607</td>\n",
+       "      <td>23.4500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>S</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>889</th>\n",
+       "      <td>890</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Behr, Mr. Karl Howell</td>\n",
+       "      <td>male</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>111369</td>\n",
+       "      <td>30.0000</td>\n",
+       "      <td>C148</td>\n",
+       "      <td>C</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>890</th>\n",
+       "      <td>891</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Dooley, Mr. Patrick</td>\n",
+       "      <td>male</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>370376</td>\n",
+       "      <td>7.7500</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Q</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>891 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     PassengerId  Survived  Pclass  \\\n",
+       "0              1         0       3   \n",
+       "1              2         1       1   \n",
+       "2              3         1       3   \n",
+       "3              4         1       1   \n",
+       "4              5         0       3   \n",
+       "..           ...       ...     ...   \n",
+       "886          887         0       2   \n",
+       "887          888         1       1   \n",
+       "888          889         0       3   \n",
+       "889          890         1       1   \n",
+       "890          891         0       3   \n",
+       "\n",
+       "                                                  Name     Sex   Age  SibSp  \\\n",
+       "0                              Braund, Mr. Owen Harris    male  22.0      1   \n",
+       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
+       "2                               Heikkinen, Miss. Laina  female  26.0      0   \n",
+       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
+       "4                             Allen, Mr. William Henry    male  35.0      0   \n",
+       "..                                                 ...     ...   ...    ...   \n",
+       "886                              Montvila, Rev. Juozas    male  27.0      0   \n",
+       "887                       Graham, Miss. Margaret Edith  female  19.0      0   \n",
+       "888           Johnston, Miss. Catherine Helen \"Carrie\"  female   NaN      1   \n",
+       "889                              Behr, Mr. Karl Howell    male  26.0      0   \n",
+       "890                                Dooley, Mr. Patrick    male  32.0      0   \n",
+       "\n",
+       "     Parch            Ticket     Fare Cabin Embarked  \n",
+       "0        0         A/5 21171   7.2500   NaN        S  \n",
+       "1        0          PC 17599  71.2833   C85        C  \n",
+       "2        0  STON/O2. 3101282   7.9250   NaN        S  \n",
+       "3        0            113803  53.1000  C123        S  \n",
+       "4        0            373450   8.0500   NaN        S  \n",
+       "..     ...               ...      ...   ...      ...  \n",
+       "886      0            211536  13.0000   NaN        S  \n",
+       "887      0            112053  30.0000   B42        S  \n",
+       "888      2        W./C. 6607  23.4500   NaN        S  \n",
+       "889      0            111369  30.0000  C148        C  \n",
+       "890      0            370376   7.7500   NaN        Q  \n",
+       "\n",
+       "[891 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv(\"titanic.csv\")\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Distribuição de Idades')"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Distribuição de idade dos passageiros no navio\n",
+    "df['Age'].plot.hist(bins=20, edgecolor='black', color = 'purple')\n",
+    "\n",
+    "plt.xlabel('Idades')\n",
+    "plt.ylabel('Quantidade')\n",
+    "plt.title('Distribuição de Idades')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 800x600 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Taxa de Sobrevivência por Classe e Sexo\n",
+    "survival_by_class_sex = df.groupby(['Pclass', 'Sex'])['Survived'].mean().unstack()\n",
+    "\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "survival_by_class_sex.plot(kind='bar', stacked=True, color=['purple', 'blue'])\n",
+    "plt.title('Taxa de Sobrevivência por Classe e Sexo')\n",
+    "plt.xlabel('Classe')\n",
+    "plt.ylabel('Taxa de Sobrevivência')\n",
+    "plt.legend(title='Sexo', loc='upper left', labels=['Feminino', 'Masculino'])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Número de pessoas por porto')"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Número de pessoas por Porto de Embarque\n",
+    "people_per_harbor = df['Embarked'].value_counts()\n",
+    "people_per_harbor.plot.bar(color=\"purple\")\n",
+    "\n",
+    "plt.xlabel('Embarcado')\n",
+    "plt.ylabel('Quantidade')\n",
+    "plt.title('Número de pessoas por porto')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Podemos concluir que a quantidade maior de pessoas tinham entre 20 e 30 anos no embarque e que a maior taxa de sobrevivência em todas as classes foi do gênero feminino pela questão delas terem sido as primeiras a serem evacuadas no acidente. O porto S(Southampton) foi o que mais teve embarque de passageiros no navio."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/exercicios/para-casa/titanic.csv b/exercicios/para-casa/titanic.csv
new file mode 100644
index 0000000..5cc466e
--- /dev/null
+++ b/exercicios/para-casa/titanic.csv
@@ -0,0 +1,892 @@
+PassengerId,Survived,Pclass,Name,Sex,Age,SibSp,Parch,Ticket,Fare,Cabin,Embarked
+1,0,3,"Braund, Mr. Owen Harris",male,22,1,0,A/5 21171,7.25,,S
+2,1,1,"Cumings, Mrs. John Bradley (Florence Briggs Thayer)",female,38,1,0,PC 17599,71.2833,C85,C
+3,1,3,"Heikkinen, Miss. Laina",female,26,0,0,STON/O2. 3101282,7.925,,S
+4,1,1,"Futrelle, Mrs. Jacques Heath (Lily May Peel)",female,35,1,0,113803,53.1,C123,S
+5,0,3,"Allen, Mr. William Henry",male,35,0,0,373450,8.05,,S
+6,0,3,"Moran, Mr. James",male,,0,0,330877,8.4583,,Q
+7,0,1,"McCarthy, Mr. Timothy J",male,54,0,0,17463,51.8625,E46,S
+8,0,3,"Palsson, Master. Gosta Leonard",male,2,3,1,349909,21.075,,S
+9,1,3,"Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)",female,27,0,2,347742,11.1333,,S
+10,1,2,"Nasser, Mrs. Nicholas (Adele Achem)",female,14,1,0,237736,30.0708,,C
+11,1,3,"Sandstrom, Miss. Marguerite Rut",female,4,1,1,PP 9549,16.7,G6,S
+12,1,1,"Bonnell, Miss. Elizabeth",female,58,0,0,113783,26.55,C103,S
+13,0,3,"Saundercock, Mr. William Henry",male,20,0,0,A/5. 2151,8.05,,S
+14,0,3,"Andersson, Mr. Anders Johan",male,39,1,5,347082,31.275,,S
+15,0,3,"Vestrom, Miss. Hulda Amanda Adolfina",female,14,0,0,350406,7.8542,,S
+16,1,2,"Hewlett, Mrs. (Mary D Kingcome) ",female,55,0,0,248706,16,,S
+17,0,3,"Rice, Master. Eugene",male,2,4,1,382652,29.125,,Q
+18,1,2,"Williams, Mr. Charles Eugene",male,,0,0,244373,13,,S
+19,0,3,"Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)",female,31,1,0,345763,18,,S
+20,1,3,"Masselmani, Mrs. Fatima",female,,0,0,2649,7.225,,C
+21,0,2,"Fynney, Mr. Joseph J",male,35,0,0,239865,26,,S
+22,1,2,"Beesley, Mr. Lawrence",male,34,0,0,248698,13,D56,S
+23,1,3,"McGowan, Miss. Anna ""Annie""",female,15,0,0,330923,8.0292,,Q
+24,1,1,"Sloper, Mr. William Thompson",male,28,0,0,113788,35.5,A6,S
+25,0,3,"Palsson, Miss. Torborg Danira",female,8,3,1,349909,21.075,,S
+26,1,3,"Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)",female,38,1,5,347077,31.3875,,S
+27,0,3,"Emir, Mr. Farred Chehab",male,,0,0,2631,7.225,,C
+28,0,1,"Fortune, Mr. Charles Alexander",male,19,3,2,19950,263,C23 C25 C27,S
+29,1,3,"O'Dwyer, Miss. Ellen ""Nellie""",female,,0,0,330959,7.8792,,Q
+30,0,3,"Todoroff, Mr. Lalio",male,,0,0,349216,7.8958,,S
+31,0,1,"Uruchurtu, Don. Manuel E",male,40,0,0,PC 17601,27.7208,,C
+32,1,1,"Spencer, Mrs. William Augustus (Marie Eugenie)",female,,1,0,PC 17569,146.5208,B78,C
+33,1,3,"Glynn, Miss. Mary Agatha",female,,0,0,335677,7.75,,Q
+34,0,2,"Wheadon, Mr. Edward H",male,66,0,0,C.A. 24579,10.5,,S
+35,0,1,"Meyer, Mr. Edgar Joseph",male,28,1,0,PC 17604,82.1708,,C
+36,0,1,"Holverson, Mr. Alexander Oskar",male,42,1,0,113789,52,,S
+37,1,3,"Mamee, Mr. Hanna",male,,0,0,2677,7.2292,,C
+38,0,3,"Cann, Mr. Ernest Charles",male,21,0,0,A./5. 2152,8.05,,S
+39,0,3,"Vander Planke, Miss. Augusta Maria",female,18,2,0,345764,18,,S
+40,1,3,"Nicola-Yarred, Miss. Jamila",female,14,1,0,2651,11.2417,,C
+41,0,3,"Ahlin, Mrs. Johan (Johanna Persdotter Larsson)",female,40,1,0,7546,9.475,,S
+42,0,2,"Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott)",female,27,1,0,11668,21,,S
+43,0,3,"Kraeff, Mr. Theodor",male,,0,0,349253,7.8958,,C
+44,1,2,"Laroche, Miss. Simonne Marie Anne Andree",female,3,1,2,SC/Paris 2123,41.5792,,C
+45,1,3,"Devaney, Miss. Margaret Delia",female,19,0,0,330958,7.8792,,Q
+46,0,3,"Rogers, Mr. William John",male,,0,0,S.C./A.4. 23567,8.05,,S
+47,0,3,"Lennon, Mr. Denis",male,,1,0,370371,15.5,,Q
+48,1,3,"O'Driscoll, Miss. Bridget",female,,0,0,14311,7.75,,Q
+49,0,3,"Samaan, Mr. Youssef",male,,2,0,2662,21.6792,,C
+50,0,3,"Arnold-Franchi, Mrs. Josef (Josefine Franchi)",female,18,1,0,349237,17.8,,S
+51,0,3,"Panula, Master. Juha Niilo",male,7,4,1,3101295,39.6875,,S
+52,0,3,"Nosworthy, Mr. Richard Cater",male,21,0,0,A/4. 39886,7.8,,S
+53,1,1,"Harper, Mrs. Henry Sleeper (Myna Haxtun)",female,49,1,0,PC 17572,76.7292,D33,C
+54,1,2,"Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson)",female,29,1,0,2926,26,,S
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+57,1,2,"Rugg, Miss. Emily",female,21,0,0,C.A. 31026,10.5,,S
+58,0,3,"Novel, Mr. Mansouer",male,28.5,0,0,2697,7.2292,,C
+59,1,2,"West, Miss. Constance Mirium",female,5,1,2,C.A. 34651,27.75,,S
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+61,0,3,"Sirayanian, Mr. Orsen",male,22,0,0,2669,7.2292,,C
+62,1,1,"Icard, Miss. Amelie",female,38,0,0,113572,80,B28,
+63,0,1,"Harris, Mr. Henry Birkhardt",male,45,1,0,36973,83.475,C83,S
+64,0,3,"Skoog, Master. Harald",male,4,3,2,347088,27.9,,S
+65,0,1,"Stewart, Mr. Albert A",male,,0,0,PC 17605,27.7208,,C
+66,1,3,"Moubarek, Master. Gerios",male,,1,1,2661,15.2458,,C
+67,1,2,"Nye, Mrs. (Elizabeth Ramell)",female,29,0,0,C.A. 29395,10.5,F33,S
+68,0,3,"Crease, Mr. Ernest James",male,19,0,0,S.P. 3464,8.1583,,S
+69,1,3,"Andersson, Miss. Erna Alexandra",female,17,4,2,3101281,7.925,,S
+70,0,3,"Kink, Mr. Vincenz",male,26,2,0,315151,8.6625,,S
+71,0,2,"Jenkin, Mr. Stephen Curnow",male,32,0,0,C.A. 33111,10.5,,S
+72,0,3,"Goodwin, Miss. Lillian Amy",female,16,5,2,CA 2144,46.9,,S
+73,0,2,"Hood, Mr. Ambrose Jr",male,21,0,0,S.O.C. 14879,73.5,,S
+74,0,3,"Chronopoulos, Mr. Apostolos",male,26,1,0,2680,14.4542,,C
+75,1,3,"Bing, Mr. Lee",male,32,0,0,1601,56.4958,,S
+76,0,3,"Moen, Mr. Sigurd Hansen",male,25,0,0,348123,7.65,F G73,S
+77,0,3,"Staneff, Mr. Ivan",male,,0,0,349208,7.8958,,S
+78,0,3,"Moutal, Mr. Rahamin Haim",male,,0,0,374746,8.05,,S
+79,1,2,"Caldwell, Master. Alden Gates",male,0.83,0,2,248738,29,,S
+80,1,3,"Dowdell, Miss. Elizabeth",female,30,0,0,364516,12.475,,S
+81,0,3,"Waelens, Mr. Achille",male,22,0,0,345767,9,,S
+82,1,3,"Sheerlinck, Mr. Jan Baptist",male,29,0,0,345779,9.5,,S
+83,1,3,"McDermott, Miss. Brigdet Delia",female,,0,0,330932,7.7875,,Q
+84,0,1,"Carrau, Mr. Francisco M",male,28,0,0,113059,47.1,,S
+85,1,2,"Ilett, Miss. Bertha",female,17,0,0,SO/C 14885,10.5,,S
+86,1,3,"Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson)",female,33,3,0,3101278,15.85,,S
+87,0,3,"Ford, Mr. William Neal",male,16,1,3,W./C. 6608,34.375,,S
+88,0,3,"Slocovski, Mr. Selman Francis",male,,0,0,SOTON/OQ 392086,8.05,,S
+89,1,1,"Fortune, Miss. Mabel Helen",female,23,3,2,19950,263,C23 C25 C27,S
+90,0,3,"Celotti, Mr. Francesco",male,24,0,0,343275,8.05,,S
+91,0,3,"Christmann, Mr. Emil",male,29,0,0,343276,8.05,,S
+92,0,3,"Andreasson, Mr. Paul Edvin",male,20,0,0,347466,7.8542,,S
+93,0,1,"Chaffee, Mr. Herbert Fuller",male,46,1,0,W.E.P. 5734,61.175,E31,S
+94,0,3,"Dean, Mr. Bertram Frank",male,26,1,2,C.A. 2315,20.575,,S
+95,0,3,"Coxon, Mr. Daniel",male,59,0,0,364500,7.25,,S
+96,0,3,"Shorney, Mr. Charles Joseph",male,,0,0,374910,8.05,,S
+97,0,1,"Goldschmidt, Mr. George B",male,71,0,0,PC 17754,34.6542,A5,C
+98,1,1,"Greenfield, Mr. William Bertram",male,23,0,1,PC 17759,63.3583,D10 D12,C
+99,1,2,"Doling, Mrs. John T (Ada Julia Bone)",female,34,0,1,231919,23,,S
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+112,0,3,"Zabour, Miss. Hileni",female,14.5,1,0,2665,14.4542,,C
+113,0,3,"Barton, Mr. David John",male,22,0,0,324669,8.05,,S
+114,0,3,"Jussila, Miss. Katriina",female,20,1,0,4136,9.825,,S
+115,0,3,"Attalah, Miss. Malake",female,17,0,0,2627,14.4583,,C
+116,0,3,"Pekoniemi, Mr. Edvard",male,21,0,0,STON/O 2. 3101294,7.925,,S
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+128,1,3,"Madsen, Mr. Fridtjof Arne",male,24,0,0,C 17369,7.1417,,S
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+130,0,3,"Ekstrom, Mr. Johan",male,45,0,0,347061,6.975,,S
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