titanic_survival_exploration.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Machine Learning Engineer Nanodegree\n",
    "## Introduction and Foundations\n",
    "## Project: Titanic Survival Exploration\n",
    "\n",
    "In 1912, the ship RMS Titanic struck an iceberg on its maiden voyage and sank, resulting in the deaths of most of its passengers and crew. In this introductory project, we will explore a subset of the RMS Titanic passenger manifest to determine which features best predict whether someone survived or did not survive. To complete this project, you will need to implement several conditional predictions and answer the questions below. Your project submission will be evaluated based on the completion of the code and your responses to the questions.\n",
    "> **Tip:** Quoted sections like this will provide helpful instructions on how to navigate and use an iPython notebook. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Getting Started\n",
    "To begin working with the RMS Titanic passenger data, we'll first need to `import` the functionality we need, and load our data into a `pandas` DataFrame.  \n",
    "Run the code cell below to load our data and display the first few entries (passengers) for examination using the `.head()` function.\n",
    "> **Tip:** You can run a code cell by clicking on the cell and using the keyboard shortcut **Shift + Enter** or **Shift + Return**. Alternatively, a code cell can be executed using the **Play** button in the hotbar after selecting it. Markdown cells (text cells like this one) can be edited by double-clicking, and saved using these same shortcuts. [Markdown](http://daringfireball.net/projects/markdown/syntax) allows you to write easy-to-read plain text that can be converted to HTML."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\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</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</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</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</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</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",
       "  </tbody>\n",
       "</table>\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",
       "                                                Name     Sex  Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male   22      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female   38      1   \n",
       "2                             Heikkinen, Miss. Laina  female   26      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female   35      1   \n",
       "4                           Allen, Mr. William Henry    male   35      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  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Import libraries necessary for this project\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from IPython.display import display # Allows the use of display() for DataFrames\n",
    "\n",
    "# Import supplementary visualizations code visuals.py\n",
    "import visuals as vs\n",
    "\n",
    "# Pretty display for notebooks\n",
    "%matplotlib inline\n",
    "\n",
    "# Load the dataset\n",
    "in_file = 'titanic_data.csv'\n",
    "full_data = pd.read_csv(in_file)\n",
    "\n",
    "# Print the first few entries of the RMS Titanic data\n",
    "display(full_data.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "From a sample of the RMS Titanic data, we can see the various features present for each passenger on the ship:\n",
    "- **Survived**: Outcome of survival (0 = No; 1 = Yes)\n",
    "- **Pclass**: Socio-economic class (1 = Upper class; 2 = Middle class; 3 = Lower class)\n",
    "- **Name**: Name of passenger\n",
    "- **Sex**: Sex of the passenger\n",
    "- **Age**: Age of the passenger (Some entries contain `NaN`)\n",
    "- **SibSp**: Number of siblings and spouses of the passenger aboard\n",
    "- **Parch**: Number of parents and children of the passenger aboard\n",
    "- **Ticket**: Ticket number of the passenger\n",
    "- **Fare**: Fare paid by the passenger\n",
    "- **Cabin** Cabin number of the passenger (Some entries contain `NaN`)\n",
    "- **Embarked**: Port of embarkation of the passenger (C = Cherbourg; Q = Queenstown; S = Southampton)\n",
    "\n",
    "Since we're interested in the outcome of survival for each passenger or crew member, we can remove the **Survived** feature from this dataset and store it as its own separate variable `outcomes`. We will use these outcomes as our prediction targets.  \n",
    "Run the code cell below to remove **Survived** as a feature of the dataset and store it in `outcomes`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</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>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22</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>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38</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>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26</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>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35</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>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Pclass                                               Name  \\\n",
       "0            1       3                            Braund, Mr. Owen Harris   \n",
       "1            2       1  Cumings, Mrs. John Bradley (Florence Briggs Th...   \n",
       "2            3       3                             Heikkinen, Miss. Laina   \n",
       "3            4       1       Futrelle, Mrs. Jacques Heath (Lily May Peel)   \n",
       "4            5       3                           Allen, Mr. William Henry   \n",
       "\n",
       "      Sex  Age  SibSp  Parch            Ticket     Fare Cabin Embarked  \n",
       "0    male   22      1      0         A/5 21171   7.2500   NaN        S  \n",
       "1  female   38      1      0          PC 17599  71.2833   C85        C  \n",
       "2  female   26      0      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3  female   35      1      0            113803  53.1000  C123        S  \n",
       "4    male   35      0      0            373450   8.0500   NaN        S  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Store the 'Survived' feature in a new variable and remove it from the dataset\n",
    "outcomes = full_data['Survived']\n",
    "data = full_data.drop('Survived', axis = 1)\n",
    "\n",
    "# Show the new dataset with 'Survived' removed\n",
    "display(data.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The very same sample of the RMS Titanic data now shows the **Survived** feature removed from the DataFrame. Note that `data` (the passenger data) and `outcomes` (the outcomes of survival) are now *paired*. That means for any passenger `data.loc[i]`, they have the survival outcome `outcomes[i]`.\n",
    "\n",
    "To measure the performance of our predictions, we need a metric to score our predictions against the true outcomes of survival. Since we are interested in how *accurate* our predictions are, we will calculate the proportion of passengers where our prediction of their survival is correct. Run the code cell below to create our `accuracy_score` function and test a prediction on the first five passengers.  \n",
    "\n",
    "**Think:** *Out of the first five passengers, if we predict that all of them survived, what would you expect the accuracy of our predictions to be?*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predictions have an accuracy of 60.00%.\n"
     ]
    }
   ],
   "source": [
    "def accuracy_score(truth, pred):\n",
    "    \"\"\" Returns accuracy score for input truth and predictions. \"\"\"\n",
    "    \n",
    "    # Ensure that the number of predictions matches number of outcomes\n",
    "    if len(truth) == len(pred): \n",
    "        \n",
    "        # Calculate and return the accuracy as a percent\n",
    "        return \"Predictions have an accuracy of {:.2f}%.\".format((truth == pred).mean()*100)\n",
    "    \n",
    "    else:\n",
    "        return \"Number of predictions does not match number of outcomes!\"\n",
    "    \n",
    "# Test the 'accuracy_score' function\n",
    "predictions = pd.Series(np.ones(5, dtype = int))\n",
    "print accuracy_score(outcomes[:5], predictions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "> **Tip:** If you save an iPython Notebook, the output from running code blocks will also be saved. However, the state of your workspace will be reset once a new session is started. Make sure that you run all of the code blocks from your previous session to reestablish variables and functions before picking up where you last left off.\n",
    "\n",
    "# Making Predictions\n",
    "\n",
    "If we were asked to make a prediction about any passenger aboard the RMS Titanic whom we knew nothing about, then the best prediction we could make would be that they did not survive. This is because we can assume that a majority of the passengers (more than 50%) did not survive the ship sinking.  \n",
    "The `predictions_0` function below will always predict that a passenger did not survive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def predictions_0(data):\n",
    "    \"\"\" Model with no features. Always predicts a passenger did not survive. \"\"\"\n",
    "\n",
    "    predictions = []\n",
    "    for _, passenger in data.iterrows():\n",
    "        \n",
    "        # Predict the survival of 'passenger'\n",
    "        predictions.append(0)\n",
    "    \n",
    "    # Return our predictions\n",
    "    return pd.Series(predictions)\n",
    "\n",
    "# Make the predictions\n",
    "predictions = predictions_0(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Question 1\n",
    "*Using the RMS Titanic data, how accurate would a prediction be that none of the passengers survived?*  \n",
    "**Hint:** Run the code cell below to see the accuracy of this prediction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predictions have an accuracy of 61.62%.\n"
     ]
    }
   ],
   "source": [
    "print accuracy_score(outcomes, predictions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "**Answer:** *Predictions have an accuracy of 61.62%.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "***\n",
    "Let's take a look at whether the feature **Sex** has any indication of survival rates among passengers using the `survival_stats` function. This function is defined in the `titanic_visualizations.py` Python script included with this project. The first two parameters passed to the function are the RMS Titanic data and passenger survival outcomes, respectively. The third parameter indicates which feature we want to plot survival statistics across.  \n",
    "Run the code cell below to plot the survival outcomes of passengers based on their sex."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArMAAAIiCAYAAADb3UD9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f535b3f6650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vs.survival_stats(data, outcomes, 'Sex')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Examining the survival statistics, a large majority of males did not survive the ship sinking. However, a majority of females *did* survive the ship sinking. Let's build on our previous prediction: If a passenger was female, then we will predict that they survived. Otherwise, we will predict the passenger did not survive.  \n",
    "Fill in the missing code below so that the function will make this prediction.  \n",
    "**Hint:** You can access the values of each feature for a passenger like a dictionary. For example, `passenger['Sex']` is the sex of the passenger."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def predictions_1(data):\n",
    "    \"\"\" Model with one feature: \n",
    "            - Predict a passenger survived if they are female. \"\"\"\n",
    "    \n",
    "    predictions = []\n",
    "    for _, passenger in data.iterrows():\n",
    "        \n",
    "        # Remove the 'pass' statement below \n",
    "        # and write your prediction conditions here\n",
    "        #pass\n",
    "        if passenger['Sex'] == 'male':\n",
    "            predictions.append(0)\n",
    "        else:\n",
    "            predictions.append(1)\n",
    "    \n",
    "    # Return our predictions\n",
    "    return pd.Series(predictions)\n",
    "\n",
    "# Make the predictions\n",
    "predictions = predictions_1(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Question 2\n",
    "*How accurate would a prediction be that all female passengers survived and the remaining passengers did not survive?*  \n",
    "**Hint:** Run the code cell below to see the accuracy of this prediction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predictions have an accuracy of 78.68%.\n"
     ]
    }
   ],
   "source": [
    "print accuracy_score(outcomes, predictions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "**Answer**: *Predictions have an accuracy of 78.68%.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "***\n",
    "Using just the **Sex** feature for each passenger, we are able to increase the accuracy of our predictions by a significant margin. Now, let's consider using an additional feature to see if we can further improve our predictions. For example, consider all of the male passengers aboard the RMS Titanic: Can we find a subset of those passengers that had a higher rate of survival? Let's start by looking at the **Age** of each male, by again using the `survival_stats` function. This time, we'll use a fourth parameter to filter out the data so that only passengers with the **Sex** 'male' will be included.  \n",
    "Run the code cell below to plot the survival outcomes of male passengers based on their age."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAroAAAIiCAYAAAAnyGs3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nV5IkSZVk0JUkSVIlGXQlSZJUSf8fsrEpimesw8cAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f535af01310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vs.survival_stats(data, outcomes, 'Age', [\"Sex == 'male'\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "source": [
    "Examining the survival statistics, the majority of males younger than 10 survived the ship sinking, whereas most males age 10 or older *did not survive* the ship sinking. Let's continue to build on our previous prediction: If a passenger was female, then we will predict they survive. If a passenger was male and younger than 10, then we will also predict they survive. Otherwise, we will predict they do not survive.  \n",
    "Fill in the missing code below so that the function will make this prediction.  \n",
    "**Hint:** You can start your implementation of this function using the prediction code you wrote earlier from `predictions_1`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def predictions_2(data):\n",
    "    \"\"\" Model with two features: \n",
    "            - Predict a passenger survived if they are female.\n",
    "            - Predict a passenger survived if they are male and younger than 10. \"\"\"\n",
    "    \n",
    "    predictions = []\n",
    "    for _, passenger in data.iterrows():\n",
    "        \n",
    "        # Remove the 'pass' statement below \n",
    "        # and write your prediction conditions here\n",
    "        #pass\n",
    "        if passenger['Sex'] == 'male':\n",
    "            if passenger['Age'] < 10:\n",
    "                predictions.append(1)\n",
    "            else:\n",
    "                predictions.append(0)\n",
    "        else:\n",
    "            predictions.append(1)\n",
    "    \n",
    "    # Return our predictions\n",
    "    return pd.Series(predictions)\n",
    "\n",
    "# Make the predictions\n",
    "predictions = predictions_2(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Question 3\n",
    "*How accurate would a prediction be that all female passengers and all male passengers younger than 10 survived?*  \n",
    "**Hint:** Run the code cell below to see the accuracy of this prediction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predictions have an accuracy of 79.35%.\n"
     ]
    }
   ],
   "source": [
    "print accuracy_score(outcomes, predictions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "**Answer**: *Predictions have an accuracy of 79.35%.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "source": [
    "***\n",
    "Adding the feature **Age** as a condition in conjunction with **Sex** improves the accuracy by a small margin more than with simply using the feature **Sex** alone. Now it's your turn: Find a series of features and conditions to split the data on to obtain an outcome prediction accuracy of at least 80%. This may require multiple features and multiple levels of conditional statements to succeed. You can use the same feature multiple times with different conditions.   \n",
    "**Pclass**, **Sex**, **Age**, **SibSp**, and **Parch** are some suggested features to try.\n",
    "\n",
    "Use the `survival_stats` function below to to examine various survival statistics.  \n",
    "**Hint:** To use mulitple filter conditions, put each condition in the list passed as the last argument. Example: `[\"Sex == 'male'\", \"Age < 18\"]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArIAAAIiCAYAAAA0HyvDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f535b08b710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAroAAAIiCAYAAAAnyGs3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nV5IkSZVk0JUkSVIlGXQlSZJUSf8fsrEpimesw8cAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f535b5dcd50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pclass: Socio-economic class (1 = Upper class; 2 = Middle class; 3 = Lower class)\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArIAAAIiCAYAAAA0HyvDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f535affb1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArEAAAIiCAYAAADfKJDAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f535adf4490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArIAAAIiCAYAAAA0HyvDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f535adf4810>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SibSp: Number of siblings and spouses of the passenger aboard\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArIAAAIiCAYAAAA0HyvDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQ5B6gAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f535ae9fa90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArMAAAIiCAYAAADb3UD9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f535b193c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parch: Number of parents and children of the passenger aboard\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArIAAAIiCAYAAAA0HyvDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f535b00c610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArMAAAIiCAYAAADb3UD9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/j9qoryppovHiAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f535b2eea10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Embarked: Port of embarkation of the passenger (C = Cherbourg; Q = Queenstown; S = Southampton)\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArIAAAIiCAYAAAA0HyvDAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f535ada7f10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Passengers with missing 'Embarked' values: 2 (2 survived, 0 did not survive)\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAArMAAAIiCAYAAADb3UD9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJUmS1CzDrCRJkpr1/wFMRVkCstFbZgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f535add1f50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#vs.survival_stats(data, outcomes, 'Age', [\"Sex == 'male'\", \"Age < 18\"])\n",
    "vs.survival_stats(data, outcomes, 'Age', [\"Sex == 'female'\"])\n",
    "vs.survival_stats(data, outcomes, 'Age', [\"Sex == 'male'\"])\n",
    "\n",
    "print \"Pclass: Socio-economic class (1 = Upper class; 2 = Middle class; 3 = Lower class)\"\n",
    "vs.survival_stats(data, outcomes, 'Pclass', [\"Sex == 'female'\"])\n",
    "vs.survival_stats(data, outcomes, 'Age', [\"Sex == 'female'\", \"Pclass == 3\"])\n",
    "vs.survival_stats(data, outcomes, 'Pclass', [\"Sex == 'male'\"])\n",
    "\n",
    "print \"SibSp: Number of siblings and spouses of the passenger aboard\"\n",
    "vs.survival_stats(data, outcomes, 'SibSp', [\"Sex == 'female'\"])\n",
    "vs.survival_stats(data, outcomes, 'SibSp', [\"Sex == 'male'\"])\n",
    "\n",
    "print \"Parch: Number of parents and children of the passenger aboard\"\n",
    "vs.survival_stats(data, outcomes, 'Parch', [\"Sex == 'female'\"])\n",
    "vs.survival_stats(data, outcomes, 'Parch', [\"Sex == 'male'\"])\n",
    "\n",
    "print \"Embarked: Port of embarkation of the passenger (C = Cherbourg; Q = Queenstown; S = Southampton)\"\n",
    "vs.survival_stats(data, outcomes, 'Embarked', [\"Sex == 'female'\"])\n",
    "vs.survival_stats(data, outcomes, 'Embarked', [\"Sex == 'male'\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "After exploring the survival statistics visualization, fill in the missing code below so that the function will make your prediction.  \n",
    "Make sure to keep track of the various features and conditions you tried before arriving at your final prediction model.  \n",
    "**Hint:** You can start your implementation of this function using the prediction code you wrote earlier from `predictions_2`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def predictions_3(data):\n",
    "    \"\"\" Model with multiple features. Makes a prediction with an accuracy of at least 80%. \"\"\"\n",
    "    \n",
    "    predictions = []\n",
    "    for _, passenger in data.iterrows():\n",
    "        \n",
    "        # Remove the 'pass' statement below \n",
    "        # and write your prediction conditions here\n",
    "        if passenger['Sex'] == 'male':\n",
    "            if passenger['Age'] < 10:\n",
    "                predictions.append(1)\n",
    "            else:\n",
    "                predictions.append(0)                \n",
    "        else:            \n",
    "            # Age does not matter\n",
    "            #if passenger['Age'] < 50:\n",
    "            #    predictions.append(1)\n",
    "            #else:\n",
    "            #    predictions.append(0) \n",
    "            \n",
    "            # With Family\n",
    "            if passenger['SibSp'] > 2:            \n",
    "                predictions.append(0)                \n",
    "            else:         \n",
    "                predictions.append(1)\n",
    "                \n",
    "            # It is complicated to tie Pclass, Age and SibSp together\n",
    "            # and it does not increase the accuracy.\n",
    "            #if passenger['Pclass'] == 3:\n",
    "            #    if passenger['Age'] < 20:\n",
    "            #        predictions.append(1)\n",
    "            #    else:                    \n",
    "            #        # With Family\n",
    "            #        if passenger['SibSp'] > 2:            \n",
    "            #            predictions.append(0)\n",
    "            #        else:         \n",
    "            #            predictions.append(1)                        \n",
    "            #else:\n",
    "            #    predictions.append(1)\n",
    "    \n",
    "    # Return our predictions\n",
    "    return pd.Series(predictions)\n",
    "\n",
    "# Make the predictions\n",
    "predictions = predictions_3(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Question 4\n",
    "*Describe the steps you took to implement the final prediction model so that it got an accuracy of at least 80%. What features did you look at? Were certain features more informative than others? Which conditions did you use to split the survival outcomes in the data? How accurate are your predictions?*  \n",
    "**Hint:** Run the code cell below to see the accuracy of your predictions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predictions have an accuracy of 80.36%.\n"
     ]
    }
   ],
   "source": [
    "print accuracy_score(outcomes, predictions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "**Answer**: *Predictions have an accuracy of 80.36%.\n",
    "I created several diagrams to see how the age of females influenced their chance of survival -- but I was not able to see any correlation in there. The code I added and then commented out in predictions_3 verified that. Then, I worked reverse on the dataset: At first, I used the Sibling-Feature and was able to increase the accuracy to 80.36%. In a second step, I created some other diagrams on the Sibling, Parch and Embarked features. One diagram verified that the Sibling-Feature is connected to females. Other correlations are also visible in the remaining diagrams. But it is complicated to use these possible correlations to increase the accuracy due to deeply nested if-else statements. I think I will learn techniques later in this nanodegree which allow using expected correlations more easily.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Conclusion\n",
    "\n",
    "After several iterations of exploring and conditioning on the data, you have built a useful algorithm for predicting the survival of each passenger aboard the RMS Titanic. The technique applied in this project is a manual implementation of a simple machine learning model, the *decision tree*. A decision tree splits a set of data into smaller and smaller groups (called *nodes*), by one feature at a time. Each time a subset of the data is split, our predictions become more accurate if each of the resulting subgroups are more homogeneous (contain similar labels) than before. The advantage of having a computer do things for us is that it will be more exhaustive and more precise than our manual exploration above. [This link](http://www.r2d3.us/visual-intro-to-machine-learning-part-1/) provides another introduction into machine learning using a decision tree.\n",
    "\n",
    "A decision tree is just one of many models that come from *supervised learning*. In supervised learning, we attempt to use features of the data to predict or model things with objective outcome labels. That is to say, each of our data points has a known outcome value, such as a categorical, discrete label like `'Survived'`, or a numerical, continuous value like predicting the price of a house.\n",
    "\n",
    "### Question 5\n",
    "*Think of a real-world scenario where supervised learning could be applied. What would be the outcome variable that you are trying to predict? Name two features about the data used in this scenario that might be helpful for making the predictions.*  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "source": [
    "**Answer**: *I could build a machine -- in this scenario a smart oven. This oven could predict and show the time (outcome variable) until the water inside a pot boils. The smart oven could calculate the amount of water (Feature A) inside the pot by measuring the size of the pot and level of water inside of the pot. A thermometer could return the current temperature (Feature B) value and use it in the prediction. This oven could also be made to estimate the time until milk, pudding or other food boils by using supervised parameter.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "> **Note**: Once you have completed all of the code implementations and successfully answered each question above, you may finalize your work by exporting the iPython Notebook as an HTML document. You can do this by using the menu above and navigating to  \n",
    "**File -> Download as -> HTML (.html)**. Include the finished document along with this notebook as your submission."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}