project-GZ.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Introduction:** \n",
    "\n",
    "On April 14th, 1912, the Titanic, which was the most advanced ship at the time, hit an iceberg and sank (History.com). Though there were 16 lifeboats that could hold a maximum of 1178 people, out of the 2208 passengers on board, only 705 survived (Barrratt 2009). There were three classes and three different resulting fare values for First, Second, and Third class. Third class made up the majority of the passengers with 709 people, but when the Titanic sank, three-quarters of them died in comparison to those in First and Second Class (Person 2011). Therefore our question is given the age, and fare value of the passenger, can we determine if they would have survived or not? The dataset we will be using is a tabular data set with comma-separated variables. It has 10 variables but out of the 10 we will be using three; Survived, Age, and Fare, in order to answer our question."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Preliminary exploratory data analysis:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(tidyverse)\n",
    "library(repr)\n",
    "library(tidymodels)\n",
    "library(forcats)\n",
    "library(broom)\n",
    "options(repr.matrix.max.rows = 6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Parsed with column specification:\n",
      "cols(\n",
      "  PassengerId = \u001b[32mcol_double()\u001b[39m,\n",
      "  Survived = \u001b[32mcol_double()\u001b[39m,\n",
      "  Pclass = \u001b[32mcol_double()\u001b[39m,\n",
      "  Name = \u001b[31mcol_character()\u001b[39m,\n",
      "  Sex = \u001b[31mcol_character()\u001b[39m,\n",
      "  Age = \u001b[32mcol_double()\u001b[39m,\n",
      "  SibSp = \u001b[32mcol_double()\u001b[39m,\n",
      "  Parch = \u001b[32mcol_double()\u001b[39m,\n",
      "  Ticket = \u001b[31mcol_character()\u001b[39m,\n",
      "  Fare = \u001b[32mcol_double()\u001b[39m,\n",
      "  Cabin = \u001b[31mcol_character()\u001b[39m,\n",
      "  Embarked = \u001b[31mcol_character()\u001b[39m\n",
      ")\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "    PassengerId.V1    Survived      Pclass.V1           Name          \n",
       " Min.   :-1.7291368   0:424    Min.   :-1.5652278   Length:712        \n",
       " 1st Qu.:-0.8674827   1:288    1st Qu.:-1.5652278   Class :character  \n",
       " Median :-0.0038857            Median :-0.3691575   Mode  :character  \n",
       " Mean   : 0.0100635            Mean   :-0.0818990                     \n",
       " 3rd Qu.: 0.8985683            3rd Qu.: 0.8269128                     \n",
       " Max.   : 1.7291368            Max.   : 0.8269128                     \n",
       "     Sex                  Age.V1             SibSp.V1            Parch.V1      \n",
       " Length:712         Min.   :-2.015566   Min.   :-0.474279   Min.   :-0.473408  \n",
       " Class :character   1st Qu.:-0.667685   1st Qu.:-0.474279   1st Qu.:-0.473408  \n",
       " Mode  :character   Median :-0.116967   Median :-0.474279   Median :-0.473408  \n",
       "                    Mean   :-0.003926   Mean   :-0.008128   Mean   : 0.063259  \n",
       "                    3rd Qu.: 0.571430   3rd Qu.: 0.432550   3rd Qu.: 0.767199  \n",
       "                    Max.   : 3.462699   Max.   : 4.059867   Max.   : 6.970233  \n",
       "    Ticket                Fare.V1          Cabin             Embarked        \n",
       " Length:712         Min.   :-0.648058   Length:712         Length:712        \n",
       " Class :character   1st Qu.:-0.486064   Class :character   Class :character  \n",
       " Mode  :character   Median :-0.333210   Mode  :character   Mode  :character  \n",
       "                    Mean   : 0.047552                                        \n",
       "                    3rd Qu.: 0.016014                                        \n",
       "                    Max.   : 9.661740                                        \n",
       " DirectRelatives.V1 \n",
       " Min.   :-0.560660  \n",
       " 1st Qu.:-0.560660  \n",
       " Median :-0.560660  \n",
       " Mean   : 0.026048  \n",
       " 3rd Qu.: 0.059127  \n",
       " Max.   : 3.777846  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train <- read_csv(\"train.csv\") %>% mutate(Survived = as_factor(Survived), DirectRelatives = SibSp + Parch) %>% mutate(across(where(is.numeric),scale)) %>%  drop_na(-Cabin)\n",
    "summary(train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dataset uses the following columns:\n",
    "<ul>\n",
    "    <li><em>\"PassengerId\"</em>: Unique identifier for passengers</li>\n",
    "    <li><em>\"Survived\"</em>: Class we are trying to predict, 1=Survived, 2=Passed</li>\n",
    "    <li><em>\"Sex\"</em>: Male or Female</li>\n",
    "    <li><em>\"Age\"</em>: Age in years(Predictor 1)</li>\n",
    "    <li><em>\"SibSp\"</em>: Number of siblings / spouses aboard</li>\n",
    "    <li><em>\"Parch\"</em>: Number of parents / children aboard</li>\n",
    "    <li><em>\"Ticket\"</em>: Ticket number</li>\n",
    "    <li><em>\"Fare\"</em>: Passenger fare (Predictor 2)</li>\n",
    "    <li><em>\"Cabin\"</em>: Cabin number</li>\n",
    "    <li><em>\"Embarked\"</em>: Port of Embarkation(C = Cherbourg, Q = Queenstown, S = Southampton)</li>\n",
    "    <li><em>\"DirectRelatives\"</em>: SibSp + Parch</li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
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8b1Upj/OCEH18qi9q/Uw9upKpk54PgBez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Op1/fVXWLWsrAwAaAtz3HGDM59SubjrC1Xo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\ndOnSpUuXLv8QXQH6MWYljn93fes71RqSbiq9nsjzGa8oWJZ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cQgDSy/K5ciXGBgAAIABJREFUWSoU2882jJHjso1V2t/D0AqCIKWIbFy5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\n4vk3fjPEYlKqbw7cKRGp7RqVqzbI9SuXxXG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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 480,
       "width": 960
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(repr.plot.width = 16, repr.plot.height = 8) \n",
    "train %>% ggplot(aes(x = Age, y =  Fare, colour=Survived)) + \n",
    "           geom_point(alpha = 0.4) +\n",
    "           xlab(\"Age\") +\n",
    "           ylab(\"Fare\") +\n",
    "           ggtitle(\"Age vs Fare\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Methods**: \n",
    "\n",
    "For columns, we choose age, sex, fare, and survived because using age and fare information can determine or compare whether the passenger survived or not. In addition, using the KNN classifies our question, making Tibble and graph simpler to comprehend. For example, we might be attempting to predict whether the passengers on the Titanic survived (1 or 0) depending on their age. We also will stratify Titanic data by sex, ensuring that the same proportion of men and woman is included in both the training and testing sets ( Timbers et al., 2022).  Using three scatter plots, explore the distributions of two variables (age and survived/ sex and survived/ fare and survived) to observe relationships between them. Positive or negative relationships, strong or weak correlations and non-linear or linear relationships can all be detected in the scatter plot."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Expected Outcomes**: \n",
    "\n",
    "From the scatter plot, we could conclude that passengers with higher fares, younger age in both genders, and middle-aged women are likely to survive. This phenomenon reflects the reality of social inequality and the vulnerability of children and women. Higher fares increase the survival chance as they tend to have more incomes and power; not saving them may even put the rescuer into trouble since those people have an excellent background to support them. Plus, children and women are a priority to save since they need more assistance to survive in a disaster, unlike males with a strong ability to respond to an emergency. With over a thousand deaths on the Titanic, this leads us to brainstorm  what evacuation procedures are safer to increase the chance of survival in similar accidents. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**References:** \n",
    "\n",
    "Barratt, Nick (2009). Lost Voices From the Titanic: The Defi History. London: Random House. p. 93. ISBN 978-1-84809-151-1.\n",
    "\n",
    "History.com Editors. “Titanic.” History.com, A&E Television Networks, 9 Nov. 2009, www.history.com/topics/early-20th-century-us/titanic#section_1.\n",
    "\n",
    "Timbers,Tiffany. Campbell, Trevor and Lee, Melissa. Data Science: A First Introduction.\\\n",
    "\n",
    "Person. “Titanic Anniversary: Remembering the Third-Class Passengers.” ABC13 Houston, KTRK-TV, 11 Apr. 2021, abc13.com/titanic-anniversary-immigration-world-history/1874040/#:~:text=Approximately 1,317 passengers died when,their area of the Titanic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Ett0uCwzYRklgLgPAXAggBYUM4Bzsth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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 480,
       "width": 960
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "set.seed(2020) # DO NOT REMOVE\n",
    "\n",
    "recipe <- recipe(Survived ~ Age + Fare , data = train) %>%\n",
    "   step_scale(all_predictors()) %>%\n",
    "    step_center(all_predictors())\n",
    "knn_tune <- nearest_neighbor(weight_func = \"rectangular\", neighbors = tune()) %>%\n",
    "      set_engine(\"kknn\") %>%\n",
    "      set_mode(\"classification\")\n",
    "the_vfold <- vfold_cv(train, v = 5, strata = Survived)\n",
    "\n",
    "k_vals <- tibble(neighbors = seq(from = 1, to = 50, by = 5))\n",
    "results <- workflow() %>%\n",
    "      add_recipe(recipe) %>%\n",
    "      add_model(knn_tune) %>%\n",
    "      tune_grid(resamples = the_vfold, grid = k_vals) %>%\n",
    "      collect_metrics()\n",
    "results %>% filter(.metric == \"accuracy\") %>%\n",
    "                ggplot(aes(x=neighbors, y=mean))+ geom_point() + geom_line()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Parsed with column specification:\n",
      "cols(\n",
      "  PassengerId = \u001b[32mcol_double()\u001b[39m,\n",
      "  Pclass = \u001b[32mcol_double()\u001b[39m,\n",
      "  Name = \u001b[31mcol_character()\u001b[39m,\n",
      "  Sex = \u001b[31mcol_character()\u001b[39m,\n",
      "  Age = \u001b[32mcol_double()\u001b[39m,\n",
      "  SibSp = \u001b[32mcol_double()\u001b[39m,\n",
      "  Parch = \u001b[32mcol_double()\u001b[39m,\n",
      "  Ticket = \u001b[31mcol_character()\u001b[39m,\n",
      "  Fare = \u001b[32mcol_double()\u001b[39m,\n",
      "  Cabin = \u001b[31mcol_character()\u001b[39m,\n",
      "  Embarked = \u001b[31mcol_character()\u001b[39m\n",
      ")\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# train_cluster <- augment(kmeans(only_predictors, centers = 4),only_predictors)\n",
    "# train_cluster %>% ggplot(aes(x = Age, y =  Fare, color=.cluster)) + \n",
    "#            geom_point(alpha = 0.4) +\n",
    "#            labs(x =\"Age\", y= \"Fare\", colour = \"Cluster\")\n",
    "best_spec <- nearest_neighbor(weight_func = \"rectangular\", neighbors = 41) %>%\n",
    "      set_engine(\"kknn\") %>%\n",
    "      set_mode(\"classification\")\n",
    "best_fit <- workflow() %>%\n",
    "      add_recipe(recipe) %>%\n",
    "      add_model(best_spec) %>%\n",
    "        fit(data=train)\n",
    "test <- read_csv(\"test.csv\") %>% mutate(DirectRelatives = SibSp + Parch) %>% mutate(across(where(is.numeric),scale)) %>%  drop_na(-Cabin)\n",
    "predictions <- predict(best_fit,test) %>% bind_cols(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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wpc2qNqfbUpuZEH27Wn+/GY05jkRYiZN/U6v/3QkJA+sAACAASURBVOEB7onEjgyF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\nxIkTl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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 480,
       "width": 960
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "predictions %>% ggplot(aes(x = Age, y =  Fare, colour=.pred_class)) + \n",
    "           geom_point(alpha = 0.4) +\n",
    "           xlab(\"Age\") +\n",
    "           ylab(\"Fare\") +\n",
    "           ggtitle(\"Age vs Fare\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The results support the popular notion that the richer passengers(higher priced fares) were more likely to survive, the explanation may be that the higher the fare the better located the rooms that would allow for a faster evacuation; or more cynically the higher classes were prioritized during evacuation or even to spread the warning of the scale of the situation.\n",
    "\n",
    "As we also expected, the younger people had higher odds of survival, being less vulnerable to the cold weather and more able to rapidly evacuate the boat after the crash."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "We trained a classification algorythm to predict wether a passenger would have survive based on the fare they paid and their age. The "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.0.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}