diff --git a/Titanic.ipynb b/Titanic.ipynb new file mode 100644 index 0000000..6d3ffb5 --- /dev/null +++ b/Titanic.ipynb @@ -0,0 +1,1003 @@ +{ + "metadata": { + "name": "", + "signature": "sha256:352b9049d2b7bb4793fce0772451218844917fe69f0a08d1ec1e5b997987aac3" + }, + "nbformat": 3, + "nbformat_minor": 0, + "worksheets": [ + { + "cells": [ + { + "cell_type": "code", + "collapsed": false, + "input": [ + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from collections import Counter" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 68 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%matplotlib inline" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 69 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "training_data = pd.read_csv(\"train.csv\")" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 70 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "training_data.info()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "\n", + "Int64Index: 891 entries, 0 to 890\n", + "Data columns (total 12 columns):\n", + "PassengerId 891 non-null int64\n", + "Survived 891 non-null int64\n", + "Pclass 891 non-null int64\n", + "Name 891 non-null object\n", + "Sex 891 non-null object\n", + "Age 714 non-null float64\n", + "SibSp 891 non-null int64\n", + "Parch 891 non-null int64\n", + "Ticket 891 non-null object\n", + "Fare 891 non-null float64\n", + "Cabin 204 non-null object\n", + "Embarked 889 non-null object\n", + "dtypes: float64(2), int64(5), object(5)\n", + "memory usage: 90.5+ KB\n" + ] + } + ], + "prompt_number": 71 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "* PassengerID - ID Number of the Passenger\n", + "* Survived - Boolean 1 for Survived, 0 for Did Not Survive\n", + "* Pclass - Passenger Ticket Class - 1, 2 or 3\n", + "* Sex - Gender of Passenger\n", + "* Age - Age of Passenger\n", + "* SibSp - Number of Siblings or Spouse on Board\n", + "* Parch - Number of Parents/Children Aboard\n", + "* Ticket - Ticket Number\n", + "* Fare - Price Paid for Ticket\n", + "* Cabin - Cabin Number\n", + "* Embarked - Location Passenger Boarded" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "training_data.Embarked" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 72, + "text": [ + "0 S\n", + "1 C\n", + "2 S\n", + "3 S\n", + "4 S\n", + "5 Q\n", + "6 S\n", + "7 S\n", + "8 S\n", + "9 C\n", + "10 S\n", + "11 S\n", + "12 S\n", + "13 S\n", + "14 S\n", + "...\n", + "876 S\n", + "877 S\n", + "878 S\n", + "879 C\n", + "880 S\n", + "881 S\n", + "882 S\n", + "883 S\n", + "884 S\n", + "885 Q\n", + "886 S\n", + "887 S\n", + "888 S\n", + "889 C\n", + "890 Q\n", + "Name: Embarked, Length: 891, dtype: object" + ] + } + ], + "prompt_number": 72 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finding the percentage of total people who survived." + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "training_data.Survived.mean()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 73, + "text": [ + "0.38383838383838381" + ] + } + ], + "prompt_number": 73 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Looking at Potential Groupings" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "pd.pivot_table(training_data, index=[\"Sex\"], values=[\"Survived\"]).plot(kind=\"barh\")\n", + "plt.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAZcAAAD9CAYAAABwfjqFAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAEoVJREFUeJzt3XuQXGWdxvHvJDFCLuQiE+QSMhjCq664i0YEQTFcygsk\nC6tAARo0IhDKxAIB5epusbWAG2IlFIsgphZRsMRylQWBFYyLF3SBZRFd+CVcwiUKiZlsyEUuA71/\ndE8cAjM9iW+fk875fqpS6e5z+vQzp2f6mfec7nc6arUakiTlNKTsAJKkbY/lIknKznKRJGVnuUiS\nsrNcJEnZWS6SpOyGlR2gSD09L9dWr95Qdoymxo0bgTnzaIeMYM7czJlXZ+fojs29T6VGLnvuObns\nCIMybNjQsiMMSjvkbIeMYM7czFm+SpWLJKkYloskKTvLRZKUneUiScrOcpEkZVepclm2bFnZESSp\nEir1ORdJAnjxxRd56qknsm5z4sRJDB8+POs225nlIqlynnrqCT7/zzcxYsyELNvbsGYFC86aweTJ\nUwZc77rr/pX77vsvenp6GDJkCOeffy4TJuy+RY+5cOFlHHvsCey005u36P7z51/KtGmHss8+796i\n+zdjuUiqpBFjJjBq3K6FPd7jjz/GL395F1deuQiApUuXcO6553LNNd/aou3NnfuFvyhPR8dmf+h+\ns1TqnIsklWXUqFE8++yz3HzzD1m5cgVTpuzFjTfeyOc+dzJPPlk/RPeDH3yPRYuu5pln/sDMmccy\nZ84pXH/9N/nEJ47euJ358y/lrrt+ypw5p/Dkk8s46aSZPPPMHwBYvPgOFiy4jPXr13H++Wczd+6p\nzJ17Ko899sjG7c+adQJnnDGHpUuXtPTrtVwkqQCdnRO45JLLePDBBzj11FmccMLHWbx48SYjiD9f\n7u7u5qtfvYLjj5/J5Ml78sAD9/Piiy9y//33ccAB79+43hFHzOC2224B4NZbb2bGjKO49tpFTJ26\nLwsXfo2zzjqXefMuYfXq1Xz3uzdw9dXXMm/eAjo6Olo6eqnUYbGuri7uuefBsmNIqqDly59m5MhR\nnHPOhQA8/PBDnHXWXMaP33HjOrVabePlnXfehWHD6i/R06cfxa233syqVas48MCDGDq0d06yDg47\n7MOcdtpnOeKII1m/fj177PEWHnvsEe6//17uvPPHAKxd+xzLlz/FpEl7bNzm3nv/9aseLzdHLpJU\ngEceWcr8+V+hp6cHgIkTJzJmzBjGjh3LH/+4EoAlSx7euP6QIX9+eZ46dV+WLAluueUmpk8/8lXb\nHTlyFCm9lYULL+Pww2cAMGnSHhxzzPFcfvlVXHjhRXzkI0ew22678/jjj/HCC89Tq9V46KHfOXKR\npNw2rFlR6LYOOmgaTzzxOCedNJPtt9+eWq3G2Wefzfr1LzF//qVMmPBmOjs7N77gb/rCP23aIdx7\n7z3ssstr34QwY8ZRnHnmXM4778sAnHjiLC6++CJuuunfWL9+PZ/5zCmMHTuWE0+cxezZJ7HDDjsw\ndGhrX/47Wjks2tp0dXXV2uGwWGfnaFauXFt2jKbaIWc7ZARz5tYs59byOZc22p+bPcRx5CKpcoYP\nH970Myn6y3jORZKUXaXKxbnFJKkYlSoXSVIxLBdJUnaWiyQpO8tFkpSd5SJJyq5S5dLV1VV2BEmq\nhEqViySpGJX6hH5PTw+PPrq07BhNrV49iu7udWXHeBX/hKukzVGpclm5eh3nXP2rsmO0ncH+CVdJ\n6lWpcukYMrTQP2sqSVXlORdJUnaVKpf9j76o7AiSVAmVKhdJUjEsF0lSdpaLJCk7y0WSlJ3lIknK\nrlLlcveNF5QdQZIqoVLlIkkqhuUiScrOcpEkZWe5SJKys1wkSdlVqlycW0ySilGpcpEkFcNykSRl\nZ7lIkrKzXCRJ2VkukqTsKlUuzi0mScWoVLlIkophuUiSsmu7ckkpfSqldHHZOSRJ/Wu7cgFqZQeQ\nJA1sWJkPnlL6FDAd2A7YGVgA/C3wDuBMYHfgKGAk8MfG5Y4+958DHEe9cL4TEZcXGF+S1I9Sy6Vh\nZER8OKV0LHB6ROyXUvogcDpwL3BoRNRSSrcB76ExckkpvR04BjiA+gjsP1JKt0fEkv4eyLnFttz4\n8aPo7Bz9mttf77atTTtkBHPmZs5ylV0uNeB/GpfXAA81Lv8fMBx4CbghpbQO2A14Q5/7/hUwCfhJ\n4/pYYE+g33LRluvuXsfKlWtfdVtn5+jX3La1aYeMYM7czJnXlhRg2eUC/Z9DeSNwZGMkM4L6KKaj\nz/IAfhcRHwFIKZ0B/KalSSVJg7I1lUttk8svAetSSndRP9/y38Auvcsj4jcppTtTSj+nfs7mV8Dv\ni4stSepPqeUSEdf2uXw7cHvj8gPAhwZx/3nAvJYFlCRtkXZ8K7IkaStXqXJxbjFJKkalykWSVAzL\nRZKUneUiScrOcpEkZWe5SJKyq1S5OLeYJBWjUuUiSSqG5SJJys5ykSRlZ7lIkrKzXCRJ2VWqXJxb\nTJKKUalykSQVw3KRJGVnuUiSsrNcJEnZWS6SpOwqVS7OLSZJxahUuUiSimG5SJKyG1Z2gCJtWLOi\n7Ahtyf0maXNVqlyuu/h4urvXlR2jqfHjR211OSdOnFR2BEltpFLlstdee7Fy5dqyYzTV2Tm6LXJK\nUn8qdc6lq6ur7AiSVAmVKhdJUjEsF0lSdpaLJCk7y0WSlJ3lIknKrlLlsmzZsrIjSFIlVKpcJEnF\nsFwkSdlZLpKk7CwXSVJ2loskKbtKlYtzi0lSMSpVLpKkYlgukqTsLBdJUnaWiyQpO8tFkpRdpcrF\nucUkqRhNyyWldOom10eklK5oXSRJUrsbNoh1jkopTQdmAQm4Bri9pakkSW2t6cglIj4E/AgI4Abg\nhIiY0+pgkqT2NZjDYgcDc6gXSwDnpZR2bXUwSVL7GswJ/W8AsyNiNnAI8GPgnpamkiS1tcGUyzsj\nYjFARNQi4grggNbGag3nFpOkYgzmhP6bUkrfB/YAPgB8m/rJfUmSXtdgRi5XAfOAtcAz1Mvl2laG\nkiS1t8GUy44RcTtARLwSEdcAY1obS5LUzgZTLhtSSrv1XkkpHQg837pIkqR2N5hzLmcAtwBvSSk9\nAIwHjm5pKklSWxtw5NL4ZH438B7gK8Aq4Drg3tZHy8+5xSSpGP2WS0rpTODLwHbAW4FzgOuB7amf\n4Jck6XUNNHKZCRwUEb8Djgd+2DiZfwbw4SLCSZLa00Dl8kpErG9cnkZjssqIqAG1VgeTJLWvgU7o\n96SUxgEjgX1olEtKaXfgpQKySZLa1EAjl0uA+4FfA9dExB9SSkcDP8FzLpKkAfRbLhHxPepziH00\nIk5r3LwBOCkivllEuNycW0ySijHg51wiYjmwvM/1W1qeSJLU9gbzCX1JkjaL5SJJys5ykSRlZ7lI\nkrKrVLk4t5gkFaNS5SJJKoblIknKznKRJGVnuUiSsrNcJEnZVapcnFtMkopRqXKRJBXDcpEkZWe5\nSJKys1wkSdkN+PdctjU9PT08+ujSsmM0tXr1KLq715Udo6l2yNkOGcGcuVUp58SJkxg+fHimRPl0\n1Gq1sjMU5r0f+/vaiDETyo4hSVlsWLOCBWfNYPLkKS19nM7O0R2be59KjVxGjJnAqHG7lh1DkrZ5\nnnORJGVnuUiSsrNcJEnZWS6SpOwqVS5333hB2REkqRIqVS6SpGJYLpKk7CwXSVJ2loskKTvLRZKU\nXaXKZf+jLyo7giRVQqXKRZJUDMtFkpSd5SJJys5ykSRlZ7lIkrKrVLk4t5gkFaNS5SJJKoblIknK\nznKRJGVnuUiSsrNcJEnZDWvVhlNKQ4E7gDcAh0fEmkzbfSYi3rwl93VuMUkqRsvKBdgVGB0RUzNv\nt5Z5e5KkzFpZLl8DpqSUFgGjgTc1bp8bEb9NKT0C/ALYC7gTGAPsC0REzEwpvQO4DBgK7AjMjoi7\nezeeUtobWAB0AKuAWRHxXAu/HknSILXynMts4H+BFcCdEXEwcApwZWP5JOA84P3AXOCKiHgvcGBK\naQzwduALEXEocCnw6U22/3XgtIiYBtwKnN3Cr0WStBlaOXLpaPy/N3BwSunYxvVxjf9XRcTTACml\n9RHxcOP2NcAbgd8DF6SU/kR95LPpOZu3AVemlKB+XmdJS74KSdqKjR8/is7O0WXHeI1Wlkuvh4Bv\nRcQNKaVdgeMatw907qSD+iGvEyLi4ZTS3wNdm6zzMPDJiHg6pfQB/nzYTZIqo7t7HStXrm3pY2xJ\nebX6rcg14J+AY1JKi4GbqJdC7zIGuPwt4MaU0o8aOXfeZPls4LqU0s+AfwQebBbGucUkqRgdtVp1\n3ny13eg31Q47eVHZMSQpi3Wrl3PxyfsxefKUlj5OZ+fojuZrvZofopQkZWe5SJKys1wkSdlZLpKk\n7CpVLs4tJknFqFS5SJKKYblIkrKzXCRJ2VkukqTsLBdJUnaVKhfnFpOkYlSqXCRJxbBcJEnZWS6S\npOwsF0lSdpaLJCm7SpWLc4tJUjEqVS6SpGJYLpKk7CwXSVJ2loskKTvLRZKUXaXKxbnFJKkYw8oO\nUKTaKy+zbvXysmNIUhYb1qwoO0K/KlUuneNGcfHJ+5Udo6nx40fR3b2u7BhNtUPOdsgI5sytSjkn\nTpyUKU1elSqXYcOGMXnylLJjNNXZOZqVK9eWHaOpdsjZDhnBnLmZs3yVOuciSSqG5SJJyq5S5bJs\n2bKyI0hSJVSqXCRJxbBcJEnZWS6SpOwsF0lSdpaLJCm7SpVLV1dX2REkqRIqVS6SpGJYLpKk7CwX\nSVJ2loskKTvLRZKUXaXKxbnFJKkYlSoXSVIxLBdJUnaWiyQpO8tFkpSd5SJJyq5S5eLcYpJUjEqV\niySpGJaLJCk7y0WSlJ3lIknKznKRJGXXUavVys4gSdrGOHKRJGVnuUiSsrNcJEnZWS6SpOwsF0lS\ndpaLJCm7YWUHyC2lNAT4F+CdwAvASRHxaJ/l04ELgB5gUURcU0pQmmdtrDMC+DEwKyJia8uYUjoO\n+Dz1/fkgcFpEFP7+9kHk/BjwRaAGfDsiFhadcTA5+6x3NbAqIs4pOGLv4zfbn6cDnwFWNm46JSKW\nbGUZ3wNcBnQAy4GZEfFikRmb5Uwp7QR8p8/qfwN8MSKu3ppyNpYfBZxL/WdoUUR8baDtbYsjlyOB\n4RHxPuBL1L+5AEgpvQGYDxwGHAScnFKaUErKun6zAqSUpgJ3AXtQf0LLMND+3B64CPhgRBwIjAGO\nKCXlwDmHAhcDhwD7A6ellMaXkrLJcw6QUjoFeAflPefQPOe7gE9GxLTGv0KLpWGg57wDuBr4VES8\nH7iT+s9RGfrNGRHP9u5D6i/c9wFfLydm0+e897XzAOALKaUxA21sWyyXA4DbACLi18DUPsveBjwS\nEWsi4iXg58AHio+40UBZAYZTf8ILH7H0MVDG54H9I+L5xvVhwJ+KjbdRvzkj4mXgrRGxFugEhgKF\n/wbbMOBznlJ6H7AvcBX137jL0ux7893AuSmln6WUvlR0uIaBMu4FrALOSCn9FBhbxsi/odm+7C3D\nhcDsMkb+Dc1yvgSMBban/r05YM5tsVx2AJ7rc/3lxnCvd9maPsvWUv9tuywDZSUifhkRTxcf61X6\nzRgRtYhYCZBSmgOMjIg7SsgIzfflKymlvwPuBxYDGwrO16vfnCmlnYELgc9RbrFAk/0J3ACcAhwM\nHJhSOrzIcA0DZdwReB9wOXAocEhKaVrB+Xo125cA04HfRsTS4mK9RrOcl1EfWf0W+PeI6Lvua2yL\n5fIcMLrP9SER8Urj8ppNlo0GVhcV7HUMlHVrMWDGlNKQlNI86oecPlZ0uD6a7suI+D6wK/BGYGaB\n2foaKOfHqb8o/oj6+aHjU0pbY06ABRHR3TgCcAuwT6Hp6gbKuIr6UYqIiB7qv5G/ZsRQkMH8nJ9A\n/TBemfrNmVLanfovPZOALmCnlNLHB9rYtlguvwA+CpBS2g/4TZ9lDwNTUkrjUkrDqR8Su7v4iBsN\nlHVr0SzjVdRfrI/qc3isDP3mTCntkFL6z5TS8MYhh/XAy+XE7D9nRFweEVMbx98vAa6PiG+WE3PA\n/TkGeDClNLJxOOdg4N6tKSPwGDAqpTS5cf391H/jLsNgfs6nRkSZr0UwcM7tqP/MvNAonBXUD5H1\na5ubuLLxzd77jgeAT1M/PjwqIr6eUjqC+qGHIcA3IuLKcpI2z9pnvcWU8G6cZhmpv6DcS/1NB70W\nRMQPCg3JoJ73z1J/d9NLwAPAnJLe1TbY5/xEIEXEuUVnbDx+s/15HHA69XcV3RER/7AVZuwt6Q7g\nFxFxetEZB5mzE7g9It5VRr5eg8h5OnA89XOtjwCfbYwKX9c2Vy6SpPJti4fFJEkls1wkSdlZLpKk\n7CwXSVJ2loskKTvLRZKUneUiScrOcpEkZff/dfiue9SBGo0AAAAASUVORK5CYII=\n", + "text": [ + "" + ] + } + ], + "prompt_number": 74 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "pd.pivot_table(training_data, index=[\"Pclass\"], values=[\"Survived\"]).plot(kind=\"barh\")\n", + "plt.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAD9CAYAAAC7iRw+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAEftJREFUeJzt3X2QXXV9x/H3JnGVsCEQu0HANYuB/HSstmhKBUGKykzV\nkIKCjDy2gASRQEFQeWw7lIItxEmoRYKNPIzRIWqRgliFiWCBKlCK6Mh3w0MAUyGR3Ql5AOLC9o+7\niVvM3nt3s/ecs/m9XzM77M3ec87nHu5+9tzfPfd32gYGBpAk5WNC2QEkScWy+CUpMxa/JGXG4pek\nzFj8kpQZi1+SMjOp7ACb9fe/MtDXt7HsGKO2yy6TMX85xnN2MH/Zxnv+zs4pbSNdpjJH/HvtNbPs\nCNtk0qSJZUfYJuM5/3jODuYv23jPPxqVKX5JUjEsfknKjMUvSZmx+CUpMxa/JGWmMsW/cuXKsiNI\nUhYqcx6/JAFs2rSJZ555akzX2dU1g/b29jFd53hm8UuqlGeeeYoz/+kWJk+dPibr27h2NQvPncvM\nmXvXvd+NN17Hgw/+lP7+fiZMmMBnPvPXpPS2UW1z0aIrOeqoY9h11zeNavkFC77IwQd/iH32ec+o\nlm/E4pdUOZOnTqdjlz0K296TTz7BvffezdVXLwFgxYoeLr30b7nuuqWjWt8ZZ3x2m/K0tY34w7gj\nUpkxfkkqS0dHB8899xy33vpd1qxZzd57z+Laa6/n9NNP4emna8NON9/8LZYsWcyzz/6a448/ivnz\n57F06Q0ce+yRW9azYMEXufvuHzF//jyefnolJ598PM8++2sAli+/g4ULr2TDhvVceOHnOOOMUznj\njFN54onHtqz/xBOP4eyz57NiRU9LH6/FLyl7nZ3TufzyK3nkkYc59dQTOeaYI7jnnrtfc+T9u+97\ne3v50pe+zNFHH8/MmXvx8MMPsWnTJh566EHe974Dt9xvzpy5fP/7twFw++23Mnfu4Vx//RJmz96X\nRYu+wrnnns8VV1xOX18fN930DRYvvp4rrlhIW1tbS4/6KzPU093dzf33P1J2DEkZWrXqV+y4Ywfn\nnXcxAI8++kvOOWc+b3xj55b7DL0++W677c6kSbX6PPTQw7n99lt5/vnnOeCAg5g4cfPcP20ccsif\nc9ppn2LOnMPYsGEDe+75Vp544jEeeugB7rzzhwCsW/cCq1Y9w4wZe25Z5zvf+Ue08nroHvFLyt5j\nj61gwYJ/pL+/H4Curi46OnZi55135je/WQNAT8+jW+4/YcLvqnP27H3p6Qluu+0WDj30sP+33h13\n7CClt7Fo0ZV89KNzAZgxY08+8Ymjueqqa7j44kv48Ifn8OY3v4Unn3yCl19+iYGBAX75y1/kccQv\nSZttXLu60HUddNDBPPXUk5x88vHssMMODAwMcPrpZzJx4iQWLPgi06e/ic7Ozi1l/NpSPvjgD/LA\nA/ez++6//4b03LmHc845Z3DBBX8DwAknnMhll13CLbf8Gxs2bOCkk+ax8847c8IJJ/LpT5/MTjvt\nxMSJra3mtla+nBiJ7u7ugfE81NPZOYU1a9aVHWPUxnP+8ZwdzP9aRZ/Hvx3s/xG/NKjMEX9/fz+P\nP76i7Bij1tfXQW/v+rJjjNpY5/cDMxqt9vb2hufca9tUpvjX9K3nvMX/VXYMjYFmPzAjqRyVKf79\nj/qHQj+wIUm58qweScqMxS9JmbH4JSkzFr8kZcbil6TMVKb471t2UdkRJCkLlSl+SVIxLH5JyozF\nL0mZsfglKTMWvyRlpjLFv9+Rl5QdQZKyUJnilyQVo2Wzc6aUJgLXArOAAeDUiPhFq7YnSWpOK4/4\n5wCvRsQBwIXApS3cliSpSS0r/oj4LjBv8GY30NeqbUmSmtfSC7FExCsppeuAw4EjWrktSVJzCrnY\nekppV+AnwNsj4sWt3ecNU944cMgpS1qeRa23vm8V13zhQ8yaNavsKFIOqnOx9ZTSccCbI+Iy4EXg\n1cEvZaC3dz1r1qwrZFudnVMK21YrmL9c20P+kWrlUM+3gOtSSncBrwPOjIiXW7g9SVITWlb8g0M6\nR7Vq/ZKk0fEDXJKUGYtfkjJTmeJ3rh5JKkZlil+SVAyLX5IyY/FLUmYsfknKjMUvSZmpTPHft+yi\nsiNIUhYqU/ySpGJY/JKUGYtfkjJj8UtSZlp6Ba6RGHj1Fdb3rSo7hsbAxrWry44gqY7KFP8jD/2U\n3t71ZccYtWnTOsw/RFfXjDFbl6SxVZninzVr1ri/Co75JY0HjvFLUmYsfknKjMUvSZmx+CUpM5Up\n/u7u7rIjSFIWKlP8kqRiWPySlBmLX5IyY/FLUmYsfknKTGWKf+XKlWVHkKQsVKb4JUnFsPglKTMW\nvyRlxuKXpMxY/JKUmcoUv3P1SFIxKlP8kqRiWPySlBmLX5IyY/FLUmYsfknKTGWK37l6JKkYlSl+\nSVIxLH5JyozFL0mZsfglKTMWvyRlpjLF71w9klSMyhS/JKkYFr8kZcbil6TMWPySlBmLX5IyU5ni\nd64eSSrGpLIDbNbT00Nv7/qyY4xaX1+H+UsynrNDtfJ3dc2gvb297BhqscoU/3HnLWXy1Ollx5Cy\ntXHtahaeO5eZM/cuO4parDLFP3nqdDp22aPsGJK03avMGL8kqRgWvyRlpuFQT0ppL+C9wFLgK8C7\ngbMi4sdjGeS+ZRdxyClLxnKVkqStaOaI/2vAJmAuMAs4G7iilaEkSa3TTPG/ISJuAuYASyPibir0\nprAkaWSaKf7+lNIR1Ir/1pTSYcArrY0lSWqVZop/HvAR4DMR8b/AJ4CTW5pKktQyDYs/In4GXBgR\n304pvR+4F3i85ckkSS3RsPhTSl8BLkgpvQP4OrAPcMNYB9nvyEvGepWSpK1oZqhnX+B04EhgSUSc\nBMxoaSpJUss0U/wTBr/+AvheSmlHYHJLU0mSWqaZ4r8B+DXwVET8BLgfWNzSVJKklml4Pn5ELEgp\nLYyIzadwHhgRzzdaLqX0OmAJtWGh1wN/HxH/vk1pJUnbrJkpGw4Ezh0c4pkATEwpvSUiuhssegyw\nJiKOSyntAvwPYPFLUsmaGer5KnAztT8S/wysAL7UxHLLgIuHbKe/3p3vW3ZRE6uUJG2rZor/xYhY\nAtwF9AGfAo5otFBEbIiI9SmlKdT+CFywTUklSWOimTl3XkwpTQOC2iydy4HOZlaeUuoCvgN8OSK+\nOeqUkgoxbVoHnZ1TRrzcaJapkvGef6SaKf4FwE3A4cADwLHAfzdaKKW0K/AD4LSIWL4tISUVo7d3\nPWvWrBvRMp2dU0a8TJVsD/lHqpkpG5YBh0TEOmpz8R9DrfwbOR+YClycUlo++PWGESeUJI2pYY/4\nU0pfe83toTcHgBPrrTgizgTO3JZwkqSxV2+o5y5qBd82+N+Wcq4eSSrGsEM9EXFdRFwPfBuYMvj9\nncBe1M7SkSSNQ82czrkU2G3w+xcGl7mxZYkkSS3VzFk9MyLiUICIeIHaFM0PtzaWJKlVmjniH0gp\nvWvzjZTS26ldfF2SNA41c8T/WeAHKaVVg7c7ae50TklSBdU7nXMP4CpgFvA94GpqR/oRES+NdZD7\nll3EIacsGevVSpJeo95Qz9eAR4FzB+93WkQ83IrSlyQVp95Qz+4RcT5ASukOwDd0JWk7UO+If8sb\nuBHxW+Dl1seRJLVaveJvKyyFJKkw9YZ63pFSenLI7d2H3B6IiLe2MJckqUXqFf+swlLgXD2SVJRh\niz8iVhaYQ5JUkGY+wFWIjWtXlx1Bypq/g/moTPHfeNnR9PauLzvGqE2b1mH+kozn7FCt/F1dM8qO\noAJUpvhnzZo17i9/Zv5yjOfsMP7za/xpZpI2SdJ2pDLF393dXXYEScpCZYpfklQMi1+SMmPxS1Jm\nLH5JyozFL0mZqUzxr1y5suwIkpSFyhS/JKkYFr8kZcbil6TMWPySlBmLX5IyU5nid64eSSpGZYpf\nklQMi1+SMmPxS1JmLH5JyozFL0mZqUzxO1ePJBWjMsUvSSqGxS9JmbH4JSkzFr8kZcbil6TMVKb4\nnatHkopRmeKXJBXD4pekzFj8kpQZi1+SMmPxS1JmKlP8ztUjScWoTPFLkoph8UtSZiaVHWCznp4e\nenvXlx1j1Pr6OsxfkvGcHcxfttHm7+qaQXt7ewsStV5liv+485Yyeer0smNIUkMb165m4blzmTlz\n77KjjEplin/y1Ol07LJH2TEkabtXmTH++5ZdVHYEScpCZYpfklQMi1+SMmPxS1JmLH5JyozFL0mZ\nqUzx73fkJWVHkKQsVKb4JUnFsPglKTMWvyRlxuKXpMxY/JKUmcoUv3P1SFIxCin+lNKfppSWF7Et\nSVJ9LZ+WOaX0OeBYYPxeqUGStiNFHPE/BnwMaCtgW5KkBlpe/BHxHaC/1duRJDWnMlfgkqTxZNq0\nDjo7p5QdY1QqU/zO1SNpPOntXc+aNevKjjGqPz5Fns45UOC2JEnDKOSIPyJWAvsXsS1JUn2V+QCX\nJKkYFr8kZcbil6TMVKb4natHkopRmeKXJBXD4pekzFj8kpQZi1+SMmPxS1JmKlP8ztUjScWoTPFL\nkoph8UtSZix+ScpMZebj37h2ddkRJKkp472v2gYGqjFNfk9Pz0Bv7/i9Hvu0aR2YvxzjOTuYv2yj\nzd/VNYP29vYWJBqZzs4pI76eeWWKv7u7e+D++x8pO8aodXZOqcTVeEZrPOcfz9nB/GXbDvKPuPgd\n45ekzFj8kpQZi1+SMmPxS1JmLH5Jykxlin/lypVlR5CkLFSm+CVJxbD4JSkzFr8kZcbil6TMWPyS\nlJnKFH93d3fZESQpC5UpfklSMSx+ScqMxS9JmbH4JSkzFr8kZaYyV+CSJBXDI35JyozFL0mZsfgl\nKTMWvyRlxuKXpMxY/JKUmUlFbiylNAH4F+BdwMvAyRHx+JCfHwpcBPQDSyLiq0Xma0ajxzB4n8nA\nD4ETIyKKT7l1Tez/TwJnUtv/jwCnRURlzvdtIv/Hgc8DA8DXI2JRKUGH0cxzZ/B+i4HnI+K8giPW\n1cT+Pws4CVgz+E/zIqKn8KBb0UT2PwGuBNqAVcDxEbGpjKxbUy9/SmlX4JtD7v7HwOcjYvFw6yv6\niP8woD0i9ge+QG1HA5BSeh2wADgEOAg4JaU0veB8zRj2MQCklGYDdwN7UiugKqm3/3cALgH+LCIO\nAKYCc0pJObx6+ScClwEfBPYDTkspTSsl5fDqPncAUkrzgD+kes8daJz/3cBxEXHw4FclSn9QvedO\nG7AY+MuIOBC4k9rvb5UMmz8intu8z4HzgQeBa+utrOjifx/wfYCI+Akwe8jP3g48FhFrI+K3wH8C\n7y84XzPqPQaAdmr/kypzpD9EvewvAftFxEuDtycBLxYbr6Fh80fEK8DbImId0AlMBCpzxDao7nMn\npbQ/sC9wDbUjz6pp9Nx/D3B+SunHKaUvFB2ugXrZZwHPA2enlH4E7FylV+qDGu37zX/AFgGfbvRK\nveji3wl4YcjtVwZfwmz+2dohP1tH7aizauo9BiLi3oj4VfGxmjJs9ogYiIg1ACml+cCOEXFHCRnr\nabTvX00pfQx4CFgObCw4XyPD5k8p7QZcDJxONUsfGux/4BvAPOADwAEppY8WGa6Betn/ANgfuAr4\nEPDBlNLBBedrpNG+BzgU+HlErGi0sqKL/wVgytDtR8Srg9+vfc3PpgB9RQUbgXqPoerqZk8pTUgp\nXUFtuOTjRYdrQsN9HxHfAfYAXg8cX2C2ZtTLfwS1Avoetfcpjk4pjaf8AAsjonfwFfttwD6Fpquv\nXvbnqY02RET0Uzuy/r0j6pI10zvHUBuyaqjo4r8H+AhASum9wM+G/OxRYO+U0i4ppXZqwzz3FZyv\nGfUeQ9U1yn4NtcI8fMiQT5UMmz+ltFNK6a6UUvvgy9wNwCvlxBzWsPkj4qqImD04Tns5sDQibign\n5rDq7f+pwCMppR0Hhxw+ADxQSsqtq/fcfwLoSCnNHLx9IPDzYuM11EzvzI6Ipjqz0EnaBp8Qm9+Z\nBvgrauOCHRFxbUppDrWXuxOAf42IqwsL16RGj2HI/ZZTobMaoH52ar+kD1B7Y3qzhRFxc6Eh62ji\n+fMpameV/BZ4GJhfsbOSmn3unACkiDi/+JTDa2L/fxI4i9pZJ3dExN+Vk/T3NZF98x/cNuCeiDir\nnKRb10T+TuA/IuLdzazP2TklKTN+gEuSMmPxS1JmLH5JyozFL0mZsfglKTMWvyRlxuKXpMxY/JKU\nmf8DFiCOaUppPFUAAAAASUVORK5CYII=\n", + "text": [ + "" + ] + } + ], + "prompt_number": 75 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "pd.pivot_table(training_data, index=[\"SibSp\"], values=[\"Survived\"]).plot(kind=\"barh\")\n", + "plt.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAD9CAYAAAC7iRw+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nT4Geq5rFQAAAAABJRU5ErkJggg==\n", + "text": [ + "" + ] + } + ], + "prompt_number": 76 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "pd.pivot_table(training_data, index=[\"Parch\"], values=[\"Survived\"]).plot(kind=\"barh\")\n", + "plt.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAD9CAYAAAC7iRw+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n", + "text": [ + "" + ] + } + ], + "prompt_number": 77 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "pd.pivot_table(training_data, index=[\"Embarked\"], values=[\"Survived\"]).plot(kind=\"barh\")\n", + "plt.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAD9CAYAAAC1DKAUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", + "text": [ + "" + ] + } + ], + "prompt_number": 78 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "ticket_counter = Counter(list(training_data.Ticket))" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 79 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "list(ticket_counter.keys())[0:2]" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 80, + "text": [ + "['W./C. 14263', '233639']" + ] + } + ], + "prompt_number": 80 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "ticket_counter['330980']" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 81, + "text": [ + "1" + ] + } + ], + "prompt_number": 81 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "training_data[\"num_ident_tickets\"] = training_data.Ticket.map(ticket_counter)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 82 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "training_data[training_data.num_ident_tickets > 1].head()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "html": [ + "
\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarkednum_ident_tickets
3 4 1 1 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35 1 0 113803 53.1000 C123 S 2
7 8 0 3 Palsson, Master. Gosta Leonard male 2 3 1 349909 21.0750 NaN S 4
8 9 1 3 Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) female 27 0 2 347742 11.1333 NaN S 3
9 10 1 2 Nasser, Mrs. Nicholas (Adele Achem) female 14 1 0 237736 30.0708 NaN C 2
10 11 1 3 Sandstrom, Miss. Marguerite Rut female 4 1 1 PP 9549 16.7000 G6 S 2
\n", + "
" + ], + "metadata": {}, + "output_type": "pyout", + "prompt_number": 83, + "text": [ + " PassengerId Survived Pclass \\\n", + "3 4 1 1 \n", + "7 8 0 3 \n", + "8 9 1 3 \n", + "9 10 1 2 \n", + "10 11 1 3 \n", + "\n", + " Name Sex Age SibSp \\\n", + "3 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35 1 \n", + "7 Palsson, Master. Gosta Leonard male 2 3 \n", + "8 Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) female 27 0 \n", + "9 Nasser, Mrs. Nicholas (Adele Achem) female 14 1 \n", + "10 Sandstrom, Miss. Marguerite Rut female 4 1 \n", + "\n", + " Parch Ticket Fare Cabin Embarked num_ident_tickets \n", + "3 0 113803 53.1000 C123 S 2 \n", + "7 1 349909 21.0750 NaN S 4 \n", + "8 2 347742 11.1333 NaN S 3 \n", + "9 0 237736 30.0708 NaN C 2 \n", + "10 1 PP 9549 16.7000 G6 S 2 " + ] + } + ], + "prompt_number": 83 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "pd.pivot_table(training_data, index=[\"num_ident_tickets\", \"Sex\"], values=[\"Survived\"]).plot(kind=\"barh\")\n", + "plt.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAakAAAD9CAYAAAAGRIgOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\np5gCAAAAAElFTkSuQmCC\n", + "text": [ + "" + ] + } + ], + "prompt_number": 84 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "people_with_cabins = training_data[training_data[\"Cabin\"] != np.nan]" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 85 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "pd.pivot_table(people_with_cabins, index=[\"Sex\"], values=[\"Survived\"]).plot(kind=\"barh\")\n", + "plt.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAZcAAAD9CAYAAABwfjqFAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", + "text": [ + "" + ] + } + ], + "prompt_number": 86 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "pd.pivot_table(training_data, index=[\"Pclass\", \"Embarked\", \"Sex\"], values=[\"Survived\"]).plot(kind=\"barh\")\n", + "plt.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAbYAAAD9CAYAAADQ4VJrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nugAAAABJRU5ErkJggg==\n", + "text": [ + "" + ] + } + ], + "prompt_number": 87 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "plt.rc('figure', figsize=(8,16))\n", + "pd.pivot_table(training_data, index=[\"Pclass\", \"Embarked\", \"Sex\", \"num_ident_tickets\"], values=[\"Survived\"]).plot(kind=\"barh\")\n", + "plt.axvline(x=.5, color=\"red\")\n", + "plt.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAjAAAAObCAYAAABNXbv2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nVhwXMGZmZlYcFzBmZmZWnN/k7MIQRDCFKQAAAABJRU5ErkJggg==\n", + "text": [ + "" + ] + } + ], + "prompt_number": 88 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "men = training_data[training_data[\"Sex\"] == \"male\"]" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 89 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "plt.rc('figure', figsize=(8,10))\n", + "pd.pivot_table(men, index=[\"Age\"], values=[\"Survived\"]).plot(kind=\"barh\")\n", + "plt.axvline(x=.5, color=\"red\")\n", + "plt.show()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "display_data", + "png": "iVBORw0KGgoAAAANSUhEUgAAAfsAAAJNCAYAAAA28NwnAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n", + "text": [ + "" + ] + } + ], + "prompt_number": 90 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "test = pd.read_csv(\"test.csv\")\n", + "test[\"num_ident_tickets\"] = test.Ticket.map(ticket_counter)\n", + "test[\"Survived\"] = 0\n", + "test.loc[(test[\"Sex\"] == \"female\") & ((test[\"Pclass\"] == 1) | (test[\"Pclass\"] == 2)), \"Survived\"] = 1\n", + "test.loc[(test[\"Sex\"] == \"female\") & (test[\"Pclass\"] == 3) & (test[\"Embarked\"] == \"Q\"), \"Survived\"] = 1\n", + "test.loc[(test[\"Sex\"] == \"male\") & ((test[\"Age\"] < 12) | (test[\"Age\"] > 79)),\"Survived\"] = 1\n", + "\n", + "test = test[[\"PassengerId\", \"Survived\"]]\n", + "test.to_csv(\"first_try.csv\", index=False)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 91 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "train = training_data.copy()\n", + "\n", + "female = (train.Sex == \"female\")\n", + "male = (train.Sex == \"male\")\n", + "c = (train.Embarked == \"C\")\n", + "q = (train.Embarked == \"Q\")\n", + "s = (train.Embarked == \"S\")\n", + "c1 = (train.Pclass == 1)\n", + "c2 = (train.Pclass == 2)\n", + "c3 = (train.Pclass == 3)\n", + "live = (train.Survived == 1)\n", + "die = (train.Survived == 0)\n" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 92 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "\"\"\"Calculate chance of surviving based on criteria\"\"\"\n", + "survival_probability = train.Survived.mean()\n", + "total_survivors = train.Survived.sum()\n", + "total_passengers = len(train.index.unique())\n", + "fcc1l = len(train[female & c & c1 & live].index.unique()) / total_survivors\n", + "fcc2l = len(train[female & c & c2 & live].index.unique()) / total_survivors\n", + "fcc3l = len(train[female & c & c3 & live].index.unique()) / total_survivors\n", + "mcc1l = len(train[male & c & c1 & live].index.unique()) / total_survivors\n", + "mcc2l = len(train[male & c & c2 & live].index.unique()) / total_survivors\n", + "mcc3l = len(train[male & c & c3 & live].index.unique()) / total_survivors\n", + "fqc1l = len(train[female & q & c1 & live].index.unique()) / total_survivors\n", + "fqc2l = len(train[female & q & c2 & live].index.unique()) / total_survivors\n", + "fqc3l = len(train[female & q & c3 & live].index.unique()) / total_survivors\n", + "mqc1l = len(train[male & q & c1 & live].index.unique()) / total_survivors\n", + "mqc2l = len(train[male & q & c2 & live].index.unique()) / total_survivors\n", + "mqc3l = len(train[male & q & c3 & live].index.unique()) / total_survivors\n", + "fsc1l = len(train[female & s & c1 & live].index.unique()) / total_survivors\n", + "fsc2l = len(train[female & s & c2 & live].index.unique()) / total_survivors\n", + "fsc3l = len(train[female & s & c3 & live].index.unique()) / total_survivors\n", + "msc1l = len(train[male & s & c1 & live].index.unique()) / total_survivors\n", + "msc2l = len(train[male & s & c2 & live].index.unique()) / total_survivors\n", + "msc3l = len(train[male & s & c3 & live].index.unique()) / total_survivors" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 93 + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "\"\"\"Caclulate chance of not surviving based on criteria\"\"\"\n", + "fcc1d = len(train[female & c & c1 & die].index.unique()) / (total_passengers - total_survivors)\n", + "fcc2d = len(train[female & c & c2 & die].index.unique()) / (total_passengers - total_survivors)\n", + "fcc3d = len(train[female & c & c3 & die].index.unique()) / (total_passengers - total_survivors)\n", + "mcc1d = len(train[male & c & c1 & die].index.unique()) / (total_passengers - total_survivors)\n", + "mcc2d = len(train[male & c & c2 & die].index.unique()) / (total_passengers - total_survivors)\n", + "mcc3d = len(train[male & c & c3 & die].index.unique()) / (total_passengers - total_survivors)\n", + "fqc1d = len(train[female & q & c1 & die].index.unique()) / (total_passengers - total_survivors)\n", + "fqc2d = len(train[female & q & c2 & die].index.unique()) / (total_passengers - total_survivors)\n", + "fqc3d = len(train[female & q & c3 & die].index.unique()) / (total_passengers - total_survivors)\n", + "mqc1d = len(train[male & q & c1 & die].index.unique()) / (total_passengers - total_survivors)\n", + "mqc2d = len(train[male & q & c2 & die].index.unique()) / (total_passengers - total_survivors)\n", + "mqc3d = len(train[male & q & c3 & die].index.unique()) / (total_passengers - total_survivors)\n", + "fsc1d = len(train[female & s & c1 & die].index.unique()) / (total_passengers - total_survivors)\n", + "fsc2d = len(train[female & s & c2 & die].index.unique()) / (total_passengers - total_survivors)\n", + "fsc3d = len(train[female & s & c3 & die].index.unique()) / (total_passengers - total_survivors)\n", + "msc1d = len(train[male & s & c1 & die].index.unique()) / (total_passengers - total_survivors)\n", + "msc2d = len(train[male & s & c2 & die].index.unique()) / (total_passengers - total_survivors)\n", + "msc3d = len(train[male & s & c3 & die].index.unique()) / (total_passengers - total_survivors)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 94 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "\"\"\"Calculate proportion of the population represented by each passenger\"\"\"\n", + "fcc1prob = len(train[female & c & c1].index.unique()) / total_passengers\n", + "fcc2prob = len(train[female & c & c2].index.unique()) / total_passengers\n", + "fcc3prob = len(train[female & c & c3].index.unique()) / total_passengers\n", + "mcc1prob = len(train[male & c & c1].index.unique()) / total_passengers\n", + "mcc2prob = len(train[male & c & c2].index.unique()) / total_passengers\n", + "mcc3prob = len(train[male & c & c3].index.unique()) / total_passengers\n", + "fqc1prob = len(train[female & q & c1].index.unique()) / total_passengers\n", + "fqc2prob = len(train[female & q & c2].index.unique()) / total_passengers\n", + "fqc3prob = len(train[female & q & c3].index.unique()) / total_passengers\n", + "mqc1prob = len(train[male & q & c1].index.unique()) / total_passengers\n", + "mqc2prob = len(train[male & q & c2].index.unique()) / total_passengers\n", + "mqc3prob = len(train[male & q & c3].index.unique()) / total_passengers\n", + "fsc1prob = len(train[female & s & c1].index.unique()) / total_passengers\n", + "fsc2prob = len(train[female & s & c2].index.unique()) / total_passengers\n", + "fsc3prob = len(train[female & s & c3].index.unique()) / total_passengers\n", + "msc1prob = len(train[male & s & c1].index.unique()) / total_passengers\n", + "msc2prob = len(train[male & s & c2].index.unique()) / total_passengers\n", + "msc3prob = len(train[male & s & c3].index.unique()) / total_passengers" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 95 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "# train.survival_prob *= survival_probability\n", + "\"\"\"Aggregate survival probability of each passenger\"\"\"\n", + "train[\"survival_prob\"] = 1\n", + "train.loc[female & c & c1, \"survival_prob\"] *= fcc1l\n", + "train.loc[female & c & c2, \"survival_prob\"] *= fcc2l\n", + "train.loc[female & c & c3, \"survival_prob\"] *= fcc3l\n", + "train.loc[male & c & c1, \"survival_prob\"] *= mcc1l\n", + "train.loc[male & c & c2, \"survival_prob\"] *= mcc2l\n", + "train.loc[male & c & c3, \"survival_prob\"] *= mcc3l\n", + "\n", + "train.loc[female & q & c1, \"survival_prob\"] *= fqc1l\n", + "train.loc[female & q & c2, \"survival_prob\"] *= fqc2l\n", + "train.loc[female & q & c3, \"survival_prob\"] *= fqc3l\n", + "train.loc[male & q & c1, \"survival_prob\"] *= mqc1l\n", + "train.loc[male & q & c2, \"survival_prob\"] *= mqc2l\n", + "train.loc[male & q & c3, \"survival_prob\"] *= mqc3l\n", + "\n", + "train.loc[female & s & c1, \"survival_prob\"] *= fsc1l\n", + "train.loc[female & s & c2, \"survival_prob\"] *= fsc2l\n", + "train.loc[female & s & c3, \"survival_prob\"] *= fsc3l\n", + "train.loc[male & s & c1, \"survival_prob\"] *= msc1l\n", + "train.loc[male & s & c2,\"survival_prob\"] *= msc2l\n", + "train.loc[male & s & c3, \"survival_prob\"] *= msc3l" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 96 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "\"\"\"Aggregate death probability of each passenger\"\"\"\n", + "train[\"death_prob\"] = 1\n", + "train.loc[female & c & c1, \"death_prob\"] *= fcc1d\n", + "train.loc[female & c & c2, \"death_prob\"] *= fcc2d\n", + "train.loc[female & c & c3, \"death_prob\"] *= fcc3d\n", + "train.loc[male & c & c1, \"death_prob\"] *= mcc1d\n", + "train.loc[male & c & c2, \"death_prob\"] *= mcc2d\n", + "train.loc[male & c & c3, \"death_prob\"] *= mcc3d\n", + "\n", + "train.loc[female & q & c1, \"death_prob\"] *= fqc1d\n", + "train.loc[female & q & c2, \"death_prob\"] *= fqc2d\n", + "train.loc[female & q & c3, \"death_prob\"] *= fqc3d\n", + "train.loc[male & q & c1, \"death_prob\"] *= mqc1d\n", + "train.loc[male & q & c2, \"death_prob\"] *= mqc2d\n", + "train.loc[male & q & c3, \"death_prob\"] *= mqc3d\n", + "\n", + "train.loc[female & s & c1, \"death_prob\"] *= fsc1d\n", + "train.loc[female & s & c2, \"death_prob\"] *= fsc2d\n", + "train.loc[female & s & c3, \"death_prob\"] *= fsc3d\n", + "train.loc[male & s & c1, \"death_prob\"] *= msc1d\n", + "train.loc[male & s & c2, \"death_prob\"] *= msc2d\n", + "train.loc[male & s & c3, \"death_prob\"] *= msc3d" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 97 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "train[\"final\"] = (train[\"survival_prob\"] * survival_probability) / ((train[\"survival_prob\"] * survival_probability) + \n", + " (train[\"death_prob\"] * (1 - survival_probability)))" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 98 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "train.final.mean" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 102, + "text": [ + "0.38245530501422759" + ] + } + ], + "prompt_number": 102 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "test2 = pd.read_csv(\"test.csv\")\n", + "test2[\"Survived\"] = 0\n", + "\n", + "female = (test2.Sex == \"female\")\n", + "male = (test2.Sex == \"male\")\n", + "c = (test2.Embarked == \"C\")\n", + "q = (test2.Embarked == \"Q\")\n", + "s = (test2.Embarked == \"S\")\n", + "c1 = (test2.Pclass == 1)\n", + "c2 = (test2.Pclass == 2)\n", + "c3 = (test2.Pclass == 3)\n", + "live = (test2.Survived == 1)\n", + "die = (test2.Survived == 0)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 139 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "test2[\"survival_prob\"] = 1\n", + "test2.loc[female & c & c1, \"survival_prob\"] *= fcc1l\n", + "test2.loc[female & c & c2, \"survival_prob\"] *= fcc2l\n", + "test2.loc[female & c & c3, \"survival_prob\"] *= fcc3l\n", + "test2.loc[male & c & c1, \"survival_prob\"] *= mcc1l\n", + "test2.loc[male & c & c2, \"survival_prob\"] *= mcc2l\n", + "test2.loc[male & c & c3, \"survival_prob\"] *= mcc3l\n", + "\n", + "test2.loc[female & q & c1, \"survival_prob\"] *= fqc1l\n", + "test2.loc[female & q & c2, \"survival_prob\"] *= fqc2l\n", + "test2.loc[female & q & c3, \"survival_prob\"] *= fqc3l\n", + "test2.loc[male & q & c1, \"survival_prob\"] *= mqc1l\n", + "test2.loc[male & q & c2, \"survival_prob\"] *= mqc2l\n", + "test2.loc[male & q & c3, \"survival_prob\"] *= mqc3l\n", + "\n", + "test2.loc[female & s & c1, \"survival_prob\"] *= fsc1l\n", + "test2.loc[female & s & c2, \"survival_prob\"] *= fsc2l\n", + "test2.loc[female & s & c3, \"survival_prob\"] *= fsc3l\n", + "test2.loc[male & s & c1, \"survival_prob\"] *= msc1l\n", + "test2.loc[male & s & c2,\"survival_prob\"] *= msc2l\n", + "test2.loc[male & s & c3, \"survival_prob\"] *= msc3l" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 140 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "test2[\"death_prob\"] = 1\n", + "test2.loc[female & c & c1, \"death_prob\"] *= fcc1d\n", + "test2.loc[female & c & c2, \"death_prob\"] *= fcc2d\n", + "test2.loc[female & c & c3, \"death_prob\"] *= fcc3d\n", + "test2.loc[male & c & c1, \"death_prob\"] *= mcc1d\n", + "test2.loc[male & c & c2, \"death_prob\"] *= mcc2d\n", + "test2.loc[male & c & c3, \"death_prob\"] *= mcc3d\n", + "\n", + "test2.loc[female & q & c1, \"death_prob\"] *= fqc1d\n", + "test2.loc[female & q & c2, \"death_prob\"] *= fqc2d\n", + "test2.loc[female & q & c3, \"death_prob\"] *= fqc3d\n", + "test2.loc[male & q & c1, \"death_prob\"] *= mqc1d\n", + "test2.loc[male & q & c2, \"death_prob\"] *= mqc2d\n", + "test2.loc[male & q & c3, \"death_prob\"] *= mqc3d\n", + "\n", + "test2.loc[female & s & c1, \"death_prob\"] *= fsc1d\n", + "test2.loc[female & s & c2, \"death_prob\"] *= fsc2d\n", + "test2.loc[female & s & c3, \"death_prob\"] *= fsc3d\n", + "test2.loc[male & s & c1, \"death_prob\"] *= msc1d\n", + "test2.loc[male & s & c2, \"death_prob\"] *= msc2d\n", + "test2.loc[male & s & c3, \"death_prob\"] *= msc3d" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 141 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "test2[\"final\"] = (test2[\"survival_prob\"] * survival_probability) / ((test2[\"survival_prob\"] * survival_probability) + \n", + " (test2[\"death_prob\"] * (1 - survival_probability)))" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 142 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "test2.loc[(test2[\"final\"] > .5), \"Survived\"] = 1\n", + "test2 = test2[[\"PassengerId\", \"Survived\"]]\n", + "test2.to_csv(\"first_try.csv\", index=False)" + ], + "language": "python", + "metadata": {}, + "outputs": [], + "prompt_number": 143 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "test2.Survived.sum()" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 144, + "text": [ + "111" + ] + } + ], + "prompt_number": 144 + }, + { + "cell_type": "code", + "collapsed": false, + "input": [], + "language": "python", + "metadata": {}, + "outputs": [] + } + ], + "metadata": {} + } + ] +} \ No newline at end of file