us-medical-insurance-costs.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# U.S. Medical Insurance Costs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "age,sex,bmi,children,smoker,region,charges\n",
      "19,female,27.9,0,yes,southwest,16884.924\n",
      "18,male,33.77,1,no,southeast,1725.5523\n",
      "28,male,33,3,no,southeast,4449.462\n",
      "33,male,22.705,0,no,northwest,21984.47061\n",
      "32,male,28.88,0,no,northwest,3866.8552\n",
      "31,female,25.74,0,no,southeast,3756.6216\n",
      "46,female,33.44,1,no,southeast,8240.5896\n",
      "37,female,27.74,3,no,northwest,7281.5056\n",
      "37,male,29.83,2,no,northeast,6406.4107\n",
      "60,female,25.84,0,no,northwest,28923.13692\n",
      "25,male,26.22,0,no,northeast,2721.3208\n",
      "62,female,26.29,0,yes,southeast,27808.7251\n",
      "23,male,34.4,0,no,southwest,1826.843\n",
      "56,female,39.82,0,no,southeast,11090.7178\n",
      "27,male,42.13,0,yes,southeast,39611.7577\n",
      "19,male,24.6,1,no,southwest,1837.237\n",
      "52,female,30.78,1,no,northeast,10797.3362\n",
      "23,male,23.845,0,no,northeast,2395.17155\n",
      "56,male,40.3,0,no,southwest,10602.385\n",
      "30,male,35.3,0,yes,southwest,36837.467\n",
      "60,female,36.005,0,no,northeast,13228.84695\n",
      "30,female,32.4,1,no,southwest,4149.736\n",
      "18,male,34.1,0,no,southeast,1137.011\n",
      "34,female,31.92,1,yes,northeast,37701.8768\n",
      "37,male,28.025,2,no,northwest,6203.90175\n",
      "59,female,27.72,3,no,southeast,14001.1338\n",
      "63,female,23.085,0,no,northeast,14451.83515\n",
      "55,female,32.775,2,no,northwest,12268.63225\n",
      "23,male,17.385,1,no,northwest,2775.19215\n",
      "31,male,36.3,2,yes,southwest,38711\n",
      "22,male,35.6,0,yes,southwest,35585.576\n",
      "18,female,26.315,0,no,northeast,2198.18985\n",
      "19,female,28.6,5,no,southwest,4687.797\n",
      "63,male,28.31,0,no,northwest,13770.0979\n",
      "28,male,36.4,1,yes,southwest,51194.55914\n",
      "19,male,20.425,0,no,northwest,1625.43375\n",
      "62,female,32.965,3,no,northwest,15612.19335\n",
      "26,male,20.8,0,no,southwest,2302.3\n",
      "35,male,36.67,1,yes,northeast,39774.2763\n",
      "60,male,39.9,0,yes,southwest,48173.361\n",
      "24,female,26.6,0,no,northeast,3046.062\n",
      "31,female,36.63,2,no,southeast,4949.7587\n",
      "41,male,21.78,1,no,southeast,6272.4772\n",
      "37,female,30.8,2,no,southeast,6313.759\n",
      "38,male,37.05,1,no,northeast,6079.6715\n",
      "55,male,37.3,0,no,southwest,20630.28351\n",
      "18,female,38.665,2,no,northeast,3393.35635\n",
      "28,female,34.77,0,no,northwest,3556.9223\n",
      "60,female,24.53,0,no,southeast,12629.8967\n",
      "36,male,35.2,1,yes,southeast,38709.176\n",
      "18,female,35.625,0,no,northeast,2211.13075\n",
      "21,female,33.63,2,no,northwest,3579.8287\n",
      "48,male,28,1,yes,southwest,23568.272\n",
      "36,male,34.43,0,yes,southeast,37742.5757\n",
      "40,female,28.69,3,no,northwest,8059.6791\n",
      "58,male,36.955,2,yes,northwest,47496.49445\n",
      "58,female,31.825,2,no,northeast,13607.36875\n",
      "18,male,31.68,2,yes,southeast,34303.1672\n",
      "53,female,22.88,1,yes,southeast,23244.7902\n",
      "34,female,37.335,2,no,northwest,5989.52365\n",
      "43,male,27.36,3,no,northeast,8606.2174\n",
      "25,male,33.66,4,no,southeast,4504.6624\n",
      "64,male,24.7,1,no,northwest,30166.61817\n",
      "28,female,25.935,1,no,northwest,4133.64165\n",
      "20,female,22.42,0,yes,northwest,14711.7438\n",
      "19,female,28.9,0,no,southwest,1743.214\n",
      "61,female,39.1,2,no,southwest,14235.072\n",
      "40,male,26.315,1,no,northwest,6389.37785\n",
      "40,female,36.19,0,no,southeast,5920.1041\n",
      "28,male,23.98,3,yes,southeast,17663.1442\n",
      "27,female,24.75,0,yes,southeast,16577.7795\n",
      "31,male,28.5,5,no,northeast,6799.458\n",
      "53,female,28.1,3,no,southwest,11741.726\n",
      "58,male,32.01,1,no,southeast,11946.6259\n",
      "44,male,27.4,2,no,southwest,7726.854\n",
      "57,male,34.01,0,no,northwest,11356.6609\n",
      "29,female,29.59,1,no,southeast,3947.4131\n",
      "21,male,35.53,0,no,southeast,1532.4697\n",
      "22,female,39.805,0,no,northeast,2755.02095\n",
      "41,female,32.965,0,no,northwest,6571.02435\n",
      "31,male,26.885,1,no,northeast,4441.21315\n",
      "45,female,38.285,0,no,northeast,7935.29115\n",
      "22,male,37.62,1,yes,southeast,37165.1638\n",
      "48,female,41.23,4,no,northwest,11033.6617\n",
      "37,female,34.8,2,yes,southwest,39836.519\n",
      "45,male,22.895,2,yes,northwest,21098.55405\n",
      "57,female,31.16,0,yes,northwest,43578.9394\n",
      "56,female,27.2,0,no,southwest,11073.176\n",
      "46,female,27.74,0,no,northwest,8026.6666\n",
      "55,female,26.98,0,no,northwest,11082.5772\n",
      "21,female,39.49,0,no,southeast,2026.9741\n",
      "53,female,24.795,1,no,northwest,10942.13205\n",
      "59,male,29.83,3,yes,northeast,30184.9367\n",
      "35,male,34.77,2,no,northwest,5729.0053\n",
      "64,female,31.3,2,yes,southwest,47291.055\n",
      "28,female,37.62,1,no,southeast,3766.8838\n",
      "54,female,30.8,3,no,southwest,12105.32\n",
      "55,male,38.28,0,no,southeast,10226.2842\n",
      "56,male,19.95,0,yes,northeast,22412.6485\n",
      "38,male,19.3,0,yes,southwest,15820.699\n",
      "41,female,31.6,0,no,southwest,6186.127\n",
      "30,male,25.46,0,no,northeast,3645.0894\n",
      "18,female,30.115,0,no,northeast,21344.8467\n",
      "61,female,29.92,3,yes,southeast,30942.1918\n",
      "34,female,27.5,1,no,southwest,5003.853\n",
      "20,male,28.025,1,yes,northwest,17560.37975\n",
      "19,female,28.4,1,no,southwest,2331.519\n",
      "26,male,30.875,2,no,northwest,3877.30425\n",
      "29,male,27.94,0,no,southeast,2867.1196\n",
      "63,male,35.09,0,yes,southeast,47055.5321\n",
      "54,male,33.63,1,no,northwest,10825.2537\n",
      "55,female,29.7,2,no,southwest,11881.358\n",
      "37,male,30.8,0,no,southwest,4646.759\n",
      "21,female,35.72,0,no,northwest,2404.7338\n",
      "52,male,32.205,3,no,northeast,11488.31695\n",
      "60,male,28.595,0,no,northeast,30259.99556\n",
      "58,male,49.06,0,no,southeast,11381.3254\n",
      "29,female,27.94,1,yes,southeast,19107.7796\n",
      "49,female,27.17,0,no,southeast,8601.3293\n",
      "37,female,23.37,2,no,northwest,6686.4313\n",
      "44,male,37.1,2,no,southwest,7740.337\n",
      "18,male,23.75,0,no,northeast,1705.6245\n",
      "20,female,28.975,0,no,northwest,2257.47525\n",
      "44,male,31.35,1,yes,northeast,39556.4945\n",
      "47,female,33.915,3,no,northwest,10115.00885\n",
      "26,female,28.785,0,no,northeast,3385.39915\n",
      "19,female,28.3,0,yes,southwest,17081.08\n",
      "52,female,37.4,0,no,southwest,9634.538\n",
      "32,female,17.765,2,yes,northwest,32734.1863\n",
      "38,male,34.7,2,no,southwest,6082.405\n",
      "59,female,26.505,0,no,northeast,12815.44495\n",
      "61,female,22.04,0,no,northeast,13616.3586\n",
      "53,female,35.9,2,no,southwest,11163.568\n",
      "19,male,25.555,0,no,northwest,1632.56445\n",
      "20,female,28.785,0,no,northeast,2457.21115\n",
      "22,female,28.05,0,no,southeast,2155.6815\n",
      "19,male,34.1,0,no,southwest,1261.442\n",
      "22,male,25.175,0,no,northwest,2045.68525\n",
      "54,female,31.9,3,no,southeast,27322.73386\n",
      "22,female,36,0,no,southwest,2166.732\n",
      "34,male,22.42,2,no,northeast,27375.90478\n",
      "26,male,32.49,1,no,northeast,3490.5491\n",
      "34,male,25.3,2,yes,southeast,18972.495\n",
      "29,male,29.735,2,no,northwest,18157.876\n",
      "30,male,28.69,3,yes,northwest,20745.9891\n",
      "29,female,38.83,3,no,southeast,5138.2567\n",
      "46,male,30.495,3,yes,northwest,40720.55105\n",
      "51,female,37.73,1,no,southeast,9877.6077\n",
      "53,female,37.43,1,no,northwest,10959.6947\n",
      "19,male,28.4,1,no,southwest,1842.519\n",
      "35,male,24.13,1,no,northwest,5125.2157\n",
      "48,male,29.7,0,no,southeast,7789.635\n",
      "32,female,37.145,3,no,northeast,6334.34355\n",
      "42,female,23.37,0,yes,northeast,19964.7463\n",
      "40,female,25.46,1,no,northeast,7077.1894\n",
      "44,male,39.52,0,no,northwest,6948.7008\n",
      "48,male,24.42,0,yes,southeast,21223.6758\n",
      "18,male,25.175,0,yes,northeast,15518.18025\n",
      "30,male,35.53,0,yes,southeast,36950.2567\n",
      "50,female,27.83,3,no,southeast,19749.38338\n",
      "42,female,26.6,0,yes,northwest,21348.706\n",
      "18,female,36.85,0,yes,southeast,36149.4835\n",
      "54,male,39.6,1,no,southwest,10450.552\n",
      "32,female,29.8,2,no,southwest,5152.134\n",
      "37,male,29.64,0,no,northwest,5028.1466\n",
      "47,male,28.215,4,no,northeast,10407.08585\n",
      "20,female,37,5,no,southwest,4830.63\n",
      "32,female,33.155,3,no,northwest,6128.79745\n",
      "19,female,31.825,1,no,northwest,2719.27975\n",
      "27,male,18.905,3,no,northeast,4827.90495\n",
      "63,male,41.47,0,no,southeast,13405.3903\n",
      "49,male,30.3,0,no,southwest,8116.68\n",
      "18,male,15.96,0,no,northeast,1694.7964\n",
      "35,female,34.8,1,no,southwest,5246.047\n",
      "24,female,33.345,0,no,northwest,2855.43755\n",
      "63,female,37.7,0,yes,southwest,48824.45\n",
      "38,male,27.835,2,no,northwest,6455.86265\n",
      "54,male,29.2,1,no,southwest,10436.096\n",
      "46,female,28.9,2,no,southwest,8823.279\n",
      "41,female,33.155,3,no,northeast,8538.28845\n",
      "58,male,28.595,0,no,northwest,11735.87905\n",
      "18,female,38.28,0,no,southeast,1631.8212\n",
      "22,male,19.95,3,no,northeast,4005.4225\n",
      "44,female,26.41,0,no,northwest,7419.4779\n",
      "44,male,30.69,2,no,southeast,7731.4271\n",
      "36,male,41.895,3,yes,northeast,43753.33705\n",
      "26,female,29.92,2,no,southeast,3981.9768\n",
      "30,female,30.9,3,no,southwest,5325.651\n",
      "41,female,32.2,1,no,southwest,6775.961\n",
      "29,female,32.11,2,no,northwest,4922.9159\n",
      "61,male,31.57,0,no,southeast,12557.6053\n",
      "36,female,26.2,0,no,southwest,4883.866\n",
      "25,male,25.74,0,no,southeast,2137.6536\n",
      "56,female,26.6,1,no,northwest,12044.342\n",
      "18,male,34.43,0,no,southeast,1137.4697\n",
      "19,male,30.59,0,no,northwest,1639.5631\n",
      "39,female,32.8,0,no,southwest,5649.715\n",
      "45,female,28.6,2,no,southeast,8516.829\n",
      "51,female,18.05,0,no,northwest,9644.2525\n",
      "64,female,39.33,0,no,northeast,14901.5167\n",
      "19,female,32.11,0,no,northwest,2130.6759\n",
      "48,female,32.23,1,no,southeast,8871.1517\n",
      "60,female,24.035,0,no,northwest,13012.20865\n",
      "27,female,36.08,0,yes,southeast,37133.8982\n",
      "46,male,22.3,0,no,southwest,7147.105\n",
      "28,female,28.88,1,no,northeast,4337.7352\n",
      "59,male,26.4,0,no,southeast,11743.299\n",
      "35,male,27.74,2,yes,northeast,20984.0936\n",
      "63,female,31.8,0,no,southwest,13880.949\n",
      "40,male,41.23,1,no,northeast,6610.1097\n",
      "20,male,33,1,no,southwest,1980.07\n",
      "40,male,30.875,4,no,northwest,8162.71625\n",
      "24,male,28.5,2,no,northwest,3537.703\n",
      "34,female,26.73,1,no,southeast,5002.7827\n",
      "45,female,30.9,2,no,southwest,8520.026\n",
      "41,female,37.1,2,no,southwest,7371.772\n",
      "53,female,26.6,0,no,northwest,10355.641\n",
      "27,male,23.1,0,no,southeast,2483.736\n",
      "26,female,29.92,1,no,southeast,3392.9768\n",
      "24,female,23.21,0,no,southeast,25081.76784\n",
      "34,female,33.7,1,no,southwest,5012.471\n",
      "53,female,33.25,0,no,northeast,10564.8845\n",
      "32,male,30.8,3,no,southwest,5253.524\n",
      "19,male,34.8,0,yes,southwest,34779.615\n",
      "42,male,24.64,0,yes,southeast,19515.5416\n",
      "55,male,33.88,3,no,southeast,11987.1682\n",
      "28,male,38.06,0,no,southeast,2689.4954\n",
      "58,female,41.91,0,no,southeast,24227.33724\n",
      "41,female,31.635,1,no,northeast,7358.17565\n",
      "47,male,25.46,2,no,northeast,9225.2564\n",
      "42,female,36.195,1,no,northwest,7443.64305\n",
      "59,female,27.83,3,no,southeast,14001.2867\n",
      "19,female,17.8,0,no,southwest,1727.785\n",
      "59,male,27.5,1,no,southwest,12333.828\n",
      "39,male,24.51,2,no,northwest,6710.1919\n",
      "40,female,22.22,2,yes,southeast,19444.2658\n",
      "18,female,26.73,0,no,southeast,1615.7667\n",
      "31,male,38.39,2,no,southeast,4463.2051\n",
      "19,male,29.07,0,yes,northwest,17352.6803\n",
      "44,male,38.06,1,no,southeast,7152.6714\n",
      "23,female,36.67,2,yes,northeast,38511.6283\n",
      "33,female,22.135,1,no,northeast,5354.07465\n",
      "55,female,26.8,1,no,southwest,35160.13457\n",
      "40,male,35.3,3,no,southwest,7196.867\n",
      "63,female,27.74,0,yes,northeast,29523.1656\n",
      "54,male,30.02,0,no,northwest,24476.47851\n",
      "60,female,38.06,0,no,southeast,12648.7034\n",
      "24,male,35.86,0,no,southeast,1986.9334\n",
      "19,male,20.9,1,no,southwest,1832.094\n",
      "29,male,28.975,1,no,northeast,4040.55825\n",
      "18,male,17.29,2,yes,northeast,12829.4551\n",
      "63,female,32.2,2,yes,southwest,47305.305\n",
      "54,male,34.21,2,yes,southeast,44260.7499\n",
      "27,male,30.3,3,no,southwest,4260.744\n",
      "50,male,31.825,0,yes,northeast,41097.16175\n",
      "55,female,25.365,3,no,northeast,13047.33235\n",
      "56,male,33.63,0,yes,northwest,43921.1837\n",
      "38,female,40.15,0,no,southeast,5400.9805\n",
      "51,male,24.415,4,no,northwest,11520.09985\n",
      "19,male,31.92,0,yes,northwest,33750.2918\n",
      "58,female,25.2,0,no,southwest,11837.16\n",
      "20,female,26.84,1,yes,southeast,17085.2676\n",
      "52,male,24.32,3,yes,northeast,24869.8368\n",
      "19,male,36.955,0,yes,northwest,36219.40545\n",
      "53,female,38.06,3,no,southeast,20462.99766\n",
      "46,male,42.35,3,yes,southeast,46151.1245\n",
      "40,male,19.8,1,yes,southeast,17179.522\n",
      "59,female,32.395,3,no,northeast,14590.63205\n",
      "45,male,30.2,1,no,southwest,7441.053\n",
      "49,male,25.84,1,no,northeast,9282.4806\n",
      "18,male,29.37,1,no,southeast,1719.4363\n",
      "50,male,34.2,2,yes,southwest,42856.838\n",
      "41,male,37.05,2,no,northwest,7265.7025\n",
      "50,male,27.455,1,no,northeast,9617.66245\n",
      "25,male,27.55,0,no,northwest,2523.1695\n",
      "47,female,26.6,2,no,northeast,9715.841\n",
      "19,male,20.615,2,no,northwest,2803.69785\n",
      "22,female,24.3,0,no,southwest,2150.469\n",
      "59,male,31.79,2,no,southeast,12928.7911\n",
      "51,female,21.56,1,no,southeast,9855.1314\n",
      "40,female,28.12,1,yes,northeast,22331.5668\n",
      "54,male,40.565,3,yes,northeast,48549.17835\n",
      "30,male,27.645,1,no,northeast,4237.12655\n",
      "55,female,32.395,1,no,northeast,11879.10405\n",
      "52,female,31.2,0,no,southwest,9625.92\n",
      "46,male,26.62,1,no,southeast,7742.1098\n",
      "46,female,48.07,2,no,northeast,9432.9253\n",
      "63,female,26.22,0,no,northwest,14256.1928\n",
      "59,female,36.765,1,yes,northeast,47896.79135\n",
      "52,male,26.4,3,no,southeast,25992.82104\n",
      "28,female,33.4,0,no,southwest,3172.018\n",
      "29,male,29.64,1,no,northeast,20277.80751\n",
      "25,male,45.54,2,yes,southeast,42112.2356\n",
      "22,female,28.82,0,no,southeast,2156.7518\n",
      "25,male,26.8,3,no,southwest,3906.127\n",
      "18,male,22.99,0,no,northeast,1704.5681\n",
      "19,male,27.7,0,yes,southwest,16297.846\n",
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      "40,male,29.355,1,no,northwest,6393.60345\n",
      "31,female,25.8,2,no,southwest,4934.705\n",
      "37,male,24.32,2,no,northwest,6198.7518\n",
      "46,male,40.375,2,no,northwest,8733.22925\n",
      "22,male,32.11,0,no,northwest,2055.3249\n",
      "51,male,32.3,1,no,northeast,9964.06\n",
      "18,female,27.28,3,yes,southeast,18223.4512\n",
      "35,male,17.86,1,no,northwest,5116.5004\n",
      "59,female,34.8,2,no,southwest,36910.60803\n",
      "36,male,33.4,2,yes,southwest,38415.474\n",
      "37,female,25.555,1,yes,northeast,20296.86345\n",
      "59,male,37.1,1,no,southwest,12347.172\n",
      "36,male,30.875,1,no,northwest,5373.36425\n",
      "39,male,34.1,2,no,southeast,23563.01618\n",
      "18,male,21.47,0,no,northeast,1702.4553\n",
      "52,female,33.3,2,no,southwest,10806.839\n",
      "27,female,31.255,1,no,northwest,3956.07145\n",
      "18,male,39.14,0,no,northeast,12890.05765\n",
      "40,male,25.08,0,no,southeast,5415.6612\n",
      "29,male,37.29,2,no,southeast,4058.1161\n",
      "46,female,34.6,1,yes,southwest,41661.602\n",
      "38,female,30.21,3,no,northwest,7537.1639\n",
      "30,female,21.945,1,no,northeast,4718.20355\n",
      "40,male,24.97,2,no,southeast,6593.5083\n",
      "50,male,25.3,0,no,southeast,8442.667\n",
      "20,female,24.42,0,yes,southeast,26125.67477\n",
      "41,male,23.94,1,no,northeast,6858.4796\n",
      "33,female,39.82,1,no,southeast,4795.6568\n",
      "38,male,16.815,2,no,northeast,6640.54485\n",
      "42,male,37.18,2,no,southeast,7162.0122\n",
      "56,male,34.43,0,no,southeast,10594.2257\n",
      "58,male,30.305,0,no,northeast,11938.25595\n",
      "52,male,34.485,3,yes,northwest,60021.39897\n",
      "20,female,21.8,0,yes,southwest,20167.33603\n",
      "54,female,24.605,3,no,northwest,12479.70895\n",
      "58,male,23.3,0,no,southwest,11345.519\n",
      "45,female,27.83,2,no,southeast,8515.7587\n",
      "26,male,31.065,0,no,northwest,2699.56835\n",
      "63,female,21.66,0,no,northeast,14449.8544\n",
      "58,female,28.215,0,no,northwest,12224.35085\n",
      "37,male,22.705,3,no,northeast,6985.50695\n",
      "25,female,42.13,1,no,southeast,3238.4357\n",
      "52,male,41.8,2,yes,southeast,47269.854\n",
      "64,male,36.96,2,yes,southeast,49577.6624\n",
      "22,female,21.28,3,no,northwest,4296.2712\n",
      "28,female,33.11,0,no,southeast,3171.6149\n",
      "18,male,33.33,0,no,southeast,1135.9407\n",
      "28,male,24.3,5,no,southwest,5615.369\n",
      "45,female,25.7,3,no,southwest,9101.798\n",
      "33,male,29.4,4,no,southwest,6059.173\n",
      "18,female,39.82,0,no,southeast,1633.9618\n",
      "32,male,33.63,1,yes,northeast,37607.5277\n",
      "24,male,29.83,0,yes,northeast,18648.4217\n",
      "19,male,19.8,0,no,southwest,1241.565\n",
      "20,male,27.3,0,yes,southwest,16232.847\n",
      "40,female,29.3,4,no,southwest,15828.82173\n",
      "34,female,27.72,0,no,southeast,4415.1588\n",
      "42,female,37.9,0,no,southwest,6474.013\n",
      "51,female,36.385,3,no,northwest,11436.73815\n",
      "54,female,27.645,1,no,northwest,11305.93455\n",
      "55,male,37.715,3,no,northwest,30063.58055\n",
      "52,female,23.18,0,no,northeast,10197.7722\n",
      "32,female,20.52,0,no,northeast,4544.2348\n",
      "28,male,37.1,1,no,southwest,3277.161\n",
      "41,female,28.05,1,no,southeast,6770.1925\n",
      "43,female,29.9,1,no,southwest,7337.748\n",
      "49,female,33.345,2,no,northeast,10370.91255\n",
      "64,male,23.76,0,yes,southeast,26926.5144\n",
      "55,female,30.5,0,no,southwest,10704.47\n",
      "24,male,31.065,0,yes,northeast,34254.05335\n",
      "20,female,33.3,0,no,southwest,1880.487\n",
      "45,male,27.5,3,no,southwest,8615.3\n",
      "26,male,33.915,1,no,northwest,3292.52985\n",
      "25,female,34.485,0,no,northwest,3021.80915\n",
      "43,male,25.52,5,no,southeast,14478.33015\n",
      "35,male,27.61,1,no,southeast,4747.0529\n",
      "26,male,27.06,0,yes,southeast,17043.3414\n",
      "57,male,23.7,0,no,southwest,10959.33\n",
      "22,female,30.4,0,no,northeast,2741.948\n",
      "32,female,29.735,0,no,northwest,4357.04365\n",
      "39,male,29.925,1,yes,northeast,22462.04375\n",
      "25,female,26.79,2,no,northwest,4189.1131\n",
      "48,female,33.33,0,no,southeast,8283.6807\n",
      "47,female,27.645,2,yes,northwest,24535.69855\n",
      "18,female,21.66,0,yes,northeast,14283.4594\n",
      "18,male,30.03,1,no,southeast,1720.3537\n",
      "61,male,36.3,1,yes,southwest,47403.88\n",
      "47,female,24.32,0,no,northeast,8534.6718\n",
      "28,female,17.29,0,no,northeast,3732.6251\n",
      "36,female,25.9,1,no,southwest,5472.449\n",
      "20,male,39.4,2,yes,southwest,38344.566\n",
      "44,male,34.32,1,no,southeast,7147.4728\n",
      "38,female,19.95,2,no,northeast,7133.9025\n",
      "19,male,34.9,0,yes,southwest,34828.654\n",
      "21,male,23.21,0,no,southeast,1515.3449\n",
      "46,male,25.745,3,no,northwest,9301.89355\n",
      "58,male,25.175,0,no,northeast,11931.12525\n",
      "20,male,22,1,no,southwest,1964.78\n",
      "18,male,26.125,0,no,northeast,1708.92575\n",
      "28,female,26.51,2,no,southeast,4340.4409\n",
      "33,male,27.455,2,no,northwest,5261.46945\n",
      "19,female,25.745,1,no,northwest,2710.82855\n",
      "45,male,30.36,0,yes,southeast,62592.87309\n",
      "62,male,30.875,3,yes,northwest,46718.16325\n",
      "25,female,20.8,1,no,southwest,3208.787\n",
      "43,male,27.8,0,yes,southwest,37829.7242\n",
      "42,male,24.605,2,yes,northeast,21259.37795\n",
      "24,female,27.72,0,no,southeast,2464.6188\n",
      "29,female,21.85,0,yes,northeast,16115.3045\n",
      "32,male,28.12,4,yes,northwest,21472.4788\n",
      "25,female,30.2,0,yes,southwest,33900.653\n",
      "41,male,32.2,2,no,southwest,6875.961\n",
      "42,male,26.315,1,no,northwest,6940.90985\n",
      "33,female,26.695,0,no,northwest,4571.41305\n",
      "34,male,42.9,1,no,southwest,4536.259\n",
      "19,female,34.7,2,yes,southwest,36397.576\n",
      "30,female,23.655,3,yes,northwest,18765.87545\n",
      "18,male,28.31,1,no,northeast,11272.33139\n",
      "19,female,20.6,0,no,southwest,1731.677\n",
      "18,male,53.13,0,no,southeast,1163.4627\n",
      "35,male,39.71,4,no,northeast,19496.71917\n",
      "39,female,26.315,2,no,northwest,7201.70085\n",
      "31,male,31.065,3,no,northwest,5425.02335\n",
      "62,male,26.695,0,yes,northeast,28101.33305\n",
      "62,male,38.83,0,no,southeast,12981.3457\n",
      "42,female,40.37,2,yes,southeast,43896.3763\n",
      "31,male,25.935,1,no,northwest,4239.89265\n",
      "61,male,33.535,0,no,northeast,13143.33665\n",
      "42,female,32.87,0,no,northeast,7050.0213\n",
      "51,male,30.03,1,no,southeast,9377.9047\n",
      "23,female,24.225,2,no,northeast,22395.74424\n",
      "52,male,38.6,2,no,southwest,10325.206\n",
      "57,female,25.74,2,no,southeast,12629.1656\n",
      "23,female,33.4,0,no,southwest,10795.93733\n",
      "52,female,44.7,3,no,southwest,11411.685\n",
      "50,male,30.97,3,no,northwest,10600.5483\n",
      "18,female,31.92,0,no,northeast,2205.9808\n",
      "18,female,36.85,0,no,southeast,1629.8335\n",
      "21,female,25.8,0,no,southwest,2007.945\n",
      "61,female,29.07,0,yes,northwest,29141.3603\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import csv\n",
    "\n",
    "with open('insurance.csv') as insurance_file:\n",
    "    print(insurance_file.read())\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "age = []\n",
    "sex = []\n",
    "bmi = []\n",
    "children = []\n",
    "smoker = []\n",
    "region = []\n",
    "charges = []\n",
    "\n",
    "with open('insurance.csv') as insurance_file:\n",
    "    insurance_data = csv.DictReader(insurance_file)\n",
    "    for row in insurance_data:\n",
    "        age.append(row[\"age\"])\n",
    "        sex.append(row[\"sex\"])\n",
    "        bmi.append(row[\"bmi\"])\n",
    "        children.append(row[\"children\"])\n",
    "        smoker.append(row[\"smoker\"])\n",
    "        region.append(row[\"region\"])\n",
    "        charges.append(row[\"charges\"])\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The average age of the dataset is 39.0\n",
      "The region with the majoirty of patients is the southwest\n",
      "The average insurance cost for a smoker is $32050.23\n",
      "The average insurance cost for a nonsmoker is $8434.27\n",
      "The average difference between insurance cost for a smoker vs a nonsmoker is $23615.96\n",
      "The average age of a parent/guardian is 40.0 years old.\n"
     ]
    }
   ],
   "source": [
    "class Insurance_Info:\n",
    "    \n",
    "    # Initialize class\n",
    "    def __init__(self, age, sex, bmi, children, smoker, region, charges):\n",
    "        self.age = age\n",
    "        self.sex = sex\n",
    "        self.bmi = bmi\n",
    "        self.children = children\n",
    "        self.smoker = smoker\n",
    "        self.region = region\n",
    "        self.charges = charges\n",
    "\n",
    "        \n",
    "    # Calculate average age of patients in dataset\n",
    "    def average_age(self):\n",
    "        total_age = 0\n",
    "        for age_value in age:\n",
    "            total_age += float(age_value)\n",
    "        average_age = total_age / len(self.age)\n",
    "        return round(average_age, 0)\n",
    " \n",
    "\n",
    "    # Determine the region the majority of patients are from\n",
    "    def region_count(self):\n",
    "        region_counts = {}\n",
    "        for region in self.region:\n",
    "            if not region in region_counts:\n",
    "                region_counts[region] = 0\n",
    "            else:\n",
    "                current_count = region_counts[region] + 1\n",
    "                region_counts[region] = current_count\n",
    "        return max(region_counts)\n",
    "    \n",
    "    \n",
    "    # Determine the difference between cost for smokers vs nonsmokers\n",
    "    def smoker_cost_difference(self):\n",
    "        smoker_patients = []\n",
    "        nonsmoker_patients = []\n",
    "        \n",
    "        # Save the index of the patient to smoker/nonsmoker lists\n",
    "        for index, patient in enumerate(self.smoker):\n",
    "            if patient == \"yes\":\n",
    "                smoker_patients.append(index)\n",
    "            else:\n",
    "                nonsmoker_patients.append(index)\n",
    "                \n",
    "        # Calculate average insurance cost for smoker\n",
    "        total_smoker_cost = 0\n",
    "        for patient in smoker_patients:\n",
    "            total_smoker_cost += float(self.charges[patient])\n",
    "        average_smoker_cost = round((total_smoker_cost / len(smoker_patients)), 2)\n",
    "        \n",
    "        # Calculate average insurnace cost for nonsmoker\n",
    "        total_nonsmoker_cost = 0\n",
    "        for patient in nonsmoker_patients:\n",
    "            total_nonsmoker_cost += float(self.charges[patient])\n",
    "        average_nonsmoker_cost = round((total_nonsmoker_cost / len(nonsmoker_patients)), 2)\n",
    "        \n",
    "        # Calculate the difference\n",
    "        average_difference = abs(average_smoker_cost - average_nonsmoker_cost)\n",
    "        \n",
    "        # Print Results\n",
    "        print(\"The average insurance cost for a smoker is $\" + str(average_smoker_cost))\n",
    "        print(\"The average insurance cost for a nonsmoker is $\" + str(average_nonsmoker_cost))\n",
    "        print(\"The average difference between insurance cost for a smoker vs a nonsmoker is $\" + str(average_difference))\n",
    "        \n",
    "        \n",
    "    # Determine the average age of a parent/guardian\n",
    "    def average_age_parent(self):\n",
    "        parent_guardian = []\n",
    "        \n",
    "        # Save the index of the patient to with children to list\n",
    "        for index, child_count in enumerate(self.children):\n",
    "            if float(child_count) > 0:\n",
    "                parent_guardian.append(index)\n",
    "                \n",
    "        # Calculate the average age of parent/guardian\n",
    "        total_age = 0\n",
    "        for patient in parent_guardian:\n",
    "            total_age += float(self.age[patient])\n",
    "        average_age = round((total_age / len(parent_guardian)), 0)\n",
    "        \n",
    "        return average_age\n",
    "                \n",
    "\n",
    "\n",
    "# Print Results   \n",
    "InsuranceInfo = Insurance_Info(age, sex, bmi, children, smoker, region, charges)\n",
    "print(\"The average age of the dataset is \" + str(InsuranceInfo.average_age()))\n",
    "print(\"The region with the majoirty of patients is the \" + str(InsuranceInfo.region_count()))\n",
    "InsuranceInfo.smoker_cost_difference()\n",
    "print(\"The average age of a parent/guardian is \" + str(InsuranceInfo.average_age_parent()) + \" years old.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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