1_Box-Cox.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.stats import boxcox"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Read the dataset and assign values of e to a varible\n",
    "dataset = pd.read_csv('exoplanet.eu_catalog.csv')\n",
    "eccentricity = dataset['eccentricity']\n",
    "eccentricity_withoutNa = eccentricity.dropna()     #We drop the NaN rows from the eccentricity column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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uAc4BrgHurKp7WpdNwOI2vRi4AaAt3wLs17POtUk2JNkwNTU1zvIlabc21oCoqp9V1ZOBJcDBwBNGsM6Tq2pFVa1YuHDhTtcoSeo3J2cxVdWdwPnA04EFSbbeJHAJsLlNbwaWArTljwBum4v6JEn/1jjPYlqYZEGbfgjwG8BVdEHx0tZtNXBmm17f5mnLz2tfVCRJmoBhvg9iRx0ArEuyB10QnVZVZyW5EvhkkncCl9J9lSnt50eTbARuB44eY22SpBmMLSCq6nLgKT3t19Idj5je/mPgZeOqR5I0O15JLUnqZUBIknoZEJKkXgaEJKmXASFJ6mVASJJ6GRCSpF7jvFBut7Ps+M+NdH3XnfDCka5PkmbDPQhJUi8DQpLUy4CQJPUyICRJvQwISVIvA0KS1MuAkCT1MiAkSb0MCElSLwNCktTLgJAk9TIgJEm9DAhJUi8DQpLUa2wBkWRpkvOTXJnkiiRvaO37JjknydXt5z6tPUlOTLIxyeVJDhpXbZKkmY1zD+Ie4M1VdSBwCHBckgOB44Fzq2o5cG6bBzgMWN4ea4GTxlibJGkGYwuIqrqxqv6xTX8fuApYDKwC1rVu64Aj2/Qq4NTqXAQsSHLAuOqTJG3fnByDSLIMeApwMbCoqm5si24CFrXpxcANA0/b1Nqmr2ttkg1JNkxNTY2tZkna3Y09IJI8FPgb4I1V9b3BZVVVQM1mfVV1clWtqKoVCxcuHGGlkqRBYw2IJA+kC4ePVdVnWvPNW4eO2s9bWvtmYOnA05e0NknSBIzzLKYAHwKuqqo/G1i0HljdplcDZw60H9POZjoE2DIwFCVJmmN7jnHdzwReCXwzyWWt7Q+AE4DTkqwBrgeOasvOBg4HNgJ3AceOsbb7hWXHf26k67vuhBeOdH2Sdm1jC4iq+gcg21i8sqd/AceNqx5J0ux4JbUkqZcBIUnqZUBIknoZEJKkXgaEJKmXASFJ6mVASJJ6GRCSpF4GhCSplwEhSeplQEiSehkQkqReBoQkqZcBIUnqNc7vg9A84/dLSJoN9yAkSb0MCElSLwNCktTLgJAk9TIgJEm9DAhJUi8DQpLUa2wBkeTDSW5J8q2Btn2TnJPk6vZzn9aeJCcm2Zjk8iQHjasuSdJwxrkHcQpw6LS244Fzq2o5cG6bBzgMWN4ea4GTxliXJGkIYwuIqvoScPu05lXAuja9DjhyoP3U6lwELEhywLhqkyTNbK6PQSyqqhvb9E3Aoja9GLhhoN+m1vZvJFmbZEOSDVNTU+OrVJJ2cxM7SF1VBdQOPO/kqlpRVSsWLlw4hsokSTD3AXHz1qGj9vOW1r4ZWDrQb0lrkyRNyFwHxHpgdZteDZw50H5MO5vpEGDLwFCUJGkCxna77ySfAJ4L7J9kE/AO4ATgtCRrgOuBo1r3s4HDgY3AXcCx46pLozPq24eDtxCX5pOxBURVvXwbi1b29C3guHHVIkmaPa+kliT1MiAkSb0MCElSLwNCktTLgJAk9TIgJEm9xnaaq7QjRn1thddVSDvOPQhJUi8DQpLUy4CQJPUyICRJvQwISVIvz2LSLs2zoqQd5x6EJKmXexDSLIzjOzBGzb0cjYp7EJKkXgaEJKmXASFJ6mVASJJ6GRCSpF6exSTtYub7mVaeZXX/4R6EJKnXvAqIJIcm+U6SjUmOn3Q9krQ7mzcBkWQP4P3AYcCBwMuTHDjZqiRp9zWfjkEcDGysqmsBknwSWAVcOdGqJI3UfD9GAqM/TjKObZ6LYznzKSAWAzcMzG8Cnja9U5K1wNo2+4Mk39nB19sfuHUHnzvfuC3zk9syP824LXn3HFWyE1qNO/q+PGqYTvMpIIZSVScDJ+/sepJsqKoVIyhp4tyW+cltmZ/cluHNm2MQwGZg6cD8ktYmSZqA+RQQlwDLkzw6yV7A0cD6CdckSbuteTPEVFX3JHkd8HfAHsCHq+qKMb7kTg9TzSNuy/zktsxPbsuQUlXjXL8k6X5qPg0xSZLmEQNCktRrlw+ImW7fkeRBST7Vll+cZNncVzmcIbblTUmuTHJ5knOTDHWu8yQMe1uVJL+VpJLM29MSh9mWJEe19+aKJB+f6xqHNcS/sUcmOT/Jpe3f2eGTqHMmST6c5JYk39rG8iQ5sW3n5UkOmusahzXEtvx224ZvJrkwyZNG9uJVtcs+6A52XwM8BtgL+AZw4LQ+/xX4QJs+GvjUpOveiW15HvALbfp378/b0vo9DPgScBGwYtJ178T7shy4FNinzf/ipOveiW05GfjdNn0gcN2k697GtjwbOAj41jaWHw58HghwCHDxpGveiW15xsC/rcNGuS27+h7Ez2/fUVU/BbbevmPQKmBdmz4dWJkkc1jjsGbclqo6v6ruarMX0V1LMh8N874A/DHwbuDHc1ncLA2zLa8B3l9VdwBU1S1zXOOwhtmWAh7eph8B/Msc1je0qvoScPt2uqwCTq3ORcCCJAfMTXWzM9O2VNWFW/9tMeL/97t6QPTdvmPxtvpU1T3AFmC/OaludobZlkFr6P5Cmo9m3Ja2y7+0qub7jXuGeV8eBzwuyVeSXJTk0DmrbnaG2ZY/Al6RZBNwNvD6uSlt5Gb7/+n+YqT/7+fNdRAanSSvAFYAz5l0LTsiyQOAPwNeNeFSRmVPumGm59L9dfelJL9WVXdOtKod83LglKr630meDnw0yROr6t5JF7a7S/I8uoB41qjWuavvQQxz+46f90myJ91u821zUt3sDHUrkiT/AfhD4Iiq+skc1TZbM23Lw4AnAhckuY5ujHj9PD1QPcz7sglYX1V3V9U/A/9EFxjzzTDbsgY4DaCqvgo8mO6Gcfc3u9StfZL8OvBBYFVVjezza1cPiGFu37EeWN2mXwqcV+1ozzwz47YkeQrw13ThMF/HuWGGbamqLVW1f1Utq6pldOOqR1TVhsmUu13D/Bv7LN3eA0n2pxtyunYuixzSMNvyXWAlQJJfpQuIqTmtcjTWA8e0s5kOAbZU1Y2TLmpHJHkk8BnglVX1TyNd+aSP0M/BGQCH0/3Fdg3wh63tf9B94ED3D/zTwEbga8BjJl3zTmzLF4GbgcvaY/2ka97RbZnW9wLm6VlMQ74voRsyuxL4JnD0pGveiW05EPgK3RlOlwEvmHTN29iOTwA3AnfT7cGtAV4LvHbgPXl/285vzvN/XzNtyweBOwb+328Y1Wt7qw1JUq9dfYhJkrSDDAhJUi8DQpLUy4CQJPUyICRJvQwISVIvA0KS1MuAkEYoyVPbvfkfnGTv9v0PT5x0XdKO8EI5acSSvJPuCv2HAJuq6l0TLknaIQaENGLtPkaX0H2PxTOq6mcTLknaIQ4xSaO3H/BQurvSPnjCtUg7zD0IacSSrKf7NrZHAwdU1esmXJK0Q/zCIGmEkhwD3F1VH0+yB3BhkudX1XmTrk2aLfcgJEm9PAYhSeplQEiSehkQkqReBoQkqZcBIUnqZUBIknoZEJKkXv8f0FXyyre369YAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot the histogram of 'e'\n",
    "plt.hist(eccentricity_withoutNa, bins=15)\n",
    "plt.title('Eccentricity Histogram')\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('y')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot the gaussian distribution using boxcox\n",
    "posdata = eccentricity[eccentricity>0]\n",
    "e_boxcox, const = boxcox(posdata)\n",
    "plt.hist(e_boxcox, bins=15)\n",
    "plt.xlabel('x')\n",
    "plt.ylabel('y')\n",
    "plt.title('Eccentricity Gaussian Distribution using boxcox transformation')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "2.7.15rc1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}