Code/Convert normal Distribution.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Vn5QNv4O06e4"
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "SFSvcRiK1lS8"
   },
   "outputs": [],
   "source": [
    "#Exponential distribution\n",
    "X = np.random.exponential(2, (10000,1))\n",
    "\n",
    "#Log Normal distribution\n",
    "Y = np.random.weibull(a = 2, size = (10000,1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot Exponential and weibull distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 475
    },
    "colab_type": "code",
    "id": "eZvP25Z81zJb",
    "outputId": "e9c4e0a0-3d2a-4648-9745-ac3c2fa1c1d7"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'weibull distribution')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x480 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,4), dpi = 120)\n",
    "\n",
    "#Plotting exponential distribution\n",
    "plt.subplot(121)\n",
    "plt.hist(X, bins = 100)\n",
    "plt.title(\"exponential distribution\")\n",
    "\n",
    "#plotting weibull distribution\n",
    "plt.subplot(122)\n",
    "plt.hist(Y, bins = 100)\n",
    "plt.title(\"weibull distribution\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 35
    },
    "colab_type": "code",
    "id": "nUBi3DZU13eZ",
    "outputId": "bdbba736-5dd4-4291-bc8f-5eeb1e6b116a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "distributions transformed\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import QuantileTransformer\n",
    "qt = QuantileTransformer(n_quantiles = len(X), output_distribution = 'normal')\n",
    "\n",
    "## transforming above distributions to Normal distribution ##\n",
    "X = qt.fit_transform(X)\n",
    "Y = qt.fit_transform(Y)\n",
    "print('distributions transformed')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot transformed distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 475
    },
    "colab_type": "code",
    "id": "sNs0JPUo4pqM",
    "outputId": "e5c88ecd-cad5-457a-fe74-6c72ac233dac"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'transformed weibull')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x480 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,4), dpi = 120)\n",
    "\n",
    "#Plotting transformed exponential\n",
    "plt.subplot(121)\n",
    "plt.hist(X, bins = 100)\n",
    "plt.title(\"transformed exponential\")\n",
    "\n",
    "#plotting transformed weibull\n",
    "plt.subplot(122)\n",
    "plt.hist(Y, bins = 100)\n",
    "plt.title(\"transformed weibull\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "5_XYuuCaFtAI"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "name": "AV hack of day.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}