3.Polynomial_Regression.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv(\"position_salaries.csv\")\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df[\"Level\"].values\n",
    "y = df[\"Salary\"].values\n",
    "\n",
    "X = X.reshape(-1,1)\n",
    "y = y.reshape(-1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "model = LinearRegression()\n",
    "model.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "y_pred = model.predict(X)\n",
    "\n",
    "plt.scatter(X, y, color = 'red')\n",
    "plt.plot(X, y_pred, color = 'blue')\n",
    "plt.title('Linear Regression')\n",
    "plt.xlabel('Position level')\n",
    "plt.ylabel('Salary')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "\n",
    "poly = PolynomialFeatures(degree = 2)\n",
    "Xp = poly.fit_transform(X)\n",
    "\n",
    "model = LinearRegression()\n",
    "model.fit(Xp, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = model.predict(Xp)\n",
    "\n",
    "plt.scatter(X, y, color = 'red')\n",
    "plt.plot(X, y_pred, color = 'blue')\n",
    "plt.title('Polynomial Linear Regression')\n",
    "plt.xlabel('Position level')\n",
    "plt.ylabel('Salary')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "datacamp",
   "language": "python",
   "name": "datacamp"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}