{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "import random\n",
    "import numpy as np\n",
    "from lets_plot import *\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "LetsPlot.setup_html()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "mpg_df = pd.read_csv('https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/mpg.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ggplot(mpg_df, aes(x='displ', y='hwy')) + geom_point() + geom_smooth( deg = 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "random.seed(42)\n",
    "n = 500\n",
    "x_range = np.arange(-2 * math.pi, 2 * math.pi, 4 * math.pi / n)\n",
    "y_range = x_range + np.sin(x_range) + np.array([random.gauss(0.0, 1.0) for i in range(n)])\n",
    "df = pd.DataFrame({ 'x' : x_range, 'y' : y_range })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "p = ggplot(df, aes(x='x', y='y')) + geom_point(shape=21, fill='yellow', color='#8c564b')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "p + geom_smooth(method='lm', deg = 5, size=1.5, color='#d62728') "
   ]
  }
 ],
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