{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### New to Plotly?\n",
    "Plotly's Python library is free and open source! [Get started](https://plotly.com/python/getting-started/) by downloading the client and [reading the primer](https://plotly.com/python/getting-started/).\n",
    "<br>You can set up Plotly to work in [online](https://plotly.com/python/getting-started/#initialization-for-online-plotting) or [offline](https://plotly.com/python/getting-started/#initialization-for-offline-plotting) mode, or in [jupyter notebooks](https://plotly.com/python/getting-started/#start-plotting-online).\n",
    "<br>We also have a quick-reference [cheatsheet](https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf) (new!) to help you get started!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Version Check\n",
    "Note: Linear fits are available in version <b>1.9.2+</b><br>\n",
    "Run  `pip install plotly --upgrade` to update your Plotly version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.12.12'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import plotly\n",
    "plotly.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Linear Fit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "u'https://plotly.com/~PythonPlotBot/162'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Learn about API authentication here: https://plotly.com/python/getting-started\n",
    "# Find your api_key here: https://plotly.com/settings/api\n",
    "\n",
    "import plotly.plotly as py\n",
    "import plotly.graph_objs as go\n",
    "\n",
    "# Scientific libraries\n",
    "from numpy import arange,array,ones\n",
    "from scipy import stats\n",
    "\n",
    "\n",
    "xi = arange(0,9)\n",
    "A = array([ xi, ones(9)])\n",
    "\n",
    "# (Almost) linear sequence\n",
    "y = [19, 20, 20.5, 21.5, 22, 23, 23, 25.5, 24]\n",
    "\n",
    "# Generated linear fit\n",
    "slope, intercept, r_value, p_value, std_err = stats.linregress(xi,y)\n",
    "line = slope*xi+intercept\n",
    "\n",
    "# Creating the dataset, and generating the plot\n",
    "trace1 = go.Scatter(\n",
    "                  x=xi, \n",
    "                  y=y, \n",
    "                  mode='markers',\n",
    "                  marker=go.Marker(color='rgb(255, 127, 14)'),\n",
    "                  name='Data'\n",
    "                  )\n",
    "\n",
    "trace2 = go.Scatter(\n",
    "                  x=xi, \n",
    "                  y=line, \n",
    "                  mode='lines',\n",
    "                  marker=go.Marker(color='rgb(31, 119, 180)'),\n",
    "                  name='Fit'\n",
    "                  )\n",
    "\n",
    "annotation = go.Annotation(\n",
    "                  x=3.5,\n",
    "                  y=23.5,\n",
    "                  text='$R^2 = 0.9551,\\\\Y = 0.716X + 19.18$',\n",
    "                  showarrow=False,\n",
    "                  font=go.Font(size=16)\n",
    "                  )\n",
    "layout = go.Layout(\n",
    "                title='Linear Fit in Python',\n",
    "                plot_bgcolor='rgb(229, 229, 229)',\n",
    "                  xaxis=go.XAxis(zerolinecolor='rgb(255,255,255)', gridcolor='rgb(255,255,255)'),\n",
    "                  yaxis=go.YAxis(zerolinecolor='rgb(255,255,255)', gridcolor='rgb(255,255,255)'),\n",
    "                  annotations=[annotation]\n",
    "                )\n",
    "\n",
    "data = [trace1, trace2]\n",
    "fig = go.Figure(data=data, layout=layout)\n",
    "\n",
    "py.plot(fig, filename='Linear-Fit-in-python')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<link href=\"//fonts.googleapis.com/css?family=Open+Sans:600,400,300,200|Inconsolata|Ubuntu+Mono:400,700\" rel=\"stylesheet\" type=\"text/css\" />"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<link rel=\"stylesheet\" type=\"text/css\" href=\"http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting git+https://github.com/plotly/publisher.git\n",
      "  Cloning https://github.com/plotly/publisher.git to /private/var/folders/ld/6cl3s_l50wd40tdjq2b03jxh0000gp/T/pip-yrr9lh6f-build\n",
      "Installing collected packages: publisher\n",
      "  Found existing installation: publisher 0.10\n",
      "    Uninstalling publisher-0.10:\n",
      "      Successfully uninstalled publisher-0.10\n",
      "  Running setup.py install for publisher ... \u001b[?25l-\b \b\\\b \b|\b \bdone\n",
      "\u001b[?25hSuccessfully installed publisher-0.10\n"
     ]
    }
   ],
   "source": [
    "from IPython.display import display, HTML\n",
    "\n",
    "display(HTML('<link href=\"//fonts.googleapis.com/css?family=Open+Sans:600,400,300,200|Inconsolata|Ubuntu+Mono:400,700\" rel=\"stylesheet\" type=\"text/css\" />'))\n",
    "display(HTML('<link rel=\"stylesheet\" type=\"text/css\" href=\"http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css\">'))\n",
    "\n",
    "! pip install git+https://github.com/plotly/publisher.git --upgrade\n",
    "import publisher\n",
    "publisher.publish(\n",
    "    'linear-fits.ipynb', 'python/linear-fits/', 'Linear Fit',\n",
    "    'Create a linear fit / regression in Python and add a line of best fit to your chart.',\n",
    "    title = 'Linear Fit',\n",
    "    name = 'Linear Fit',\n",
    "    has_thumbnail='true', thumbnail='thumbnail/linear_fit.jpg', \n",
    "    language='python', page_type='example_index',\n",
    "    display_as='statistics', order=10,\n",
    "    ipynb= '~notebook_demo/139')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "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": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}