{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "block_hidden": true,
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%load_ext rpy2.ipython\n",
    "%matplotlib inline\n",
    "from fbprophet import Prophet\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "df = pd.read_csv('../examples/example_wp_peyton_manning.csv')\n",
    "df['y'] = np.log(df['y'])\n",
    "m = Prophet()\n",
    "m.fit(df)\n",
    "future = m.make_future_dataframe(periods=366)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "block_hidden": true,
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python2.7/dist-packages/rpy2/rinterface/__init__.py:186: RRuntimeWarning: Loading required package: Rcpp\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "STAN OPTIMIZATION COMMAND (LBFGS)\n",
       "init = user\n",
       "save_iterations = 1\n",
       "init_alpha = 0.001\n",
       "tol_obj = 1e-12\n",
       "tol_grad = 1e-08\n",
       "tol_param = 1e-08\n",
       "tol_rel_obj = 10000\n",
       "tol_rel_grad = 1e+07\n",
       "history_size = 5\n",
       "seed = 1733845324\n",
       "initial log joint probability = -19.4685\n",
       "Optimization terminated normally: \n",
       "  Convergence detected: relative gradient magnitude is below tolerance\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "library(prophet)\n",
    "df <- read.csv('../examples/example_wp_peyton_manning.csv')\n",
    "df$y <- log(df$y)\n",
    "m <- prophet(df)\n",
    "future <- make_future_dataframe(m, periods=366)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Modeling Holidays\n",
    "If you have holidays that you'd like to model, you must create a dataframe for them. It has two columns (`holiday` and `ds`) and a row for each occurrence of the holiday. It must include all occurrences of the holiday, both in the past (back as far as the historical data go) and in the future (out as far as the forecast is being made). If they won't repeat in the future, Prophet will model them and then not include them in the forecast.\n",
    "\n",
    "You can also include columns `lower_window` and `upper_window` which extend the holiday out to `[lower_window, upper_window]` days around the date. For instance, if you wanted to included Christmas Eve in addition to Christmas you'd include `lower_window=-1,upper_window=0`. If you wanted to use Black Friday in addition to Thanksgiving, you'd include `lower_window=0,upper_window=1`.\n",
    "\n",
    "Here we create a dataframe that includes the dates of all of Peyton Manning's playoff appearances:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "playoffs = pd.DataFrame({\n",
    "  'holiday': 'playoff',\n",
    "  'ds': pd.to_datetime(['2008-01-13', '2009-01-03', '2010-01-16',\n",
    "                        '2010-01-24', '2010-02-07', '2011-01-08',\n",
    "                        '2013-01-12', '2014-01-12', '2014-01-19',\n",
    "                        '2014-02-02', '2015-01-11', '2016-01-17',\n",
    "                        '2016-01-24', '2016-02-07']),\n",
    "  'lower_window': 0,\n",
    "  'upper_window': 1,\n",
    "})\n",
    "superbowls = pd.DataFrame({\n",
    "  'holiday': 'superbowl',\n",
    "  'ds': pd.to_datetime(['2010-02-07', '2014-02-02', '2016-02-07']),\n",
    "  'lower_window': 0,\n",
    "  'upper_window': 1,\n",
    "})\n",
    "holidays = pd.concat((playoffs, superbowls))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "output_hidden": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python2.7/dist-packages/rpy2/rinterface/__init__.py:186: RRuntimeWarning: \n",
      "Attaching package: ‘dplyr’\n",
      "\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/usr/lib/python2.7/dist-packages/rpy2/rinterface/__init__.py:186: RRuntimeWarning: The following objects are masked from ‘package:stats’:\n",
      "\n",
      "    filter, lag\n",
      "\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/usr/lib/python2.7/dist-packages/rpy2/rinterface/__init__.py:186: RRuntimeWarning: The following objects are masked from ‘package:base’:\n",
      "\n",
      "    intersect, setdiff, setequal, union\n",
      "\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n"
     ]
    }
   ],
   "source": [
    "%%R\n",
    "library(dplyr)\n",
    "playoffs <- data_frame(\n",
    "  holiday = 'playoff',\n",
    "  ds = as.Date(c('2008-01-13', '2009-01-03', '2010-01-16',\n",
    "                 '2010-01-24', '2010-02-07', '2011-01-08',\n",
    "                 '2013-01-12', '2014-01-12', '2014-01-19',\n",
    "                 '2014-02-02', '2015-01-11', '2016-01-17',\n",
    "                 '2016-01-24', '2016-02-07')),\n",
    "  lower_window = 0,\n",
    "  upper_window = 1\n",
    ")\n",
    "superbowls <- data_frame(\n",
    "  holiday = 'superbowl',\n",
    "  ds = as.Date(c('2010-02-07', '2014-02-02', '2016-02-07')),\n",
    "  lower_window = 0,\n",
    "  upper_window = 1\n",
    ")\n",
    "holidays <- bind_rows(playoffs, superbowls)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above we have include the superbowl days as both playoff games and superbowl games. This means that the superbowl effect will be an additional additive bonus on top of the playoff effect.\n",
    "\n",
    "Once the table is created, holiday effects are included in the forecast by passing them in with the `holidays` argument. Here we do it with the Peyton Manning data from the Quickstart:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "m = Prophet(holidays=holidays)\n",
    "forecast = m.fit(df).predict(future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "output_hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "STAN OPTIMIZATION COMMAND (LBFGS)\n",
       "init = user\n",
       "save_iterations = 1\n",
       "init_alpha = 0.001\n",
       "tol_obj = 1e-12\n",
       "tol_grad = 1e-08\n",
       "tol_param = 1e-08\n",
       "tol_rel_obj = 10000\n",
       "tol_rel_grad = 1e+07\n",
       "history_size = 5\n",
       "seed = 1274276645\n",
       "initial log joint probability = -19.4685\n",
       "Optimization terminated normally: \n",
       "  Convergence detected: relative gradient magnitude is below tolerance\n",
       "\r",
       "|======================================================|100% ~0 s remaining     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "m <- prophet(df, holidays = holidays)\n",
    "forecast <- predict(m, future)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The holiday effect can be seen in the `forecast` dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "output_hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "           ds  playoff superbowl\n",
       "17 2014-02-02 1.219014  1.230508\n",
       "18 2014-02-03 1.908609  1.398806\n",
       "19 2015-01-11 1.219014  0.000000\n",
       "20 2015-01-12 1.908609  0.000000\n",
       "21 2016-01-17 1.219014  0.000000\n",
       "22 2016-01-18 1.908609  0.000000\n",
       "23 2016-01-24 1.219014  0.000000\n",
       "24 2016-01-25 1.908609  0.000000\n",
       "25 2016-02-07 1.219014  1.230508\n",
       "26 2016-02-08 1.908609  1.398806\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "forecast %>% \n",
    "  select(ds, playoff, superbowl) %>% \n",
    "  filter(abs(playoff + superbowl) > 0) %>%\n",
    "  tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>playoff</th>\n",
       "      <th>superbowl</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2190</th>\n",
       "      <td>2014-02-02</td>\n",
       "      <td>1.220308</td>\n",
       "      <td>1.204992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2191</th>\n",
       "      <td>2014-02-03</td>\n",
       "      <td>1.900465</td>\n",
       "      <td>1.444581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2532</th>\n",
       "      <td>2015-01-11</td>\n",
       "      <td>1.220308</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2533</th>\n",
       "      <td>2015-01-12</td>\n",
       "      <td>1.900465</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2901</th>\n",
       "      <td>2016-01-17</td>\n",
       "      <td>1.220308</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2902</th>\n",
       "      <td>2016-01-18</td>\n",
       "      <td>1.900465</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2908</th>\n",
       "      <td>2016-01-24</td>\n",
       "      <td>1.220308</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2909</th>\n",
       "      <td>2016-01-25</td>\n",
       "      <td>1.900465</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2922</th>\n",
       "      <td>2016-02-07</td>\n",
       "      <td>1.220308</td>\n",
       "      <td>1.204992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2923</th>\n",
       "      <td>2016-02-08</td>\n",
       "      <td>1.900465</td>\n",
       "      <td>1.444581</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ds   playoff  superbowl\n",
       "2190 2014-02-02  1.220308   1.204992\n",
       "2191 2014-02-03  1.900465   1.444581\n",
       "2532 2015-01-11  1.220308   0.000000\n",
       "2533 2015-01-12  1.900465   0.000000\n",
       "2901 2016-01-17  1.220308   0.000000\n",
       "2902 2016-01-18  1.900465   0.000000\n",
       "2908 2016-01-24  1.220308   0.000000\n",
       "2909 2016-01-25  1.900465   0.000000\n",
       "2922 2016-02-07  1.220308   1.204992\n",
       "2923 2016-02-08  1.900465   1.444581"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast[(forecast['playoff'] + forecast['superbowl']).abs() > 0][\n",
    "        ['ds', 'playoff', 'superbowl']][-10:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The holiday effects will also show up in the components plot, where we see that there is a spike on the days around playoff appearances, with an especially large spike for the superbowl:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "output_hidden": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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TExDmbiv1aJLTakU88dNhLNp/DuPjvDF7SCgLIBERALlchie6+iO5ix+WHyzE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\nQgghhBA10P8H/1Kqiuvsn+0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc9ec395310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m.plot_components(forecast);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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BRbd10/PKbBRm3aAw6+Y8LMxBRyq9L68r/GDLietyUx4YmKnDqBsKc73OfROL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\njMj/A58bRt2VRI6NAAAAAElFTkSuQmCC\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R -w 9 -h 12 -u in\n",
    "prophet_plot_components(m, forecast);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prior scale for holidays and seasonality\n",
    "If you find that the holidays are overfitting, you can adjust their prior scale to smooth them using the parameter `holidays_prior_scale`, which by default is 10:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "output_hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "STAN OPTIMIZATION COMMAND (LBFGS)\n",
       "init = user\n",
       "save_iterations = 1\n",
       "init_alpha = 0.001\n",
       "tol_obj = 1e-12\n",
       "tol_grad = 1e-08\n",
       "tol_param = 1e-08\n",
       "tol_rel_obj = 10000\n",
       "tol_rel_grad = 1e+07\n",
       "history_size = 5\n",
       "seed = 1488013908\n",
       "initial log joint probability = -19.4685\n",
       "Optimization terminated normally: \n",
       "  Convergence detected: relative gradient magnitude is below tolerance\n",
       "\r",
       "|======================================================|100% ~0 s remaining                ds  playoff superbowl\n",
       "17 2014-02-02 1.322980 0.7580416\n",
       "18 2014-02-03 1.991028 0.6133796\n",
       "19 2015-01-11 1.322980 0.0000000\n",
       "20 2015-01-12 1.991028 0.0000000\n",
       "21 2016-01-17 1.322980 0.0000000\n",
       "22 2016-01-18 1.991028 0.0000000\n",
       "23 2016-01-24 1.322980 0.0000000\n",
       "24 2016-01-25 1.991028 0.0000000\n",
       "25 2016-02-07 1.322980 0.7580416\n",
       "26 2016-02-08 1.991028 0.6133796\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "m <- prophet(df, holidays = holidays, holidays.prior.scale = 1)\n",
    "forecast <- predict(m, future)\n",
    "forecast %>% \n",
    "  select(ds, playoff, superbowl) %>% \n",
    "  filter(abs(playoff + superbowl) > 0) %>%\n",
    "  tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>playoff</th>\n",
       "      <th>superbowl</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2190</th>\n",
       "      <td>2014-02-02</td>\n",
       "      <td>1.362312</td>\n",
       "      <td>0.693425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2191</th>\n",
       "      <td>2014-02-03</td>\n",
       "      <td>2.033471</td>\n",
       "      <td>0.542254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2532</th>\n",
       "      <td>2015-01-11</td>\n",
       "      <td>1.362312</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2533</th>\n",
       "      <td>2015-01-12</td>\n",
       "      <td>2.033471</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2901</th>\n",
       "      <td>2016-01-17</td>\n",
       "      <td>1.362312</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2902</th>\n",
       "      <td>2016-01-18</td>\n",
       "      <td>2.033471</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2908</th>\n",
       "      <td>2016-01-24</td>\n",
       "      <td>1.362312</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2909</th>\n",
       "      <td>2016-01-25</td>\n",
       "      <td>2.033471</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2922</th>\n",
       "      <td>2016-02-07</td>\n",
       "      <td>1.362312</td>\n",
       "      <td>0.693425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2923</th>\n",
       "      <td>2016-02-08</td>\n",
       "      <td>2.033471</td>\n",
       "      <td>0.542254</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ds   playoff  superbowl\n",
       "2190 2014-02-02  1.362312   0.693425\n",
       "2191 2014-02-03  2.033471   0.542254\n",
       "2532 2015-01-11  1.362312   0.000000\n",
       "2533 2015-01-12  2.033471   0.000000\n",
       "2901 2016-01-17  1.362312   0.000000\n",
       "2902 2016-01-18  2.033471   0.000000\n",
       "2908 2016-01-24  1.362312   0.000000\n",
       "2909 2016-01-25  2.033471   0.000000\n",
       "2922 2016-02-07  1.362312   0.693425\n",
       "2923 2016-02-08  2.033471   0.542254"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m = Prophet(holidays=holidays, holidays_prior_scale=1).fit(df)\n",
    "forecast = m.predict(future)\n",
    "forecast[(forecast['playoff'] + forecast['superbowl']).abs() > 0][\n",
    "    ['ds', 'playoff', 'superbowl']][-10:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The magnitude of the holiday effect has been reduced compared to before, especially for superbowls, which had the fewest observations. There is a parameter `seasonality_prior_scale` which similarly adjusts the extent to which the seasonality model will fit the data."
   ]
  }
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