{
 "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 = 1107322390\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 = 1071452747\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",
    "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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EaJyZ1hPjIj2x+XQ+Qj75DQOXH8KRKyVSl0cGQi8hcMGCBRg4cCDMzc1ha2tb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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff3bdc48290>"
      ]
     },
     "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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WvRri4kUAqEJmsmVa/4w1f+9kNfA3fbrjwSXZO08TmxAQ9aoozP/4xz9uueWW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\nTCbDMMze3t7Ozk4oFC5fvryxsZGUkpctW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     },
     "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 = 1982704938\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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