{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "block_hidden": true
   },
   "outputs": [],
   "source": [
    "%load_ext rpy2.ipython\n",
    "%matplotlib inline\n",
    "import logging\n",
    "logging.getLogger('fbprophet').setLevel(logging.ERROR)\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Python API\n",
    "\n",
    "Prophet follows the `sklearn` model API.  We create an instance of the `Prophet` class and then call its `fit` and `predict` methods.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The input to Prophet is always a dataframe with two columns: `ds` and `y`.  The `ds` (datestamp) column must contain a date or datetime (either is fine). The `y` column must be numeric, and represents the measurement we wish to forecast.\n",
    "\n",
    "As an example, let's look at a time series of daily page views for the Wikipedia page for [Peyton Manning](https://en.wikipedia.org/wiki/Peyton_Manning).  We scraped this data using the [Wikipediatrend](https://cran.r-project.org/web/packages/wikipediatrend/vignettes/using-wikipediatrend.html) package in R.  Peyton Manning provides a nice example because it illustrates some of Prophet's features, like multiple seasonality, changing growth rates, and the ability to model special days (such as Manning's playoff and superbowl appearances). The CSV is available [here](https://github.com/facebook/prophet/blob/master/examples/example_wp_peyton_manning.csv).\n",
    "\n",
    "First we'll import the data and log-transform the y variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from fbprophet import Prophet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>y</th>\n",
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      "text/plain": [
       "           ds         y\n",
       "0  2007-12-10  9.590761\n",
       "1  2007-12-11  8.519590\n",
       "2  2007-12-12  8.183677\n",
       "3  2007-12-13  8.072467\n",
       "4  2007-12-14  7.893572"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('../examples/example_wp_peyton_manning.csv')\n",
    "df['y'] = np.log(df['y'])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We fit the model by instantiating a new `Prophet` object.  Any settings to the forecasting procedure are passed into the constructor.  Then you call its `fit` method and pass in the historical dataframe. Fitting should take 1-5 seconds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = Prophet()\n",
    "m.fit(df);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Predictions are then made on a dataframe with a column `ds` containing the dates for which a prediction is to be made. You can get a suitable dataframe that extends into the future a specified number of days using the helper method `Prophet.make_future_dataframe`. By default it will also include the dates from the history, so we will see the model fit as well. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>ds</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3265</th>\n",
       "      <td>2017-01-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3266</th>\n",
       "      <td>2017-01-16</td>\n",
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       "      <th>3267</th>\n",
       "      <td>2017-01-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3268</th>\n",
       "      <td>2017-01-18</td>\n",
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       "    <tr>\n",
       "      <th>3269</th>\n",
       "      <td>2017-01-19</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ds\n",
       "3265 2017-01-15\n",
       "3266 2017-01-16\n",
       "3267 2017-01-17\n",
       "3268 2017-01-18\n",
       "3269 2017-01-19"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "future = m.make_future_dataframe(periods=365)\n",
    "future.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `predict` method will assign each row in `future` a predicted value which it names `yhat`.  If you pass in historical dates, it will provide an in-sample fit. The `forecast` object here is a new dataframe that includes a column `yhat` with the forecast, as well as columns for components and uncertainty intervals."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>yhat</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3265</th>\n",
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       "      <td>8.937916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3266</th>\n",
       "      <td>2017-01-16</td>\n",
       "      <td>8.531766</td>\n",
       "      <td>7.791623</td>\n",
       "      <td>9.279194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3267</th>\n",
       "      <td>2017-01-17</td>\n",
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       "      <td>9.077195</td>\n",
       "    </tr>\n",
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       "      <th>3268</th>\n",
       "      <td>2017-01-18</td>\n",
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       "      <td>2017-01-19</td>\n",
       "      <td>8.163690</td>\n",
       "      <td>7.472291</td>\n",
       "      <td>8.926861</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ds      yhat  yhat_lower  yhat_upper\n",
       "3265 2017-01-15  8.206753    7.432279    8.937916\n",
       "3266 2017-01-16  8.531766    7.791623    9.279194\n",
       "3267 2017-01-17  8.319156    7.601640    9.077195\n",
       "3268 2017-01-18  8.151772    7.436613    8.895926\n",
       "3269 2017-01-19  8.163690    7.472291    8.926861"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast = m.predict(future)\n",
    "forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can plot the forecast by calling the `Prophet.plot` method and passing in your forecast dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "[encoded data, 157984 characters]\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f466b44ce10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1 = m.plot(forecast)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want to see the forecast components, you can use the `Prophet.plot_components` method.  By default you'll see the trend, yearly seasonality, and weekly seasonality of the time series.  If you include holidays, you'll see those here, too."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "[encoded data, 68804 characters]\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f466b44ced0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2 = m.plot_components(forecast)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "More details about the options available for each method are available in the docstrings, for example, via `help(Prophet)` or `help(Prophet.fit)`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## R API\n",
    "\n",
    "In R, we use the normal model fitting API.  We provide a `prophet` function that performs fitting and returns a model object.  You can then call `predict` and `plot` on this model object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "output_hidden": true
   },
   "outputs": [],
   "source": [
    "%%R\n",
    "library(prophet)\n",
    "library(dplyr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we read in the data and create the outcome variable. As in the Python API, this is a dataframe with columns `ds` and `y`, containing the date and numeric value respectively. As above, we use here the log number of views to Petyon Manning's Wikipedia page, available [here](https://github.com/facebook/prophet/blob/master/examples/example_wp_peyton_manning.csv)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%%R\n",
    "df <- read.csv('../examples/example_wp_peyton_manning.csv') %>%\n",
    "  mutate(y = log(y))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We call the `prophet` function to fit the model.  The first argument is the historical dataframe.  Additional arguments control how Prophet fits the data and are described in later pages of this documentation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "output_hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "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)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Predictions are made on a dataframe with a column `ds` containing the dates for which predictions are to be made. The `make_future_dataframe` function takes the model object and a number of periods to forecast and produces a suitable dataframe. By default it will also include the historical dates so we can evaluate in-sample fit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "             ds\n",
       "3265 2017-01-14\n",
       "3266 2017-01-15\n",
       "3267 2017-01-16\n",
       "3268 2017-01-17\n",
       "3269 2017-01-18\n",
       "3270 2017-01-19\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "future <- make_future_dataframe(m, periods = 365)\n",
    "tail(future)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As with most modeling procedures in R, we use the generic `predict` function to get our forecast. The `forecast` object is a dataframe with a column `yhat` containing the forecast. It has additional columns for uncertainty intervals and seasonal components."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "             ds     yhat yhat_lower yhat_upper\n",
       "3265 2017-01-14 7.825609   7.183818   8.488012\n",
       "3266 2017-01-15 8.207400   7.478778   8.951113\n",
       "3267 2017-01-16 8.532394   7.826360   9.240482\n",
       "3268 2017-01-17 8.319785   7.596815   9.042505\n",
       "3269 2017-01-18 8.152424   7.440858   8.874581\n",
       "3270 2017-01-19 8.164327   7.419148   8.882906\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "forecast <- predict(m, future)\n",
    "tail(forecast[c('ds', 'yhat', 'yhat_lower', 'yhat_upper')])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can use the generic `plot` function to plot the forecast, by passing in the model and the forecast dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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j41u3bs3n89kOB8lyc3OjpioMHDjQ2dmZ7XAQQqoHEw6kLOrUqYOLkbIuOTl51apVX79+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\nAABJRU5ErkJggg==\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R -w 10 -h 6 -u in\n",
    "plot(m, forecast)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can use the `prophet_plot_components` function to see the forecast broken down into trend, weekly seasonality, and yearly seasonality."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Dr1+/vnTp0j59+ixYsIDlstjkLmG+Hx81OVYx4vuM7Wm3uC6nqeqN5um7suqN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\nD5PeU17oMMO5AAAAAElFTkSuQmCC\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R -w 9 -h 9 -u in\n",
    "prophet_plot_components(m, forecast)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "More details about the options available for each method are available in the docstrings, for example, via `?prophet` or `?fit.prophet`. This documentation is also available in the [reference manual](https://cran.r-project.org/web/packages/prophet/prophet.pdf) on CRAN."
   ]
  }
 ],
 "metadata": {
  "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": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
