GettingStarted.ipynb

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    "Causal Impact\n",
    "=============\n",
    "\n",
    "A Python package for causal inference using Bayesian structural time-series models. It's a port of the R package CausalImpact, see https://github.com/google/CausalImpact.\n",
    "  \n",
    "### What does the package do?\n",
    "This package implements an approach to estimating the causal effect of a designed intervention on a time series. For example, how many additional daily clicks were generated by an advertising campaign? Answering a question like this can be difficult when a randomized experiment is not available.\n",
    "\n",
    "### How does it work?\n",
    "Given a response time series (e.g., clicks) and a set of control time series (e.g., clicks in non-affected markets or clicks on other sites), the package constructs a Bayesian structural time-series model. This model is then used to try and predict the counterfactual, i.e., how the response metric would have evolved after the intervention if the intervention had never occurred. For details, see: [Brodersen et al., Annals of Applied Statistics (2015)](http://research.google.com/pubs/pub41854.html).\n",
    "\n",
    "### What assumptions does the model make?\n",
    "As with all non-experimental approaches to causal inference, valid conclusions require strong assumptions. In the case of CausalImpact, we assume that there is a set control time series that were *themselves not affected by the intervention.* If they were, we might falsely under- or overestimate the true effect. Or we might falsely conclude that there was an effect even though in reality there wasn't. The model also assumes that the relationship between covariates and treated time series, as established during the pre-period, remains stable throughout the post-period (see `impact.model_args[\"dynamic_regression\"]` for a way of relaxing this assumption). Finally, it's important to be aware of the *priors* that are part of the model (see `impact.model_args[\"prior_level_sd\"]` in particular).\n",
    "\n",
    "### How is the package structured?\n",
    "The package is designed to make counterfactual inference as easy as fitting a regression model, but much more powerful, provided the assumptions above are met. The package has a single entry point, the function `CausalImpact()`. Given a response time series and a set of control time series, the function constructs a time-series model, performs posterior inference on the counterfactual, and returns a `CausalImpact` object. The results can be summarized in terms of a table, a verbal description, or a plot.\n",
    "\n",
    "\n",
    "### 1. Installing the package\n",
    "\n",
    "To install `causalimpact` run:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# !pip install git+https://github.com/jamalsenouci/causalimpact.git"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once installed, the package can be imported using:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from causalimpact import CausalImpact"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Creating an example dataset\n",
    "\n",
    "To illustrate how the package works, we create a simple toy dataset. It consists of a response variable `y` and a predictor `x1`. Note that in practice, we'd strive for including many more predictor variables and let the model choose an appropriate subset. The example data has 100 observations. We create an *intervention effect* by lifting the response variable by 10 units after timepoint 71.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from statsmodels.tsa.arima_process import arma_generate_sample\n",
    "import matplotlib\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "matplotlib.rcParams['figure.figsize'] = (15, 6)\n",
    "\n",
    "np.random.seed(1)\n",
    "\n",
    "x1 = arma_generate_sample(ar=[0.999], ma=[0.9], nsample=100) + 100\n",
    "y = 1.2 * x1 + np.random.randn(100)\n",
    "\n",
    "y[71:100] = y[71:100] + 10\n",
    "data = pd.DataFrame(np.array([y, x1]).T, columns=[\"y\",\"x1\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now have a simple matrix with 100 rows and two columns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>y</th>\n",
       "      <th>x1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>121.308920</td>\n",
       "      <td>101.463374</td>\n",
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       "      <th>1</th>\n",
       "      <td>120.563149</td>\n",
       "      <td>99.448868</td>\n",
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       "      <th>2</th>\n",
       "      <td>119.832495</td>\n",
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      "text/plain": [
       "            y          x1\n",
       "0  121.308920  101.463374\n",
       "1  120.563149   99.448868\n",
       "2  119.832495   99.524170\n",
       "3  119.433612   99.033362\n",
       "4  119.840664  100.779647"
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     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can visualize the generated data using:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1f25f6759b0>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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AVnEL7d0D7FwdOeV1RSOC/dx5aFc8n71lKRUN3WQUNV/xR6fVkBDtxxf2JIxWt6Yip7QV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\no6a1AfZEYsK88HZ3IresdcL3rry+i30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MZvOMT0u5uzqzcXEU//qNFfzLN5azYVEkXb1D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lbz9jVN45PE1RzMi2ZM4AhuCV9ySdY5HcyN5uvUddRaTPTvHsLSQded1znzaEEc78V/ysSeY7lh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\nCCHskARrQgghhBBCCGGH/j8ukDHrPKX0OQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f25f34e860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Running an Analysis\n",
    "\n",
    "To estimate the causal effect, we begin by specifying which period in the data should be used for training the model (pre-intervention period) and which period for computing a counterfactual prediction (post-intervention period)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pre_period = [0,69]\n",
    "post_period = [71,99]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This says that time points 0...70 will be used for training, and time points 71...99 will be used for computing predictions. Alternatively, we could specify the periods in terms of dates or time points; see <a href=\"#5.-Working-with-dates-and-times\">Section 5</a> for an example.\n",
    "\n",
    "To perform inference, we run the analysis using:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\projects\\causalimpact\\causalimpact\\analysis.py:19: Warning: This code is still wip and not fully\n",
      "                tested yet\n",
      "  tested yet\"\"\"))\n"
     ]
    }
   ],
   "source": [
    "impact = CausalImpact(data, pre_period, post_period)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This initialises a `CausalImpact` object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "impact.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This instructs the package to assemble a structural time-series model, fit the model using MLE by default, and compute estimates \n",
    "of the causal effect. We can view the results in a dataframe as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "results = impact.model.fit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Plotting the results\n",
    "The easiest way of visualising the results is to use the `plot()` method of the `CausalImpact` object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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cp02bttx8823YbDafWoD/+utPnn32Kf744/eKCjcgmUwm3n9/SqnrSTInhBBCCFHLLFly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\n73UdIxSzcu7RUeLPP5yxo49l8LQ3AdB13S/qfu6S4eGhspUKbduuaWGRj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b6C4UMOm9i/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MExPjDA0VG6JvHOUyvdf8B4dc8RHSk5OU8927DWy1uM0SgBjji4B/YOb5uc5dDuWB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\naTHEqTEY5iRJktQ09rjJSZLQ873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AAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f25ecd0f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "impact.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default, the plot contains three panels. The first panel shows the data and a counterfactual prediction for the post-treatment period. The second panel shows the difference between observed data and counterfactual predictions. This is the *pointwise* causal effect, as estimated by the model. The third panel adds up the pointwise contributions from the second panel, resulting in a plot of the *cumulative* effect of the intervention.\n",
    "\n",
    "Remember, once again, that all of the above inferences depend critically on the assumption that the covariates were not themselves affected by the intervention. The model also assumes that the relationship between covariates and treated time series, as established during the pre-period, remains stable throughout the post-period.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Working with dates and times\n",
    "\n",
    "It is often more natural to feed a time-series object into `CausalImpact()` rather than a data frame. For example, we might create a `data` variable as follows:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>y</th>\n",
       "      <th>x1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-01-01</th>\n",
       "      <td>121.308920</td>\n",
       "      <td>101.463374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-02</th>\n",
       "      <td>120.563149</td>\n",
       "      <td>99.448868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-03</th>\n",
       "      <td>119.832495</td>\n",
       "      <td>99.524170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-04</th>\n",
       "      <td>119.433612</td>\n",
       "      <td>99.033362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-05</th>\n",
       "      <td>119.840664</td>\n",
       "      <td>100.779647</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     y          x1\n",
       "2014-01-01  121.308920  101.463374\n",
       "2014-01-02  120.563149   99.448868\n",
       "2014-01-03  119.832495   99.524170\n",
       "2014-01-04  119.433612   99.033362\n",
       "2014-01-05  119.840664  100.779647"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date_range = pd.date_range(start=\"2014-01-01\", periods=100)\n",
    "data.index = date_range\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now specify the pre_period and post_period in terms of time points rather than indices:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pre_period = [pd.to_datetime(date) for date in [\"2014-01-01\", \"2014-03-12\"]]\n",
    "post_period = [pd.to_datetime(date) for date in [\"2014-03-13\", \"2014-04-10\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a result, the x-axis of the plot shows time points instead of indices:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\projects\\causalimpact\\causalimpact\\analysis.py:19: Warning: This code is still wip and not fully\n",
      "                tested yet\n",
      "  tested yet\"\"\"))\n"
     ]
    }
   ],
   "source": [
    "impact = CausalImpact(data, pre_period, post_period)\n",
    "impact.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "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>response</th>\n",
       "      <th>cum_response</th>\n",
       "      <th>point_pred</th>\n",
       "      <th>point_pred_upper</th>\n",
       "      <th>point_pred_lower</th>\n",
       "      <th>cum_pred</th>\n",
       "      <th>cum_pred_lower</th>\n",
       "      <th>cum_pred_upper</th>\n",
       "      <th>point_effect</th>\n",
       "      <th>point_effect_lower</th>\n",
       "      <th>point_effect_upper</th>\n",
       "      <th>cum_effect</th>\n",
       "      <th>cum_effect_lower</th>\n",
       "      <th>cum_effect_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-01-01</th>\n",
       "      <td>121.308920</td>\n",
       "      <td>121.30892</td>\n",
       "      <td>121.994855</td>\n",
       "      <td>3069.636857</td>\n",
       "      <td>-2825.647146</td>\n",
       "      <td>121.994855</td>\n",
       "      <td>-2825.647146</td>\n",
       "      <td>3069.636857</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-02</th>\n",
       "      <td>120.563149</td>\n",
       "      <td>241.87207</td>\n",
       "      <td>118.618183</td>\n",
       "      <td>121.228648</td>\n",
       "      <td>116.007719</td>\n",
       "      <td>240.613039</td>\n",
       "      <td>-2709.639428</td>\n",
       "      <td>3190.865505</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              response  cum_response  point_pred  point_pred_upper  \\\n",
       "2014-01-01  121.308920     121.30892  121.994855       3069.636857   \n",
       "2014-01-02  120.563149     241.87207  118.618183        121.228648   \n",
       "\n",
       "            point_pred_lower    cum_pred  cum_pred_lower  cum_pred_upper  \\\n",
       "2014-01-01      -2825.647146  121.994855    -2825.647146     3069.636857   \n",
       "2014-01-02        116.007719  240.613039    -2709.639428     3190.865505   \n",
       "\n",
       "            point_effect  point_effect_lower  point_effect_upper  cum_effect  \\\n",
       "2014-01-01           0.0                 0.0                 0.0         0.0   \n",
       "2014-01-02           0.0                 0.0                 0.0         0.0   \n",
       "\n",
       "            cum_effect_lower  cum_effect_upper  \n",
       "2014-01-01               0.0               0.0  \n",
       "2014-01-02               0.0               0.0  "
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "impact.inferences.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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vv49w2WWdsNvtfPPN9yh1VonjSAJZCfUtgaxL5CIleEnZBjcp3+Am5Ru8qlu2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0tK2PH+AjTZ0dG+Nm3ayJtvTuXll1+LqbK2datwPI2vaor3gBDsH33uRc7fMAhyIvj8mBMwtu/I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\nP+PjI9i2TU9PgEgkNbmfLpUqkUo193nbtgOPpwun0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jbNb+fS3HY2zW/nasbcDg6GjSYN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\n3f8B3P6GNzNxzMP3u45sNks22+e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IDaQkSZIkaSA2kJIkSZKkgdhASpIkSZIGYgMpSZIk\nSRqIDaQkSZIkaSAzJzqB6S4i1gYuBrYAZgELMvOaiNgK+BEwAiwBjsnMlTVmK+CXmfmuxli7AJdn\n5mYt+5kDXAGsBzwKHJqZ/67r5gK3A9tm5gstsYcDRwIv1fyujYjNa94zgSHgiMzMRtypwL417rjM\nvGus46ox6wGXAW8BlgGfzczhiNgPOKWOdXFmXtjYV+u4bTk0j29N6XBtNwEuB9YB/gkcMjpeT9y0\nrm3Nq5P1HXCf07q+Xa1tRGwE/LXmBrAwM8/piZkBnA+8G3gROCwzl0bEjsA5dazFmXn6IHmO9fyq\nca8bt18OzeNbkzpc3zcCPwC2pLw+H9ucF87dztb2u8B76iabAE9n5o49Mc5dOl3fzYFLKe+XnwTm\ndf19lWcgJ95ngCcyc2dgH+C8uvzbwPy6fAj4BEBEHARcCczpHSQiNgNOANbus59TgCvqePdQntxE\nxF7AYmDjtqDaTHwR+BCwF3BWRMwCvgqcl5m7AmcCZzXitgc+DOwAHAB8f6zj6vF54L66/sfA/PqC\n8R1gzzrmETWvXq8bd4wcxktXa3sScEkd74HR8XrirG3R1fqOuU/rC3S3ttsDP8nMXet/5zRCPwms\nm5kfpMzzb9XlFwDzgJ2AHerjP2aeYz2/erSN2y+H8dTV+p4ILKnjHQ5EI86529HaZuZx9f3UHsAz\nlPr2cu4WnawvcDzw08zcBbgf+FwjrnNz1wZy4l0NnNzz+0v1/+8Dbq4/XwfsXn9+ilLgV0TEupTJ\nfvQY+9kJuL5lvJX15yf7xH0AuC0zX8zMZ4ClwHaUiffrus1MoPkpzE6UT61GMvMfwMz6qU3rcUXE\n4ohYp0+eWwNLM/OpzFwO3ArsHBHbRMT5ddu2cfvlMF66Wtvjgcvqp42bAf9q2d90ry10tL4D7NP6\ndrS2Nb/tI+LmiLg6It7ab3+Z+Qfg/RGxPjArM/+WmSPAIuCjEbFRRPxijDz7Pb92i4hT+o3blsMY\nj8+a0tX67gUsj4hFNf9FLftz7naztqOOpTx+9/Xbn3O3k/W9F9iwbrM+sKJlf52au17COsEy8zmA\niJgN/AyYX1cN1YkL5bT0BnX7a+v2vcOcB5ydmY80lvdan/KpVnO8G1rG6xf3SmxmPl7jAjib8slU\nM+6JZtwYx7VnHa8tz345PMCrLwBt4/bLYbjfwa5OHa7tSETMBP4ErAuc0RI3rWsL3a3vAPuc9vXt\ncG3/AtydmTdGxIHA94BPjxH3cl32bGOst2fmk8D+Y+TZr7Y3Ar+NiE3bxm3LISJmZuZLjJMO13cO\nsGFm7hURB1P+7T24EefcpZO1pTYER1KakFXFOXe7Vd+Hga9HxDzKpbentcR1au7aQE4C9VT6QuD8\nzLyiLl7Zs8ls4Ok+sW8Ddga2inLt8kYRcSVlgiyom32T8mIwG/jPWOPVMS8CtqI8aS6t278ul4j4\nCOV6+IMyX/v9x579NeNWdVy9caPr+43Vq23cQeLWqK7WNjNXANtExO6UyyJ6P8GztlUH67u8bZ+Z\neUDPdtaXTtb2aeBOYPR7NQt5/Yc/zcd1RsuysWrbm+eq4vqtf0Mzh/F8Azqqo/V9ArimLvsV5TLC\nXs5dOltbKGeBfl/PXDU5d6uO1veHlPtJLIqIfSnvq/bt2a5zc9cGcoJFxMaU66m/kJm/6Vl1T0Ts\nmpm/o1znfVNbfGY+Ss/3ICLisZ43g7v2LN8b+BjlS7P7ALf0yykzD+uJ2wT4Wj3lP4tyanxJbR7P\nAfbOzL+3DHMb8I2IOBvYlPJC83hErOq4bqt53tWT54PAO6PcIOI5YBfKJ6+92sZd2pZDv+Ne3Tpc\n2/OBqzPzJsonUCsbw0z72kJn63tXZvbb56hpX9+O1nYJcAnwc+AqyiVndzeGuQ3YD7gqyk0y7svM\nZyNieUS8A3iIcpnk6S1xzTzv6pPDaL79xt20mUO/Y15TOlzfW+t4d1Pm0v2NYZy73a0tlAbyuj7D\nOHfpdH2f4tWzgo/y6uWsozo3d20gJ96XKU+kkyNi9LrufSjfMbwwyiUND1JO1f8/FgCXRLk71OOU\nL0evUmY+FhHnUp6UM4CvZOYLUe4Ytk4ds26aR/bE3R0RtwB31Lhj6qrW44qIxcDHKXeYuyQibqWc\nLZmXmSsi4kuU6/BnUO4o9UhEbEN5ETm6bdzMfLlPDuOlq7U9F7ggIk6hNI9HN+KsbdHJ+g4QZ307\nWtuIOAm4OCKOBp4HDmuELgT2iIjbKTdOOLQuP4py5+W1KN+BubO++bgoM/dvyzMzn++Tw27ATpl5\nRp9x/9gnh/HU1fqeCVwUEXdQvkN1cCPOudvR2tbVQTkz1ca5W3SyvhFxLHBeRKxFeeyOacR1bu4O\njYyMjLVekiRJkiTAu7BKkiRJkgZkAylJkiRJGogNpCRJkiRpIDaQkiRJkqSB2EBKkiRJkgZiAylJ\nkiRJGogNpCRJkiRpIDMnOgFJkiaTiDgQOLH+uiXwDPBk/f2kzLx+QhKTJGkSGBoZGZnoHCRJmpQi\n4s/ACZl5w0TnIknSZOAlrJIktYiIWcDWwL0TnYskSZOFDaQkSe22BR7LzOGJTkSSpMnCBlKSpHbv\nBe6Z6CQkSZpMbCAlSWpnAylJUoMNpCRJ7WwgJUlqsIGUJKkhImYA2+ENdCRJeg3/jIckSZIkaSCe\ngZQkSZIkDcQGUpIkSZI0EBtISZIkSdJAbCAlSZIkSQOxgZQkSZIkDcQGUpIkSZI0EBtISZIkSdJA\n/gvUFKyi+OKjnQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f25f299080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "impact.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Printing a summary table\n",
    "\n",
    "To obtain a numerical summary of the analysis we use: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                       Average     Cumulative\n",
      "Actual                     130           3784\n",
      "Predicted                  120           3484\n",
      "95% CI              [118, 122]   [3430, 3538]\n",
      "                                             \n",
      "Absolute Effect             10            300\n",
      "95% CI                 [12, 8]     [354, 246]\n",
      "                                             \n",
      "Relative Effect           8.6%           8.6%\n",
      "95% CI           [10.2%, 7.1%]  [10.2%, 7.1%]\n"
     ]
    }
   ],
   "source": [
    "impact.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The **Average** column talks about the average (across time) during the post-intervention period (in the example: time points 71 through 100). The **Cumulative** column sums up individual time points, which is a useful perspective if the response variable represents a flow quantity (such as queries, clicks, visits, installs, sales, or revenue) rather than a stock quantity (such as number of users or stock price).\n",
    "\n",
    "In the example, the estimated average causal effect of treatment was 11 (rounded to a whole number; for full precision see `impact$summary`). This is because we observed an average value of 99 but would have expected an average value of only 89. The 95% posterior interval of the average effect is [9.8, 11]. Since this excludes 0, we (correctly) conclude that the intervention had a causal effect on the response variable. Since we generated the data ourselves, we know that we injected a true effect of 10, and so the model accurately recovered ground truth. One reason for this is that we ensured, by design, that the covariate `x1` was not itself affected by the intervention. In practice, we must always reason whether this assumption is justified.\n",
    "\n",
    "For additional guidance about the correct interpretation of the summary table, the package provides a verbal interpretation, which we can print using:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " During the post-intervention period, the response variable had an average value of approx. 130.  By contrast, in  the\n",
      "absence of an intervention, we would have expected an average response of 120. The 95% interval of this counterfactual\n",
      "prediction is [118, 122]. Subtracting this prediction from the observed response yields an estimate of the causal effect\n",
      "the intervention had on the response variable. This effect is 10 with a 95% interval of [12, 8]. For a discussion of the\n",
      "significance of this effect, see below.\n",
      "\n",
      "\n",
      " Summing up the individual data points during the post-intervention period (which can only sometimes be meaningfully\n",
      "interpreted), the response variable had an overall value of 3784.  By contrast, had  the intervention not taken place,\n",
      "we would have expected a sum of 3784. The 95% interval of this prediction is [3430, 3538]\n",
      "\n",
      "\n",
      " The above results are given in terms of absolute numbers. In relative terms, the response variable showed  an increase\n",
      "of  8.6%. The 95% interval of this percentage is [10.2%, 7.1%]\n",
      "\n",
      "\n",
      " This means that the positive effect observed during the intervention period is statistically significant and unlikely\n",
      "to be due to random fluctuations. It should be noted, however, that the question of whether this increase also bears\n",
      "substantive significance can only be answered by comparing the absolute effect 10 to the original goal of the underlying\n",
      "intervention.\n"
     ]
    }
   ],
   "source": [
    "impact.summary(\"report\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7. Adjusting the model\n",
    "\n",
    "So far, we've simply let the package decide how to construct a time-series model for the available data. However, there are several options that allow us to gain a little more control over this process. These options are passed into `model_args` as individual list elements, for example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\projects\\causalimpact\\causalimpact\\analysis.py:19: Warning: This code is still wip and not fully\n",
      "                tested yet\n",
      "  tested yet\"\"\"))\n"
     ]
    }
   ],
   "source": [
    "impact = CausalImpact(data, pre_period, post_period, model_args={\"niter\":5000, \"nseasons\":7})\n",
    "impact.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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J+4au6rZt584Xc/ToEX78cZfXY/F8lZyczDXXdCEzM9Pn5T4cDgfnn98Wo9HI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qmK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\nC2zaBNu3s+PQ58HkuM8NaHdw7u659sTcjru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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f25f8d8d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "impact.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Available options\n",
    "\n",
    "* `niter` Number of MCMC samples to draw. More samples lead to more accurate inferences. Defaults to __1000__.\n",
    "\n",
    "* `standardize_data` Whether to standardize all columns of the data before fitting the model. This is equivalent to an empirical Bayes approach to setting the priors. It ensures that results are invariant to linear transformations of the data. Defaults to __TRUE__.\n",
    "\n",
    "* `prior_level_sd` Prior standard deviation of the Gaussian random walk of the local level. Expressed in terms of data standard deviations. Defaults to __0.01__, a typical choice for  well-behaved and stable datasets with low residual volatility after regressing out known predictors (e.g., web searches or sales in high quantities). When in doubt, a safer option is to use __0.1__, as validated on synthetic data, although this may sometimes give rise to unrealistically wide prediction intervals.\n",
    "\n",
    "* `nseasons` Period of the seasonal components. In order to include a seasonal component, set this to a whole number greater than 1. For example, if the data represent daily observations, use 7 for a day-of-week component. This interface currently only supports up to one seasonal component. To specify multiple seasonal components, use bsts to specify the model directly, then pass the fitted model in as bsts.model. Defaults to __1__, which means no seasonal component is used.\n",
    "\n",
    "* `season_duration` Duration of each season, i.e., number of data points each season spans. Defaults to __1__. For example, to add a day-of-week component to data with daily granularity, use __model_args = list(nseasons = 7, season_duration = 1)__. To add a day-of-week component to data with hourly granularity, set __model_args = list(nseasons = 7, season_duration = 24)__.\n",
    "\n",
    "* `dynamic_regression` Whether to include time-varying regression coefficients. In combination with a time-varying local trend or even a time-varying local level, this often leads to overspecification, in which case a static regression is safer. Defaults to __FALSE__."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 8. Using a custom model\n",
    "\n",
    "Instead of using the default model constructed by the CausalImpact package, we can use the bsts package to specify our own model. This provides the greatest degree of flexibility.\n",
    "\n",
    "Before constructing a custom model, we set the observed data in the post-treatment period to NA, reflecting the fact that the counterfactual response is unobserved after the intervention. We keep a copy of the actual observed response in the variable `post_period_response`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "post_period = [70,100]\n",
    "post_period_response = y[post_period[0]:post_period[1]].copy()\n",
    "y[post_period[0]:post_period[1]] = np.nan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We next set up and estimate a time series model using the statsmodels package. Here is a simple example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\projects\\causalimpact\\causalimpact\\analysis.py:19: Warning: This code is still wip and not fully\n",
      "                tested yet\n",
      "  tested yet\"\"\"))\n"
     ]
    },
    {
     "data": {
      "image/png": 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DzzzzHAALFsx16Ng7dmxj1Khn+fHH5YwePZKUlJR8idkVzZpl6VUbMSL7moySrAkhhBBC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a+fjY8++hBGoxEzZx5a0QXrXq+9Yvumwni9E/Dggw/iK1/5CmbMmIHjjuOFcTqeq5V33HEL8NRT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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f25f438240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statsmodels.tsa.statespace.structural import UnobservedComponents\n",
    "ucm_model = UnobservedComponents(endog=y, level=\"llevel\")\n",
    "impact = CausalImpact(ucm_model=ucm_model, post_period_response=post_period_response)\n",
    "impact.run()\n",
    "#TODO\n",
    "impact.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>response</th>\n",
       "      <th>cum_response</th>\n",
       "      <th>point_pred</th>\n",
       "      <th>point_pred_upper</th>\n",
       "      <th>point_pred_lower</th>\n",
       "      <th>cum_pred</th>\n",
       "      <th>cum_pred_lower</th>\n",
       "      <th>cum_pred_upper</th>\n",
       "      <th>point_effect</th>\n",
       "      <th>point_effect_lower</th>\n",
       "      <th>point_effect_upper</th>\n",
       "      <th>cum_effect</th>\n",
       "      <th>cum_effect_lower</th>\n",
       "      <th>cum_effect_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>121.308920</td>\n",
       "      <td>121.308920</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1959.966134</td>\n",
       "      <td>-1959.966134</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1959.966134</td>\n",
       "      <td>1959.966134</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>120.563149</td>\n",
       "      <td>241.872070</td>\n",
       "      <td>121.308654</td>\n",
       "      <td>125.414913</td>\n",
       "      <td>117.202395</td>\n",
       "      <td>121.308654</td>\n",
       "      <td>-1842.763739</td>\n",
       "      <td>2085.381048</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>119.832495</td>\n",
       "      <td>361.704565</td>\n",
       "      <td>120.935753</td>\n",
       "      <td>124.492354</td>\n",
       "      <td>117.379151</td>\n",
       "      <td>242.244407</td>\n",
       "      <td>-1725.384588</td>\n",
       "      <td>2209.873402</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>119.433612</td>\n",
       "      <td>481.138177</td>\n",
       "      <td>120.567508</td>\n",
       "      <td>123.921153</td>\n",
       "      <td>117.213863</td>\n",
       "      <td>362.811915</td>\n",
       "      <td>-1608.170725</td>\n",
       "      <td>2333.794555</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>119.840664</td>\n",
       "      <td>600.978841</td>\n",
       "      <td>120.283238</td>\n",
       "      <td>123.530825</td>\n",
       "      <td>117.035651</td>\n",
       "      <td>483.095153</td>\n",
       "      <td>-1491.135074</td>\n",
       "      <td>2457.325380</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>117.681232</td>\n",
       "      <td>718.660074</td>\n",
       "      <td>120.194297</td>\n",
       "      <td>123.376694</td>\n",
       "      <td>117.011900</td>\n",
       "      <td>603.289450</td>\n",
       "      <td>-1374.123174</td>\n",
       "      <td>2580.702074</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>122.626839</td>\n",
       "      <td>841.286913</td>\n",
       "      <td>119.772375</td>\n",
       "      <td>122.910679</td>\n",
       "      <td>116.634072</td>\n",
       "      <td>723.061826</td>\n",
       "      <td>-1257.489102</td>\n",
       "      <td>2703.612753</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>118.223373</td>\n",
       "      <td>959.510286</td>\n",
       "      <td>120.184402</td>\n",
       "      <td>123.290930</td>\n",
       "      <td>117.077875</td>\n",
       "      <td>843.246228</td>\n",
       "      <td>-1140.411227</td>\n",
       "      <td>2826.903683</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>120.078689</td>\n",
       "      <td>1079.588975</td>\n",
       "      <td>119.935840</td>\n",
       "      <td>123.018411</td>\n",
       "      <td>116.853269</td>\n",
       "      <td>963.182068</td>\n",
       "      <td>-1023.557957</td>\n",
       "      <td>2949.922094</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>119.763025</td>\n",
       "      <td>1199.352000</td>\n",
       "      <td>119.952000</td>\n",
       "      <td>123.015889</td>\n",
       "      <td>116.888111</td>\n",
       "      <td>1083.134069</td>\n",
       "      <td>-906.669846</td>\n",
       "      <td>3072.937983</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>120.207540</td>\n",
       "      <td>1319.559540</td>\n",
       "      <td>119.932672</td>\n",
       "      <td>122.981605</td>\n",
       "      <td>116.883740</td>\n",
       "      <td>1203.066741</td>\n",
       "      <td>-789.786106</td>\n",
       "      <td>3195.919588</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>118.087980</td>\n",
       "      <td>1437.647520</td>\n",
       "      <td>119.958358</td>\n",
       "      <td>122.995064</td>\n",
       "      <td>116.921652</td>\n",
       "      <td>1323.025099</td>\n",
       "      <td>-672.864454</td>\n",
       "      <td>3318.914652</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>120.497602</td>\n",
       "      <td>1558.145122</td>\n",
       "      <td>119.797257</td>\n",
       "      <td>122.823797</td>\n",
       "      <td>116.770717</td>\n",
       "      <td>1442.822356</td>\n",
       "      <td>-556.093737</td>\n",
       "      <td>3441.738449</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>118.725290</td>\n",
       "      <td>1676.870412</td>\n",
       "      <td>119.853273</td>\n",
       "      <td>122.871239</td>\n",
       "      <td>116.835307</td>\n",
       "      <td>1562.675629</td>\n",
       "      <td>-439.258430</td>\n",
       "      <td>3564.609688</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>121.576243</td>\n",
       "      <td>1798.446654</td>\n",
       "      <td>119.768958</td>\n",
       "      <td>122.779606</td>\n",
       "      <td>116.758310</td>\n",
       "      <td>1682.444587</td>\n",
       "      <td>-322.500120</td>\n",
       "      <td>3687.389294</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>117.498645</td>\n",
       "      <td>1915.945299</td>\n",
       "      <td>119.895910</td>\n",
       "      <td>122.900248</td>\n",
       "      <td>116.891572</td>\n",
       "      <td>1802.340497</td>\n",
       "      <td>-205.608548</td>\n",
       "      <td>3810.289543</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>119.774896</td>\n",
       "      <td>2035.720195</td>\n",
       "      <td>119.736887</td>\n",
       "      <td>122.735738</td>\n",
       "      <td>116.738037</td>\n",
       "      <td>1922.077385</td>\n",
       "      <td>-88.870511</td>\n",
       "      <td>3933.025280</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>117.435192</td>\n",
       "      <td>2153.155387</td>\n",
       "      <td>119.739279</td>\n",
       "      <td>122.733319</td>\n",
       "      <td>116.745238</td>\n",
       "      <td>2041.816663</td>\n",
       "      <td>27.874727</td>\n",
       "      <td>4055.758599</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>121.167054</td>\n",
       "      <td>2274.322441</td>\n",
       "      <td>119.601260</td>\n",
       "      <td>122.591057</td>\n",
       "      <td>116.611463</td>\n",
       "      <td>2161.417923</td>\n",
       "      <td>144.486190</td>\n",
       "      <td>4178.349656</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>121.038971</td>\n",
       "      <td>2395.361412</td>\n",
       "      <td>119.690872</td>\n",
       "      <td>122.676903</td>\n",
       "      <td>116.704841</td>\n",
       "      <td>2281.108795</td>\n",
       "      <td>261.191032</td>\n",
       "      <td>4301.026559</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>118.785524</td>\n",
       "      <td>2514.146936</td>\n",
       "      <td>119.764817</td>\n",
       "      <td>122.747488</td>\n",
       "      <td>116.782146</td>\n",
       "      <td>2400.873612</td>\n",
       "      <td>377.973178</td>\n",
       "      <td>4423.774047</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>120.462378</td>\n",
       "      <td>2634.609314</td>\n",
       "      <td>119.713188</td>\n",
       "      <td>122.692847</td>\n",
       "      <td>116.733529</td>\n",
       "      <td>2520.586800</td>\n",
       "      <td>494.706706</td>\n",
       "      <td>4546.466894</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>122.248449</td>\n",
       "      <td>2756.857762</td>\n",
       "      <td>119.751251</td>\n",
       "      <td>122.728200</td>\n",
       "      <td>116.774301</td>\n",
       "      <td>2640.338051</td>\n",
       "      <td>611.481008</td>\n",
       "      <td>4669.195094</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>122.510339</td>\n",
       "      <td>2879.368101</td>\n",
       "      <td>119.873803</td>\n",
       "      <td>122.848304</td>\n",
       "      <td>116.899302</td>\n",
       "      <td>2760.211854</td>\n",
       "      <td>728.380310</td>\n",
       "      <td>4792.043397</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>119.115916</td>\n",
       "      <td>2998.484018</td>\n",
       "      <td>119.999064</td>\n",
       "      <td>122.971345</td>\n",
       "      <td>117.026783</td>\n",
       "      <td>2880.210918</td>\n",
       "      <td>845.407093</td>\n",
       "      <td>4915.014743</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>120.496999</td>\n",
       "      <td>3118.981017</td>\n",
       "      <td>119.958363</td>\n",
       "      <td>122.928626</td>\n",
       "      <td>116.988099</td>\n",
       "      <td>3000.169280</td>\n",
       "      <td>962.395192</td>\n",
       "      <td>5037.943369</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>121.494796</td>\n",
       "      <td>3240.475813</td>\n",
       "      <td>119.982488</td>\n",
       "      <td>122.950912</td>\n",
       "      <td>117.014065</td>\n",
       "      <td>3120.151769</td>\n",
       "      <td>1079.409257</td>\n",
       "      <td>5160.894280</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>119.326369</td>\n",
       "      <td>3359.802182</td>\n",
       "      <td>120.048433</td>\n",
       "      <td>123.015175</td>\n",
       "      <td>117.081692</td>\n",
       "      <td>3240.200202</td>\n",
       "      <td>1196.490949</td>\n",
       "      <td>5283.909455</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>118.511123</td>\n",
       "      <td>3478.313305</td>\n",
       "      <td>120.017731</td>\n",
       "      <td>122.982931</td>\n",
       "      <td>117.052530</td>\n",
       "      <td>3360.217933</td>\n",
       "      <td>1313.543479</td>\n",
       "      <td>5406.892386</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>121.436703</td>\n",
       "      <td>3599.750008</td>\n",
       "      <td>119.955168</td>\n",
       "      <td>122.918953</td>\n",
       "      <td>116.991382</td>\n",
       "      <td>3480.173101</td>\n",
       "      <td>1430.534862</td>\n",
       "      <td>5529.811340</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>117.791879</td>\n",
       "      <td>8527.215896</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.193394</td>\n",
       "      <td>117.301427</td>\n",
       "      <td>8401.735165</td>\n",
       "      <td>6231.105043</td>\n",
       "      <td>10572.365286</td>\n",
       "      <td>-2.455531</td>\n",
       "      <td>0.490452</td>\n",
       "      <td>-5.401515</td>\n",
       "      <td>-2.455531</td>\n",
       "      <td>0.490452</td>\n",
       "      <td>-5.401515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>130.356118</td>\n",
       "      <td>8657.572014</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.194543</td>\n",
       "      <td>117.300278</td>\n",
       "      <td>8521.982575</td>\n",
       "      <td>6348.405321</td>\n",
       "      <td>10695.559829</td>\n",
       "      <td>10.108708</td>\n",
       "      <td>13.055840</td>\n",
       "      <td>7.161575</td>\n",
       "      <td>7.653177</td>\n",
       "      <td>13.546293</td>\n",
       "      <td>1.760061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>132.701339</td>\n",
       "      <td>8790.273353</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.195692</td>\n",
       "      <td>117.299129</td>\n",
       "      <td>8642.229985</td>\n",
       "      <td>6465.704450</td>\n",
       "      <td>10818.755521</td>\n",
       "      <td>12.453928</td>\n",
       "      <td>15.402210</td>\n",
       "      <td>9.505647</td>\n",
       "      <td>20.107105</td>\n",
       "      <td>28.948502</td>\n",
       "      <td>11.265708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>130.698575</td>\n",
       "      <td>8920.971928</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.196840</td>\n",
       "      <td>117.297981</td>\n",
       "      <td>8762.477396</td>\n",
       "      <td>6583.002431</td>\n",
       "      <td>10941.952361</td>\n",
       "      <td>10.451164</td>\n",
       "      <td>13.400594</td>\n",
       "      <td>7.501735</td>\n",
       "      <td>30.558269</td>\n",
       "      <td>42.349096</td>\n",
       "      <td>18.767442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>130.384896</td>\n",
       "      <td>9051.356824</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.197988</td>\n",
       "      <td>117.296833</td>\n",
       "      <td>8882.724806</td>\n",
       "      <td>6700.299264</td>\n",
       "      <td>11065.150349</td>\n",
       "      <td>10.137485</td>\n",
       "      <td>13.088063</td>\n",
       "      <td>7.186908</td>\n",
       "      <td>40.695755</td>\n",
       "      <td>55.437159</td>\n",
       "      <td>25.954350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>127.587522</td>\n",
       "      <td>9178.944346</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.199135</td>\n",
       "      <td>117.295686</td>\n",
       "      <td>9002.972217</td>\n",
       "      <td>6817.594949</td>\n",
       "      <td>11188.349485</td>\n",
       "      <td>7.340112</td>\n",
       "      <td>10.291837</td>\n",
       "      <td>4.388387</td>\n",
       "      <td>48.035867</td>\n",
       "      <td>65.728996</td>\n",
       "      <td>30.342737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>131.000426</td>\n",
       "      <td>9309.944772</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.200282</td>\n",
       "      <td>117.294539</td>\n",
       "      <td>9123.219627</td>\n",
       "      <td>6934.889488</td>\n",
       "      <td>11311.549767</td>\n",
       "      <td>10.753015</td>\n",
       "      <td>13.705887</td>\n",
       "      <td>7.800143</td>\n",
       "      <td>58.788882</td>\n",
       "      <td>79.434883</td>\n",
       "      <td>38.142881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>130.607800</td>\n",
       "      <td>9440.552571</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.201429</td>\n",
       "      <td>117.293392</td>\n",
       "      <td>9243.467038</td>\n",
       "      <td>7052.182880</td>\n",
       "      <td>11434.751196</td>\n",
       "      <td>10.360389</td>\n",
       "      <td>13.314408</td>\n",
       "      <td>7.406371</td>\n",
       "      <td>69.149271</td>\n",
       "      <td>92.749291</td>\n",
       "      <td>45.549252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>130.928821</td>\n",
       "      <td>9571.481392</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.202575</td>\n",
       "      <td>117.292246</td>\n",
       "      <td>9363.714448</td>\n",
       "      <td>7169.475126</td>\n",
       "      <td>11557.953771</td>\n",
       "      <td>10.681410</td>\n",
       "      <td>13.636575</td>\n",
       "      <td>7.726246</td>\n",
       "      <td>79.830682</td>\n",
       "      <td>106.385865</td>\n",
       "      <td>53.275498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>130.503994</td>\n",
       "      <td>9701.985387</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.203721</td>\n",
       "      <td>117.291100</td>\n",
       "      <td>9483.961859</td>\n",
       "      <td>7286.766227</td>\n",
       "      <td>11681.157491</td>\n",
       "      <td>10.256584</td>\n",
       "      <td>13.212894</td>\n",
       "      <td>7.300274</td>\n",
       "      <td>90.087265</td>\n",
       "      <td>119.598759</td>\n",
       "      <td>60.575772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>128.487086</td>\n",
       "      <td>9830.472473</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.204866</td>\n",
       "      <td>117.289955</td>\n",
       "      <td>9604.209269</td>\n",
       "      <td>7404.056182</td>\n",
       "      <td>11804.362357</td>\n",
       "      <td>8.239676</td>\n",
       "      <td>11.197131</td>\n",
       "      <td>5.282221</td>\n",
       "      <td>98.326941</td>\n",
       "      <td>130.795890</td>\n",
       "      <td>65.857992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>130.096512</td>\n",
       "      <td>9960.568985</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.206010</td>\n",
       "      <td>117.288811</td>\n",
       "      <td>9724.456680</td>\n",
       "      <td>7521.344993</td>\n",
       "      <td>11927.568367</td>\n",
       "      <td>9.849101</td>\n",
       "      <td>12.807701</td>\n",
       "      <td>6.890502</td>\n",
       "      <td>108.176043</td>\n",
       "      <td>143.603592</td>\n",
       "      <td>72.748494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>130.704873</td>\n",
       "      <td>10091.273858</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.207155</td>\n",
       "      <td>117.287666</td>\n",
       "      <td>9844.704090</td>\n",
       "      <td>7638.632659</td>\n",
       "      <td>12050.775522</td>\n",
       "      <td>10.457462</td>\n",
       "      <td>13.417207</td>\n",
       "      <td>7.497718</td>\n",
       "      <td>118.633505</td>\n",
       "      <td>157.020798</td>\n",
       "      <td>80.246212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>131.736525</td>\n",
       "      <td>10223.010383</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.208299</td>\n",
       "      <td>117.286522</td>\n",
       "      <td>9964.951501</td>\n",
       "      <td>7755.919181</td>\n",
       "      <td>12173.983820</td>\n",
       "      <td>11.489114</td>\n",
       "      <td>14.450003</td>\n",
       "      <td>8.528226</td>\n",
       "      <td>130.122620</td>\n",
       "      <td>171.470801</td>\n",
       "      <td>88.774438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>130.103931</td>\n",
       "      <td>10353.114314</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.209442</td>\n",
       "      <td>117.285379</td>\n",
       "      <td>10085.198911</td>\n",
       "      <td>7873.204560</td>\n",
       "      <td>12297.193262</td>\n",
       "      <td>9.856521</td>\n",
       "      <td>12.818552</td>\n",
       "      <td>6.894489</td>\n",
       "      <td>139.979140</td>\n",
       "      <td>184.289353</td>\n",
       "      <td>95.668927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>129.511296</td>\n",
       "      <td>10482.625610</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.210585</td>\n",
       "      <td>117.284236</td>\n",
       "      <td>10205.446322</td>\n",
       "      <td>7990.488796</td>\n",
       "      <td>12420.403847</td>\n",
       "      <td>9.263885</td>\n",
       "      <td>12.227060</td>\n",
       "      <td>6.300711</td>\n",
       "      <td>149.243026</td>\n",
       "      <td>196.516413</td>\n",
       "      <td>101.969638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>129.837721</td>\n",
       "      <td>10612.463331</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.211727</td>\n",
       "      <td>117.283093</td>\n",
       "      <td>10325.693732</td>\n",
       "      <td>8107.771890</td>\n",
       "      <td>12543.615575</td>\n",
       "      <td>9.590310</td>\n",
       "      <td>12.554627</td>\n",
       "      <td>6.625993</td>\n",
       "      <td>158.833336</td>\n",
       "      <td>209.071040</td>\n",
       "      <td>108.595632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>130.648914</td>\n",
       "      <td>10743.112245</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.212870</td>\n",
       "      <td>117.281951</td>\n",
       "      <td>10445.941143</td>\n",
       "      <td>8225.053841</td>\n",
       "      <td>12666.828444</td>\n",
       "      <td>10.401504</td>\n",
       "      <td>13.366963</td>\n",
       "      <td>7.436045</td>\n",
       "      <td>169.234840</td>\n",
       "      <td>222.438003</td>\n",
       "      <td>116.031676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>130.412364</td>\n",
       "      <td>10873.524608</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.214011</td>\n",
       "      <td>117.280810</td>\n",
       "      <td>10566.188553</td>\n",
       "      <td>8342.334651</td>\n",
       "      <td>12790.042456</td>\n",
       "      <td>10.164953</td>\n",
       "      <td>13.131554</td>\n",
       "      <td>7.198353</td>\n",
       "      <td>179.399793</td>\n",
       "      <td>235.569557</td>\n",
       "      <td>123.230029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>131.147951</td>\n",
       "      <td>11004.672559</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.215152</td>\n",
       "      <td>117.279669</td>\n",
       "      <td>10686.435964</td>\n",
       "      <td>8459.614319</td>\n",
       "      <td>12913.257608</td>\n",
       "      <td>10.900540</td>\n",
       "      <td>13.868282</td>\n",
       "      <td>7.932799</td>\n",
       "      <td>190.300333</td>\n",
       "      <td>249.437839</td>\n",
       "      <td>131.162827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>132.456466</td>\n",
       "      <td>11137.129025</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.216293</td>\n",
       "      <td>117.278528</td>\n",
       "      <td>10806.683374</td>\n",
       "      <td>8576.892847</td>\n",
       "      <td>13036.473901</td>\n",
       "      <td>12.209056</td>\n",
       "      <td>15.177938</td>\n",
       "      <td>9.240173</td>\n",
       "      <td>202.509389</td>\n",
       "      <td>264.615778</td>\n",
       "      <td>140.403000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>130.569662</td>\n",
       "      <td>11267.698687</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.217434</td>\n",
       "      <td>117.277387</td>\n",
       "      <td>10926.930785</td>\n",
       "      <td>8694.170235</td>\n",
       "      <td>13159.691335</td>\n",
       "      <td>10.322251</td>\n",
       "      <td>13.292274</td>\n",
       "      <td>7.352228</td>\n",
       "      <td>212.831640</td>\n",
       "      <td>277.908052</td>\n",
       "      <td>147.755229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>131.498945</td>\n",
       "      <td>11399.197633</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.218573</td>\n",
       "      <td>117.276248</td>\n",
       "      <td>11047.178195</td>\n",
       "      <td>8811.446482</td>\n",
       "      <td>13282.909908</td>\n",
       "      <td>11.251535</td>\n",
       "      <td>14.222698</td>\n",
       "      <td>8.280372</td>\n",
       "      <td>224.083175</td>\n",
       "      <td>292.130750</td>\n",
       "      <td>156.035600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>130.420537</td>\n",
       "      <td>11529.618170</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.219713</td>\n",
       "      <td>117.275108</td>\n",
       "      <td>11167.425606</td>\n",
       "      <td>8928.721590</td>\n",
       "      <td>13406.129621</td>\n",
       "      <td>10.173127</td>\n",
       "      <td>13.145429</td>\n",
       "      <td>7.200824</td>\n",
       "      <td>234.256302</td>\n",
       "      <td>305.276179</td>\n",
       "      <td>163.236425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>131.116882</td>\n",
       "      <td>11660.735051</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.220852</td>\n",
       "      <td>117.273969</td>\n",
       "      <td>11287.673016</td>\n",
       "      <td>9045.995559</td>\n",
       "      <td>13529.350473</td>\n",
       "      <td>10.869471</td>\n",
       "      <td>13.842912</td>\n",
       "      <td>7.896030</td>\n",
       "      <td>245.125773</td>\n",
       "      <td>319.119092</td>\n",
       "      <td>171.132454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>128.456173</td>\n",
       "      <td>11789.191224</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.221990</td>\n",
       "      <td>117.272830</td>\n",
       "      <td>11407.920427</td>\n",
       "      <td>9163.268390</td>\n",
       "      <td>13652.572464</td>\n",
       "      <td>8.208762</td>\n",
       "      <td>11.183342</td>\n",
       "      <td>5.234182</td>\n",
       "      <td>253.334535</td>\n",
       "      <td>330.302434</td>\n",
       "      <td>176.366636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>130.230586</td>\n",
       "      <td>11919.421810</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.223129</td>\n",
       "      <td>117.271692</td>\n",
       "      <td>11528.167837</td>\n",
       "      <td>9280.540082</td>\n",
       "      <td>13775.795592</td>\n",
       "      <td>9.983175</td>\n",
       "      <td>12.958893</td>\n",
       "      <td>7.007457</td>\n",
       "      <td>263.317710</td>\n",
       "      <td>343.261327</td>\n",
       "      <td>183.374093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>130.467414</td>\n",
       "      <td>12049.889223</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.224266</td>\n",
       "      <td>117.270555</td>\n",
       "      <td>11648.415248</td>\n",
       "      <td>9397.810637</td>\n",
       "      <td>13899.019859</td>\n",
       "      <td>10.220003</td>\n",
       "      <td>13.196859</td>\n",
       "      <td>7.243148</td>\n",
       "      <td>273.537714</td>\n",
       "      <td>356.458186</td>\n",
       "      <td>190.617241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>130.140680</td>\n",
       "      <td>12180.029904</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.225404</td>\n",
       "      <td>117.269417</td>\n",
       "      <td>11768.662658</td>\n",
       "      <td>9515.080054</td>\n",
       "      <td>14022.245262</td>\n",
       "      <td>9.893270</td>\n",
       "      <td>12.871263</td>\n",
       "      <td>6.915277</td>\n",
       "      <td>283.430984</td>\n",
       "      <td>369.329449</td>\n",
       "      <td>197.532518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>131.799071</td>\n",
       "      <td>12311.828975</td>\n",
       "      <td>120.247410</td>\n",
       "      <td>123.226540</td>\n",
       "      <td>117.268280</td>\n",
       "      <td>11888.910069</td>\n",
       "      <td>9632.348334</td>\n",
       "      <td>14145.471803</td>\n",
       "      <td>11.551661</td>\n",
       "      <td>14.530791</td>\n",
       "      <td>8.572531</td>\n",
       "      <td>294.982644</td>\n",
       "      <td>383.860240</td>\n",
       "      <td>206.105049</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      response  cum_response  point_pred  point_pred_upper  point_pred_lower  \\\n",
       "0   121.308920    121.308920    0.000000       1959.966134      -1959.966134   \n",
       "1   120.563149    241.872070  121.308654        125.414913        117.202395   \n",
       "2   119.832495    361.704565  120.935753        124.492354        117.379151   \n",
       "3   119.433612    481.138177  120.567508        123.921153        117.213863   \n",
       "4   119.840664    600.978841  120.283238        123.530825        117.035651   \n",
       "5   117.681232    718.660074  120.194297        123.376694        117.011900   \n",
       "6   122.626839    841.286913  119.772375        122.910679        116.634072   \n",
       "7   118.223373    959.510286  120.184402        123.290930        117.077875   \n",
       "8   120.078689   1079.588975  119.935840        123.018411        116.853269   \n",
       "9   119.763025   1199.352000  119.952000        123.015889        116.888111   \n",
       "10  120.207540   1319.559540  119.932672        122.981605        116.883740   \n",
       "11  118.087980   1437.647520  119.958358        122.995064        116.921652   \n",
       "12  120.497602   1558.145122  119.797257        122.823797        116.770717   \n",
       "13  118.725290   1676.870412  119.853273        122.871239        116.835307   \n",
       "14  121.576243   1798.446654  119.768958        122.779606        116.758310   \n",
       "15  117.498645   1915.945299  119.895910        122.900248        116.891572   \n",
       "16  119.774896   2035.720195  119.736887        122.735738        116.738037   \n",
       "17  117.435192   2153.155387  119.739279        122.733319        116.745238   \n",
       "18  121.167054   2274.322441  119.601260        122.591057        116.611463   \n",
       "19  121.038971   2395.361412  119.690872        122.676903        116.704841   \n",
       "20  118.785524   2514.146936  119.764817        122.747488        116.782146   \n",
       "21  120.462378   2634.609314  119.713188        122.692847        116.733529   \n",
       "22  122.248449   2756.857762  119.751251        122.728200        116.774301   \n",
       "23  122.510339   2879.368101  119.873803        122.848304        116.899302   \n",
       "24  119.115916   2998.484018  119.999064        122.971345        117.026783   \n",
       "25  120.496999   3118.981017  119.958363        122.928626        116.988099   \n",
       "26  121.494796   3240.475813  119.982488        122.950912        117.014065   \n",
       "27  119.326369   3359.802182  120.048433        123.015175        117.081692   \n",
       "28  118.511123   3478.313305  120.017731        122.982931        117.052530   \n",
       "29  121.436703   3599.750008  119.955168        122.918953        116.991382   \n",
       "..         ...           ...         ...               ...               ...   \n",
       "70  117.791879   8527.215896  120.247410        123.193394        117.301427   \n",
       "71  130.356118   8657.572014  120.247410        123.194543        117.300278   \n",
       "72  132.701339   8790.273353  120.247410        123.195692        117.299129   \n",
       "73  130.698575   8920.971928  120.247410        123.196840        117.297981   \n",
       "74  130.384896   9051.356824  120.247410        123.197988        117.296833   \n",
       "75  127.587522   9178.944346  120.247410        123.199135        117.295686   \n",
       "76  131.000426   9309.944772  120.247410        123.200282        117.294539   \n",
       "77  130.607800   9440.552571  120.247410        123.201429        117.293392   \n",
       "78  130.928821   9571.481392  120.247410        123.202575        117.292246   \n",
       "79  130.503994   9701.985387  120.247410        123.203721        117.291100   \n",
       "80  128.487086   9830.472473  120.247410        123.204866        117.289955   \n",
       "81  130.096512   9960.568985  120.247410        123.206010        117.288811   \n",
       "82  130.704873  10091.273858  120.247410        123.207155        117.287666   \n",
       "83  131.736525  10223.010383  120.247410        123.208299        117.286522   \n",
       "84  130.103931  10353.114314  120.247410        123.209442        117.285379   \n",
       "85  129.511296  10482.625610  120.247410        123.210585        117.284236   \n",
       "86  129.837721  10612.463331  120.247410        123.211727        117.283093   \n",
       "87  130.648914  10743.112245  120.247410        123.212870        117.281951   \n",
       "88  130.412364  10873.524608  120.247410        123.214011        117.280810   \n",
       "89  131.147951  11004.672559  120.247410        123.215152        117.279669   \n",
       "90  132.456466  11137.129025  120.247410        123.216293        117.278528   \n",
       "91  130.569662  11267.698687  120.247410        123.217434        117.277387   \n",
       "92  131.498945  11399.197633  120.247410        123.218573        117.276248   \n",
       "93  130.420537  11529.618170  120.247410        123.219713        117.275108   \n",
       "94  131.116882  11660.735051  120.247410        123.220852        117.273969   \n",
       "95  128.456173  11789.191224  120.247410        123.221990        117.272830   \n",
       "96  130.230586  11919.421810  120.247410        123.223129        117.271692   \n",
       "97  130.467414  12049.889223  120.247410        123.224266        117.270555   \n",
       "98  130.140680  12180.029904  120.247410        123.225404        117.269417   \n",
       "99  131.799071  12311.828975  120.247410        123.226540        117.268280   \n",
       "\n",
       "        cum_pred  cum_pred_lower  cum_pred_upper  point_effect  \\\n",
       "0       0.000000    -1959.966134     1959.966134      0.000000   \n",
       "1     121.308654    -1842.763739     2085.381048      0.000000   \n",
       "2     242.244407    -1725.384588     2209.873402      0.000000   \n",
       "3     362.811915    -1608.170725     2333.794555      0.000000   \n",
       "4     483.095153    -1491.135074     2457.325380      0.000000   \n",
       "5     603.289450    -1374.123174     2580.702074      0.000000   \n",
       "6     723.061826    -1257.489102     2703.612753      0.000000   \n",
       "7     843.246228    -1140.411227     2826.903683      0.000000   \n",
       "8     963.182068    -1023.557957     2949.922094      0.000000   \n",
       "9    1083.134069     -906.669846     3072.937983      0.000000   \n",
       "10   1203.066741     -789.786106     3195.919588      0.000000   \n",
       "11   1323.025099     -672.864454     3318.914652      0.000000   \n",
       "12   1442.822356     -556.093737     3441.738449      0.000000   \n",
       "13   1562.675629     -439.258430     3564.609688      0.000000   \n",
       "14   1682.444587     -322.500120     3687.389294      0.000000   \n",
       "15   1802.340497     -205.608548     3810.289543      0.000000   \n",
       "16   1922.077385      -88.870511     3933.025280      0.000000   \n",
       "17   2041.816663       27.874727     4055.758599      0.000000   \n",
       "18   2161.417923      144.486190     4178.349656      0.000000   \n",
       "19   2281.108795      261.191032     4301.026559      0.000000   \n",
       "20   2400.873612      377.973178     4423.774047      0.000000   \n",
       "21   2520.586800      494.706706     4546.466894      0.000000   \n",
       "22   2640.338051      611.481008     4669.195094      0.000000   \n",
       "23   2760.211854      728.380310     4792.043397      0.000000   \n",
       "24   2880.210918      845.407093     4915.014743      0.000000   \n",
       "25   3000.169280      962.395192     5037.943369      0.000000   \n",
       "26   3120.151769     1079.409257     5160.894280      0.000000   \n",
       "27   3240.200202     1196.490949     5283.909455      0.000000   \n",
       "28   3360.217933     1313.543479     5406.892386      0.000000   \n",
       "29   3480.173101     1430.534862     5529.811340      0.000000   \n",
       "..           ...             ...             ...           ...   \n",
       "70   8401.735165     6231.105043    10572.365286     -2.455531   \n",
       "71   8521.982575     6348.405321    10695.559829     10.108708   \n",
       "72   8642.229985     6465.704450    10818.755521     12.453928   \n",
       "73   8762.477396     6583.002431    10941.952361     10.451164   \n",
       "74   8882.724806     6700.299264    11065.150349     10.137485   \n",
       "75   9002.972217     6817.594949    11188.349485      7.340112   \n",
       "76   9123.219627     6934.889488    11311.549767     10.753015   \n",
       "77   9243.467038     7052.182880    11434.751196     10.360389   \n",
       "78   9363.714448     7169.475126    11557.953771     10.681410   \n",
       "79   9483.961859     7286.766227    11681.157491     10.256584   \n",
       "80   9604.209269     7404.056182    11804.362357      8.239676   \n",
       "81   9724.456680     7521.344993    11927.568367      9.849101   \n",
       "82   9844.704090     7638.632659    12050.775522     10.457462   \n",
       "83   9964.951501     7755.919181    12173.983820     11.489114   \n",
       "84  10085.198911     7873.204560    12297.193262      9.856521   \n",
       "85  10205.446322     7990.488796    12420.403847      9.263885   \n",
       "86  10325.693732     8107.771890    12543.615575      9.590310   \n",
       "87  10445.941143     8225.053841    12666.828444     10.401504   \n",
       "88  10566.188553     8342.334651    12790.042456     10.164953   \n",
       "89  10686.435964     8459.614319    12913.257608     10.900540   \n",
       "90  10806.683374     8576.892847    13036.473901     12.209056   \n",
       "91  10926.930785     8694.170235    13159.691335     10.322251   \n",
       "92  11047.178195     8811.446482    13282.909908     11.251535   \n",
       "93  11167.425606     8928.721590    13406.129621     10.173127   \n",
       "94  11287.673016     9045.995559    13529.350473     10.869471   \n",
       "95  11407.920427     9163.268390    13652.572464      8.208762   \n",
       "96  11528.167837     9280.540082    13775.795592      9.983175   \n",
       "97  11648.415248     9397.810637    13899.019859     10.220003   \n",
       "98  11768.662658     9515.080054    14022.245262      9.893270   \n",
       "99  11888.910069     9632.348334    14145.471803     11.551661   \n",
       "\n",
       "    point_effect_lower  point_effect_upper  cum_effect  cum_effect_lower  \\\n",
       "0             0.000000            0.000000    0.000000          0.000000   \n",
       "1             0.000000            0.000000    0.000000          0.000000   \n",
       "2             0.000000            0.000000    0.000000          0.000000   \n",
       "3             0.000000            0.000000    0.000000          0.000000   \n",
       "4             0.000000            0.000000    0.000000          0.000000   \n",
       "5             0.000000            0.000000    0.000000          0.000000   \n",
       "6             0.000000            0.000000    0.000000          0.000000   \n",
       "7             0.000000            0.000000    0.000000          0.000000   \n",
       "8             0.000000            0.000000    0.000000          0.000000   \n",
       "9             0.000000            0.000000    0.000000          0.000000   \n",
       "10            0.000000            0.000000    0.000000          0.000000   \n",
       "11            0.000000            0.000000    0.000000          0.000000   \n",
       "12            0.000000            0.000000    0.000000          0.000000   \n",
       "13            0.000000            0.000000    0.000000          0.000000   \n",
       "14            0.000000            0.000000    0.000000          0.000000   \n",
       "15            0.000000            0.000000    0.000000          0.000000   \n",
       "16            0.000000            0.000000    0.000000          0.000000   \n",
       "17            0.000000            0.000000    0.000000          0.000000   \n",
       "18            0.000000            0.000000    0.000000          0.000000   \n",
       "19            0.000000            0.000000    0.000000          0.000000   \n",
       "20            0.000000            0.000000    0.000000          0.000000   \n",
       "21            0.000000            0.000000    0.000000          0.000000   \n",
       "22            0.000000            0.000000    0.000000          0.000000   \n",
       "23            0.000000            0.000000    0.000000          0.000000   \n",
       "24            0.000000            0.000000    0.000000          0.000000   \n",
       "25            0.000000            0.000000    0.000000          0.000000   \n",
       "26            0.000000            0.000000    0.000000          0.000000   \n",
       "27            0.000000            0.000000    0.000000          0.000000   \n",
       "28            0.000000            0.000000    0.000000          0.000000   \n",
       "29            0.000000            0.000000    0.000000          0.000000   \n",
       "..                 ...                 ...         ...               ...   \n",
       "70            0.490452           -5.401515   -2.455531          0.490452   \n",
       "71           13.055840            7.161575    7.653177         13.546293   \n",
       "72           15.402210            9.505647   20.107105         28.948502   \n",
       "73           13.400594            7.501735   30.558269         42.349096   \n",
       "74           13.088063            7.186908   40.695755         55.437159   \n",
       "75           10.291837            4.388387   48.035867         65.728996   \n",
       "76           13.705887            7.800143   58.788882         79.434883   \n",
       "77           13.314408            7.406371   69.149271         92.749291   \n",
       "78           13.636575            7.726246   79.830682        106.385865   \n",
       "79           13.212894            7.300274   90.087265        119.598759   \n",
       "80           11.197131            5.282221   98.326941        130.795890   \n",
       "81           12.807701            6.890502  108.176043        143.603592   \n",
       "82           13.417207            7.497718  118.633505        157.020798   \n",
       "83           14.450003            8.528226  130.122620        171.470801   \n",
       "84           12.818552            6.894489  139.979140        184.289353   \n",
       "85           12.227060            6.300711  149.243026        196.516413   \n",
       "86           12.554627            6.625993  158.833336        209.071040   \n",
       "87           13.366963            7.436045  169.234840        222.438003   \n",
       "88           13.131554            7.198353  179.399793        235.569557   \n",
       "89           13.868282            7.932799  190.300333        249.437839   \n",
       "90           15.177938            9.240173  202.509389        264.615778   \n",
       "91           13.292274            7.352228  212.831640        277.908052   \n",
       "92           14.222698            8.280372  224.083175        292.130750   \n",
       "93           13.145429            7.200824  234.256302        305.276179   \n",
       "94           13.842912            7.896030  245.125773        319.119092   \n",
       "95           11.183342            5.234182  253.334535        330.302434   \n",
       "96           12.958893            7.007457  263.317710        343.261327   \n",
       "97           13.196859            7.243148  273.537714        356.458186   \n",
       "98           12.871263            6.915277  283.430984        369.329449   \n",
       "99           14.530791            8.572531  294.982644        383.860240   \n",
       "\n",
       "    cum_effect_upper  \n",
       "0           0.000000  \n",
       "1           0.000000  \n",
       "2           0.000000  \n",
       "3           0.000000  \n",
       "4           0.000000  \n",
       "5           0.000000  \n",
       "6           0.000000  \n",
       "7           0.000000  \n",
       "8           0.000000  \n",
       "9           0.000000  \n",
       "10          0.000000  \n",
       "11          0.000000  \n",
       "12          0.000000  \n",
       "13          0.000000  \n",
       "14          0.000000  \n",
       "15          0.000000  \n",
       "16          0.000000  \n",
       "17          0.000000  \n",
       "18          0.000000  \n",
       "19          0.000000  \n",
       "20          0.000000  \n",
       "21          0.000000  \n",
       "22          0.000000  \n",
       "23          0.000000  \n",
       "24          0.000000  \n",
       "25          0.000000  \n",
       "26          0.000000  \n",
       "27          0.000000  \n",
       "28          0.000000  \n",
       "29          0.000000  \n",
       "..               ...  \n",
       "70         -5.401515  \n",
       "71          1.760061  \n",
       "72         11.265708  \n",
       "73         18.767442  \n",
       "74         25.954350  \n",
       "75         30.342737  \n",
       "76         38.142881  \n",
       "77         45.549252  \n",
       "78         53.275498  \n",
       "79         60.575772  \n",
       "80         65.857992  \n",
       "81         72.748494  \n",
       "82         80.246212  \n",
       "83         88.774438  \n",
       "84         95.668927  \n",
       "85        101.969638  \n",
       "86        108.595632  \n",
       "87        116.031676  \n",
       "88        123.230029  \n",
       "89        131.162827  \n",
       "90        140.403000  \n",
       "91        147.755229  \n",
       "92        156.035600  \n",
       "93        163.236425  \n",
       "94        171.132454  \n",
       "95        176.366636  \n",
       "96        183.374093  \n",
       "97        190.617241  \n",
       "98        197.532518  \n",
       "99        206.105049  \n",
       "\n",
       "[100 rows x 14 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "impact.inferences"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we call `CausalImpact()`. Instead of providing input data, we simply pass in the fitted model object (`bsts_model`). We also need to provide the actual observed response. This is needed so that the package can compute the difference between predicted response (stored in `bsts_model`) and actual observed response (stored in `post_period_response`)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 9. FAQ\n",
    "\n",
    "### How do I cite the package in my work?\n",
    "We recommend referencing the use of the CausalImpact R package as shown in the example below:\n",
    "\n",
    "\"CausalImpact `r packageVersion(\"CausalImpact\")`, Brodersen et al., Annals of Applied Statistics (2015). http://google.github.io/CausalImpact/\"\n",
    "\n",
    "To find out which package version you are using, type `import causalimpact; causalimpact.__version__`. See the bottom of this page for full bibliographic details.\n",
    "\n",
    "### How can I check whether the model assumptions are fulfilled?\n",
    "It's the elephant in the room with any causal analysis on observational data: how can we verify the assumptions that go into the model? Here are a few ways of getting started. First of all, it is critical to reason why the covariates that are included in the model (this was *x1* in the example) *were not themselves affected* by the intervention. Sometimes it helps to plot all covariates and do a visual sanity check. Next, it is a good idea to examine how well the outcome data *y* can be predicted *before the beginning of the intervention*. This can be done by running `CausalImpact()` on an imaginary intervention. Then check how well the model predicted the data following this imaginary intervention. We would expect not to find a significant effect, i.e., counterfactual estimates and actual data should agree reasonably closely. Finally, when presenting or writing up results, be sure to list the above assumptions explicitly, including the priors in `model_args`, and discuss them with your audience.\n",
    "\n",
    "### May the data contain missing values?\n",
    "The response variable (i.e., the first column in data) may contain missing values (`NA`), but covariates (all other columns in data) may not. If one of your covariates contains missing values, consider imputing (i.e., estimating) the missing values; if this is not feasible, leave the regressor out.\n",
    "\n",
    "### How can I customize the default plot?\n",
    "By default, `impact.plot()` creates three panels, showing the counterfactual, pointwise, and cumulative impact estimates. One way of customizing the plot is to specify which panels should be included:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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vu6hUqRKnTp3km2++YM6cWSQlJQHQokVLHnvsSUaPfoGUlBS2bt2VryqQxbZn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\nsAYAANBC/wWolUVabQcY6AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f25ed64978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "impact.plot([\"original\", \"pointwise\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This creates a plot without cumulative impact estimates. This is sensible whenever the response variable represents a stock quantity that cannot be meaningfully summed up across time (e.g., number of current subscribers), rather than a flow quantity (e.g., number of clicks).\n",
    "\n",
    "### How can I change the font size in the plot?\n",
    "The `plot()` function for `CausalImpact` objects returns a matplotlib object. This means we can customize the plot using standard bokeh functions. For example, to increase the font size, we can do:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# TODO"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How can I obtain 90% intervals instead of 95% intervals?\n",
    "The size of the intervals is specified by the argument `alpha`, which defaults to 0.05. To obtain 90% intervals instead, we would use:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\projects\\causalimpact\\causalimpact\\analysis.py:19: Warning: This code is still wip and not fully\n",
      "                tested yet\n",
      "  tested yet\"\"\"))\n"
     ]
    }
   ],
   "source": [
    "impact = CausalImpact(data, pre_period, post_period, alpha = 0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Which predictor variables were used in the model?\n",
    "Analyses may easily contain tens or hundreds of potential predictors (i.e., columns in the data function argument). Which of these were informative? We can plot the posterior probability of each predictor being included in the model using:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# TODO impact.coefficient_plot()"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [Root]",
   "language": "python",
   "name": "Python [Root]"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}