Notebook_EDA.ipynb

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  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import pandas as pd \n",
    "from pandas.plotting import autocorrelation_plot\n",
    "from pandas import read_csv\n",
    "from pandas import datetime\n",
    "from pandas import DataFrame\n",
    "from sklearn.metrics import mean_squared_error\n",
    "import os\n",
    "\n",
    "from statsmodels.tsa.arima.model import ARIMA\n",
    "dirname = os.getcwd()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# My Personal Power Usage\n",
    "filename = os.path.join(dirname, 'data.csv')\n",
    "plt.title(\"Personal Energy Usage\")\n",
    "data = pd.read_csv(open(filename,'rb+'),index_col=\"Date\")['Quantity']\n",
    "data.index = pd.to_datetime(data.index, format='%m/%d/%Y')\n",
    "\n",
    "#data = data.resample('W').sum()\n",
    "data.resample('W').sum().plot()\n",
    "data = data.to_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "<AxesSubplot:title={'center':'Weekly AEP demand'}, xlabel='Datetime'>"
     },
     "metadata": {},
     "execution_count": 8
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "#Larger dataset for better analysis\n",
    "plt.title(\"Weekly AEP demand\")\n",
    "data = pd.read_csv(open('AEP_hourly.csv','r'),index_col=\"Datetime\")['AEP_MW']\n",
    "data.index = pd.to_datetime(data.index, format='%Y-%m-%d %H:%M:%S')\n",
    "\n",
    "data = data.resample('W').sum()\n",
    "data.plot()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 2 Axes>",
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "plt.title(\"AEP autocorrelation\")\n",
    "autocorrelation_plot(data[0:50])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "                               SARIMAX Results                                \n==============================================================================\nDep. Variable:                 AEP_MW   No. Observations:                  723\nModel:                 ARIMA(6, 1, 0)   Log Likelihood               -9817.183\nDate:                Sun, 27 Sep 2020   AIC                          19648.366\nTime:                        16:41:45   BIC                          19680.441\nSample:                    10-03-2004   HQIC                         19660.747\n                         - 08-05-2018                                         \nCovariance Type:                  opg                                         \n==============================================================================\n                 coef    std err          z      P>|z|      [0.025      0.975]\n------------------------------------------------------------------------------\nar.L1         -0.1814      0.023     -7.944      0.000      -0.226      -0.137\nar.L2         -0.1337      0.031     -4.377      0.000      -0.194      -0.074\nar.L3          0.0086      0.036      0.240      0.811      -0.062       0.079\nar.L4          0.0341      0.039      0.883      0.377      -0.042       0.110\nar.L5          0.0943      0.040      2.361      0.018       0.016       0.173\nar.L6          0.0575      0.036      1.598      0.110      -0.013       0.128\nsigma2      3.423e+10   2.88e-13   1.19e+23      0.000    3.42e+10    3.42e+10\n===================================================================================\nLjung-Box (L1) (Q):                   1.05   Jarque-Bera (JB):              1232.42\nProb(Q):                              0.31   Prob(JB):                         0.00\nHeteroskedasticity (H):               1.03   Skew:                             0.44\nProb(H) (two-sided):                  0.83   Kurtosis:                         9.34\n===================================================================================\n\nWarnings:\n[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n[2] Covariance matrix is singular or near-singular, with condition number 5.18e+37. Standard errors may be unstable.\n"
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "<AxesSubplot:xlabel='Datetime'>"
     },
     "metadata": {},
     "execution_count": 12
    },
    {
     "output_type": "display_data",
     "data": {
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "# fit model\n",
    "model = ARIMA(data, order=(6,1,0))\n",
    "model_fit = model.fit()\n",
    "\n",
    "#Summary\n",
    "print(model_fit.summary())\n",
    "# plot residual errors\n",
    "residuals = DataFrame(model_fit.resid)\n",
    "residuals.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "<AxesSubplot:title={'center':'Personal Weekly demand'}, xlabel='Date'>"
     },
     "metadata": {},
     "execution_count": 15
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "#Larger dataset for better analysis\n",
    "plt.title(\"Personal Weekly demand\")\n",
    "data = pd.read_csv(open('data.csv','r'),index_col=\"Date\")['Quantity']\n",
    "data.index = pd.to_datetime(data.index, format='%m/%d/%Y')\n",
    "data = data.resample('W').sum()\n",
    "data.plot()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 2 Axes>",
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "plt.title(\"Personal Energy Autocorrelation\")\n",
    "autocorrelation_plot(data)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "predicted=198.147957, expected=240.009000\npredicted=201.411175, expected=239.889000\npredicted=238.192970, expected=202.482000\npredicted=197.755912, expected=164.761000\npredicted=171.877475, expected=201.865000\npredicted=211.297343, expected=181.720000\npredicted=200.163749, expected=78.590000\npredicted=123.243132, expected=99.355000\npredicted=107.999695, expected=104.596000\npredicted=92.990179, expected=108.658000\npredicted=136.496451, expected=88.591000\npredicted=101.287997, expected=60.828000\npredicted=55.879087, expected=74.084000\npredicted=77.447094, expected=134.140000\npredicted=124.594359, expected=118.364000\npredicted=113.549092, expected=110.227000\npredicted=111.762244, expected=43.847000\npredicted=45.441828, expected=32.814000\npredicted=51.091951, expected=30.663000\npredicted=47.106364, expected=31.154000\npredicted=41.092670, expected=30.905000\npredicted=34.419557, expected=30.716000\npredicted=23.687929, expected=28.008000\npredicted=27.230630, expected=83.489000\npredicted=75.059629, expected=50.940000\nTest MSE: 1593.311\n"
    },
    {
     "output_type": "error",
     "ename": "NameError",
     "evalue": "name 'pyplot' is not defined",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-21-085110f057ea>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     17\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Test MSE: %.3f'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0merror\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     18\u001b[0m \u001b[0;31m# plot\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 19\u001b[0;31m \u001b[0mpyplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     20\u001b[0m \u001b[0mpyplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpredictions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'red'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     21\u001b[0m \u001b[0mpyplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'pyplot' is not defined"
     ]
    }
   ],
   "source": [
    "\n",
    "X = data.values\n",
    "size = int(len(X) * 0.5)\n",
    "train, test = X[0:size], X[size:len(X)]\n",
    "\n",
    "history = [x for x in train]\n",
    "predictions = list()\n",
    "for t in range(len(test)):\n",
    "\tmodel = ARIMA(history, order=(6,1,0))\n",
    "\tmodel_fit = model.fit()\n",
    "\toutput = model_fit.forecast()\n",
    "\tyhat = output[0]\n",
    "\tpredictions.append(yhat)\n",
    "\tobs = test[t]\n",
    "\thistory.append(obs)\n",
    "\tprint('predicted=%f, expected=%f' % (yhat, obs))\n",
    "error = mean_squared_error(test, predictions)\n",
    "print('Test MSE: %.3f' % error)\n",
    "# plot\n",
    "plt.plot(test)\n",
    "plt.plot(predictions, color='red')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}