ICPE_DS3_Spring_2023 (1).ipynb

{"cells":[{"cell_type":"markdown","metadata":{"id":"FcI7yYsGrrIO"},"source":["# Forecasting Electricity Load of Houston\n","###  ICPE 638 - Spring 2023\n","\n","[Enrique Z. Losoya](https://orcid.org/0000-0001-7763-3349), and [Jian Tao](https://orcid.org/0000-0003-4228-6089), Texas A&M University.\n","Updated: Jan. 3, 2023.\n","\n","**(30 points)**\n","\n","- Name:  Juan David Baquero Barrios\n","- GitHub or Google colab link: https://drive.google.com/file/d/1QxH31Qq6xYOko9HM1qjuScZ4Ylj-UcIB/view?usp=sharing\n","\n","### **Data Set**\n","A Cross-Domain Data Hub to Track the Impact of COVID-19 on U.S. Electricity Markets\n","\n","https://github.com/tamu-engineering-research/COVID-EMDA\n","\n","Particularly, we will use the electricity load data of Houston.\n","\n","https://raw.githubusercontent.com/tamu-engineering-research/COVID-EMDA/master/data_release/ercot/ercot_houston_load.csv\n","\n","### **Problem**\n","1. Carry out component decomposition for the electricity load of Houston\n","\n","2. Perform KPSS and ADF Stationarity Tests, explain your results. \n","\n","3. Build an ARIMA model with an optimal order (p, d, q)\n","   \n","4.  *(Extra credit)* Make a prediction for the next 30 days, plot it out, and explain your results."]},{"cell_type":"markdown","metadata":{"id":"c5BTEuYQeGlZ"},"source":["## Download and Process Dataset\n","**Please don't change this section!**\n","\n","You can use the dataframe `df` for the rest of your analysis."]},{"cell_type":"code","execution_count":3,"metadata":{"id":"NvsZ4lnle1Gv","executionInfo":{"status":"ok","timestamp":1673827293296,"user_tz":360,"elapsed":127,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}}},"outputs":[],"source":["DATA_URL=\"https://raw.githubusercontent.com/tamu-engineering-research/COVID-EMDA/master/data_release/ercot/ercot_houston_load.csv\""]},{"cell_type":"code","execution_count":4,"metadata":{"id":"aiG7AtdBeN3c","executionInfo":{"status":"ok","timestamp":1673827299854,"user_tz":360,"elapsed":5831,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}}},"outputs":[],"source":["# import pandas, numpy and seaborn. sns.set() will set multiple theme parameters in one step for seaborn\n","import pandas as pd\n","import matplotlib.pyplot as plt\n","import numpy as np\n","import seaborn as sns\n","sns.set()"]},{"cell_type":"code","execution_count":5,"metadata":{"id":"KUhdnJDkeX5N","colab":{"base_uri":"https://localhost:8080/","height":267},"executionInfo":{"status":"ok","timestamp":1673827300477,"user_tz":360,"elapsed":473,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}},"outputId":"5f3025a8-5b55-46e1-ceb8-72db7cec129b"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["             00:00   01:00   02:00   03:00   04:00   05:00    06:00    07:00  \\\n","date                                                                           \n","2017-01-01  8791.8  8569.7  8326.4  8137.5  8011.9  7978.1   8057.1   8125.8   \n","2017-01-02  8836.8  8588.2  8480.8  8506.0  8644.7  8887.0   9176.5   9323.8   \n","2017-01-03  8516.6  8238.2  8102.8  8094.3  8265.7  8816.3   9615.5  10009.8   \n","2017-01-04  8462.0  8316.5  8259.6  8336.3  8636.6  9357.1  10504.8  10955.0   \n","2017-01-05  9472.0  9198.3  9051.1  9031.1  9237.9  9836.5  10685.2  10931.8   \n","\n","              08:00    09:00  ...    14:00    15:00    16:00    17:00  \\\n","date                          ...                                       \n","2017-01-01   8289.2   8646.5  ...   9957.6   9987.9   9943.9  10181.0   \n","2017-01-02   9559.9   9602.7  ...  10937.1  11037.0  10931.5  10859.0   \n","2017-01-03  10102.3  10235.3  ...  11022.6  10988.9  10883.8  10882.0   \n","2017-01-04  10944.0  11119.8  ...  10713.0  10602.9  10638.3  11099.4   \n","2017-01-05  10841.5  10912.8  ...  10692.5  10696.2  10791.9  11130.9   \n","\n","              18:00    19:00    20:00    21:00    22:00   23:00  \n","date                                                             \n","2017-01-01  10583.5  10451.0  10230.6  10014.8   9667.7  9287.7  \n","2017-01-02  11112.1  10893.9  10594.2  10196.7   9568.1  8935.5  \n","2017-01-03  11092.8  10889.1  10577.2  10100.1   9488.8  8916.9  \n","2017-01-04  11605.9  11578.6  11416.8  11010.9  10392.6  9784.5  \n","2017-01-05  11378.8  11311.2  11194.9  10882.2  10416.8  9959.7  \n","\n","[5 rows x 24 columns]"],"text/html":["\n","  <div id=\"df-a14d44a2-57ca-4d05-93ba-66586c4cea9b\">\n","    <div class=\"colab-df-container\">\n","      <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>00:00</th>\n","      <th>01:00</th>\n","      <th>02:00</th>\n","      <th>03:00</th>\n","      <th>04:00</th>\n","      <th>05:00</th>\n","      <th>06:00</th>\n","      <th>07:00</th>\n","      <th>08:00</th>\n","      <th>09:00</th>\n","      <th>...</th>\n","      <th>14:00</th>\n","      <th>15:00</th>\n","      <th>16:00</th>\n","      <th>17:00</th>\n","      <th>18:00</th>\n","      <th>19:00</th>\n","      <th>20:00</th>\n","      <th>21:00</th>\n","      <th>22:00</th>\n","      <th>23:00</th>\n","    </tr>\n","    <tr>\n","      <th>date</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2017-01-01</th>\n","      <td>8791.8</td>\n","      <td>8569.7</td>\n","      <td>8326.4</td>\n","      <td>8137.5</td>\n","      <td>8011.9</td>\n","      <td>7978.1</td>\n","      <td>8057.1</td>\n","      <td>8125.8</td>\n","      <td>8289.2</td>\n","      <td>8646.5</td>\n","      <td>...</td>\n","      <td>9957.6</td>\n","      <td>9987.9</td>\n","      <td>9943.9</td>\n","      <td>10181.0</td>\n","      <td>10583.5</td>\n","      <td>10451.0</td>\n","      <td>10230.6</td>\n","      <td>10014.8</td>\n","      <td>9667.7</td>\n","      <td>9287.7</td>\n","    </tr>\n","    <tr>\n","      <th>2017-01-02</th>\n","      <td>8836.8</td>\n","      <td>8588.2</td>\n","      <td>8480.8</td>\n","      <td>8506.0</td>\n","      <td>8644.7</td>\n","      <td>8887.0</td>\n","      <td>9176.5</td>\n","      <td>9323.8</td>\n","      <td>9559.9</td>\n","      <td>9602.7</td>\n","      <td>...</td>\n","      <td>10937.1</td>\n","      <td>11037.0</td>\n","      <td>10931.5</td>\n","      <td>10859.0</td>\n","      <td>11112.1</td>\n","      <td>10893.9</td>\n","      <td>10594.2</td>\n","      <td>10196.7</td>\n","      <td>9568.1</td>\n","      <td>8935.5</td>\n","    </tr>\n","    <tr>\n","      <th>2017-01-03</th>\n","      <td>8516.6</td>\n","      <td>8238.2</td>\n","      <td>8102.8</td>\n","      <td>8094.3</td>\n","      <td>8265.7</td>\n","      <td>8816.3</td>\n","      <td>9615.5</td>\n","      <td>10009.8</td>\n","      <td>10102.3</td>\n","      <td>10235.3</td>\n","      <td>...</td>\n","      <td>11022.6</td>\n","      <td>10988.9</td>\n","      <td>10883.8</td>\n","      <td>10882.0</td>\n","      <td>11092.8</td>\n","      <td>10889.1</td>\n","      <td>10577.2</td>\n","      <td>10100.1</td>\n","      <td>9488.8</td>\n","      <td>8916.9</td>\n","    </tr>\n","    <tr>\n","      <th>2017-01-04</th>\n","      <td>8462.0</td>\n","      <td>8316.5</td>\n","      <td>8259.6</td>\n","      <td>8336.3</td>\n","      <td>8636.6</td>\n","      <td>9357.1</td>\n","      <td>10504.8</td>\n","      <td>10955.0</td>\n","      <td>10944.0</td>\n","      <td>11119.8</td>\n","      <td>...</td>\n","      <td>10713.0</td>\n","      <td>10602.9</td>\n","      <td>10638.3</td>\n","      <td>11099.4</td>\n","      <td>11605.9</td>\n","      <td>11578.6</td>\n","      <td>11416.8</td>\n","      <td>11010.9</td>\n","      <td>10392.6</td>\n","      <td>9784.5</td>\n","    </tr>\n","    <tr>\n","      <th>2017-01-05</th>\n","      <td>9472.0</td>\n","      <td>9198.3</td>\n","      <td>9051.1</td>\n","      <td>9031.1</td>\n","      <td>9237.9</td>\n","      <td>9836.5</td>\n","      <td>10685.2</td>\n","      <td>10931.8</td>\n","      <td>10841.5</td>\n","      <td>10912.8</td>\n","      <td>...</td>\n","      <td>10692.5</td>\n","      <td>10696.2</td>\n","      <td>10791.9</td>\n","      <td>11130.9</td>\n","      <td>11378.8</td>\n","      <td>11311.2</td>\n","      <td>11194.9</td>\n","      <td>10882.2</td>\n","      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'pandas.core.frame.DataFrame'>\n","DatetimeIndex: 1793 entries, 2017-01-01 to 2021-11-30\n","Data columns (total 1 columns):\n"," #   Column  Non-Null Count  Dtype  \n","---  ------  --------------  -----  \n"," 0   load    1793 non-null   float64\n","dtypes: float64(1)\n","memory usage: 28.0 KB\n"]}]},{"cell_type":"code","execution_count":8,"metadata":{"id":"WXiR9iGOaOio","colab":{"base_uri":"https://localhost:8080/","height":293},"executionInfo":{"status":"ok","timestamp":1673827301463,"user_tz":360,"elapsed":661,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}},"outputId":"e78e3c07-9c90-44dc-c101-c16d31150c83"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f1b55d97130>"]},"metadata":{},"execution_count":8},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 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\n"},"metadata":{}}],"source":["df.plot()"]},{"cell_type":"markdown","metadata":{"id":"AqRWqN7TZrrq"},"source":["## Component Decomposition"]},{"cell_type":"code","source":["df_weekly_mean = df[[\"load\"]].resample(\"w\").mean(); df_weekly_mean"],"metadata":{"id":"CG650GQYDJof"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["df_weekly_mean.plot()"],"metadata":{"id":"UrX9n7AnDJdf"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["df_diff_d=df.diff(periods=1)"],"metadata":{"id":"FWzk68zh-6dx","executionInfo":{"status":"ok","timestamp":1673830484495,"user_tz":360,"elapsed":149,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}}},"execution_count":24,"outputs":[]},{"cell_type":"code","source":["df_diff_d.plot()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":293},"id":"SwONYRA1D7LR","executionInfo":{"status":"ok","timestamp":1673830496731,"user_tz":360,"elapsed":1004,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}},"outputId":"71387305-2e35-41ef-b7b8-a631f6f31903"},"execution_count":26,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7f1b52db1e50>"]},"metadata":{},"execution_count":26},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["df_diff_d=df_diff_d[2:]"],"metadata":{"id":"J676tTfmE3ay","executionInfo":{"status":"ok","timestamp":1673830595483,"user_tz":360,"elapsed":132,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}}},"execution_count":27,"outputs":[]},{"cell_type":"code","source":["from statsmodels.tsa.stattools import kpss\n","\n","def kpss_test(timeseries):\n","    print ('Results of KPSS Test:')\n","    kpsstest = kpss(timeseries, regression='c')\n","    kpss_output = pd.Series(kpsstest[0:3], index=['Test Statistic','p-value','Lags Used'])\n","    for key,value in kpsstest[3].items():\n","        kpss_output['Critical Value (%s)'%key] = value\n","    print (kpss_output)"],"metadata":{"id":"3_PygcGdFNV-","executionInfo":{"status":"ok","timestamp":1673830667498,"user_tz":360,"elapsed":287,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}}},"execution_count":29,"outputs":[]},{"cell_type":"markdown","source":["**KPSS test** p-value is 0.1, which less than all the critial values. The null hypothesis can be rejected. Hence the series is non-stationary."],"metadata":{"id":"XfwLMxTeGOT1"}},{"cell_type":"code","source":["kpss_test(df_diff_d[\"load\"])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"SsnR48jjFSHL","executionInfo":{"status":"ok","timestamp":1673830963470,"user_tz":360,"elapsed":152,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}},"outputId":"91eab270-7344-45aa-dfec-0c8c1fa69702"},"execution_count":31,"outputs":[{"output_type":"stream","name":"stdout","text":["Results of KPSS Test:\n","Test Statistic            0.03599\n","p-value                   0.10000\n","Lags Used                25.00000\n","Critical Value (10%)      0.34700\n","Critical Value (5%)       0.46300\n","Critical Value (2.5%)     0.57400\n","Critical Value (1%)       0.73900\n","dtype: float64\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.8/dist-packages/statsmodels/tsa/stattools.py:1875: FutureWarning: The behavior of using nlags=None will change in release 0.13.Currently nlags=None is the same as nlags=\"legacy\", and so a sample-size lag length is used. After the next release, the default will change to be the same as nlags=\"auto\" which uses an automatic lag length selection method. To silence this warning, either use \"auto\" or \"legacy\"\n","  warnings.warn(msg, FutureWarning)\n","/usr/local/lib/python3.8/dist-packages/statsmodels/tsa/stattools.py:1910: InterpolationWarning: The test statistic is outside of the range of p-values available in the\n","look-up table. The actual p-value is greater than the p-value returned.\n","\n","  warnings.warn(\n"]}]},{"cell_type":"markdown","source":["**ADF Test** p-value is 1*10^-22 which is higher than all the critical values , which less than 10% confidence level. The null hypothesis can be rejected. Hence the series is non-stationary."],"metadata":{"id":"HZje_FMOHYTL"}},{"cell_type":"code","source":["from statsmodels.tsa.stattools import adfuller\n","\n","def adf_test(timeseries):\n","    print ('Results of Dickey-Fuller Test:')\n","    dftest = adfuller(timeseries, autolag='AIC')\n","    dfoutput = pd.Series(dftest[0:4], index=['Test Statistic','p-value','#Lags Used','Number of Observations Used'])\n","    for key,value in dftest[4].items():\n","       dfoutput['Critical Value (%s)'%key] = value\n","    print (dfoutput)"],"metadata":{"id":"SH278TlvGi8j","executionInfo":{"status":"ok","timestamp":1673831019818,"user_tz":360,"elapsed":118,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}}},"execution_count":32,"outputs":[]},{"cell_type":"code","source":["adf_test(df_diff_d[\"load\"])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"1J3PdmriGn9M","executionInfo":{"status":"ok","timestamp":1673831055925,"user_tz":360,"elapsed":1388,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}},"outputId":"9964f82e-bc4d-4e59-ef38-40656e7d3702"},"execution_count":33,"outputs":[{"output_type":"stream","name":"stdout","text":["Results of Dickey-Fuller Test:\n","Test Statistic                -1.217527e+01\n","p-value                        1.390888e-22\n","#Lags Used                     2.200000e+01\n","Number of Observations Used    1.768000e+03\n","Critical Value (1%)           -3.434054e+00\n","Critical Value (5%)           -2.863176e+00\n","Critical Value (10%)          -2.567641e+00\n","dtype: float64\n"]}]},{"cell_type":"markdown","source":["This **ACF and PACF** graphs represents a patter of a non stationary time series of load,  due they do not show any significant correlation at higher lags, and the values of the patterns are in the variance of the graphic. It represents that do not have a change depending in the season.\n"],"metadata":{"id":"l3SXpMF5K3Ao"}},{"cell_type":"code","source":["import matplotlib.gridspec as gridspec\n","from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n","\n","fig = plt.figure(tight_layout = True, figsize = (14, 8))\n","gs = gridspec.GridSpec(2, 2)\n","ax = fig.add_subplot(gs[0,0])\n","plot_acf(df_diff_d[\"load\"],title='ACF of ARMA(2,1)', ax = ax)\n","ax = fig.add_subplot(gs[0,1])\n","plot_pacf(pd.DataFrame(df_diff_d[\"load\"]),title='PACF of ARMA(2,1)',ax = ax)\n","ax = fig.add_subplot(gs[1,0])\n","plot_acf(df_diff_d[\"load\"],title='ACF of ARIMA(2,1,1)',ax = ax)\n","ax = fig.add_subplot(gs[1,1])\n","plot_pacf(df_diff_d[\"load\"],title='PACF of ARIMA(2,1,1)',ax = ax)\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":581},"id":"EoMP9R1jH1h8","executionInfo":{"status":"ok","timestamp":1673832125467,"user_tz":360,"elapsed":3753,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}},"outputId":"c51b54be-d3b5-4ef4-d6ad-609ea1cbba11"},"execution_count":38,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1008x576 with 4 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","metadata":{"id":"N_fDTK3vZvgB"},"source":["##   ARIMA Model with optimal order (p, d, q)"]},{"cell_type":"code","execution_count":123,"metadata":{"id":"gFI11LxkZx4Y","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1673837568014,"user_tz":360,"elapsed":9505,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}},"outputId":"d564a010-f913-4309-ebb8-0fe670668161"},"outputs":[{"output_type":"stream","name":"stdout","text":["                               SARIMAX Results                                \n","==============================================================================\n","Dep. Variable:                   load   No. Observations:                 1400\n","Model:                 ARIMA(2, 1, 3)   Log Likelihood              -15653.978\n","Date:                Mon, 16 Jan 2023   AIC                          31319.955\n","Time:                        02:52:47   BIC                          31351.416\n","Sample:                    01-03-2017   HQIC                         31331.716\n","                         - 11-02-2020                                         \n","Covariance Type:                  opg                                         \n","==============================================================================\n","                 coef    std err          z      P>|z|      [0.025      0.975]\n","------------------------------------------------------------------------------\n","ar.L1          0.3695      0.078      4.745      0.000       0.217       0.522\n","ar.L2         -0.0488      0.071     -0.690      0.490      -0.187       0.090\n","ma.L1         -1.3913      0.076    -18.312      0.000      -1.540      -1.242\n","ma.L2          0.0334      0.143      0.234      0.815      -0.247       0.313\n","ma.L3          0.3583      0.073      4.880      0.000       0.214       0.502\n","sigma2      3.602e+08   3.65e-10   9.86e+17      0.000     3.6e+08     3.6e+08\n","===================================================================================\n","Ljung-Box (L1) (Q):                   0.00   Jarque-Bera (JB):               246.42\n","Prob(Q):                              0.97   Prob(JB):                         0.00\n","Heteroskedasticity (H):               0.99   Skew:                            -0.45\n","Prob(H) (two-sided):                  0.92   Kurtosis:                         4.85\n","===================================================================================\n","\n","Warnings:\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 1.84e+34. Standard errors may be unstable.\n"]}],"source":["from statsmodels.tsa.arima.model import ARIMA\n","\n","# Split sample. Use the first 200 data points in my_arima_array as training data and the last 50 as test data. \n","my_arima_array_train = df_diff_d[\"load\"][:1400] \n","my_arima_array_test = df_diff_d[\"load\"][1400:]\n","\n","# fit the ARIMA model\n","model = ARIMA(my_arima_array_train,order=(2, 1, 3))\n","model_fit = model.fit()\n","\n","# print the fitting result\n","print(model.fit().summary())"]},{"cell_type":"code","source":["residuals = pd.DataFrame(model.fit().resid)\n","\n","# Generate the residual plot\n","fig = plt.figure(tight_layout = True, figsize = (10, 4))\n","gs = gridspec.GridSpec(1, 2)\n","ax = fig.add_subplot(gs[0,0])\n","residuals.plot(title=\"Residuals\",ax=ax, legend=False)\n","ax = fig.add_subplot(gs[0,1])\n","residuals.plot(kind='kde',title='Density',ax=ax,legend = False)\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":293},"id":"VOccEoaePNiQ","executionInfo":{"status":"ok","timestamp":1673837575056,"user_tz":360,"elapsed":5058,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}},"outputId":"0be019be-29ff-4384-802c-f5668e4ebc98"},"execution_count":124,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 720x288 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["There is a constant mean of variance and covriance in the plots Autocorrelation and Partial correlation, so the model is adequate"],"metadata":{"id":"k_WH_i37RIRb"}},{"cell_type":"code","source":["fig = plt.figure(tight_layout = True, figsize = (10, 4))\n","gs = gridspec.GridSpec(1, 2)\n","ax = fig.add_subplot(gs[0,0])\n","plot_acf(residuals,ax = ax)\n","ax = fig.add_subplot(gs[0,1])\n","plot_pacf(residuals,ax = ax)\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":293},"id":"9OCPtDiGQIEQ","executionInfo":{"status":"ok","timestamp":1673837581813,"user_tz":360,"elapsed":185,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}},"outputId":"ed33ea85-09df-4b4f-c9fa-ee663344fed8"},"execution_count":125,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 720x288 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["from statsmodels.tsa import arima_model\n","from statsmodels.graphics.tsaplots import plot_predict\n"," \n","# True values vs predicted by model \n","\n","results = model.fit() \n","plot_predict(results, 100, 300, dynamic=False)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":541},"id":"BlPti7dagUVj","executionInfo":{"status":"ok","timestamp":1673837792749,"user_tz":360,"elapsed":6664,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}},"outputId":"f7d080f1-0e26-42fc-e722-5bdccad4ba21"},"execution_count":130,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<Figure size 432x288 with 1 Axes>"],"image/png":"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\n"},"metadata":{},"execution_count":130},{"output_type":"display_data","data":{"text/plain":["<Figure 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\n"},"metadata":{}}]},{"cell_type":"code","source":["import itertools\n","def arima_order(data, order=10, verbose=True):\n","  p=d=q=range(0,order)\n","  pdq = list(itertools.product(p,d,q))\n","  warnings.filterwarnings(\"ignore\")\n","  aic_pair={}\n","  min_aic=9999999\n","  min_order=(0,0,0)\n","  for o in pdq:\n","    try:\n","      model_arima = ARIMA(data, order=o)\n","      model_arima_fit=model_arima.fit()\n","      fit_aic = model_arima_fit.aic\n","      if verbose: print(o, \"AIC=\", fit_aic)\n","      if not np.isnan(fit_aic):\n","        if min_aic>fit_aic:\n","          min_aic = fit_aic\n","          min_order=o\n","      aic_pair.update({o, rmodel_arima_fit.aic})\n","    except:\n","      continue\n","  return min_order"],"metadata":{"id":"bk0ErImgW8El","executionInfo":{"status":"ok","timestamp":1673837410754,"user_tz":360,"elapsed":141,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}}},"execution_count":118,"outputs":[]},{"cell_type":"code","source":["arima_order(df_diff_d[\"load\"], order=4)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"HoKd_p4mXOFZ","executionInfo":{"status":"ok","timestamp":1673837533496,"user_tz":360,"elapsed":119801,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}},"outputId":"2f0456e8-399f-4e19-e5f2-b15f69782ed3"},"execution_count":119,"outputs":[{"output_type":"stream","name":"stdout","text":["(0, 0, 0) AIC= 51985.367491465346\n","(0, 0, 1) AIC= 40349.802862647615\n","(0, 0, 2) AIC= 40111.65304804666\n","(0, 0, 3) AIC= 40055.91983118744\n","(0, 1, 0) AIC= 41484.05485867349\n","(0, 1, 1) AIC= 40360.67825913404\n","(0, 1, 2) AIC= 40345.42748361486\n","(0, 1, 3) AIC= 40141.91856527359\n","(0, 2, 0) AIC= 43175.23621908178\n","(0, 2, 1) AIC= 41502.45479392297\n","(0, 2, 2) AIC= 40344.254131387315\n","(0, 2, 3) AIC= 40601.89304721213\n","(0, 3, 0) AIC= 45119.820730927444\n","(0, 3, 1) AIC= 43160.7835219498\n","(0, 3, 2) AIC= 41483.79996295975\n","(0, 3, 3) AIC= 41460.14491971793\n","(1, 0, 0) AIC= 40357.23852207491\n","(1, 0, 1) AIC= 40212.644167989674\n","(1, 0, 2) AIC= 40057.51480945868\n","(1, 0, 3) AIC= 40056.894072792296\n","(1, 1, 0) AIC= 41313.68900778846\n","(1, 1, 1) AIC= 40342.447619163344\n","(1, 1, 2) AIC= 40285.47845916428\n","(1, 1, 3) AIC= 40053.23229937109\n","(1, 2, 0) AIC= 42655.09734237523\n","(1, 2, 1) AIC= 41300.121013523494\n","(1, 2, 2) AIC= 41472.31194220666\n","(1, 2, 3) AIC= 40347.62224314176\n","(1, 3, 0) AIC= 44228.393137443476\n","(1, 3, 1) AIC= 42680.39711263974\n","(1, 3, 2) AIC= 41292.26500545331\n","(1, 3, 3) AIC= 41469.75397467436\n","(2, 0, 0) AIC= 40156.8900042904\n","(2, 0, 1) AIC= 40077.52717608216\n","(2, 0, 2) AIC= 40058.055288565076\n","(2, 0, 3) AIC= 40058.79577154683\n","(2, 1, 0) AIC= 40958.03398787706\n","(2, 1, 1) AIC= 40245.63011439245\n","(2, 1, 2) AIC= 40112.27737191502\n","(2, 1, 3) AIC= 33.67344346795659\n","(2, 2, 0) AIC= 42140.66599298757\n","(2, 2, 1) AIC= 41105.768666273434\n","(2, 2, 2) AIC= 40493.98409083682\n","(2, 2, 3) AIC= 40465.96512450311\n","(2, 3, 0) AIC= 43561.90245276047\n","(2, 3, 1) AIC= 42305.16667895524\n","(2, 3, 2) AIC= 41515.62203546977\n","(2, 3, 3) AIC= 41498.42666902667\n","(3, 0, 0) AIC= 40136.3390405571\n","(3, 0, 1) AIC= 40057.43468690246\n","(3, 0, 2) AIC= 40057.31710001097\n","(3, 0, 3) AIC= 40048.34232877429\n","(3, 1, 0) AIC= 40783.45636002832\n","(3, 1, 1) AIC= 40232.20502841739\n","(3, 1, 2) AIC= 40159.11567986473\n","(3, 1, 3) AIC= 40080.618781817946\n","(3, 2, 0) AIC= 41760.1682190017\n","(3, 2, 1) AIC= 41001.765368450855\n","(3, 2, 2) AIC= 40394.454556069264\n","(3, 2, 3) AIC= 40297.343244804084\n","(3, 3, 0) AIC= 42987.303365491796\n","(3, 3, 1) AIC= 42095.01723083209\n","(3, 3, 2) AIC= 41280.77512603377\n","(3, 3, 3) AIC= 41143.08986061292\n"]},{"output_type":"execute_result","data":{"text/plain":["(2, 1, 3)"]},"metadata":{},"execution_count":119}]},{"cell_type":"markdown","metadata":{"id":"neZQxM4IWsxB"},"source":["##   ARIMA Model Forecasting (Extra)"]},{"cell_type":"code","execution_count":131,"metadata":{"id":"5CK1lJLMWsxC","executionInfo":{"status":"ok","timestamp":1673837817169,"user_tz":360,"elapsed":3270,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}}},"outputs":[],"source":["from statsmodels.tsa.arima.model import ARIMA\n","from statsmodels.tsa import arima_model\n","from statsmodels.graphics.tsaplots import plot_predict\n","from statsmodels.tsa.arima_process import arma_generate_sample\n","import warnings\n","\n","my_arima_array_train = df_diff_d[\"load\"][:1400] \n","my_arima_array_test = df_diff_d[\"load\"][1400:]\n","\n","model = ARIMA(my_arima_array_train,order=(2, 1, 3))\n","model_fit = model.fit()\n"]},{"cell_type":"code","source":["model_arima_fit=model.fit()\n","print(model_arima_fit.aic)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"nRZbG5uybNWs","executionInfo":{"status":"ok","timestamp":1673837822961,"user_tz":360,"elapsed":3199,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}},"outputId":"c8fb1e0a-5df8-414e-ee2f-cf5654f53c24"},"execution_count":132,"outputs":[{"output_type":"stream","name":"stdout","text":["31319.955159387493\n"]}]},{"cell_type":"code","source":["n_pred = 30 # Lead time, or forecasting horizon -- the number of steps ahead for out of sample forecast \n","result = model.fit().forecast(steps=n_pred,alpha=0.05)\n","pred_array = result[0]\n","se_array = result[1]\n","CI_array = result[2]\n","plt.figure(figsize=(12,4))\n","pred_array_index = range(1300,1800)\n","plt.plot(df_diff_d[\"load\"][500:])\n","plt.plot(pred_array_index, pred_array, color = \"red\")\n","plt.fill_between(pred_array_index, CI_array[:,0], CI_array[:,1], color = \"k\", alpha = .03 )\n","plt.title('Forecast of the simulated data')\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":632},"id":"9326-daObDB3","executionInfo":{"status":"error","timestamp":1673838520953,"user_tz":360,"elapsed":5747,"user":{"displayName":"Juan David Baquero Barrios","userId":"05486740569965299773"}},"outputId":"b351c16f-d084-4f66-b4e2-b3785e0d82dc"},"execution_count":152,"outputs":[{"output_type":"error","ename":"ValueError","evalue":"ignored","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)","\u001b[0;32m<ipython-input-152-f13840dc2657>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mpred_array_index\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1300\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1800\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf_diff_d\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"load\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m500\u001b[0m\u001b[0;34m:\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;32m----> 7\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpred_array_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpred_array\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[0m\u001b[1;32m      8\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfill_between\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpred_array_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mCI_array\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mCI_array\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"k\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malpha\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m.03\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Forecast of the simulated data'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.8/dist-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mplot\u001b[0;34m(scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m   2759\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0mdocstring\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAxes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2760\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscalex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscaley\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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;32m-> 2761\u001b[0;31m     return gca().plot(\n\u001b[0m\u001b[1;32m   2762\u001b[0m         *args, scalex=scalex, scaley=scaley, **({\"data\": data} if data\n\u001b[1;32m   2763\u001b[0m         is not None else {}), **kwargs)\n","\u001b[0;32m/usr/local/lib/python3.8/dist-packages/matplotlib/axes/_axes.py\u001b[0m in \u001b[0;36mplot\u001b[0;34m(self, scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1645\u001b[0m         \"\"\"\n\u001b[1;32m   1646\u001b[0m         \u001b[0mkwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcbook\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnormalize_kwargs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmlines\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLine2D\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1647\u001b[0;31m         \u001b[0mlines\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_lines\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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[0m\u001b[1;32m   1648\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mline\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlines\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1649\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_line\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.8/dist-packages/matplotlib/axes/_base.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    214\u001b[0m                 \u001b[0mthis\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\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[1;32m    215\u001b[0m                 \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\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;32m--> 216\u001b[0;31m             \u001b[0;32myield\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_plot_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mthis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\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    217\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    218\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mget_next_color\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\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;32m/usr/local/lib/python3.8/dist-packages/matplotlib/axes/_base.py\u001b[0m in \u001b[0;36m_plot_args\u001b[0;34m(self, tup, kwargs)\u001b[0m\n\u001b[1;32m    340\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    341\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\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;32m--> 342\u001b[0;31m             raise ValueError(f\"x and y must have same first dimension, but \"\n\u001b[0m\u001b[1;32m    343\u001b[0m                              f\"have shapes {x.shape} and {y.shape}\")\n\u001b[1;32m    344\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m2\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mValueError\u001b[0m: x and y must have same first dimension, but have shapes (500,) and (1,)"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 864x288 with 1 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\n"},"metadata":{}}]},{"cell_type":"code","source":[],"metadata":{"id":"QM7C48zMUXsg"},"execution_count":null,"outputs":[]}],"metadata":{"colab":{"provenance":[{"file_id":"1DvVw2yaLwXneZyhJY-loghTIFeFifi8f","timestamp":1663605380532}]},"kernelspec":{"display_name":"Python 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