WD_Scenario_Builder_Monthly2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pandas.tseries.offsets import MonthEnd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn import linear_model\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "from sklearn. metrics import accuracy_score\n",
    "from sklearn import metrics\n",
    "from sklearn.metrics import r2_score\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn import metrics\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.utils import resample\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.model_selection import LeaveOneOut\n",
    "from sklearn import preprocessing\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "from sklearn.pipeline import make_pipeline\n",
    "import seaborn as sns; sns.set()\n",
    "import joblib\n",
    "from sklearn.linear_model import LassoCV\n",
    "from sklearn.datasets import make_regression\n",
    "from pathlib import Path\n",
    "import copy\n",
    "\n",
    "#Trying out recusive feature elimination to compare with step wise regression\n",
    "from sklearn.feature_selection import RFE\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.model_selection import KFold\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.pipeline import make_pipeline\n",
    "import sklearn\n",
    "\n",
    "from progressbar import ProgressBar\n",
    "\n",
    "\n",
    "\n",
    "import datetime\n",
    "import calendar\n",
    "\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "\n",
    "#need to make daily demand forecasts for each 18yr time block\n",
    "def IndexOffset(df, yr):\n",
    "    df.index = df.index+pd.offsets.DateOffset(years=yr)\n",
    "    return df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "#this function selects the scenario and makes a df to compare to preditcions and adjust\n",
    "def DemandOffset(Demand_Forecast, MLR, YR, months, pred, Out_Demand, begdate, enddate, PrePeakFact, PostPeakFact):\n",
    "    \n",
    "    #select forecasts dates\n",
    "    OGOut_Demand = Out_Demand.loc[str(YR)+begdate:str(YR)+enddate].copy()\n",
    "\n",
    "    ForecastAnalysis = pd.DataFrame(Demand_Forecast['SLC_OutdoorDemand'][str(YR)+begdate:str(YR)+enddate])\n",
    "    #Take the mean monthly values, these will be compared against mean monthly prediction/observeations\n",
    "    ForecastAnalysis = ForecastAnalysis.resample('M').mean()\n",
    "    ForecastAnalysis['Interpolated_Mean_Demand'] =ForecastAnalysis['SLC_OutdoorDemand'].copy()\n",
    "    del ForecastAnalysis['SLC_OutdoorDemand']\n",
    "\n",
    "    \n",
    "    #print('The Forecast Length is: ', len(ForecastAnalysis))\n",
    "     \n",
    "    df = copy.deepcopy(MLR)\n",
    "    newdf = []\n",
    "    #Get the actual mean monthly prediction/observation\n",
    "    for i in months:\n",
    "        df[i].index =df[i].index.year\n",
    "        df[i] = df[i].loc[YR]\n",
    "        newdf = newdf + df[i][pred].to_list()\n",
    "    #add the observed/predictions to Forecast df \n",
    "    #Offset the date in ForecastAnalysis to begin putting data back together\n",
    "    #Need to add indices/copy values to match new Out_Demands  \n",
    "\n",
    "    ForecastAnalysis.index = ForecastAnalysis.index - pd.DateOffset(days=15)\n",
    "\n",
    "    ForecastAnalysis2 = ForecastAnalysis.copy()\n",
    "    ForecastAnalysis2.index = ForecastAnalysis2.index - pd.DateOffset(days=1)\n",
    "    ForecastAnalysis2.loc[:str(YR)+'-07-31'] =ForecastAnalysis2.loc[:str(YR)+'-07-31']*PrePeakFact[0]\n",
    "    ForecastAnalysis2.loc[str(YR)+'-07-31':] =ForecastAnalysis2.loc[str(YR)+'-07-31':]*PostPeakFact[0]\n",
    "    \n",
    "    ForecastAnalysis3 = ForecastAnalysis.copy()\n",
    "    ForecastAnalysis3.index = ForecastAnalysis3.index + pd.DateOffset(days=1)\n",
    "    ForecastAnalysis3.loc[:str(YR)+'-07-31'] =ForecastAnalysis3.loc[:str(YR)+'-07-31']*PrePeakFact[2]\n",
    "    ForecastAnalysis3.loc[str(YR)+'-07-31':] =ForecastAnalysis3.loc[str(YR)+'-07-31':]*PostPeakFact[2]    \n",
    "    \n",
    "    ForecastAnalysis4 = ForecastAnalysis.copy()\n",
    "    ForecastAnalysis4.index = ForecastAnalysis4.index + pd.DateOffset(days=2)\n",
    "    ForecastAnalysis4.loc[:str(YR)+'-07-31'] =ForecastAnalysis4.loc[:str(YR)+'-07-31']*PrePeakFact[3]\n",
    "    ForecastAnalysis4.loc[str(YR)+'-07-31':] =ForecastAnalysis4.loc[str(YR)+'-07-31':]*PostPeakFact[3]  \n",
    "    \n",
    "    ForecastAnalysis.loc[:str(YR)+'-07-31'] =ForecastAnalysis.loc[:str(YR)+'-07-31']*PrePeakFact[1]\n",
    "    ForecastAnalysis.loc[str(YR)+'-07-31':] =ForecastAnalysis.loc[str(YR)+'-07-31':]*PostPeakFact[1] \n",
    "    \n",
    "    ForecastAnalysis = ForecastAnalysis.append(ForecastAnalysis2).sort_index() \n",
    "    ForecastAnalysis = ForecastAnalysis.append(ForecastAnalysis3).sort_index() \n",
    "    ForecastAnalysis = ForecastAnalysis.append(ForecastAnalysis4).sort_index()\n",
    "    ForecastAnalysis['Goal']= newdf \n",
    "   \n",
    "    #Find the difference to offset the new predictions\n",
    "    ForecastAnalysis['Diff'] = ForecastAnalysis['Goal'] - ForecastAnalysis['Interpolated_Mean_Demand']\n",
    "    \n",
    "    \n",
    "    #set Forecast1 to same index as Out_Demand\n",
    "    Out_Demand = pd.DataFrame(Out_Demand[pred][str(YR)+begdate:str(YR)+enddate]) \n",
    "    ForecastAnalysis.index = Out_Demand.index\n",
    "    \n",
    "    \n",
    "    #Adjust/offset the MLR_Out_Demand to fix the mean monthly demand (make very close to predictions/observations)\n",
    "    Out_Demand[pred] = Out_Demand[pred]+ ForecastAnalysis['Diff']/2\n",
    "    \n",
    "    #make non zero values zero\n",
    "    Out_Demand[Out_Demand<0]=0\n",
    "    #show the modified outdemand as part of the forecast stats\n",
    "    ForecastAnalysis['OGOut_Demand'] = OGOut_Demand[pred]\n",
    "    ForecastAnalysis['NewOut_Demand'] = Out_Demand[pred]\n",
    "    #make non zero values zero\n",
    "    print('Analysis of the means:')\n",
    "    print(pd.DataFrame(ForecastAnalysis))\n",
    "    \n",
    "    return Out_Demand\n",
    "\n",
    "def DemandIterationAllyrs(iteration, DemandPlot, Demand_Forecast, MLR, YR, months, pred, Out_Demand, begdate, enddate, DemandOffset, Years, PrePeakFact, PostPeakFact):\n",
    "    \n",
    "    #This function evaluates the iteratted means with the predicted means to modify the interpolation to match mean monthly predictions\n",
    "    Out_Demand2 = DemandOffset(Demand_Forecast, MLR, YR, months, pred, Out_Demand, begdate, enddate, PrePeakFact, PostPeakFact)\n",
    "    #print('The new forecast monthly means are:')\n",
    "    #print(Out_Demand2)\n",
    "    \n",
    "    Out_Demand3 = Out_Demand2.copy()\n",
    "\n",
    "   # print('OutDemand3 Before adding days is ')\n",
    "    #print(Out_Demand3.loc[str(YR)+'-4-1': str(YR)+\"-5-30\"])\n",
    "    #interpolate between end of months to have better daily data\n",
    "    Out_Demand3 = Out_Demand3.reindex(pd.date_range(start=Out_Demand3.index.min(),\n",
    "                                                      end=Out_Demand3.index.max(),\n",
    "                                                      freq='3D'))\n",
    "    #print('OutDemand3 After adding 3days is ')\n",
    "    #print(Out_Demand3.loc[str(YR)+'-4-1': str(YR)+\"-5-30\"])\n",
    "    Y = [Years]\n",
    "    for y in Y:\n",
    "        Out_Demand3[pred].loc[str(y)+'-1-01': str(y)+\"-3-30\"] = 0\n",
    "        Out_Demand3[pred].loc[str(y)+'-11-01': str(y)+\"-12-30\"] = 0\n",
    "        #the spline order = 2 adds some demand pre April, however I think this is good as it adds a bit\n",
    "    #of demand variability in the early months--Use this for the low flow scenario\n",
    "    Out_Demand3 = Out_Demand3.interpolate(method= 'spline', order = 3)\n",
    "    \n",
    "    Out_Demand3 = Out_Demand3.reindex(pd.date_range(start=Out_Demand3.index.min(),\n",
    "                                                      end=Out_Demand3.index.max(),\n",
    "                                                      freq='2D'))\n",
    "    Y = [Years]\n",
    "    for y in Y:\n",
    "        Out_Demand3[pred].loc[str(y)+'-1-01': str(y)+\"-3-30\"] = 0\n",
    "        Out_Demand3[pred].loc[str(y)+'-11-01': str(y)+\"-12-30\"] = 0\n",
    "    Out_Demand3 = Out_Demand3.interpolate(method= 'spline', order = 3)\n",
    "    \n",
    "    Out_Demand3 = Out_Demand3.reindex(pd.date_range(start=Out_Demand3.index.min(),\n",
    "                                                      end=Out_Demand3.index.max(),\n",
    "                                                      freq='1D'))\n",
    "    Y = [Years]\n",
    "    for y in Y:\n",
    "        Out_Demand3[pred].loc[str(y)+'-1-01': str(y)+\"-3-30\"] = 0\n",
    "        Out_Demand3[pred].loc[str(y)+'-11-01': str(y)+\"-12-30\"] = 0\n",
    "    Out_Demand3 = Out_Demand3.interpolate(method= 'spline', order = 3)\n",
    "\n",
    "    Out_Demand3['SLC_OutdoorDemand'] = Out_Demand3[pred].copy()\n",
    "    del Out_Demand3[pred]\n",
    "\n",
    "    Out_Demand3 = pd.DataFrame(Out_Demand3)\n",
    "\n",
    "    #Fix interpolations errors with demands\n",
    "    Out_Demand3.SLC_OutdoorDemand.loc[str(YR)+'-1-01': str(YR)+\"-3-30\"] = 0\n",
    "    Out_Demand3.SLC_OutdoorDemand.loc[str(YR)+'-11-01': str(YR)+\"-12-30\"] = 0\n",
    "    Out_Demand3[Out_Demand3 < 0]=0\n",
    "    \n",
    "    #make a plot of the iterations\n",
    "    DemandPlot['Iteration_'+str(iteration)]=Out_Demand3.SLC_OutdoorDemand.loc[str(YR)+'-4-01': str(YR)+\"-11-15\"]\n",
    "    \n",
    "\n",
    "\n",
    "    #Update the water demand time series with forecasted values\n",
    "    Demand_Forecast.update(Out_Demand3)\n",
    "    return Demand_Forecast, Out_Demand2, DemandPlot\n",
    "\n",
    "\n",
    "def Obs_Demand(Demand_Forecast, yr, Scenario, cities):\n",
    "    #need to make observed demand dataframes for goldsim\n",
    "    sim = Demand_Forecast.loc[str(yr)+'-01-01':str(yr)+'-12-30'].copy()\n",
    "    yroffset = 2021-yr\n",
    "    sim.index = sim.index + pd.DateOffset(years = yroffset)\n",
    "    sim = sim[~sim.index.duplicated(keep='first')]\n",
    "    #print(sim.loc['2021-02-01':'2021-03-01'])\n",
    "    Demand_Forecast.update(sim)\n",
    "    for i in cities:\n",
    "        Demand_Forecast[i] = Demand_Forecast['SLC_OutdoorDemand'].copy()\n",
    "\n",
    "    #Save dataframe\n",
    "    Demand_Forecast.to_excel('C:/Users/rjohnson18/Box/Dissertation/Paper2/Data/Demand_Forecast/'+Scenario+'.xlsx')\n",
    "    print('Done with simulation demand set up')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "p = Path('C:/Users/rjohnson18/Box/Dissertation/Paper1/Data/Processed_Training_Data')\n",
    "#Load historical data\n",
    "slc = {i.stem[0:3] : pd.read_excel(i) for i in p.glob('**/*.xlsx')}\n",
    "\n",
    "#load model predictions and place into desired year\n",
    "MLR2 = np.load('C:/Users/rjohnson18/Box/Dissertation/Paper1/Python/ModelOutput/Slc_Pred.npy',allow_pickle=True).item()\n",
    "MLR = np.load('C:/Users/rjohnson18/Box/Dissertation/Paper1/Python/ModelOutput/Slc_Pred_Low_Ave_High_WY.npy',allow_pickle=True).item()\n",
    "MLR_E = np.load('C:/Users/rjohnson18/Box/Dissertation/Paper1/Python/ModelOutput/Slc_Pred_Uncertainty.npy', allow_pickle =True).item()\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>y_test</th>\n",
       "      <th>y_pred</th>\n",
       "      <th>y_pred_lower</th>\n",
       "      <th>y_pred_upper</th>\n",
       "      <th>y_test_tot</th>\n",
       "      <th>y_pred_tot</th>\n",
       "      <th>y_pred_lower_tot</th>\n",
       "      <th>y_pred_upper_tot</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",
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       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2008-04-30</th>\n",
       "      <td>2008</td>\n",
       "      <td>9.222</td>\n",
       "      <td>19.508404</td>\n",
       "      <td>14.798673</td>\n",
       "      <td>24.259356</td>\n",
       "      <td>160.030</td>\n",
       "      <td>145.299068</td>\n",
       "      <td>140.589338</td>\n",
       "      <td>150.050021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-30</th>\n",
       "      <td>2015</td>\n",
       "      <td>26.980</td>\n",
       "      <td>41.101437</td>\n",
       "      <td>20.734183</td>\n",
       "      <td>61.907437</td>\n",
       "      <td>139.970</td>\n",
       "      <td>153.009799</td>\n",
       "      <td>132.642545</td>\n",
       "      <td>173.815799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-30</th>\n",
       "      <td>2017</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.533604</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>16.551459</td>\n",
       "      <td>120.354</td>\n",
       "      <td>108.475593</td>\n",
       "      <td>107.941989</td>\n",
       "      <td>124.493448</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "            Year  y_test     y_pred  y_pred_lower  y_pred_upper  y_test_tot  \\\n",
       "Date                                                                          \n",
       "2008-04-30  2008   9.222  19.508404     14.798673     24.259356     160.030   \n",
       "2015-04-30  2015  26.980  41.101437     20.734183     61.907437     139.970   \n",
       "2017-04-30  2017   0.000   0.533604      0.000000     16.551459     120.354   \n",
       "\n",
       "            y_pred_tot  y_pred_lower_tot  y_pred_upper_tot  \n",
       "Date                                                        \n",
       "2008-04-30  145.299068        140.589338        150.050021  \n",
       "2015-04-30  153.009799        132.642545        173.815799  \n",
       "2017-04-30  108.475593        107.941989        124.493448  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MLR_E['Apr']"
   ]
  },
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "#monthly demand factors\n",
    "#PrePeakFact = [.985,.995,1.005,1.015]\n",
    "#PostPeakFact = [1.015,1.005,.995,.985]\n",
    "\n",
    "PrePeakFact = [1,1,1,1]\n",
    "PostPeakFact = [1,1,1,1]\n",
    "\n",
    "\n",
    "#need to subtract indoor demands from outdoor and make indoor months 0\n",
    "Ind_Mon = ['Nov', 'Dec', 'Jan', 'Feb', 'Mar']\n",
    "\n",
    "#make indoor df\n",
    "Ind_Dem = pd.DataFrame()\n",
    "\n",
    "for i in Ind_Mon:\n",
    "    slc[i].index = slc[i]['Year']\n",
    "    slc[i] = slc[i][str(i)+'_gpcd']\n",
    "    slc[i] = pd.DataFrame(slc[i])\n",
    "    Ind_Dem = pd.concat([Ind_Dem, slc[i].copy()], axis=1)\n",
    "    \n",
    "    #now need to set slc indoor demand to zero for input into outdoor demands\n",
    "    slc[i][str(i)+'_gpcd'] = 0\n",
    "    slc[i] = slc[i].reset_index()\n",
    "\n",
    "    \n",
    "#now need to get row averages\n",
    "#Ind_Dem = Ind_Dem.loc[2000:]\n",
    "Ind_Dem['Mean_Indoor'] = Ind_Dem.mean(axis=1)\n",
    "ave_ind = list(Ind_Dem['Mean_Indoor'])\n",
    "\n",
    "\n",
    "\n",
    "Demand_Forecast = pd.DataFrame()\n",
    "Demand_Month = pd.DataFrame()\n",
    "#rename the gpcd column\n",
    "for i in slc:\n",
    "    slc[i].rename(columns={i+'_gpcd': 'Obs_gpcd'}, inplace=True)\n",
    "    slc[i]['Obs_gpcd'] = slc[i]['Obs_gpcd'] - ave_ind\n",
    "    slc[i].loc[slc[i]['Obs_gpcd'] < 0, 'Obs_gpcd'] = 0\n",
    "    slc[i]=slc[i].set_index('Year')\n",
    "    slc[i]=slc[i]['Obs_gpcd']\n",
    "    slc[i]=pd.DataFrame(slc[i].loc[2000:])\n",
    "    \n",
    "    #input the middle of month date to set up regressions between\n",
    "    slc[i]['Month'] = pd.to_datetime(i, format='%b').month\n",
    "    slc[i]['Year'] = slc[i].index\n",
    "    slc[i]['Date'] = slc[i]['Year'].map(str)+ '-' + slc[i]['Month'].map(str) \n",
    "    slc[i]['Date'] = pd.to_datetime(pd.to_datetime(slc[i]['Date']), format=\"%Y%m\") + MonthEnd(1)\n",
    "    slc[i].index = slc[i]['Date']\n",
    "    \n",
    "    #Since this is the mean, it will form the middle of the month\n",
    "    slc[i].index = slc[i].index - pd.DateOffset(days=15)\n",
    "    \n",
    "    #drop columns\n",
    "    coldrop = ['Month', 'Year', 'Date']\n",
    "    slc[i] = slc[i].drop(columns = coldrop)\n",
    "    \n",
    "    #Adjust when we want the mean to occur\n",
    "    if i == 'Apr':\n",
    "        slc[i].index = slc[i].index + pd.DateOffset(days=0)\n",
    "    elif i == 'May':\n",
    "        slc[i].index = slc[i].index - pd.DateOffset(days=0)\n",
    "    elif i == 'Jun':\n",
    "        slc[i].index = slc[i].index + pd.DateOffset(days=0)\n",
    "    elif i == 'Jul':\n",
    "        slc[i].index = slc[i].index + pd.DateOffset(days=0)\n",
    "    elif i == 'Aug':\n",
    "        slc[i].index = slc[i].index - pd.DateOffset(days=0)\n",
    "    elif i == 'Sep':\n",
    "        slc[i].index = slc[i].index - pd.DateOffset(days=0)\n",
    "    elif i == 'Oct':\n",
    "        slc[i].index = slc[i].index - pd.DateOffset(days=0)\n",
    "    slc[i] = pd.DataFrame(slc[i])\n",
    "    \n",
    "    \n",
    "    slc2=copy.deepcopy(slc)\n",
    "    if i == 'Apr':\n",
    "        slc2[i].index = slc2[i].index - pd.DateOffset(days=1)\n",
    "        slc2[i]= slc2[i]['Obs_gpcd']*PrePeakFact[0]\n",
    "    if i == 'May':\n",
    "        slc2[i].index = slc2[i].index - pd.DateOffset(days=1)\n",
    "        slc2[i]= slc2[i]['Obs_gpcd']*PrePeakFact[0]\n",
    "    elif i == 'Jun':\n",
    "        slc2[i].index = slc2[i].index - pd.DateOffset(days=1)\n",
    "        slc2[i]= slc2[i]['Obs_gpcd']*PrePeakFact[0]\n",
    "    elif i == 'Jul':\n",
    "        slc2[i].index = slc2[i].index - pd.DateOffset(days=1)\n",
    "        slc2[i]= slc2[i]['Obs_gpcd']*PrePeakFact[0]\n",
    "    elif i == 'Aug':\n",
    "        slc2[i].index = slc2[i].index - pd.DateOffset(days=1)\n",
    "        slc2[i]= slc2[i]['Obs_gpcd']*PostPeakFact[0]\n",
    "    elif i == 'Sep':\n",
    "        slc2[i].index = slc2[i].index - pd.DateOffset(days=1)\n",
    "        slc2[i]= slc2[i]['Obs_gpcd']*PostPeakFact[0]\n",
    "    elif i == 'Oct':\n",
    "        slc2[i].index = slc2[i].index - pd.DateOffset(days=1)\n",
    "        slc2[i]= slc2[i]['Obs_gpcd']*PostPeakFact[0]\n",
    "    else:\n",
    "        slc2[i].index = slc2[i].index - pd.DateOffset(days=1)\n",
    "        \n",
    "    #This adds another data point to help with demand curve, at the end of month\n",
    "    #This demand factors influences the 3rd week of the month\n",
    "    slc3=copy.deepcopy(slc)\n",
    "    if i == 'Apr':\n",
    "        slc3[i].index = slc3[i].index + pd.DateOffset(days=1)\n",
    "        slc3[i]= slc3[i]['Obs_gpcd']*PrePeakFact[2]\n",
    "    elif i == 'May':\n",
    "        slc3[i].index = slc3[i].index + pd.DateOffset(days=1)\n",
    "        slc3[i]= slc3[i]['Obs_gpcd']*PrePeakFact[2]\n",
    "    elif i == 'Jun':\n",
    "        slc3[i].index = slc3[i].index + pd.DateOffset(days=1)\n",
    "        slc3[i]= slc3[i]['Obs_gpcd']*PrePeakFact[2]\n",
    "    elif i == 'Jul':\n",
    "        slc3[i].index = slc3[i].index + pd.DateOffset(days=1)\n",
    "        slc3[i]= slc3[i]['Obs_gpcd']*PrePeakFact[2]\n",
    "    elif i == 'Aug':\n",
    "        slc3[i].index = slc3[i].index + pd.DateOffset(days=1)\n",
    "        slc3[i]= slc3[i]['Obs_gpcd']*PostPeakFact[2]\n",
    "    elif i == 'Sep':\n",
    "        slc3[i].index = slc3[i].index + pd.DateOffset(days=1)\n",
    "        slc3[i]= slc3[i]['Obs_gpcd']*PostPeakFact[2]\n",
    "    elif i == 'Oct':\n",
    "        slc3[i].index = slc3[i].index + pd.DateOffset(days=1)\n",
    "        slc3[i]= slc3[i]['Obs_gpcd']*PostPeakFact[2]\n",
    "    else:\n",
    "        slc3[i].index = slc3[i].index + pd.DateOffset(days=1)\n",
    "        \n",
    "        \n",
    "    #This adds another data point to help with demand curve, at the end of month\n",
    "    #This demand factor influences the last week of the month\n",
    "    slc4=copy.deepcopy(slc)\n",
    "    if i == 'Apr':\n",
    "        slc4[i].index = slc4[i].index + pd.DateOffset(days=2)\n",
    "        slc4[i]= slc4[i]['Obs_gpcd']*PrePeakFact[3]\n",
    "    elif i == 'May':\n",
    "        slc4[i].index = slc4[i].index + pd.DateOffset(days=2)\n",
    "        slc4[i]= slc4[i]['Obs_gpcd']*PrePeakFact[3]\n",
    "    elif i == 'Jun':\n",
    "        slc4[i].index = slc4[i].index + pd.DateOffset(days=2)\n",
    "        slc4[i]= slc4[i]['Obs_gpcd']*PrePeakFact[3]\n",
    "    elif i == 'Jul':\n",
    "        slc4[i].index = slc4[i].index + pd.DateOffset(days=2)\n",
    "        slc4[i]= slc4[i]['Obs_gpcd']*PrePeakFact[3]\n",
    "    elif i == 'Aug':\n",
    "        slc4[i].index = slc4[i].index + pd.DateOffset(days=2)\n",
    "        slc4[i]= slc4[i]['Obs_gpcd']*PostPeakFact[3]\n",
    "    elif i == 'Sep':\n",
    "        slc4[i].index = slc4[i].index + pd.DateOffset(days=2)\n",
    "        slc4[i]= slc4[i]['Obs_gpcd']*PostPeakFact[3]\n",
    "    elif i == 'Oct':\n",
    "        slc4[i].index = slc4[i].index + pd.DateOffset(days=2)\n",
    "        slc4[i]= slc4[i]['Obs_gpcd']*PostPeakFact[3]\n",
    "    else:\n",
    "        slc4[i].index = slc4[i].index + pd.DateOffset(days=2)\n",
    "        \n",
    "        \n",
    "    if i == 'Apr':\n",
    "        slc[i]= slc[i]['Obs_gpcd']*PrePeakFact[1]\n",
    "    elif i == 'May':\n",
    "        slc[i]= slc[i]['Obs_gpcd']*PrePeakFact[1]\n",
    "    elif i == 'Jun':\n",
    "        slc[i]= slc[i]['Obs_gpcd']*PrePeakFact[1]\n",
    "    elif i == 'Jul':\n",
    "        slc[i]= slc[i]['Obs_gpcd']*PrePeakFact[1]\n",
    "    elif i == 'Aug':\n",
    "        slc[i]= slc[i]['Obs_gpcd']*PostPeakFact[1]\n",
    "    elif i == 'Sep':\n",
    "        slc[i]= slc[i]['Obs_gpcd']*PostPeakFact[1]\n",
    "    elif i == 'Oct':\n",
    "        slc[i]= slc[i]['Obs_gpcd']*PostPeakFact[1]\n",
    "    slc[i] = pd.DataFrame(slc[i])\n",
    "        \n",
    "    #connect DF's and drop duplicate indices\n",
    "    slc[i] =pd.DataFrame(slc[i])\n",
    "    Demand_Month = Demand_Month.append(pd.DataFrame(slc[i]))\n",
    "    Demand_Month = Demand_Month.sort_index()\n",
    "    slc2[i] =pd.DataFrame(slc2[i])\n",
    "    slc3[i] =pd.DataFrame(slc3[i])\n",
    "    slc4[i] =pd.DataFrame(slc4[i])\n",
    "    slc[i] = slc[i].append(slc2[i]).sort_index()\n",
    "    slc[i] = slc[i].append(slc3[i]).sort_index()\n",
    "    slc[i] = slc[i].append(slc4[i]).sort_index()\n",
    "   # slc[i] = slc[i][~slc[i].index.duplicated(keep='first')]    \n",
    "        \n",
    "    Demand_Forecast = Demand_Forecast.append(pd.DataFrame(slc[i]))\n",
    "    Out_Demand=Demand_Forecast.copy()\n",
    "    Out_Demand = Out_Demand.sort_index()\n",
    "    \n",
    "Demand_Forecast = Demand_Forecast.sort_index()\n",
    "Demand_Forecast['SLC_OutdoorDemand'] = Demand_Forecast['Obs_gpcd'].copy()\n",
    "del Demand_Forecast['Obs_gpcd']\n",
    "\n",
    "#interpolate between end of months to have better daily data\n",
    "Demand_Forecast = Demand_Forecast.reindex(pd.date_range(start=Demand_Forecast.index.min(),\n",
    "                                                  end=Demand_Forecast.index.max(),\n",
    "                                                  freq='3D'))\n",
    "Demand_Forecast = Demand_Forecast.interpolate(method='spline', order=5) \n",
    "\n",
    "#now linearly interpolate between values\n",
    "Demand_Forecast = Demand_Forecast.reindex(pd.date_range(start=Demand_Forecast.index.min(),\n",
    "                                                  end=Demand_Forecast.index.max(),\n",
    "                                                  freq='2D'))\n",
    "Demand_Forecast = Demand_Forecast.interpolate(method='spline', order=5) \n",
    "\n",
    "Demand_Forecast = Demand_Forecast.reindex(pd.date_range(start=Demand_Forecast.index.min(),\n",
    "                                                  end=Demand_Forecast.index.max(),\n",
    "                                                  freq='1D'))\n",
    "Demand_Forecast = Demand_Forecast.interpolate(method='spline', order=5) \n",
    "\n",
    "#Fix interpolations errors with demands\n",
    "Demand_Forecast[Demand_Forecast < 0]=0\n",
    "\n",
    "#2006 and 2010 data are missing. need to fill them with nearby demands with nearby years\n",
    "Demand2006 = Demand_Forecast.loc['2005-1-1':'2005-12-30'].copy()\n",
    "Demand2010 = Demand_Forecast.loc['2009-1-1':'2009-12-30'].copy() \n",
    "\n",
    "#add a year to the index\n",
    "Demand2006 = IndexOffset(Demand2006, 1)\n",
    "Demand2010 = IndexOffset(Demand2010, 1)\n",
    "\n",
    "#need to updated the rows in Demand_Forecast now\n",
    "Demand_Forecast.update(Demand2006)\n",
    "Demand_Forecast.update(Demand2010)\n",
    "\n",
    "Demand_Forecast.SLC_OutdoorDemand.loc['2001-1-01': \"2001-12-30\"].plot.line()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                     \n",
      "2003-01-15                  1.507644    0.000  -1.507644         0.000   \n",
      "2003-01-16                  1.507644    0.000  -1.507644         0.000   \n",
      "2003-01-17                  1.507644    0.000  -1.507644         0.000   \n",
      "2003-01-18                  1.507644    0.000  -1.507644         0.000   \n",
      "2003-02-12                  0.573693    0.000  -0.573693         0.000   \n",
      "2003-02-13                  0.573693    0.000  -0.573693         0.000   \n",
      "2003-02-14                  0.573693    0.000  -0.573693         0.000   \n",
      "2003-02-15                  0.573693    0.000  -0.573693         0.000   \n",
      "2003-03-15                  1.484792    0.000  -1.484792         0.000   \n",
      "2003-03-16                  1.484792    0.000  -1.484792         0.000   \n",
      "2003-03-17                  1.484792    0.000  -1.484792         0.000   \n",
      "2003-03-18                  1.484792    0.000  -1.484792         0.000   \n",
      "2003-04-13                  7.907961    2.752  -5.155961         2.752   \n",
      "2003-04-15                  7.907961    2.752  -5.155961         2.752   \n",
      "2003-04-16                  7.907961    2.752  -5.155961         2.752   \n",
      "2003-04-17                  7.907961    2.752  -5.155961         2.752   \n",
      "2003-05-15                100.960974  102.812   1.851026       102.812   \n",
      "2003-05-16                100.960974  102.812   1.851026       102.812   \n",
      "2003-05-17                100.960974  102.812   1.851026       102.812   \n",
      "2003-05-18                100.960974  102.812   1.851026       102.812   \n",
      "2003-06-14                274.705836  278.802   4.096164       278.802   \n",
      "2003-06-15                274.705836  278.802   4.096164       278.802   \n",
      "2003-06-16                274.705836  278.802   4.096164       278.802   \n",
      "2003-06-17                274.705836  278.802   4.096164       278.802   \n",
      "2003-07-15                380.790026  391.662  10.871974       391.662   \n",
      "2003-07-16                380.790026  391.662  10.871974       391.662   \n",
      "2003-07-17                380.790026  391.662  10.871974       391.662   \n",
      "2003-07-18                380.790026  391.662  10.871974       391.662   \n",
      "2003-08-15                334.976536  343.682   8.705464       343.682   \n",
      "2003-08-16                334.976536  343.682   8.705464       343.682   \n",
      "2003-08-17                334.976536  343.682   8.705464       343.682   \n",
      "2003-08-18                334.976536  343.682   8.705464       343.682   \n",
      "2003-09-14                226.530437  217.222  -9.308437       217.222   \n",
      "2003-09-15                226.530437  217.222  -9.308437       217.222   \n",
      "2003-09-16                226.530437  217.222  -9.308437       217.222   \n",
      "2003-09-17                226.530437  217.222  -9.308437       217.222   \n",
      "2003-10-15                134.102350  131.582  -2.520350       131.582   \n",
      "2003-10-16                134.102350  131.582  -2.520350       131.582   \n",
      "2003-10-17                134.102350  131.582  -2.520350       131.582   \n",
      "2003-10-18                134.102350  131.582  -2.520350       131.582   \n",
      "2003-11-14                 11.414816    0.000 -11.414816         0.000   \n",
      "2003-11-15                 11.414816    0.000 -11.414816         0.000   \n",
      "2003-11-16                 11.414816    0.000 -11.414816         0.000   \n",
      "2003-11-17                 11.414816    0.000 -11.414816         0.000   \n",
      "2003-12-15                  0.710775    0.000  -0.710775         0.000   \n",
      "2003-12-16                  0.710775    0.000  -0.710775         0.000   \n",
      "2003-12-17                  0.710775    0.000  -0.710775         0.000   \n",
      "2003-12-18                  0.710775    0.000  -0.710775         0.000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.174019  \n",
      "2003-04-15       0.174019  \n",
      "2003-04-16       0.174019  \n",
      "2003-04-17       0.174019  \n",
      "2003-05-15     103.737513  \n",
      "2003-05-16     103.737513  \n",
      "2003-05-17     103.737513  \n",
      "2003-05-18     103.737513  \n",
      "2003-06-14     280.850082  \n",
      "2003-06-15     280.850082  \n",
      "2003-06-16     280.850082  \n",
      "2003-06-17     280.850082  \n",
      "2003-07-15     397.097987  \n",
      "2003-07-16     397.097987  \n",
      "2003-07-17     397.097987  \n",
      "2003-07-18     397.097987  \n",
      "2003-08-15     348.034732  \n",
      "2003-08-16     348.034732  \n",
      "2003-08-17     348.034732  \n",
      "2003-08-18     348.034732  \n",
      "2003-09-14     212.567782  \n",
      "2003-09-15     212.567782  \n",
      "2003-09-16     212.567782  \n",
      "2003-09-17     212.567782  \n",
      "2003-10-15     130.321825  \n",
      "2003-10-16     130.321825  \n",
      "2003-10-17     130.321825  \n",
      "2003-10-18     130.321825  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                     \n",
      "2003-01-15                  1.270985    0.000  -1.270985      0.000000   \n",
      "2003-01-16                  1.270985    0.000  -1.270985      0.000000   \n",
      "2003-01-17                  1.270985    0.000  -1.270985      0.000000   \n",
      "2003-01-18                  1.270985    0.000  -1.270985      0.000000   \n",
      "2003-02-12                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-02-13                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-02-14                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-02-15                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-03-15                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-03-16                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-03-17                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-03-18                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-04-13                 12.966366    2.752 -10.214366      0.174019   \n",
      "2003-04-15                 12.966366    2.752 -10.214366      0.174019   \n",
      "2003-04-16                 12.966366    2.752 -10.214366      0.174019   \n",
      "2003-04-17                 12.966366    2.752 -10.214366      0.174019   \n",
      "2003-05-15                111.161340  102.812  -8.349340    103.737513   \n",
      "2003-05-16                111.161340  102.812  -8.349340    103.737513   \n",
      "2003-05-17                111.161340  102.812  -8.349340    103.737513   \n",
      "2003-05-18                111.161340  102.812  -8.349340    103.737513   \n",
      "2003-06-14                273.502169  278.802   5.299831    280.850082   \n",
      "2003-06-15                273.502169  278.802   5.299831    280.850082   \n",
      "2003-06-16                273.502169  278.802   5.299831    280.850082   \n",
      "2003-06-17                273.502169  278.802   5.299831    280.850082   \n",
      "2003-07-15                382.979340  391.662   8.682660    397.097987   \n",
      "2003-07-16                382.979340  391.662   8.682660    397.097987   \n",
      "2003-07-17                382.979340  391.662   8.682660    397.097987   \n",
      "2003-07-18                382.979340  391.662   8.682660    397.097987   \n",
      "2003-08-15                344.682236  343.682  -1.000236    348.034732   \n",
      "2003-08-16                344.682236  343.682  -1.000236    348.034732   \n",
      "2003-08-17                344.682236  343.682  -1.000236    348.034732   \n",
      "2003-08-18                344.682236  343.682  -1.000236    348.034732   \n",
      "2003-09-14                213.346661  217.222   3.875339    212.567782   \n",
      "2003-09-15                213.346661  217.222   3.875339    212.567782   \n",
      "2003-09-16                213.346661  217.222   3.875339    212.567782   \n",
      "2003-09-17                213.346661  217.222   3.875339    212.567782   \n",
      "2003-10-15                112.262853  131.582  19.319147    130.321825   \n",
      "2003-10-16                112.262853  131.582  19.319147    130.321825   \n",
      "2003-10-17                112.262853  131.582  19.319147    130.321825   \n",
      "2003-10-18                112.262853  131.582  19.319147    130.321825   \n",
      "2003-11-14                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-11-15                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-11-16                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-11-17                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-12-15                  0.710775    0.000  -0.710775      0.000000   \n",
      "2003-12-16                  0.710775    0.000  -0.710775      0.000000   \n",
      "2003-12-17                  0.710775    0.000  -0.710775      0.000000   \n",
      "2003-12-18                  0.710775    0.000  -0.710775      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.000000  \n",
      "2003-04-15       0.000000  \n",
      "2003-04-16       0.000000  \n",
      "2003-04-17       0.000000  \n",
      "2003-05-15      99.562843  \n",
      "2003-05-16      99.562843  \n",
      "2003-05-17      99.562843  \n",
      "2003-05-18      99.562843  \n",
      "2003-06-14     283.499998  \n",
      "2003-06-15     283.499998  \n",
      "2003-06-16     283.499998  \n",
      "2003-06-17     283.499998  \n",
      "2003-07-15     401.439317  \n",
      "2003-07-16     401.439317  \n",
      "2003-07-17     401.439317  \n",
      "2003-07-18     401.439317  \n",
      "2003-08-15     347.534614  \n",
      "2003-08-16     347.534614  \n",
      "2003-08-17     347.534614  \n",
      "2003-08-18     347.534614  \n",
      "2003-09-14     214.505451  \n",
      "2003-09-15     214.505451  \n",
      "2003-09-16     214.505451  \n",
      "2003-09-17     214.505451  \n",
      "2003-10-15     139.981399  \n",
      "2003-10-16     139.981399  \n",
      "2003-10-17     139.981399  \n",
      "2003-10-18     139.981399  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                     \n",
      "2003-01-15                  1.270985    0.000  -1.270985      0.000000   \n",
      "2003-01-16                  1.270985    0.000  -1.270985      0.000000   \n",
      "2003-01-17                  1.270985    0.000  -1.270985      0.000000   \n",
      "2003-01-18                  1.270985    0.000  -1.270985      0.000000   \n",
      "2003-02-12                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-02-13                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-02-14                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-02-15                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-03-15                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-03-16                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-03-17                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-03-18                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-04-13                 12.652732    2.752  -9.900732      0.000000   \n",
      "2003-04-15                 12.652732    2.752  -9.900732      0.000000   \n",
      "2003-04-16                 12.652732    2.752  -9.900732      0.000000   \n",
      "2003-04-17                 12.652732    2.752  -9.900732      0.000000   \n",
      "2003-05-15                107.937703  102.812  -5.125703     99.562843   \n",
      "2003-05-16                107.937703  102.812  -5.125703     99.562843   \n",
      "2003-05-17                107.937703  102.812  -5.125703     99.562843   \n",
      "2003-05-18                107.937703  102.812  -5.125703     99.562843   \n",
      "2003-06-14                275.611186  278.802   3.190814    283.499998   \n",
      "2003-06-15                275.611186  278.802   3.190814    283.499998   \n",
      "2003-06-16                275.611186  278.802   3.190814    283.499998   \n",
      "2003-06-17                275.611186  278.802   3.190814    283.499998   \n",
      "2003-07-15                386.749267  391.662   4.912733    401.439317   \n",
      "2003-07-16                386.749267  391.662   4.912733    401.439317   \n",
      "2003-07-17                386.749267  391.662   4.912733    401.439317   \n",
      "2003-07-18                386.749267  391.662   4.912733    401.439317   \n",
      "2003-08-15                344.596345  343.682  -0.914345    347.534614   \n",
      "2003-08-16                344.596345  343.682  -0.914345    347.534614   \n",
      "2003-08-17                344.596345  343.682  -0.914345    347.534614   \n",
      "2003-08-18                344.596345  343.682  -0.914345    347.534614   \n",
      "2003-09-14                215.783397  217.222   1.438603    214.505451   \n",
      "2003-09-15                215.783397  217.222   1.438603    214.505451   \n",
      "2003-09-16                215.783397  217.222   1.438603    214.505451   \n",
      "2003-09-17                215.783397  217.222   1.438603    214.505451   \n",
      "2003-10-15                119.668872  131.582  11.913128    139.981399   \n",
      "2003-10-16                119.668872  131.582  11.913128    139.981399   \n",
      "2003-10-17                119.668872  131.582  11.913128    139.981399   \n",
      "2003-10-18                119.668872  131.582  11.913128    139.981399   \n",
      "2003-11-14                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-11-15                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-11-16                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-11-17                  0.000000    0.000   0.000000      0.000000   \n",
      "2003-12-15                  0.710775    0.000  -0.710775      0.000000   \n",
      "2003-12-16                  0.710775    0.000  -0.710775      0.000000   \n",
      "2003-12-17                  0.710775    0.000  -0.710775      0.000000   \n",
      "2003-12-18                  0.710775    0.000  -0.710775      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.000000  \n",
      "2003-04-15       0.000000  \n",
      "2003-04-16       0.000000  \n",
      "2003-04-17       0.000000  \n",
      "2003-05-15      96.999991  \n",
      "2003-05-16      96.999991  \n",
      "2003-05-17      96.999991  \n",
      "2003-05-18      96.999991  \n",
      "2003-06-14     285.095405  \n",
      "2003-06-15     285.095405  \n",
      "2003-06-16     285.095405  \n",
      "2003-06-17     285.095405  \n",
      "2003-07-15     403.895684  \n",
      "2003-07-16     403.895684  \n",
      "2003-07-17     403.895684  \n",
      "2003-07-18     403.895684  \n",
      "2003-08-15     347.077442  \n",
      "2003-08-16     347.077442  \n",
      "2003-08-17     347.077442  \n",
      "2003-08-18     347.077442  \n",
      "2003-09-14     215.224753  \n",
      "2003-09-15     215.224753  \n",
      "2003-09-16     215.224753  \n",
      "2003-09-17     215.224753  \n",
      "2003-10-15     145.937963  \n",
      "2003-10-16     145.937963  \n",
      "2003-10-17     145.937963  \n",
      "2003-10-18     145.937963  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal      Diff  OGOut_Demand  \\\n",
      "Date                                                                    \n",
      "2003-01-15                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-16                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-17                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-18                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-02-12                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-13                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-18                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-04-13                 12.397984    2.752 -9.645984      0.000000   \n",
      "2003-04-15                 12.397984    2.752 -9.645984      0.000000   \n",
      "2003-04-16                 12.397984    2.752 -9.645984      0.000000   \n",
      "2003-04-17                 12.397984    2.752 -9.645984      0.000000   \n",
      "2003-05-15                105.992930  102.812 -3.180930     96.999991   \n",
      "2003-05-16                105.992930  102.812 -3.180930     96.999991   \n",
      "2003-05-17                105.992930  102.812 -3.180930     96.999991   \n",
      "2003-05-18                105.992930  102.812 -3.180930     96.999991   \n",
      "2003-06-14                276.950366  278.802  1.851634    285.095405   \n",
      "2003-06-15                276.950366  278.802  1.851634    285.095405   \n",
      "2003-06-16                276.950366  278.802  1.851634    285.095405   \n",
      "2003-06-17                276.950366  278.802  1.851634    285.095405   \n",
      "2003-07-15                388.783371  391.662  2.878629    403.895684   \n",
      "2003-07-16                388.783371  391.662  2.878629    403.895684   \n",
      "2003-07-17                388.783371  391.662  2.878629    403.895684   \n",
      "2003-07-18                388.783371  391.662  2.878629    403.895684   \n",
      "2003-08-15                344.375495  343.682 -0.693495    347.077442   \n",
      "2003-08-16                344.375495  343.682 -0.693495    347.077442   \n",
      "2003-08-17                344.375495  343.682 -0.693495    347.077442   \n",
      "2003-08-18                344.375495  343.682 -0.693495    347.077442   \n",
      "2003-09-14                216.817945  217.222  0.404055    215.224753   \n",
      "2003-09-15                216.817945  217.222  0.404055    215.224753   \n",
      "2003-09-16                216.817945  217.222  0.404055    215.224753   \n",
      "2003-09-17                216.817945  217.222  0.404055    215.224753   \n",
      "2003-10-15                124.140198  131.582  7.441802    145.937963   \n",
      "2003-10-16                124.140198  131.582  7.441802    145.937963   \n",
      "2003-10-17                124.140198  131.582  7.441802    145.937963   \n",
      "2003-10-18                124.140198  131.582  7.441802    145.937963   \n",
      "2003-11-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-12-15                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-16                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-17                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-18                  0.710775    0.000 -0.710775      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.000000  \n",
      "2003-04-15       0.000000  \n",
      "2003-04-16       0.000000  \n",
      "2003-04-17       0.000000  \n",
      "2003-05-15      95.409526  \n",
      "2003-05-16      95.409526  \n",
      "2003-05-17      95.409526  \n",
      "2003-05-18      95.409526  \n",
      "2003-06-14     286.021222  \n",
      "2003-06-15     286.021222  \n",
      "2003-06-16     286.021222  \n",
      "2003-06-17     286.021222  \n",
      "2003-07-15     405.334998  \n",
      "2003-07-16     405.334998  \n",
      "2003-07-17     405.334998  \n",
      "2003-07-18     405.334998  \n",
      "2003-08-15     346.730694  \n",
      "2003-08-16     346.730694  \n",
      "2003-08-17     346.730694  \n",
      "2003-08-18     346.730694  \n",
      "2003-09-14     215.426780  \n",
      "2003-09-15     215.426780  \n",
      "2003-09-16     215.426780  \n",
      "2003-09-17     215.426780  \n",
      "2003-10-15     149.658864  \n",
      "2003-10-16     149.658864  \n",
      "2003-10-17     149.658864  \n",
      "2003-10-18     149.658864  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal      Diff  OGOut_Demand  \\\n",
      "Date                                                                    \n",
      "2003-01-15                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-16                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-17                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-18                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-02-12                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-13                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-18                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-04-13                 12.261267    2.752 -9.509267      0.000000   \n",
      "2003-04-15                 12.261267    2.752 -9.509267      0.000000   \n",
      "2003-04-16                 12.261267    2.752 -9.509267      0.000000   \n",
      "2003-04-17                 12.261267    2.752 -9.509267      0.000000   \n",
      "2003-05-15                104.755149  102.812 -1.943149     95.409526   \n",
      "2003-05-16                104.755149  102.812 -1.943149     95.409526   \n",
      "2003-05-17                104.755149  102.812 -1.943149     95.409526   \n",
      "2003-05-18                104.755149  102.812 -1.943149     95.409526   \n",
      "2003-06-14                277.683530  278.802  1.118470    286.021222   \n",
      "2003-06-15                277.683530  278.802  1.118470    286.021222   \n",
      "2003-06-16                277.683530  278.802  1.118470    286.021222   \n",
      "2003-06-17                277.683530  278.802  1.118470    286.021222   \n",
      "2003-07-15                390.057776  391.662  1.604224    405.334998   \n",
      "2003-07-16                390.057776  391.662  1.604224    405.334998   \n",
      "2003-07-17                390.057776  391.662  1.604224    405.334998   \n",
      "2003-07-18                390.057776  391.662  1.604224    405.334998   \n",
      "2003-08-15                344.102092  343.682 -0.420092    346.730694   \n",
      "2003-08-16                344.102092  343.682 -0.420092    346.730694   \n",
      "2003-08-17                344.102092  343.682 -0.420092    346.730694   \n",
      "2003-08-18                344.102092  343.682 -0.420092    346.730694   \n",
      "2003-09-14                217.307674  217.222 -0.085674    215.426780   \n",
      "2003-09-15                217.307674  217.222 -0.085674    215.426780   \n",
      "2003-09-16                217.307674  217.222 -0.085674    215.426780   \n",
      "2003-09-17                217.307674  217.222 -0.085674    215.426780   \n",
      "2003-10-15                126.867570  131.582  4.714430    149.658864   \n",
      "2003-10-16                126.867570  131.582  4.714430    149.658864   \n",
      "2003-10-17                126.867570  131.582  4.714430    149.658864   \n",
      "2003-10-18                126.867570  131.582  4.714430    149.658864   \n",
      "2003-11-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-12-15                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-16                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-17                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-18                  0.710775    0.000 -0.710775      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.000000  \n",
      "2003-04-15       0.000000  \n",
      "2003-04-16       0.000000  \n",
      "2003-04-17       0.000000  \n",
      "2003-05-15      94.437952  \n",
      "2003-05-16      94.437952  \n",
      "2003-05-17      94.437952  \n",
      "2003-05-18      94.437952  \n",
      "2003-06-14     286.580457  \n",
      "2003-06-15     286.580457  \n",
      "2003-06-16     286.580457  \n",
      "2003-06-17     286.580457  \n",
      "2003-07-15     406.137110  \n",
      "2003-07-16     406.137110  \n",
      "2003-07-17     406.137110  \n",
      "2003-07-18     406.137110  \n",
      "2003-08-15     346.520648  \n",
      "2003-08-16     346.520648  \n",
      "2003-08-17     346.520648  \n",
      "2003-08-18     346.520648  \n",
      "2003-09-14     215.383943  \n",
      "2003-09-15     215.383943  \n",
      "2003-09-16     215.383943  \n",
      "2003-09-17     215.383943  \n",
      "2003-10-15     152.016079  \n",
      "2003-10-16     152.016079  \n",
      "2003-10-17     152.016079  \n",
      "2003-10-18     152.016079  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal      Diff  OGOut_Demand  \\\n",
      "Date                                                                    \n",
      "2003-01-15                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-16                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-17                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-18                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-02-12                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-13                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-18                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-04-13                 12.150020    2.752 -9.398020      0.000000   \n",
      "2003-04-15                 12.150020    2.752 -9.398020      0.000000   \n",
      "2003-04-16                 12.150020    2.752 -9.398020      0.000000   \n",
      "2003-04-17                 12.150020    2.752 -9.398020      0.000000   \n",
      "2003-05-15                104.018682  102.812 -1.206682     94.437952   \n",
      "2003-05-16                104.018682  102.812 -1.206682     94.437952   \n",
      "2003-05-17                104.018682  102.812 -1.206682     94.437952   \n",
      "2003-05-18                104.018682  102.812 -1.206682     94.437952   \n",
      "2003-06-14                278.111563  278.802  0.690437    286.580457   \n",
      "2003-06-15                278.111563  278.802  0.690437    286.580457   \n",
      "2003-06-16                278.111563  278.802  0.690437    286.580457   \n",
      "2003-06-17                278.111563  278.802  0.690437    286.580457   \n",
      "2003-07-15                390.754038  391.662  0.907962    406.137110   \n",
      "2003-07-16                390.754038  391.662  0.907962    406.137110   \n",
      "2003-07-17                390.754038  391.662  0.907962    406.137110   \n",
      "2003-07-18                390.754038  391.662  0.907962    406.137110   \n",
      "2003-08-15                343.945930  343.682 -0.263930    346.520648   \n",
      "2003-08-16                343.945930  343.682 -0.263930    346.520648   \n",
      "2003-08-17                343.945930  343.682 -0.263930    346.520648   \n",
      "2003-08-18                343.945930  343.682 -0.263930    346.520648   \n",
      "2003-09-14                217.461800  217.222 -0.239800    215.383943   \n",
      "2003-09-15                217.461800  217.222 -0.239800    215.383943   \n",
      "2003-09-16                217.461800  217.222 -0.239800    215.383943   \n",
      "2003-09-17                217.461800  217.222 -0.239800    215.383943   \n",
      "2003-10-15                128.545745  131.582  3.036255    152.016079   \n",
      "2003-10-16                128.545745  131.582  3.036255    152.016079   \n",
      "2003-10-17                128.545745  131.582  3.036255    152.016079   \n",
      "2003-10-18                128.545745  131.582  3.036255    152.016079   \n",
      "2003-11-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-12-15                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-16                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-17                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-18                  0.710775    0.000 -0.710775      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.000000  \n",
      "2003-04-15       0.000000  \n",
      "2003-04-16       0.000000  \n",
      "2003-04-17       0.000000  \n",
      "2003-05-15      93.834610  \n",
      "2003-05-16      93.834610  \n",
      "2003-05-17      93.834610  \n",
      "2003-05-18      93.834610  \n",
      "2003-06-14     286.925675  \n",
      "2003-06-15     286.925675  \n",
      "2003-06-16     286.925675  \n",
      "2003-06-17     286.925675  \n",
      "2003-07-15     406.591091  \n",
      "2003-07-16     406.591091  \n",
      "2003-07-17     406.591091  \n",
      "2003-07-18     406.591091  \n",
      "2003-08-15     346.388683  \n",
      "2003-08-16     346.388683  \n",
      "2003-08-17     346.388683  \n",
      "2003-08-18     346.388683  \n",
      "2003-09-14     215.264043  \n",
      "2003-09-15     215.264043  \n",
      "2003-09-16     215.264043  \n",
      "2003-09-17     215.264043  \n",
      "2003-10-15     153.534207  \n",
      "2003-10-16     153.534207  \n",
      "2003-10-17     153.534207  \n",
      "2003-10-18     153.534207  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal      Diff  OGOut_Demand  \\\n",
      "Date                                                                    \n",
      "2003-01-15                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-16                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-17                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-18                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-02-12                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-13                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-18                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-04-13                 12.082914    2.752 -9.330914      0.000000   \n",
      "2003-04-15                 12.082914    2.752 -9.330914      0.000000   \n",
      "2003-04-16                 12.082914    2.752 -9.330914      0.000000   \n",
      "2003-04-17                 12.082914    2.752 -9.330914      0.000000   \n",
      "2003-05-15                103.554591  102.812 -0.742591     93.834610   \n",
      "2003-05-16                103.554591  102.812 -0.742591     93.834610   \n",
      "2003-05-17                103.554591  102.812 -0.742591     93.834610   \n",
      "2003-05-18                103.554591  102.812 -0.742591     93.834610   \n",
      "2003-06-14                278.371346  278.802  0.430654    286.925675   \n",
      "2003-06-15                278.371346  278.802  0.430654    286.925675   \n",
      "2003-06-16                278.371346  278.802  0.430654    286.925675   \n",
      "2003-06-17                278.371346  278.802  0.430654    286.925675   \n",
      "2003-07-15                391.159247  391.662  0.502753    406.591091   \n",
      "2003-07-16                391.159247  391.662  0.502753    406.591091   \n",
      "2003-07-17                391.159247  391.662  0.502753    406.591091   \n",
      "2003-07-18                391.159247  391.662  0.502753    406.591091   \n",
      "2003-08-15                343.830851  343.682 -0.148851    346.388683   \n",
      "2003-08-16                343.830851  343.682 -0.148851    346.388683   \n",
      "2003-08-17                343.830851  343.682 -0.148851    346.388683   \n",
      "2003-08-18                343.830851  343.682 -0.148851    346.388683   \n",
      "2003-09-14                217.480982  217.222 -0.258982    215.264043   \n",
      "2003-09-15                217.480982  217.222 -0.258982    215.264043   \n",
      "2003-09-16                217.480982  217.222 -0.258982    215.264043   \n",
      "2003-09-17                217.480982  217.222 -0.258982    215.264043   \n",
      "2003-10-15                129.655431  131.582  1.926569    153.534207   \n",
      "2003-10-16                129.655431  131.582  1.926569    153.534207   \n",
      "2003-10-17                129.655431  131.582  1.926569    153.534207   \n",
      "2003-10-18                129.655431  131.582  1.926569    153.534207   \n",
      "2003-11-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-12-15                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-16                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-17                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-18                  0.710775    0.000 -0.710775      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.000000  \n",
      "2003-04-15       0.000000  \n",
      "2003-04-16       0.000000  \n",
      "2003-04-17       0.000000  \n",
      "2003-05-15      93.463315  \n",
      "2003-05-16      93.463315  \n",
      "2003-05-17      93.463315  \n",
      "2003-05-18      93.463315  \n",
      "2003-06-14     287.141002  \n",
      "2003-06-15     287.141002  \n",
      "2003-06-16     287.141002  \n",
      "2003-06-17     287.141002  \n",
      "2003-07-15     406.842467  \n",
      "2003-07-16     406.842467  \n",
      "2003-07-17     406.842467  \n",
      "2003-07-18     406.842467  \n",
      "2003-08-15     346.314258  \n",
      "2003-08-16     346.314258  \n",
      "2003-08-17     346.314258  \n",
      "2003-08-18     346.314258  \n",
      "2003-09-14     215.134552  \n",
      "2003-09-15     215.134552  \n",
      "2003-09-16     215.134552  \n",
      "2003-09-17     215.134552  \n",
      "2003-10-15     154.497491  \n",
      "2003-10-16     154.497491  \n",
      "2003-10-17     154.497491  \n",
      "2003-10-18     154.497491  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal      Diff  OGOut_Demand  \\\n",
      "Date                                                                    \n",
      "2003-01-15                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-16                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-17                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-18                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-02-12                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-13                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-18                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-04-13                 12.096546    2.752 -9.344546      0.000000   \n",
      "2003-04-15                 12.096546    2.752 -9.344546      0.000000   \n",
      "2003-04-16                 12.096546    2.752 -9.344546      0.000000   \n",
      "2003-04-17                 12.096546    2.752 -9.344546      0.000000   \n",
      "2003-05-15                103.338737  102.812 -0.526737     93.463315   \n",
      "2003-05-16                103.338737  102.812 -0.526737     93.463315   \n",
      "2003-05-17                103.338737  102.812 -0.526737     93.463315   \n",
      "2003-05-18                103.338737  102.812 -0.526737     93.463315   \n",
      "2003-06-14                278.517184  278.802  0.284816    287.141002   \n",
      "2003-06-15                278.517184  278.802  0.284816    287.141002   \n",
      "2003-06-16                278.517184  278.802  0.284816    287.141002   \n",
      "2003-06-17                278.517184  278.802  0.284816    287.141002   \n",
      "2003-07-15                391.332856  391.662  0.329144    406.842467   \n",
      "2003-07-16                391.332856  391.662  0.329144    406.842467   \n",
      "2003-07-17                391.332856  391.662  0.329144    406.842467   \n",
      "2003-07-18                391.332856  391.662  0.329144    406.842467   \n",
      "2003-08-15                343.789643  343.682 -0.107643    346.314258   \n",
      "2003-08-16                343.789643  343.682 -0.107643    346.314258   \n",
      "2003-08-17                343.789643  343.682 -0.107643    346.314258   \n",
      "2003-08-18                343.789643  343.682 -0.107643    346.314258   \n",
      "2003-09-14                217.372520  217.222 -0.150520    215.134552   \n",
      "2003-09-15                217.372520  217.222 -0.150520    215.134552   \n",
      "2003-09-16                217.372520  217.222 -0.150520    215.134552   \n",
      "2003-09-17                217.372520  217.222 -0.150520    215.134552   \n",
      "2003-10-15                130.195952  131.582  1.386048    154.497491   \n",
      "2003-10-16                130.195952  131.582  1.386048    154.497491   \n",
      "2003-10-17                130.195952  131.582  1.386048    154.497491   \n",
      "2003-10-18                130.195952  131.582  1.386048    154.497491   \n",
      "2003-11-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-12-15                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-16                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-17                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-18                  0.710775    0.000 -0.710775      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.000000  \n",
      "2003-04-15       0.000000  \n",
      "2003-04-16       0.000000  \n",
      "2003-04-17       0.000000  \n",
      "2003-05-15      93.199947  \n",
      "2003-05-16      93.199947  \n",
      "2003-05-17      93.199947  \n",
      "2003-05-18      93.199947  \n",
      "2003-06-14     287.283410  \n",
      "2003-06-15     287.283410  \n",
      "2003-06-16     287.283410  \n",
      "2003-06-17     287.283410  \n",
      "2003-07-15     407.007039  \n",
      "2003-07-16     407.007039  \n",
      "2003-07-17     407.007039  \n",
      "2003-07-18     407.007039  \n",
      "2003-08-15     346.260436  \n",
      "2003-08-16     346.260436  \n",
      "2003-08-17     346.260436  \n",
      "2003-08-18     346.260436  \n",
      "2003-09-14     215.059292  \n",
      "2003-09-15     215.059292  \n",
      "2003-09-16     215.059292  \n",
      "2003-09-17     215.059292  \n",
      "2003-10-15     155.190515  \n",
      "2003-10-16     155.190515  \n",
      "2003-10-17     155.190515  \n",
      "2003-10-18     155.190515  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal      Diff  OGOut_Demand  \\\n",
      "Date                                                                    \n",
      "2003-01-15                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-16                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-17                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-18                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-02-12                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-13                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-18                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-04-13                 12.067089    2.752 -9.315089      0.000000   \n",
      "2003-04-15                 12.067089    2.752 -9.315089      0.000000   \n",
      "2003-04-16                 12.067089    2.752 -9.315089      0.000000   \n",
      "2003-04-17                 12.067089    2.752 -9.315089      0.000000   \n",
      "2003-05-15                103.135194  102.812 -0.323194     93.199947   \n",
      "2003-05-16                103.135194  102.812 -0.323194     93.199947   \n",
      "2003-05-17                103.135194  102.812 -0.323194     93.199947   \n",
      "2003-05-18                103.135194  102.812 -0.323194     93.199947   \n",
      "2003-06-14                278.620596  278.802  0.181404    287.283410   \n",
      "2003-06-15                278.620596  278.802  0.181404    287.283410   \n",
      "2003-06-16                278.620596  278.802  0.181404    287.283410   \n",
      "2003-06-17                278.620596  278.802  0.181404    287.283410   \n",
      "2003-07-15                391.482319  391.662  0.179681    407.007039   \n",
      "2003-07-16                391.482319  391.662  0.179681    407.007039   \n",
      "2003-07-17                391.482319  391.662  0.179681    407.007039   \n",
      "2003-07-18                391.482319  391.662  0.179681    407.007039   \n",
      "2003-08-15                343.736295  343.682 -0.054295    346.260436   \n",
      "2003-08-16                343.736295  343.682 -0.054295    346.260436   \n",
      "2003-08-17                343.736295  343.682 -0.054295    346.260436   \n",
      "2003-08-18                343.736295  343.682 -0.054295    346.260436   \n",
      "2003-09-14                217.365633  217.222 -0.143633    215.059292   \n",
      "2003-09-15                217.365633  217.222 -0.143633    215.059292   \n",
      "2003-09-16                217.365633  217.222 -0.143633    215.059292   \n",
      "2003-09-17                217.365633  217.222 -0.143633    215.059292   \n",
      "2003-10-15                130.700078  131.582  0.881922    155.190515   \n",
      "2003-10-16                130.700078  131.582  0.881922    155.190515   \n",
      "2003-10-17                130.700078  131.582  0.881922    155.190515   \n",
      "2003-10-18                130.700078  131.582  0.881922    155.190515   \n",
      "2003-11-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-12-15                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-16                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-17                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-18                  0.710775    0.000 -0.710775      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.000000  \n",
      "2003-04-15       0.000000  \n",
      "2003-04-16       0.000000  \n",
      "2003-04-17       0.000000  \n",
      "2003-05-15      93.038350  \n",
      "2003-05-16      93.038350  \n",
      "2003-05-17      93.038350  \n",
      "2003-05-18      93.038350  \n",
      "2003-06-14     287.374112  \n",
      "2003-06-15     287.374112  \n",
      "2003-06-16     287.374112  \n",
      "2003-06-17     287.374112  \n",
      "2003-07-15     407.096880  \n",
      "2003-07-16     407.096880  \n",
      "2003-07-17     407.096880  \n",
      "2003-07-18     407.096880  \n",
      "2003-08-15     346.233289  \n",
      "2003-08-16     346.233289  \n",
      "2003-08-17     346.233289  \n",
      "2003-08-18     346.233289  \n",
      "2003-09-14     214.987475  \n",
      "2003-09-15     214.987475  \n",
      "2003-09-16     214.987475  \n",
      "2003-09-17     214.987475  \n",
      "2003-10-15     155.631477  \n",
      "2003-10-16     155.631477  \n",
      "2003-10-17     155.631477  \n",
      "2003-10-18     155.631477  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal      Diff  OGOut_Demand  \\\n",
      "Date                                                                    \n",
      "2003-01-15                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-16                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-17                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-18                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-02-12                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-13                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-18                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-04-13                 11.958917    2.752 -9.206917      0.000000   \n",
      "2003-04-15                 11.958917    2.752 -9.206917      0.000000   \n",
      "2003-04-16                 11.958917    2.752 -9.206917      0.000000   \n",
      "2003-04-17                 11.958917    2.752 -9.206917      0.000000   \n",
      "2003-05-15                103.076703  102.812 -0.264703     93.038350   \n",
      "2003-05-16                103.076703  102.812 -0.264703     93.038350   \n",
      "2003-05-17                103.076703  102.812 -0.264703     93.038350   \n",
      "2003-05-18                103.076703  102.812 -0.264703     93.038350   \n",
      "2003-06-14                278.660218  278.802  0.141782    287.374112   \n",
      "2003-06-15                278.660218  278.802  0.141782    287.374112   \n",
      "2003-06-16                278.660218  278.802  0.141782    287.374112   \n",
      "2003-06-17                278.660218  278.802  0.141782    287.374112   \n",
      "2003-07-15                391.532885  391.662  0.129115    407.096880   \n",
      "2003-07-16                391.532885  391.662  0.129115    407.096880   \n",
      "2003-07-17                391.532885  391.662  0.129115    407.096880   \n",
      "2003-07-18                391.532885  391.662  0.129115    407.096880   \n",
      "2003-08-15                343.816710  343.682 -0.134710    346.233289   \n",
      "2003-08-16                343.816710  343.682 -0.134710    346.233289   \n",
      "2003-08-17                343.816710  343.682 -0.134710    346.233289   \n",
      "2003-08-18                343.816710  343.682 -0.134710    346.233289   \n",
      "2003-09-14                217.398440  217.222 -0.176440    214.987475   \n",
      "2003-09-15                217.398440  217.222 -0.176440    214.987475   \n",
      "2003-09-16                217.398440  217.222 -0.176440    214.987475   \n",
      "2003-09-17                217.398440  217.222 -0.176440    214.987475   \n",
      "2003-10-15                130.788931  131.582  0.793069    155.631477   \n",
      "2003-10-16                130.788931  131.582  0.793069    155.631477   \n",
      "2003-10-17                130.788931  131.582  0.793069    155.631477   \n",
      "2003-10-18                130.788931  131.582  0.793069    155.631477   \n",
      "2003-11-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-12-15                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-16                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-17                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-18                  0.710775    0.000 -0.710775      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.000000  \n",
      "2003-04-15       0.000000  \n",
      "2003-04-16       0.000000  \n",
      "2003-04-17       0.000000  \n",
      "2003-05-15      92.905998  \n",
      "2003-05-16      92.905998  \n",
      "2003-05-17      92.905998  \n",
      "2003-05-18      92.905998  \n",
      "2003-06-14     287.445003  \n",
      "2003-06-15     287.445003  \n",
      "2003-06-16     287.445003  \n",
      "2003-06-17     287.445003  \n",
      "2003-07-15     407.161438  \n",
      "2003-07-16     407.161438  \n",
      "2003-07-17     407.161438  \n",
      "2003-07-18     407.161438  \n",
      "2003-08-15     346.165934  \n",
      "2003-08-16     346.165934  \n",
      "2003-08-17     346.165934  \n",
      "2003-08-18     346.165934  \n",
      "2003-09-14     214.899255  \n",
      "2003-09-15     214.899255  \n",
      "2003-09-16     214.899255  \n",
      "2003-09-17     214.899255  \n",
      "2003-10-15     156.028011  \n",
      "2003-10-16     156.028011  \n",
      "2003-10-17     156.028011  \n",
      "2003-10-18     156.028011  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal      Diff  OGOut_Demand  \\\n",
      "Date                                                                    \n",
      "2003-01-15                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-16                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-17                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-18                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-02-12                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-13                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-18                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-04-13                 11.943964    2.752 -9.191964      0.000000   \n",
      "2003-04-15                 11.943964    2.752 -9.191964      0.000000   \n",
      "2003-04-16                 11.943964    2.752 -9.191964      0.000000   \n",
      "2003-04-17                 11.943964    2.752 -9.191964      0.000000   \n",
      "2003-05-15                102.974474  102.812 -0.162474     92.905998   \n",
      "2003-05-16                102.974474  102.812 -0.162474     92.905998   \n",
      "2003-05-17                102.974474  102.812 -0.162474     92.905998   \n",
      "2003-05-18                102.974474  102.812 -0.162474     92.905998   \n",
      "2003-06-14                278.710449  278.802  0.091551    287.445003   \n",
      "2003-06-15                278.710449  278.802  0.091551    287.445003   \n",
      "2003-06-16                278.710449  278.802  0.091551    287.445003   \n",
      "2003-06-17                278.710449  278.802  0.091551    287.445003   \n",
      "2003-07-15                391.590753  391.662  0.071247    407.161438   \n",
      "2003-07-16                391.590753  391.662  0.071247    407.161438   \n",
      "2003-07-17                391.590753  391.662  0.071247    407.161438   \n",
      "2003-07-18                391.590753  391.662  0.071247    407.161438   \n",
      "2003-08-15                343.749006  343.682 -0.067006    346.165934   \n",
      "2003-08-16                343.749006  343.682 -0.067006    346.165934   \n",
      "2003-08-17                343.749006  343.682 -0.067006    346.165934   \n",
      "2003-08-18                343.749006  343.682 -0.067006    346.165934   \n",
      "2003-09-14                217.354586  217.222 -0.132586    214.899255   \n",
      "2003-09-15                217.354586  217.222 -0.132586    214.899255   \n",
      "2003-09-16                217.354586  217.222 -0.132586    214.899255   \n",
      "2003-09-17                217.354586  217.222 -0.132586    214.899255   \n",
      "2003-10-15                131.071605  131.582  0.510395    156.028011   \n",
      "2003-10-16                131.071605  131.582  0.510395    156.028011   \n",
      "2003-10-17                131.071605  131.582  0.510395    156.028011   \n",
      "2003-10-18                131.071605  131.582  0.510395    156.028011   \n",
      "2003-11-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-12-15                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-16                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-17                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-18                  0.710775    0.000 -0.710775      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.000000  \n",
      "2003-04-15       0.000000  \n",
      "2003-04-16       0.000000  \n",
      "2003-04-17       0.000000  \n",
      "2003-05-15      92.824761  \n",
      "2003-05-16      92.824761  \n",
      "2003-05-17      92.824761  \n",
      "2003-05-18      92.824761  \n",
      "2003-06-14     287.490778  \n",
      "2003-06-15     287.490778  \n",
      "2003-06-16     287.490778  \n",
      "2003-06-17     287.490778  \n",
      "2003-07-15     407.197061  \n",
      "2003-07-16     407.197061  \n",
      "2003-07-17     407.197061  \n",
      "2003-07-18     407.197061  \n",
      "2003-08-15     346.132431  \n",
      "2003-08-16     346.132431  \n",
      "2003-08-17     346.132431  \n",
      "2003-08-18     346.132431  \n",
      "2003-09-14     214.832962  \n",
      "2003-09-15     214.832962  \n",
      "2003-09-16     214.832962  \n",
      "2003-09-17     214.832962  \n",
      "2003-10-15     156.283208  \n",
      "2003-10-16     156.283208  \n",
      "2003-10-17     156.283208  \n",
      "2003-10-18     156.283208  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal      Diff  OGOut_Demand  \\\n",
      "Date                                                                    \n",
      "2003-01-15                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-16                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-17                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-18                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-02-12                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-13                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-18                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-04-13                 11.934854    2.752 -9.182854      0.000000   \n",
      "2003-04-15                 11.934854    2.752 -9.182854      0.000000   \n",
      "2003-04-16                 11.934854    2.752 -9.182854      0.000000   \n",
      "2003-04-17                 11.934854    2.752 -9.182854      0.000000   \n",
      "2003-05-15                102.911966  102.812 -0.099966     92.824761   \n",
      "2003-05-16                102.911966  102.812 -0.099966     92.824761   \n",
      "2003-05-17                102.911966  102.812 -0.099966     92.824761   \n",
      "2003-05-18                102.911966  102.812 -0.099966     92.824761   \n",
      "2003-06-14                278.742511  278.802  0.059489    287.490778   \n",
      "2003-06-15                278.742511  278.802  0.059489    287.490778   \n",
      "2003-06-16                278.742511  278.802  0.059489    287.490778   \n",
      "2003-06-17                278.742511  278.802  0.059489    287.490778   \n",
      "2003-07-15                391.624125  391.662  0.037875    407.197061   \n",
      "2003-07-16                391.624125  391.662  0.037875    407.197061   \n",
      "2003-07-17                391.624125  391.662  0.037875    407.197061   \n",
      "2003-07-18                391.624125  391.662  0.037875    407.197061   \n",
      "2003-08-15                343.712157  343.682 -0.030157    346.132431   \n",
      "2003-08-16                343.712157  343.682 -0.030157    346.132431   \n",
      "2003-08-17                343.712157  343.682 -0.030157    346.132431   \n",
      "2003-08-18                343.712157  343.682 -0.030157    346.132431   \n",
      "2003-09-14                217.319321  217.222 -0.097321    214.832962   \n",
      "2003-09-15                217.319321  217.222 -0.097321    214.832962   \n",
      "2003-09-16                217.319321  217.222 -0.097321    214.832962   \n",
      "2003-09-17                217.319321  217.222 -0.097321    214.832962   \n",
      "2003-10-15                131.252414  131.582  0.329586    156.283208   \n",
      "2003-10-16                131.252414  131.582  0.329586    156.283208   \n",
      "2003-10-17                131.252414  131.582  0.329586    156.283208   \n",
      "2003-10-18                131.252414  131.582  0.329586    156.283208   \n",
      "2003-11-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-12-15                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-16                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-17                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-18                  0.710775    0.000 -0.710775      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.000000  \n",
      "2003-04-15       0.000000  \n",
      "2003-04-16       0.000000  \n",
      "2003-04-17       0.000000  \n",
      "2003-05-15      92.774778  \n",
      "2003-05-16      92.774778  \n",
      "2003-05-17      92.774778  \n",
      "2003-05-18      92.774778  \n",
      "2003-06-14     287.520523  \n",
      "2003-06-15     287.520523  \n",
      "2003-06-16     287.520523  \n",
      "2003-06-17     287.520523  \n",
      "2003-07-15     407.215999  \n",
      "2003-07-16     407.215999  \n",
      "2003-07-17     407.215999  \n",
      "2003-07-18     407.215999  \n",
      "2003-08-15     346.117353  \n",
      "2003-08-16     346.117353  \n",
      "2003-08-17     346.117353  \n",
      "2003-08-18     346.117353  \n",
      "2003-09-14     214.784301  \n",
      "2003-09-15     214.784301  \n",
      "2003-09-16     214.784301  \n",
      "2003-09-17     214.784301  \n",
      "2003-10-15     156.448001  \n",
      "2003-10-16     156.448001  \n",
      "2003-10-17     156.448001  \n",
      "2003-10-18     156.448001  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal      Diff  OGOut_Demand  \\\n",
      "Date                                                                    \n",
      "2003-01-15                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-16                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-17                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-18                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-02-12                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-13                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-18                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-04-13                 11.929294    2.752 -9.177294      0.000000   \n",
      "2003-04-15                 11.929294    2.752 -9.177294      0.000000   \n",
      "2003-04-16                 11.929294    2.752 -9.177294      0.000000   \n",
      "2003-04-17                 11.929294    2.752 -9.177294      0.000000   \n",
      "2003-05-15                102.873672  102.812 -0.061672     92.774778   \n",
      "2003-05-16                102.873672  102.812 -0.061672     92.774778   \n",
      "2003-05-17                102.873672  102.812 -0.061672     92.774778   \n",
      "2003-05-18                102.873672  102.812 -0.061672     92.774778   \n",
      "2003-06-14                278.763090  278.802  0.038910    287.520523   \n",
      "2003-06-15                278.763090  278.802  0.038910    287.520523   \n",
      "2003-06-16                278.763090  278.802  0.038910    287.520523   \n",
      "2003-06-17                278.763090  278.802  0.038910    287.520523   \n",
      "2003-07-15                391.642995  391.662  0.019005    407.215999   \n",
      "2003-07-16                391.642995  391.662  0.019005    407.215999   \n",
      "2003-07-17                391.642995  391.662  0.019005    407.215999   \n",
      "2003-07-18                391.642995  391.662  0.019005    407.215999   \n",
      "2003-08-15                343.692875  343.682 -0.010875    346.117353   \n",
      "2003-08-16                343.692875  343.682 -0.010875    346.117353   \n",
      "2003-08-17                343.692875  343.682 -0.010875    346.117353   \n",
      "2003-08-18                343.692875  343.682 -0.010875    346.117353   \n",
      "2003-09-14                217.292268  217.222 -0.070268    214.784301   \n",
      "2003-09-15                217.292268  217.222 -0.070268    214.784301   \n",
      "2003-09-16                217.292268  217.222 -0.070268    214.784301   \n",
      "2003-09-17                217.292268  217.222 -0.070268    214.784301   \n",
      "2003-10-15                131.368475  131.582  0.213525    156.448001   \n",
      "2003-10-16                131.368475  131.582  0.213525    156.448001   \n",
      "2003-10-17                131.368475  131.582  0.213525    156.448001   \n",
      "2003-10-18                131.368475  131.582  0.213525    156.448001   \n",
      "2003-11-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-12-15                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-16                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-17                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-18                  0.710775    0.000 -0.710775      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.000000  \n",
      "2003-04-15       0.000000  \n",
      "2003-04-16       0.000000  \n",
      "2003-04-17       0.000000  \n",
      "2003-05-15      92.743942  \n",
      "2003-05-16      92.743942  \n",
      "2003-05-17      92.743942  \n",
      "2003-05-18      92.743942  \n",
      "2003-06-14     287.539978  \n",
      "2003-06-15     287.539978  \n",
      "2003-06-16     287.539978  \n",
      "2003-06-17     287.539978  \n",
      "2003-07-15     407.225501  \n",
      "2003-07-16     407.225501  \n",
      "2003-07-17     407.225501  \n",
      "2003-07-18     407.225501  \n",
      "2003-08-15     346.111915  \n",
      "2003-08-16     346.111915  \n",
      "2003-08-17     346.111915  \n",
      "2003-08-18     346.111915  \n",
      "2003-09-14     214.749167  \n",
      "2003-09-15     214.749167  \n",
      "2003-09-16     214.749167  \n",
      "2003-09-17     214.749167  \n",
      "2003-10-15     156.554764  \n",
      "2003-10-16     156.554764  \n",
      "2003-10-17     156.554764  \n",
      "2003-10-18     156.554764  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand     Goal      Diff  OGOut_Demand  \\\n",
      "Date                                                                    \n",
      "2003-01-15                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-16                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-17                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-01-18                  1.270985    0.000 -1.270985      0.000000   \n",
      "2003-02-12                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-13                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-02-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-03-18                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-04-13                 11.925893    2.752 -9.173893      0.000000   \n",
      "2003-04-15                 11.925893    2.752 -9.173893      0.000000   \n",
      "2003-04-16                 11.925893    2.752 -9.173893      0.000000   \n",
      "2003-04-17                 11.925893    2.752 -9.173893      0.000000   \n",
      "2003-05-15                102.850162  102.812 -0.038162     92.743942   \n",
      "2003-05-16                102.850162  102.812 -0.038162     92.743942   \n",
      "2003-05-17                102.850162  102.812 -0.038162     92.743942   \n",
      "2003-05-18                102.850162  102.812 -0.038162     92.743942   \n",
      "2003-06-14                278.776379  278.802  0.025621    287.539978   \n",
      "2003-06-15                278.776379  278.802  0.025621    287.539978   \n",
      "2003-06-16                278.776379  278.802  0.025621    287.539978   \n",
      "2003-06-17                278.776379  278.802  0.025621    287.539978   \n",
      "2003-07-15                391.653385  391.662  0.008615    407.225501   \n",
      "2003-07-16                391.653385  391.662  0.008615    407.225501   \n",
      "2003-07-17                391.653385  391.662  0.008615    407.225501   \n",
      "2003-07-18                391.653385  391.662  0.008615    407.225501   \n",
      "2003-08-15                343.683381  343.682 -0.001381    346.111915   \n",
      "2003-08-16                343.683381  343.682 -0.001381    346.111915   \n",
      "2003-08-17                343.683381  343.682 -0.001381    346.111915   \n",
      "2003-08-18                343.683381  343.682 -0.001381    346.111915   \n",
      "2003-09-14                217.272131  217.222 -0.050131    214.749167   \n",
      "2003-09-15                217.272131  217.222 -0.050131    214.749167   \n",
      "2003-09-16                217.272131  217.222 -0.050131    214.749167   \n",
      "2003-09-17                217.272131  217.222 -0.050131    214.749167   \n",
      "2003-10-15                131.443230  131.582  0.138770    156.554764   \n",
      "2003-10-16                131.443230  131.582  0.138770    156.554764   \n",
      "2003-10-17                131.443230  131.582  0.138770    156.554764   \n",
      "2003-10-18                131.443230  131.582  0.138770    156.554764   \n",
      "2003-11-14                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-15                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-16                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-11-17                  0.000000    0.000  0.000000      0.000000   \n",
      "2003-12-15                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-16                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-17                  0.710775    0.000 -0.710775      0.000000   \n",
      "2003-12-18                  0.710775    0.000 -0.710775      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2003-01-15       0.000000  \n",
      "2003-01-16       0.000000  \n",
      "2003-01-17       0.000000  \n",
      "2003-01-18       0.000000  \n",
      "2003-02-12       0.000000  \n",
      "2003-02-13       0.000000  \n",
      "2003-02-14       0.000000  \n",
      "2003-02-15       0.000000  \n",
      "2003-03-15       0.000000  \n",
      "2003-03-16       0.000000  \n",
      "2003-03-17       0.000000  \n",
      "2003-03-18       0.000000  \n",
      "2003-04-13       0.000000  \n",
      "2003-04-15       0.000000  \n",
      "2003-04-16       0.000000  \n",
      "2003-04-17       0.000000  \n",
      "2003-05-15      92.724861  \n",
      "2003-05-16      92.724861  \n",
      "2003-05-17      92.724861  \n",
      "2003-05-18      92.724861  \n",
      "2003-06-14     287.552789  \n",
      "2003-06-15     287.552789  \n",
      "2003-06-16     287.552789  \n",
      "2003-06-17     287.552789  \n",
      "2003-07-15     407.229809  \n",
      "2003-07-16     407.229809  \n",
      "2003-07-17     407.229809  \n",
      "2003-07-18     407.229809  \n",
      "2003-08-15     346.111225  \n",
      "2003-08-16     346.111225  \n",
      "2003-08-17     346.111225  \n",
      "2003-08-18     346.111225  \n",
      "2003-09-14     214.724102  \n",
      "2003-09-15     214.724102  \n",
      "2003-09-16     214.724102  \n",
      "2003-09-17     214.724102  \n",
      "2003-10-15     156.624148  \n",
      "2003-10-16     156.624148  \n",
      "2003-10-17     156.624148  \n",
      "2003-10-18     156.624148  \n",
      "2003-11-14       0.000000  \n",
      "2003-11-15       0.000000  \n",
      "2003-11-16       0.000000  \n",
      "2003-11-17       0.000000  \n",
      "2003-12-15       0.000000  \n",
      "2003-12-16       0.000000  \n",
      "2003-12-17       0.000000  \n",
      "2003-12-18       0.000000  \n"
     ]
    }
   ],
   "source": [
    "'''\n",
    "This step ensures the mean demands are retained.\n",
    "\n",
    "'''\n",
    "months = ['Jan', 'Feb', 'Mar', 'Apr','May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct','Nov', 'Dec']\n",
    "Year1 = list(np.arange(2000,2006,1))\n",
    "Year2 = [2007, 2008, 2009]\n",
    "Year3 = list(np.arange(2011,2018,1))\n",
    "Years = Year1+Year2+Year3\n",
    "Year = [2003]\n",
    "iterations = list(np.arange(1,15,1))\n",
    "DemandPlot = pd.DataFrame()\n",
    "for i in Year:\n",
    "    Out_Demand2 = Out_Demand.copy()\n",
    "    for j in iterations:\n",
    "        DemandPlot['Iteration_'+str(j)] = 0\n",
    "        Demand_Forecast, Out_Demand2, DemandPlot =DemandIterationAllyrs(j, DemandPlot, Demand_Forecast, slc, i, months, 'Obs_gpcd', \n",
    "                            Out_Demand2, '-01-01', '-12-30',DemandOffset,i, PrePeakFact, PostPeakFact)\n",
    "        \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#conver to liter for ASCE\n",
    "#DemandPlot = DemandPlot*3.78541\n",
    "\n",
    "fig = plt.figure()\n",
    "fig, ax = plt.subplots(1, 2)\n",
    "fig.set_size_inches(6, 4)\n",
    "labelsize = 11\n",
    "\n",
    "gal_to_l = 3.785\n",
    "\n",
    "ax[0].set_facecolor('white')\n",
    "ax[0].plot(DemandPlot.Iteration_1*gal_to_l, label = 'Iteration 1', color = 'green')\n",
    "ax[0].plot(DemandPlot.Iteration_2*gal_to_l, label = 'Iteration 2', color = 'blue')\n",
    "ax[0].plot(DemandPlot.Iteration_3*gal_to_l, label = 'Iteration 3', color = 'orange')\n",
    "ax[0].plot(DemandPlot.Iteration_4*gal_to_l, label = 'Iteration 4', color = 'black')\n",
    "ax[0].plot(DemandPlot.Iteration_14*gal_to_l, label = 'Iteration Final', linewidth = 1, color = 'red')\n",
    "\n",
    "ax[0].spines['bottom'].set_color('black')\n",
    "ax[0].spines['left'].set_color('black')\n",
    "ax[0].xaxis.set_major_locator(plt.MaxNLocator(3))\n",
    "ax[0].set_xlabel('Time', size = labelsize)\n",
    "ax[0].set_ylabel('Water Demand (lpcd)', size = labelsize)\n",
    "ax[0].text(pd.to_datetime('2003-10-15'),405*gal_to_l , \"A.\", size = labelsize)\n",
    "ax[0].tick_params(axis='x', which='major', labelsize=10)\n",
    "\n",
    "\n",
    "\n",
    "ax[1].set_facecolor('white')\n",
    "ax[1].plot(DemandPlot.Iteration_1.loc['2003-07-15':'2003-08-15']*gal_to_l, label = 'Iteration 1', color = 'green')\n",
    "ax[1].plot(DemandPlot.Iteration_2.loc['2003-07-15':'2003-08-15']*gal_to_l, label = 'Iteration 2', color = 'blue')\n",
    "ax[1].plot(DemandPlot.Iteration_3.loc['2003-07-15':'2003-08-15']*gal_to_l, label = 'Iteration 3', color = 'orange')\n",
    "ax[1].plot(DemandPlot.Iteration_4.loc['2003-07-15':'2003-08-15']*gal_to_l, label = 'Iteration 4', color = 'black')\n",
    "ax[1].plot(DemandPlot.Iteration_14.loc['2003-07-15':'2003-08-15']*gal_to_l, label = 'Iteration Final', linewidth = 1, color = 'red')\n",
    "\n",
    "ax[1].spines['bottom'].set_color('black')\n",
    "ax[1].spines['left'].set_color('black')\n",
    "ax[1].xaxis.set_major_locator(plt.MaxNLocator(3))\n",
    "ax[1].set_xlabel('Time', size = labelsize)\n",
    "ax[1].text(pd.to_datetime('2003-08-15'),414*gal_to_l , \"B.\", size = labelsize)\n",
    "ax[1].tick_params(axis='x', which='major', labelsize=10)\n",
    "\n",
    "leg = ax[1].legend(bbox_to_anchor=(1, 1.2), loc = 'upper right', ncol = 3)\n",
    "frame = leg.get_frame()\n",
    "frame.set_facecolor('white')\n",
    "fig.savefig('C:/Users/rjohnson18/Box/Dissertation/Paper2/Figures/Downscaling_Iterations.pdf', bbox_inches='tight',pad_inches=.15)   \n",
    "fig.savefig('C:/Users/rjohnson18/Box/Dissertation/Paper2/Figures/Downscaling_Iterations.png',dpi = 300, bbox_inches='tight',pad_inches=.15)   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "#need to make daily demand forecasts for each 18yr time block\n",
    "Demand_Forecast2017 = IndexOffset(Demand_Forecast.copy(), 17)\n",
    "Demand_Forecast2034 = IndexOffset(Demand_Forecast.copy(), 34)\n",
    "Demand_Forecast2051 = IndexOffset(Demand_Forecast.copy(), 51)\n",
    "Demand_Forecast2068 = IndexOffset(Demand_Forecast.copy(), 68)\n",
    "Demand_Forecast2085 = IndexOffset(Demand_Forecast.copy(), 85)\n",
    "\n",
    "#Now append to create time series\n",
    "Demand_Forecast = Demand_Forecast.append(Demand_Forecast2017)\n",
    "Demand_Forecast = Demand_Forecast.append(Demand_Forecast2034)\n",
    "Demand_Forecast = Demand_Forecast.append(Demand_Forecast2051)\n",
    "Demand_Forecast = Demand_Forecast.append(Demand_Forecast2068)\n",
    "Demand_Forecast = Demand_Forecast.append(Demand_Forecast2085)\n",
    "\n",
    "Demand_Forecast = Demand_Forecast.loc['2000-10-01' :'2099-1-15']\n",
    "Demand_Forecast = Demand_Forecast[~Demand_Forecast.index.duplicated(keep='first')]\n",
    "#make sure date range is correct\n",
    "DateRange = pd.date_range(start=\"2000-10-01\",end=\"2098-12-31\")\n",
    "Demand_Forecast['Time'] = DateRange\n",
    "Demand_Forecast.index = Demand_Forecast['Time']\n",
    "del Demand_Forecast['Time']\n",
    "\n",
    "Demand_Forecast = pd.DataFrame(Demand_Forecast)\n",
    "#Since we did a cubic spline interpolation, all values need to be above zero\n",
    "Demand_Forecast[Demand_Forecast < 0]=0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "MLR['Apr']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>y_test</th>\n",
       "      <th>y_pred</th>\n",
       "      <th>y_pred_lower</th>\n",
       "      <th>y_pred_upper</th>\n",
       "      <th>y_test_tot</th>\n",
       "      <th>y_pred_tot</th>\n",
       "      <th>y_pred_lower_tot</th>\n",
       "      <th>y_pred_upper_tot</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2008-06-30</th>\n",
       "      <td>2008</td>\n",
       "      <td>252.512</td>\n",
       "      <td>254.158191</td>\n",
       "      <td>214.982524</td>\n",
       "      <td>293.196992</td>\n",
       "      <td>403.32</td>\n",
       "      <td>379.948856</td>\n",
       "      <td>340.773188</td>\n",
       "      <td>418.987657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06-30</th>\n",
       "      <td>2015</td>\n",
       "      <td>246.680</td>\n",
       "      <td>258.712664</td>\n",
       "      <td>228.001702</td>\n",
       "      <td>289.846501</td>\n",
       "      <td>359.67</td>\n",
       "      <td>370.621025</td>\n",
       "      <td>339.910064</td>\n",
       "      <td>401.754863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-06-30</th>\n",
       "      <td>2017</td>\n",
       "      <td>309.616</td>\n",
       "      <td>281.984760</td>\n",
       "      <td>234.599193</td>\n",
       "      <td>329.625625</td>\n",
       "      <td>429.97</td>\n",
       "      <td>389.926749</td>\n",
       "      <td>342.541182</td>\n",
       "      <td>437.567615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Year   y_test      y_pred  y_pred_lower  y_pred_upper  y_test_tot  \\\n",
       "Date                                                                            \n",
       "2008-06-30  2008  252.512  254.158191    214.982524    293.196992      403.32   \n",
       "2015-06-30  2015  246.680  258.712664    228.001702    289.846501      359.67   \n",
       "2017-06-30  2017  309.616  281.984760    234.599193    329.625625      429.97   \n",
       "\n",
       "            y_pred_tot  y_pred_lower_tot  y_pred_upper_tot  \n",
       "Date                                                        \n",
       "2008-06-30  379.948856        340.773188        418.987657  \n",
       "2015-06-30  370.621025        339.910064        401.754863  \n",
       "2017-06-30  389.926749        342.541182        437.567615  "
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MLR_E['Jun']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Make a prediction out DF\n",
    "#original DF\n",
    "#MLR = np.load('C:/Users/Ryan/Box/Dissertation/Paper1/Python/ModelOutput/Slc_Pred_Low_Ave_High_WY.npy',allow_pickle=True).item()\n",
    "#DF w/error\n",
    "MLR = np.load('C:/Users/rjohnson18/Box/Dissertation/Paper1/Python/ModelOutput/Slc_Pred_Uncertainty.npy', allow_pickle =True).item()\n",
    "MLR_Out_Demand= pd.DataFrame()\n",
    "\n",
    "#Select year to use (Drought = 2015, Average = 2017, Surplus = 2008)\n",
    "Year = 2015\n",
    "\n",
    "DemandPrediction = 'y_pred_lower'\n",
    "\n",
    "Scenario = 'Drought_LowerD'\n",
    "\n",
    "PrePeakFact = [1,1,1,1]\n",
    "PostPeakFact = [1,1,1,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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55rxZLJpVQKO7n6c31HPPb7dx8VmVLJpVQFlhBmkp5lfY3e3B6/WxfnsTZy8spa1rkP9df4jsjGTmzcjjcx9ayB/fPMqSmkJSkp0hz/Oqc6p5a08b614/xM2XqckfICJGiryIG0etk66BtnRjgWEYzK3KY25VHtVlOTz52kHWrT/EuvWHSE1xctWamRxq6mXr/vbjj3nh7WPkZKZQ4crkm7euPN6f//FLa8OWZ6Uri8tWVvHC28eYPyOfFfOKwxZLBEeKvIgbx+KwyPubVZbDXR9fRlvXIA3uAdZvb+KpvxwiyWlwxdkz6eob5oK6cn7x+5109Q1z7QWzIzqG/boL57C7voun1h9i2dwinA4ZvBcNpMiLuHGsrR9XXhrpqfH9sS7Oz6A4P4OlNYW89E4Dc6vymFX23rTKn7piHq9tbWLV/JKI5pXkdHD1ubP4z3Xv8tbuNtYsiq0L0uJVfH8bREJpaOuPq/74yTgdDt6/asbfbF8yp4glc4psyAiWzS2iqjiLpzfWs2pBsbTmo4C8AyIueL0+3N0eSgpiZ2KyeOQwDD60tprWzkG2H+iwOx2BFHkRJ7r7hxn3+nDJgti2q6stIjMtia373HanIpAiL+KEu9uc58WVJ0Xebk6HgyVzCtl+sAOv12d3OglPiryIC+7uIQCK8tJszkQALKt10e8Z5a09rXankvCkyIu40N7jwQAKc6TIR4O62iLmlOfw6xf20d0/bHc6CU2KvIgL7m4PBTmpMrd5lEhyOrjtgwsYGR3nmQ31dqeT0OQbIeKCu2eIIjnpGlVK8jM4v66c9dubZJFyG0mRFzHP5/PR3D5AaWHsTi8cry5YWs6418eOgzKc0i5S5EXM6xscZWBojLLC2FsNKt5VFWeRn53K9gPtk+8swkKKvIh5E4tKlxdJSz7aGIbB0jmF7DzcyeDQmN3pJCQp8iLmNXUMAlAuLfmodOGyCoZHx3nh7aN2p5KQApq7RimVA2wErtJa1yulfgWcCwxYu3xLa71OKVUH3A/kAOuBO7TW8vMtwqqpfYDUFCf52al2pyJOYUZJNsvnunjpnQY+uLZa5rOJsEn/tZVSq4E3AP/1wlYA52ut66z/1lnbHwG+oLWeCxjA7aFOWIiTtXQOUlqQEdAi1MIeK+cXMzg8Rn1Ln92pJJxAflJvBz4PNAEopTKAGcCDSqkdSqlvKaUcSqmZQLrW+k3rcQ8B14chZyFO4O72UCzTGUS1edbar3vqu2zOJPFM2l2jtb4NQKnjS3qVAq8AdwI9wLPAZ4CdQLPfQ5uBymATKiyM/IIPLlf4p6eNRAy7Y9oRb9zro7N3iPOXVYY9vryH03heYFZ5Dgeaek+IES+vL1rinUrQ88lrrQ8B10zcVkrdC3wS2A34z0ZkAN5gn7+joz+ikxq5XNm43eE9hIxEDLtj2hWvs3eIsXEfGSmOsMaX93D6aspzeW1bI80tPSQ5HXH3+uyK53AYZ2wcB30GRCm1WCl1rd8mAxgFGoAyv+2lWF08QoTL8dkn5WrXqFdbmcvomJcjrdIvH0lTOc1tAD9RSuUrpZKBzwLrtNZHgCGl1Fprv5uB50OUpxCnJLNPxo7aylwA9h/rsTmTxBJ0kdda7wC+B2zA7KLZprX+jXX3TcCPlVJ7gSzgZ6FKVIhTkdknY0duViquvDT2Heu2O5WEEnCfvNa62u/vnwM/P8U+24FVIclMiAC4uz3ky+yTMWP53GL+/PZRGt39UXFSMhHIN0PEtEb3AOVFcqVrrLhizUzSUpJY9/phu1NJGFLkRcwaG/fS1DFAlSvyw27F1GSlJ3PJ8gq27nPT1N5vdzoJQYq8iFmtXR7Gxn1USpGPKZecVYnTafD8xnq7U0kIUuRFzGpoM1uClcVS5GNJblYqc6vy2L7fbXcqCUGKvIhZDe5+nA6DMlksJObUVuZR39wr0w9HgBR5EbPc3R4Kc9JkZE0Mqq3MxeeDg00yZj7c5NshYlZn3zAFOTK9cCyaXZ6Dw2HIhGURIEVexKzO3iEK5CKomJSWksTK+SVs3NnM2HjQU1yJIEiRFzFpfNxLd9+ItORj2OXnVNM7OMqWfXICNpykyIuY1Nk7jNfnk5Z8DFs2t5jMtCR2He60O5W4JkVexKR2a/bJgmwp8rHK4TCYU5HLgUY5+RpOUuRFTHJ3m4t3F0p3TUyrrcyluWOQfs+o3anELSnyIiYdb8lLd01Mq6kwpx8+0CCt+XCRIi9iUnPHIFnpyaSnBr24mYgi1WU5OB2GdNmEkRR5EZNa2gdwyeLdMS812cmMkmwONHTbnUrckiIvYlJTxwAl+VLk40FtZS6HW/pkvHyYSJEXMWds3Et71yDFUuTjQk2FufZrfYus/RoOUuRFzGnvGcLrQ7pr4sS8mfk4HQabdZvdqcQlKfIi5rR1mcMnS/Jl9sl4kJWezJI5hby5q5Vxr3TZhJoUeRFzWrvM4ZPSXRM/zllUSs/ACLtlwrKQkyIvYk5bl4f01CSyM5LtTkWEyJI5RWSmJbFxZ4vdqcQdKfIi5ri7PZQVZmIYht2piBBJTnKwan4JW/a58QzLQiKhJEVexJzWLg9lRZl2pyFCbLlyMTrmZb+MmQ8pKfIipni9Ptq7pcjHozkVuTgdBvuOydWvoSRFXsSUzt4hxr0+SgulyMeb1GQn1aXZ7JOWfEhJkRcxpdWamKxcWvJxqbYqj8NNvQyPjtudStyQIi9iSqN7AIDK4iybMxHhsGhWAeNeHzsPyUIioSJFXsSUY6195GamkC9TDMeluVV5ZKYlsWWfXP0aKlLkRUw52tZPVYm04uNVktPBsloX2w50yNWvISJFXsSMsXEvTe0DzCjOtjsVEUaLZhfgGR6TCctCJKAVF5RSOcBG4Cqtdb1S6lLgHiAdeEJr/TVrvzrgfiAHWA/cobWWKxtESDS1DzDu9TFDWvJxbd6MfAD2HuliTnmuzdnEvklb8kqp1cAbwFzrdjrwIHA1MB9YqZS63Nr9EeALWuu5gAHcHo6kRWJqs+asKS2QicniWU5mChWuTPYekXlsQiGQ7prbgc8DTdbtVcB+rfVhq5X+CHC9UmomkK61ftPa7yHg+hDnKxJYZ+8QIOu6JoJ5M/LZ39AjC4mEwKTdNVrr2wCUUhObyoFmv12agcozbA9KYWHkD8VdrvD38UYiht0xwx3PM+YjNcVJdVV+ROKdTN7DyMVbvbiclzc30Dk4xsLZhWGPFy52fGZONpVVkB2Az++2AXjPsD0oHR39eL2+yXcMEZcrG7c7vCd4IhHD7piRiNfY2kt+Virt7f1x+frsjhlN8cryUjGAN7c3UpydEvZ44RCpeA6HccbG8VRG1zQAZX63SzG7ck63XYiQ6OwbpiAn1e40RARkpiUzoySbPdIvP21TKfKbAKWUqlFKOYEbgee11keAIaXUWmu/m4HnQ5SnEHT2DlGQLf3xiWLBrHwONPYwOCQD9KYj6CKvtR4CbgWeAnYDe4EnrbtvAn6slNoLZAE/C02aItGNjXvp6R+RlnwCqaspMqc4ONxhdyoxLeA+ea11td/fLwNLT7HPdszRN0KEVHf/MD5kZE0imVOeS1Z6MtsPtLNqfond6cQsueJVxISWTnPxbleerOuaKBwOg8WzC9lxUKY4mA4p8iImNLRZs0+6ZIrhRFJXW8TA0BgHG3vtTiVmSZEXMaHB3U9uVgrZGaEZTidiw6JZBTgdBtsOtNudSsySIi9iQoO7n0qXzFmTaNJTk5hblceOg3LydaqkyIuoN+710tQ+KF01CWrpnEKa2gdot1YFE8GRIi+iXkfPEGPjXsplXdeEtKSmCIDt0pqfEinyIuq5e8yJyWRkTWIqLcigOD9dumymSIq8iHoTh+lFeTJGPlEtmVPI3qNdssD3FEiRF1GvvWcIp8MgP1uudk1US+cUMTrmlblspkCKvIh67T1D5Gen4nTIxzVRza3KIzXZKV02UyDfGhH12rs90h+f4JKTHCyozmfHwXZ8vshNRR4PpMiLqNfeM0RRrvTHJ7qlNUV09g7T6B6wO5WYIkVeRLWR0XF6BkakyAsWWytEbT8oV78GQ4q8iGrt1vDJIumuSXj52anMKstm634p8sGQIi+i2kSRd+VKkRdQV+viUFMv3f3DdqcSM6TIi6jW3iNj5MV7ltWaV7/KhGWBkyIvolp79xBJTgc5mTL7pICKokxceWls3SdFPlBS5EVUa+/xUJSbhsMw7E5FRAHDMFhW62LPkU48w7L2ayCkyIuo5u4Zkq4acYJltUWMjfvYdbjT7lRighR5EbV8Ph/t3R6K5KSr8FNTmUt6ahLvHpKrXwMhRV5Era6+YQaGxmQeeXECp8PBwup8dh7ulKtfAyBFXkStIy19AMwsybY5ExFtFs8upKtvmKOt/XanEvWkyIuodaS1D8OAymJZ9k+cqK62CKfDYOPOFrtTiXpS5EXUOtLSR1lhJqnJTrtTEVEmOyOFutoi/rqrhbFxr93pRDUp8iJqHXP3M0Na8eI0zllUSr9nFH2s2+5UopoUeRGVhkfG6ewdpqwww+5URJRaMLOAJKeDHQdklM2ZSJEXUam1axCAkgIp8uLUUlOczJuZxw6ZlfKMpMiLqNTSaRb5Uiny4gyW1bpo7fJwuLnX7lSilhR5EZVarSJfki9FXpze2QtKSE1x8tI7DXanErWkyIuo1NI5SEFOKqkpMrJGnF56ahLnLi7jrT2t9Mj0w6eUNJ0HK6VeBYqBUWvT54Bs4B4gHXhCa/21aWUoElJzx6C04kVALlleycubG3htWxNXnzvL7nSizpRb8kopA5gLLNVa12mt64AdwIPA1cB8YKVS6vJQJCoSx7jXS2P7AFUyfFIEoLQgg8WzC/nLtka8Ms3B35hOd42y/v+CUmq7UuoLwCpgv9b6sNZ6DHgEuH66SYrE0trpYXTMK0VeBOzshSV0949wuElOwJ5sOt01+cDLwN8DycBrwA+AZr99moHKYJ60sDDyX2yXK/xzo0Qiht0xQxVv97EeAJbOKznjc8bq64vmmLEa7+JVqTz43B72NvRwdt3pS06svr7pmHKR11r/FfjrxG2l1APAt4E3/HYzgKCuOe7o6Mfrjdwhl8uVjdvdF/Mx7I4Zyni7DrhJchqkOTjtc8by64vWmLEeT83IY8P2Jq5cPSMi8SYTqXgOh3HGxvF0+uTPVUpd4rfJAOqBMr9tpUDTVGOIxHTM3U95YSZJThn8JQK3rNZFS+cgzR0DdqcSVabzLcoDfqiUSlNKZQO3AP8XUEqpGqWUE7gReH76aYpE0to5SKlMZyCCNLHI95Z9bpsziS5TLvJa62eB54CtwGbgQasL51bgKWA3sBd4cvppikQxNu6lvWdIhk+KoBXkpFFdms2bu1pllI2faY2T11p/Hfj6SdteBpZO53lF4nJ3e/D5oKRAlvwTwXvfiirue3Y32/a3c9Zcl93pRAXp9BRRZWLOGpmYTEzFqgXFuPLSeOmdY3anEjWkyIuo0trpAWTOGjE1ToeDNQtL0ce6ZZoDixR5EVVaOgfJTEsiKz3Z7lREjFo5rxifD97RcgIWpMiLKHOwqYfqUvsvIBGxq8KVxczSbP781lFGx2RpQCnyImr0e0ZpdA8wd0a+3amIGHft+bNp7xnitW2NdqdiOynyImrss9bqVFV5tuYhYt/CWQXMn5nPMxvq8QyP2Z2OraTIi6hxoLGHJKfBrLIcu1MRMc4wDK6/aA79nlFe2ZLYC4pIkRdRo7VzkOL8DJKT5GMppq+6NIe5VXm8saMZXwJfHCXfJhE12ro9FOfJRVAidNYuLqW1y8OBxh67U7GNFHkRFXw+H+5uD8X5UuRF6KycV0xqspMN7zZPvnOckiIvokLPwAgjo15c0pIXIZSWksSKeS7e2tPGUIKegJUiL6JCW5d5pau05EWorV5QwtDIOLvrO+1OxRZS5EVUOF7kpSUvQiwvKxWAwaFRmzOxhxT5BLTvWDfffuhtDjT2sOdIF72DI3anhD7WRWqyk8LcNLtTEXEmNdkJwNDwuM2Z2GNaUw2L2DA27uUnv9vORcsq2N/Qw9t72+jqG+bffr35+D4FOalccfZMLj4rqCV5Q2JgaJS397SxZlGprAYlQm6iyA+PJGafvBT5ONfW7aGlY4Dd9V3oo92MW+vnrl5QgsOAFaqY1i4Pm/a08rtXD+LzQU1FLjMjOH/MFu1mZMzLBXXlEYspEsfxlvyItORFnPH6fHz1v46vtc6410dhThpnLyzhyjUzSUt57+2fXZ7D9x/dwqMv7qOsMIPv3n52xPKsb+0jPdXJzBKZmEyEXnKyeXSYqEVejo3jWFP7ewsaOwyD8qJMPnPlfK69YM4JBR6gtjL3+EIdbV0eXt7cQFdfZObjbmjrp9KVhWEYEYknEovDMEhJdjCUoN01UuTj1L8/splvPPDW8dszS7P5zm2rmTfz1DM8GobBN29dwZ0fXsS418ejL+7j4T/tDXuePp+PBnc/lcVZYY8lEldqspPhBG3JS3dNHBoZHecvW9+blOnz1ywKqI89LSWJBdUFx2/vONjBO3vbWDGvOCx5ArT3DOEZHqdKirwIo9RkZ8K25KXIx5kX3z7Gb17ef/z2innFLFeBF+mMtCS+fssKCnPS+NlTO/jlM7soL8qkvCgzHOlyuLkXQIq8CKvUFKf0yYv4sGHne3N03Pul8/jsBxcE/RyzynLIyUzh89csZmzcx/aD7aFM8QTv7G0jJyNZVoMSYZXI3TVS5ONMtrU26qc/uJDMtORpjTvPz06lpCCDfUe7Q5TdiTzDY2w/2MGKecU4HfJRFOGTyN018s2KM32eUZbMKeSaC2tC8nyqKpftBzv42ZM7Qv4l2V3fxeiYl5Vh7PMXAiaKvLTkRRwY8IySZbXmQ0FVmaNxth1oZ8+RrpA9L8Deo12kJDmYU5Eb0ucV4mQpyY6EveJVinyc6QtxkV+9oIQ7P7wIp8Ngd31oi7w+2kVNZa5MZSDCLjXZiSdB566Rb1ccGRkdZ2TUS3ZG6Iq8w2GwYl4x86vzeXlzA69saQjJUmq9gyM0uAdQM049bl+IUDJPvEpLXsS4fo85lWpmCFvyE5bVugB45IV9vLmrddrPt3WfG4DFswsm2VOI6ZMhlCIuTBT57DAU+Qvryrn3S+dRU5nLYy/tm/ZJ2E27WykpyJD5akREpCQ7Gff6GBv32p1KxEmRjyMTRT6UffITDMMgMy2Zj15Uw8DQGK/vmPqamT0DI+ij3ayeXyzz1YiIOD7d8GjitebDUuSVUjcqpXYrpfYrpT4fjhjib4WzyE+oqciltjKXF946xrh3aq2inYc68PFeF5AQ4ZZqzUSZiBdEhbzIK6UqgO8C5wJ1wGeVUsFfdimC1jcY/iIPcPnqmXT0DrFp99T65ncc7CA3K4UZJTKVgYiMRG7Jh2PumkuBV7TWnQBKqSeB64BvB/Lgbz7wFu5uTxjSOjXDYeDzTn+0iN0xAEat/sZwnHj1t6SmkApXJvc/u4dHX9yPQXCv0TMyxtrFZdJVIyJmYmrtf334HRwR+txF6ntfnJ/OvXddfNr7w1HkywH/DttmYFWgDz6nrpz+wcRccDcUqoqzKCs1Ly5yucJ3UvN7d57LK+8co6N3KOjHGgZccc4sXK7pteTD+fqiIZ4dMeM13trsNJq6PHHZkp9syHQ4irwD8P/5MoCAO2/fv7wSbwR+/Sa4XNm43X0xH8Of290XkZjnLy49/nfw8XzTyi/S/6aRjmdHzHiPd8uVC+Ly9TkcZz4yCceJ1wagzO92KdAUhjhCCCEmEY6W/EvA3UopFzAAXAt8NgxxhBBCTCLkLXmtdSPwL8CrwDbgMa31W2d8kBBCiLAIy8pQWuvHgMfC8dxCCCECJ1e8CiFEHJMiL4QQcUyKvBBCxLGw9MlPkRMmH/MZDpGIGa+vS+LFV0yJF3vx/GI4T3W/EYoFIELkXOB1u5MQQogYdR7wxskbo6nIpwIrMadBiL9rj4UQIjycmBegvg0Mn3xnNBV5IYQQISYnXoUQIo5JkRdCiDgmRV4IIeKYFHkhhIhjUuSFECKOSZEXQog4JkVeCCHimC3TGiilbgUu1FrfGuY41cA+YPdJd31Qa33sFPvfDaC1vnsKcQ4Dv9Raf85vex2wFfiU1vqhYJ4ziNiLgHeB67TWT4Xh+aux6bX5xbqVCHxegomplHoIeG26rz3c799Jsa4D/hnze+8A/kdr/cMwx8wCfgC8H3MRoV7gbq31y6fZPxd4SGt9zRRiVWN+Vi/TWr/ot70e872sD/Y5J4nlX1vSgY3AV7XWraGKEwqJ0JJv0lrXnfTf3xT4EOgAPqCU8p8/4gbAHYZY/j4N/A743GQ7ToNdry0RROL9QylVAfwIswAuBdYAH1NKfSiMMQ3gGWAEWGDF/T/Ar5VSF57mYfnAsmmEHQXuU0pFYoXw47UFmAe0AE9GIG5QbJ2gTCl1AfBdIAPIA/5Ba/0Hq5XUAywHKoBva61/FcK4JcB/A1WYi4z/s9b6JevuVUqpTUAWZuv1pwE+bT/mSljnY66KBXAZ5nKIKKW+ANwMZGJ+6D+utdZWK2MTUAecp7VuC+J1JAM3Yc5ZsVEpNUdrfdB6zt8C77N2/bTWeqtS6jWgE1gI3KC13hau1wZUYr5va619bgVWa63/LtDXdzIr/7u11q9ZLanXtNbV4fy8nC5miJ77TO/fhVrreqsY3q21vtBq9T+E+b19Hbhca10TYLgiIBnzu9ahte5XSt0CDCmlVgI/tu5rBz6ntT5svfZtmO97GvAlrfULQbzEC4CZwMVaax+A9Tn8DvB1pVQ35vcwA/NzeRPwM6BcKbVuKq15zPWkX8T8QTth2VGl1P8FPoE5bcoLwFeAHwKNWusfWfs8BTyitV4XTFCttU8p9U2gVSm1BLgC+CjmlAN/Bv7J2ucfgDusHJ7RWv/TFF5jUOxuyf89cJvW+izgNuA7fvdVYX74PwT8+zRilCultvn9dxfwU+BBrfVy6/n/2++Xvwy4GLOl8wWrWyJQvwWuA7C+ODswi14O8GHML+4i4FngC36Pe15rrYIp8JYrgSNa633A7znxQz2gtV4GfAN42G/7DivWtiBjBfvaXgHKlFJzrMd/ErNAhUuoPi+RdKb371QeBr5htRwPEUQjTWu9HfgDcEgp9ZZS6geYBegocD9wo/U9/BFwn99Dc6ztNwIPK6VSAo2JORfVOxMF3s96675HgX/VWi8GHge+iNnSb5pigZ/wZeD9Sqn3+W27HPOzsQLzSKEGs9j+GrNRglUD1gDPTSWo1noE2I/ZYFuO+RqXYTY8brK+N3cCq4AlwHKl1PKpxAqG3UX+E8AipdTXMd+YLL/7XrA+HDuBgmnEOLm75ofApcC3lVLbgOcxWzgTxehxrfWA1roX81DzgiBiPQ1crpRyYHZnPGFt78X8knxMKfU94IOc+Fo3TfG1fQr4jfX3E8Cn/L6EvwTQWj8DVCqliqYZK6jXZr13DwOfUErNAEq01lONHYhQfV4i6Uzv3wmUUgVAtdb6j9amB4MNZh1FVQO/wGxhvwl8FfOz/7T1ffgBMNvvYfdZj92GOXngkiBC+jj1D1EK1qRaWutnref/hdb6riCe+7Ss7+7tnNhtcwnwG631oNZ6DPPf7xKt9VYgTSlVA1yD2boemUZ4H+aP1WpgM7AF84dlIWYteUZr3aO1HtNaX6q13jyNWAGJWJFXSp2nlCq3bhrAGOYh5yrMf4zvWtsnDIF5GBSGdJyYh5AT/WmrMU9+YeU1wYHZxxcQrXU/sB1z2uSLsbozMFuZf8Xsknoes0Xr/1o9wb4ApVQxZuvky9bh/f2Y/ZkfsXY5+XVMzOwZdCyY8mt7CPgYZkvpf4KJd5rPi8/vuZNPesi0Py9TiDllk7x/p4o5zomfmWDjXamUukFr3ai1/pXW+mOYreaLgEN+34XlmO/xhJM/R/63J7MJWGF1S/lbA7yF+Ton8ktTSs0mRKxupYluG/jbWmfw3g/QI5gNlxusv6fE+oFWmEdHPzmpvnwXs5b4v+ZypVTeVOMFKpIt+U9jHtaD2Ro4BMzF7E54Hria00x6HwavYB42oZRagNn6y7Duu04plaqUygeu4r0+6ED9Fvg+5mHqxBdiADigtf4x5nSg1zD913oz8LLWulJrXa21non5QbrDuv9jAEqpa4A9WuuuacaDIF+b1voI0AD8HeZhcTBO9Xlpx2wR4XdfKEUy5pneP/+YVwNorXuAg0qpy63tN+JXMAIwCHzPOq8wcVK0DrM1X6CUOs/a79PAY36Pm/gcrcD8EXqXAGmtXwd2AT+ZKPRW98TXgG8BDUqpy6zdbwa+jfkjEqpzhV/GHNVThvmd/7hSKl0plYR5FDXx3X4Us8DXcIr52ANhHeF+C/Pf80HgZqVUlhXr95hdna8DV/ht/w1mKz+sIlnkvwfcopTaAyzCPGR8APNDsAfIBjKUUpkRyOXvgbOVUjswD5M/obXus+47AmzAfLP/TWu9J8jnfgbzy/OE37YRwKGU2o15+LYXmDX19AG4Ffj5Sdv+E/PIKA1Yax1+/yNwyzRjTZjKa3sc2K21bgoy1qk+L/8PuFMptQVzyFqoRTLmrZz+/fsV8FOl1NtAt9/9nwS+YeWymiCOyrTWr2IWoWeVUhrzfRoH7gauB35kfR9uAT7j99DZVrxfYp6sD3ath49gznG+0/qM/BTz+/YaZnftN6zP6Q3AXUArcFQpFWzj6m/4ddukYJ4rehZ4B7PmHAXutfY7hvnD+mSQR4LHz/dhHuVWYA6oeAZ4CvNIZifmyeuHtdZbgP/APPLdDqz3G/ARNjKffBxSYRgXPMU8kjBb8L/TWv+vnbnEA6XUN4D7tNbNSqmPADdpra8NY7zXsEYWhSuGCL9oWuNVxBGrO2BiONvv7c0mbhwFXlRKjQJdnNjiFuKUpCUvhBBxzO4hlEIIIcIo7N011lVgH7VuPqe1/opS6lLgHswTWU9orb9m7Xs15skhA3MOik/5jwpRSv0rMK6DnFtGCCESVVhb8lYxvwzzqq86zCu8Po45xOhqYD6wUil1uVIqB3M0w5XanONiB+aZf5RSuUqpBzCHRAkhhAhQuLtrmoEva61HtNajmEMl5wL7tdaHrbHWj2AO4UoGPq+1brQeuwOYYf19Neblwj9CCCFEwMLaXaO13jXxt1KqFrPb5l7M4j+hGajUWncA66x90zEvt54Yx/o/1va7w5mvEELEm4iceFVKLcQcSncX5lWE/kN6DMyZICf2zcWcIGi71tp/Yi0hhBBBCnuRV0qtBV7GnEz/YczL3Mv8dinFHE+NUqoM89LfHZizUgohhJiGsHbXKKWqMC+EuUFr/Yq1eZN5l6rBHEFzI/CgMhekeAb4rdb6O6d6PiGEEMEJ9xDKf8ScR+UepdTEtv/CnLfjKeu+P2KupvJh4CwgSZnLlIE5EZa06IUQYorkilchhIhjcsWrEELEMSnyQggRx6TICyFEHJMiL4QQcUyKvBBCxDEp8kIIEcekyAshRBz7/5yziwljmJBHAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "coldrop = ['y_pred_tot', 'Year', 'y_test', 'y_test_tot']\n",
    "#need to make indoor months 0\n",
    "for i in Ind_Mon:\n",
    "    MLR[i][DemandPrediction] = 0\n",
    "\n",
    " #Adjust when we want the mean to occur\n",
    "for i in months:\n",
    "    \n",
    "    if i == 'Apr':\n",
    "        MLR[i].index = MLR[i].index - pd.DateOffset(days=15)\n",
    "    elif i == 'May':\n",
    "        MLR[i].index = MLR[i].index - pd.DateOffset(days=15)\n",
    "    elif i == 'Jun':\n",
    "        MLR[i].index = MLR[i].index - pd.DateOffset(days=15)\n",
    "    elif i == 'Jul':\n",
    "        MLR[i].index = MLR[i].index - pd.DateOffset(days=15)\n",
    "    elif i == 'Aug':\n",
    "        MLR[i].index = MLR[i].index - pd.DateOffset(days=15)\n",
    "    elif i == 'Sep':\n",
    "        MLR[i].index = MLR[i].index - pd.DateOffset(days=15)\n",
    "    elif i == 'Oct':\n",
    "        MLR[i].index = MLR[i].index - pd.DateOffset(days=15)\n",
    "    else:\n",
    "        MLR[i].index = MLR[i].index - pd.DateOffset(days=15)\n",
    "    MLR[i] = pd.DataFrame(MLR[i])\n",
    "    MLR[i] = MLR[i].drop(columns = coldrop)\n",
    "    \n",
    "    MLR2=copy.deepcopy(MLR)\n",
    "    if i == 'Apr':\n",
    "        MLR2[i].index = MLR2[i].index - pd.DateOffset(days=1)\n",
    "        MLR2[i]= MLR2[i][DemandPrediction]*PrePeakFact[0]\n",
    "    if i == 'May':\n",
    "        MLR2[i].index = MLR2[i].index - pd.DateOffset(days=1)\n",
    "        MLR2[i]= MLR2[i][DemandPrediction]*PrePeakFact[0]\n",
    "    elif i == 'Jun':\n",
    "        MLR2[i].index = MLR2[i].index - pd.DateOffset(days=1)\n",
    "        MLR2[i]= MLR2[i][DemandPrediction]*PrePeakFact[0]\n",
    "    elif i == 'Jul':\n",
    "        MLR2[i].index = MLR2[i].index - pd.DateOffset(days=1)\n",
    "        MLR2[i]= MLR2[i][DemandPrediction]*PrePeakFact[0]\n",
    "    elif i == 'Aug':\n",
    "        MLR2[i].index = MLR2[i].index - pd.DateOffset(days=1)\n",
    "        MLR2[i]= MLR2[i][DemandPrediction]*PostPeakFact[0]\n",
    "    elif i == 'Sep':\n",
    "        MLR2[i].index = MLR2[i].index - pd.DateOffset(days=1)\n",
    "        MLR2[i]= MLR2[i][DemandPrediction]*PostPeakFact[0]\n",
    "    elif i == 'Oct':\n",
    "        MLR2[i].index = MLR2[i].index - pd.DateOffset(days=1)\n",
    "        MLR2[i]= MLR2[i][DemandPrediction]*PostPeakFact[0]\n",
    "    else:\n",
    "        MLR2[i].index = MLR2[i].index - pd.DateOffset(days=1)\n",
    "        \n",
    "    #This adds another data point to help with demand curve, at the end of month\n",
    "    #This demand factors influences the 3rd week of the month\n",
    "    MLR3=copy.deepcopy(MLR)\n",
    "    if i == 'Apr':\n",
    "        MLR3[i].index = MLR3[i].index + pd.DateOffset(days=1)\n",
    "        MLR3[i]= MLR3[i][DemandPrediction]*PrePeakFact[2]\n",
    "    elif i == 'May':\n",
    "        MLR3[i].index = MLR3[i].index + pd.DateOffset(days=1)\n",
    "        MLR3[i]= MLR3[i][DemandPrediction]*PrePeakFact[2]\n",
    "    elif i == 'Jun':\n",
    "        MLR3[i].index = MLR3[i].index + pd.DateOffset(days=1)\n",
    "        MLR3[i]= MLR3[i][DemandPrediction]*PrePeakFact[2]\n",
    "    elif i == 'Jul':\n",
    "        MLR3[i].index = MLR3[i].index + pd.DateOffset(days=1)\n",
    "        MLR3[i]= MLR3[i][DemandPrediction]*PrePeakFact[2]\n",
    "    elif i == 'Aug':\n",
    "        MLR3[i].index = MLR3[i].index + pd.DateOffset(days=1)\n",
    "        MLR3[i]= MLR3[i][DemandPrediction]*PostPeakFact[2]\n",
    "    elif i == 'Sep':\n",
    "        MLR3[i].index = MLR3[i].index + pd.DateOffset(days=1)\n",
    "        MLR3[i]= MLR3[i][DemandPrediction]*PostPeakFact[2]\n",
    "    elif i == 'Oct':\n",
    "        MLR3[i].index = MLR3[i].index + pd.DateOffset(days=1)\n",
    "        MLR3[i]= MLR3[i][DemandPrediction]*PostPeakFact[2]\n",
    "    else:\n",
    "        MLR3[i].index = MLR3[i].index + pd.DateOffset(days=1)\n",
    "        \n",
    "        \n",
    "    #This adds another data point to help with demand curve, at the end of month\n",
    "    #This demand factor influences the last week of the month\n",
    "    MLR4=copy.deepcopy(MLR)\n",
    "    if i == 'Apr':\n",
    "        MLR4[i].index = MLR4[i].index + pd.DateOffset(days=2)\n",
    "        MLR4[i]= MLR4[i][DemandPrediction]*PrePeakFact[3]\n",
    "    elif i == 'May':\n",
    "        MLR4[i].index = MLR4[i].index + pd.DateOffset(days=2)\n",
    "        MLR4[i]= MLR4[i][DemandPrediction]*PrePeakFact[3]\n",
    "    elif i == 'Jun':\n",
    "        MLR4[i].index = MLR4[i].index + pd.DateOffset(days=2)\n",
    "        MLR4[i]= MLR4[i][DemandPrediction]*PrePeakFact[3]\n",
    "    elif i == 'Jul':\n",
    "        MLR4[i].index = MLR4[i].index + pd.DateOffset(days=2)\n",
    "        MLR4[i]= MLR4[i][DemandPrediction]*PrePeakFact[3]\n",
    "    elif i == 'Aug':\n",
    "        MLR4[i].index = MLR4[i].index + pd.DateOffset(days=2)\n",
    "        MLR4[i]= MLR4[i][DemandPrediction]*PostPeakFact[3]\n",
    "    elif i == 'Sep':\n",
    "        MLR4[i].index = MLR4[i].index + pd.DateOffset(days=2)\n",
    "        MLR4[i]= MLR4[i][DemandPrediction]*PostPeakFact[3]\n",
    "    elif i == 'Oct':\n",
    "        MLR4[i].index = MLR4[i].index + pd.DateOffset(days=2)\n",
    "        MLR4[i]= MLR4[i][DemandPrediction]*PostPeakFact[3]\n",
    "    else:\n",
    "        MLR4[i].index = MLR4[i].index + pd.DateOffset(days=2)\n",
    "        \n",
    "        \n",
    "    if i == 'Apr':\n",
    "        MLR[i]= MLR[i][DemandPrediction]*PrePeakFact[1]\n",
    "    elif i == 'May':\n",
    "        MLR[i]= MLR[i][DemandPrediction]*PrePeakFact[1]\n",
    "    elif i == 'Jun':\n",
    "        MLR[i]= MLR[i][DemandPrediction]*PrePeakFact[1]\n",
    "    elif i == 'Jul':\n",
    "        MLR[i]= MLR[i][DemandPrediction]*PrePeakFact[1]\n",
    "    elif i == 'Aug':\n",
    "        MLR[i]= MLR[i][DemandPrediction]*PostPeakFact[1]\n",
    "    elif i == 'Sep':\n",
    "        MLR[i]= MLR[i][DemandPrediction]*PostPeakFact[1]\n",
    "    elif i == 'Oct':\n",
    "        MLR[i]= MLR[i][DemandPrediction]*PostPeakFact[1]\n",
    "        \n",
    "    #connect DF's and drop duplicate indices\n",
    "    MLR[i] =pd.DataFrame(MLR[i])\n",
    "    Demand_Month = Demand_Month.append(pd.DataFrame(MLR[i]))\n",
    "    Demand_Month = Demand_Month.sort_index()\n",
    "    MLR2[i] =pd.DataFrame(MLR2[i])\n",
    "    MLR3[i] =pd.DataFrame(MLR3[i])\n",
    "    MLR4[i] =pd.DataFrame(MLR4[i])\n",
    "    MLR[i] = MLR[i].append(MLR2[i]).sort_index()\n",
    "    MLR[i] = MLR[i].append(MLR3[i]).sort_index()\n",
    "    MLR[i] = MLR[i].append(MLR4[i]).sort_index()\n",
    " \n",
    "\n",
    "#Cherry pick date range of interest, this is where you input a date\n",
    "\n",
    "MLR_Out_Demand = MLR_Out_Demand.loc[str(Year)+'-01-01': str(Year)+'-12-30']\n",
    "YearOffset = 2021-Year\n",
    "for i in months:\n",
    "    MLR[i].index = MLR[i].index + pd.DateOffset(years = YearOffset)\n",
    "    MLR_Out_Demand = MLR_Out_Demand.append(MLR[i])\n",
    "    \n",
    "#Sort the df index \n",
    "MLR_Out_DemandM = MLR_Out_Demand.copy()\n",
    "#print('MLR_Out_DemandM is:')\n",
    "#print (MLR_Out_DemandM)\n",
    " \n",
    "#interpolate between end of months to have better daily data\n",
    "MLR_Out_Demand = MLR_Out_Demand.reindex(pd.date_range(start=MLR_Out_Demand.index.min(),\n",
    "                                                  end=MLR_Out_Demand.index.max(),\n",
    "                                                  freq='3D'))\n",
    "#the spline order = 2 adds some demand pre April, however I think this is good as it adds a bit\n",
    "#of demand variability in the early months--Use this for the low flow scenario\n",
    "MLR_Out_Demand = MLR_Out_Demand.interpolate(method='spline', order = 3) \n",
    "\n",
    "#interpolate between end of months to have better daily data\n",
    "MLR_Out_Demand = MLR_Out_Demand.reindex(pd.date_range(start=MLR_Out_Demand.index.min(),\n",
    "                                                  end=MLR_Out_Demand.index.max(),\n",
    "                                                  freq='2D'))\n",
    "#the spline order = 2 adds some demand pre April, however I think this is good as it adds a bit\n",
    "#of demand variability in the early months--Use this for the low flow scenario\n",
    "MLR_Out_Demand = MLR_Out_Demand.interpolate(method='spline', order = 3) \n",
    "\n",
    "#interpolate between end of months to have better daily data\n",
    "MLR_Out_Demand = MLR_Out_Demand.reindex(pd.date_range(start=MLR_Out_Demand.index.min(),\n",
    "                                                  end=MLR_Out_Demand.index.max(),\n",
    "                                                  freq='1D'))\n",
    "#the spline order = 2 adds some demand pre April, however I think this is good as it adds a bit\n",
    "#of demand variability in the early months--Use this for the low flow scenario\n",
    "MLR_Out_Demand = MLR_Out_Demand.interpolate(method='spline', order = 3) \n",
    "\n",
    "MLR_Out_Demand['SLC_OutdoorDemand'] = MLR_Out_Demand[DemandPrediction].copy()\n",
    "del MLR_Out_Demand[DemandPrediction]\n",
    "\n",
    "#move the df to the desired date\n",
    "#MLR_Out_Demand2021=MLR_Out_Demand.copy()\n",
    "#MLR_Out_Demand2021 = IndexOffset(MLR_Out_Demand2021.copy(), YearOffset)\n",
    "#MLR_Out_Demand2021 = MLR_Out_Demand2021[~MLR_Out_Demand2021.index.duplicated(keep='first')]\n",
    "\n",
    "#make sure date range is correct!!! Need to add a leap year if/else statement\n",
    "#DateRange = pd.date_range(start=\"2021-1-28\",end=\"2021-12-30\")\n",
    "#MLR_Out_Demand2021['Time'] = DateRange- pd.DateOffset(days=15)\n",
    "#MLR_Out_Demand2021.index = MLR_Out_Demand2021['Time']\n",
    "#del MLR_Out_Demand2021['Time']\n",
    "\n",
    "MLR_Out_Demand = pd.DataFrame(MLR_Out_Demand)\n",
    "MLR_Out_Demand[MLR_Out_Demand < 0]=0\n",
    "\n",
    "#Fix interpolations errors with demands\n",
    "MLR_Out_Demand.SLC_OutdoorDemand.loc['2021-1-01': \"2021-3-30\"] = 0\n",
    "MLR_Out_Demand.SLC_OutdoorDemand.loc['2021-11-01': \"2021-12-30\"] = 0\n",
    "\n",
    "#Plot figure of interpolation time of interestest\n",
    "#MLR_Out_Demand2021.SLC_OutdoorDemand.loc['2021-1-01': \"2021-12-30\"].plot.line()\n",
    "\n",
    "#Update the water demand time series with forecasted values\n",
    "Demand_Forecast.update(MLR_Out_Demand.loc['2021-1-01': \"2021-12-30\"])\n",
    "#print('MLR_Out_Demand is')\n",
    "#print(MLR_Out_Demand)\n",
    "\n",
    "MLR_Out_Demand.SLC_OutdoorDemand.loc['2021-1-01': \"2021-12-30\"].plot.line()\n",
    "#Demand_Forecast.SLC_OutdoorDemand.loc['2013-01-01':'2016-12-30'].plot.line()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-26-c38864e3deff>:5: FutureWarning: Value based partial slicing on non-monotonic DatetimeIndexes with non-existing keys is deprecated and will raise a KeyError in a future Version.\n",
      "  OGOut_Demand = Out_Demand.loc[str(YR)+begdate:str(YR)+enddate].copy()\n",
      "<ipython-input-26-c38864e3deff>:57: FutureWarning: Value based partial slicing on non-monotonic DatetimeIndexes with non-existing keys is deprecated and will raise a KeyError in a future Version.\n",
      "  Out_Demand = pd.DataFrame(Out_Demand[pred][str(YR)+begdate:str(YR)+enddate])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.498981    0.000000  -0.498981      0.000000   \n",
      "2021-03-16                  0.498981    0.000000  -0.498981      0.000000   \n",
      "2021-03-17                  0.498981    0.000000  -0.498981      0.000000   \n",
      "2021-03-18                  0.498981    0.000000  -0.498981      0.000000   \n",
      "2021-04-13                 15.601432   20.734183   5.132751     20.734183   \n",
      "2021-04-15                 15.601432   20.734183   5.132751     20.734183   \n",
      "2021-04-16                 15.601432   20.734183   5.132751     20.734183   \n",
      "2021-04-17                 15.601432   20.734183   5.132751     20.734183   \n",
      "2021-05-15                 27.432980    9.782886 -17.650094      9.782886   \n",
      "2021-05-16                 27.432980    9.782886 -17.650094      9.782886   \n",
      "2021-05-17                 27.432980    9.782886 -17.650094      9.782886   \n",
      "2021-05-18                 27.432980    9.782886 -17.650094      9.782886   \n",
      "2021-06-14                208.223425  228.001702  19.778277    228.001702   \n",
      "2021-06-15                208.223425  228.001702  19.778277    228.001702   \n",
      "2021-06-16                208.223425  228.001702  19.778277    228.001702   \n",
      "2021-06-17                208.223425  228.001702  19.778277    228.001702   \n",
      "2021-07-15                216.218179  214.930296  -1.287883    214.930296   \n",
      "2021-07-16                216.218179  214.930296  -1.287883    214.930296   \n",
      "2021-07-17                216.218179  214.930296  -1.287883    214.930296   \n",
      "2021-07-18                216.218179  214.930296  -1.287883    214.930296   \n",
      "2021-08-15                174.653629  170.190510  -4.463118    170.190510   \n",
      "2021-08-16                174.653629  170.190510  -4.463118    170.190510   \n",
      "2021-08-17                174.653629  170.190510  -4.463118    170.190510   \n",
      "2021-08-18                174.653629  170.190510  -4.463118    170.190510   \n",
      "2021-09-14                172.383624  179.618162   7.234537    179.618162   \n",
      "2021-09-15                172.383624  179.618162   7.234537    179.618162   \n",
      "2021-09-16                172.383624  179.618162   7.234537    179.618162   \n",
      "2021-09-17                172.383624  179.618162   7.234537    179.618162   \n",
      "2021-10-15                 78.637119   72.291073  -6.346046     72.291073   \n",
      "2021-10-16                 78.637119   72.291073  -6.346046     72.291073   \n",
      "2021-10-17                 78.637119   72.291073  -6.346046     72.291073   \n",
      "2021-10-18                 78.637119   72.291073  -6.346046     72.291073   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      23.300559  \n",
      "2021-04-15      23.300559  \n",
      "2021-04-16      23.300559  \n",
      "2021-04-17      23.300559  \n",
      "2021-05-15       0.957840  \n",
      "2021-05-16       0.957840  \n",
      "2021-05-17       0.957840  \n",
      "2021-05-18       0.957840  \n",
      "2021-06-14     237.890841  \n",
      "2021-06-15     237.890841  \n",
      "2021-06-16     237.890841  \n",
      "2021-06-17     237.890841  \n",
      "2021-07-15     214.286354  \n",
      "2021-07-16     214.286354  \n",
      "2021-07-17     214.286354  \n",
      "2021-07-18     214.286354  \n",
      "2021-08-15     167.958951  \n",
      "2021-08-16     167.958951  \n",
      "2021-08-17     167.958951  \n",
      "2021-08-18     167.958951  \n",
      "2021-09-14     183.235430  \n",
      "2021-09-15     183.235430  \n",
      "2021-09-16     183.235430  \n",
      "2021-09-17     183.235430  \n",
      "2021-10-15      69.118050  \n",
      "2021-10-16      69.118050  \n",
      "2021-10-17      69.118050  \n",
      "2021-10-18      69.118050  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n",
      "2021-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.113410    0.000000  -0.113410      0.000000   \n",
      "2021-03-16                  0.113410    0.000000  -0.113410      0.000000   \n",
      "2021-03-17                  0.113410    0.000000  -0.113410      0.000000   \n",
      "2021-03-18                  0.113410    0.000000  -0.113410      0.000000   \n",
      "2021-04-13                 17.435956   20.734183   3.298228     23.300559   \n",
      "2021-04-15                 17.435956   20.734183   3.298228     23.300559   \n",
      "2021-04-16                 17.435956   20.734183   3.298228     23.300559   \n",
      "2021-04-17                 17.435956   20.734183   3.298228     23.300559   \n",
      "2021-05-15                 23.793416    9.782886 -14.010530      0.957840   \n",
      "2021-05-16                 23.793416    9.782886 -14.010530      0.957840   \n",
      "2021-05-17                 23.793416    9.782886 -14.010530      0.957840   \n",
      "2021-05-18                 23.793416    9.782886 -14.010530      0.957840   \n",
      "2021-06-14                216.626467  228.001702  11.375235    237.890841   \n",
      "2021-06-15                216.626467  228.001702  11.375235    237.890841   \n",
      "2021-06-16                216.626467  228.001702  11.375235    237.890841   \n",
      "2021-06-17                216.626467  228.001702  11.375235    237.890841   \n",
      "2021-07-15                214.232254  214.930296   0.698041    214.286354   \n",
      "2021-07-16                214.232254  214.930296   0.698041    214.286354   \n",
      "2021-07-17                214.232254  214.930296   0.698041    214.286354   \n",
      "2021-07-18                214.232254  214.930296   0.698041    214.286354   \n",
      "2021-08-15                174.117393  170.190510  -3.926883    167.958951   \n",
      "2021-08-16                174.117393  170.190510  -3.926883    167.958951   \n",
      "2021-08-17                174.117393  170.190510  -3.926883    167.958951   \n",
      "2021-08-18                174.117393  170.190510  -3.926883    167.958951   \n",
      "2021-09-14                171.532892  179.618162   8.085270    183.235430   \n",
      "2021-09-15                171.532892  179.618162   8.085270    183.235430   \n",
      "2021-09-16                171.532892  179.618162   8.085270    183.235430   \n",
      "2021-09-17                171.532892  179.618162   8.085270    183.235430   \n",
      "2021-10-15                 67.553776   72.291073   4.737297     69.118050   \n",
      "2021-10-16                 67.553776   72.291073   4.737297     69.118050   \n",
      "2021-10-17                 67.553776   72.291073   4.737297     69.118050   \n",
      "2021-10-18                 67.553776   72.291073   4.737297     69.118050   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      24.949672  \n",
      "2021-04-15      24.949672  \n",
      "2021-04-16      24.949672  \n",
      "2021-04-17      24.949672  \n",
      "2021-05-15       0.000000  \n",
      "2021-05-16       0.000000  \n",
      "2021-05-17       0.000000  \n",
      "2021-05-18       0.000000  \n",
      "2021-06-14     243.578458  \n",
      "2021-06-15     243.578458  \n",
      "2021-06-16     243.578458  \n",
      "2021-06-17     243.578458  \n",
      "2021-07-15     214.635375  \n",
      "2021-07-16     214.635375  \n",
      "2021-07-17     214.635375  \n",
      "2021-07-18     214.635375  \n",
      "2021-08-15     165.995510  \n",
      "2021-08-16     165.995510  \n",
      "2021-08-17     165.995510  \n",
      "2021-08-18     165.995510  \n",
      "2021-09-14     187.278066  \n",
      "2021-09-15     187.278066  \n",
      "2021-09-16     187.278066  \n",
      "2021-09-17     187.278066  \n",
      "2021-10-15      71.486698  \n",
      "2021-10-16      71.486698  \n",
      "2021-10-17      71.486698  \n",
      "2021-10-18      71.486698  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n",
      "2021-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.113523    0.000000  -0.113523      0.000000   \n",
      "2021-03-16                  0.113523    0.000000  -0.113523      0.000000   \n",
      "2021-03-17                  0.113523    0.000000  -0.113523      0.000000   \n",
      "2021-03-18                  0.113523    0.000000  -0.113523      0.000000   \n",
      "2021-04-13                 19.148347   20.734183   1.585836     24.949672   \n",
      "2021-04-15                 19.148347   20.734183   1.585836     24.949672   \n",
      "2021-04-16                 19.148347   20.734183   1.585836     24.949672   \n",
      "2021-04-17                 19.148347   20.734183   1.585836     24.949672   \n",
      "2021-05-15                 24.394904    9.782886 -14.612018      0.000000   \n",
      "2021-05-16                 24.394904    9.782886 -14.612018      0.000000   \n",
      "2021-05-17                 24.394904    9.782886 -14.612018      0.000000   \n",
      "2021-05-18                 24.394904    9.782886 -14.612018      0.000000   \n",
      "2021-06-14                220.730542  228.001702   7.271161    243.578458   \n",
      "2021-06-15                220.730542  228.001702   7.271161    243.578458   \n",
      "2021-06-16                220.730542  228.001702   7.271161    243.578458   \n",
      "2021-06-17                220.730542  228.001702   7.271161    243.578458   \n",
      "2021-07-15                214.278319  214.930296   0.651976    214.635375   \n",
      "2021-07-16                214.278319  214.930296   0.651976    214.635375   \n",
      "2021-07-17                214.278319  214.930296   0.651976    214.635375   \n",
      "2021-07-18                214.278319  214.930296   0.651976    214.635375   \n",
      "2021-08-15                172.962910  170.190510  -2.772400    165.995510   \n",
      "2021-08-16                172.962910  170.190510  -2.772400    165.995510   \n",
      "2021-08-17                172.962910  170.190510  -2.772400    165.995510   \n",
      "2021-08-18                172.962910  170.190510  -2.772400    165.995510   \n",
      "2021-09-14                174.881721  179.618162   4.736441    187.278066   \n",
      "2021-09-15                174.881721  179.618162   4.736441    187.278066   \n",
      "2021-09-16                174.881721  179.618162   4.736441    187.278066   \n",
      "2021-09-17                174.881721  179.618162   4.736441    187.278066   \n",
      "2021-10-15                 69.382371   72.291073   2.908702     71.486698   \n",
      "2021-10-16                 69.382371   72.291073   2.908702     71.486698   \n",
      "2021-10-17                 69.382371   72.291073   2.908702     71.486698   \n",
      "2021-10-18                 69.382371   72.291073   2.908702     71.486698   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      25.742590  \n",
      "2021-04-15      25.742590  \n",
      "2021-04-16      25.742590  \n",
      "2021-04-17      25.742590  \n",
      "2021-05-15       0.000000  \n",
      "2021-05-16       0.000000  \n",
      "2021-05-17       0.000000  \n",
      "2021-05-18       0.000000  \n",
      "2021-06-14     247.214039  \n",
      "2021-06-15     247.214039  \n",
      "2021-06-16     247.214039  \n",
      "2021-06-17     247.214039  \n",
      "2021-07-15     214.961363  \n",
      "2021-07-16     214.961363  \n",
      "2021-07-17     214.961363  \n",
      "2021-07-18     214.961363  \n",
      "2021-08-15     164.609310  \n",
      "2021-08-16     164.609310  \n",
      "2021-08-17     164.609310  \n",
      "2021-08-18     164.609310  \n",
      "2021-09-14     189.646286  \n",
      "2021-09-15     189.646286  \n",
      "2021-09-16     189.646286  \n",
      "2021-09-17     189.646286  \n",
      "2021-10-15      72.941049  \n",
      "2021-10-16      72.941049  \n",
      "2021-10-17      72.941049  \n",
      "2021-10-18      72.941049  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n",
      "2021-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.120525    0.000000  -0.120525      0.000000   \n",
      "2021-03-16                  0.120525    0.000000  -0.120525      0.000000   \n",
      "2021-03-17                  0.120525    0.000000  -0.120525      0.000000   \n",
      "2021-03-18                  0.120525    0.000000  -0.120525      0.000000   \n",
      "2021-04-13                 19.796378   20.734183   0.937805     25.742590   \n",
      "2021-04-15                 19.796378   20.734183   0.937805     25.742590   \n",
      "2021-04-16                 19.796378   20.734183   0.937805     25.742590   \n",
      "2021-04-17                 19.796378   20.734183   0.937805     25.742590   \n",
      "2021-05-15                 24.739095    9.782886 -14.956208      0.000000   \n",
      "2021-05-16                 24.739095    9.782886 -14.956208      0.000000   \n",
      "2021-05-17                 24.739095    9.782886 -14.956208      0.000000   \n",
      "2021-05-18                 24.739095    9.782886 -14.956208      0.000000   \n",
      "2021-06-14                223.770473  228.001702   4.231230    247.214039   \n",
      "2021-06-15                223.770473  228.001702   4.231230    247.214039   \n",
      "2021-06-16                223.770473  228.001702   4.231230    247.214039   \n",
      "2021-06-17                223.770473  228.001702   4.231230    247.214039   \n",
      "2021-07-15                214.686666  214.930296   0.243630    214.961363   \n",
      "2021-07-16                214.686666  214.930296   0.243630    214.961363   \n",
      "2021-07-17                214.686666  214.930296   0.243630    214.961363   \n",
      "2021-07-18                214.686666  214.930296   0.243630    214.961363   \n",
      "2021-08-15                172.016610  170.190510  -1.826100    164.609310   \n",
      "2021-08-16                172.016610  170.190510  -1.826100    164.609310   \n",
      "2021-08-17                172.016610  170.190510  -1.826100    164.609310   \n",
      "2021-08-18                172.016610  170.190510  -1.826100    164.609310   \n",
      "2021-09-14                176.852963  179.618162   2.765199    189.646286   \n",
      "2021-09-15                176.852963  179.618162   2.765199    189.646286   \n",
      "2021-09-16                176.852963  179.618162   2.765199    189.646286   \n",
      "2021-09-17                176.852963  179.618162   2.765199    189.646286   \n",
      "2021-10-15                 70.446560   72.291073   1.844513     72.941049   \n",
      "2021-10-16                 70.446560   72.291073   1.844513     72.941049   \n",
      "2021-10-17                 70.446560   72.291073   1.844513     72.941049   \n",
      "2021-10-18                 70.446560   72.291073   1.844513     72.941049   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      26.211493  \n",
      "2021-04-15      26.211493  \n",
      "2021-04-16      26.211493  \n",
      "2021-04-17      26.211493  \n",
      "2021-05-15       0.000000  \n",
      "2021-05-16       0.000000  \n",
      "2021-05-17       0.000000  \n",
      "2021-05-18       0.000000  \n",
      "2021-06-14     249.329654  \n",
      "2021-06-15     249.329654  \n",
      "2021-06-16     249.329654  \n",
      "2021-06-17     249.329654  \n",
      "2021-07-15     215.083178  \n",
      "2021-07-16     215.083178  \n",
      "2021-07-17     215.083178  \n",
      "2021-07-18     215.083178  \n",
      "2021-08-15     163.696260  \n",
      "2021-08-16     163.696260  \n",
      "2021-08-17     163.696260  \n",
      "2021-08-18     163.696260  \n",
      "2021-09-14     191.028885  \n",
      "2021-09-15     191.028885  \n",
      "2021-09-16     191.028885  \n",
      "2021-09-17     191.028885  \n",
      "2021-10-15      73.863306  \n",
      "2021-10-16      73.863306  \n",
      "2021-10-17      73.863306  \n",
      "2021-10-18      73.863306  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n",
      "2021-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.120561    0.000000  -0.120561      0.000000   \n",
      "2021-03-16                  0.120561    0.000000  -0.120561      0.000000   \n",
      "2021-03-17                  0.120561    0.000000  -0.120561      0.000000   \n",
      "2021-03-18                  0.120561    0.000000  -0.120561      0.000000   \n",
      "2021-04-13                 20.238531   20.734183   0.495652     26.211493   \n",
      "2021-04-15                 20.238531   20.734183   0.495652     26.211493   \n",
      "2021-04-16                 20.238531   20.734183   0.495652     26.211493   \n",
      "2021-04-17                 20.238531   20.734183   0.495652     26.211493   \n",
      "2021-05-15                 25.037679    9.782886 -15.254793      0.000000   \n",
      "2021-05-16                 25.037679    9.782886 -15.254793      0.000000   \n",
      "2021-05-17                 25.037679    9.782886 -15.254793      0.000000   \n",
      "2021-05-18                 25.037679    9.782886 -15.254793      0.000000   \n",
      "2021-06-14                225.484789  228.001702   2.516914    249.329654   \n",
      "2021-06-15                225.484789  228.001702   2.516914    249.329654   \n",
      "2021-06-16                225.484789  228.001702   2.516914    249.329654   \n",
      "2021-06-17                225.484789  228.001702   2.516914    249.329654   \n",
      "2021-07-15                214.852156  214.930296   0.078140    215.083178   \n",
      "2021-07-16                214.852156  214.930296   0.078140    215.083178   \n",
      "2021-07-17                214.852156  214.930296   0.078140    215.083178   \n",
      "2021-07-18                214.852156  214.930296   0.078140    215.083178   \n",
      "2021-08-15                171.366743  170.190510  -1.176232    163.696260   \n",
      "2021-08-16                171.366743  170.190510  -1.176232    163.696260   \n",
      "2021-08-17                171.366743  170.190510  -1.176232    163.696260   \n",
      "2021-08-18                171.366743  170.190510  -1.176232    163.696260   \n",
      "2021-09-14                177.972518  179.618162   1.645644    191.028885   \n",
      "2021-09-15                177.972518  179.618162   1.645644    191.028885   \n",
      "2021-09-16                177.972518  179.618162   1.645644    191.028885   \n",
      "2021-09-17                177.972518  179.618162   1.645644    191.028885   \n",
      "2021-10-15                 71.188089   72.291073   1.102984     73.863306   \n",
      "2021-10-16                 71.188089   72.291073   1.102984     73.863306   \n",
      "2021-10-17                 71.188089   72.291073   1.102984     73.863306   \n",
      "2021-10-18                 71.188089   72.291073   1.102984     73.863306   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      26.459319  \n",
      "2021-04-15      26.459319  \n",
      "2021-04-16      26.459319  \n",
      "2021-04-17      26.459319  \n",
      "2021-05-15       0.000000  \n",
      "2021-05-16       0.000000  \n",
      "2021-05-17       0.000000  \n",
      "2021-05-18       0.000000  \n",
      "2021-06-14     250.588111  \n",
      "2021-06-15     250.588111  \n",
      "2021-06-16     250.588111  \n",
      "2021-06-17     250.588111  \n",
      "2021-07-15     215.122248  \n",
      "2021-07-16     215.122248  \n",
      "2021-07-17     215.122248  \n",
      "2021-07-18     215.122248  \n",
      "2021-08-15     163.108144  \n",
      "2021-08-16     163.108144  \n",
      "2021-08-17     163.108144  \n",
      "2021-08-18     163.108144  \n",
      "2021-09-14     191.851707  \n",
      "2021-09-15     191.851707  \n",
      "2021-09-16     191.851707  \n",
      "2021-09-17     191.851707  \n",
      "2021-10-15      74.414797  \n",
      "2021-10-16      74.414797  \n",
      "2021-10-17      74.414797  \n",
      "2021-10-18      74.414797  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2021-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.115711    0.000000  -0.115711      0.000000   \n",
      "2021-03-16                  0.115711    0.000000  -0.115711      0.000000   \n",
      "2021-03-17                  0.115711    0.000000  -0.115711      0.000000   \n",
      "2021-03-18                  0.115711    0.000000  -0.115711      0.000000   \n",
      "2021-04-13                 20.588331   20.734183   0.145852     26.459319   \n",
      "2021-04-15                 20.588331   20.734183   0.145852     26.459319   \n",
      "2021-04-16                 20.588331   20.734183   0.145852     26.459319   \n",
      "2021-04-17                 20.588331   20.734183   0.145852     26.459319   \n",
      "2021-05-15                 25.346925    9.782886 -15.564038      0.000000   \n",
      "2021-05-16                 25.346925    9.782886 -15.564038      0.000000   \n",
      "2021-05-17                 25.346925    9.782886 -15.564038      0.000000   \n",
      "2021-05-18                 25.346925    9.782886 -15.564038      0.000000   \n",
      "2021-06-14                226.338030  228.001702   1.663672    250.588111   \n",
      "2021-06-15                226.338030  228.001702   1.663672    250.588111   \n",
      "2021-06-16                226.338030  228.001702   1.663672    250.588111   \n",
      "2021-06-17                226.338030  228.001702   1.663672    250.588111   \n",
      "2021-07-15                215.034856  214.930296  -0.104561    215.122248   \n",
      "2021-07-16                215.034856  214.930296  -0.104561    215.122248   \n",
      "2021-07-17                215.034856  214.930296  -0.104561    215.122248   \n",
      "2021-07-18                215.034856  214.930296  -0.104561    215.122248   \n",
      "2021-08-15                170.850365  170.190510  -0.659854    163.108144   \n",
      "2021-08-16                170.850365  170.190510  -0.659854    163.108144   \n",
      "2021-08-17                170.850365  170.190510  -0.659854    163.108144   \n",
      "2021-08-18                170.850365  170.190510  -0.659854    163.108144   \n",
      "2021-09-14                178.294482  179.618162   1.323680    191.851707   \n",
      "2021-09-15                178.294482  179.618162   1.323680    191.851707   \n",
      "2021-09-16                178.294482  179.618162   1.323680    191.851707   \n",
      "2021-09-17                178.294482  179.618162   1.323680    191.851707   \n",
      "2021-10-15                 71.993810   72.291073   0.297263     74.414797   \n",
      "2021-10-16                 71.993810   72.291073   0.297263     74.414797   \n",
      "2021-10-17                 71.993810   72.291073   0.297263     74.414797   \n",
      "2021-10-18                 71.993810   72.291073   0.297263     74.414797   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      26.532245  \n",
      "2021-04-15      26.532245  \n",
      "2021-04-16      26.532245  \n",
      "2021-04-17      26.532245  \n",
      "2021-05-15       0.000000  \n",
      "2021-05-16       0.000000  \n",
      "2021-05-17       0.000000  \n",
      "2021-05-18       0.000000  \n",
      "2021-06-14     251.419947  \n",
      "2021-06-15     251.419947  \n",
      "2021-06-16     251.419947  \n",
      "2021-06-17     251.419947  \n",
      "2021-07-15     215.069968  \n",
      "2021-07-16     215.069968  \n",
      "2021-07-17     215.069968  \n",
      "2021-07-18     215.069968  \n",
      "2021-08-15     162.778217  \n",
      "2021-08-16     162.778217  \n",
      "2021-08-17     162.778217  \n",
      "2021-08-18     162.778217  \n",
      "2021-09-14     192.513547  \n",
      "2021-09-15     192.513547  \n",
      "2021-09-16     192.513547  \n",
      "2021-09-17     192.513547  \n",
      "2021-10-15      74.563429  \n",
      "2021-10-16      74.563429  \n",
      "2021-10-17      74.563429  \n",
      "2021-10-18      74.563429  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n",
      "2021-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.120797    0.000000  -0.120797      0.000000   \n",
      "2021-03-16                  0.120797    0.000000  -0.120797      0.000000   \n",
      "2021-03-17                  0.120797    0.000000  -0.120797      0.000000   \n",
      "2021-03-18                  0.120797    0.000000  -0.120797      0.000000   \n",
      "2021-04-13                 20.564909   20.734183   0.169274     26.532245   \n",
      "2021-04-15                 20.564909   20.734183   0.169274     26.532245   \n",
      "2021-04-16                 20.564909   20.734183   0.169274     26.532245   \n",
      "2021-04-17                 20.564909   20.734183   0.169274     26.532245   \n",
      "2021-05-15                 25.463310    9.782886 -15.680423      0.000000   \n",
      "2021-05-16                 25.463310    9.782886 -15.680423      0.000000   \n",
      "2021-05-17                 25.463310    9.782886 -15.680423      0.000000   \n",
      "2021-05-18                 25.463310    9.782886 -15.680423      0.000000   \n",
      "2021-06-14                227.043374  228.001702   0.958328    251.419947   \n",
      "2021-06-15                227.043374  228.001702   0.958328    251.419947   \n",
      "2021-06-16                227.043374  228.001702   0.958328    251.419947   \n",
      "2021-06-17                227.043374  228.001702   0.958328    251.419947   \n",
      "2021-07-15                214.941370  214.930296  -0.011075    215.069968   \n",
      "2021-07-16                214.941370  214.930296  -0.011075    215.069968   \n",
      "2021-07-17                214.941370  214.930296  -0.011075    215.069968   \n",
      "2021-07-18                214.941370  214.930296  -0.011075    215.069968   \n",
      "2021-08-15                170.709106  170.190510  -0.518595    162.778217   \n",
      "2021-08-16                170.709106  170.190510  -0.518595    162.778217   \n",
      "2021-08-17                170.709106  170.190510  -0.518595    162.778217   \n",
      "2021-08-18                170.709106  170.190510  -0.518595    162.778217   \n",
      "2021-09-14                179.052589  179.618162   0.565572    192.513547   \n",
      "2021-09-15                179.052589  179.618162   0.565572    192.513547   \n",
      "2021-09-16                179.052589  179.618162   0.565572    192.513547   \n",
      "2021-09-17                179.052589  179.618162   0.565572    192.513547   \n",
      "2021-10-15                 71.844310   72.291073   0.446763     74.563429   \n",
      "2021-10-16                 71.844310   72.291073   0.446763     74.563429   \n",
      "2021-10-17                 71.844310   72.291073   0.446763     74.563429   \n",
      "2021-10-18                 71.844310   72.291073   0.446763     74.563429   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      26.616882  \n",
      "2021-04-15      26.616882  \n",
      "2021-04-16      26.616882  \n",
      "2021-04-17      26.616882  \n",
      "2021-05-15       0.000000  \n",
      "2021-05-16       0.000000  \n",
      "2021-05-17       0.000000  \n",
      "2021-05-18       0.000000  \n",
      "2021-06-14     251.899111  \n",
      "2021-06-15     251.899111  \n",
      "2021-06-16     251.899111  \n",
      "2021-06-17     251.899111  \n",
      "2021-07-15     215.064430  \n",
      "2021-07-16     215.064430  \n",
      "2021-07-17     215.064430  \n",
      "2021-07-18     215.064430  \n",
      "2021-08-15     162.518919  \n",
      "2021-08-16     162.518919  \n",
      "2021-08-17     162.518919  \n",
      "2021-08-18     162.518919  \n",
      "2021-09-14     192.796333  \n",
      "2021-09-15     192.796333  \n",
      "2021-09-16     192.796333  \n",
      "2021-09-17     192.796333  \n",
      "2021-10-15      74.786810  \n",
      "2021-10-16      74.786810  \n",
      "2021-10-17      74.786810  \n",
      "2021-10-18      74.786810  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n",
      "2021-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.120770    0.000000  -0.120770      0.000000   \n",
      "2021-03-16                  0.120770    0.000000  -0.120770      0.000000   \n",
      "2021-03-17                  0.120770    0.000000  -0.120770      0.000000   \n",
      "2021-03-18                  0.120770    0.000000  -0.120770      0.000000   \n",
      "2021-04-13                 20.651745   20.734183   0.082438     26.616882   \n",
      "2021-04-15                 20.651745   20.734183   0.082438     26.616882   \n",
      "2021-04-16                 20.651745   20.734183   0.082438     26.616882   \n",
      "2021-04-17                 20.651745   20.734183   0.082438     26.616882   \n",
      "2021-05-15                 25.531782    9.782886 -15.748895      0.000000   \n",
      "2021-05-16                 25.531782    9.782886 -15.748895      0.000000   \n",
      "2021-05-17                 25.531782    9.782886 -15.748895      0.000000   \n",
      "2021-05-18                 25.531782    9.782886 -15.748895      0.000000   \n",
      "2021-06-14                227.425169  228.001702   0.576534    251.899111   \n",
      "2021-06-15                227.425169  228.001702   0.576534    251.899111   \n",
      "2021-06-16                227.425169  228.001702   0.576534    251.899111   \n",
      "2021-06-17                227.425169  228.001702   0.576534    251.899111   \n",
      "2021-07-15                214.945151  214.930296  -0.014855    215.064430   \n",
      "2021-07-16                214.945151  214.930296  -0.014855    215.064430   \n",
      "2021-07-17                214.945151  214.930296  -0.014855    215.064430   \n",
      "2021-07-18                214.945151  214.930296  -0.014855    215.064430   \n",
      "2021-08-15                170.512540  170.190510  -0.322029    162.518919   \n",
      "2021-08-16                170.512540  170.190510  -0.322029    162.518919   \n",
      "2021-08-17                170.512540  170.190510  -0.322029    162.518919   \n",
      "2021-08-18                170.512540  170.190510  -0.322029    162.518919   \n",
      "2021-09-14                179.276036  179.618162   0.342126    192.796333   \n",
      "2021-09-15                179.276036  179.618162   0.342126    192.796333   \n",
      "2021-09-16                179.276036  179.618162   0.342126    192.796333   \n",
      "2021-09-17                179.276036  179.618162   0.342126    192.796333   \n",
      "2021-10-15                 72.013027   72.291073   0.278046     74.786810   \n",
      "2021-10-16                 72.013027   72.291073   0.278046     74.786810   \n",
      "2021-10-17                 72.013027   72.291073   0.278046     74.786810   \n",
      "2021-10-18                 72.013027   72.291073   0.278046     74.786810   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      26.658101  \n",
      "2021-04-15      26.658101  \n",
      "2021-04-16      26.658101  \n",
      "2021-04-17      26.658101  \n",
      "2021-05-15       0.000000  \n",
      "2021-05-16       0.000000  \n",
      "2021-05-17       0.000000  \n",
      "2021-05-18       0.000000  \n",
      "2021-06-14     252.187378  \n",
      "2021-06-15     252.187378  \n",
      "2021-06-16     252.187378  \n",
      "2021-06-17     252.187378  \n",
      "2021-07-15     215.057003  \n",
      "2021-07-16     215.057003  \n",
      "2021-07-17     215.057003  \n",
      "2021-07-18     215.057003  \n",
      "2021-08-15     162.357905  \n",
      "2021-08-16     162.357905  \n",
      "2021-08-17     162.357905  \n",
      "2021-08-18     162.357905  \n",
      "2021-09-14     192.967396  \n",
      "2021-09-15     192.967396  \n",
      "2021-09-16     192.967396  \n",
      "2021-09-17     192.967396  \n",
      "2021-10-15      74.925833  \n",
      "2021-10-16      74.925833  \n",
      "2021-10-17      74.925833  \n",
      "2021-10-18      74.925833  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n",
      "2021-12-18       0.000000  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.120712    0.000000  -0.120712      0.000000   \n",
      "2021-03-16                  0.120712    0.000000  -0.120712      0.000000   \n",
      "2021-03-17                  0.120712    0.000000  -0.120712      0.000000   \n",
      "2021-03-18                  0.120712    0.000000  -0.120712      0.000000   \n",
      "2021-04-13                 20.696312   20.734183   0.037871     26.658101   \n",
      "2021-04-15                 20.696312   20.734183   0.037871     26.658101   \n",
      "2021-04-16                 20.696312   20.734183   0.037871     26.658101   \n",
      "2021-04-17                 20.696312   20.734183   0.037871     26.658101   \n",
      "2021-05-15                 25.571828    9.782886 -15.788942      0.000000   \n",
      "2021-05-16                 25.571828    9.782886 -15.788942      0.000000   \n",
      "2021-05-17                 25.571828    9.782886 -15.788942      0.000000   \n",
      "2021-05-18                 25.571828    9.782886 -15.788942      0.000000   \n",
      "2021-06-14                227.654965  228.001702   0.346738    252.187378   \n",
      "2021-06-15                227.654965  228.001702   0.346738    252.187378   \n",
      "2021-06-16                227.654965  228.001702   0.346738    252.187378   \n",
      "2021-06-17                227.654965  228.001702   0.346738    252.187378   \n",
      "2021-07-15                214.943907  214.930296  -0.013612    215.057003   \n",
      "2021-07-16                214.943907  214.930296  -0.013612    215.057003   \n",
      "2021-07-17                214.943907  214.930296  -0.013612    215.057003   \n",
      "2021-07-18                214.943907  214.930296  -0.013612    215.057003   \n",
      "2021-08-15                170.389558  170.190510  -0.199048    162.357905   \n",
      "2021-08-16                170.389558  170.190510  -0.199048    162.357905   \n",
      "2021-08-17                170.389558  170.190510  -0.199048    162.357905   \n",
      "2021-08-18                170.389558  170.190510  -0.199048    162.357905   \n",
      "2021-09-14                179.411544  179.618162   0.206618    192.967396   \n",
      "2021-09-15                179.411544  179.618162   0.206618    192.967396   \n",
      "2021-09-16                179.411544  179.618162   0.206618    192.967396   \n",
      "2021-09-17                179.411544  179.618162   0.206618    192.967396   \n",
      "2021-10-15                 72.118500   72.291073   0.172573     74.925833   \n",
      "2021-10-16                 72.118500   72.291073   0.172573     74.925833   \n",
      "2021-10-17                 72.118500   72.291073   0.172573     74.925833   \n",
      "2021-10-18                 72.118500   72.291073   0.172573     74.925833   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      26.677037  \n",
      "2021-04-15      26.677037  \n",
      "2021-04-16      26.677037  \n",
      "2021-04-17      26.677037  \n",
      "2021-05-15       0.000000  \n",
      "2021-05-16       0.000000  \n",
      "2021-05-17       0.000000  \n",
      "2021-05-18       0.000000  \n",
      "2021-06-14     252.360746  \n",
      "2021-06-15     252.360746  \n",
      "2021-06-16     252.360746  \n",
      "2021-06-17     252.360746  \n",
      "2021-07-15     215.050197  \n",
      "2021-07-16     215.050197  \n",
      "2021-07-17     215.050197  \n",
      "2021-07-18     215.050197  \n",
      "2021-08-15     162.258381  \n",
      "2021-08-16     162.258381  \n",
      "2021-08-17     162.258381  \n",
      "2021-08-18     162.258381  \n",
      "2021-09-14     193.070705  \n",
      "2021-09-15     193.070705  \n",
      "2021-09-16     193.070705  \n",
      "2021-09-17     193.070705  \n",
      "2021-10-15      75.012120  \n",
      "2021-10-16      75.012120  \n",
      "2021-10-17      75.012120  \n",
      "2021-10-18      75.012120  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n",
      "2021-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.181788    0.000000  -0.181788      0.000000   \n",
      "2021-03-16                  0.181788    0.000000  -0.181788      0.000000   \n",
      "2021-03-17                  0.181788    0.000000  -0.181788      0.000000   \n",
      "2021-03-18                  0.181788    0.000000  -0.181788      0.000000   \n",
      "2021-04-13                 20.787056   20.734183  -0.052873     26.677037   \n",
      "2021-04-15                 20.787056   20.734183  -0.052873     26.677037   \n",
      "2021-04-16                 20.787056   20.734183  -0.052873     26.677037   \n",
      "2021-04-17                 20.787056   20.734183  -0.052873     26.677037   \n",
      "2021-05-15                 25.444919    9.782886 -15.662032      0.000000   \n",
      "2021-05-16                 25.444919    9.782886 -15.662032      0.000000   \n",
      "2021-05-17                 25.444919    9.782886 -15.662032      0.000000   \n",
      "2021-05-18                 25.444919    9.782886 -15.662032      0.000000   \n",
      "2021-06-14                227.888373  228.001702   0.113330    252.360746   \n",
      "2021-06-15                227.888373  228.001702   0.113330    252.360746   \n",
      "2021-06-16                227.888373  228.001702   0.113330    252.360746   \n",
      "2021-06-17                227.888373  228.001702   0.113330    252.360746   \n",
      "2021-07-15                214.933955  214.930296  -0.003659    215.050197   \n",
      "2021-07-16                214.933955  214.930296  -0.003659    215.050197   \n",
      "2021-07-17                214.933955  214.930296  -0.003659    215.050197   \n",
      "2021-07-18                214.933955  214.930296  -0.003659    215.050197   \n",
      "2021-08-15                170.326762  170.190510  -0.136252    162.258381   \n",
      "2021-08-16                170.326762  170.190510  -0.136252    162.258381   \n",
      "2021-08-17                170.326762  170.190510  -0.136252    162.258381   \n",
      "2021-08-18                170.326762  170.190510  -0.136252    162.258381   \n",
      "2021-09-14                179.591737  179.618162   0.026425    193.070705   \n",
      "2021-09-15                179.591737  179.618162   0.026425    193.070705   \n",
      "2021-09-16                179.591737  179.618162   0.026425    193.070705   \n",
      "2021-09-17                179.591737  179.618162   0.026425    193.070705   \n",
      "2021-10-15                 72.015303   72.291073   0.275770     75.012120   \n",
      "2021-10-16                 72.015303   72.291073   0.275770     75.012120   \n",
      "2021-10-17                 72.015303   72.291073   0.275770     75.012120   \n",
      "2021-10-18                 72.015303   72.291073   0.275770     75.012120   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      26.650600  \n",
      "2021-04-15      26.650600  \n",
      "2021-04-16      26.650600  \n",
      "2021-04-17      26.650600  \n",
      "2021-05-15       0.000000  \n",
      "2021-05-16       0.000000  \n",
      "2021-05-17       0.000000  \n",
      "2021-05-18       0.000000  \n",
      "2021-06-14     252.417411  \n",
      "2021-06-15     252.417411  \n",
      "2021-06-16     252.417411  \n",
      "2021-06-17     252.417411  \n",
      "2021-07-15     215.048367  \n",
      "2021-07-16     215.048367  \n",
      "2021-07-17     215.048367  \n",
      "2021-07-18     215.048367  \n",
      "2021-08-15     162.190255  \n",
      "2021-08-16     162.190255  \n",
      "2021-08-17     162.190255  \n",
      "2021-08-18     162.190255  \n",
      "2021-09-14     193.083917  \n",
      "2021-09-15     193.083917  \n",
      "2021-09-16     193.083917  \n",
      "2021-09-17     193.083917  \n",
      "2021-10-15      75.150005  \n",
      "2021-10-16      75.150005  \n",
      "2021-10-17      75.150005  \n",
      "2021-10-18      75.150005  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n",
      "2021-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.181548    0.000000  -0.181548      0.000000   \n",
      "2021-03-16                  0.181548    0.000000  -0.181548      0.000000   \n",
      "2021-03-17                  0.181548    0.000000  -0.181548      0.000000   \n",
      "2021-03-18                  0.181548    0.000000  -0.181548      0.000000   \n",
      "2021-04-13                 20.773418   20.734183  -0.039235     26.650600   \n",
      "2021-04-15                 20.773418   20.734183  -0.039235     26.650600   \n",
      "2021-04-16                 20.773418   20.734183  -0.039235     26.650600   \n",
      "2021-04-17                 20.773418   20.734183  -0.039235     26.650600   \n",
      "2021-05-15                 25.452377    9.782886 -15.669490      0.000000   \n",
      "2021-05-16                 25.452377    9.782886 -15.669490      0.000000   \n",
      "2021-05-17                 25.452377    9.782886 -15.669490      0.000000   \n",
      "2021-05-18                 25.452377    9.782886 -15.669490      0.000000   \n",
      "2021-06-14                227.929112  228.001702   0.072590    252.417411   \n",
      "2021-06-15                227.929112  228.001702   0.072590    252.417411   \n",
      "2021-06-16                227.929112  228.001702   0.072590    252.417411   \n",
      "2021-06-17                227.929112  228.001702   0.072590    252.417411   \n",
      "2021-07-15                214.927153  214.930296   0.003143    215.048367   \n",
      "2021-07-16                214.927153  214.930296   0.003143    215.048367   \n",
      "2021-07-17                214.927153  214.930296   0.003143    215.048367   \n",
      "2021-07-18                214.927153  214.930296   0.003143    215.048367   \n",
      "2021-08-15                170.269157  170.190510  -0.078646    162.190255   \n",
      "2021-08-16                170.269157  170.190510  -0.078646    162.190255   \n",
      "2021-08-17                170.269157  170.190510  -0.078646    162.190255   \n",
      "2021-08-18                170.269157  170.190510  -0.078646    162.190255   \n",
      "2021-09-14                179.606168  179.618162   0.011994    193.083917   \n",
      "2021-09-15                179.606168  179.618162   0.011994    193.083917   \n",
      "2021-09-16                179.606168  179.618162   0.011994    193.083917   \n",
      "2021-09-17                179.606168  179.618162   0.011994    193.083917   \n",
      "2021-10-15                 72.112804   72.291073   0.178269     75.150005   \n",
      "2021-10-16                 72.112804   72.291073   0.178269     75.150005   \n",
      "2021-10-17                 72.112804   72.291073   0.178269     75.150005   \n",
      "2021-10-18                 72.112804   72.291073   0.178269     75.150005   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      26.630983  \n",
      "2021-04-15      26.630983  \n",
      "2021-04-16      26.630983  \n",
      "2021-04-17      26.630983  \n",
      "2021-05-15       0.000000  \n",
      "2021-05-16       0.000000  \n",
      "2021-05-17       0.000000  \n",
      "2021-05-18       0.000000  \n",
      "2021-06-14     252.453707  \n",
      "2021-06-15     252.453707  \n",
      "2021-06-16     252.453707  \n",
      "2021-06-17     252.453707  \n",
      "2021-07-15     215.049939  \n",
      "2021-07-16     215.049939  \n",
      "2021-07-17     215.049939  \n",
      "2021-07-18     215.049939  \n",
      "2021-08-15     162.150932  \n",
      "2021-08-16     162.150932  \n",
      "2021-08-17     162.150932  \n",
      "2021-08-18     162.150932  \n",
      "2021-09-14     193.089914  \n",
      "2021-09-15     193.089914  \n",
      "2021-09-16     193.089914  \n",
      "2021-09-17     193.089914  \n",
      "2021-10-15      75.239140  \n",
      "2021-10-16      75.239140  \n",
      "2021-10-17      75.239140  \n",
      "2021-10-18      75.239140  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n",
      "2021-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.120208    0.000000  -0.120208      0.000000   \n",
      "2021-03-16                  0.120208    0.000000  -0.120208      0.000000   \n",
      "2021-03-17                  0.120208    0.000000  -0.120208      0.000000   \n",
      "2021-03-18                  0.120208    0.000000  -0.120208      0.000000   \n",
      "2021-04-13                 20.695416   20.734183   0.038767     26.630983   \n",
      "2021-04-15                 20.695416   20.734183   0.038767     26.630983   \n",
      "2021-04-16                 20.695416   20.734183   0.038767     26.630983   \n",
      "2021-04-17                 20.695416   20.734183   0.038767     26.630983   \n",
      "2021-05-15                 25.608754    9.782886 -15.825867      0.000000   \n",
      "2021-05-16                 25.608754    9.782886 -15.825867      0.000000   \n",
      "2021-05-17                 25.608754    9.782886 -15.825867      0.000000   \n",
      "2021-05-18                 25.608754    9.782886 -15.825867      0.000000   \n",
      "2021-06-14                227.857818  228.001702   0.143884    252.453707   \n",
      "2021-06-15                227.857818  228.001702   0.143884    252.453707   \n",
      "2021-06-16                227.857818  228.001702   0.143884    252.453707   \n",
      "2021-06-17                227.857818  228.001702   0.143884    252.453707   \n",
      "2021-07-15                214.931314  214.930296  -0.001018    215.049939   \n",
      "2021-07-16                214.931314  214.930296  -0.001018    215.049939   \n",
      "2021-07-17                214.931314  214.930296  -0.001018    215.049939   \n",
      "2021-07-18                214.931314  214.930296  -0.001018    215.049939   \n",
      "2021-08-15                170.222935  170.190510  -0.032424    162.150932   \n",
      "2021-08-16                170.222935  170.190510  -0.032424    162.150932   \n",
      "2021-08-17                170.222935  170.190510  -0.032424    162.150932   \n",
      "2021-08-18                170.222935  170.190510  -0.032424    162.150932   \n",
      "2021-09-14                179.514051  179.618162   0.104110    193.089914   \n",
      "2021-09-15                179.514051  179.618162   0.104110    193.089914   \n",
      "2021-09-16                179.514051  179.618162   0.104110    193.089914   \n",
      "2021-09-17                179.514051  179.618162   0.104110    193.089914   \n",
      "2021-10-15                 72.342062   72.291073  -0.050989     75.239140   \n",
      "2021-10-16                 72.342062   72.291073  -0.050989     75.239140   \n",
      "2021-10-17                 72.342062   72.291073  -0.050989     75.239140   \n",
      "2021-10-18                 72.342062   72.291073  -0.050989     75.239140   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      26.650367  \n",
      "2021-04-15      26.650367  \n",
      "2021-04-16      26.650367  \n",
      "2021-04-17      26.650367  \n",
      "2021-05-15       0.000000  \n",
      "2021-05-16       0.000000  \n",
      "2021-05-17       0.000000  \n",
      "2021-05-18       0.000000  \n",
      "2021-06-14     252.525649  \n",
      "2021-06-15     252.525649  \n",
      "2021-06-16     252.525649  \n",
      "2021-06-17     252.525649  \n",
      "2021-07-15     215.049429  \n",
      "2021-07-16     215.049429  \n",
      "2021-07-17     215.049429  \n",
      "2021-07-18     215.049429  \n",
      "2021-08-15     162.134719  \n",
      "2021-08-16     162.134719  \n",
      "2021-08-17     162.134719  \n",
      "2021-08-18     162.134719  \n",
      "2021-09-14     193.141970  \n",
      "2021-09-15     193.141970  \n",
      "2021-09-16     193.141970  \n",
      "2021-09-17     193.141970  \n",
      "2021-10-15      75.213645  \n",
      "2021-10-16      75.213645  \n",
      "2021-10-17      75.213645  \n",
      "2021-10-18      75.213645  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n",
      "2021-12-18       0.000000  \n",
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.181494    0.000000  -0.181494      0.000000   \n",
      "2021-03-16                  0.181494    0.000000  -0.181494      0.000000   \n",
      "2021-03-17                  0.181494    0.000000  -0.181494      0.000000   \n",
      "2021-03-18                  0.181494    0.000000  -0.181494      0.000000   \n",
      "2021-04-13                 20.779224   20.734183  -0.045041     26.650367   \n",
      "2021-04-15                 20.779224   20.734183  -0.045041     26.650367   \n",
      "2021-04-16                 20.779224   20.734183  -0.045041     26.650367   \n",
      "2021-04-17                 20.779224   20.734183  -0.045041     26.650367   \n",
      "2021-05-15                 25.466469    9.782886 -15.683583      0.000000   \n",
      "2021-05-16                 25.466469    9.782886 -15.683583      0.000000   \n",
      "2021-05-17                 25.466469    9.782886 -15.683583      0.000000   \n",
      "2021-05-18                 25.466469    9.782886 -15.683583      0.000000   \n",
      "2021-06-14                228.014540  228.001702  -0.012838    252.525649   \n",
      "2021-06-15                228.014540  228.001702  -0.012838    252.525649   \n",
      "2021-06-16                228.014540  228.001702  -0.012838    252.525649   \n",
      "2021-06-17                228.014540  228.001702  -0.012838    252.525649   \n",
      "2021-07-15                214.929251  214.930296   0.001045    215.049429   \n",
      "2021-07-16                214.929251  214.930296   0.001045    215.049429   \n",
      "2021-07-17                214.929251  214.930296   0.001045    215.049429   \n",
      "2021-07-18                214.929251  214.930296   0.001045    215.049429   \n",
      "2021-08-15                170.227028  170.190510  -0.036518    162.134719   \n",
      "2021-08-16                170.227028  170.190510  -0.036518    162.134719   \n",
      "2021-08-17                170.227028  170.190510  -0.036518    162.134719   \n",
      "2021-08-18                170.227028  170.190510  -0.036518    162.134719   \n",
      "2021-09-14                179.652474  179.618162  -0.034313    193.141970   \n",
      "2021-09-15                179.652474  179.618162  -0.034313    193.141970   \n",
      "2021-09-16                179.652474  179.618162  -0.034313    193.141970   \n",
      "2021-09-17                179.652474  179.618162  -0.034313    193.141970   \n",
      "2021-10-15                 72.159153   72.291073   0.131920     75.213645   \n",
      "2021-10-16                 72.159153   72.291073   0.131920     75.213645   \n",
      "2021-10-17                 72.159153   72.291073   0.131920     75.213645   \n",
      "2021-10-18                 72.159153   72.291073   0.131920     75.213645   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      26.627846  \n",
      "2021-04-15      26.627846  \n",
      "2021-04-16      26.627846  \n",
      "2021-04-17      26.627846  \n",
      "2021-05-15       0.000000  \n",
      "2021-05-16       0.000000  \n",
      "2021-05-17       0.000000  \n",
      "2021-05-18       0.000000  \n",
      "2021-06-14     252.519230  \n",
      "2021-06-15     252.519230  \n",
      "2021-06-16     252.519230  \n",
      "2021-06-17     252.519230  \n",
      "2021-07-15     215.049952  \n",
      "2021-07-16     215.049952  \n",
      "2021-07-17     215.049952  \n",
      "2021-07-18     215.049952  \n",
      "2021-08-15     162.116461  \n",
      "2021-08-16     162.116461  \n",
      "2021-08-17     162.116461  \n",
      "2021-08-18     162.116461  \n",
      "2021-09-14     193.124813  \n",
      "2021-09-15     193.124813  \n",
      "2021-09-16     193.124813  \n",
      "2021-09-17     193.124813  \n",
      "2021-10-15      75.279605  \n",
      "2021-10-16      75.279605  \n",
      "2021-10-17      75.279605  \n",
      "2021-10-18      75.279605  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n",
      "2021-12-18       0.000000  \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis of the means:\n",
      "            Interpolated_Mean_Demand        Goal       Diff  OGOut_Demand  \\\n",
      "Date                                                                        \n",
      "2021-01-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-01-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-12                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-13                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-02-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-03-15                  0.120139    0.000000  -0.120139      0.000000   \n",
      "2021-03-16                  0.120139    0.000000  -0.120139      0.000000   \n",
      "2021-03-17                  0.120139    0.000000  -0.120139      0.000000   \n",
      "2021-03-18                  0.120139    0.000000  -0.120139      0.000000   \n",
      "2021-04-13                 20.695689   20.734183   0.038495     26.627846   \n",
      "2021-04-15                 20.695689   20.734183   0.038495     26.627846   \n",
      "2021-04-16                 20.695689   20.734183   0.038495     26.627846   \n",
      "2021-04-17                 20.695689   20.734183   0.038495     26.627846   \n",
      "2021-05-15                 25.616421    9.782886 -15.833535      0.000000   \n",
      "2021-05-16                 25.616421    9.782886 -15.833535      0.000000   \n",
      "2021-05-17                 25.616421    9.782886 -15.833535      0.000000   \n",
      "2021-05-18                 25.616421    9.782886 -15.833535      0.000000   \n",
      "2021-06-14                227.910502  228.001702   0.091200    252.519230   \n",
      "2021-06-15                227.910502  228.001702   0.091200    252.519230   \n",
      "2021-06-16                227.910502  228.001702   0.091200    252.519230   \n",
      "2021-06-17                227.910502  228.001702   0.091200    252.519230   \n",
      "2021-07-15                214.932955  214.930296  -0.002659    215.049952   \n",
      "2021-07-16                214.932955  214.930296  -0.002659    215.049952   \n",
      "2021-07-17                214.932955  214.930296  -0.002659    215.049952   \n",
      "2021-07-18                214.932955  214.930296  -0.002659    215.049952   \n",
      "2021-08-15                170.196269  170.190510  -0.005759    162.116461   \n",
      "2021-08-16                170.196269  170.190510  -0.005759    162.116461   \n",
      "2021-08-17                170.196269  170.190510  -0.005759    162.116461   \n",
      "2021-08-18                170.196269  170.190510  -0.005759    162.116461   \n",
      "2021-09-14                179.542724  179.618162   0.075438    193.124813   \n",
      "2021-09-15                179.542724  179.618162   0.075438    193.124813   \n",
      "2021-09-16                179.542724  179.618162   0.075438    193.124813   \n",
      "2021-09-17                179.542724  179.618162   0.075438    193.124813   \n",
      "2021-10-15                 72.372699   72.291073  -0.081626     75.279605   \n",
      "2021-10-16                 72.372699   72.291073  -0.081626     75.279605   \n",
      "2021-10-17                 72.372699   72.291073  -0.081626     75.279605   \n",
      "2021-10-18                 72.372699   72.291073  -0.081626     75.279605   \n",
      "2021-11-14                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-11-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-15                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-16                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-17                  0.000000    0.000000   0.000000      0.000000   \n",
      "2021-12-18                  0.000000    0.000000   0.000000      0.000000   \n",
      "\n",
      "            NewOut_Demand  \n",
      "Date                       \n",
      "2021-01-15       0.000000  \n",
      "2021-01-16       0.000000  \n",
      "2021-01-17       0.000000  \n",
      "2021-01-18       0.000000  \n",
      "2021-02-12       0.000000  \n",
      "2021-02-13       0.000000  \n",
      "2021-02-14       0.000000  \n",
      "2021-02-15       0.000000  \n",
      "2021-03-15       0.000000  \n",
      "2021-03-16       0.000000  \n",
      "2021-03-17       0.000000  \n",
      "2021-03-18       0.000000  \n",
      "2021-04-13      26.647094  \n",
      "2021-04-15      26.647094  \n",
      "2021-04-16      26.647094  \n",
      "2021-04-17      26.647094  \n",
      "2021-05-15       0.000000  \n",
      "2021-05-16       0.000000  \n",
      "2021-05-17       0.000000  \n",
      "2021-05-18       0.000000  \n",
      "2021-06-14     252.564830  \n",
      "2021-06-15     252.564830  \n",
      "2021-06-16     252.564830  \n",
      "2021-06-17     252.564830  \n",
      "2021-07-15     215.048623  \n",
      "2021-07-16     215.048623  \n",
      "2021-07-17     215.048623  \n",
      "2021-07-18     215.048623  \n",
      "2021-08-15     162.113581  \n",
      "2021-08-16     162.113581  \n",
      "2021-08-17     162.113581  \n",
      "2021-08-18     162.113581  \n",
      "2021-09-14     193.162532  \n",
      "2021-09-15     193.162532  \n",
      "2021-09-16     193.162532  \n",
      "2021-09-17     193.162532  \n",
      "2021-10-15      75.238793  \n",
      "2021-10-16      75.238793  \n",
      "2021-10-17      75.238793  \n",
      "2021-10-18      75.238793  \n",
      "2021-11-14       0.000000  \n",
      "2021-11-15       0.000000  \n",
      "2021-11-16       0.000000  \n",
      "2021-11-17       0.000000  \n",
      "2021-12-15       0.000000  \n",
      "2021-12-16       0.000000  \n",
      "2021-12-17       0.000000  \n",
      "2021-12-18       0.000000  \n"
     ]
    }
   ],
   "source": [
    "PrePeakFact = [1,1,1,1]\n",
    "PostPeakFact = [1,1,1,1]\n",
    "\n",
    "iterations = list(np.arange(1,15,1))\n",
    "DemandPlot = pd.DataFrame()\n",
    "Year = [2021]\n",
    "for i in Year:\n",
    "    MLR_Out_DemandM2 = MLR_Out_DemandM.copy()\n",
    "    for j in iterations:\n",
    "        Demand_Forecast, MLR_Out_DemandM2, DemandPlot =DemandIterationAllyrs(j,DemandPlot,Demand_Forecast , MLR, i, months, DemandPrediction, \n",
    "                            MLR_Out_DemandM2, '-01-01', '-12-30',DemandOffset,i, PrePeakFact, PostPeakFact)\n",
    "        #Demand_Forecast, Out_Demand2, DemandPlot =DemandIterationAllyrs(j, DemandPlot, Demand_Forecast, slc, i, months, 'Obs_gpcd', \n",
    "         #                   Out_Demand2, '-01-01', '-12-30',DemandOffset,i, PrePeakFact, PostPeakFact)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#conver to liter for ASCE\n",
    "#DemandPlot = DemandPlot*3.78541\n",
    "\n",
    "fig = plt.figure()\n",
    "fig, ax = plt.subplots(1, 2)\n",
    "fig.set_size_inches(6, 4)\n",
    "labelsize = 11\n",
    "\n",
    "gal_to_l = 3.785\n",
    "\n",
    "ax[0].set_facecolor('white')\n",
    "ax[0].plot(DemandPlot.Iteration_1*gal_to_l, label = 'Iteration 1', color = 'green')\n",
    "ax[0].plot(DemandPlot.Iteration_2*gal_to_l, label = 'Iteration 2', color = 'blue')\n",
    "ax[0].plot(DemandPlot.Iteration_3*gal_to_l, label = 'Iteration 3', color = 'orange')\n",
    "ax[0].plot(DemandPlot.Iteration_4*gal_to_l, label = 'Iteration 4', color = 'black')\n",
    "ax[0].plot(DemandPlot.Iteration_14*gal_to_l, label = 'Iteration Final', linewidth = 1, color = 'red')\n",
    "\n",
    "ax[0].spines['bottom'].set_color('black')\n",
    "ax[0].spines['left'].set_color('black')\n",
    "ax[0].xaxis.set_major_locator(plt.MaxNLocator(3))\n",
    "ax[0].set_xlabel('Time', size = labelsize)\n",
    "ax[0].set_ylabel('Water Demand (lpcd)', size = labelsize)\n",
    "ax[0].text(pd.to_datetime('2021-10-15'),405*gal_to_l , \"A.\", size = labelsize)\n",
    "ax[0].tick_params(axis='x', which='major', labelsize=10)\n",
    "\n",
    "\n",
    "\n",
    "ax[1].set_facecolor('white')\n",
    "ax[1].plot(DemandPlot.Iteration_1.loc['2021-07-15':'2021-08-15']*gal_to_l, label = 'Iteration 1', color = 'green')\n",
    "ax[1].plot(DemandPlot.Iteration_2.loc['2021-07-15':'2021-08-15']*gal_to_l, label = 'Iteration 2', color = 'blue')\n",
    "ax[1].plot(DemandPlot.Iteration_3.loc['2021-07-15':'2021-08-15']*gal_to_l, label = 'Iteration 3', color = 'orange')\n",
    "ax[1].plot(DemandPlot.Iteration_4.loc['2021-07-15':'2021-08-15']*gal_to_l, label = 'Iteration 4', color = 'black')\n",
    "ax[1].plot(DemandPlot.Iteration_14.loc['2021-07-15':'2021-08-15']*gal_to_l, label = 'Iteration Final', linewidth = 1, color = 'red')\n",
    "\n",
    "ax[1].spines['bottom'].set_color('black')\n",
    "ax[1].spines['left'].set_color('black')\n",
    "ax[1].xaxis.set_major_locator(plt.MaxNLocator(3))\n",
    "ax[1].set_xlabel('Time', size = labelsize)\n",
    "ax[1].text(pd.to_datetime('2021-08-15'),414*gal_to_l , \"B.\", size = labelsize)\n",
    "ax[1].tick_params(axis='x', which='major', labelsize=10)\n",
    "\n",
    "leg = ax[1].legend(bbox_to_anchor=(1, 1.2), loc = 'upper right', ncol = 3)\n",
    "frame = leg.get_frame()\n",
    "frame.set_facecolor('white')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "#need to add additional cities, just copy them\n",
    "cities = ['MIll_OutdoorDemand', 'Holl_OutdoorDemand', 'CottHeigh_OutdoorDemand',\n",
    "          'Murray', 'Sandy', 'Draper','WaterPro','Midvale', 'SouthSL', 'WhiteCity', \n",
    "            'Kearns', 'WestValley', 'Bluffdale', 'Copperton', 'Herriman', 'Magna',\n",
    "            'Riverton', 'SoJordan', 'TayBen', 'Prison', 'WJordan', 'Lehi', 'AmericanFork',\n",
    "            'PleasantGrove', 'Orem', 'Provo', 'Springville','SpanishFork']\n",
    "\n",
    "for i in cities:\n",
    "    Demand_Forecast[i] = Demand_Forecast['SLC_OutdoorDemand'].copy()\n",
    "\n",
    "#Save dataframe\n",
    "Demand_Forecast.to_excel('C:/Users/rjohnson18/Box/Dissertation/Paper2/Data/Demand_Forecast/'+Scenario+'.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done with simulation demand set up\n"
     ]
    }
   ],
   "source": [
    "#Make forecast yr 2021 with observations to match to gage prediction accuracy\n",
    "#Obs_Demand(Demand_Forecast, 2015, 'Drought', cities)\n",
    "#Obs_Demand(Demand_Forecast, 2008, 'Surplus', cities)\n",
    "#Obs_Demand(Demand_Forecast, 2017, 'Average', cities)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SLC_OutdoorDemand</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Time</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-01-01</th>\n",
       "      <td>1.782656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-02</th>\n",
       "      <td>1.685020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-03</th>\n",
       "      <td>1.623489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-04</th>\n",
       "      <td>1.591862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-05</th>\n",
       "      <td>1.412124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-26</th>\n",
       "      <td>1.181210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-27</th>\n",
       "      <td>0.521006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-28</th>\n",
       "      <td>0.588783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-29</th>\n",
       "      <td>0.328868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-30</th>\n",
       "      <td>0.797824</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>364 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            SLC_OutdoorDemand\n",
       "Time                         \n",
       "2021-01-01           1.782656\n",
       "2021-01-02           1.685020\n",
       "2021-01-03           1.623489\n",
       "2021-01-04           1.591862\n",
       "2021-01-05           1.412124\n",
       "...                       ...\n",
       "2021-12-26           1.181210\n",
       "2021-12-27           0.521006\n",
       "2021-12-28           0.588783\n",
       "2021-12-29           0.328868\n",
       "2021-12-30           0.797824\n",
       "\n",
       "[364 rows x 1 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#need to make observed demand dataframes for goldsim\n",
    "Drought = Demand_Forecast.loc['2015-01-01':'2015-12-30'].copy()\n",
    "Drought.index = Drought.index + pd.DateOffset(years = 6)\n",
    "Demand_Forecast.update(Drought)\n",
    "#need to add additional cities, just copy them\n",
    "cities = ['MIll_OutdoorDemand', 'Holl_OutdoorDemand', 'CottHeigh_OutdoorDemand',\n",
    "          'Murray', 'Sandy', 'Draper','WaterPro','Midvale', 'SouthSL', 'WhiteCity', \n",
    "            'Kearns', 'WestValley', 'Bluffdale', 'Copperton', 'Herriman', 'Magna',\n",
    "            'Riverton', 'SoJordan', 'TayBen', 'Prison', 'WJordan', 'Lehi', 'AmericanFork',\n",
    "            'PleasantGrove', 'Orem', 'Provo', 'Springville','SpanishFork']\n",
    "\n",
    "for i in cities:\n",
    "    Demand_Forecast[i] = Demand_Forecast['SLC_OutdoorDemand'].copy()\n",
    "\n",
    "#Save dataframe\n",
    "Demand_Forecast.to_excel('C:/Users/Ryan/Box/Dissertation/Paper2/Data/Demand_Forecast/OBS_Drought_Dem.xlsx')\n",
    "print('Done with Drought demand set up')\n",
    "\n",
    "#need to make observed demand dataframes for goldsim\n",
    "Average = Demand_Forecast.loc['2017-01-01':'2017-12-30'].copy()\n",
    "Average.index = Average.index + pd.DateOffset(years = 6)\n",
    "Demand_Forecast.update(Drought)\n",
    "#need to add additional cities, just copy them\n",
    "cities = ['MIll_OutdoorDemand', 'Holl_OutdoorDemand', 'CottHeigh_OutdoorDemand',\n",
    "          'Murray', 'Sandy', 'Draper','WaterPro','Midvale', 'SouthSL', 'WhiteCity', \n",
    "            'Kearns', 'WestValley', 'Bluffdale', 'Copperton', 'Herriman', 'Magna',\n",
    "            'Riverton', 'SoJordan', 'TayBen', 'Prison', 'WJordan', 'Lehi', 'AmericanFork',\n",
    "            'PleasantGrove', 'Orem', 'Provo', 'Springville','SpanishFork']\n",
    "\n",
    "for i in cities:\n",
    "    Demand_Forecast[i] = Demand_Forecast['SLC_OutdoorDemand'].copy()\n",
    "\n",
    "#Save dataframe\n",
    "Demand_Forecast.to_excel('C:/Users/Ryan/Box/Dissertation/Paper2/Data/Demand_Forecast/OBS_Drought_Dem.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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