heatpump_visuals.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2f352c10-47c3-4799-bda8-0bb38c39fabf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in ./.venv/lib/python3.12/site-packages (2.2.3)\n",
      "Requirement already satisfied: numpy in ./.venv/lib/python3.12/site-packages (2.2.1)\n",
      "Requirement already satisfied: matplotlib in ./.venv/lib/python3.12/site-packages (3.10.0)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in ./.venv/lib/python3.12/site-packages (from pandas) (2.9.0.post0)\n",
      "Requirement already satisfied: pytz>=2020.1 in ./.venv/lib/python3.12/site-packages (from pandas) (2024.2)\n",
      "Requirement already satisfied: tzdata>=2022.7 in ./.venv/lib/python3.12/site-packages (from pandas) (2024.2)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in ./.venv/lib/python3.12/site-packages (from matplotlib) (1.3.1)\n",
      "Requirement already satisfied: cycler>=0.10 in ./.venv/lib/python3.12/site-packages (from matplotlib) (0.12.1)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in ./.venv/lib/python3.12/site-packages (from matplotlib) (4.55.3)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in ./.venv/lib/python3.12/site-packages (from matplotlib) (1.4.8)\n",
      "Requirement already satisfied: packaging>=20.0 in ./.venv/lib/python3.12/site-packages (from matplotlib) (24.2)\n",
      "Requirement already satisfied: pillow>=8 in ./.venv/lib/python3.12/site-packages (from matplotlib) (11.0.0)\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in ./.venv/lib/python3.12/site-packages (from matplotlib) (3.2.1)\n",
      "Requirement already satisfied: six>=1.5 in ./.venv/lib/python3.12/site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\n"
     ]
    }
   ],
   "source": [
    "!pip install pandas numpy matplotlib\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "120d292c-95de-434b-b1d9-d989fdacb63c",
   "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>Timestamp</th>\n",
       "      <th>Frostschutz</th>\n",
       "      <th>HKPumpeAktiv</th>\n",
       "      <th>HKSupplyTemp</th>\n",
       "      <th>HKTargetSupplyTemp</th>\n",
       "      <th>HKWunschTemp</th>\n",
       "      <th>HeizKurveNeigung</th>\n",
       "      <th>HeizkurveNiveau</th>\n",
       "      <th>KompressorPhase</th>\n",
       "      <th>KompressorStatus</th>\n",
       "      <th>AussenTemperatur</th>\n",
       "      <th>SpeicherTemp</th>\n",
       "      <th>SupplyTempPrimaryCircuit</th>\n",
       "      <th>VerbrauchHeute</th>\n",
       "      <th>VolumenStrom</th>\n",
       "      <th>WERücklauf</th>\n",
       "      <th>WEVorlauf</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2025-01-05T00:00:05.535698</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>49.5</td>\n",
       "      <td>45.2</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0</td>\n",
       "      <td>ready</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>49.2</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1886</td>\n",
       "      <td>34.8</td>\n",
       "      <td>34.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2025-01-05T00:01:05.000243</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>49.5</td>\n",
       "      <td>45.2</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0</td>\n",
       "      <td>ready</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>49.2</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1884</td>\n",
       "      <td>34.3</td>\n",
       "      <td>34.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2025-01-05T00:02:04.307337</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>49.5</td>\n",
       "      <td>45.2</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0</td>\n",
       "      <td>ready</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>49.2</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1877</td>\n",
       "      <td>34.3</td>\n",
       "      <td>34.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2025-01-05T00:03:04.553887</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>49.5</td>\n",
       "      <td>45.2</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0</td>\n",
       "      <td>ready</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>49.2</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1881</td>\n",
       "      <td>34.3</td>\n",
       "      <td>34.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2025-01-05T00:04:04.953366</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>49.5</td>\n",
       "      <td>45.2</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0</td>\n",
       "      <td>ready</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>49.2</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1875</td>\n",
       "      <td>34.3</td>\n",
       "      <td>34.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Timestamp  Frostschutz  HKPumpeAktiv  HKSupplyTemp  \\\n",
       "0  2025-01-05T00:00:05.535698            0             1          49.5   \n",
       "1  2025-01-05T00:01:05.000243            0             1          49.5   \n",
       "2  2025-01-05T00:02:04.307337            0             1          49.5   \n",
       "3  2025-01-05T00:03:04.553887            0             1          49.5   \n",
       "4  2025-01-05T00:04:04.953366            0             1          49.5   \n",
       "\n",
       "   HKTargetSupplyTemp  HKWunschTemp  HeizKurveNeigung  HeizkurveNiveau  \\\n",
       "0                45.2          19.0               1.2                0   \n",
       "1                45.2          19.0               1.2                0   \n",
       "2                45.2          19.0               1.2                0   \n",
       "3                45.2          19.0               1.2                0   \n",
       "4                45.2          19.0               1.2                0   \n",
       "\n",
       "  KompressorPhase  KompressorStatus  AussenTemperatur  SpeicherTemp  \\\n",
       "0           ready                 0              -0.5          49.2   \n",
       "1           ready                 0              -0.5          49.2   \n",
       "2           ready                 0              -0.5          49.2   \n",
       "3           ready                 0              -0.5          49.2   \n",
       "4           ready                 0              -0.5          49.2   \n",
       "\n",
       "   SupplyTempPrimaryCircuit  VerbrauchHeute  VolumenStrom  WERücklauf  \\\n",
       "0                       0.7             0.0          1886        34.8   \n",
       "1                       0.7             0.0          1884        34.3   \n",
       "2                       0.7             0.0          1877        34.3   \n",
       "3                       0.7             0.0          1881        34.3   \n",
       "4                       0.7             0.0          1875        34.3   \n",
       "\n",
       "   WEVorlauf  \n",
       "0       34.5  \n",
       "1       34.5  \n",
       "2       34.5  \n",
       "3       34.5  \n",
       "4       34.5  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# Read the CSV file\n",
    "\n",
    "analysis_date = \"2025-01-05\"\n",
    "df = pd.read_csv(f\"heatpump-{analysis_date}.csv\")\n",
    "\n",
    "# Display the first few rows to verify the data\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "415201d9-9c29-48dd-96f5-a05435a3774d",
   "metadata": {},
   "source": [
    "# Convert data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0d4fbe78-ab52-456e-99b1-98f13246dedc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Fix Typo\n",
    "# df = df.drop('WePumpe',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ff654fbf-db77-4526-ba79-9aba31e83f47",
   "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>Timestamp</th>\n",
       "      <th>Frostschutz</th>\n",
       "      <th>HKPumpeAktiv</th>\n",
       "      <th>HKSupplyTemp</th>\n",
       "      <th>HKTargetSupplyTemp</th>\n",
       "      <th>HKWunschTemp</th>\n",
       "      <th>HeizKurveNeigung</th>\n",
       "      <th>HeizkurveNiveau</th>\n",
       "      <th>KompressorPhase</th>\n",
       "      <th>KompressorStatus</th>\n",
       "      <th>AussenTemperatur</th>\n",
       "      <th>SpeicherTemp</th>\n",
       "      <th>SupplyTempPrimaryCircuit</th>\n",
       "      <th>VerbrauchHeute</th>\n",
       "      <th>VolumenStrom</th>\n",
       "      <th>WERücklauf</th>\n",
       "      <th>WEVorlauf</th>\n",
       "      <th>HKWunschTemp1</th>\n",
       "      <th>TimeOnly</th>\n",
       "      <th>WEPumpe</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>691</td>\n",
       "      <td>691.0</td>\n",
       "      <td>691.0</td>\n",
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       "      <td>691.000000</td>\n",
       "      <td>691.000000</td>\n",
       "      <td>6.910000e+02</td>\n",
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       "      <td>691</td>\n",
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       "      <td>691.000000</td>\n",
       "      <td>691.000000</td>\n",
       "      <td>691.000000</td>\n",
       "      <td>691.000000</td>\n",
       "      <td>691.000000</td>\n",
       "      <td>691.000000</td>\n",
       "      <td>691.000000</td>\n",
       "      <td>691.000000</td>\n",
       "      <td>691</td>\n",
       "      <td>691.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>691</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ready</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12:33:04</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>691</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2025-01-05 06:46:41.094356992</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>41.153401</td>\n",
       "      <td>46.595658</td>\n",
       "      <td>19.756874</td>\n",
       "      <td>1.200000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.532562</td>\n",
       "      <td>-0.352388</td>\n",
       "      <td>41.122287</td>\n",
       "      <td>0.327786</td>\n",
       "      <td>9.501013</td>\n",
       "      <td>1872.222865</td>\n",
       "      <td>36.336903</td>\n",
       "      <td>38.799566</td>\n",
       "      <td>19.756874</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2025-01-05 01:00:05.535698</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>21.500000</td>\n",
       "      <td>42.700000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1.200000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.200000</td>\n",
       "      <td>21.300000</td>\n",
       "      <td>-2.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1812.000000</td>\n",
       "      <td>21.100000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2025-01-05 03:52:34.626575872</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>35.500000</td>\n",
       "      <td>42.700000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1.200000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.700000</td>\n",
       "      <td>35.600000</td>\n",
       "      <td>-0.300000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1863.000000</td>\n",
       "      <td>28.300000</td>\n",
       "      <td>28.500000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2025-01-05 06:47:04.585423104</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>43.500000</td>\n",
       "      <td>46.200000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>1.200000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.200000</td>\n",
       "      <td>43.400000</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>5.900000</td>\n",
       "      <td>1872.000000</td>\n",
       "      <td>36.100000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2025-01-05 09:40:34.522384128</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>51.100000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>1.200000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.100000</td>\n",
       "      <td>48.150000</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>16.650000</td>\n",
       "      <td>1881.000000</td>\n",
       "      <td>43.900000</td>\n",
       "      <td>47.950000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2025-01-05 12:33:04.061695</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>54.500000</td>\n",
       "      <td>52.100000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>1.200000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>54.600000</td>\n",
       "      <td>9.500000</td>\n",
       "      <td>29.200000</td>\n",
       "      <td>1961.000000</td>\n",
       "      <td>52.900000</td>\n",
       "      <td>56.500000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.907393</td>\n",
       "      <td>3.658301</td>\n",
       "      <td>1.636386</td>\n",
       "      <td>2.222054e-16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.499300</td>\n",
       "      <td>0.548653</td>\n",
       "      <td>8.923972</td>\n",
       "      <td>1.044382</td>\n",
       "      <td>10.034774</td>\n",
       "      <td>16.740460</td>\n",
       "      <td>8.739176</td>\n",
       "      <td>10.319160</td>\n",
       "      <td>1.636386</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Timestamp  Frostschutz  HKPumpeAktiv  \\\n",
       "count                             691        691.0         691.0   \n",
       "unique                            NaN          NaN           NaN   \n",
       "top                               NaN          NaN           NaN   \n",
       "freq                              NaN          NaN           NaN   \n",
       "mean    2025-01-05 06:46:41.094356992          0.0           1.0   \n",
       "min        2025-01-05 01:00:05.535698          0.0           1.0   \n",
       "25%     2025-01-05 03:52:34.626575872          0.0           1.0   \n",
       "50%     2025-01-05 06:47:04.585423104          0.0           1.0   \n",
       "75%     2025-01-05 09:40:34.522384128          0.0           1.0   \n",
       "max        2025-01-05 12:33:04.061695          0.0           1.0   \n",
       "std                               NaN          0.0           0.0   \n",
       "\n",
       "        HKSupplyTemp  HKTargetSupplyTemp  HKWunschTemp  HeizKurveNeigung  \\\n",
       "count     691.000000          691.000000    691.000000      6.910000e+02   \n",
       "unique           NaN                 NaN           NaN               NaN   \n",
       "top              NaN                 NaN           NaN               NaN   \n",
       "freq             NaN                 NaN           NaN               NaN   \n",
       "mean       41.153401           46.595658     19.756874      1.200000e+00   \n",
       "min        21.500000           42.700000     18.000000      1.200000e+00   \n",
       "25%        35.500000           42.700000     18.000000      1.200000e+00   \n",
       "50%        43.500000           46.200000     20.000000      1.200000e+00   \n",
       "75%        48.000000           51.100000     22.000000      1.200000e+00   \n",
       "max        54.500000           52.100000     22.000000      1.200000e+00   \n",
       "std         8.907393            3.658301      1.636386      2.222054e-16   \n",
       "\n",
       "        HeizkurveNiveau KompressorPhase  KompressorStatus  AussenTemperatur  \\\n",
       "count             691.0             691        691.000000        691.000000   \n",
       "unique              NaN               1               NaN               NaN   \n",
       "top                 NaN           ready               NaN               NaN   \n",
       "freq                NaN             691               NaN               NaN   \n",
       "mean                0.0             NaN          0.532562         -0.352388   \n",
       "min                 0.0             NaN          0.000000         -1.200000   \n",
       "25%                 0.0             NaN          0.000000         -0.700000   \n",
       "50%                 0.0             NaN          1.000000         -0.200000   \n",
       "75%                 0.0             NaN          1.000000         -0.100000   \n",
       "max                 0.0             NaN          1.000000          1.000000   \n",
       "std                 0.0             NaN          0.499300          0.548653   \n",
       "\n",
       "        SpeicherTemp  SupplyTempPrimaryCircuit  VerbrauchHeute  VolumenStrom  \\\n",
       "count     691.000000                691.000000      691.000000    691.000000   \n",
       "unique           NaN                       NaN             NaN           NaN   \n",
       "top              NaN                       NaN             NaN           NaN   \n",
       "freq             NaN                       NaN             NaN           NaN   \n",
       "mean       41.122287                  0.327786        9.501013   1872.222865   \n",
       "min        21.300000                 -2.100000        0.000000   1812.000000   \n",
       "25%        35.600000                 -0.300000        0.000000   1863.000000   \n",
       "50%        43.400000                  0.700000        5.900000   1872.000000   \n",
       "75%        48.150000                  0.700000       16.650000   1881.000000   \n",
       "max        54.600000                  9.500000       29.200000   1961.000000   \n",
       "std         8.923972                  1.044382       10.034774     16.740460   \n",
       "\n",
       "        WERücklauf   WEVorlauf  HKWunschTemp1  TimeOnly  WEPumpe  \n",
       "count   691.000000  691.000000     691.000000       691    691.0  \n",
       "unique         NaN         NaN            NaN       691      NaN  \n",
       "top            NaN         NaN            NaN  12:33:04      NaN  \n",
       "freq           NaN         NaN            NaN         1      NaN  \n",
       "mean     36.336903   38.799566      19.756874       NaN      1.0  \n",
       "min      21.100000   22.000000      18.000000       NaN      1.0  \n",
       "25%      28.300000   28.500000      18.000000       NaN      1.0  \n",
       "50%      36.100000   41.000000      20.000000       NaN      1.0  \n",
       "75%      43.900000   47.950000      22.000000       NaN      1.0  \n",
       "max      52.900000   56.500000      22.000000       NaN      1.0  \n",
       "std       8.739176   10.319160       1.636386       NaN      0.0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['HKWunschTemp1'] = pd.to_numeric(df['HKWunschTemp'], errors='coerce')\n",
    "df['Timestamp'] = pd.to_datetime(df.Timestamp)\n",
    "# Convert from UTC to MET\n",
    "df['Timestamp'] = df['Timestamp'] + pd.Timedelta(hours=1)\n",
    "df['TimeOnly'] = df.Timestamp.dt.strftime('%H:%M:%S')\n",
    "df['WEPumpe'] = (df.VolumenStrom > 300.0).astype(int)\n",
    "df.describe(include='all')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5b158f5-fd24-4780-b690-2d2919696bf9",
   "metadata": {},
   "source": [
    "# Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3135571e-76a8-493a-aab8-62e2674767bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.gridspec as gridspec\n",
    "\n",
    "fig = plt.figure(figsize=(15,10))\n",
    "gs = gridspec.GridSpec(4,1, height_ratios=[1,3,3,1])\n",
    "\n",
    "ax1 = fig.add_subplot(gs[0])\n",
    "ax2 = fig.add_subplot(gs[1])\n",
    "ax3 = fig.add_subplot(gs[2])\n",
    "ax4 = fig.add_subplot(gs[3])\n",
    "\n",
    "# fig, (ax1,ax2,ax3) =plt.subplots(3,1, figsize=(12,10), sharex=True)\n",
    "\n",
    "ax = ax1\n",
    "ax.plot(df.Timestamp, df.HeizKurveNeigung, label='Neigung')\n",
    "ax.plot(df.Timestamp, df.HeizkurveNiveau, label='Niveau')\n",
    "ax.set_ylabel('Heizkurve')\n",
    "ax.grid(True)\n",
    "\n",
    "ax = ax2\n",
    "ax.plot(df.Timestamp, df.HKTargetSupplyTemp, label='Ziel Vorlauf')\n",
    "ax.plot(df.Timestamp, df.SpeicherTemp, label='Speicher / °C')\n",
    "ax.plot(df.Timestamp, df.HKWunschTemp1, label='Wunschtemperatur')\n",
    "ax.plot(df.Timestamp, df.HKPumpeAktiv*5+20, label='HK Pumpe an/aus')\n",
    "ax.plot(df.Timestamp, df.HKSupplyTemp, label='Heizkreis Vorlauf', color='red')\n",
    "ax.set_ylabel('Heizkreis')\n",
    "ax.grid(True)\n",
    "\n",
    "# Turn off x-axis label and ticks for the upper subplot (ax1)\n",
    "ax.set_xlabel('')  # Remove the x-axis label\n",
    "ax.set_xticklabels([])  # Remove x-axis tick labels\n",
    "\n",
    "ax.legend()\n",
    "\n",
    "ax = ax3\n",
    "ax.plot(df.Timestamp, df.WEVorlauf, label='WE Vorlauf / °C')\n",
    "ax.plot(df.Timestamp, df.WERücklauf, label='WE Rücklauf / °C')\n",
    "ax.plot(df.Timestamp, df.WEPumpe*2.5 + 30-1.25, label='Pumpe an/aus')\n",
    "ax.plot(df.Timestamp, df.KompressorStatus*2.5 + 30-1.25, label='Kompressor an/aus')\n",
    "ax.set_ylabel('Wärmeerzeuger')\n",
    "ax.grid(True)\n",
    "ax.legend()\n",
    "\n",
    "# Turn off x-axis label and ticks for the upper subplot (ax1)\n",
    "ax.set_xlabel('')  # Remove the x-axis label\n",
    "ax.set_xticklabels([])  # Remove x-axis tick labels\n",
    "\n",
    "ax = ax4\n",
    "ax4.plot(df.Timestamp, df.AussenTemperatur, label='Aussen / °C')\n",
    "\n",
    "plt.subplots_adjust(hspace=0.02) \n",
    "plt.legend(loc=(0.85,0.6))\n",
    "plt.grid(True)\n",
    "plt.xticks(rotation=90)\n",
    "plt.savefig(f\"{analysis_date}.png\", format='png', dpi=300, bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e51f1bec-fece-4ca5-a762-ba9cb5f8b031",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}