electricity_usage.ipynb

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   "source": [
    "# Energy usage analysis of meter readings using Pandas\n",
    "- Load file containg dates and reaings (copied from Ovo site + some entries added by hand). Fairly unstructured format.\n",
    "- Use regexp to parse these and create a dataframe\n",
    "- Readings are on random dates so resample to interpolate to daily and plot\n",
    "- Resample daily to monthly and look at usage per month\n",
    "- Resample daily to annual and look at usage per year\n",
    "- Pivot by month and compare year on year usage by month"
   ],
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  },
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   "source": [
    "#imports\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import re\n",
    "import dateparser\n",
    "import seaborn as sns\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
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   "source": [
    "#global plotting styles\n",
    "sns.set_context('talk')\n",
    "sns.set_style(\"darkgrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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     "data": {
      "text/plain": [
       "'13 Mar 2021You gave121381\\n14 Nov 2020You gave117334\\n01 Nov 2020You gave116656\\n13 Oct 2020You gave115'"
      ]
     },
     "metadata": {},
     "execution_count": 3
    }
   ],
   "source": [
    "#read the file in\n",
    "with open('meter_readings.txt') as f:\n",
    "    raw = f.read()\n",
    "raw[:100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "[('13 Mar 2021', '121381'),\n",
       " ('14 Nov 2020', '117334'),\n",
       " ('01 Nov 2020', '116656'),\n",
       " ('13 Oct 2020', '115792'),\n",
       " ('26 Sep 2020', '115113')]"
      ]
     },
     "metadata": {},
     "execution_count": 4
    }
   ],
   "source": [
    "#parse into a list of dates and readings\n",
    "readings = re.findall(\"(\\d\\d \\w{3} \\d{4}).*(\\d{6})\", raw)\n",
    "readings[:5]"
   ]
  },
  {
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   "execution_count": 5,
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      "text/plain": [
       "            Reading\n",
       "Date               \n",
       "2021-03-13   121381\n",
       "2020-11-14   117334\n",
       "2020-11-01   116656\n",
       "2020-10-13   115792\n",
       "2020-09-26   115113"
      ],
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Reading</th>\n    </tr>\n    <tr>\n      <th>Date</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2021-03-13</th>\n      <td>121381</td>\n    </tr>\n    <tr>\n      <th>2020-11-14</th>\n      <td>117334</td>\n    </tr>\n    <tr>\n      <th>2020-11-01</th>\n      <td>116656</td>\n    </tr>\n    <tr>\n      <th>2020-10-13</th>\n      <td>115792</td>\n    </tr>\n    <tr>\n      <th>2020-09-26</th>\n      <td>115113</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 5
    }
   ],
   "source": [
    "#Convert to dataframe with datetime index\n",
    "df = pd.DataFrame([(dateparser.parse(d), int(r)) for d,r in readings], columns=['Date', 'Reading'])\n",
    "df = df.set_index('Date')\n",
    "df.head()"
   ]
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   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#resample to daily\n",
    "rng = pd.date_range(df.index.min(), df.index.max())\n",
    "daily = df.reindex(rng).interpolate(method='time')"
   ]
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   "execution_count": 7,
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     },
     "metadata": {}
    }
   ],
   "source": [
    "#plot daily series\n",
    "ax = daily.plot(figsize=(20,10), title = 'Cumulative usage', ylabel='Usage (kWh)')\n",
    "ax.get_yaxis().set_major_formatter(matplotlib.ticker.FuncFormatter(lambda x, p: format(int(x), ',')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                Reading\n",
       "2013-11-30   384.105960\n",
       "2013-12-31   794.701987\n",
       "2014-01-31  1205.298013\n",
       "2014-02-28  1576.158940\n",
       "2014-03-31  1986.754967"
      ],
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Reading</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2013-11-30</th>\n      <td>384.105960</td>\n    </tr>\n    <tr>\n      <th>2013-12-31</th>\n      <td>794.701987</td>\n    </tr>\n    <tr>\n      <th>2014-01-31</th>\n      <td>1205.298013</td>\n    </tr>\n    <tr>\n      <th>2014-02-28</th>\n      <td>1576.158940</td>\n    </tr>\n    <tr>\n      <th>2014-03-31</th>\n      <td>1986.754967</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 8
    }
   ],
   "source": [
    "#Resample to monthly\n",
    "monthly = daily.resample('M').last()\n",
    "monthly.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def line_format(date):\n",
    "    tlm = date.month_name()[:3]\n",
    "    return f'{date.year} {tlm}' if tlm == 'Jan' else tlm\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 2520x720 with 1 Axes>",
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39.703125 27 39.703125 \r\nQ 22.75 39.703125 19.328125 37.765625 \r\nQ 15.921875 35.84375 13.96875 32.765625 \r\nL 5.71875 33.84375 \r\nL 12.640625 70.609375 \r\nL 48.25 70.609375 \r\nL 48.25 62.203125 \r\nL 19.671875 62.203125 \r\nL 15.828125 42.96875 \r\nQ 22.265625 47.46875 29.34375 47.46875 \r\nQ 38.71875 47.46875 45.15625 40.96875 \r\nQ 51.609375 34.46875 51.609375 24.265625 \r\nQ 51.609375 14.546875 45.953125 7.46875 \r\nQ 39.0625 -1.21875 27.15625 -1.21875 \r\nQ 17.390625 -1.21875 11.203125 4.25 \r\nQ 5.03125 9.71875 4.15625 18.75 \r\nz\r\n\" id=\"ArialMT-53\"/>\r\n       </defs>\r\n       <use xlink:href=\"#ArialMT-50\"/>\r\n       <use x=\"55.615234\" xlink:href=\"#ArialMT-48\"/>\r\n       <use x=\"111.230469\" xlink:href=\"#ArialMT-49\"/>\r\n       <use x=\"166.845703\" xlink:href=\"#ArialMT-53\"/>\r\n       <use x=\"222.460938\" xlink:href=\"#ArialMT-32\"/>\r\n       <use x=\"250.244141\" xlink:href=\"#ArialMT-74\"/>\r\n       <use x=\"300.244141\" xlink:href=\"#ArialMT-97\"/>\r\n       <use x=\"355.859375\" xlink:href=\"#ArialMT-110\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_16\">\r\n     <g id=\"line2d_16\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 434.007182 569.7375 \r\nL 434.007182 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_16\">\r\n      <!-- Feb -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(438.27269 610.666484)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-70\"/>\r\n       <use x=\"61.083984\" xlink:href=\"#ArialMT-101\"/>\r\n       <use x=\"116.699219\" xlink:href=\"#ArialMT-98\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_17\">\r\n     <g id=\"line2d_17\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 455.951002 569.7375 \r\nL 455.951002 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n 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id=\"xtick_19\">\r\n     <g id=\"line2d_19\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 499.838643 569.7375 \r\nL 499.838643 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_19\">\r\n      <!-- May -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(504.007471 613.407031)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-77\"/>\r\n       <use x=\"83.300781\" xlink:href=\"#ArialMT-97\"/>\r\n       <use x=\"138.916016\" xlink:href=\"#ArialMT-121\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_20\">\r\n     <g id=\"line2d_20\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 521.782463 569.7375 \r\nL 521.782463 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_20\">\r\n      <!-- Jun -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(526.047971 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565.670104 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_22\">\r\n      <!-- Aug -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(569.838932 611.594609)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-65\"/>\r\n       <use x=\"66.699219\" xlink:href=\"#ArialMT-117\"/>\r\n       <use x=\"122.314453\" xlink:href=\"#ArialMT-103\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_23\">\r\n     <g id=\"line2d_23\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 587.613924 569.7375 \r\nL 587.613924 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_23\">\r\n      <!-- Sep -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(591.979978 611.594609)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-83\"/>\r\n       <use x=\"66.699219\" xlink:href=\"#ArialMT-101\"/>\r\n       <use x=\"122.314453\" xlink:href=\"#ArialMT-112\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_24\">\r\n     <g id=\"line2d_24\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 609.557744 569.7375 \r\nL 609.557744 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_24\">\r\n      <!-- Oct -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(613.823252 607.905312)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-79\"/>\r\n       <use x=\"77.783203\" xlink:href=\"#ArialMT-99\"/>\r\n       <use x=\"127.783203\" xlink:href=\"#ArialMT-116\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_25\">\r\n     <g id=\"line2d_25\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 631.501564 569.7375 \r\nL 631.501564 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     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<g id=\"xtick_27\">\r\n     <g id=\"line2d_27\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 675.389205 569.7375 \r\nL 675.389205 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_27\">\r\n      <!-- 2016 Jan -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(679.654713 650.124687)rotate(-90)scale(0.165 -0.165)\">\r\n       <defs>\r\n        <path d=\"M 49.75 54.046875 \r\nL 41.015625 53.375 \r\nQ 39.84375 58.546875 37.703125 60.890625 \r\nQ 34.125 64.65625 28.90625 64.65625 \r\nQ 24.703125 64.65625 21.53125 62.3125 \r\nQ 17.390625 59.28125 14.984375 53.46875 \r\nQ 12.59375 47.65625 12.5 36.921875 \r\nQ 15.671875 41.75 20.265625 44.09375 \r\nQ 24.859375 46.4375 29.890625 46.4375 \r\nQ 38.671875 46.4375 44.84375 39.96875 \r\nQ 51.03125 33.5 51.03125 23.25 \r\nQ 51.03125 16.5 48.125 10.71875 \r\nQ 45.21875 4.9375 40.140625 1.859375 \r\nQ 35.0625 -1.21875 28.609375 -1.21875 \r\nQ 17.625 -1.21875 10.6875 6.859375 \r\nQ 3.765625 14.9375 3.765625 33.5 \r\nQ 3.765625 54.25 11.421875 63.671875 \r\nQ 18.109375 71.875 29.4375 71.875 \r\nQ 37.890625 71.875 43.28125 67.140625 \r\nQ 48.6875 62.40625 49.75 54.046875 \r\nz\r\nM 13.875 23.1875 \r\nQ 13.875 18.65625 15.796875 14.5 \r\nQ 17.71875 10.359375 21.1875 8.171875 \r\nQ 24.65625 6 28.46875 6 \r\nQ 34.03125 6 38.03125 10.484375 \r\nQ 42.046875 14.984375 42.046875 22.703125 \r\nQ 42.046875 30.125 38.078125 34.390625 \r\nQ 34.125 38.671875 28.125 38.671875 \r\nQ 22.171875 38.671875 18.015625 34.390625 \r\nQ 13.875 30.125 13.875 23.1875 \r\nz\r\n\" id=\"ArialMT-54\"/>\r\n       </defs>\r\n       <use xlink:href=\"#ArialMT-50\"/>\r\n       <use x=\"55.615234\" xlink:href=\"#ArialMT-48\"/>\r\n       <use x=\"111.230469\" xlink:href=\"#ArialMT-49\"/>\r\n       <use x=\"166.845703\" xlink:href=\"#ArialMT-54\"/>\r\n       <use x=\"222.460938\" xlink:href=\"#ArialMT-32\"/>\r\n       <use x=\"250.244141\" xlink:href=\"#ArialMT-74\"/>\r\n       <use x=\"300.244141\" xlink:href=\"#ArialMT-97\"/>\r\n       <use x=\"355.859375\" xlink:href=\"#ArialMT-110\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_28\">\r\n     <g id=\"line2d_28\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 697.333025 569.7375 \r\nL 697.333025 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_28\">\r\n      <!-- Feb -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(701.598533 610.666484)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-70\"/>\r\n       <use x=\"61.083984\" xlink:href=\"#ArialMT-101\"/>\r\n       <use x=\"116.699219\" xlink:href=\"#ArialMT-98\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_29\">\r\n     <g id=\"line2d_29\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 719.276845 569.7375 \r\nL 719.276845 26.1375 \r\n\" 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x=\"122.314453\" xlink:href=\"#ArialMT-114\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_31\">\r\n     <g id=\"line2d_31\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 763.164486 569.7375 \r\nL 763.164486 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_31\">\r\n      <!-- May -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(767.333314 613.407031)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-77\"/>\r\n       <use x=\"83.300781\" xlink:href=\"#ArialMT-97\"/>\r\n       <use x=\"138.916016\" xlink:href=\"#ArialMT-121\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_32\">\r\n     <g id=\"line2d_32\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 785.108306 569.7375 \r\nL 785.108306 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_32\">\r\n      <!-- Jun -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(789.373814 608.838594)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-74\"/>\r\n       <use x=\"50\" xlink:href=\"#ArialMT-117\"/>\r\n       <use x=\"105.615234\" xlink:href=\"#ArialMT-110\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_33\">\r\n     <g id=\"line2d_33\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 807.052126 569.7375 \r\nL 807.052126 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_33\">\r\n      <!-- Jul -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(811.317634 603.329141)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-74\"/>\r\n       <use x=\"50\" xlink:href=\"#ArialMT-117\"/>\r\n       <use x=\"105.615234\" xlink:href=\"#ArialMT-108\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_34\">\r\n     <g id=\"line2d_34\">\r\n      <path 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xlink:href=\"#ArialMT-83\"/>\r\n       <use x=\"66.699219\" xlink:href=\"#ArialMT-101\"/>\r\n       <use x=\"122.314453\" xlink:href=\"#ArialMT-112\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_36\">\r\n     <g id=\"line2d_36\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 872.883587 569.7375 \r\nL 872.883587 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_36\">\r\n      <!-- Oct -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(877.149095 607.905312)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-79\"/>\r\n       <use x=\"77.783203\" xlink:href=\"#ArialMT-99\"/>\r\n       <use x=\"127.783203\" xlink:href=\"#ArialMT-116\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_37\">\r\n     <g id=\"line2d_37\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 894.827407 569.7375 \r\nL 894.827407 26.1375 \r\n\" 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x=\"127.832031\" xlink:href=\"#ArialMT-99\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_39\">\r\n     <g id=\"line2d_39\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 938.715047 569.7375 \r\nL 938.715047 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_39\">\r\n      <!-- 2017 Jan -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(942.980555 650.124687)rotate(-90)scale(0.165 -0.165)\">\r\n       <defs>\r\n        <path d=\"M 4.734375 62.203125 \r\nL 4.734375 70.65625 \r\nL 51.078125 70.65625 \r\nL 51.078125 63.8125 \r\nQ 44.234375 56.546875 37.515625 44.484375 \r\nQ 30.8125 32.421875 27.15625 19.671875 \r\nQ 24.515625 10.6875 23.78125 0 \r\nL 14.75 0 \r\nQ 14.890625 8.453125 18.0625 20.40625 \r\nQ 21.234375 32.375 27.171875 43.484375 \r\nQ 33.109375 54.59375 39.796875 62.203125 \r\nz\r\n\" id=\"ArialMT-55\"/>\r\n       </defs>\r\n       <use xlink:href=\"#ArialMT-50\"/>\r\n 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x=\"116.699219\" xlink:href=\"#ArialMT-98\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_41\">\r\n     <g id=\"line2d_41\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 982.602688 569.7375 \r\nL 982.602688 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_41\">\r\n      <!-- Mar -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(986.868196 610.651016)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-77\"/>\r\n       <use x=\"83.300781\" xlink:href=\"#ArialMT-97\"/>\r\n       <use x=\"138.916016\" xlink:href=\"#ArialMT-114\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_42\">\r\n     <g id=\"line2d_42\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1004.546508 569.7375 \r\nL 1004.546508 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_42\">\r\n      <!-- Apr -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1008.812016 607.913047)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-65\"/>\r\n       <use x=\"66.699219\" xlink:href=\"#ArialMT-112\"/>\r\n       <use x=\"122.314453\" xlink:href=\"#ArialMT-114\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_43\">\r\n     <g id=\"line2d_43\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1026.490328 569.7375 \r\nL 1026.490328 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_43\">\r\n      <!-- May -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1030.659156 613.407031)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-77\"/>\r\n       <use x=\"83.300781\" xlink:href=\"#ArialMT-97\"/>\r\n       <use x=\"138.916016\" xlink:href=\"#ArialMT-121\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_44\">\r\n     <g id=\"line2d_44\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1048.434149 569.7375 \r\nL 1048.434149 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_44\">\r\n      <!-- Jun -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1052.699656 608.838594)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-74\"/>\r\n       <use x=\"50\" xlink:href=\"#ArialMT-117\"/>\r\n       <use x=\"105.615234\" xlink:href=\"#ArialMT-110\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_45\">\r\n     <g id=\"line2d_45\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1070.377969 569.7375 \r\nL 1070.377969 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_45\">\r\n      <!-- Jul -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1074.643477 603.329141)rotate(-90)scale(0.165 -0.165)\">\r\n     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x=\"127.783203\" xlink:href=\"#ArialMT-116\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_49\">\r\n     <g id=\"line2d_49\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1158.15325 569.7375 \r\nL 1158.15325 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_49\">\r\n      <!-- Nov -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1162.418757 611.579141)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-78\"/>\r\n       <use x=\"72.216797\" xlink:href=\"#ArialMT-111\"/>\r\n       <use x=\"127.832031\" xlink:href=\"#ArialMT-118\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_50\">\r\n     <g id=\"line2d_50\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1180.09707 569.7375 \r\nL 1180.09707 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_50\">\r\n      <!-- Dec -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1184.362578 611.579141)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-68\"/>\r\n       <use x=\"72.216797\" xlink:href=\"#ArialMT-101\"/>\r\n       <use x=\"127.832031\" xlink:href=\"#ArialMT-99\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_51\">\r\n     <g id=\"line2d_51\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1202.04089 569.7375 \r\nL 1202.04089 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_51\">\r\n      <!-- 2018 Jan -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1206.306398 650.124687)rotate(-90)scale(0.165 -0.165)\">\r\n       <defs>\r\n        <path d=\"M 17.671875 38.8125 \r\nQ 12.203125 40.828125 9.5625 44.53125 \r\nQ 6.9375 48.25 6.9375 53.421875 \r\nQ 6.9375 61.234375 12.546875 66.546875 \r\nQ 18.171875 71.875 27.484375 71.875 \r\nQ 36.859375 71.875 42.578125 66.421875 \r\nQ 48.296875 60.984375 48.296875 53.171875 \r\nQ 48.296875 48.1875 45.671875 44.5 \r\nQ 43.0625 40.828125 37.75 38.8125 \r\nQ 44.34375 36.671875 47.78125 31.875 \r\nQ 51.21875 27.09375 51.21875 20.453125 \r\nQ 51.21875 11.28125 44.71875 5.03125 \r\nQ 38.234375 -1.21875 27.640625 -1.21875 \r\nQ 17.046875 -1.21875 10.546875 5.046875 \r\nQ 4.046875 11.328125 4.046875 20.703125 \r\nQ 4.046875 27.6875 7.59375 32.390625 \r\nQ 11.140625 37.109375 17.671875 38.8125 \r\nz\r\nM 15.921875 53.71875 \r\nQ 15.921875 48.640625 19.1875 45.40625 \r\nQ 22.46875 42.1875 27.6875 42.1875 \r\nQ 32.765625 42.1875 36.015625 45.375 \r\nQ 39.265625 48.578125 39.265625 53.21875 \r\nQ 39.265625 58.0625 35.90625 61.359375 \r\nQ 32.5625 64.65625 27.59375 64.65625 \r\nQ 22.5625 64.65625 19.234375 61.421875 \r\nQ 15.921875 58.203125 15.921875 53.71875 \r\nz\r\nM 13.09375 20.65625 \r\nQ 13.09375 16.890625 14.875 13.375 \r\nQ 16.65625 9.859375 20.171875 7.921875 \r\nQ 23.6875 6 27.734375 6 \r\nQ 34.03125 6 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x=\"127.832031\" xlink:href=\"#ArialMT-118\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_62\">\r\n     <g id=\"line2d_62\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1443.422913 569.7375 \r\nL 1443.422913 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_62\">\r\n      <!-- Dec -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1447.68842 611.579141)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-68\"/>\r\n       <use x=\"72.216797\" xlink:href=\"#ArialMT-101\"/>\r\n       <use x=\"127.832031\" xlink:href=\"#ArialMT-99\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_63\">\r\n     <g id=\"line2d_63\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1465.366733 569.7375 \r\nL 1465.366733 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_63\">\r\n      <!-- 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id=\"xtick_64\">\r\n     <g id=\"line2d_64\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1487.310553 569.7375 \r\nL 1487.310553 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_64\">\r\n      <!-- Feb -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1491.576061 610.666484)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-70\"/>\r\n       <use x=\"61.083984\" xlink:href=\"#ArialMT-101\"/>\r\n       <use x=\"116.699219\" xlink:href=\"#ArialMT-98\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_65\">\r\n     <g id=\"line2d_65\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1509.254373 569.7375 \r\nL 1509.254373 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_65\">\r\n      <!-- Mar -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1513.519881 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style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_76\">\r\n      <!-- Feb -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1754.901904 610.666484)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-70\"/>\r\n       <use x=\"61.083984\" xlink:href=\"#ArialMT-101\"/>\r\n       <use x=\"116.699219\" xlink:href=\"#ArialMT-98\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_77\">\r\n     <g id=\"line2d_77\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1772.580216 569.7375 \r\nL 1772.580216 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_77\">\r\n      <!-- Mar -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1776.845724 610.651016)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-77\"/>\r\n       <use x=\"83.300781\" xlink:href=\"#ArialMT-97\"/>\r\n       <use 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May -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1820.636685 613.407031)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-77\"/>\r\n       <use x=\"83.300781\" xlink:href=\"#ArialMT-97\"/>\r\n       <use x=\"138.916016\" xlink:href=\"#ArialMT-121\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_80\">\r\n     <g id=\"line2d_80\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1838.411677 569.7375 \r\nL 1838.411677 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_80\">\r\n      <!-- Jun -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1842.677184 608.838594)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-74\"/>\r\n       <use x=\"50\" xlink:href=\"#ArialMT-117\"/>\r\n       <use x=\"105.615234\" xlink:href=\"#ArialMT-110\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_81\">\r\n     <g id=\"line2d_81\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1860.355497 569.7375 \r\nL 1860.355497 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_81\">\r\n      <!-- Jul -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1864.621005 603.329141)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-74\"/>\r\n       <use x=\"50\" xlink:href=\"#ArialMT-117\"/>\r\n       <use x=\"105.615234\" xlink:href=\"#ArialMT-108\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_82\">\r\n     <g id=\"line2d_82\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1882.299317 569.7375 \r\nL 1882.299317 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_82\">\r\n      <!-- Aug -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1886.468145 611.594609)rotate(-90)scale(0.165 -0.165)\">\r\n     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style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_84\">\r\n      <!-- Oct -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1930.452465 607.905312)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-79\"/>\r\n       <use x=\"77.783203\" xlink:href=\"#ArialMT-99\"/>\r\n       <use x=\"127.783203\" xlink:href=\"#ArialMT-116\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_85\">\r\n     <g id=\"line2d_85\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1948.130778 569.7375 \r\nL 1948.130778 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_85\">\r\n      <!-- Nov -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1952.396286 611.579141)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-78\"/>\r\n       <use x=\"72.216797\" xlink:href=\"#ArialMT-111\"/>\r\n       <use x=\"127.832031\" xlink:href=\"#ArialMT-118\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_86\">\r\n     <g id=\"line2d_86\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1970.074598 569.7375 \r\nL 1970.074598 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_86\">\r\n      <!-- Dec -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(1974.340106 611.579141)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-68\"/>\r\n       <use x=\"72.216797\" xlink:href=\"#ArialMT-101\"/>\r\n       <use x=\"127.832031\" xlink:href=\"#ArialMT-99\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_87\">\r\n     <g id=\"line2d_87\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 1992.018418 569.7375 \r\nL 1992.018418 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_87\">\r\n      <!-- 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transform=\"translate(2018.227746 610.666484)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-70\"/>\r\n       <use x=\"61.083984\" xlink:href=\"#ArialMT-101\"/>\r\n       <use x=\"116.699219\" xlink:href=\"#ArialMT-98\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_89\">\r\n     <g id=\"line2d_89\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 2035.906059 569.7375 \r\nL 2035.906059 26.1375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_89\">\r\n      <!-- Mar -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(2040.171566 610.651016)rotate(-90)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-77\"/>\r\n       <use x=\"83.300781\" xlink:href=\"#ArialMT-97\"/>\r\n       <use x=\"138.916016\" xlink:href=\"#ArialMT-114\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n   </g>\r\n   <g id=\"matplotlib.axis_2\">\r\n    <g id=\"ytick_1\">\r\n     <g id=\"line2d_90\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 93.877969 569.7375 \r\nL 2046.877969 569.7375 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_90\">\r\n      <!-- 0 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(72.202422 575.642695)scale(0.165 -0.165)\">\r\n       <use xlink:href=\"#ArialMT-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_2\">\r\n     <g id=\"line2d_91\">\r\n      <path clip-path=\"url(#p65b8fd9dba)\" d=\"M 93.877969 469.444817 \r\nL 2046.877969 469.444817 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_91\">\r\n      <!-- 1,000 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(40.091875 475.350013)scale(0.165 -0.165)\">\r\n       <defs>\r\n        <path d=\"M 8.890625 0 \r\nL 8.890625 10.015625 \r\nL 18.890625 10.015625 \r\nL 18.890625 0 \r\nQ 18.890625 -5.515625 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     },
     "metadata": {}
    }
   ],
   "source": [
    "#plot monthly diff (usage by month)\n",
    "ax = monthly.diff().plot.bar(figsize=(35,10), title='3 phase power usage', grid=True)\n",
    "ax.get_yaxis().set_major_formatter(matplotlib.ticker.FuncFormatter(lambda x, p: format(int(x), ',')))\n",
    "ax.set_ylabel('Usage (kWh)', labelpad=16)\n",
    "ax.set_xticklabels(map(line_format, monthly.index));\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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17.390625 -1.21875 11.203125 4.25 \r\nQ 5.03125 9.71875 4.15625 18.75 \r\nz\r\n\" id=\"ArialMT-53\"/>\r\n       </defs>\r\n       <use xlink:href=\"#ArialMT-50\"/>\r\n       <use x=\"55.615234\" xlink:href=\"#ArialMT-48\"/>\r\n       <use x=\"111.230469\" xlink:href=\"#ArialMT-49\"/>\r\n       <use x=\"166.845703\" xlink:href=\"#ArialMT-53\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_4\">\r\n     <g id=\"line2d_4\">\r\n      <path clip-path=\"url(#p42b79ea52a)\" d=\"M 416.553516 569.684062 \r\nL 416.553516 26.084062 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_4\">\r\n      <!-- 2016 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(420.819023 618.88625)rotate(-90)scale(0.165 -0.165)\">\r\n       <defs>\r\n        <path d=\"M 49.75 54.046875 \r\nL 41.015625 53.375 \r\nQ 39.84375 58.546875 37.703125 60.890625 \r\nQ 34.125 64.65625 28.90625 64.65625 \r\nQ 24.703125 64.65625 21.53125 62.3125 \r\nQ 17.390625 59.28125 14.984375 53.46875 \r\nQ 12.59375 47.65625 12.5 36.921875 \r\nQ 15.671875 41.75 20.265625 44.09375 \r\nQ 24.859375 46.4375 29.890625 46.4375 \r\nQ 38.671875 46.4375 44.84375 39.96875 \r\nQ 51.03125 33.5 51.03125 23.25 \r\nQ 51.03125 16.5 48.125 10.71875 \r\nQ 45.21875 4.9375 40.140625 1.859375 \r\nQ 35.0625 -1.21875 28.609375 -1.21875 \r\nQ 17.625 -1.21875 10.6875 6.859375 \r\nQ 3.765625 14.9375 3.765625 33.5 \r\nQ 3.765625 54.25 11.421875 63.671875 \r\nQ 18.109375 71.875 29.4375 71.875 \r\nQ 37.890625 71.875 43.28125 67.140625 \r\nQ 48.6875 62.40625 49.75 54.046875 \r\nz\r\nM 13.875 23.1875 \r\nQ 13.875 18.65625 15.796875 14.5 \r\nQ 17.71875 10.359375 21.1875 8.171875 \r\nQ 24.65625 6 28.46875 6 \r\nQ 34.03125 6 38.03125 10.484375 \r\nQ 42.046875 14.984375 42.046875 22.703125 \r\nQ 42.046875 30.125 38.078125 34.390625 \r\nQ 34.125 38.671875 28.125 38.671875 \r\nQ 22.171875 38.671875 18.015625 34.390625 \r\nQ 13.875 30.125 13.875 23.1875 \r\nz\r\n\" id=\"ArialMT-54\"/>\r\n       </defs>\r\n       <use xlink:href=\"#ArialMT-50\"/>\r\n       <use x=\"55.615234\" xlink:href=\"#ArialMT-48\"/>\r\n       <use x=\"111.230469\" xlink:href=\"#ArialMT-49\"/>\r\n       <use x=\"166.845703\" xlink:href=\"#ArialMT-54\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_5\">\r\n     <g id=\"line2d_5\">\r\n      <path clip-path=\"url(#p42b79ea52a)\" d=\"M 509.553516 569.684062 \r\nL 509.553516 26.084062 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_5\">\r\n      <!-- 2017 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(513.819023 618.88625)rotate(-90)scale(0.165 -0.165)\">\r\n       <defs>\r\n        <path d=\"M 4.734375 62.203125 \r\nL 4.734375 70.65625 \r\nL 51.078125 70.65625 \r\nL 51.078125 63.8125 \r\nQ 44.234375 56.546875 37.515625 44.484375 \r\nQ 30.8125 32.421875 27.15625 19.671875 \r\nQ 24.515625 10.6875 23.78125 0 \r\nL 14.75 0 \r\nQ 14.890625 8.453125 18.0625 20.40625 \r\nQ 21.234375 32.375 27.171875 43.484375 \r\nQ 33.109375 54.59375 39.796875 62.203125 \r\nz\r\n\" id=\"ArialMT-55\"/>\r\n       </defs>\r\n       <use xlink:href=\"#ArialMT-50\"/>\r\n       <use x=\"55.615234\" xlink:href=\"#ArialMT-48\"/>\r\n       <use x=\"111.230469\" xlink:href=\"#ArialMT-49\"/>\r\n       <use x=\"166.845703\" xlink:href=\"#ArialMT-55\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_6\">\r\n     <g id=\"line2d_6\">\r\n      <path clip-path=\"url(#p42b79ea52a)\" d=\"M 602.553516 569.684062 \r\nL 602.553516 26.084062 \r\n\" style=\"fill:none;stroke:#ffffff;stroke-linecap:round;stroke-width:1.5;\"/>\r\n     </g>\r\n     <g id=\"text_6\">\r\n      <!-- 2018 -->\r\n      <g style=\"fill:#262626;\" transform=\"translate(606.819023 618.88625)rotate(-90)scale(0.165 -0.165)\">\r\n       <defs>\r\n        <path d=\"M 17.671875 38.8125 \r\nQ 12.203125 40.828125 9.5625 44.53125 \r\nQ 6.9375 48.25 6.9375 53.421875 \r\nQ 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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "#The same, but for yearly usage\n",
    "yearly = daily.resample('Y').last().diff()\n",
    "ax = yearly.plot.bar(title='Annual consumption', figsize=(15,10), ylabel='Usage (kWh)')\n",
    "ax.get_yaxis().set_major_formatter(matplotlib.ticker.FuncFormatter(lambda x, p: format(int(x), ',')))\n",
    "ax.set_xticklabels(yearly.index.year);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "           2013         2014         2015         2016         2017  \\\n",
       "Jan         NaN   410.596026   843.774834   662.935000  1106.981818   \n",
       "Feb         NaN   370.860927   762.119205   726.046122  1657.140909   \n",
       "Mar         NaN   410.596026  1244.479229  1319.397959  2238.975000   \n",
       "Apr         NaN  1925.332945  1741.258741  1276.836735  2166.750000   \n",
       "May         NaN  2043.956044  1799.300699  1319.397959  2238.975000   \n",
       "Jun         NaN  1978.021978  1741.258741  1895.137613  2166.750000   \n",
       "Jul         NaN  1880.450195  1799.300699  1980.340278  2238.975000   \n",
       "Aug         NaN   835.483871   956.190664  1980.340278  2238.975000   \n",
       "Sep         NaN   775.000000   641.550000  1916.458333  2166.750000   \n",
       "Oct         NaN   818.841060   662.935000  1754.957449  1054.190805   \n",
       "Nov         NaN   816.556291   641.550000  1071.272727   621.379310   \n",
       "Dec  410.596026   843.774834   662.935000  1106.981818   642.091954   \n",
       "\n",
       "            2018         2019         2020         2021  \n",
       "Jan   642.091954   861.905983  1523.598522  1054.260504  \n",
       "Feb   579.954023  1074.873932  1251.884236   952.235294  \n",
       "Mar   642.091954  1000.750000  1030.795658   442.109244  \n",
       "Apr  1954.687500   867.456140  1445.962963          NaN  \n",
       "May  2019.843750   751.614035  1793.419355          NaN  \n",
       "Jun  1954.687500  1079.657097  1577.447312          NaN  \n",
       "Jul  1813.836045  4225.169279  1525.975439          NaN  \n",
       "Aug  1774.219178  5162.034483  2115.120858          NaN  \n",
       "Sep  1380.837139  2151.423804  1640.801743          NaN  \n",
       "Oct   932.350427  1344.472747  1337.761610          NaN  \n",
       "Nov   834.102564  1246.643002  1267.608138          NaN  \n",
       "Dec   861.905983  1262.288032  1054.260504          NaN  "
      ],
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     },
     "metadata": {},
     "execution_count": 12
    }
   ],
   "source": [
    "#Take monthly diff and pivot by month name and year\r\n",
    "months_in_order = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']\r\n",
    "monthly_pivot=pd.pivot_table(monthly.diff(), index=pd.Index([x[:3] for x in monthly.index.month_name()]), columns=monthly.index.year, values=\"Reading\").reindex(months_in_order)\r\n",
    "monthly_pivot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {}
    }
   ],
   "source": [
    "#Plot year on year usage by month\n",
    "ax = monthly_pivot.plot.bar(figsize=(25,15), width=1, title='Monthly usage', ylabel='Usage (kWh)')\n",
    "ax.get_yaxis().set_major_formatter(matplotlib.ticker.FuncFormatter(lambda x, p: format(int(x), ',')))"
   ]
  }
 ]
}