acbeo.csv

acbeo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as dates\n",
    "import matplotlib.ticker as ticker\n",
    "import seaborn as sns\n",
    "from pandas.plotting import register_matplotlib_converters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "register_matplotlib_converters()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>Flüssige Mittel (ohne SM und Schulden)</th>\n",
       "      <th>Gesamtes Vermögen (ohne Schulden)</th>\n",
       "      <th>Instandhaltung Bus</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jahr</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>5221.70</td>\n",
       "      <td>5921.70</td>\n",
       "      <td>1850.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>8633.81</td>\n",
       "      <td>14333.81</td>\n",
       "      <td>1502.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>12660.84</td>\n",
       "      <td>20516.16</td>\n",
       "      <td>5755.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>16314.19</td>\n",
       "      <td>26396.04</td>\n",
       "      <td>5631.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>16443.89</td>\n",
       "      <td>28986.99</td>\n",
       "      <td>4465.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>19414.81</td>\n",
       "      <td>29809.39</td>\n",
       "      <td>1380.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>19696.26</td>\n",
       "      <td>31776.44</td>\n",
       "      <td>4431.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>3134.26</td>\n",
       "      <td>25409.98</td>\n",
       "      <td>2477.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-31</th>\n",
       "      <td>9536.81</td>\n",
       "      <td>27885.14</td>\n",
       "      <td>1425.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>17799.11</td>\n",
       "      <td>36603.16</td>\n",
       "      <td>2625.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>23529.96</td>\n",
       "      <td>38663.11</td>\n",
       "      <td>2576.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>30157.85</td>\n",
       "      <td>43597.40</td>\n",
       "      <td>5250.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-31</th>\n",
       "      <td>33762.32</td>\n",
       "      <td>44570.62</td>\n",
       "      <td>2159.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>43044.59</td>\n",
       "      <td>50589.04</td>\n",
       "      <td>4605.50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Flüssige Mittel (ohne SM und Schulden)  \\\n",
       "Jahr                                                 \n",
       "2010-12-31                                 5221.70   \n",
       "2011-12-31                                 8633.81   \n",
       "2012-12-31                                12660.84   \n",
       "2013-12-31                                16314.19   \n",
       "2014-12-31                                16443.89   \n",
       "2015-12-31                                19414.81   \n",
       "2016-12-31                                19696.26   \n",
       "2017-12-31                                 3134.26   \n",
       "2018-12-31                                 9536.81   \n",
       "2019-12-31                                17799.11   \n",
       "2020-12-31                                23529.96   \n",
       "2021-12-31                                30157.85   \n",
       "2022-12-31                                33762.32   \n",
       "2023-12-31                                43044.59   \n",
       "\n",
       "            Gesamtes Vermögen (ohne Schulden)  Instandhaltung Bus  \n",
       "Jahr                                                               \n",
       "2010-12-31                            5921.70             1850.00  \n",
       "2011-12-31                           14333.81             1502.30  \n",
       "2012-12-31                           20516.16             5755.48  \n",
       "2013-12-31                           26396.04             5631.70  \n",
       "2014-12-31                           28986.99             4465.80  \n",
       "2015-12-31                           29809.39             1380.15  \n",
       "2016-12-31                           31776.44             4431.95  \n",
       "2017-12-31                           25409.98             2477.60  \n",
       "2018-12-31                           27885.14             1425.40  \n",
       "2019-12-31                           36603.16             2625.90  \n",
       "2020-12-31                           38663.11             2576.10  \n",
       "2021-12-31                           43597.40             5250.75  \n",
       "2022-12-31                           44570.62             2159.40  \n",
       "2023-12-31                           50589.04             4605.50  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "balance = pd.read_csv(\"acbeo.csv\", index_col=0, thousands=\"'\", parse_dates=True)\n",
    "balance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for column in balance.columns:\n",
    "    plt.plot(balance[column], label=column)\n",
    "\n",
    "for label, date in {\n",
    "    \"T4\": pd.to_datetime(\"2011-3-1\"),  # at some point in 2011 ... \n",
    "    \"SM12\": pd.to_datetime(\"2012-8-12\"), \n",
    "    \"SM13\": pd.to_datetime(\"2013-8-8\"), \n",
    "    \"Neues Boot\": pd.to_datetime(\"2015-3-22\"), \n",
    "    \"Vivaro\": pd.to_datetime(\"2017-10-21\"),\n",
    "    \"SM24\": pd.to_datetime(\"2023-7-26\"), \n",
    "}.items():\n",
    "    plt.annotate(label, (date + pd.to_timedelta(31, \"days\"), 22000), c=\"0.5\")    \n",
    "    plt.axvline(date, c=\"0.9\")\n",
    "\n",
    "plt.gca().set_xlim(left=pd.to_datetime(\"2011\"), right=pd.to_datetime(\"2024\"))\n",
    "plt.gca().xaxis.set_major_locator(dates.YearLocator())\n",
    "plt.gca().xaxis.set_minor_locator(dates.YearLocator(month=7))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.NullFormatter())\n",
    "plt.gca().xaxis.set_minor_formatter(dates.DateFormatter(\"%Y\"))\n",
    "for tick in plt.gca().xaxis.get_minor_ticks():\n",
    "    tick.tick1line.set_markersize(0)\n",
    "    tick.tick2line.set_markersize(0)\n",
    "    tick.label1.set_horizontalalignment(\"center\")\n",
    "\n",
    "plt.legend(loc=\"upper left\", frameon=False)\n",
    "sns.despine()\n",
    "plt.ylabel(\"CHF\")\n",
    "plt.ylim(0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}