From 3f8e34d6a28fd26121521da685acdb7a34c00119 Mon Sep 17 00:00:00 2001
From: Florian Kotthoff <74312290+FlorianK13@users.noreply.github.com>
Date: Thu, 12 Sep 2024 10:05:27 +0200
Subject: [PATCH 1/2] Delete content belonging to old paper #552
---
scripts/Completeness_test.ipynb | 1104 -----------------
.../Matching coordinates with districts.ipynb | 273 ----
scripts/data/VG2500_Districts/VG2500_KRS.cpg | 1 -
scripts/data/VG2500_Districts/VG2500_KRS.dbf | Bin 119202 -> 0 bytes
scripts/data/VG2500_Districts/VG2500_KRS.prj | 1 -
scripts/data/VG2500_Districts/VG2500_KRS.shp | Bin 993992 -> 0 bytes
scripts/data/VG2500_Districts/VG2500_KRS.shx | Bin 3300 -> 0 bytes
scripts/data/VG2500_Districts/aktualitaet.txt | 2 -
.../datenlizenz_deutschland_v2_0_eng.pdf | Bin 207537 -> 0 bytes
...quellenvermerk_datenlizenz_deutschland.txt | 19 -
.../data/VG5000_Municipalities/VG5000_GEM.cpg | 1 -
.../data/VG5000_Municipalities/VG5000_GEM.dbf | Bin 3255026 -> 0 bytes
.../data/VG5000_Municipalities/VG5000_GEM.prj | 1 -
.../data/VG5000_Municipalities/VG5000_GEM.shp | Bin 3404636 -> 0 bytes
.../data/VG5000_Municipalities/VG5000_GEM.shx | Bin 88052 -> 0 bytes
.../VG5000_Municipalities/aktualitaet.txt | 2 -
.../datenlizenz_deutschland_v2_0_eng.pdf | Bin 207537 -> 0 bytes
...quellenvermerk_datenlizenz_deutschland.txt | 19 -
scripts/docker-compose.yml | 19 -
scripts/map_checker/DatabaseSynchronizer.py | 91 --
scripts/map_checker/MapCheckerApp.py | 454 -------
scripts/map_checker/MapCheckerEngine.py | 146 ---
scripts/map_checker/README.md | 15 -
scripts/map_checker/config.py | 42 -
scripts/map_checker/requirements.txt | 10 -
25 files changed, 2200 deletions(-)
delete mode 100644 scripts/Completeness_test.ipynb
delete mode 100644 scripts/Matching coordinates with districts.ipynb
delete mode 100644 scripts/data/VG2500_Districts/VG2500_KRS.cpg
delete mode 100644 scripts/data/VG2500_Districts/VG2500_KRS.dbf
delete mode 100644 scripts/data/VG2500_Districts/VG2500_KRS.prj
delete mode 100644 scripts/data/VG2500_Districts/VG2500_KRS.shp
delete mode 100644 scripts/data/VG2500_Districts/VG2500_KRS.shx
delete mode 100644 scripts/data/VG2500_Districts/aktualitaet.txt
delete mode 100644 scripts/data/VG2500_Districts/datenlizenz_deutschland_v2_0_eng.pdf
delete mode 100644 scripts/data/VG2500_Districts/quellenvermerk_datenlizenz_deutschland.txt
delete mode 100644 scripts/data/VG5000_Municipalities/VG5000_GEM.cpg
delete mode 100644 scripts/data/VG5000_Municipalities/VG5000_GEM.dbf
delete mode 100644 scripts/data/VG5000_Municipalities/VG5000_GEM.prj
delete mode 100644 scripts/data/VG5000_Municipalities/VG5000_GEM.shp
delete mode 100644 scripts/data/VG5000_Municipalities/VG5000_GEM.shx
delete mode 100644 scripts/data/VG5000_Municipalities/aktualitaet.txt
delete mode 100644 scripts/data/VG5000_Municipalities/datenlizenz_deutschland_v2_0_eng.pdf
delete mode 100644 scripts/data/VG5000_Municipalities/quellenvermerk_datenlizenz_deutschland.txt
delete mode 100644 scripts/docker-compose.yml
delete mode 100644 scripts/map_checker/DatabaseSynchronizer.py
delete mode 100644 scripts/map_checker/MapCheckerApp.py
delete mode 100644 scripts/map_checker/MapCheckerEngine.py
delete mode 100644 scripts/map_checker/README.md
delete mode 100644 scripts/map_checker/config.py
delete mode 100644 scripts/map_checker/requirements.txt
diff --git a/scripts/Completeness_test.ipynb b/scripts/Completeness_test.ipynb
deleted file mode 100644
index 61aa7be4..00000000
--- a/scripts/Completeness_test.ipynb
+++ /dev/null
@@ -1,1104 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "id": "1443777f-5a16-4e40-a1e3-3ce6ad9ffb04",
- "metadata": {},
- "source": [
- "# Data completeness of 6 technology tables"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "a4587d1c-49bb-4ae5-8faa-735e05f525cc",
- "metadata": {
- "tags": []
- },
- "source": [
- "### Import dependencies"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 27,
- "id": "07f0efa4-e400-4ed3-879e-83d6af261477",
- "metadata": {},
- "outputs": [],
- "source": [
- "import pandas as pd\n",
- "import numpy as np\n",
- "from sqlalchemy import create_engine\n",
- "from missingno import nullity_filter, nullity_sort\n",
- "import matplotlib.pyplot as plt\n",
- "from matplotlib.lines import Line2D"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "98f0e3a4-c2d5-48cf-bbaf-7736c9c0c014",
- "metadata": {},
- "source": [
- "### Define the modified missing value matrix function\n",
- "Credits to https://github.com/ResidentMario/missingno"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 30,
- "id": "ed8ee384-d0d8-46a1-abce-c6aaea46e8d8",
- "metadata": {},
- "outputs": [],
- "source": [
- "def matrix(\n",
- " df,\n",
- " filter=None,\n",
- " n=0,\n",
- " p=0,\n",
- " sort=None,\n",
- " figsize=(25, 10),\n",
- " width_ratios=(15, 1),\n",
- " color=(0.25, 0.25, 0.25),\n",
- " small_unit_color=None,\n",
- " rasterized=False,\n",
- " fontsize=16,\n",
- " labels=None,\n",
- " label_rotation=45,\n",
- " sparkline=True,\n",
- " freq=None,\n",
- " ax=None,\n",
- " wind=False,\n",
- "):\n",
- " \"\"\"\n",
- " A matrix visualization of the nullity of the given DataFrame.\n",
- "\n",
- " :param df: The `DataFrame` being mapped.\n",
- " :param filter: The filter to apply to the heatmap. Should be one of \"top\", \"bottom\", or None (default).\n",
- " :param n: The max number of columns to include in the filtered DataFrame.\n",
- " :param p: The max percentage fill of the columns in the filtered DataFrame.\n",
- " :param sort: The row sort order to apply. Can be \"ascending\", \"descending\", or None.\n",
- " :param figsize: The size of the figure to display.\n",
- " :param fontsize: The figure's font size. Default to 16.\n",
- " :param labels: Whether or not to display the column names. Defaults to the underlying data labels when there are\n",
- " 50 columns or less, and no labels when there are more than 50 columns.\n",
- " :param label_rotation: What angle to rotate the text labels to. Defaults to 45 degrees.\n",
- " :param sparkline: Whether or not to display the sparkline. Defaults to True.\n",
- " :param width_ratios: The ratio of the width of the matrix to the width of the sparkline. Defaults to `(15, 1)`.\n",
- " Does nothing if `sparkline=False`.\n",
- " :param color: The color of the filled columns. Default is `(0.25, 0.25, 0.25)`.\n",
- " :param small_units_color: The color of units <30 kW\n",
- " :param rasterized: matplotlib rasterized option\n",
- " :param wind: Special case for wind matrix\n",
- " :return: The plot axis.\n",
- " \"\"\"\n",
- " df = nullity_filter(df, filter=filter, n=n, p=p)\n",
- " df = nullity_sort(df, sort=sort, axis=\"columns\")\n",
- "\n",
- " height = df.shape[0]\n",
- " width = df.shape[1]\n",
- "\n",
- " # z is the color-mask array, g is a NxNx3 matrix. Apply the z color-mask to set the RGB of each pixel.\n",
- " z = df.notnull().values\n",
- " g = np.zeros((height, width, 3), dtype=np.float32)\n",
- "\n",
- " g[z > 0.5] = color\n",
- " # Different coloring for small units\n",
- " col_list = df.columns.to_list()\n",
- " if small_unit_color and \"Capacity\" in col_list:\n",
- " column_position = col_list.index(\"Capacity\")\n",
- " z_small = np.zeros_like(z, dtype=np.bool8)\n",
- " z_small = df.iloc[:, column_position].values <= 30\n",
- " g[z_small > 0.5] = small_unit_color\n",
- "\n",
- " g[z < 0.5] = [1, 1, 1]\n",
- "\n",
- " if wind:\n",
- " g_old = g.copy()\n",
- " g_new = np.zeros((height, 2 * width, 3), dtype=np.float32)\n",
- " for i in range(width):\n",
- " g_new[:, [i * 2, i * 2 + 1], :] = (\n",
- " g_old[:, i, :].reshape(height, 1, 3).repeat(2, axis=1)\n",
- " )\n",
- "\n",
- " g = np.delete(g_new, [7, 9], 1)\n",
- "\n",
- " # Set up the matplotlib grid layout. A unary subplot if no sparkline, a left-right splot if yes sparkline.\n",
- " if ax is None:\n",
- " plt.figure(figsize=figsize)\n",
- " if sparkline:\n",
- " gs = gridspec.GridSpec(1, 2, width_ratios=width_ratios)\n",
- " gs.update(wspace=0.08)\n",
- " ax1 = plt.subplot(gs[1])\n",
- " else:\n",
- " gs = gridspec.GridSpec(1, 1)\n",
- " ax0 = plt.subplot(gs[0])\n",
- " else:\n",
- " if sparkline is not False:\n",
- " warnings.warn(\n",
- " \"Plotting a sparkline on an existing axis is not currently supported. \"\n",
- " \"To remove this warning, set sparkline=False.\"\n",
- " )\n",
- " sparkline = False\n",
- " ax0 = ax\n",
- "\n",
- " # Create the nullity plot.\n",
- " ax0.imshow(g, interpolation=\"none\", rasterized=rasterized)\n",
- "\n",
- " # Remove extraneous default visual elements.\n",
- " ax0.set_aspect(\"auto\")\n",
- " ax0.grid(visible=False)\n",
- " ax0.xaxis.tick_top()\n",
- " ax0.xaxis.set_ticks_position(\"none\")\n",
- " ax0.yaxis.set_ticks_position(\"none\")\n",
- " ax0.spines[\"top\"].set_visible(False)\n",
- " ax0.spines[\"right\"].set_visible(False)\n",
- " ax0.spines[\"bottom\"].set_visible(False)\n",
- " ax0.spines[\"left\"].set_visible(False)\n",
- "\n",
- " # Set up and rotate the column ticks. The labels argument is set to None by default. If the user specifies it in\n",
- " # the argument, respect that specification. Otherwise display for <= 50 columns and do not display for > 50.\n",
- " if (labels or (labels is None and len(df.columns) <= 50)) and not wind:\n",
- " ha = \"left\"\n",
- " ax0.set_xticks(list(range(0, width)))\n",
- " ax0.set_xticklabels(\n",
- " list(df.columns), rotation=label_rotation, ha=ha, fontsize=fontsize\n",
- " )\n",
- " else:\n",
- " ax0.set_xticks([])\n",
- "\n",
- " # Adds Timestamps ticks if freq is not None, else set up the two top-bottom row ticks.\n",
- " if freq:\n",
- " ts_list = []\n",
- "\n",
- " if type(df.index) == pd.PeriodIndex:\n",
- " ts_array = pd.date_range(\n",
- " df.index.to_timestamp().date[0],\n",
- " df.index.to_timestamp().date[-1],\n",
- " freq=freq,\n",
- " ).values\n",
- "\n",
- " ts_ticks = pd.date_range(\n",
- " df.index.to_timestamp().date[0],\n",
- " df.index.to_timestamp().date[-1],\n",
- " freq=freq,\n",
- " ).map(lambda t: t.strftime(\"%Y-%m-%d\"))\n",
- "\n",
- " elif type(df.index) == pd.DatetimeIndex:\n",
- " ts_array = pd.date_range(df.index[0], df.index[-1], freq=freq).values\n",
- "\n",
- " ts_ticks = pd.date_range(df.index[0], df.index[-1], freq=freq).map(\n",
- " lambda t: t.strftime(\"%Y-%m-%d\")\n",
- " )\n",
- " else:\n",
- " raise KeyError(\"Dataframe index must be PeriodIndex or DatetimeIndex.\")\n",
- " try:\n",
- " for value in ts_array:\n",
- " ts_list.append(df.index.get_loc(value))\n",
- " except KeyError:\n",
- " raise KeyError(\"Could not divide time index into desired frequency.\")\n",
- "\n",
- " ax0.set_yticks(ts_list)\n",
- " ax0.set_yticklabels(ts_ticks, fontsize=int(fontsize / 16 * 20), rotation=0)\n",
- " else:\n",
- " ax0.set_yticks([0, df.shape[0] - 1])\n",
- " ax0.set_yticklabels(\n",
- " [1, df.shape[0]], fontsize=int(fontsize / 16 * 20), rotation=0\n",
- " )\n",
- "\n",
- " # Create the inter-column vertical grid.\n",
- " if not wind:\n",
- " in_between_point = [x + 0.5 for x in range(0, width - 1)]\n",
- " for in_between_point in in_between_point:\n",
- " ax0.axvline(in_between_point, linestyle=\"-\", color=\"white\")\n",
- "\n",
- " if sparkline:\n",
- " # Calculate row-wise completeness for the sparkline.\n",
- " completeness_srs = df.notnull().astype(bool).sum(axis=1)\n",
- " x_domain = list(range(0, height))\n",
- " y_range = list(reversed(completeness_srs.values))\n",
- " min_completeness = min(y_range)\n",
- " max_completeness = max(y_range)\n",
- " min_completeness_index = y_range.index(min_completeness)\n",
- " max_completeness_index = y_range.index(max_completeness)\n",
- "\n",
- " # Set up the sparkline, remove the border element.\n",
- " ax1.grid(b=False)\n",
- " ax1.set_aspect(\"auto\")\n",
- " # GH 25\n",
- " if int(mpl.__version__[0]) <= 1:\n",
- " ax1.set_axis_bgcolor((1, 1, 1))\n",
- " else:\n",
- " ax1.set_facecolor((1, 1, 1))\n",
- " ax1.spines[\"top\"].set_visible(False)\n",
- " ax1.spines[\"right\"].set_visible(False)\n",
- " ax1.spines[\"bottom\"].set_visible(False)\n",
- " ax1.spines[\"left\"].set_visible(False)\n",
- " ax1.set_ymargin(0)\n",
- "\n",
- " # Plot sparkline---plot is sideways so the x and y axis are reversed.\n",
- " ax1.plot(y_range, x_domain, color=color)\n",
- "\n",
- " if labels:\n",
- " # Figure out what case to display the label in: mixed, upper, lower.\n",
- " label = \"Data Completeness\"\n",
- " if str(df.columns[0]).islower():\n",
- " label = label.lower()\n",
- " if str(df.columns[0]).isupper():\n",
- " label = label.upper()\n",
- "\n",
- " # Set up and rotate the sparkline label.\n",
- " ha = \"left\"\n",
- " ax1.set_xticks(\n",
- " [min_completeness + (max_completeness - min_completeness) / 2]\n",
- " )\n",
- " ax1.set_xticklabels(\n",
- " [label], rotation=label_rotation, ha=ha, fontsize=fontsize\n",
- " )\n",
- " ax1.xaxis.tick_top()\n",
- " ax1.set_yticks([])\n",
- " else:\n",
- " ax1.set_xticks([])\n",
- " ax1.set_yticks([])\n",
- "\n",
- " # Add maximum and minimum labels, circles.\n",
- " ax1.annotate(\n",
- " max_completeness,\n",
- " xy=(max_completeness, max_completeness_index),\n",
- " xytext=(max_completeness + 2, max_completeness_index),\n",
- " fontsize=int(fontsize / 16 * 14),\n",
- " va=\"center\",\n",
- " ha=\"left\",\n",
- " )\n",
- " ax1.annotate(\n",
- " min_completeness,\n",
- " xy=(min_completeness, min_completeness_index),\n",
- " xytext=(min_completeness - 2, min_completeness_index),\n",
- " fontsize=int(fontsize / 16 * 14),\n",
- " va=\"center\",\n",
- " ha=\"right\",\n",
- " )\n",
- "\n",
- " ax1.set_xlim(\n",
- " [min_completeness - 2, max_completeness + 2]\n",
- " ) # Otherwise the circles are cut off.\n",
- " ax1.plot(\n",
- " [min_completeness],\n",
- " [min_completeness_index],\n",
- " \".\",\n",
- " color=color,\n",
- " markersize=10.0,\n",
- " )\n",
- " ax1.plot(\n",
- " [max_completeness],\n",
- " [max_completeness_index],\n",
- " \".\",\n",
- " color=color,\n",
- " markersize=10.0,\n",
- " )\n",
- "\n",
- " # Remove tick mark (only works after plotting).\n",
- " ax1.xaxis.set_ticks_position(\"none\")\n",
- "\n",
- " return ax0"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "44dfdf79-47c9-48d1-9c35-c9c0503dcd46",
- "metadata": {},
- "source": [
- "### Establish a connection to open-mastr database"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "id": "7f409571-ab4a-403a-8c3c-93d6e7f7927f",
- "metadata": {},
- "outputs": [],
- "source": [
- "db_url = \"postgresql://postgres:postsgg@localhost:5432/open-mastr-local\"\n",
- "engine = create_engine(db_url)\n",
- "con = engine.connect()"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "bd489063-6750-41b4-a24b-b7cc7daeecd8",
- "metadata": {},
- "source": [
- "## Analysis"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "53942a4a-8073-437d-a576-2afd5b922c51",
- "metadata": {
- "tags": []
- },
- "source": [
- "### Load first wind dataset, others subsequently"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "id": "605ab1fd-36e3-45a8-8306-49fb49132235",
- "metadata": {
- "tags": []
- },
- "outputs": [],
- "source": [
- "column_query = \"\"\"SELECT column_name \n",
- " FROM information_schema.columns\n",
- " WHERE table_name = 'wind_extended'\"\"\"\n",
- "column_list = pd.read_sql(column_query, con=con).values.tolist()\n",
- "column_list = [sublist[0] for sublist in column_list]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "id": "2888c14f-e692-400c-b83f-522ecb02a6e9",
- "metadata": {},
- "outputs": [],
- "source": [
- "wind_completeness = {}\n",
- "for column in column_list:\n",
- " comp_query = f\"\"\"SELECT AVG(CASE WHEN \"{column}\" IS NULL THEN 0.0 ELSE 1.0 END)*100 AS completeness\n",
- " FROM wind_extended\"\"\"\n",
- " df = pd.read_sql(comp_query, con=con)\n",
- " wind_completeness[column] = df.completeness[0]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "id": "c0e22fae-b807-4d4c-8814-abc817c3de3a",
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "{'geom': 97.48636471425183,\n",
- " 'DatumDownload': 100.0,\n",
- " 'UtmEast': 0.0,\n",
- " 'UtmNorth': 0.0,\n",
- " 'GaussKruegerHoch': 0.0}"
- ]
- },
- "execution_count": 19,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "dict(list(wind_completeness.items())[:5])"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "8e758406-6d41-4796-8124-cdfd9c55b7b3",
- "metadata": {},
- "source": [
- "### Focus on interesting columns"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "id": "3dd89e21-2f84-4850-8836-00476fd218b1",
- "metadata": {},
- "outputs": [],
- "source": [
- "wind_include_columns = [\n",
- " \"Nettonennleistung\",\n",
- " \"Landkreis\",\n",
- " \"Postleitzahl\",\n",
- " \"Hausnummer\",\n",
- " \"Seelage\",\n",
- " \"Laengengrad\",\n",
- "]\n",
- "wind_english_columns = [\n",
- " \"Capacity\",\n",
- " \"Region\",\n",
- " \"Postcode\",\n",
- " \"Address\",\n",
- " \"Offshore position\",\n",
- " \"Coordinates\",\n",
- "]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "id": "3f7d7620",
- "metadata": {
- "collapsed": false,
- "jupyter": {
- "outputs_hidden": false
- },
- "pycharm": {
- "name": "#%%\n"
- }
- },
- "outputs": [],
- "source": [
- "specific_completeness_query = \"SELECT \"\n",
- "for column in wind_include_columns[:-1]:\n",
- " specific_completeness_query += f\"\"\"\"{column}\", \"\"\"\n",
- "specific_completeness_query += f\"\"\" \"{wind_include_columns[-1]}\" \"\"\"\n",
- "specific_completeness_query += \"\"\"FROM wind_extended ORDER BY \"EinheitMastrNummer\"; \"\"\"\n",
- "\n",
- "wind_df = pd.read_sql_query(sql=specific_completeness_query, con=con)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "id": "8e0439ce",
- "metadata": {
- "collapsed": false,
- "jupyter": {
- "outputs_hidden": false
- },
- "pycharm": {
- "name": "#%%\n"
- }
- },
- "outputs": [
- {
- "data": {
- "text/html": [
- "\n",
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " Nettonennleistung | \n",
- " Landkreis | \n",
- " Postleitzahl | \n",
- " Hausnummer | \n",
- " Seelage | \n",
- " Laengengrad | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " | 0 | \n",
- " 31.00 | \n",
- " Oder-Spree | \n",
- " 1 | \n",
- " None | \n",
- " None | \n",
- " 14.387865 | \n",
- "
\n",
- " \n",
- " | 1 | \n",
- " 31.00 | \n",
- " Paderborn | \n",
- " 1 | \n",
- " None | \n",
- " None | \n",
- " 8.651723 | \n",
- "
\n",
- " \n",
- " | 2 | \n",
- " 31.00 | \n",
- " Eifelkreis Bitburg-Prüm | \n",
- " 1 | \n",
- " None | \n",
- " None | \n",
- " 6.248464 | \n",
- "
\n",
- " \n",
- " | 3 | \n",
- " 31.00 | \n",
- " Donnersbergkreis | \n",
- " 1 | \n",
- " None | \n",
- " None | \n",
- " 8.045690 | \n",
- "
\n",
- " \n",
- " | 4 | \n",
- " 2.02 | \n",
- " Erfurt | \n",
- " 1 | \n",
- " None | \n",
- " None | \n",
- " NaN | \n",
- "
\n",
- " \n",
- " | ... | \n",
- " ... | \n",
- " ... | \n",
- " ... | \n",
- " ... | \n",
- " ... | \n",
- " ... | \n",
- "
\n",
- " \n",
- " | 33731 | \n",
- " 31.00 | \n",
- " Ostholstein | \n",
- " 1 | \n",
- " None | \n",
- " None | \n",
- " 11.015243 | \n",
- "
\n",
- " \n",
- " | 33732 | \n",
- " 31.00 | \n",
- " Nordfriesland | \n",
- " 1 | \n",
- " None | \n",
- " None | \n",
- " 9.096121 | \n",
- "
\n",
- " \n",
- " | 33733 | \n",
- " 31.00 | \n",
- " Esslingen | \n",
- " 1 | \n",
- " None | \n",
- " None | \n",
- " 9.620833 | \n",
- "
\n",
- " \n",
- " | 33734 | \n",
- " 31.00 | \n",
- " Salzlandkreis | \n",
- " 1 | \n",
- " None | \n",
- " None | \n",
- " 11.502701 | \n",
- "
\n",
- " \n",
- " | 33735 | \n",
- " 31.00 | \n",
- " Ludwigslust-Parchim | \n",
- " 1 | \n",
- " None | \n",
- " None | \n",
- " 12.234140 | \n",
- "
\n",
- " \n",
- "
\n",
- "
33736 rows × 6 columns
\n",
- "
\n",
- "\n",
- "
\n",
- " \n",
- " \n",
- " | \n",
- " Capacity | \n",
- " Region | \n",
- " Postcode | \n",
- " Address | \n",
- " Offshore position | \n",
- " Coordinates | \n",
- "
\n",
- " \n",
- " \n",
- " \n",
- " | 6927 | \n",
- " 31.0 | \n",
- " Zwickau | \n",
- " 1 | \n",
- " 95Z | \n",
- " None | \n",
- " 12.348829 | \n",
- "
\n",
- " \n",
- " | 8280 | \n",
- " 31.0 | \n",
- " Zwickau | \n",
- " 1 | \n",
- " 901 | \n",
- " None | \n",
- " 12.348285 | \n",
- "
\n",
- " \n",
- " | 29577 | \n",
- " 31.0 | \n",
- " Zwickau | \n",
- " 1 | \n",
- " 4 | \n",
- " None | \n",
- " 16.593999 | \n",
- "
\n",
- " \n",
- " | 12174 | \n",
- " 31.0 | \n",
- " Zwickau | \n",
- " 1 | \n",
- " 1 Y | \n",
- " None | \n",
- " 12.556667 | \n",
- "
\n",
- " \n",
- " | 33620 | \n",
- " 31.0 | \n",
- " Zwickau | \n",
- " 1 | \n",
- " 1 | \n",
- " None | \n",
- " 12.385010 | \n",
- "
\n",
- " \n",
- "
\n",
- "