src/pub_3_pca.ipynb

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 "metadata": {
  "language_info": {
   "name": "python",
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "version": "3.7.3-final"
  },
  "orig_nbformat": 2,
  "file_extension": ".py",
  "mimetype": "text/x-python",
  "name": "python",
  "npconvert_exporter": "python",
  "pygments_lexer": "ipython3",
  "version": 3,
  "kernelspec": {
   "name": "python37364bit72a75e54b0294944b34ebbde9c9c68ed",
   "display_name": "Python 3.7.3 64-bit"
  }
 },
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import preprocessing\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from scipy.cluster.hierarchy import dendrogram\n",
    "from sklearn.cluster import AgglomerativeClustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "strSource = r\"D:\\ML\\data\\StadtteilprofileBerichtsjahr2018_endversion.csv\"\n",
    "df = pd.read_csv(strSource, sep=';', header=0, encoding='iso-8859-1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def createIndex(df):\n",
    "    #Create Coumn ID and set as Index\n",
    "    newIndex = []\n",
    "    for i in df.index:\n",
    "        i += 1\n",
    "        newIndex.append(\"ST\" + str(i))\n",
    "\n",
    "    df['id'] = newIndex\n",
    "    dfi = df.set_index('id')\n",
    "    return dfi\n",
    "\n",
    "df = createIndex(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.dropna(axis='columns')\n",
    "\n",
    "scaler = preprocessing.StandardScaler()\n",
    "array_scaled = scaler.fit_transform(df.loc[:,df.columns.difference(['Stadtteil'])])\n",
    "dfs = pd.DataFrame(array_scaled,columns = df.columns.difference(['Stadtteil']))\n",
    "dfs.cov().to_csv(r\"D:\\ML\\work\\Korrelationsmatrix.csv\", sep=';', na_rep='NaN', index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "0\n0   0.461172\n1   0.185561\n2   0.129668\n3   0.032940\n4   0.028806\n5   0.027496\n6   0.022767\n7   0.017476\n8   0.013959\n9   0.011174\n10  0.009634\n11  0.008792\n12  0.007671\nAnzahl Hauptkomponenten: 13\n"
    }
   ],
   "source": [
    "pca = PCA(n_components=0.95)\n",
    "array_pc = pca.fit(dfs).transform(dfs)\n",
    "print(pd.DataFrame(pca.explained_variance_ratio_))\n",
    "print('Anzahl Hauptkomponenten: ' + str(pca.components_.shape[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": "<Figure size 432x288 with 1 Axes>"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pca_scores = []\n",
    "for n in range(pca.components_.shape[0]):\n",
    "    pca.n_components = n\n",
    "    pca_scores.append(np.mean(cross_val_score(pca, dfs)))\n",
    "    \n",
    "plt.figure()\n",
    "n_components = np.arange(0, pca.n_components+1, 1)\n",
    "plt.plot(n_components, pca_scores, 'b', label='PCA scores')\n",
    "plt.xlabel('nb of components')\n",
    "plt.ylabel('CV scores')\n",
    "plt.legend(loc='lower right')\n",
    "plt.title('PCA-Scores')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "pca = PCA(n_components=9)\n",
    "array_pc = pca.fit(dfs).transform(dfs)\n",
    "dfp = pd.DataFrame(array_pc)\n",
    "dfp = createIndex(dfp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_dendrogram(model, **kwargs):\n",
    "    # Create linkage matrix and then plot the dendrogram\n",
    "    counts = np.zeros(model.children_.shape[0])\n",
    "    n_samples = len(model.labels_)\n",
    "\n",
    "    for i, merge in enumerate(model.children_):\n",
    "        current_count = 0\n",
    "        for child_idx in merge:\n",
    "            if child_idx < n_samples:\n",
    "                current_count += 1\n",
    "            else:\n",
    "                current_count += counts[child_idx - n_samples]\n",
    "        counts[i] = current_count\n",
    "    \n",
    "    linkage_matrix = np.column_stack([model.children_, model.distances_,\n",
    "                                      counts]).astype(float)\n",
    "    \n",
    "    dendrogram(linkage_matrix, **kwargs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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</g>\r\n    <g id=\"xtick_22\">\r\n     <g id=\"text_22\">\r\n      <!-- 91 -->\r\n      <g transform=\"translate(110.554403 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-49\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_23\">\r\n     <g id=\"text_23\">\r\n      <!-- 36 -->\r\n      <g transform=\"translate(113.936222 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-51\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-54\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_24\">\r\n     <g id=\"text_24\">\r\n      <!-- 57 -->\r\n      <g transform=\"translate(117.31804 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-55\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_25\">\r\n     <g id=\"text_25\">\r\n      <!-- 95 -->\r\n      <g transform=\"translate(120.699858 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-53\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_26\">\r\n     <g id=\"text_26\">\r\n      <!-- 37 -->\r\n      <g transform=\"translate(124.081676 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-51\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-55\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_27\">\r\n     <g id=\"text_27\">\r\n      <!-- 70 -->\r\n      <g transform=\"translate(127.463494 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-55\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_28\">\r\n     <g id=\"text_28\">\r\n      <!-- 0 -->\r\n      <g transform=\"translate(130.845312 249.939375)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_29\">\r\n     <g id=\"text_29\">\r\n      <!-- 2 -->\r\n      <g transform=\"translate(134.227131 249.939375)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-50\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_30\">\r\n     <g id=\"text_30\">\r\n      <!-- 4 -->\r\n      <g transform=\"translate(137.608949 249.939375)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-52\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_31\">\r\n     <g id=\"text_31\">\r\n      <!-- 45 -->\r\n      <g transform=\"translate(140.990767 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-52\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-53\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_32\">\r\n     <g id=\"text_32\">\r\n      <!-- 6 -->\r\n      <g transform=\"translate(144.372585 249.939375)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-54\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_33\">\r\n     <g id=\"text_33\">\r\n      <!-- 17 -->\r\n      <g transform=\"translate(147.754403 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-55\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_34\">\r\n     <g id=\"text_34\">\r\n      <!-- 52 -->\r\n      <g transform=\"translate(151.136222 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-50\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_35\">\r\n     <g id=\"text_35\">\r\n      <!-- 3 -->\r\n      <g transform=\"translate(154.51804 249.939375)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-51\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_36\">\r\n     <g id=\"text_36\">\r\n      <!-- 47 -->\r\n      <g transform=\"translate(157.899858 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-52\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-55\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_37\">\r\n     <g id=\"text_37\">\r\n      <!-- 18 -->\r\n      <g transform=\"translate(161.281676 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-56\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_38\">\r\n     <g id=\"text_38\">\r\n      <!-- 34 -->\r\n      <g transform=\"translate(164.663494 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-51\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-52\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_39\">\r\n     <g id=\"text_39\">\r\n      <!-- 38 -->\r\n      <g transform=\"translate(168.045313 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-51\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-56\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_40\">\r\n     <g id=\"text_40\">\r\n      <!-- 31 -->\r\n      <g transform=\"translate(171.427131 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-51\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-49\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_41\">\r\n     <g id=\"text_41\">\r\n      <!-- 32 -->\r\n      <g transform=\"translate(174.808949 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-51\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-50\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_42\">\r\n     <g id=\"text_42\">\r\n      <!-- 40 -->\r\n      <g transform=\"translate(178.190767 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-52\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_43\">\r\n     <g id=\"text_43\">\r\n      <!-- 44 -->\r\n      <g transform=\"translate(181.572585 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-52\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-52\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_44\">\r\n     <g id=\"text_44\">\r\n      <!-- 54 -->\r\n      <g transform=\"translate(184.954403 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-52\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_45\">\r\n     <g id=\"text_45\">\r\n      <!-- 42 -->\r\n      <g transform=\"translate(188.336222 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-52\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-50\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_46\">\r\n     <g id=\"text_46\">\r\n      <!-- 33 -->\r\n      <g transform=\"translate(191.71804 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-51\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-51\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_47\">\r\n     <g id=\"text_47\">\r\n      <!-- 39 -->\r\n      <g transform=\"translate(195.099858 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-51\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-57\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_48\">\r\n     <g id=\"text_48\">\r\n      <!-- 86 -->\r\n      <g transform=\"translate(198.481676 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-56\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-54\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_49\">\r\n     <g id=\"text_49\">\r\n      <!-- 92 -->\r\n      <g transform=\"translate(201.863494 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-50\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_50\">\r\n     <g id=\"text_50\">\r\n      <!-- 59 -->\r\n      <g transform=\"translate(205.245313 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-57\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_51\">\r\n     <g id=\"text_51\">\r\n      <!-- 83 -->\r\n      <g transform=\"translate(208.627131 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-56\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-51\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_52\">\r\n     <g id=\"text_52\">\r\n      <!-- 5 -->\r\n      <g transform=\"translate(212.008949 249.939375)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-53\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_53\">\r\n     <g id=\"text_53\">\r\n      <!-- 14 -->\r\n      <g transform=\"translate(215.390767 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-52\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_54\">\r\n     <g id=\"text_54\">\r\n      <!-- 11 -->\r\n      <g transform=\"translate(218.772585 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-49\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_55\">\r\n     <g id=\"text_55\">\r\n      <!-- 10 -->\r\n      <g transform=\"translate(222.154403 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_56\">\r\n     <g id=\"text_56\">\r\n      <!-- 12 -->\r\n      <g transform=\"translate(225.536222 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-50\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_57\">\r\n     <g id=\"text_57\">\r\n      <!-- 72 -->\r\n      <g transform=\"translate(228.91804 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-55\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-50\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_58\">\r\n     <g id=\"text_58\">\r\n      <!-- 89 -->\r\n      <g transform=\"translate(232.299858 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-56\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-57\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_59\">\r\n     <g id=\"text_59\">\r\n      <!-- 85 -->\r\n      <g transform=\"translate(235.681676 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-56\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-53\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_60\">\r\n     <g id=\"text_60\">\r\n      <!-- 97 -->\r\n      <g transform=\"translate(239.063494 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-55\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_61\">\r\n     <g id=\"text_61\">\r\n      <!-- 79 -->\r\n      <g transform=\"translate(242.445312 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-55\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-57\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_62\">\r\n     <g id=\"text_62\">\r\n      <!-- 94 -->\r\n      <g transform=\"translate(245.827131 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-52\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_63\">\r\n     <g id=\"text_63\">\r\n      <!-- 49 -->\r\n      <g transform=\"translate(249.208949 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-52\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-57\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_64\">\r\n     <g id=\"text_64\">\r\n      <!-- 50 -->\r\n      <g transform=\"translate(252.590767 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_65\">\r\n     <g id=\"text_65\">\r\n      <!-- 1 -->\r\n      <g transform=\"translate(255.972585 249.939375)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_66\">\r\n     <g id=\"text_66\">\r\n      <!-- 56 -->\r\n      <g transform=\"translate(259.354403 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-54\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_67\">\r\n     <g id=\"text_67\">\r\n      <!-- 15 -->\r\n      <g transform=\"translate(262.736222 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-53\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_68\">\r\n     <g id=\"text_68\">\r\n      <!-- 75 -->\r\n      <g transform=\"translate(266.11804 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-55\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-53\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_69\">\r\n     <g id=\"text_69\">\r\n      <!-- 67 -->\r\n      <g transform=\"translate(269.499858 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-54\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-55\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_70\">\r\n     <g id=\"text_70\">\r\n      <!-- 65 -->\r\n      <g transform=\"translate(272.881676 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-54\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-53\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_71\">\r\n     <g id=\"text_71\">\r\n      <!-- 66 -->\r\n      <g transform=\"translate(276.263494 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-54\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-54\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_72\">\r\n     <g id=\"text_72\">\r\n      <!-- 28 -->\r\n      <g transform=\"translate(279.645312 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-50\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-56\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_73\">\r\n     <g id=\"text_73\">\r\n      <!-- 27 -->\r\n      <g transform=\"translate(283.027131 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-50\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-55\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_74\">\r\n     <g id=\"text_74\">\r\n      <!-- 90 -->\r\n      <g transform=\"translate(286.408949 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_75\">\r\n     <g id=\"text_75\">\r\n      <!-- 80 -->\r\n      <g transform=\"translate(289.790767 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-56\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_76\">\r\n     <g id=\"text_76\">\r\n      <!-- 93 -->\r\n      <g transform=\"translate(293.172585 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-51\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_77\">\r\n     <g id=\"text_77\">\r\n      <!-- 78 -->\r\n      <g transform=\"translate(296.554403 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-55\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-56\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_78\">\r\n     <g id=\"text_78\">\r\n      <!-- 96 -->\r\n      <g transform=\"translate(299.936222 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-54\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_79\">\r\n     <g id=\"text_79\">\r\n      <!-- 77 -->\r\n      <g transform=\"translate(303.31804 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-55\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-55\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_80\">\r\n     <g id=\"text_80\">\r\n      <!-- 82 -->\r\n      <g transform=\"translate(306.699858 253.120625)rotate(-90)scale(0.05 -0.05)\">\r\n       <use xlink:href=\"#DejaVuSans-56\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-50\"/>\r\n      </g>\r\n     </g>\r\n    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      "text/plain": "<Figure size 432x288 with 1 Axes>"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "methode='complete'; distanz='cosine'\n",
    "model = AgglomerativeClustering(n_clusters=None, affinity=distanz, linkage=methode, distance_threshold=0)\n",
    "model = model.fit(dfp)\n",
    "\n",
    "#Dendrogram\n",
    "plt.figure()\n",
    "plt.title('Hierarchical Clustering Dendrogram '+ '(' + methode + '-' + distanz + ')')\n",
    "plot_dendrogram(model, truncate_mode='level', p=10)\n",
    "plt.xlabel(\"Index of point in node (or Number of points in parenthesis).\")\n",
    "    \n",
    "#Agglomerationstabelle\n",
    "plt.figure()\n",
    "plt.title('Agglomerationstabelle ' + '(' + methode + '-' + distanz + ')')\n",
    "plt.plot(model.distances_, \"ob\")\n",
    "plt.xlabel('Cluster')\n",
    "plt.ylabel('Distanz')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": "<Figure size 432x288 with 1 Axes>"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "clusterZahl=7\n",
    "model = AgglomerativeClustering(n_clusters=clusterZahl,  affinity=distanz, linkage=methode, distance_threshold=None)\n",
    "cluster = model.fit_predict(dfp)\n",
    "dfp['Cluster'] = pd.Series(cluster, index=dfp.index)\n",
    "\n",
    "dfm = pd.merge(dfp, df.loc[:,['Stadtteil']], on='id')\n",
    "dfm.to_csv(r\"D:\\ML\\work\\pca_StadtteilprofileBerichtsjahr2018_5.csv\", sep=';', na_rep='NaN', index=True)\n",
    "\n",
    "dfSeries = pd.DataFrame()\n",
    "for i in range(model.n_clusters_):\n",
    "    dfm_plot = dfm.loc[dfp['Cluster'] == i]\n",
    "    dfm_plot = dfm_plot.loc[:,dfm.columns.difference(['Cluster','Stadtteil'])]\n",
    "    s = dfm_plot.median().round(3)\n",
    "    s.name = 'Cluster ' + str(i)\n",
    "    s.plot.line()\n",
    "    dfSeries = dfSeries.append(s)\n",
    "\n",
    "filePath = \"D:/ML/work/\" + methode + \"_\" + distanz + \"_\" + str(clusterZahl) + \".csv\"\n",
    "dfSeries.to_csv(filePath, sep=';', na_rep='NaN', index=True)\n",
    " \n",
    "plt.title('Cluster Median')\n",
    "plt.xlabel('Variablen')\n",
    "plt.ylabel('Value normiert (0-1)')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}