Data Mining - Unsupervised Learning.ipynb

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   "cell_type": "code",
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   "id": "2e5f7e29",
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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.cluster import KMeans\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as plticker\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "798882ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_1 = pd.read_csv('Datasets/transformation_result_1_year_SD.csv')\n",
    "df_2 = pd.read_csv('Datasets/transformation_result_2_year_SD.csv')\n",
    "df_3 = pd.read_csv('Datasets/transformation_result_3_year_SD.csv')\n",
    "df_4 = pd.read_csv('Datasets/transformation_result_4_year_SD.csv')\n",
    "df_5 = pd.read_csv('Datasets/transformation_result_5_year_SD.csv')\n",
    "df = pd.read_csv('Datasets/transformation_result_SD.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c631c40a",
   "metadata": {},
   "source": [
    "## 1.0 Uso do Kmeans para cada Base de dados, com preços após 1, 2, 3, 4 e 5 anos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "760067f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "km_1 = KMeans(n_clusters=3)\n",
    "km_2 = KMeans(n_clusters=3)\n",
    "km_3 = KMeans(n_clusters=3)\n",
    "km_4 = KMeans(n_clusters=3)\n",
    "km_5 = KMeans(n_clusters=3)\n",
    "km = KMeans(n_clusters=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a9b412bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "open_dif_1 = df_1['Open_dif']\n",
    "df_1.drop('Open_dif', axis=1, inplace=True)\n",
    "\n",
    "open_dif_2 = df_2['Open_dif']\n",
    "df_2.drop('Open_dif', axis=1, inplace=True)\n",
    "\n",
    "open_dif_3 = df_3['Open_dif']\n",
    "df_3.drop('Open_dif', axis=1, inplace=True)\n",
    "\n",
    "open_dif_4 = df_4['Open_dif']\n",
    "df_4.drop('Open_dif', axis=1, inplace=True)\n",
    "\n",
    "open_dif_5 = df_5['Open_dif']\n",
    "df_5.drop('Open_dif', axis=1, inplace=True)\n",
    "\n",
    "open_dif = df['Open_dif']\n",
    "df.drop('Open_dif', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b797c99d",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_1 = km_1.fit_predict(df_1)\n",
    "y_2 = km_2.fit_predict(df_2)\n",
    "y_3 = km_3.fit_predict(df_3)\n",
    "y_4 = km_4.fit_predict(df_4)\n",
    "y_5 = km_5.fit_predict(df_5)\n",
    "y = km.fit_predict(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3d429387",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_1['Open_dif'] = open_dif_1\n",
    "df_2['Open_dif'] = open_dif_2\n",
    "df_3['Open_dif'] = open_dif_3\n",
    "df_4['Open_dif'] = open_dif_4\n",
    "df_5['Open_dif'] = open_dif_5\n",
    "df  ['Open_dif'] = y"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b394f396",
   "metadata": {},
   "source": [
    "## 2.0 Registro da distribuição de cada cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e7219562",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 ano: cluster 1:4119 / Cluster 2:418 / Cluster 3:356\n",
      "\n",
      "2 anos: cluster 1:3097 / Cluster 2:396 / Cluster 3:225\n",
      "\n",
      "3 anos: cluster 1:2303 / Cluster 2:383 / Cluster 3:115\n",
      "\n",
      "4 anos: cluster 1:1898 / Cluster 2:357 / Cluster 3:98\n",
      "\n",
      "5 anos: cluster 1:1531 / Cluster 2:308 / Cluster 3:75\n",
      "\n",
      "X anos: cluster 1:52602 / Cluster 2:8512 / Cluster 3:2635\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"1 ano: cluster 1:{} / Cluster 2:{} / Cluster 3:{}\\n\".format(len(df_1[y_1 == 0]), len(df_1[y_1 == 1]), len(df_1[y_1 == 2])))\n",
    "print(\"2 anos: cluster 1:{} / Cluster 2:{} / Cluster 3:{}\\n\".format(len(df_2[y_2 == 0]), len(df_2[y_2 == 1]), len(df_2[y_2 == 2])))\n",
    "print(\"3 anos: cluster 1:{} / Cluster 2:{} / Cluster 3:{}\\n\".format(len(df_3[y_3 == 0]), len(df_3[y_3 == 1]), len(df_3[y_3 == 2])))\n",
    "print(\"4 anos: cluster 1:{} / Cluster 2:{} / Cluster 3:{}\\n\".format(len(df_4[y_4 == 0]), len(df_4[y_4 == 1]), len(df_4[y_4 == 2])))\n",
    "print(\"5 anos: cluster 1:{} / Cluster 2:{} / Cluster 3:{}\\n\".format(len(df_5[y_5 == 0]), len(df_5[y_5 == 1]), len(df_5[y_5 == 2])))\n",
    "\n",
    "print(\"X anos: cluster 1:{} / Cluster 2:{} / Cluster 3:{}\\n\".format(len(df[y == 0]), len(df[y == 1]), len(df[y == 2])))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1cbf783",
   "metadata": {},
   "source": [
    "## 3.0. Criação de gráficos de dispersão\n",
    "Para cada Base de dados e cada combinação de x = Preço e Y = Parâmetro, é criado um gráfico de dispersão com separação idenficado pelos cluters e destacados com cores diferentes."
   ]
  },
  {
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   "execution_count": 8,
   "id": "4dce1bcf",
   "metadata": {},
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   "source": [
    "current_directory_path = os.getcwd()"
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   "source": [
    "counter = 1\n",
    "\n",
    "for col in df_1.drop('Open_dif', axis=1).columns:\n",
    "    \n",
    "    #-----------------------------------------------------------------------------------------------------------------------\n",
    "    #plots individuais\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    loc = plticker.MultipleLocator(base=1.0)\n",
    "    ax = plt.axes()\n",
    "    ax.xaxis.set_major_locator(loc)\n",
    "    \n",
    "    plt.scatter(\n",
    "        df_1['Open_dif'][y_1 == 0], df_1[col][y_1 == 0],\n",
    "        s=50, c='lightgreen',\n",
    "        marker='s', edgecolor='black',\n",
    "        label='cluster 1',\n",
    "        alpha=0.5\n",
    "    )\n",
    "\n",
    "    plt.scatter(\n",
    "        df_1['Open_dif'][y_1 == 1], df_1[col][y_1 == 1],\n",
    "        s=50, c='orange',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 2',\n",
    "        alpha=0.5\n",
    "    )\n",
    "\n",
    "    plt.scatter(\n",
    "        df_1['Open_dif'][y_1 == 2], df_1[col][y_1 == 2],\n",
    "        s=50, c='blue',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 3',\n",
    "        alpha=0.5\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\1_year_plt_{}.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "#   --------------------------------------------------------------------------------------------------------------------\n",
    "#     plots mesclados\n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    loc = plticker.MultipleLocator(base=1.0)\n",
    "    ax = plt.axes()\n",
    "    ax.xaxis.set_major_locator(loc)\n",
    "    \n",
    "    plt.scatter(\n",
    "        df_1['Open_dif'][y_1 == 0], df_1[col][y_1 == 0],\n",
    "        s=50, c='lightgreen',\n",
    "        marker='s', edgecolor='black',\n",
    "        label='cluster 1'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_1\\\\1_year_plt_{}_cluster_1.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    loc = plticker.MultipleLocator(base=1.0)\n",
    "    ax = plt.axes()\n",
    "    ax.xaxis.set_major_locator(loc)\n",
    "\n",
    "    plt.scatter(\n",
    "        df_1['Open_dif'][y_1 == 1], df_1[col][y_1 == 1],\n",
    "        s=50, c='orange',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 2'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_2\\\\1_year_plt_{}_cluster_2.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    loc = plticker.MultipleLocator(base=1.0)\n",
    "    ax = plt.axes()\n",
    "    ax.xaxis.set_major_locator(loc)\n",
    "\n",
    "    plt.scatter(\n",
    "        df_1['Open_dif'][y_1 == 2], df_1[col][y_1 == 2],\n",
    "        s=50, c='blue',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 3'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_3\\\\1_year_plt_{}_cluster_3.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    counter += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5821c12d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\panto\\AppData\\Local\\Temp/ipykernel_12632/4015674699.py:8: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
      "  plt.figure(figsize=(20, 20), dpi=80)\n"
     ]
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   ],
   "source": [
    "counter = 1\n",
    "\n",
    "for col in df_2.drop('Open_dif', axis=1).columns:\n",
    "    \n",
    "    #-----------------------------------------------------------------------------------------------------------------------\n",
    "    #plots individuais\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    loc = plticker.MultipleLocator(base=1.0)\n",
    "    ax = plt.axes()\n",
    "    ax.xaxis.set_major_locator(loc)\n",
    "    \n",
    "    plt.scatter(\n",
    "        df_2['Open_dif'][y_2 == 0], df_2[col][y_2 == 0],\n",
    "        s=50, c='lightgreen',\n",
    "        marker='s', edgecolor='black',\n",
    "        label='cluster 1',\n",
    "        alpha=0.5\n",
    "    )\n",
    "\n",
    "    plt.scatter(\n",
    "        df_2['Open_dif'][y_2 == 1], df_2[col][y_2 == 1],\n",
    "        s=50, c='orange',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 2',\n",
    "        alpha=0.5\n",
    "    )\n",
    "\n",
    "    plt.scatter(\n",
    "        df_2['Open_dif'][y_2 == 2], df_2[col][y_2 == 2],\n",
    "        s=50, c='blue',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 3',\n",
    "        alpha=0.5\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\2_year_plt_{}.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    counter += 1\n",
    "    \n",
    "#   --------------------------------------------------------------------------------------------------------------------\n",
    "#     plots mesclados\n",
    "\n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    loc = plticker.MultipleLocator(base=1.0)\n",
    "    ax = plt.axes()\n",
    "    ax.xaxis.set_major_locator(loc)\n",
    "    \n",
    "    plt.scatter(\n",
    "        df_2['Open_dif'][y_2 == 0], df_2[col][y_2 == 0],\n",
    "        s=50, c='lightgreen',\n",
    "        marker='s', edgecolor='black',\n",
    "        label='cluster 1'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_1\\\\2_year_plt_{}_cluster_1.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "\n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    loc = plticker.MultipleLocator(base=1.0)\n",
    "    ax = plt.axes()\n",
    "    ax.xaxis.set_major_locator(loc)\n",
    "\n",
    "    plt.scatter(\n",
    "        df_2['Open_dif'][y_2 == 1], df_2[col][y_2 == 1],\n",
    "        s=50, c='orange',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 2'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_2\\\\2_year_plt_{}_clustes_2.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "\n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    loc = plticker.MultipleLocator(base=1.0)\n",
    "    ax = plt.axes()\n",
    "    ax.xaxis.set_major_locator(loc)\n",
    "\n",
    "    plt.scatter(\n",
    "        df_2['Open_dif'][y_2 == 2], df_2[col][y_2 == 2],\n",
    "        s=50, c='blue',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 3'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_3\\\\2_year_plt_{}_cluster_3.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    counter += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b1aa3d1e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\panto\\AppData\\Local\\Temp/ipykernel_12632/3764644688.py:8: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
      "  plt.figure(figsize=(20, 20), dpi=80)\n"
     ]
    },
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    {
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    {
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    {
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   ],
   "source": [
    "counter = 1\n",
    "\n",
    "for col in df_3.drop('Open_dif', axis=1).columns:\n",
    "    \n",
    "    #-----------------------------------------------------------------------------------------------------------------------\n",
    "    #plots individuais\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    loc = plticker.MultipleLocator(base=1.0)\n",
    "    ax = plt.axes()\n",
    "    ax.xaxis.set_major_locator(loc)\n",
    "    \n",
    "    plt.scatter(\n",
    "        df_3['Open_dif'][y_3 == 0], df_3[col][y_3 == 0],\n",
    "        s=50, c='lightgreen',\n",
    "        marker='s', edgecolor='black',\n",
    "        label='cluster 1',\n",
    "        alpha=0.5\n",
    "    )\n",
    "\n",
    "    plt.scatter(\n",
    "        df_3['Open_dif'][y_3 == 1], df_3[col][y_3 == 1],\n",
    "        s=50, c='orange',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 2',\n",
    "        alpha=0.5\n",
    "    )\n",
    "\n",
    "    plt.scatter(\n",
    "        df_3['Open_dif'][y_3 == 2], df_3[col][y_3 == 2],\n",
    "        s=50, c='blue',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 3',\n",
    "        alpha=0.5\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\3_year_plt_{}.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "#   --------------------------------------------------------------------------------------------------------------------\n",
    "#     plots mesclados\n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    loc = plticker.MultipleLocator(base=1.0)\n",
    "    ax = plt.axes()\n",
    "    ax.xaxis.set_major_locator(loc)\n",
    "    \n",
    "    plt.scatter(\n",
    "        df_3['Open_dif'][y_3 == 0], df_3[col][y_3 == 0],\n",
    "        s=50, c='lightgreen',\n",
    "        marker='s', edgecolor='black',\n",
    "        label='cluster 1'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_1\\\\3_year_plt_{}_cluster_1.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    loc = plticker.MultipleLocator(base=1.0)\n",
    "    ax = plt.axes()\n",
    "    ax.xaxis.set_major_locator(loc)\n",
    "\n",
    "    plt.scatter(\n",
    "        df_3['Open_dif'][y_3 == 1], df_3[col][y_3 == 1],\n",
    "        s=50, c='orange',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 2'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_2\\\\3_year_plt_{}_cluster_2.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    loc = plticker.MultipleLocator(base=1.0)\n",
    "    ax = plt.axes()\n",
    "    ax.xaxis.set_major_locator(loc)\n",
    "\n",
    "    plt.scatter(\n",
    "        df_3['Open_dif'][y_3 == 2], df_3[col][y_3 == 2],\n",
    "        s=50, c='blue',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 3'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_3\\\\3_year_plt_{}_cluster_3.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    counter += 1"
   ]
  },
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   "id": "05deffd9",
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    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x1600 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x1600 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x1600 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x1600 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x1600 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x1600 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x1600 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x1600 with 0 Axes>"
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     },
     "metadata": {},
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   ],
   "source": [
    "counter = 1\n",
    "\n",
    "for col in df_4.drop('Open_dif', axis=1).columns:\n",
    "    \n",
    "    #-----------------------------------------------------------------------------------------------------------------------\n",
    "    #plots individuais\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    plt.scatter(\n",
    "        df_4['Open_dif'][y_4 == 0], df_4[col][y_4 == 0],\n",
    "        s=50, c='lightgreen',\n",
    "        marker='s', edgecolor='black',\n",
    "        label='cluster 1',\n",
    "        alpha=0.5\n",
    "    )\n",
    "\n",
    "    plt.scatter(\n",
    "        df_4['Open_dif'][y_4 == 1], df_4[col][y_4 == 1],\n",
    "        s=50, c='orange',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 2',\n",
    "        alpha=0.5\n",
    "    )\n",
    "\n",
    "    plt.scatter(\n",
    "        df_4['Open_dif'][y_4 == 2], df_4[col][y_4 == 2],\n",
    "        s=50, c='blue',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 3',\n",
    "        alpha=0.5\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\4_year_plt_{}.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "#   --------------------------------------------------------------------------------------------------------------------\n",
    "#     plots mesclados\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    plt.scatter(\n",
    "        df_4['Open_dif'][y_4 == 0], df_4[col][y_4 == 0],\n",
    "        s=50, c='lightgreen',\n",
    "        marker='s', edgecolor='black',\n",
    "        label='cluster 1'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_1\\\\4_year_plt_{}_cluster_1.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "\n",
    "    plt.scatter(\n",
    "        df_4['Open_dif'][y_4 == 1], df_4[col][y_4 == 1],\n",
    "        s=50, c='orange',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 2'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_2\\\\4_year_plt_{}_cluster_2.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "\n",
    "    plt.scatter(\n",
    "        df_4['Open_dif'][y_4 == 2], df_4[col][y_4 == 2],\n",
    "        s=50, c='blue',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 3'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_3\\\\4_year_plt_{}_cluster_3.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    counter += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "efa8c6ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\panto\\AppData\\Local\\Temp/ipykernel_12632/1636391312.py:8: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
      "  plt.figure(figsize=(20, 20), dpi=80)\n"
     ]
    },
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    {
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       "<Figure size 1600x1600 with 0 Axes>"
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   ],
   "source": [
    "counter = 1\n",
    "\n",
    "for col in df_5.drop('Open_dif', axis=1).columns:\n",
    "    \n",
    "    #-----------------------------------------------------------------------------------------------------------------------\n",
    "    #plots individuais\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    plt.scatter(\n",
    "        df_5['Open_dif'][y_5 == 0], df_5[col][y_5 == 0],\n",
    "        s=50, c='lightgreen',\n",
    "        marker='s', edgecolor='black',\n",
    "        label='cluster 1',\n",
    "        alpha=0.5\n",
    "    )\n",
    "\n",
    "    plt.scatter(\n",
    "        df_5['Open_dif'][y_5 == 1], df_5[col][y_5 == 1],\n",
    "        s=50, c='orange',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 2',\n",
    "        alpha=0.5\n",
    "    )\n",
    "\n",
    "    plt.scatter(\n",
    "        df_5['Open_dif'][y_5 == 2], df_5[col][y_5 == 2],\n",
    "        s=50, c='blue',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 3',\n",
    "        alpha=0.5\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\5_year_plt_{}.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "#   --------------------------------------------------------------------------------------------------------------------\n",
    "#     plots mesclados\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "    plt.scatter(\n",
    "        df_5['Open_dif'][y_5 == 0], df_5[col][y_5 == 0],\n",
    "        s=50, c='lightgreen',\n",
    "        marker='s', edgecolor='black',\n",
    "        label='cluster 1'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_1\\\\5_year_plt_{}_cluster_1.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "\n",
    "    plt.scatter(\n",
    "        df_5['Open_dif'][y_5 == 1], df_5[col][y_5 == 1],\n",
    "        s=50, c='orange',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 2'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_2\\\\5_year_plt_{}_cluster_2.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    plt.figure(figsize=(20, 20), dpi=80)\n",
    "\n",
    "    plt.scatter(\n",
    "        df_5['Open_dif'][y_5 == 2], df_5[col][y_5 == 2],\n",
    "        s=50, c='blue',\n",
    "        marker='o', edgecolor='black',\n",
    "        label='cluster 3'\n",
    "    )\n",
    "    \n",
    "    plt.title(\"{} x Price in a Year\".format(col))\n",
    "    plt.xlabel('Price')\n",
    "    plt.ylabel(col)\n",
    "    plt.legend(scatterpoints=1)\n",
    "    plt.grid()\n",
    "    \n",
    "    file_name = \"Unsurpevised_plots\\\\cluster_3\\\\5_year_plt_{}_cluster_3.jpg\".format(counter)\n",
    "    file_path = os.path.join(current_directory_path, file_name)\n",
    "    plt.savefig(file_path)\n",
    "    plt.clf()\n",
    "    \n",
    "    counter += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8c55e2a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\panto\\AppData\\Local\\Temp/ipykernel_12632/2261176412.py:7: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n",
      "  plt.figure(figsize=(20, 20), dpi=80)\n"
     ]
    },
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   "source": [
    "for i in range(1,6):\n",
    "    counter = 1\n",
    "    for col in df.drop('Open_dif', axis=1).columns:\n",
    "        \n",
    "        #-----------------------------------------------------------------------------------------------------------------------\n",
    "        #plots mesclados\n",
    "        plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "        loc = plticker.MultipleLocator(base=1.0)\n",
    "        ax = plt.axes()\n",
    "        ax.xaxis.set_major_locator(loc)\n",
    "    \n",
    "    \n",
    "        plt.scatter(\n",
    "            df['Open_dif'][(df['years_dif'] == i) & (y == 0)], df[col][(df['years_dif'] == i) & (y == 0)],\n",
    "            s=50, c='lightgreen',\n",
    "            marker='s', edgecolor='black',\n",
    "            label='cluster 1',\n",
    "            alpha=0.5\n",
    "        )\n",
    "\n",
    "        plt.scatter(\n",
    "            df['Open_dif'][(df['years_dif'] == i) & (y == 1)], df[col][(df['years_dif'] == i) & (y == 1)],\n",
    "            s=50, c='orange',\n",
    "            marker='o', edgecolor='black',\n",
    "            label='cluster 2',\n",
    "            alpha=0.5\n",
    "        )\n",
    "\n",
    "        plt.scatter(\n",
    "            df['Open_dif'][(df['years_dif'] == i) & (y == 2)], df[col][(df['years_dif'] == i) & (y == 2)],\n",
    "            s=50, c='blue',\n",
    "            marker='o', edgecolor='black',\n",
    "            label='cluster 3',\n",
    "            alpha=0.5\n",
    "        )\n",
    "\n",
    "        plt.title(\"{} x Price in a Year\".format(col))\n",
    "        plt.xlabel('Price')\n",
    "        plt.ylabel(col)\n",
    "        plt.legend(scatterpoints=1)\n",
    "        plt.grid()\n",
    "\n",
    "        file_name = \"Unsurpevised_plots\\\\merged_datasets\\\\{}_year_plt_{}.jpg\".format(i, counter)\n",
    "        file_path = os.path.join(current_directory_path, file_name)\n",
    "        plt.savefig(file_path)\n",
    "        plt.clf()\n",
    "    \n",
    "#         --------------------------------------------------------------------------------------------------------------------\n",
    "#         plots individuais\n",
    "        plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "        loc = plticker.MultipleLocator(base=1.0)\n",
    "        ax = plt.axes()\n",
    "        ax.xaxis.set_major_locator(loc)\n",
    "    \n",
    "        plt.scatter(\n",
    "            df['Open_dif'][(df['years_dif'] == i) & (y == 0)], df[col][(df['years_dif'] == i) & (y == 0)],\n",
    "            s=50, c='lightgreen',\n",
    "            marker='s', edgecolor='black',\n",
    "            label='cluster 1',\n",
    "            alpha=0.5\n",
    "        )\n",
    "\n",
    "        plt.title(\"{} x Price in a Year\".format(col))\n",
    "        plt.xlabel('Price')\n",
    "        plt.ylabel(col)\n",
    "        plt.legend(scatterpoints=1)\n",
    "        plt.grid()\n",
    "\n",
    "        file_name = \"Unsurpevised_plots\\\\merged_datasets\\\\cluster_1\\\\{}_year_plt_{}_cluester_1.jpg\".format(i, counter)\n",
    "        file_path = os.path.join(current_directory_path, file_name)\n",
    "        plt.savefig(file_path)\n",
    "        plt.clf()\n",
    "        \n",
    "        plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "        loc = plticker.MultipleLocator(base=1.0)\n",
    "        ax = plt.axes()\n",
    "        ax.xaxis.set_major_locator(loc)\n",
    "\n",
    "        plt.scatter(\n",
    "            df['Open_dif'][(df['years_dif'] == i) & (y == 1)], df[col][(df['years_dif'] == i) & (y == 1)],\n",
    "            s=50, c='orange',\n",
    "            marker='o', edgecolor='black',\n",
    "            label='cluster 2',\n",
    "            alpha=0.5\n",
    "        )\n",
    "\n",
    "        plt.title(\"{} x Price in a Year\".format(col))\n",
    "        plt.xlabel('Price')\n",
    "        plt.ylabel(col)\n",
    "        plt.legend(scatterpoints=1)\n",
    "        plt.grid()\n",
    "\n",
    "        file_name = \"Unsurpevised_plots\\\\merged_datasets\\\\cluster_2\\\\{}_year_plt_{}_cluester_2.jpg\".format(i, counter)\n",
    "        file_path = os.path.join(current_directory_path, file_name)\n",
    "        plt.savefig(file_path)\n",
    "        plt.clf()\n",
    "        \n",
    "        plt.figure(figsize=(20, 20), dpi=80)\n",
    "    \n",
    "        loc = plticker.MultipleLocator(base=1.0)\n",
    "        ax = plt.axes()\n",
    "        ax.xaxis.set_major_locator(loc)\n",
    "\n",
    "        plt.scatter(\n",
    "            df['Open_dif'][(df['years_dif'] == i) & (y == 2)], df[col][(df['years_dif'] == i) & (y == 2)],\n",
    "            s=50, c='blue',\n",
    "            marker='o', edgecolor='black',\n",
    "            label='cluster 3',\n",
    "            alpha=0.5\n",
    "        )\n",
    "\n",
    "        plt.title(\"{} x Price in a Year\".format(col))\n",
    "        plt.xlabel('Price')\n",
    "        plt.ylabel(col)\n",
    "        plt.legend(scatterpoints=1)\n",
    "        plt.grid()\n",
    "\n",
    "        file_name = \"Unsurpevised_plots\\\\merged_datasets\\\\cluster_3\\\\{}_year_plt_{}_cluster_3.jpg\".format(i, counter)\n",
    "        file_path = os.path.join(current_directory_path, file_name)\n",
    "        plt.savefig(file_path)\n",
    "        plt.clf()\n",
    "        \n",
    "        counter += 1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d791d19f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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