0104_Discretisation_Quantiles_Binning.ipynb

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    "%load_ext nb_black"
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   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "\n",
       "            setTimeout(function() {\n",
       "                var nbb_cell_id = 4;\n",
       "                var nbb_unformatted_code = \"import random\\nimport pandas as pd\\nimport numpy as np\\nfrom scipy import stats\\nimport matplotlib.pyplot as plt\\nfrom sklearn.preprocessing import QuantileTransformer\\nfrom IPython.display import Image\\n\\nplt.style.use(\\\"fivethirtyeight\\\")\";\n",
       "                var nbb_formatted_code = \"import random\\nimport pandas as pd\\nimport numpy as np\\nfrom scipy import stats\\nimport matplotlib.pyplot as plt\\nfrom sklearn.preprocessing import QuantileTransformer\\nfrom IPython.display import Image\\n\\nplt.style.use(\\\"fivethirtyeight\\\")\";\n",
       "                var nbb_cells = Jupyter.notebook.get_cells();\n",
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   "source": [
    "import random\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.preprocessing import QuantileTransformer\n",
    "from IPython.display import Image\n",
    "\n",
    "plt.style.use(\"fivethirtyeight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "                var nbb_cell_id = 5;\n",
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    "plt.rcParams[\"figure.figsize\"] = (12, 4)\n",
    "plt.rcParams.update({\"font.size\": 14})\n",
    "pd.set_option(\"display.precision\", 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 6,
     "metadata": {
      "image/png": {
       "width": 400
      }
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "            setTimeout(function() {\n",
       "                var nbb_cell_id = 6;\n",
       "                var nbb_unformatted_code = \"Image(\\\"images/quantiles.png\\\", width=400)\";\n",
       "                var nbb_formatted_code = \"Image(\\\"images/quantiles.png\\\", width=400)\";\n",
       "                var nbb_cells = Jupyter.notebook.get_cells();\n",
       "                for (var i = 0; i < nbb_cells.length; ++i) {\n",
       "                    if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n",
       "                        if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n",
       "                             nbb_cells[i].set_text(nbb_formatted_code);\n",
       "                        }\n",
       "                        break;\n",
       "                    }\n",
       "                }\n",
       "            }, 500);\n",
       "            "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Image(\"images/quantiles.png\", width=400)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"https://en.wikipedia.org/wiki/Probability_density_function#/media/File:Boxplot_vs_PDF.svg\">Quantiles Wikipedia</a>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div id=00b01b5a-cce4-4795-893c-7ba8313ee4c8 style=\"display:none; background-color:#9D6CFF; color:white; width:200px; height:30px; padding-left:5px; border-radius:4px; flex-direction:row; justify-content:space-around; align-items:center;\" onmouseover=\"this.style.backgroundColor='#BA9BF8'\" onmouseout=\"this.style.backgroundColor='#9D6CFF'\" onclick=\"window.commands?.execute('create-mitosheet-from-dataframe-output');\">See Full Dataframe in Mito</div> <script> if (window.commands?.hasCommand('create-mitosheet-from-dataframe-output')) document.getElementById('00b01b5a-cce4-4795-893c-7ba8313ee4c8').style.display = 'flex' </script> <table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>sensor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>t_0</td>\n",
       "      <td>48.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>t_1</td>\n",
       "      <td>50.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>t_2</td>\n",
       "      <td>57.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>t_3</td>\n",
       "      <td>43.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>t_4</td>\n",
       "      <td>44.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>t_5</td>\n",
       "      <td>32.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>t_6</td>\n",
       "      <td>52.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>t_7</td>\n",
       "      <td>71.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>t_8</td>\n",
       "      <td>33.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>t_9</td>\n",
       "      <td>48.18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table></div>"
      ],
      "text/plain": [
       "  timestamp  sensor\n",
       "0       t_0   48.07\n",
       "1       t_1   50.02\n",
       "2       t_2   57.68\n",
       "3       t_3   43.51\n",
       "4       t_4   44.51\n",
       "5       t_5   32.90\n",
       "6       t_6   52.96\n",
       "7       t_7   71.52\n",
       "8       t_8   33.50\n",
       "9       t_9   48.18"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "            setTimeout(function() {\n",
       "                var nbb_cell_id = 7;\n",
       "                var nbb_unformatted_code = \"sensor = np.random.normal(50, 10, 10000)\\ntimestamp = [\\\"t_\\\" + str(i) for i in range(len(sensor))]\\ndf = pd.DataFrame({\\\"timestamp\\\": timestamp, \\\"sensor\\\": sensor})\\ndf.head(10)\";\n",
       "                var nbb_formatted_code = \"sensor = np.random.normal(50, 10, 10000)\\ntimestamp = [\\\"t_\\\" + str(i) for i in range(len(sensor))]\\ndf = pd.DataFrame({\\\"timestamp\\\": timestamp, \\\"sensor\\\": sensor})\\ndf.head(10)\";\n",
       "                var nbb_cells = Jupyter.notebook.get_cells();\n",
       "                for (var i = 0; i < nbb_cells.length; ++i) {\n",
       "                    if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n",
       "                        if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n",
       "                             nbb_cells[i].set_text(nbb_formatted_code);\n",
       "                        }\n",
       "                        break;\n",
       "                    }\n",
       "                }\n",
       "            }, 500);\n",
       "            "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sensor = np.random.normal(50, 10, 10000)\n",
    "timestamp = [\"t_\" + str(i) for i in range(len(sensor))]\n",
    "df = pd.DataFrame({\"timestamp\": timestamp, \"sensor\": sensor})\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "            setTimeout(function() {\n",
       "                var nbb_cell_id = 8;\n",
       "                var nbb_unformatted_code = \"plt.figure(figsize=(12, 4))\\nplt.subplot(1, 2, 1)\\nplt.plot(df[\\\"sensor\\\"], \\\"o\\\")\\nplt.xlabel(\\\"timestamp\\\")\\nplt.ylabel(\\\"Sensor Value\\\")\\nplt.subplot(1, 2, 2)\\nplt.hist(df[\\\"sensor\\\"].values, bins=50, edgecolor=\\\"black\\\")\\nplt.xlabel(\\\"Sensor Value\\\")\\nplt.ylabel(\\\"Histogram (Count)\\\")\\nplt.show()\";\n",
       "                var nbb_formatted_code = \"plt.figure(figsize=(12, 4))\\nplt.subplot(1, 2, 1)\\nplt.plot(df[\\\"sensor\\\"], \\\"o\\\")\\nplt.xlabel(\\\"timestamp\\\")\\nplt.ylabel(\\\"Sensor Value\\\")\\nplt.subplot(1, 2, 2)\\nplt.hist(df[\\\"sensor\\\"].values, bins=50, edgecolor=\\\"black\\\")\\nplt.xlabel(\\\"Sensor Value\\\")\\nplt.ylabel(\\\"Histogram (Count)\\\")\\nplt.show()\";\n",
       "                var nbb_cells = Jupyter.notebook.get_cells();\n",
       "                for (var i = 0; i < nbb_cells.length; ++i) {\n",
       "                    if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n",
       "                        if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n",
       "                             nbb_cells[i].set_text(nbb_formatted_code);\n",
       "                        }\n",
       "                        break;\n",
       "                    }\n",
       "                }\n",
       "            }, 500);\n",
       "            "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 4))\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.plot(df[\"sensor\"], \"o\")\n",
    "plt.xlabel(\"timestamp\")\n",
    "plt.ylabel(\"Sensor Value\")\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.hist(df[\"sensor\"].values, bins=50, edgecolor=\"black\")\n",
    "plt.xlabel(\"Sensor Value\")\n",
    "plt.ylabel(\"Histogram (Count)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median is  49.92\n",
      "0.00    15.18\n",
      "0.25    43.11\n",
      "0.50    49.92\n",
      "0.75    56.74\n",
      "1.00    91.95\n",
      "Name: sensor, dtype: float64\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "            setTimeout(function() {\n",
       "                var nbb_cell_id = 12;\n",
       "                var nbb_unformatted_code = \"print(\\\"Median is \\\", round(df[\\\"sensor\\\"].median(), 2))\\n\\nquantile_list = [0, 0.25, 0.5, 0.75, 1.0]\\nquantiles = df[\\\"sensor\\\"].quantile(quantile_list)\\n\\ndf[\\\"sensor_quantile\\\"] = pd.qcut(\\n    df[\\\"sensor\\\"], quantile_list, labels=[\\\"1st\\\", \\\"2nd\\\", \\\"3rd\\\", \\\"4th\\\"]\\n)\\nprint(quantiles)\";\n",
       "                var nbb_formatted_code = \"print(\\\"Median is \\\", round(df[\\\"sensor\\\"].median(), 2))\\n\\nquantile_list = [0, 0.25, 0.5, 0.75, 1.0]\\nquantiles = df[\\\"sensor\\\"].quantile(quantile_list)\\n\\ndf[\\\"sensor_quantile\\\"] = pd.qcut(\\n    df[\\\"sensor\\\"], quantile_list, labels=[\\\"1st\\\", \\\"2nd\\\", \\\"3rd\\\", \\\"4th\\\"]\\n)\\nprint(quantiles)\";\n",
       "                var nbb_cells = Jupyter.notebook.get_cells();\n",
       "                for (var i = 0; i < nbb_cells.length; ++i) {\n",
       "                    if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n",
       "                        if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n",
       "                             nbb_cells[i].set_text(nbb_formatted_code);\n",
       "                        }\n",
       "                        break;\n",
       "                    }\n",
       "                }\n",
       "            }, 500);\n",
       "            "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Median is \", round(df[\"sensor\"].median(), 2))\n",
    "\n",
    "quantile_list = [0, 0.25, 0.5, 0.75, 1.0]\n",
    "quantiles = df[\"sensor\"].quantile(quantile_list)\n",
    "\n",
    "df[\"sensor_quantile\"] = pd.qcut(\n",
    "    df[\"sensor\"], quantile_list, labels=[\"1st\", \"2nd\", \"3rd\", \"4th\"]\n",
    ")\n",
    "print(quantiles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><div id=bf1f3c22-e40f-4da5-8b6e-d4e2352dff9f style=\"display:none; background-color:#9D6CFF; color:white; width:200px; height:30px; padding-left:5px; border-radius:4px; flex-direction:row; justify-content:space-around; align-items:center;\" onmouseover=\"this.style.backgroundColor='#BA9BF8'\" onmouseout=\"this.style.backgroundColor='#9D6CFF'\" onclick=\"window.commands?.execute('create-mitosheet-from-dataframe-output');\">See Full Dataframe in Mito</div> <script> if (window.commands?.hasCommand('create-mitosheet-from-dataframe-output')) document.getElementById('bf1f3c22-e40f-4da5-8b6e-d4e2352dff9f').style.display = 'flex' </script> <table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timestamp</th>\n",
       "      <th>sensor</th>\n",
       "      <th>sensor_quantile</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>t_0</td>\n",
       "      <td>40.184013</td>\n",
       "      <td>1st</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>t_1</td>\n",
       "      <td>44.059282</td>\n",
       "      <td>2nd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>t_2</td>\n",
       "      <td>57.160237</td>\n",
       "      <td>4th</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>t_3</td>\n",
       "      <td>51.773008</td>\n",
       "      <td>3rd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>t_4</td>\n",
       "      <td>46.436468</td>\n",
       "      <td>2nd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>t_5</td>\n",
       "      <td>58.946407</td>\n",
       "      <td>4th</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>t_6</td>\n",
       "      <td>70.844171</td>\n",
       "      <td>4th</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>t_7</td>\n",
       "      <td>45.881821</td>\n",
       "      <td>2nd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>t_8</td>\n",
       "      <td>38.664042</td>\n",
       "      <td>1st</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>t_9</td>\n",
       "      <td>70.340981</td>\n",
       "      <td>4th</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table></div>"
      ],
      "text/plain": [
       "  timestamp     sensor sensor_quantile\n",
       "0       t_0  40.184013             1st\n",
       "1       t_1  44.059282             2nd\n",
       "2       t_2  57.160237             4th\n",
       "3       t_3  51.773008             3rd\n",
       "4       t_4  46.436468             2nd\n",
       "5       t_5  58.946407             4th\n",
       "6       t_6  70.844171             4th\n",
       "7       t_7  45.881821             2nd\n",
       "8       t_8  38.664042             1st\n",
       "9       t_9  70.340981             4th"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "            setTimeout(function() {\n",
       "                var nbb_cell_id = 42;\n",
       "                var nbb_unformatted_code = \"df.head(10)\";\n",
       "                var nbb_formatted_code = \"df.head(10)\";\n",
       "                var nbb_cells = Jupyter.notebook.get_cells();\n",
       "                for (var i = 0; i < nbb_cells.length; ++i) {\n",
       "                    if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n",
       "                        if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n",
       "                             nbb_cells[i].set_text(nbb_formatted_code);\n",
       "                        }\n",
       "                        break;\n",
       "                    }\n",
       "                }\n",
       "            }, 500);\n",
       "            "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "            setTimeout(function() {\n",
       "                var nbb_cell_id = 46;\n",
       "                var nbb_unformatted_code = \"plt.figure(figsize=(12, 8))\\nplt.subplot(2, 2, 1)\\nplt.hist(df[\\\"sensor\\\"], bins=50, edgecolor=\\\"black\\\")\\nplt.xlabel(\\\"Sensor Value\\\")\\nplt.ylabel(\\\"Histogram\\\")\\nplt.subplot(2, 2, 2)\\nplt.boxplot(df[\\\"sensor\\\"].values)\\n# plt.xlabel(\\\"\\\")\\n# plt.ylabel(\\\"\\\")\\nplt.subplot(2, 2, 3)\\nplt.hist(df[\\\"sensor\\\"], bins=50, edgecolor=\\\"black\\\")\\nfor quantile in quantiles:\\n    plt.axvline(quantile, color=\\\"r\\\")\\nplt.subplot(2, 2, 4)\\ndf[\\\"sensor_quantile\\\"].value_counts().plot(kind=\\\"bar\\\", rot=0, edgecolor=\\\"black\\\")\\nplt.xlabel(\\\"Quantile\\\")\\nplt.ylabel(\\\"Number of Values\\\")\\nplt.tight_layout()\";\n",
       "                var nbb_formatted_code = \"plt.figure(figsize=(12, 8))\\nplt.subplot(2, 2, 1)\\nplt.hist(df[\\\"sensor\\\"], bins=50, edgecolor=\\\"black\\\")\\nplt.xlabel(\\\"Sensor Value\\\")\\nplt.ylabel(\\\"Histogram\\\")\\nplt.subplot(2, 2, 2)\\nplt.boxplot(df[\\\"sensor\\\"].values)\\n# plt.xlabel(\\\"\\\")\\n# plt.ylabel(\\\"\\\")\\nplt.subplot(2, 2, 3)\\nplt.hist(df[\\\"sensor\\\"], bins=50, edgecolor=\\\"black\\\")\\nfor quantile in quantiles:\\n    plt.axvline(quantile, color=\\\"r\\\")\\nplt.subplot(2, 2, 4)\\ndf[\\\"sensor_quantile\\\"].value_counts().plot(kind=\\\"bar\\\", rot=0, edgecolor=\\\"black\\\")\\nplt.xlabel(\\\"Quantile\\\")\\nplt.ylabel(\\\"Number of Values\\\")\\nplt.tight_layout()\";\n",
       "                var nbb_cells = Jupyter.notebook.get_cells();\n",
       "                for (var i = 0; i < nbb_cells.length; ++i) {\n",
       "                    if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n",
       "                        if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n",
       "                             nbb_cells[i].set_text(nbb_formatted_code);\n",
       "                        }\n",
       "                        break;\n",
       "                    }\n",
       "                }\n",
       "            }, 500);\n",
       "            "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 8))\n",
    "plt.subplot(2, 2, 1)\n",
    "plt.hist(df[\"sensor\"], bins=50, edgecolor=\"black\")\n",
    "plt.xlabel(\"Sensor Value\")\n",
    "plt.ylabel(\"Histogram\")\n",
    "plt.subplot(2, 2, 2)\n",
    "plt.boxplot(df[\"sensor\"].values)\n",
    "# plt.xlabel(\"\")\n",
    "# plt.ylabel(\"\")\n",
    "plt.subplot(2, 2, 3)\n",
    "plt.hist(df[\"sensor\"], bins=50, edgecolor=\"black\")\n",
    "for quantile in quantiles:\n",
    "    plt.axvline(quantile, color=\"r\")\n",
    "plt.subplot(2, 2, 4)\n",
    "df[\"sensor_quantile\"].value_counts().plot(kind=\"bar\", rot=0, edgecolor=\"black\")\n",
    "plt.xlabel(\"Quantile\")\n",
    "plt.ylabel(\"Number of Values\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0    15.18\n",
      "0.2    41.58\n",
      "0.4    47.43\n",
      "0.6    52.43\n",
      "0.8    58.38\n",
      "1.0    91.95\n",
      "Name: sensor, dtype: float64\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "            setTimeout(function() {\n",
       "                var nbb_cell_id = 14;\n",
       "                var nbb_unformatted_code = \"quantile_list = [0, 0.2, 0.4, 0.6, 0.8, 1.0]\\nquantiles = df[\\\"sensor\\\"].quantile(quantile_list)\\n\\ndf[\\\"sensor_quantile\\\"] = pd.qcut(\\n    df[\\\"sensor\\\"], quantile_list, labels=[\\\"1st\\\", \\\"2nd\\\", \\\"3rd\\\", \\\"4th\\\", \\\"5th\\\"]\\n)\\n\\nprint(quantiles)\";\n",
       "                var nbb_formatted_code = \"quantile_list = [0, 0.2, 0.4, 0.6, 0.8, 1.0]\\nquantiles = df[\\\"sensor\\\"].quantile(quantile_list)\\n\\ndf[\\\"sensor_quantile\\\"] = pd.qcut(\\n    df[\\\"sensor\\\"], quantile_list, labels=[\\\"1st\\\", \\\"2nd\\\", \\\"3rd\\\", \\\"4th\\\", \\\"5th\\\"]\\n)\\n\\nprint(quantiles)\";\n",
       "                var nbb_cells = Jupyter.notebook.get_cells();\n",
       "                for (var i = 0; i < nbb_cells.length; ++i) {\n",
       "                    if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n",
       "                        if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n",
       "                             nbb_cells[i].set_text(nbb_formatted_code);\n",
       "                        }\n",
       "                        break;\n",
       "                    }\n",
       "                }\n",
       "            }, 500);\n",
       "            "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "quantile_list = [0, 0.2, 0.4, 0.6, 0.8, 1.0]\n",
    "quantiles = df[\"sensor\"].quantile(quantile_list)\n",
    "\n",
    "df[\"sensor_quantile\"] = pd.qcut(\n",
    "    df[\"sensor\"], quantile_list, labels=[\"1st\", \"2nd\", \"3rd\", \"4th\", \"5th\"]\n",
    ")\n",
    "\n",
    "print(quantiles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "            setTimeout(function() {\n",
       "                var nbb_cell_id = 15;\n",
       "                var nbb_unformatted_code = \"plt.figure(figsize=(12, 8))\\nplt.subplot(2, 2, 1)\\nplt.hist(df[\\\"sensor\\\"], bins=50, edgecolor=\\\"black\\\")\\nplt.xlabel(\\\"Sensor Value\\\")\\nplt.ylabel(\\\"Histogram\\\")\\nplt.subplot(2, 2, 2)\\nplt.boxplot(df[\\\"sensor\\\"].values)\\n# plt.xlabel(\\\"\\\")\\n# plt.ylabel(\\\"\\\")\\nplt.subplot(2, 2, 3)\\nplt.hist(df[\\\"sensor\\\"], bins=50, edgecolor=\\\"black\\\")\\nfor quantile in quantiles:\\n    plt.axvline(quantile, color=\\\"r\\\")\\nplt.subplot(2, 2, 4)\\ndf[\\\"sensor_quantile\\\"].value_counts().plot(kind=\\\"bar\\\", rot=0, edgecolor=\\\"black\\\")\\nplt.xlabel(\\\"Quantile\\\")\\nplt.ylabel(\\\"Number of Values\\\")\\nplt.tight_layout()\";\n",
       "                var nbb_formatted_code = \"plt.figure(figsize=(12, 8))\\nplt.subplot(2, 2, 1)\\nplt.hist(df[\\\"sensor\\\"], bins=50, edgecolor=\\\"black\\\")\\nplt.xlabel(\\\"Sensor Value\\\")\\nplt.ylabel(\\\"Histogram\\\")\\nplt.subplot(2, 2, 2)\\nplt.boxplot(df[\\\"sensor\\\"].values)\\n# plt.xlabel(\\\"\\\")\\n# plt.ylabel(\\\"\\\")\\nplt.subplot(2, 2, 3)\\nplt.hist(df[\\\"sensor\\\"], bins=50, edgecolor=\\\"black\\\")\\nfor quantile in quantiles:\\n    plt.axvline(quantile, color=\\\"r\\\")\\nplt.subplot(2, 2, 4)\\ndf[\\\"sensor_quantile\\\"].value_counts().plot(kind=\\\"bar\\\", rot=0, edgecolor=\\\"black\\\")\\nplt.xlabel(\\\"Quantile\\\")\\nplt.ylabel(\\\"Number of Values\\\")\\nplt.tight_layout()\";\n",
       "                var nbb_cells = Jupyter.notebook.get_cells();\n",
       "                for (var i = 0; i < nbb_cells.length; ++i) {\n",
       "                    if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n",
       "                        if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n",
       "                             nbb_cells[i].set_text(nbb_formatted_code);\n",
       "                        }\n",
       "                        break;\n",
       "                    }\n",
       "                }\n",
       "            }, 500);\n",
       "            "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 8))\n",
    "plt.subplot(2, 2, 1)\n",
    "plt.hist(df[\"sensor\"], bins=50, edgecolor=\"black\")\n",
    "plt.xlabel(\"Sensor Value\")\n",
    "plt.ylabel(\"Histogram\")\n",
    "plt.subplot(2, 2, 2)\n",
    "plt.boxplot(df[\"sensor\"].values)\n",
    "# plt.xlabel(\"\")\n",
    "# plt.ylabel(\"\")\n",
    "plt.subplot(2, 2, 3)\n",
    "plt.hist(df[\"sensor\"], bins=50, edgecolor=\"black\")\n",
    "for quantile in quantiles:\n",
    "    plt.axvline(quantile, color=\"r\")\n",
    "plt.subplot(2, 2, 4)\n",
    "df[\"sensor_quantile\"].value_counts().plot(kind=\"bar\", rot=0, edgecolor=\"black\")\n",
    "plt.xlabel(\"Quantile\")\n",
    "plt.ylabel(\"Number of Values\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "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": "3.8.13"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}