db_risk0123.ipynb

{
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        "colab_type": "text",
        "id": "view-in-github"
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        "<a href=\"https://colab.research.google.com/github/neurobit-ai/eyeForm/blob/main/db_risk0123.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "id": "NRfo5Uqgi7Dm",
        "outputId": "2d6d03ff-f555-40ff-c58a-b954997707ee"
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              "      Upload widget is only available when the cell has been executed in the\n",
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              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
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              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
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              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
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              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
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              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
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              "\n",
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              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
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              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
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              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
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              "\n",
              "  for (const file of files) {\n",
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              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
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              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
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              "\n",
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              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
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              "\n",
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              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
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        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Saving eyeForm.db.xlsx to eyeForm.db.xlsx\n"
          ]
        }
      ],
      "source": [
        "from google.colab import files\n",
        "assert files.upload()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "v6giYQ0gGOf2",
        "outputId": "fbbe84d4-b823-48a9-fd8a-68c2d6e4469b"
      },
      "outputs": [
        {
          "data": {
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>性別</th>\n",
              "      <th>實歲</th>\n",
              "      <th>右眼軸長</th>\n",
              "      <th>左眼軸長</th>\n",
              "      <th>右眼危險度</th>\n",
              "      <th>左眼危險度</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>男</td>\n",
              "      <td>6歲11月</td>\n",
              "      <td>25.46</td>\n",
              "      <td>25.13</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>男</td>\n",
              "      <td>7歲2月</td>\n",
              "      <td>25.48</td>\n",
              "      <td>25.20</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>男</td>\n",
              "      <td>7歲4月</td>\n",
              "      <td>25.56</td>\n",
              "      <td>25.26</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>女</td>\n",
              "      <td>7歲7月</td>\n",
              "      <td>23.66</td>\n",
              "      <td>23.50</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>女</td>\n",
              "      <td>8歲3月</td>\n",
              "      <td>24.0</td>\n",
              "      <td>23.77</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
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              "    <tr>\n",
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              "    <tr>\n",
              "      <th>3979</th>\n",
              "      <td>女</td>\n",
              "      <td>3歲10個月</td>\n",
              "      <td>21.48</td>\n",
              "      <td>21.51</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>3980</th>\n",
              "      <td>男</td>\n",
              "      <td>3歲5個月</td>\n",
              "      <td>22.62</td>\n",
              "      <td>22.73</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>3981</th>\n",
              "      <td>男</td>\n",
              "      <td>3歲6個月</td>\n",
              "      <td>22.63</td>\n",
              "      <td>22.68</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3982</th>\n",
              "      <td>男</td>\n",
              "      <td>5歲6個月</td>\n",
              "      <td>22.52</td>\n",
              "      <td>22.74</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>3998</th>\n",
              "      <td>女</td>\n",
              "      <td>17歲2個月</td>\n",
              "      <td>23.63</td>\n",
              "      <td>22.79</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "<p>1904 rows × 6 columns</p>\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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            ],
            "text/plain": [
              "     性別      實歲   右眼軸長   左眼軸長  右眼危險度  左眼危險度\n",
              "0     男   6歲11月  25.46  25.13    3.0    3.0\n",
              "1     男    7歲2月  25.48  25.20    3.0    3.0\n",
              "2     男    7歲4月  25.56  25.26    3.0    3.0\n",
              "3     女    7歲7月  23.66  23.50    1.0    0.0\n",
              "5     女    8歲3月   24.0  23.77    1.0    1.0\n",
              "...  ..     ...    ...    ...    ...    ...\n",
              "3979  女  3歲10個月  21.48  21.51    NaN    NaN\n",
              "3980  男   3歲5個月  22.62  22.73    NaN    NaN\n",
              "3981  男   3歲6個月  22.63  22.68    NaN    NaN\n",
              "3982  男   5歲6個月  22.52  22.74    NaN    NaN\n",
              "3998  女  17歲2個月  23.63  22.79    NaN    NaN\n",
              "\n",
              "[1904 rows x 6 columns]"
            ]
          },
          "execution_count": 2,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import pandas as pd\n",
        "sheet = pd.read_excel('eyeForm.db.xlsx', sheet_name='三總', skiprows=2)\n",
        "db_version = f\"v{sheet.iloc[-1]['時間戳記']}\".split()[0].replace('-', '')\n",
        "df = sheet[['性別', '實歲', '右眼軸長', '左眼軸長', '右眼危險度', '左眼危險度']].dropna(subset=['性別', '實歲', '右眼軸長', '左眼軸長'])\n",
        "df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "BsLQTB4M5N7P",
        "outputId": "fe34eee4-1c5f-4efe-b21a-e6bea91f0b38"
      },
      "outputs": [
        {
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>性別</th>\n",
              "      <th>實歲</th>\n",
              "      <th>軸長</th>\n",
              "      <th>右眼危險度</th>\n",
              "      <th>左眼危險度</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>男</td>\n",
              "      <td>6歲11月</td>\n",
              "      <td>25.46</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>男</td>\n",
              "      <td>7歲2月</td>\n",
              "      <td>25.48</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>男</td>\n",
              "      <td>7歲4月</td>\n",
              "      <td>25.56</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>女</td>\n",
              "      <td>7歲7月</td>\n",
              "      <td>23.66</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>女</td>\n",
              "      <td>8歲3月</td>\n",
              "      <td>24.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3979</th>\n",
              "      <td>女</td>\n",
              "      <td>3歲10個月</td>\n",
              "      <td>21.51</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3980</th>\n",
              "      <td>男</td>\n",
              "      <td>3歲5個月</td>\n",
              "      <td>22.73</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3981</th>\n",
              "      <td>男</td>\n",
              "      <td>3歲6個月</td>\n",
              "      <td>22.68</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>3982</th>\n",
              "      <td>男</td>\n",
              "      <td>5歲6個月</td>\n",
              "      <td>22.74</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>3998</th>\n",
              "      <td>女</td>\n",
              "      <td>17歲2個月</td>\n",
              "      <td>22.79</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3808 rows × 5 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6789adeb-308a-4a4a-953c-5ece089cca18')\"\n",
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              "\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     性別      實歲     軸長  右眼危險度  左眼危險度\n",
              "0     男   6歲11月  25.46    3.0    3.0\n",
              "1     男    7歲2月  25.48    3.0    3.0\n",
              "2     男    7歲4月  25.56    3.0    3.0\n",
              "3     女    7歲7月  23.66    1.0    0.0\n",
              "5     女    8歲3月   24.0    1.0    1.0\n",
              "...  ..     ...    ...    ...    ...\n",
              "3979  女  3歲10個月  21.51    NaN    NaN\n",
              "3980  男   3歲5個月  22.73    NaN    NaN\n",
              "3981  男   3歲6個月  22.68    NaN    NaN\n",
              "3982  男   5歲6個月  22.74    NaN    NaN\n",
              "3998  女  17歲2個月  22.79    NaN    NaN\n",
              "\n",
              "[3808 rows x 5 columns]"
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "od = df.drop(columns='左眼軸長')\n",
        "os = df.drop(columns='右眼軸長')\n",
        "od.columns = ['性別', '實歲', '軸長', '右眼危險度', '左眼危險度']\n",
        "os.columns = ['性別', '實歲', '軸長', '右眼危險度', '左眼危險度']\n",
        "data = pd.concat([od, os])\n",
        "data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "J-sTG_nvtrs0",
        "outputId": "709b82c1-d3e5-4efa-8836-c88e8ab01388"
      },
      "outputs": [
        {
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              "      <td>NaN</td>\n",
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              "<p>3806 rows × 5 columns</p>\n",
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              "                                                     [key], {});\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  "
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            "text/plain": [
              "     性別      實歲     軸長  右眼危險度  左眼危險度\n",
              "0     男   6歲11月  25.46    3.0    3.0\n",
              "1     男    7歲2月  25.48    3.0    3.0\n",
              "2     男    7歲4月  25.56    3.0    3.0\n",
              "3     女    7歲7月  23.66    1.0    0.0\n",
              "5     女    8歲3月   24.0    1.0    1.0\n",
              "...  ..     ...    ...    ...    ...\n",
              "3979  女  3歲10個月  21.51    NaN    NaN\n",
              "3980  男   3歲5個月  22.73    NaN    NaN\n",
              "3981  男   3歲6個月  22.68    NaN    NaN\n",
              "3982  男   5歲6個月  22.74    NaN    NaN\n",
              "3998  女  17歲2個月  22.79    NaN    NaN\n",
              "\n",
              "[3806 rows x 5 columns]"
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          },
          "execution_count": 4,
          "metadata": {},
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      ],
      "source": [
        "data = data.drop(data[data['軸長'] == '< 20'].index)\n",
        "data = data.drop(data[data['軸長'] == '> 30'].index)\n",
        "data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
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        "id": "pTI_XHknMXDi",
        "outputId": "2ab6a30d-8218-4fcc-f93c-4fe2180732d8"
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      "outputs": [
        {
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              "</table>\n",
              "<p>3806 rows × 2 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e0d33e96-4b4f-4f49-8212-dcab1da5c2b7')\"\n",
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              "        buttonEl.style.display =\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e0d33e96-4b4f-4f49-8212-dcab1da5c2b7');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       0   1\n",
              "0      6  11\n",
              "1      7   2\n",
              "2      7   4\n",
              "3      7   7\n",
              "5      8   3\n",
              "...   ..  ..\n",
              "3979   3  10\n",
              "3980   3   5\n",
              "3981   3   6\n",
              "3982   5   6\n",
              "3998  17   2\n",
              "\n",
              "[3806 rows x 2 columns]"
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "age = data['實歲'].str.extract('(\\d+)歲(\\d+)')\n",
        "age"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
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              "                                                     [key], {});\n",
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              "\n",
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            "text/plain": [
              "     性別         實歲     軸長  右眼危險度  左眼危險度  年歲\n",
              "0     男   6.916667  25.46    3.0    3.0   7\n",
              "1     男   7.166667  25.48    3.0    3.0   7\n",
              "2     男   7.333333  25.56    3.0    3.0   7\n",
              "3     女   7.583333  23.66    1.0    0.0   8\n",
              "5     女   8.250000  24.00    1.0    1.0   8\n",
              "...  ..        ...    ...    ...    ...  ..\n",
              "3979  女   3.833333  21.51    NaN    NaN   4\n",
              "3980  男   3.416667  22.73    NaN    NaN   3\n",
              "3981  男   3.500000  22.68    NaN    NaN   4\n",
              "3982  男   5.500000  22.74    NaN    NaN   6\n",
              "3998  女  17.166667  22.79    NaN    NaN  17\n",
              "\n",
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          },
          "execution_count": 6,
          "metadata": {},
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      ],
      "source": [
        "data['實歲'] = age[0].astype(int) + age[1].astype(int) / 12\n",
        "data['年歲'] = age[0].astype(int) + (age[1].astype(int) >= 6).astype(int) # round() could be wrong\n",
        "data['軸長'] = data['軸長'].astype(float)\n",
        "data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "t71-LKO9TiVu"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "def percentile(q):\n",
        "    def function(a):\n",
        "        return np.percentile(a, q)\n",
        "    function.__name__ = f'P{q}'\n",
        "    return function"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "2XUwvRKS1nxu"
      },
      "outputs": [],
      "source": [
        "quartile = data.groupby(['性別', '年歲'])['軸長'].aggregate([percentile(25), percentile(75)])\n",
        "IQR = quartile['P75'] - quartile['P25']\n",
        "lower_fence = quartile['P25'] - IQR * 1.5\n",
        "upper_fence = quartile['P75'] + IQR * 1.5"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
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        },
        "id": "sP-GjRqBK_7y",
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              "      <td>24.98000</td>\n",
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              "    <tr>\n",
              "      <th>3981</th>\n",
              "      <td>男</td>\n",
              "      <td>3.500000</td>\n",
              "      <td>22.68</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4</td>\n",
              "      <td>20.29125</td>\n",
              "      <td>24.20125</td>\n",
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              "    <tr>\n",
              "      <th>3982</th>\n",
              "      <td>男</td>\n",
              "      <td>5.500000</td>\n",
              "      <td>22.74</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>6</td>\n",
              "      <td>20.07500</td>\n",
              "      <td>25.93500</td>\n",
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              "    <tr>\n",
              "      <th>3998</th>\n",
              "      <td>女</td>\n",
              "      <td>17.166667</td>\n",
              "      <td>22.79</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>17</td>\n",
              "      <td>23.06375</td>\n",
              "      <td>26.95375</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3806 rows × 8 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6cfa0fe8-757c-4f4f-b2f4-4279feb2d373')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  "
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            "text/plain": [
              "     性別         實歲     軸長  右眼危險度  左眼危險度  年歲  lower_fence  upper_fence\n",
              "0     男   6.916667  25.46    3.0    3.0   7     20.47250     26.29250\n",
              "1     男   7.166667  25.48    3.0    3.0   7     20.47250     26.29250\n",
              "2     男   7.333333  25.56    3.0    3.0   7     20.47250     26.29250\n",
              "3     女   7.583333  23.66    1.0    0.0   8     21.29125     25.60125\n",
              "5     女   8.250000  24.00    1.0    1.0   8     21.29125     25.60125\n",
              "...  ..        ...    ...    ...    ...  ..          ...          ...\n",
              "3979  女   3.833333  21.51    NaN    NaN   4     19.90125     23.47125\n",
              "3980  男   3.416667  22.73    NaN    NaN   3     20.24000     24.98000\n",
              "3981  男   3.500000  22.68    NaN    NaN   4     20.29125     24.20125\n",
              "3982  男   5.500000  22.74    NaN    NaN   6     20.07500     25.93500\n",
              "3998  女  17.166667  22.79    NaN    NaN  17     23.06375     26.95375\n",
              "\n",
              "[3806 rows x 8 columns]"
            ]
          },
          "execution_count": 9,
          "metadata": {},
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        }
      ],
      "source": [
        "for i in quartile.index:\n",
        "    data.loc[(data['性別'] == i[0]) & (data['年歲'] == i[1]), 'lower_fence'] = lower_fence[i]\n",
        "    data.loc[(data['性別'] == i[0]) & (data['年歲'] == i[1]), 'upper_fence'] = upper_fence[i]\n",
        "data"
      ]
    },
    {
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      "metadata": {
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        },
        "id": "W8agHf7fhnXN",
        "outputId": "b155168e-2f50-4ae3-9fba-2accb6422567"
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              "      <td>21.51</td>\n",
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            "text/plain": [
              "     性別        實歲     軸長  右眼危險度  左眼危險度  年歲  lower_fence  upper_fence\n",
              "0     男  6.916667  25.46    3.0    3.0   7     20.47250     26.29250\n",
              "1     男  7.166667  25.48    3.0    3.0   7     20.47250     26.29250\n",
              "2     男  7.333333  25.56    3.0    3.0   7     20.47250     26.29250\n",
              "3     女  7.583333  23.66    1.0    0.0   8     21.29125     25.60125\n",
              "5     女  8.250000  24.00    1.0    1.0   8     21.29125     25.60125\n",
              "...  ..       ...    ...    ...    ...  ..          ...          ...\n",
              "3978  女  3.416667  21.76    NaN    NaN   3     19.73500     23.07500\n",
              "3979  女  3.833333  21.51    NaN    NaN   4     19.90125     23.47125\n",
              "3980  男  3.416667  22.73    NaN    NaN   3     20.24000     24.98000\n",
              "3981  男  3.500000  22.68    NaN    NaN   4     20.29125     24.20125\n",
              "3982  男  5.500000  22.74    NaN    NaN   6     20.07500     25.93500\n",
              "\n",
              "[3658 rows x 8 columns]"
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "data_without_outliers = data[(data['軸長'] > data['lower_fence']) & (data['軸長'] < data['upper_fence'])]\n",
        "data_without_outliers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
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        },
        "id": "c42aysNJDa2P",
        "outputId": "83cfdd50-5c50-4456-c70a-b6f370a56b2e"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "8     459\n",
              "6     447\n",
              "5     443\n",
              "7     397\n",
              "9     371\n",
              "10    357\n",
              "4     295\n",
              "11    215\n",
              "12    188\n",
              "13    115\n",
              "3     113\n",
              "14     99\n",
              "15     83\n",
              "16     40\n",
              "17     11\n",
              "2       9\n",
              "18      6\n",
              "1       6\n",
              "21      2\n",
              "0       2\n",
              "Name: 年歲, dtype: int64"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "data_without_outliers['年歲'].value_counts()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
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        "id": "f4APhLvYklAw",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>P0</th>\n",
              "      <th>P50</th>\n",
              "      <th>P75</th>\n",
              "      <th>P90</th>\n",
              "      <th>P100</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>性別</th>\n",
              "      <th>年歲</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"20\" valign=\"top\">女</th>\n",
              "      <th>0</th>\n",
              "      <td>20.50</td>\n",
              "      <td>20.520</td>\n",
              "      <td>20.5300</td>\n",
              "      <td>20.536</td>\n",
              "      <td>20.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>20.55</td>\n",
              "      <td>20.690</td>\n",
              "      <td>20.7450</td>\n",
              "      <td>20.765</td>\n",
              "      <td>20.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>20.86</td>\n",
              "      <td>20.905</td>\n",
              "      <td>20.9700</td>\n",
              "      <td>21.024</td>\n",
              "      <td>21.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>20.26</td>\n",
              "      <td>21.310</td>\n",
              "      <td>21.7850</td>\n",
              "      <td>22.194</td>\n",
              "      <td>23.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>20.35</td>\n",
              "      <td>21.720</td>\n",
              "      <td>22.0200</td>\n",
              "      <td>22.789</td>\n",
              "      <td>23.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>19.73</td>\n",
              "      <td>22.130</td>\n",
              "      <td>22.6200</td>\n",
              "      <td>23.021</td>\n",
              "      <td>24.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>19.64</td>\n",
              "      <td>22.180</td>\n",
              "      <td>22.9300</td>\n",
              "      <td>23.326</td>\n",
              "      <td>24.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>21.03</td>\n",
              "      <td>22.980</td>\n",
              "      <td>23.4275</td>\n",
              "      <td>24.008</td>\n",
              "      <td>24.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>21.35</td>\n",
              "      <td>23.450</td>\n",
              "      <td>23.8600</td>\n",
              "      <td>24.620</td>\n",
              "      <td>25.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>21.51</td>\n",
              "      <td>23.680</td>\n",
              "      <td>24.0600</td>\n",
              "      <td>24.556</td>\n",
              "      <td>25.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>21.58</td>\n",
              "      <td>23.770</td>\n",
              "      <td>24.4650</td>\n",
              "      <td>24.920</td>\n",
              "      <td>25.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>21.49</td>\n",
              "      <td>23.910</td>\n",
              "      <td>24.8000</td>\n",
              "      <td>25.190</td>\n",
              "      <td>25.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>22.51</td>\n",
              "      <td>24.320</td>\n",
              "      <td>24.7200</td>\n",
              "      <td>25.070</td>\n",
              "      <td>25.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>22.81</td>\n",
              "      <td>24.480</td>\n",
              "      <td>25.0100</td>\n",
              "      <td>25.680</td>\n",
              "      <td>26.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>22.92</td>\n",
              "      <td>24.855</td>\n",
              "      <td>25.6550</td>\n",
              "      <td>25.932</td>\n",
              "      <td>26.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>22.39</td>\n",
              "      <td>25.010</td>\n",
              "      <td>25.4475</td>\n",
              "      <td>26.078</td>\n",
              "      <td>26.44</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>23.29</td>\n",
              "      <td>24.600</td>\n",
              "      <td>25.3250</td>\n",
              "      <td>25.840</td>\n",
              "      <td>26.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>23.63</td>\n",
              "      <td>25.290</td>\n",
              "      <td>25.5900</td>\n",
              "      <td>25.872</td>\n",
              "      <td>26.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>22.42</td>\n",
              "      <td>23.700</td>\n",
              "      <td>25.1400</td>\n",
              "      <td>25.806</td>\n",
              "      <td>26.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>24.69</td>\n",
              "      <td>24.915</td>\n",
              "      <td>25.0275</td>\n",
              "      <td>25.095</td>\n",
              "      <td>25.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"17\" valign=\"top\">男</th>\n",
              "      <th>2</th>\n",
              "      <td>21.88</td>\n",
              "      <td>22.060</td>\n",
              "      <td>22.0800</td>\n",
              "      <td>22.296</td>\n",
              "      <td>22.44</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>20.99</td>\n",
              "      <td>22.610</td>\n",
              "      <td>23.2450</td>\n",
              "      <td>23.825</td>\n",
              "      <td>24.29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>20.37</td>\n",
              "      <td>22.170</td>\n",
              "      <td>22.7000</td>\n",
              "      <td>23.134</td>\n",
              "      <td>24.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>20.48</td>\n",
              "      <td>22.640</td>\n",
              "      <td>23.3050</td>\n",
              "      <td>23.890</td>\n",
              "      <td>24.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>20.13</td>\n",
              "      <td>22.840</td>\n",
              "      <td>23.7400</td>\n",
              "      <td>24.344</td>\n",
              "      <td>25.53</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>20.52</td>\n",
              "      <td>23.560</td>\n",
              "      <td>24.1100</td>\n",
              "      <td>24.628</td>\n",
              "      <td>26.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>21.45</td>\n",
              "      <td>23.965</td>\n",
              "      <td>24.4300</td>\n",
              "      <td>25.019</td>\n",
              "      <td>25.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>22.45</td>\n",
              "      <td>24.245</td>\n",
              "      <td>24.6550</td>\n",
              "      <td>24.990</td>\n",
              "      <td>25.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>21.99</td>\n",
              "      <td>24.510</td>\n",
              "      <td>25.1175</td>\n",
              "      <td>25.490</td>\n",
              "      <td>26.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>22.36</td>\n",
              "      <td>24.510</td>\n",
              "      <td>25.2550</td>\n",
              "      <td>25.932</td>\n",
              "      <td>26.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>23.02</td>\n",
              "      <td>24.665</td>\n",
              "      <td>25.1725</td>\n",
              "      <td>25.826</td>\n",
              "      <td>26.93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>23.26</td>\n",
              "      <td>24.885</td>\n",
              "      <td>25.1600</td>\n",
              "      <td>25.530</td>\n",
              "      <td>26.44</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>23.21</td>\n",
              "      <td>24.820</td>\n",
              "      <td>25.1900</td>\n",
              "      <td>25.840</td>\n",
              "      <td>26.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>23.54</td>\n",
              "      <td>24.840</td>\n",
              "      <td>25.0800</td>\n",
              "      <td>25.398</td>\n",
              "      <td>26.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>22.40</td>\n",
              "      <td>25.410</td>\n",
              "      <td>26.6525</td>\n",
              "      <td>27.197</td>\n",
              "      <td>27.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>26.55</td>\n",
              "      <td>27.010</td>\n",
              "      <td>27.4675</td>\n",
              "      <td>27.715</td>\n",
              "      <td>27.88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>25.46</td>\n",
              "      <td>25.695</td>\n",
              "      <td>25.8125</td>\n",
              "      <td>25.883</td>\n",
              "      <td>25.93</td>\n",
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            "text/plain": [
              "          P0     P50      P75     P90   P100\n",
              "性別 年歲                                       \n",
              "女  0   20.50  20.520  20.5300  20.536  20.54\n",
              "   1   20.55  20.690  20.7450  20.765  20.77\n",
              "   2   20.86  20.905  20.9700  21.024  21.06\n",
              "   3   20.26  21.310  21.7850  22.194  23.06\n",
              "   4   20.35  21.720  22.0200  22.789  23.33\n",
              "   5   19.73  22.130  22.6200  23.021  24.50\n",
              "   6   19.64  22.180  22.9300  23.326  24.57\n",
              "   7   21.03  22.980  23.4275  24.008  24.84\n",
              "   8   21.35  23.450  23.8600  24.620  25.54\n",
              "   9   21.51  23.680  24.0600  24.556  25.57\n",
              "   10  21.58  23.770  24.4650  24.920  25.89\n",
              "   11  21.49  23.910  24.8000  25.190  25.90\n",
              "   12  22.51  24.320  24.7200  25.070  25.33\n",
              "   13  22.81  24.480  25.0100  25.680  26.66\n",
              "   14  22.92  24.855  25.6550  25.932  26.20\n",
              "   15  22.39  25.010  25.4475  26.078  26.44\n",
              "   16  23.29  24.600  25.3250  25.840  26.54\n",
              "   17  23.63  25.290  25.5900  25.872  26.01\n",
              "   18  22.42  23.700  25.1400  25.806  26.25\n",
              "   21  24.69  24.915  25.0275  25.095  25.14\n",
              "男  2   21.88  22.060  22.0800  22.296  22.44\n",
              "   3   20.99  22.610  23.2450  23.825  24.29\n",
              "   4   20.37  22.170  22.7000  23.134  24.14\n",
              "   5   20.48  22.640  23.3050  23.890  24.96\n",
              "   6   20.13  22.840  23.7400  24.344  25.53\n",
              "   7   20.52  23.560  24.1100  24.628  26.14\n",
              "   8   21.45  23.965  24.4300  25.019  25.76\n",
              "   9   22.45  24.245  24.6550  24.990  25.90\n",
              "   10  21.99  24.510  25.1175  25.490  26.28\n",
              "   11  22.36  24.510  25.2550  25.932  26.77\n",
              "   12  23.02  24.665  25.1725  25.826  26.93\n",
              "   13  23.26  24.885  25.1600  25.530  26.44\n",
              "   14  23.21  24.820  25.1900  25.840  26.56\n",
              "   15  23.54  24.840  25.0800  25.398  26.23\n",
              "   16  22.40  25.410  26.6525  27.197  27.86\n",
              "   17  26.55  27.010  27.4675  27.715  27.88\n",
              "   18  25.46  25.695  25.8125  25.883  25.93"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "stacked_area = data_without_outliers.groupby(['性別', '年歲'])['軸長'].aggregate([percentile(0), percentile(50), percentile(75), percentile(90), percentile(100)])\n",
        "stacked_area"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "lQsjLN-uEvGt"
      },
      "outputs": [],
      "source": [
        "def level(sex, age, length):\n",
        "    if length < stacked_area.loc[sex].loc[age].P50:\n",
        "        return 0\n",
        "    elif length < stacked_area.loc[sex].loc[age].P75:\n",
        "        return 1\n",
        "    elif length < stacked_area.loc[sex].loc[age].P90:\n",
        "        return 2\n",
        "    else:\n",
        "        return 3"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "M_m68V5bTxp_",
        "outputId": "459a49a7-54f4-4a7f-86d4-72e09347f5e9"
      },
      "outputs": [
        {
          "data": {
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              "      <th>實歲</th>\n",
              "      <th>右眼軸長</th>\n",
              "      <th>左眼軸長</th>\n",
              "      <th>右眼危險度</th>\n",
              "      <th>左眼危險度</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>男</td>\n",
              "      <td>6歲11月</td>\n",
              "      <td>25.46</td>\n",
              "      <td>25.13</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>男</td>\n",
              "      <td>7歲2月</td>\n",
              "      <td>25.48</td>\n",
              "      <td>25.20</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>男</td>\n",
              "      <td>7歲4月</td>\n",
              "      <td>25.56</td>\n",
              "      <td>25.26</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>女</td>\n",
              "      <td>7歲7月</td>\n",
              "      <td>23.66</td>\n",
              "      <td>23.50</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>女</td>\n",
              "      <td>8歲3月</td>\n",
              "      <td>24.0</td>\n",
              "      <td>23.77</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>3979</th>\n",
              "      <td>女</td>\n",
              "      <td>3歲10個月</td>\n",
              "      <td>21.48</td>\n",
              "      <td>21.51</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3980</th>\n",
              "      <td>男</td>\n",
              "      <td>3歲5個月</td>\n",
              "      <td>22.62</td>\n",
              "      <td>22.73</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3981</th>\n",
              "      <td>男</td>\n",
              "      <td>3歲6個月</td>\n",
              "      <td>22.63</td>\n",
              "      <td>22.68</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3982</th>\n",
              "      <td>男</td>\n",
              "      <td>5歲6個月</td>\n",
              "      <td>22.52</td>\n",
              "      <td>22.74</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3998</th>\n",
              "      <td>女</td>\n",
              "      <td>17歲2個月</td>\n",
              "      <td>23.63</td>\n",
              "      <td>22.79</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1903 rows × 6 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-89d7577f-e723-4c26-9c8f-156f7027cc21')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-89d7577f-e723-4c26-9c8f-156f7027cc21');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     性別      實歲   右眼軸長   左眼軸長  右眼危險度  左眼危險度\n",
              "0     男   6歲11月  25.46  25.13    3.0    3.0\n",
              "1     男    7歲2月  25.48  25.20    3.0    3.0\n",
              "2     男    7歲4月  25.56  25.26    3.0    3.0\n",
              "3     女    7歲7月  23.66  23.50    1.0    0.0\n",
              "5     女    8歲3月   24.0  23.77    1.0    1.0\n",
              "...  ..     ...    ...    ...    ...    ...\n",
              "3979  女  3歲10個月  21.48  21.51    NaN    NaN\n",
              "3980  男   3歲5個月  22.62  22.73    NaN    NaN\n",
              "3981  男   3歲6個月  22.63  22.68    NaN    NaN\n",
              "3982  男   5歲6個月  22.52  22.74    NaN    NaN\n",
              "3998  女  17歲2個月  23.63  22.79    NaN    NaN\n",
              "\n",
              "[1903 rows x 6 columns]"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df = df.drop(df[df['右眼軸長'] == '< 20'].index)\n",
        "df = df.drop(df[df['右眼軸長'] == '> 30'].index)\n",
        "df = df.drop(df[df['左眼軸長'] == '< 20'].index)\n",
        "df = df.drop(df[df['左眼軸長'] == '> 30'].index)\n",
        "df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "gi2_OFuaGwMW",
        "outputId": "0984255e-e0d7-46d0-b92e-1e684edd68a9"
      },
      "outputs": [
        {
          "data": {
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              "                                                     [key], {});\n",
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              "\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  "
            ],
            "text/plain": [
              "       0   1\n",
              "0      6  11\n",
              "1      7   2\n",
              "2      7   4\n",
              "3      7   7\n",
              "5      8   3\n",
              "...   ..  ..\n",
              "3979   3  10\n",
              "3980   3   5\n",
              "3981   3   6\n",
              "3982   5   6\n",
              "3998  17   2\n",
              "\n",
              "[1903 rows x 2 columns]"
            ]
          },
          "execution_count": 15,
          "metadata": {},
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        }
      ],
      "source": [
        "age = df['實歲'].str.extract('(\\d+)歲(\\d+)')\n",
        "age"
      ]
    },
    {
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      "execution_count": 16,
      "metadata": {
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              "      <th></th>\n",
              "      <th>性別</th>\n",
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              "      <th>右眼軸長</th>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>3979</th>\n",
              "      <td>女</td>\n",
              "      <td>3.833333</td>\n",
              "      <td>21.48</td>\n",
              "      <td>21.51</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3980</th>\n",
              "      <td>男</td>\n",
              "      <td>3.416667</td>\n",
              "      <td>22.62</td>\n",
              "      <td>22.73</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3981</th>\n",
              "      <td>男</td>\n",
              "      <td>3.500000</td>\n",
              "      <td>22.63</td>\n",
              "      <td>22.68</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3982</th>\n",
              "      <td>男</td>\n",
              "      <td>5.500000</td>\n",
              "      <td>22.52</td>\n",
              "      <td>22.74</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3998</th>\n",
              "      <td>女</td>\n",
              "      <td>17.166667</td>\n",
              "      <td>23.63</td>\n",
              "      <td>22.79</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1903 rows × 7 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9333902b-90d2-4c4b-9a42-059c45f495f5')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
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              "\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-9333902b-90d2-4c4b-9a42-059c45f495f5 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-9333902b-90d2-4c4b-9a42-059c45f495f5');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     性別         實歲   右眼軸長   左眼軸長  右眼危險度  左眼危險度  年歲\n",
              "0     男   6.916667  25.46  25.13    3.0    3.0   7\n",
              "1     男   7.166667  25.48  25.20    3.0    3.0   7\n",
              "2     男   7.333333  25.56  25.26    3.0    3.0   7\n",
              "3     女   7.583333  23.66  23.50    1.0    0.0   8\n",
              "5     女   8.250000  24.00  23.77    1.0    1.0   8\n",
              "...  ..        ...    ...    ...    ...    ...  ..\n",
              "3979  女   3.833333  21.48  21.51    NaN    NaN   4\n",
              "3980  男   3.416667  22.62  22.73    NaN    NaN   3\n",
              "3981  男   3.500000  22.63  22.68    NaN    NaN   4\n",
              "3982  男   5.500000  22.52  22.74    NaN    NaN   6\n",
              "3998  女  17.166667  23.63  22.79    NaN    NaN  17\n",
              "\n",
              "[1903 rows x 7 columns]"
            ]
          },
          "execution_count": 16,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "df['實歲'] = age[0].astype(int) + age[1].astype(int) / 12\n",
        "df['年歲'] = age[0].astype(int) + (age[1].astype(int) >= 6).astype(int) # round() could be wrong\n",
        "df['右眼軸長'] = df['右眼軸長'].astype(float)\n",
        "df['左眼軸長'] = df['左眼軸長'].astype(float)\n",
        "df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "tpNFwONnUfIB",
        "outputId": "adf21822-e25e-42f7-bda6-293ad6b9d5b2"
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      "outputs": [
        {
          "data": {
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              "      <th></th>\n",
              "      <th>性別</th>\n",
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              "      <td>22.62</td>\n",
              "      <td>22.73</td>\n",
              "      <td>1.0</td>\n",
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              "      <th>3981</th>\n",
              "      <td>男</td>\n",
              "      <td>3.500000</td>\n",
              "      <td>22.63</td>\n",
              "      <td>22.68</td>\n",
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              "      <th>3982</th>\n",
              "      <td>男</td>\n",
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              "      <td>22.52</td>\n",
              "      <td>22.74</td>\n",
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              "<p>1903 rows × 7 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-efe8256c-fd5b-4675-963a-f8ae60f585c1')\"\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-efe8256c-fd5b-4675-963a-f8ae60f585c1');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  "
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            "text/plain": [
              "     性別         實歲   右眼軸長   左眼軸長  右眼危險度  左眼危險度  年歲\n",
              "0     男   6.916667  25.46  25.13    3.0    3.0   7\n",
              "1     男   7.166667  25.48  25.20    3.0    3.0   7\n",
              "2     男   7.333333  25.56  25.26    3.0    3.0   7\n",
              "3     女   7.583333  23.66  23.50    1.0    1.0   8\n",
              "5     女   8.250000  24.00  23.77    2.0    1.0   8\n",
              "...  ..        ...    ...    ...    ...    ...  ..\n",
              "3979  女   3.833333  21.48  21.51    0.0    0.0   4\n",
              "3980  男   3.416667  22.62  22.73    1.0    1.0   3\n",
              "3981  男   3.500000  22.63  22.68    1.0    1.0   4\n",
              "3982  男   5.500000  22.52  22.74    0.0    0.0   6\n",
              "3998  女  17.166667  23.63  22.79    0.0    0.0  17\n",
              "\n",
              "[1903 rows x 7 columns]"
            ]
          },
          "execution_count": 17,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "for i in df.index:\n",
        "    sex = df.loc[i]['性別']\n",
        "    age = df.loc[i]['年歲']\n",
        "    df.loc[i, '右眼危險度'] = level(sex, age, df.loc[i]['右眼軸長'])\n",
        "    df.loc[i, '左眼危險度'] = level(sex, age, df.loc[i]['左眼軸長'])\n",
        "df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "BtG-RFMmmQUr"
      },
      "outputs": [],
      "source": [
        "sheet['右眼危險度'] = ''\n",
        "sheet['左眼危險度'] = ''\n",
        "sheet.loc[df.index, '右眼危險度'] = df['右眼危險度'].astype(int)\n",
        "sheet.loc[df.index, '左眼危險度'] = df['左眼危險度'].astype(int)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17
        },
        "id": "fLcd_AwHr4qE",
        "outputId": "bb2501de-23b0-48de-cb22-fdbf4ff0c076"
      },
      "outputs": [
        {
          "data": {
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            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/javascript": "download(\"download_75a144ae-949f-4d89-9d30-fca9e5bb5654\", \"update_db.xlsx\", 555941)",
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "sheet.to_excel('db_risk0123.xlsx')\n",
        "files.download('db_risk0123.xlsx')"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "authorship_tag": "ABX9TyNpW1MtHxV4FjF5Ln0UQy4q",
      "include_colab_link": true,
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}