tutorials/data_preparation/missing_data/data_imputation_with_statistical_methods.ipynb

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        "# 02 - Missing Data Imputation with Statistical Methods\n",
        "\n",
        "- Types of imputation\n",
        "  - Numerical\n",
        "  - Temporal\n",
        "  - Categorical\n",
        "## Preprocessing\n",
        "- Determine if Temporal\n",
        "- Split out numerical vs categorical\n",
        "\n",
        "## Base Cases\n",
        "- Drop Rows\n",
        "- Drop Columns\n",
        "\n",
        "## Numerical\n",
        "- Mean\n",
        "- Meadian\n",
        "- Most Freq\n",
        "- Set Value\n",
        "## Temporal\n",
        "- Backfill\n",
        "- Forwardfill\n",
        "- Linear\n",
        "- Polynomial\n",
        "## Categorical\n",
        "- Most Freq\n",
        "\n",
        "> Unforturtunately Categorical data does not have a lot statistical methods of imputation as the data may have many specific subject matter related differences."
      ],
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        "\n",
        "# Preprocessing\n",
        "\n",
        "- Download this [dataset](https://www.kaggle.com/datasets/nelgiriyewithana/countries-of-the-world-2023)\n"
      ],
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        "import pandas as pd\n",
        "df = pd.read_csv('/content/world-data-2023.csv')\n",
        "df_limited = df.iloc[:,:7]\n",
        "df_limited.isna().sum()"
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      "execution_count": 49,
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              "Country                   0\n",
              "Density\\n(P/Km2)          0\n",
              "Abbreviation              7\n",
              "Agricultural Land( %)     7\n",
              "Land Area(Km2)            1\n",
              "Armed Forces size        24\n",
              "Birth Rate                6\n",
              "dtype: int64"
            ]
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        "df_limited.head()"
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              "       Country Density\\n(P/Km2) Abbreviation Agricultural Land( %)  \\\n",
              "0  Afghanistan               60           AF                58.10%   \n",
              "1      Albania              105           AL                43.10%   \n",
              "2      Algeria               18           DZ                17.40%   \n",
              "3      Andorra              164           AD                40.00%   \n",
              "4       Angola               26           AO                47.50%   \n",
              "\n",
              "  Land Area(Km2) Armed Forces size  Birth Rate  \n",
              "0        652,230           323,000       32.49  \n",
              "1         28,748             9,000       11.78  \n",
              "2      2,381,741           317,000       24.28  \n",
              "3            468               NaN        7.20  \n",
              "4      1,246,700           117,000       40.73  "
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            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 195 entries, 0 to 194\n",
            "Data columns (total 7 columns):\n",
            " #   Column                 Non-Null Count  Dtype  \n",
            "---  ------                 --------------  -----  \n",
            " 0   Country                195 non-null    object \n",
            " 1   Density\n",
            "(P/Km2)        195 non-null    object \n",
            " 2   Abbreviation           188 non-null    object \n",
            " 3   Agricultural Land( %)  188 non-null    object \n",
            " 4   Land Area(Km2)         194 non-null    object \n",
            " 5   Armed Forces size      171 non-null    object \n",
            " 6   Birth Rate             189 non-null    float64\n",
            "dtypes: float64(1), object(6)\n",
            "memory usage: 10.8+ KB\n"
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              "Index(['Country', 'Density\\n(P/Km2)', 'Abbreviation', 'Agricultural Land( %)',\n",
              "       'Land Area(Km2)', 'Armed Forces size', 'Birth Rate'],\n",
              "      dtype='object')"
            ]
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        "categorical_cols = ['Country','Abbreviation']\n",
        "numerical_cols = ['Density\\n(P/Km2)', 'Agricultural Land( %)',\n",
        "       'Land Area(Km2)', 'Armed Forces size']\n",
        "\n",
        "\n",
        "df_cat = df_limited[categorical_cols]\n",
        "df_num = df_limited[numerical_cols]\n",
        "for col in numerical_cols:\n",
        "  df_num[col] = df_limited[col].str.replace(',','').str.replace('%','').astype('float64')\n",
        "\n",
        "df_num"
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      "execution_count": 54,
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          "name": "stderr",
          "text": [
            "<ipython-input-54-05294a6399b0>:9: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  df_num[col] = df_limited[col].str.replace(',','').str.replace('%','').astype('float64')\n"
          ]
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              "     Density\\n(P/Km2)  Agricultural Land( %)  Land Area(Km2)  \\\n",
              "0                60.0                   58.1        652230.0   \n",
              "1               105.0                   43.1         28748.0   \n",
              "2                18.0                   17.4       2381741.0   \n",
              "3               164.0                   40.0           468.0   \n",
              "4                26.0                   47.5       1246700.0   \n",
              "..                ...                    ...             ...   \n",
              "190              32.0                   24.5        912050.0   \n",
              "191             314.0                   39.3        331210.0   \n",
              "192              56.0                   44.6        527968.0   \n",
              "193              25.0                   32.1        752618.0   \n",
              "194              38.0                   41.9        390757.0   \n",
              "\n",
              "     Armed Forces size  \n",
              "0             323000.0  \n",
              "1               9000.0  \n",
              "2             317000.0  \n",
              "3                  NaN  \n",
              "4             117000.0  \n",
              "..                 ...  \n",
              "190           343000.0  \n",
              "191           522000.0  \n",
              "192            40000.0  \n",
              "193            16000.0  \n",
              "194            51000.0  \n",
              "\n",
              "[195 rows x 4 columns]"
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              "      <th>190</th>\n",
              "      <td>32.0</td>\n",
              "      <td>24.5</td>\n",
              "      <td>912050.0</td>\n",
              "      <td>343000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>191</th>\n",
              "      <td>314.0</td>\n",
              "      <td>39.3</td>\n",
              "      <td>331210.0</td>\n",
              "      <td>522000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>192</th>\n",
              "      <td>56.0</td>\n",
              "      <td>44.6</td>\n",
              "      <td>527968.0</td>\n",
              "      <td>40000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>193</th>\n",
              "      <td>25.0</td>\n",
              "      <td>32.1</td>\n",
              "      <td>752618.0</td>\n",
              "      <td>16000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>194</th>\n",
              "      <td>38.0</td>\n",
              "      <td>41.9</td>\n",
              "      <td>390757.0</td>\n",
              "      <td>51000.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>195 rows × 4 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e945ef0d-29c6-4233-9a5d-841dc174573e')\"\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",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-27481c34-cb09-4c5e-ac0d-6183219358d0\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-27481c34-cb09-4c5e-ac0d-6183219358d0')\"\n",
              "              title=\"Suggest charts.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
              "  }\n",
              "</style>\n",
              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-27481c34-cb09-4c5e-ac0d-6183219358d0 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e945ef0d-29c6-4233-9a5d-841dc174573e 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-e945ef0d-29c6-4233-9a5d-841dc174573e');\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"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Naive Method"
      ],
      "metadata": {
        "id": "JqagEsY46n2Y"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Drop Rows\n"
      ],
      "metadata": {
        "id": "SPZ3oQag9E7q"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_limited_dropped = df_limited.dropna()\n",
        "df_limited_dropped.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d41PcUKq2DsA",
        "outputId": "76b6cb42-913e-4519-96b6-fb78619e188a"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 167 entries, 0 to 194\n",
            "Data columns (total 7 columns):\n",
            " #   Column                 Non-Null Count  Dtype  \n",
            "---  ------                 --------------  -----  \n",
            " 0   Country                167 non-null    object \n",
            " 1   Density\n",
            "(P/Km2)        167 non-null    object \n",
            " 2   Abbreviation           167 non-null    object \n",
            " 3   Agricultural Land( %)  167 non-null    object \n",
            " 4   Land Area(Km2)         167 non-null    object \n",
            " 5   Armed Forces size      167 non-null    object \n",
            " 6   Birth Rate             167 non-null    float64\n",
            "dtypes: float64(1), object(6)\n",
            "memory usage: 10.4+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- Notice we now have 167 of the initial 195 rows.\n",
        "- This is almost 20% of the data, which can drastically effect model performance."
      ],
      "metadata": {
        "id": "WCS1wBl27IUa"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Drop Columns"
      ],
      "metadata": {
        "id": "mMq2scmi9BAu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Drop Columns\n",
        "# df_limited_col_drop = df\n",
        "df_limited_col_drop = df_limited[df_limited.columns[~df_limited.isnull().any()]]\n",
        "\n",
        "df_limited_col_drop"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "rPjkFJWa2oSb",
        "outputId": "e4dd23f7-82c3-43dd-ae65-c9bed520f938"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Country Density\\n(P/Km2)\n",
              "0    Afghanistan               60\n",
              "1        Albania              105\n",
              "2        Algeria               18\n",
              "3        Andorra              164\n",
              "4         Angola               26\n",
              "..           ...              ...\n",
              "190    Venezuela               32\n",
              "191      Vietnam              314\n",
              "192        Yemen               56\n",
              "193       Zambia               25\n",
              "194     Zimbabwe               38\n",
              "\n",
              "[195 rows x 2 columns]"
            ],
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              "\n",
              "\n",
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              "      <td>Afghanistan</td>\n",
              "      <td>60</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Albania</td>\n",
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              "      <th>2</th>\n",
              "      <td>Algeria</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Angola</td>\n",
              "      <td>26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>190</th>\n",
              "      <td>Venezuela</td>\n",
              "      <td>32</td>\n",
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              "    <tr>\n",
              "      <th>191</th>\n",
              "      <td>Vietnam</td>\n",
              "      <td>314</td>\n",
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              "    <tr>\n",
              "      <th>192</th>\n",
              "      <td>Yemen</td>\n",
              "      <td>56</td>\n",
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              "    <tr>\n",
              "      <th>193</th>\n",
              "      <td>Zambia</td>\n",
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              "    <tr>\n",
              "      <th>194</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>38</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>195 rows × 2 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-067187d4-322f-4435-91d6-db08aedf1e4a')\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-24b62ff2-db2b-4e3e-90f5-c614fade3a28\">\n",
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              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: #1967D2;\n",
              "    height: 32px;\n",
              "    padding: 0 0 0 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
              "    background-color: #434B5C;\n",
              "    box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "    fill: #FFFFFF;\n",
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              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-24b62ff2-db2b-4e3e-90f5-c614fade3a28 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-067187d4-322f-4435-91d6-db08aedf1e4a 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-067187d4-322f-4435-91d6-db08aedf1e4a');\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"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- This may be an extreme case, but you want to be more selective of which columns you're stripping for model development. These columns may give powerful insights."
      ],
      "metadata": {
        "id": "cHYaO2NF8kIa"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Numerical\n",
        "\n",
        "- For the purposes of implementing these imputation we'll use birth rate as the target (what our model is predicting)"
      ],
      "metadata": {
        "id": "boUlPYDR8vO9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X = df_num\n",
        "y = df_limited[['Birth Rate']]"
      ],
      "metadata": {
        "id": "XJvUYzuy-PKg"
      },
      "execution_count": 74,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Mean\n",
        "\n",
        "- Skewed distributions and outliers can impact mean value imputation has.\n",
        "- The mean may not correlate well to the filled in null."
      ],
      "metadata": {
        "id": "UUi9SPS99Jho"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_num.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "puoTp4Ob-qyz",
        "outputId": "639c9cec-4ebd-4240-e119-1508feef5454"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       Birth Rate\n",
              "count  189.000000\n",
              "mean    20.214974\n",
              "std      9.945774\n",
              "min      5.900000\n",
              "25%     11.300000\n",
              "50%     17.950000\n",
              "75%     28.750000\n",
              "max     46.080000"
            ],
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              "\n",
              "\n",
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              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
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              "      <th></th>\n",
              "      <th>Birth Rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>189.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>20.214974</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>9.945774</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>5.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>11.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>17.950000</td>\n",
              "    </tr>\n",
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              "      <th>75%</th>\n",
              "      <td>28.750000</td>\n",
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              "    <tr>\n",
              "      <th>max</th>\n",
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              "    </g>\n",
              "</svg>\n",
              "      </button>\n",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "    background-color: #E8F0FE;\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart:hover {\n",
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              "\n",
              "    <script>\n",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
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              "    domScope.querySelector('#df-36eab374-d92b-4b19-b187-409cee6f5f85 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-9562c43b-f2c4-4d4f-bb62-988058364613 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-9562c43b-f2c4-4d4f-bb62-988058364613');\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"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "from sklearn.impute import SimpleImputer\n",
        "imp_mean = SimpleImputer(missing_values=np.nan, strategy='mean')\n",
        "columns = X.columns.append(y.columns)\n",
        "mean_imputed = imp_mean.fit_transform(X, y)\n",
        "df_mean_imputed = pd.DataFrame(mean_imputed, columns=X.columns)\n",
        "df_mean_imputed.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gQXcko__7nAQ",
        "outputId": "1edf7701-effe-4d31-ce9a-cb25728c3454"
      },
      "execution_count": 77,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 195 entries, 0 to 194\n",
            "Data columns (total 4 columns):\n",
            " #   Column                 Non-Null Count  Dtype  \n",
            "---  ------                 --------------  -----  \n",
            " 0   Density\n",
            "(P/Km2)        195 non-null    float64\n",
            " 1   Agricultural Land( %)  195 non-null    float64\n",
            " 2   Land Area(Km2)         195 non-null    float64\n",
            " 3   Armed Forces size      195 non-null    float64\n",
            "dtypes: float64(4)\n",
            "memory usage: 6.2 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "- ==TODO==: Explination"
      ],
      "metadata": {
        "id": "Ys3-8bLgKdNt"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Median"
      ],
      "metadata": {
        "id": "FvU6WJBw9LNP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "from sklearn.impute import SimpleImputer\n",
        "imp_mean = SimpleImputer(missing_values=np.nan, strategy='median')\n",
        "columns = X.columns.append(y.columns)\n",
        "mean_imputed = imp_mean.fit_transform(X, y)\n",
        "df_mean_imputed = pd.DataFrame(mean_imputed, columns=X.columns)\n",
        "df_mean_imputed.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O1oq-db5Ky2o",
        "outputId": "3fb309e2-362c-4662-d829-916b9eb24f10"
      },
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 195 entries, 0 to 194\n",
            "Data columns (total 4 columns):\n",
            " #   Column                 Non-Null Count  Dtype  \n",
            "---  ------                 --------------  -----  \n",
            " 0   Density\n",
            "(P/Km2)        195 non-null    float64\n",
            " 1   Agricultural Land( %)  195 non-null    float64\n",
            " 2   Land Area(Km2)         195 non-null    float64\n",
            " 3   Armed Forces size      195 non-null    float64\n",
            "dtypes: float64(4)\n",
            "memory usage: 6.2 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Most Frequent"
      ],
      "metadata": {
        "id": "6E9VuCIN9NsO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "from sklearn.impute import SimpleImputer\n",
        "imp_mean = SimpleImputer(missing_values=np.nan, strategy='most_frequent')\n",
        "columns = X.columns.append(y.columns)\n",
        "mean_imputed = imp_mean.fit_transform(X, y)\n",
        "df_mean_imputed = pd.DataFrame(mean_imputed, columns=X.columns)\n",
        "df_mean_imputed.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vXEC6lC-K36f",
        "outputId": "b99913b2-a5ba-469d-9f08-33dfb33b3eae"
      },
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 195 entries, 0 to 194\n",
            "Data columns (total 4 columns):\n",
            " #   Column                 Non-Null Count  Dtype  \n",
            "---  ------                 --------------  -----  \n",
            " 0   Density\n",
            "(P/Km2)        195 non-null    float64\n",
            " 1   Agricultural Land( %)  195 non-null    float64\n",
            " 2   Land Area(Km2)         195 non-null    float64\n",
            " 3   Armed Forces size      195 non-null    float64\n",
            "dtypes: float64(4)\n",
            "memory usage: 6.2 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Set Value"
      ],
      "metadata": {
        "id": "ZThX4rWC9Ugn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "from sklearn.impute import SimpleImputer\n",
        "imp_mean = SimpleImputer(missing_values=np.nan, strategy='constant', fill_value=20)\n",
        "columns = X.columns.append(y.columns)\n",
        "mean_imputed = imp_mean.fit_transform(X, y)\n",
        "df_mean_imputed = pd.DataFrame(mean_imputed, columns=X.columns)\n",
        "df_mean_imputed.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "543C5c95K-CM",
        "outputId": "a40546ca-7aef-4a4f-80d9-0e5289f2db3e"
      },
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 195 entries, 0 to 194\n",
            "Data columns (total 4 columns):\n",
            " #   Column                 Non-Null Count  Dtype  \n",
            "---  ------                 --------------  -----  \n",
            " 0   Density\n",
            "(P/Km2)        195 non-null    float64\n",
            " 1   Agricultural Land( %)  195 non-null    float64\n",
            " 2   Land Area(Km2)         195 non-null    float64\n",
            " 3   Armed Forces size      195 non-null    float64\n",
            "dtypes: float64(4)\n",
            "memory usage: 6.2 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Temporal\n",
        "\n",
        "- One of the best ways to manipulate temporal data is with a time series library like Darts\n",
        "- Using fill_missing_values function on the time series allows you to determine the type of fill\n",
        "- [darts](https://unit8co.github.io/darts/generated_api/darts.utils.missing_values.html?highlight=fill_missing_values#darts.utils.missing_values.fill_missing_values) link to the function.\n",
        "- can give a type of fit from [pandas_dataframe_interpolate](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.interpolate.html)"
      ],
      "metadata": {
        "id": "c86TLjfg83-0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install darts --quiet\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "n2t7hd5ssyt3",
        "outputId": "ab3ebda2-f60d-4222-d3c0-cd9ceb5a53d0"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m144.2/144.2 kB\u001b[0m \u001b[31m13.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m135.3/135.3 kB\u001b[0m \u001b[31m13.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Building wheel for pyod (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for fugue-sql-antlr (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%matplotlib inline\n",
        "\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "from darts import TimeSeries"
      ],
      "metadata": {
        "id": "tZ9-KOcTrM75"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from darts.utils.missing_values import fill_missing_values\n",
        "\n",
        "values = np.random.randint(50, size=50)\n",
        "df = pd.DataFrame({'values':values})\n",
        "df.head()\n",
        "\n",
        "df[20:25] = np.nan\n",
        "df[:5] = np.nan\n",
        "ts = TimeSeries.from_dataframe(df)\n",
        "ts.plot()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "id": "HWCyVJsdtTLf",
        "outputId": "523e76f4-2014-4f3b-adf9-726570836ae3"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Backfill - Linear"
      ],
      "metadata": {
        "id": "AL0VCk9jqCPm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame({'values':values})\n",
        "df[20:25] = np.nan\n",
        "df[:5] = np.nan\n",
        "ts = TimeSeries.from_dataframe(df)\n",
        "\n",
        "(ts - 20).plot(label=\"with missing values (shifted below)\")\n",
        "filled_series = fill_missing_values(ts, fit='linear', limit_direction='backward')\n",
        "filled_series.plot(label=\"without missing values\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 448
        },
        "id": "DFKSINkEteOg",
        "outputId": "0bda2d4e-603f-4765-b25d-1fbedc59ae95"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Fowardfill - Linear"
      ],
      "metadata": {
        "id": "xK-PI_0oxNrf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame({'values':values})\n",
        "df[20:25] = np.nan\n",
        "df[:5] = np.nan\n",
        "ts = TimeSeries.from_dataframe(df)\n",
        "\n",
        "(ts - 20).plot(label=\"with missing values (shifted below)\")\n",
        "filled_series = fill_missing_values(ts, fit='linear', limit_direction='forward')\n",
        "filled_series.plot(label=\"without missing values\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 448
        },
        "id": "2Zr7suLPxpQp",
        "outputId": "148ef1e4-59c1-4a32-e9ea-33b2b3d19aeb"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Both - Linear"
      ],
      "metadata": {
        "id": "6Bcf17P0xvvC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame({'values':values})\n",
        "df[20:25] = np.nan\n",
        "df[:5] = np.nan\n",
        "ts = TimeSeries.from_dataframe(df)\n",
        "\n",
        "(ts - 20).plot(label=\"with missing values (shifted below)\")\n",
        "filled_series = fill_missing_values(ts, method='linear')\n",
        "filled_series.plot(label=\"without missing values\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 448
        },
        "id": "7MpPM1y8xyiq",
        "outputId": "6269baed-f820-4143-f662-8f76f492bbe6"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Backfill - Polynomial"
      ],
      "metadata": {
        "id": "_CBiTtD3xUqW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame({'values':values})\n",
        "df[20:25] = np.nan\n",
        "df[:5] = np.nan\n",
        "ts = TimeSeries.from_dataframe(df)\n",
        "\n",
        "(ts - 20).plot(label=\"with missing values (shifted below)\")\n",
        "filled_series = fill_missing_values(ts, method='polynomial', limit_direction='backward', order=2)\n",
        "filled_series.plot(label=\"without missing values\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "I2-gBUB7yc55",
        "outputId": "0b9ad347-e48d-484b-f0f1-0adcb268bf11"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Forwardfill - Polynomial"
      ],
      "metadata": {
        "id": "FqX2fdObyU-B"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame({'values':values})\n",
        "df[20:25] = np.nan\n",
        "df[:5] = np.nan\n",
        "ts = TimeSeries.from_dataframe(df)\n",
        "\n",
        "(ts - 20).plot(label=\"with missing values (shifted below)\")\n",
        "filled_series = fill_missing_values(ts, method='polynomial', limit_direction='forward', order=2)\n",
        "filled_series.plot(label=\"without missing values\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "MMgzl82Ay1IN",
        "outputId": "2ac5e35e-255d-435a-d435-c5f9b33902d7"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Both - Polynomial"
      ],
      "metadata": {
        "id": "L3e3tcSlyZS6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame({'values':values})\n",
        "df[20:25] = np.nan\n",
        "df[:5] = np.nan\n",
        "ts = TimeSeries.from_dataframe(df)\n",
        "\n",
        "(ts - 20).plot(label=\"with missing values (shifted below)\")\n",
        "filled_series = fill_missing_values(ts, method='polynomial', order=2)\n",
        "filled_series.plot(label=\"without missing values\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 452
        },
        "id": "5Gcv4wJjy7LA",
        "outputId": "09547fb1-0b92-4b11-b4e6-fdfba1d9a969"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Categorical"
      ],
      "metadata": {
        "id": "La__yu8t80VN"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Mode imputation:\n",
        "- Replace the missing values with the most frequent value in the column. You can use the `SimpleImputer` class from sklearn to do this. Here's an example code snippet:\n"
      ],
      "metadata": {
        "id": "6roY_OPTMLpU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.impute import SimpleImputer\n",
        "\n",
        "imputer = SimpleImputer(strategy='most_frequent')\n",
        "df['column_name'] = imputer.fit_transform(df[['column_name']])\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "rHXIzF5483QB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# KNN imputation:\n",
        "Use K-Nearest Neighbors algorithm to fill in missing values. You can use the `KNNImputer` class from sklearn to do this. Here's an example code snippet:\n",
        "\n"
      ],
      "metadata": {
        "id": "BtTlOPogMbfr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.impute import KNNImputer\n",
        "\n",
        "imputer = KNNImputer(n_neighbors=5)\n",
        "df['column_name'] = imputer.fit_transform(df[['column_name']])"
      ],
      "metadata": {
        "id": "V3q9fkmuMg3c"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Multiple Imputation by Chained Equations (MICE):\n",
        "Use MICE algorithm to fill in missing values. You can use the `IterativeImputer` class from sklearn to do this. Here's an example code snippet:"
      ],
      "metadata": {
        "id": "Vr01GMynMmDj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.experimental import enable_iterative_imputer\n",
        "from sklearn.impute import IterativeImputer\n",
        "\n",
        "imputer = IterativeImputer()\n",
        "df['column_name'] = imputer.fit_transform(df[['column_name']])"
      ],
      "metadata": {
        "id": "DtCh7t6SMs3Q"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}