Analysis_of_Global_Educational_Inequality.ipynb

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        "### Technical Report: Analysis of Global Educational Inequality\n",
        "\n",
        "#### Objective\n",
        "The objective of this analysis is to explore global educational inequality trends from 2010 to 2021, examining how disparities vary across countries and regions. By identifying key patterns and relationships, this report aims to shed light on the factors contributing to these inequalities and inform policy efforts to reduce them.\n",
        "\n",
        "#### Dataset Overview\n",
        "The dataset utilized in this analysis is titled *Inequality in Education Around the World*, encompassing historical data on educational inequality indicators from 2010 to 2021. The dataset includes 195 countries and features columns such as:\n",
        "\n",
        "- **ISO3**: Country code.\n",
        "- **Country**: Name of the country.\n",
        "- **Human Development Groups**: Categorization by development level (e.g., Low, Medium, High, Very High).\n",
        "- **UNDP Developing Regions**: Regional grouping (e.g., Sub-Saharan Africa (SSA), Latin America and the Caribbean (LAC)).\n",
        "- **HDI Rank (2021)**: Human Development Index rank for 2021.\n",
        "- **Inequality in Education (2010-2021)**: Yearly educational inequality scores.\n",
        "\n",
        "#### Exploratory Data Analysis (EDA)\n",
        "The dataset analysis began with an inspection of the data structure, types, and completeness. A heatmap visualized missing values, revealing incomplete data across several years for specific countries and columns.\n",
        "\n",
        "##### Global Trends in Educational Inequality (2010-2021)\n",
        "A line plot was used to depict the global average of educational inequality over the 12-year period. This visualization showed that while some fluctuation exists, there is a general downward trend, indicating improvements in educational access and quality in many parts of the world. The confidence interval represented by the shaded region displayed variations in inequality scores.\n",
        "\n",
        "##### Regional Disparities in Educational Inequality (2021)\n",
        "Two specific analyses were conducted for 2021:\n",
        "1. **Box Plot by UNDP Regions**:\n",
        "   - **Findings**: Sub-Saharan Africa (SSA) and South Asia (SA) regions displayed higher median educational inequality. In contrast, regions like Europe and Central Asia (ECA) had lower medians, indicating better education equity.\n",
        "   - **Implications**: These findings highlight the need for focused educational interventions in lower-performing regions.\n",
        "\n",
        "2. **Violin Plot by Human Development Groups**:\n",
        "   - **Findings**: Countries in the \"Low\" human development group exhibited significant variability and higher median educational inequality. \"Very High\" development groups consistently had lower inequality scores, emphasizing the link between socioeconomic development and access to quality education.\n",
        "   - **Implications**: Reducing educational disparities may require multi-faceted approaches that address broader social and economic inequalities.\n",
        "\n",
        "##### Correlation Analysis: HDI Rank and Educational Inequality (2021)\n",
        "A scatter plot was used to analyze the relationship between the 2021 HDI rank and educational inequality:\n",
        "- **Observations**: Higher HDI-ranked countries (those with lower numerical values) generally had lower educational inequality. The scatter plot, with countries color-coded by region, illustrated that regions like SSA and SA clustered at higher inequality levels, while ECA and East Asia and the Pacific (EAP) tended to perform better.\n",
        "- **Conclusion**: This analysis confirms that educational inequality is closely linked to a country's overall human development, suggesting that policies improving economic and social development can also lead to more equitable educational outcomes.\n",
        "\n",
        "#### Insights and Key Observations\n",
        "1. **Overall Improvement**: The global trend indicates progress, with many countries showing reductions in educational inequality over the past decade.\n",
        "2. **Regional Disparities**: Sub-Saharan Africa and South Asia have the highest educational inequality, pointing to persistent challenges in access and quality. This underscores the importance of targeted educational investments and reforms.\n",
        "3. **Impact of Development Level**: Countries classified under \"Very High\" human development consistently display lower educational inequality, suggesting that development and education are interlinked.\n",
        "4. **HDI and Education**: The strong inverse relationship between HDI rank and educational inequality highlights the importance of integrated policy approaches that address both economic development and education.\n",
        "\n",
        "\n",
        "#### Conclusion\n",
        "The analysis provided a comprehensive overview of global educational inequality from 2010 to 2021, underscoring significant regional disparities and the role of human development. Addressing educational inequality requires holistic approaches that encompass not only educational policies but also broader socioeconomic development efforts.\n",
        "\n",
        "\n",
        "### Reference\n",
        "\n",
        " - https://www.kaggle.com/datasets/iamsouravbanerjee/inequality-in-education-around-the-world/data"
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        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "### setting the seaborn style for visualizations\n",
        "sns.set(style=\"whitegrid\")\n",
        "\n",
        "### loading the dataset from the uploaded file\n",
        "file_path = 'Inequality in Education.csv'\n",
        "data = pd.read_csv(file_path)\n",
        "\n",
        "### displaying the first few rows of the dataset to understand its structure\n",
        "data.head()"
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              "  ISO3               Country Human Development Groups UNDP Developing Regions  \\\n",
              "0  AFG           Afghanistan                      Low                      SA   \n",
              "1  AGO                Angola                   Medium                     SSA   \n",
              "2  ALB               Albania                     High                     ECA   \n",
              "3  AND               Andorra                Very High                     NaN   \n",
              "4  ARE  United Arab Emirates                Very High                      AS   \n",
              "\n",
              "   HDI Rank (2021)  Inequality in Education (2010)  \\\n",
              "0            180.0                       42.809000   \n",
              "1            148.0                             NaN   \n",
              "2             67.0                       11.900000   \n",
              "3             40.0                       15.160302   \n",
              "4             26.0                             NaN   \n",
              "\n",
              "   Inequality in Education (2011)  Inequality in Education (2012)  \\\n",
              "0                       44.823380                       44.823380   \n",
              "1                             NaN                             NaN   \n",
              "2                       11.900000                       11.900000   \n",
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              "4                             NaN                             NaN   \n",
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              "   Inequality in Education (2013)  Inequality in Education (2014)  \\\n",
              "0                       44.823380                       44.823380   \n",
              "1                             NaN                             NaN   \n",
              "2                       11.900000                       11.900000   \n",
              "3                       15.160302                        9.965681   \n",
              "4                             NaN                             NaN   \n",
              "\n",
              "   Inequality in Education (2015)  Inequality in Education (2016)  \\\n",
              "0                       45.365170                       45.365170   \n",
              "1                       34.171440                       34.171440   \n",
              "2                       11.900000                       11.900000   \n",
              "3                       10.083815                       10.008154   \n",
              "4                             NaN                       18.241437   \n",
              "\n",
              "   Inequality in Education (2017)  Inequality in Education (2018)  \\\n",
              "0                       45.365170                       45.365170   \n",
              "1                       34.171440                       34.171440   \n",
              "2                       12.333440                       12.333440   \n",
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              "4                       14.475335                       12.634355   \n",
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              "   Inequality in Education (2019)  Inequality in Education (2020)  \\\n",
              "0                       45.365170                       45.365170   \n",
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              "2                       12.333440                       12.333440   \n",
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              "   Inequality in Education (2021)  \n",
              "0                       45.365170  \n",
              "1                       34.171440  \n",
              "2                       12.333440  \n",
              "3                       10.008154  \n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-da13309e-5b0d-492a-8c4f-7fa60cfa0b45 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "data",
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 195,\n  \"fields\": [\n    {\n      \"column\": \"ISO3\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 195,\n        \"samples\": [\n          \"PHL\",\n          \"BGR\",\n          \"SLE\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Country\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 195,\n        \"samples\": [\n          \"Philippines\",\n          \"Bulgaria\",\n          \"Sierra Leone\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Human Development Groups\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Medium\",\n          \"Very High\",\n          \"Low\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"UNDP Developing Regions\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"SA\",\n          \"SSA\",\n          \"EAP\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"HDI Rank (2021)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 55.307333417801125,\n        \"min\": 1.0,\n        \"max\": 191.0,\n        \"num_unique_values\": 162,\n        \"samples\": [\n          111.0,\n          185.0,\n          170.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2010)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14.39255216762455,\n        \"min\": 1.32297,\n        \"max\": 48.723,\n        \"num_unique_values\": 136,\n        \"samples\": [\n          3.573789055,\n          10.48157,\n          6.587\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2011)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14.34249897115697,\n        \"min\": 1.38564,\n        \"max\": 48.723,\n        \"num_unique_values\": 150,\n        \"samples\": [\n          24.47025119,\n          21.6249,\n          12.21469479\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2012)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14.305732311105848,\n        \"min\": 1.39045,\n        \"max\": 48.723,\n        \"num_unique_values\": 157,\n        \"samples\": [\n          26.71518884,\n          2.05054,\n          26.81536\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2013)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14.470344412689688,\n        \"min\": 0.779396797,\n        \"max\": 49.32129,\n        \"num_unique_values\": 165,\n        \"samples\": [\n          19.992,\n          30.54286069,\n          11.55614286\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2014)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14.3507587893155,\n        \"min\": 0.765510466,\n        \"max\": 49.32129,\n        \"num_unique_values\": 168,\n        \"samples\": [\n          39.55255,\n          32.95967,\n          16.08547\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2015)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14.474999584656873,\n        \"min\": 0.757375436,\n        \"max\": 49.32129,\n        \"num_unique_values\": 168,\n        \"samples\": [\n          9.26056,\n          45.11142,\n          12.51679831\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2016)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14.479261184912843,\n        \"min\": 0.724853929,\n        \"max\": 49.32129,\n        \"num_unique_values\": 168,\n        \"samples\": [\n          47.29928,\n          11.68,\n          44.39953\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2017)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14.558071530271988,\n        \"min\": 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]\n}"
            }
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "### inspecting the dataset to identify missing values and data types\n",
        "data.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5LrBFbWZ-NyF",
        "outputId": "0e3a8537-d090-4501-c0d0-14b55c30deae"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 195 entries, 0 to 194\n",
            "Data columns (total 17 columns):\n",
            " #   Column                          Non-Null Count  Dtype  \n",
            "---  ------                          --------------  -----  \n",
            " 0   ISO3                            195 non-null    object \n",
            " 1   Country                         195 non-null    object \n",
            " 2   Human Development Groups        191 non-null    object \n",
            " 3   UNDP Developing Regions         151 non-null    object \n",
            " 4   HDI Rank (2021)                 191 non-null    float64\n",
            " 5   Inequality in Education (2010)  137 non-null    float64\n",
            " 6   Inequality in Education (2011)  150 non-null    float64\n",
            " 7   Inequality in Education (2012)  157 non-null    float64\n",
            " 8   Inequality in Education (2013)  165 non-null    float64\n",
            " 9   Inequality in Education (2014)  168 non-null    float64\n",
            " 10  Inequality in Education (2015)  168 non-null    float64\n",
            " 11  Inequality in Education (2016)  168 non-null    float64\n",
            " 12  Inequality in Education (2017)  168 non-null    float64\n",
            " 13  Inequality in Education (2018)  172 non-null    float64\n",
            " 14  Inequality in Education (2019)  174 non-null    float64\n",
            " 15  Inequality in Education (2020)  176 non-null    float64\n",
            " 16  Inequality in Education (2021)  176 non-null    float64\n",
            "dtypes: float64(13), object(4)\n",
            "memory usage: 26.0+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "### checking basic statistics of the dataset\n",
        "data.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 352
        },
        "id": "v-3zO9xZ-Qeg",
        "outputId": "299bb8ba-03e5-4ee9-8a52-1f7de15299b9"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       HDI Rank (2021)  Inequality in Education (2010)  \\\n",
              "count       191.000000                      137.000000   \n",
              "mean         95.811518                       20.654419   \n",
              "std          55.307333                       14.392552   \n",
              "min           1.000000                        1.322970   \n",
              "25%          48.500000                        6.917102   \n",
              "50%          96.000000                       17.825000   \n",
              "75%         143.500000                       30.542861   \n",
              "max         191.000000                       48.723000   \n",
              "\n",
              "       Inequality in Education (2011)  Inequality in Education (2012)  \\\n",
              "count                      150.000000                      157.000000   \n",
              "mean                        19.991823                       19.473658   \n",
              "std                         14.342499                       14.305732   \n",
              "min                          1.385640                        1.390450   \n",
              "25%                          6.119250                        6.011760   \n",
              "50%                         17.312742                       16.421150   \n",
              "75%                         30.176057                       30.201410   \n",
              "max                         48.723000                       48.723000   \n",
              "\n",
              "       Inequality in Education (2013)  Inequality in Education (2014)  \\\n",
              "count                      165.000000                      168.000000   \n",
              "mean                        19.258472                       19.135457   \n",
              "std                         14.470344                       14.350759   \n",
              "min                          0.779397                        0.765510   \n",
              "25%                          5.605950                        6.127907   \n",
              "50%                         16.060770                       15.957630   \n",
              "75%                         30.542861                       30.564901   \n",
              "max                         49.321290                       49.321290   \n",
              "\n",
              "       Inequality in Education (2015)  Inequality in Education (2016)  \\\n",
              "count                      168.000000                      168.000000   \n",
              "mean                        19.133751                       18.853851   \n",
              "std                         14.475000                       14.479261   \n",
              "min                          0.757375                        0.724854   \n",
              "25%                          6.209205                        6.130745   \n",
              "50%                         15.344075                       14.461598   \n",
              "75%                         29.686837                       29.647365   \n",
              "max                         49.321290                       49.321290   \n",
              "\n",
              "       Inequality in Education (2017)  Inequality in Education (2018)  \\\n",
              "count                      168.000000                      172.000000   \n",
              "mean                        18.649140                       18.396401   \n",
              "std                         14.558072                       14.546446   \n",
              "min                          0.724854                        0.550110   \n",
              "25%                          5.591175                        5.854422   \n",
              "50%                         14.292875                       13.565415   \n",
              "75%                         29.647365                       29.326065   \n",
              "max                         49.321290                       50.124110   \n",
              "\n",
              "       Inequality in Education (2019)  Inequality in Education (2020)  \\\n",
              "count                      174.000000                      176.000000   \n",
              "mean                        18.212993                       18.006314   \n",
              "std                         14.553003                       14.569313   \n",
              "min                          0.550110                        0.550110   \n",
              "25%                          5.618515                        5.518733   \n",
              "50%                         13.263530                       12.843558   \n",
              "75%                         29.303075                       28.335352   \n",
              "max                         50.124110                       50.124110   \n",
              "\n",
              "       Inequality in Education (2021)  \n",
              "count                      176.000000  \n",
              "mean                        18.006314  \n",
              "std                         14.569313  \n",
              "min                          0.550110  \n",
              "25%                          5.518733  \n",
              "50%                         12.843558  \n",
              "75%                         28.335352  \n",
              "max                         50.124110  "
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              "      <th>HDI Rank (2021)</th>\n",
              "      <th>Inequality in Education (2010)</th>\n",
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              "      <th>Inequality in Education (2019)</th>\n",
              "      <th>Inequality in Education (2020)</th>\n",
              "      <th>Inequality in Education (2021)</th>\n",
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              "      <th>count</th>\n",
              "      <td>191.000000</td>\n",
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              "      <th>mean</th>\n",
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              "      <td>19.991823</td>\n",
              "      <td>19.473658</td>\n",
              "      <td>19.258472</td>\n",
              "      <td>19.135457</td>\n",
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              "      <td>18.396401</td>\n",
              "      <td>18.212993</td>\n",
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              "      <td>14.392552</td>\n",
              "      <td>14.342499</td>\n",
              "      <td>14.305732</td>\n",
              "      <td>14.470344</td>\n",
              "      <td>14.350759</td>\n",
              "      <td>14.475000</td>\n",
              "      <td>14.479261</td>\n",
              "      <td>14.558072</td>\n",
              "      <td>14.546446</td>\n",
              "      <td>14.553003</td>\n",
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              "      <td>0.724854</td>\n",
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              "      <td>0.550110</td>\n",
              "      <td>0.550110</td>\n",
              "      <td>0.550110</td>\n",
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              "      <th>25%</th>\n",
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              "      <td>6.917102</td>\n",
              "      <td>6.119250</td>\n",
              "      <td>6.011760</td>\n",
              "      <td>5.605950</td>\n",
              "      <td>6.127907</td>\n",
              "      <td>6.209205</td>\n",
              "      <td>6.130745</td>\n",
              "      <td>5.591175</td>\n",
              "      <td>5.854422</td>\n",
              "      <td>5.618515</td>\n",
              "      <td>5.518733</td>\n",
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              "      <td>17.312742</td>\n",
              "      <td>16.421150</td>\n",
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              "      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-be667920-8558-4dad-88fc-f2672f7ca6cb 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-be667920-8558-4dad-88fc-f2672f7ca6cb');\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",
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              "\n",
              "\n",
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              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-335864ef-3488-4fcc-8753-23a1e2fb0189')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
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              "    </g>\n",
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              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
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              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-335864ef-3488-4fcc-8753-23a1e2fb0189 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"HDI Rank (2021)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 68.53291427656428,\n        \"min\": 1.0,\n        \"max\": 191.0,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          191.0,\n          95.81151832460733,\n          96.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2010)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 43.84968177551575,\n        \"min\": 1.32297,\n        \"max\": 137.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          20.654418955291973,\n          17.825,\n          137.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2011)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 48.34005812683905,\n        \"min\": 1.38564,\n        \"max\": 150.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          19.99182290426,\n          17.31274219,\n          150.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2012)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 50.78932364588883,\n        \"min\": 1.39045,\n        \"max\": 157.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          19.47365799370064,\n          16.42115,\n          157.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2013)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 53.62921888198947,\n        \"min\": 0.779396797,\n        \"max\": 165.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          19.25847161108485,\n          16.06077,\n          165.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2014)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 54.62431069366273,\n        \"min\": 0.765510466,\n        \"max\": 168.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          19.13545693755952,\n          15.957630000000002,\n          168.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2015)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 54.66450420260892,\n        \"min\": 0.757375436,\n        \"max\": 168.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          19.13375134389881,\n          15.344075414999999,\n          168.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2016)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 54.741172707056236,\n        \"min\": 0.724853929,\n        \"max\": 168.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          18.85385136647619,\n          14.46159771,\n          168.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2017)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 54.80148840187127,\n        \"min\": 0.724853929,\n        \"max\": 168.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          18.649139963583334,\n          14.292875245000001,\n          168.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2018)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 56.24622709543404,\n        \"min\": 0.550110115,\n        \"max\": 172.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          18.396400748918605,\n          13.565415315,\n          172.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2019)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 56.9743494211281,\n        \"min\": 0.550110115,\n        \"max\": 174.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          18.212992962971263,\n          13.26353,\n          174.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2020)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 57.722295165482905,\n        \"min\": 0.550110115,\n        \"max\": 176.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          18.006313952028407,\n          12.843557635,\n          176.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Inequality in Education (2021)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 57.722295165482905,\n        \"min\": 0.550110115,\n        \"max\": 176.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          18.006313952028407,\n          12.843557635,\n          176.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The dataset contains 195 entries and 17 columns, with a mix of complete and missing data for various years of \"Inequality in Education\" and other attributes."
      ],
      "metadata": {
        "id": "dwW0Khm6-5Uf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "### visualizing missing data using a heatmap\n",
        "plt.figure(figsize=(14, 8))\n",
        "sns.heatmap(data.isnull(), cbar=False, cmap='viridis')\n",
        "plt.title('Heatmap of Missing Values in the Dataset')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 919
        },
        "id": "7bb6i5xf-TI2",
        "outputId": "53d951ae-9a94-4968-cd4f-1f3ec953dbe5"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1400x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "### reshaping the dataset for analysis\n",
        "years = [str(year) for year in range(2010, 2022)]\n",
        "data_long = data.melt(\n",
        "    id_vars=[\"Country\", \"ISO3\", \"Human Development Groups\", \"UNDP Developing Regions\", \"HDI Rank (2021)\"],\n",
        "    value_vars=[f\"Inequality in Education ({year})\" for year in years],\n",
        "    var_name=\"Year\", value_name=\"Inequality in Education\"\n",
        ")"
      ],
      "metadata": {
        "id": "X3wM0JeY-XFQ"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "### converting 'Year' to a numerical format\n",
        "data_long['Year'] = data_long['Year'].str.extract('(\\d+)').astype(int)\n",
        "\n",
        "### plotting global average trend of educational inequality over time\n",
        "plt.figure(figsize=(12, 6))\n",
        "sns.lineplot(data=data_long, x='Year', y='Inequality in Education', estimator='mean', ci='sd')\n",
        "plt.title('Global Average Educational Inequality Trend (2010-2021)')\n",
        "plt.ylabel('Inequality in Education (Mean)')\n",
        "plt.xlabel('Year')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 660
        },
        "id": "AFOZ20NX-aH4",
        "outputId": "68a00366-727c-4eaa-cf9d-183288b8a515"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-8-df51336f2f70>:6: FutureWarning: \n",
            "\n",
            "The `ci` parameter is deprecated. Use `errorbar='sd'` for the same effect.\n",
            "\n",
            "  sns.lineplot(data=data_long, x='Year', y='Inequality in Education', estimator='mean', ci='sd')\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The line plot displays the global average trend of educational inequality from 2010 to 2021, along with a confidence interval for the standard deviation. This visualization highlights general patterns and changes over time, indicating whether inequality in education has been increasing, decreasing, or remaining stable. Overall, we can observe a slight decline in Inequality in Education during this period."
      ],
      "metadata": {
        "id": "V11ztXpk_LHJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "### visualizing educational inequality by UNDP Developing Regions for 2021\n",
        "plt.figure(figsize=(14, 8))\n",
        "sns.boxplot(data=data_long[data_long['Year'] == 2021],\n",
        "            x='UNDP Developing Regions', y='Inequality in Education')\n",
        "plt.title('Educational Inequality by UNDP Developing Regions in 2021')\n",
        "plt.ylabel('Inequality in Education (2021)')\n",
        "plt.xlabel('Region')\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 744
        },
        "id": "ObHyoN3S-knl",
        "outputId": "9d3bef50-3115-459f-db7c-63c479311c76"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1400x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "(From the box plot) Educational Inequality by UNDP Developing Regions:\n",
        "\n",
        " - Regions such as Sub-Saharan Africa (SSA) and South Asia (SA) show higher median levels of educational inequality.\n",
        " - Europe and Central Asia (ECA) and East Asia and the Pacific (EAP) tend to have lower median inequality, indicating better access and quality of education."
      ],
      "metadata": {
        "id": "aLRLSWHa_v3A"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "### comparing inequality based on human development groups in 2021\n",
        "plt.figure(figsize=(14, 8))\n",
        "sns.violinplot(data=data_long[data_long['Year'] == 2021],\n",
        "               x='Human Development Groups', y='Inequality in Education')\n",
        "plt.title('Educational Inequality by Human Development Groups in 2021')\n",
        "plt.ylabel('Inequality in Education (2021)')\n",
        "plt.xlabel('Human Development Group')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 727
        },
        "id": "Mcthm18j-p0c",
        "outputId": "72d9e18c-40f8-4ecb-da9b-247e4b65ede3"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1400x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "(From the violin plot) Educational Inequality by Human Development Groups:\n",
        "\n",
        " - Countries in the \"Low\" human development group display higher variability and higher average educational inequality.\n",
        " - \"Very High\" development groups show significantly lower levels of educational inequality, highlighting the disparities between groups with different developmental levels."
      ],
      "metadata": {
        "id": "X0EGZn5SAFco"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "### scatter plot to show the correlation between HDI Rank and educational inequality in 2021\n",
        "plt.figure(figsize=(12, 8))\n",
        "sns.scatterplot(data=data, x='HDI Rank (2021)', y='Inequality in Education (2021)',\n",
        "                hue='UNDP Developing Regions', palette='Set2', alpha=0.7)\n",
        "plt.title('Correlation Between HDI Rank and Educational Inequality (2021)')\n",
        "plt.xlabel('HDI Rank (2021)')\n",
        "plt.ylabel('Inequality in Education (2021)')\n",
        "plt.gca().invert_xaxis()  ### inverting the x-axis for a more intuitive view (higher HDI rank = lower development)\n",
        "plt.legend(title='Region', bbox_to_anchor=(1.05, 1), loc='upper left')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 727
        },
        "id": "cQl3NxoQ-soD",
        "outputId": "61845aaf-1100-4e2a-9193-4cb736634418"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x800 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "The scatter plot illustrates the relationship between the Human Development Index (HDI) rank and educational inequality in 2021.\n",
        "\n",
        " - General Observation: Countries with higher HDI ranks (lower numerical value) tend to have lower educational inequality, indicating that more developed countries usually have better educational access and quality.\n",
        " - Regional Insights: The markers, colored by region, show distinct clusters, with regions like Sub-Saharan Africa and South Asia displaying higher educational inequality for lower HDI ranks, while Europe and Central Asia generally have lower inequality for higher HDI ranks."
      ],
      "metadata": {
        "id": "R_6ZqxvIAWTp"
      }
    }
  ]
}