ANES 2024 graphs

anes_2024_data.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "collapsed_sections": [
        "ZFX8OuQuV8YW",
        "HVi_0IZRak0b"
      ]
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "!unzip anes_timeseries_2024_csv_20250219.zip -d /content/"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AEvRmd_LeCqI",
        "outputId": "08eaf6d3-d907-4462-b360-658119f89419"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  anes_timeseries_2024_csv_20250219.zip\n",
            "  inflating: /content/anes_timeseries_2024_csv_20250219.csv  \n",
            "  inflating: /content/anes_timeseries_2024_userguidecodebook_20250219.pdf  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "df = pd.read_csv('/content/anes_timeseries_2024_csv_20250219.csv')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qh7tMBgXd8ED",
        "outputId": "b9db48a2-e7e8-438c-a19b-627c9e1ebb80"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-3-fc8fb15f58d5>:3: DtypeWarning: Columns (6,7,8,12,13,14,15,16,17,705,706) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv('/content/anes_timeseries_2024_csv_20250219.csv')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Latinos for or against increased border funding?\n"
      ],
      "metadata": {
        "id": "ZFX8OuQuV8YW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "# Filter for Latino respondents\n",
        "latino_df = df[df['V241499'] == 1]\n",
        "\n",
        "x_value_labels = {\n",
        "    -9: 'Refused',\n",
        "    -8: 'Don’t know',\n",
        "    -1: 'Inapplicable',\n",
        "     1: 'Increased',\n",
        "     2: 'Decreased',\n",
        "     3: 'Kept the same',\n",
        "}\n",
        "\n",
        "# Remove missing values\n",
        "latino_df = latino_df[latino_df['V241267'].isin(x_value_labels.keys())]\n",
        "\n",
        "# Count occurrences and calculate percentages\n",
        "value_counts = latino_df['V241267'].value_counts(normalize=True) * 100  # Convert to percentage\n",
        "\n",
        "# Convert index to meaningful labels\n",
        "value_counts.index = value_counts.index.map(x_value_labels)\n",
        "\n",
        "# Create figure\n",
        "plt.figure(figsize=(10, 6))\n",
        "ax = sns.barplot(x=value_counts.index, y=value_counts.values, palette=\"Blues\")\n",
        "\n",
        "# Add annotations (percentage values) on bars\n",
        "for p in ax.patches:\n",
        "    ax.annotate(f'{p.get_height():.1f}%',\n",
        "                (p.get_x() + p.get_width() / 2., p.get_height()),\n",
        "                ha='center', va='bottom', fontsize=10)\n",
        "\n",
        "# Titles and labels\n",
        "plt.title('Latino Support for Border Security Funding')\n",
        "plt.xlabel('Should federal spending on tightening border security to prevent illegal immigration be increased, decreased, or kept the same?')\n",
        "plt.ylabel('Percentage of Respondents')\n",
        "plt.xticks(rotation=45, ha='right')  # Rotate labels for readability\n",
        "\n",
        "# Add source text\n",
        "ax.text(0.95, 0.99, 'Stabs', ha='left', va='top', transform=ax.transAxes)\n",
        "ax.text(0, -0.4, 'American National Election Studies. 2025. \\nANES 2024 Time Series Study Preliminary Release: Pre-Election Data [dataset and documentation]. \\nFebruary 19, 2025 version. www.electionstudies.org',\n",
        "        ha='left', va='center_baseline', transform=ax.transAxes, fontsize=8)\n",
        "ax.text(0.95, 0.89, 'n = ' + str(len(latino_df)), ha='right', va='top', transform=ax.transAxes)\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 649
        },
        "id": "yU9DKrNbWerW",
        "outputId": "5d4eb155-2d67-430d-8bd4-858b31cdea70"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-26-de9488d63263>:27: FutureWarning: \n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "  ax = sns.barplot(x=value_counts.index, y=value_counts.values, palette=\"Blues\")\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Latino political leanings"
      ],
      "metadata": {
        "id": "HVi_0IZRak0b"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "blue_shades = sns.color_palette(\"Blues\", n_colors=3)\n",
        "purple = ['#800080']\n",
        "red_shades = sns.color_palette(\"Reds\", n_colors=3)\n",
        "custom_palette = blue_shades + purple + red_shades\n",
        "\n",
        "latino_df = df[df['V241499'] == 1]\n",
        "\n",
        "lcself_labels = {\n",
        "    1: 'Very liberal',\n",
        "    2: 'Somewhat Liberal',\n",
        "    3: 'Closer to liberals',\n",
        "    4: 'Neither liberal nor conservative',\n",
        "    5: 'Closer to conservatives',\n",
        "    6: 'Somewhat Conservative',\n",
        "    7: 'Very Conservative',\n",
        "    99: 'No Opinion'\n",
        "}\n",
        "\n",
        "# Remove missing values\n",
        "latino_df = latino_df[latino_df['V241177'].isin(lcself_labels.keys())]\n",
        "\n",
        "# Count occurrences and calculate percentages\n",
        "value_counts = latino_df['V241177'].value_counts(normalize=True) * 100\n",
        "\n",
        "# Convert index to meaningful labels\n",
        "value_counts.index = value_counts.index.map(lcself_labels)\n",
        "\n",
        "# Define category order\n",
        "ordered_labels = [\n",
        "    'Very liberal', 'Somewhat Liberal', 'Closer to liberals',\n",
        "    'Neither liberal nor conservative', 'Closer to conservatives',\n",
        "    'Somewhat Conservative', 'Very Conservative', 'No Opinion'\n",
        "]\n",
        "\n",
        "# Convert index to categorical type to enforce order\n",
        "value_counts = value_counts.reindex(ordered_labels)\n",
        "\n",
        "plt.figure(figsize=(12, 6))\n",
        "ax = sns.barplot(x=value_counts.index, y=value_counts.values, palette=custom_palette, order=ordered_labels)\n",
        "\n",
        "# Add annotations (percentage values) on bars\n",
        "for p in ax.patches:\n",
        "    ax.annotate(f'{p.get_height():.1f}%',\n",
        "                (p.get_x() + p.get_width() / 2., p.get_height()),\n",
        "                ha='center', va='bottom', fontsize=10)\n",
        "\n",
        "plt.title('Latino Political Leanings')\n",
        "plt.xlabel('Political Leaning')\n",
        "plt.ylabel('Percentage of Respondents')\n",
        "plt.xticks(rotation=45, ha='right')\n",
        "\n",
        "# Add source text\n",
        "ax.text(0, -0.4, 'American National Election Studies. 2025. \\nANES 2024 Time Series Study Preliminary Release: Pre-Election Data [dataset and documentation]. \\nFebruary 19, 2025 version. www.electionstudies.org',\n",
        "        ha='left', va='center_baseline', transform=ax.transAxes, fontsize=8)\n",
        "ax.text(0.001, 0.98, 'Stabs',\n",
        "        ha='left', va='center_baseline', transform=ax.transAxes, fontsize=8)\n",
        "ax.text(0.95, 0.99, 'n = ' + str(len(latino_df)), ha='right', va='top', transform=ax.transAxes)\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 743
        },
        "id": "wnu84YuobtgH",
        "outputId": "b43f6a7e-be17-4d44-c738-2c0015656bbe"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-41-1a018c2dd503>:43: FutureWarning: \n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "  ax = sns.barplot(x=value_counts.index, y=value_counts.values, palette=custom_palette, order=ordered_labels)\n",
            "<ipython-input-41-1a018c2dd503>:43: UserWarning: \n",
            "The palette list has fewer values (7) than needed (8) and will cycle, which may produce an uninterpretable plot.\n",
            "  ax = sns.barplot(x=value_counts.index, y=value_counts.values, palette=custom_palette, order=ordered_labels)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "RZJdJLMsd68t",
        "outputId": "54efe5d9-e6c1-4df6-f44e-bf5a55ea4ba1"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x1100 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import pandas as pd\n",
        "\n",
        "\n",
        "ideology = 'V241177'\n",
        "compared_value = 'V241373'\n",
        "\n",
        "# Remove refused, error, and haven't thought much about it\n",
        "df =  df[~df[ideology].isin([-4, -9, 99])]\n",
        "\n",
        "\n",
        "# Define color palette\n",
        "blue_shades = sns.color_palette(\"Blues\", n_colors=3)\n",
        "purple = ['#800080']\n",
        "red_shades = sns.color_palette(\"Reds\", n_colors=3)\n",
        "custom_palette = blue_shades + purple + red_shades\n",
        "\n",
        "# Create figure\n",
        "plt.figure(figsize=(15, 11))\n",
        "\n",
        "# Normalize counts within each pcorrect group\n",
        "counts = df.groupby([compared_value, ideology]).size().reset_index(name='count')\n",
        "total_per_pcorrect = df.groupby(compared_value).size().reset_index(name='total')\n",
        "counts = counts.merge(total_per_pcorrect, on=compared_value)\n",
        "counts['percentage'] = (counts['count'] / counts['total']) * 100  # Convert to percentage\n",
        "\n",
        "# Plot using normalized percentages instead of raw counts\n",
        "ax = sns.barplot(\n",
        "    x=compared_value, y='percentage', hue=ideology, data=counts, palette=custom_palette\n",
        ")\n",
        "\n",
        "# Set labels and title\n",
        "plt.title('Distribution of Answers by Political Ideology')\n",
        "plt.xlabel(' FAVOR OR OPPOSE BANNING TRANSGEDER GIRLS FROM PARTICIPATING IN K-12 GIRLS SPORT')\n",
        "plt.ylabel('Percentage within Each Response Group')\n",
        "\n",
        "# Define x-axis labels\n",
        "\n",
        "x_value_labels = {\n",
        "    -9: 'Refused',\n",
        "    -8: 'Don’t know',\n",
        "    -1: 'Inapplicable',\n",
        "     1: 'Favor',\n",
        "     2: 'Oppose',\n",
        "     3: 'Neither favor nor oppose'\n",
        "}\n",
        "\n",
        "plt.xticks(ticks=range(len(x_value_labels)), labels=list(x_value_labels.values()))\n",
        "\n",
        "# Define ideological labels\n",
        "lcself_labels = {\n",
        "    1: 'Very liberal',\n",
        "    2: 'Somewhat Liberal',\n",
        "    3: 'Closer to liberals',\n",
        "    4: 'Neither liberal nor conservative',\n",
        "    5: 'Closer to conservatives',\n",
        "    6: 'Somewhat Conservative',\n",
        "    7: 'Very Conservative',\n",
        "    -9: 'Refused',\n",
        "    -4: 'Error',\n",
        "    99: 'Haven’t thought much about it'\n",
        "}\n",
        "\n",
        "# Update legend with ideological labels\n",
        "handles, labels = plt.gca().get_legend_handles_labels()\n",
        "plt.legend(handles, [lcself_labels[int(label)] for label in labels], title='Ideological Bias')\n",
        "\n",
        "\n",
        "# Add annotations for each bar\n",
        "for p in ax.patches:\n",
        "    height = p.get_height()\n",
        "    if height > 0:  # Only annotate non-zero bars\n",
        "        x_pos = p.get_x()\n",
        "        width = p.get_width()\n",
        "\n",
        "        # Find the corresponding percentage\n",
        "        percentage_value = height  # Since y-axis is now percentage\n",
        "\n",
        "        # Annotate with percentage\n",
        "        ax.text(x_pos + width / 2, height, f'{percentage_value:.1f}%',\n",
        "                ha='center', va='bottom', fontsize=8)\n",
        "\n",
        "# Add source text\n",
        "ax.text(0, -0.1, 'American National Election Studies. 2025. \\nANES 2024 Time Series Study Preliminary Release: Pre-Election Data [dataset and documentation]. \\nFebruary 19, 2025 version. www.electionstudies.org',\n",
        "        ha='left', va='center_baseline', transform=ax.transAxes, fontsize=8)\n",
        "ax.text(0, 0.99, 'Stabs',\n",
        "        ha='left', va='center_baseline', transform=ax.transAxes, fontsize=8)\n",
        "ax.text(0.95, 0.99, 'n = ' + str(len(latino_df)), ha='right', va='top', transform=ax.transAxes)\n",
        "\n",
        "# Adjust layout\n",
        "# plt.tight_layout()\n",
        "\n",
        "# Show the plot\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# DEI Support based on political ideology"
      ],
      "metadata": {
        "id": "mR0eAHfxRHJf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import pandas as pd\n",
        "\n",
        "\n",
        "ideology = 'V241177'\n",
        "compared_value = 'V241288'\n",
        "\n",
        "# Remove refused, error, and haven't thought much about it\n",
        "df =  df[~df[ideology].isin([-4, -9, 99])]\n",
        "\n",
        "# For this graph the N for\n",
        "# df =  df[~df[compared_value].isin([-4, -9, 99])]\n",
        "\n",
        "\n",
        "# Define color palette\n",
        "blue_shades = sns.color_palette(\"Blues\", n_colors=3)\n",
        "purple = ['#800080']\n",
        "red_shades = sns.color_palette(\"Reds\", n_colors=3)\n",
        "custom_palette = blue_shades + purple + red_shades\n",
        "\n",
        "# Create figure\n",
        "plt.figure(figsize=(15, 11))\n",
        "\n",
        "# Normalize counts within each pcorrect group\n",
        "counts = df.groupby([compared_value, ideology]).size().reset_index(name='count')\n",
        "total_per_pcorrect = df.groupby(compared_value).size().reset_index(name='total')\n",
        "counts = counts.merge(total_per_pcorrect, on=compared_value)\n",
        "counts['percentage'] = (counts['count'] / counts['total']) * 100  # Convert to percentage\n",
        "\n",
        "# Plot using normalized percentages instead of raw counts\n",
        "ax = sns.barplot(\n",
        "    x=compared_value, y='percentage', hue=ideology, data=counts, palette=custom_palette\n",
        ")\n",
        "\n",
        "# Set labels and title\n",
        "plt.title('Distribution of Answers by Political Ideology')\n",
        "plt.xlabel('Do you favor, oppose, or neither favor nor oppose Diversity, Equity, and Inclusion (DEI) policies on college campuses that influence admission, hiring, and promotion?')\n",
        "plt.ylabel('Percentage within Each Response Group')\n",
        "\n",
        "# Define x-axis labels\n",
        "\n",
        "x_value_labels = {\n",
        "    -9: 'Refused',\n",
        "    -8: 'Don’t know',\n",
        "    -1: 'Inapplicable',\n",
        "     1: 'Favor',\n",
        "     2: 'Oppose',\n",
        "     3: 'Neither favor nor oppose'\n",
        "}\n",
        "\n",
        "plt.xticks(ticks=range(len(x_value_labels)), labels=list(x_value_labels.values()))\n",
        "\n",
        "# Define ideological labels\n",
        "lcself_labels = {\n",
        "    1: 'Very liberal',\n",
        "    2: 'Somewhat Liberal',\n",
        "    3: 'Closer to liberals',\n",
        "    4: 'Neither liberal nor conservative',\n",
        "    5: 'Closer to conservatives',\n",
        "    6: 'Somewhat Conservative',\n",
        "    7: 'Very Conservative',\n",
        "    -9: 'Refused',\n",
        "    -4: 'Error',\n",
        "    99: 'Haven’t thought much about it'\n",
        "}\n",
        "\n",
        "# Update legend with ideological labels\n",
        "handles, labels = plt.gca().get_legend_handles_labels()\n",
        "plt.legend(handles, [lcself_labels[int(label)] for label in labels], title='Ideological Bias')\n",
        "\n",
        "\n",
        "# Add annotations for each bar\n",
        "for p in ax.patches:\n",
        "    height = p.get_height()\n",
        "    if height > 0:  # Only annotate non-zero bars\n",
        "        x_pos = p.get_x()\n",
        "        width = p.get_width()\n",
        "\n",
        "        # Find the corresponding percentage\n",
        "        percentage_value = height  # Since y-axis is now percentage\n",
        "\n",
        "        # Annotate with percentage\n",
        "        ax.text(x_pos + width / 2, height, f'{percentage_value:.1f}%',\n",
        "                ha='center', va='bottom', fontsize=8)\n",
        "\n",
        "# Add source text\n",
        "ax.text(0, -0.1, 'American National Election Studies. 2025. \\nANES 2024 Time Series Study Preliminary Release: Pre-Election Data [dataset and documentation]. \\nFebruary 19, 2025 version. www.electionstudies.org',\n",
        "        ha='left', va='center_baseline', transform=ax.transAxes, fontsize=8)\n",
        "ax.text(0, 0.99, 'Stabs',\n",
        "        ha='left', va='center_baseline', transform=ax.transAxes, fontsize=8)\n",
        "ax.text(0.95, 0.99, 'n = ' + str(len(df)), ha='right', va='top', transform=ax.transAxes)\n",
        "\n",
        "# Adjust layout\n",
        "# plt.tight_layout()\n",
        "\n",
        "# Show the plot\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "8mXwr5bpREMv",
        "outputId": "95db6912-3990-40e3-ccbf-2cac9b29e1d0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x1100 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# DEI Support by race"
      ],
      "metadata": {
        "id": "5Q4SCsuITfcl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "ideology = 'V241501x'\n",
        "compared_value = 'V241288'\n",
        "\n",
        "race_labels = {\n",
        "    1: 'White, non-Hispanic',\n",
        "    2: 'Black, non-Hispanic',\n",
        "    3: 'Hispanic',\n",
        "    4: 'Asian/Native Hawaiian',\n",
        "    5: 'Native American/Alaska Native, Other',\n",
        "    6: 'Multiple Races, Non-Hispanic',\n",
        "    -8: 'Don’t know',\n",
        "    -9: 'Refused'\n",
        "}\n",
        "\n",
        "answer_labels = {\n",
        "    -9: 'Refused',\n",
        "    -8: 'Don’t know',\n",
        "    -1: 'Inapplicable',\n",
        "     1: 'Favor',\n",
        "     2: 'Oppose',\n",
        "     3: 'Neither favor nor oppose'\n",
        "}\n",
        "counts = df.groupby([compared_value, ideology]).size().reset_index(name='count')\n",
        "counts['V241501x'] = counts['V241501x'].map(race_labels)\n",
        "counts['V241288'] = counts['V241288'].map(answer_labels)\n",
        "\n",
        "counts.columns = ['Opinion', 'Race', 'Count']\n",
        "counts.to_csv('dei_opinions_by_race.csv', index=False)\n"
      ],
      "metadata": {
        "id": "GdxCi6RKUFow"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "counts"
      ],
      "metadata": {
        "id": "x8rr3UAEXQy7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "6d985e01-b024-4487-95ab-6b09b5a9bc13"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     Opinion                                  Race  count  \\\n",
              "0                    Refused                   White, non-Hispanic      8   \n",
              "1                    Refused                   Black, non-Hispanic      1   \n",
              "2                    Refused                              Hispanic      2   \n",
              "3                    Refused                 Asian/Native Hawaiian      1   \n",
              "4                 Don’t know                               Refused      1   \n",
              "5                 Don’t know                   White, non-Hispanic     15   \n",
              "6                 Don’t know                   Black, non-Hispanic      1   \n",
              "7                 Don’t know                              Hispanic      3   \n",
              "8                 Don’t know                 Asian/Native Hawaiian      1   \n",
              "9                 Don’t know          Multiple Races, Non-Hispanic      2   \n",
              "10              Inapplicable                               Refused      4   \n",
              "11              Inapplicable                   White, non-Hispanic    140   \n",
              "12              Inapplicable                   Black, non-Hispanic     15   \n",
              "13              Inapplicable                              Hispanic     14   \n",
              "14              Inapplicable                 Asian/Native Hawaiian      6   \n",
              "15              Inapplicable  Native American/Alaska Native, Other      2   \n",
              "16              Inapplicable          Multiple Races, Non-Hispanic      3   \n",
              "17                     Favor                               Refused      4   \n",
              "18                     Favor                   White, non-Hispanic    592   \n",
              "19                     Favor                   Black, non-Hispanic    110   \n",
              "20                     Favor                              Hispanic    122   \n",
              "21                     Favor                 Asian/Native Hawaiian     51   \n",
              "22                     Favor  Native American/Alaska Native, Other      5   \n",
              "23                     Favor          Multiple Races, Non-Hispanic     38   \n",
              "24                    Oppose                               Refused     13   \n",
              "25                    Oppose                                   NaN      1   \n",
              "26                    Oppose                   White, non-Hispanic    655   \n",
              "27                    Oppose                   Black, non-Hispanic     20   \n",
              "28                    Oppose                              Hispanic     50   \n",
              "29                    Oppose                 Asian/Native Hawaiian     27   \n",
              "30                    Oppose  Native American/Alaska Native, Other      4   \n",
              "31                    Oppose          Multiple Races, Non-Hispanic     35   \n",
              "32  Neither favor nor oppose                               Refused      9   \n",
              "33  Neither favor nor oppose                            Don’t know      1   \n",
              "34  Neither favor nor oppose                   White, non-Hispanic    608   \n",
              "35  Neither favor nor oppose                   Black, non-Hispanic     54   \n",
              "36  Neither favor nor oppose                              Hispanic    107   \n",
              "37  Neither favor nor oppose                 Asian/Native Hawaiian     25   \n",
              "38  Neither favor nor oppose  Native American/Alaska Native, Other      5   \n",
              "39  Neither favor nor oppose          Multiple Races, Non-Hispanic     28   \n",
              "\n",
              "    total  percentage  \n",
              "0      12   66.666667  \n",
              "1      12    8.333333  \n",
              "2      12   16.666667  \n",
              "3      12    8.333333  \n",
              "4      23    4.347826  \n",
              "5      23   65.217391  \n",
              "6      23    4.347826  \n",
              "7      23   13.043478  \n",
              "8      23    4.347826  \n",
              "9      23    8.695652  \n",
              "10    184    2.173913  \n",
              "11    184   76.086957  \n",
              "12    184    8.152174  \n",
              "13    184    7.608696  \n",
              "14    184    3.260870  \n",
              "15    184    1.086957  \n",
              "16    184    1.630435  \n",
              "17    922    0.433839  \n",
              "18    922   64.208243  \n",
              "19    922   11.930586  \n",
              "20    922   13.232104  \n",
              "21    922    5.531453  \n",
              "22    922    0.542299  \n",
              "23    922    4.121475  \n",
              "24    805    1.614907  \n",
              "25    805    0.124224  \n",
              "26    805   81.366460  \n",
              "27    805    2.484472  \n",
              "28    805    6.211180  \n",
              "29    805    3.354037  \n",
              "30    805    0.496894  \n",
              "31    805    4.347826  \n",
              "32    837    1.075269  \n",
              "33    837    0.119474  \n",
              "34    837   72.640382  \n",
              "35    837    6.451613  \n",
              "36    837   12.783751  \n",
              "37    837    2.986858  \n",
              "38    837    0.597372  \n",
              "39    837    3.345281  "
            ],
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              "\n",
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              "      <th></th>\n",
              "      <th>Opinion</th>\n",
              "      <th>Race</th>\n",
              "      <th>count</th>\n",
              "      <th>total</th>\n",
              "      <th>percentage</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Refused</td>\n",
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              "      <td>12</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Refused</td>\n",
              "      <td>Black, non-Hispanic</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Refused</td>\n",
              "      <td>Hispanic</td>\n",
              "      <td>2</td>\n",
              "      <td>12</td>\n",
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              "      <th>3</th>\n",
              "      <td>Refused</td>\n",
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              "      <td>12</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Don’t know</td>\n",
              "      <td>Refused</td>\n",
              "      <td>1</td>\n",
              "      <td>23</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Don’t know</td>\n",
              "      <td>White, non-Hispanic</td>\n",
              "      <td>15</td>\n",
              "      <td>23</td>\n",
              "      <td>65.217391</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Don’t know</td>\n",
              "      <td>Black, non-Hispanic</td>\n",
              "      <td>1</td>\n",
              "      <td>23</td>\n",
              "      <td>4.347826</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Don’t know</td>\n",
              "      <td>Hispanic</td>\n",
              "      <td>3</td>\n",
              "      <td>23</td>\n",
              "      <td>13.043478</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Don’t know</td>\n",
              "      <td>Asian/Native Hawaiian</td>\n",
              "      <td>1</td>\n",
              "      <td>23</td>\n",
              "      <td>4.347826</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Don’t know</td>\n",
              "      <td>Multiple Races, Non-Hispanic</td>\n",
              "      <td>2</td>\n",
              "      <td>23</td>\n",
              "      <td>8.695652</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>Refused</td>\n",
              "      <td>4</td>\n",
              "      <td>184</td>\n",
              "      <td>2.173913</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>White, non-Hispanic</td>\n",
              "      <td>140</td>\n",
              "      <td>184</td>\n",
              "      <td>76.086957</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>Black, non-Hispanic</td>\n",
              "      <td>15</td>\n",
              "      <td>184</td>\n",
              "      <td>8.152174</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>Hispanic</td>\n",
              "      <td>14</td>\n",
              "      <td>184</td>\n",
              "      <td>7.608696</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>Asian/Native Hawaiian</td>\n",
              "      <td>6</td>\n",
              "      <td>184</td>\n",
              "      <td>3.260870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>Native American/Alaska Native, Other</td>\n",
              "      <td>2</td>\n",
              "      <td>184</td>\n",
              "      <td>1.086957</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>Multiple Races, Non-Hispanic</td>\n",
              "      <td>3</td>\n",
              "      <td>184</td>\n",
              "      <td>1.630435</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Favor</td>\n",
              "      <td>Refused</td>\n",
              "      <td>4</td>\n",
              "      <td>922</td>\n",
              "      <td>0.433839</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Favor</td>\n",
              "      <td>White, non-Hispanic</td>\n",
              "      <td>592</td>\n",
              "      <td>922</td>\n",
              "      <td>64.208243</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Favor</td>\n",
              "      <td>Black, non-Hispanic</td>\n",
              "      <td>110</td>\n",
              "      <td>922</td>\n",
              "      <td>11.930586</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Favor</td>\n",
              "      <td>Hispanic</td>\n",
              "      <td>122</td>\n",
              "      <td>922</td>\n",
              "      <td>13.232104</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Favor</td>\n",
              "      <td>Asian/Native Hawaiian</td>\n",
              "      <td>51</td>\n",
              "      <td>922</td>\n",
              "      <td>5.531453</td>\n",
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              "      <th>22</th>\n",
              "      <td>Favor</td>\n",
              "      <td>Native American/Alaska Native, Other</td>\n",
              "      <td>5</td>\n",
              "      <td>922</td>\n",
              "      <td>0.542299</td>\n",
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              "      <th>23</th>\n",
              "      <td>Favor</td>\n",
              "      <td>Multiple Races, Non-Hispanic</td>\n",
              "      <td>38</td>\n",
              "      <td>922</td>\n",
              "      <td>4.121475</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>Refused</td>\n",
              "      <td>13</td>\n",
              "      <td>805</td>\n",
              "      <td>1.614907</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>805</td>\n",
              "      <td>0.124224</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>White, non-Hispanic</td>\n",
              "      <td>655</td>\n",
              "      <td>805</td>\n",
              "      <td>81.366460</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>Black, non-Hispanic</td>\n",
              "      <td>20</td>\n",
              "      <td>805</td>\n",
              "      <td>2.484472</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>Hispanic</td>\n",
              "      <td>50</td>\n",
              "      <td>805</td>\n",
              "      <td>6.211180</td>\n",
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              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>Asian/Native Hawaiian</td>\n",
              "      <td>27</td>\n",
              "      <td>805</td>\n",
              "      <td>3.354037</td>\n",
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              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>Native American/Alaska Native, Other</td>\n",
              "      <td>4</td>\n",
              "      <td>805</td>\n",
              "      <td>0.496894</td>\n",
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              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>Multiple Races, Non-Hispanic</td>\n",
              "      <td>35</td>\n",
              "      <td>805</td>\n",
              "      <td>4.347826</td>\n",
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              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Refused</td>\n",
              "      <td>9</td>\n",
              "      <td>837</td>\n",
              "      <td>1.075269</td>\n",
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              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Don’t know</td>\n",
              "      <td>1</td>\n",
              "      <td>837</td>\n",
              "      <td>0.119474</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>White, non-Hispanic</td>\n",
              "      <td>608</td>\n",
              "      <td>837</td>\n",
              "      <td>72.640382</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Black, non-Hispanic</td>\n",
              "      <td>54</td>\n",
              "      <td>837</td>\n",
              "      <td>6.451613</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Hispanic</td>\n",
              "      <td>107</td>\n",
              "      <td>837</td>\n",
              "      <td>12.783751</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Asian/Native Hawaiian</td>\n",
              "      <td>25</td>\n",
              "      <td>837</td>\n",
              "      <td>2.986858</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Native American/Alaska Native, Other</td>\n",
              "      <td>5</td>\n",
              "      <td>837</td>\n",
              "      <td>0.597372</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Multiple Races, Non-Hispanic</td>\n",
              "      <td>28</td>\n",
              "      <td>837</td>\n",
              "      <td>3.345281</td>\n",
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              "    background-color: var(--disabled-bg-color);\n",
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              "    border-color: transparent;\n",
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              "    animation:\n",
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              "\n",
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              "    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",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('counts')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "counts",
              "summary": "{\n  \"name\": \"counts\",\n  \"rows\": 40,\n  \"fields\": [\n    {\n      \"column\": \"Opinion\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"Refused\",\n          \"Don\\u2019t know\",\n          \"Neither favor nor oppose\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Race\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 8,\n        \"samples\": [\n          \"Black, non-Hispanic\",\n          \"Multiple Races, Non-Hispanic\",\n          \"White, non-Hispanic\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"count\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 162,\n        \"min\": 1,\n        \"max\": 655,\n        \"num_unique_values\": 27,\n        \"samples\": [\n          6,\n          5,\n          592\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"total\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 388,\n        \"min\": 12,\n        \"max\": 922,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          12,\n          23,\n          837\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"percentage\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 24.30544436260403,\n        \"min\": 0.11947431302270012,\n        \"max\": 81.36645962732919,\n        \"num_unique_values\": 36,\n        \"samples\": [\n          3.345280764635603,\n          1.6304347826086956,\n          3.354037267080745\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 104
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "ideology = 'V241501x'\n",
        "compared_value = 'V241288'\n",
        "\n",
        "race_labels = {\n",
        "    1: 'White, non-Hispanic',\n",
        "    2: 'Black, non-Hispanic',\n",
        "    3: 'Hispanic',\n",
        "    4: 'Asian/Native Hawaiian',\n",
        "    5: 'Native American/Alaska Native, Other',\n",
        "    6: 'Multiple Races, Non-Hispanic',\n",
        "    -8: 'Don’t know',\n",
        "    -9: 'Refused'\n",
        "}\n",
        "\n",
        "answer_labels = {\n",
        "    -9: 'Refused',\n",
        "    -8: 'Don’t know',\n",
        "    -1: 'Inapplicable',\n",
        "     1: 'Favor',\n",
        "     2: 'Oppose',\n",
        "     3: 'Neither favor nor oppose'\n",
        "}\n",
        "\n",
        "\n",
        "# Group the data by 'Race' and 'Opinion'\n",
        "counts = df.groupby([compared_value, ideology]).size().reset_index(name='count')\n",
        "\n",
        "total_per_pcorrect = df.groupby(compared_value).size().reset_index(name='total')\n",
        "counts = counts.merge(total_per_pcorrect, on=compared_value)\n",
        "counts['percentage'] = (counts['count'] / counts['total']) * 100  # Convert to percentage\n",
        "\n",
        "counts['V241501x'] = counts['V241501x'].map(race_labels)\n",
        "counts['V241288'] = counts['V241288'].map(answer_labels)\n",
        "\n",
        "counts.columns = ['Opinion', 'Race', 'count', 'total', 'percentage']\n",
        "grouped_data = counts.groupby(['Race', 'Opinion'])['percentage'].sum().unstack()\n",
        "\n",
        "# Create the bar plot\n",
        "ax = grouped_data.plot(kind='bar', figsize=(15, 10))\n",
        "\n",
        "# Add annotations for each bar\n",
        "for p in ax.patches:\n",
        "    height = p.get_height()\n",
        "    if height > 0:  # Only annotate non-zero bars\n",
        "        x_pos = p.get_x()\n",
        "        width = p.get_width()\n",
        "\n",
        "        # Find the corresponding percentage\n",
        "        percentage_value = height  # Since y-axis is now percentage\n",
        "\n",
        "        # Annotate with percentage\n",
        "        ax.text(x_pos + width / 2, height, f'{percentage_value:.1f}%',\n",
        "                ha='center', va='bottom', fontsize=8)\n",
        "\n",
        "\n",
        "ax.text(0, -0.5, 'American National Election Studies. 2025. \\nANES 2024 Time Series Study Preliminary Release: Pre-Election Data [dataset and documentation]. \\nFebruary 19, 2025 version. www.electionstudies.org',\n",
        "        ha='left', va='center_baseline', transform=ax.transAxes, fontsize=8)\n",
        "ax.text(0, 0.95, 'Stabs',\n",
        "        ha='left', va='center_baseline', transform=ax.transAxes, fontsize=8)\n",
        "ax.text(0.99, 0.99, 'n = ' + str(len(df)), ha='right', va='top', transform=ax.transAxes)\n",
        "\n",
        "# Customize the plot\n",
        "plt.title(' Do you favor, oppose, or neither favor nor oppose Diversity, Equity, and Inclusion (DEI) policies on college campuses that influence admission, hiring, and promotion')\n",
        "plt.xlabel('Race')\n",
        "plt.ylabel('Percentage')\n",
        "plt.xticks(rotation=45, ha='right')  # Rotate x-axis labels for readability\n",
        "plt.legend(title='Opinion')\n",
        "plt.tight_layout()  # Adjust layout to prevent labels from overlapping\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 894
        },
        "id": "mLkqdlAJYY6G",
        "outputId": "a3a7a243-ea79-4d53-f2b2-fa6833e6dd1f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x1000 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "a1xHMB7KXu_j"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "counts"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "objbJuEoYDKV",
        "outputId": "1250fcc5-9f4e-4d5c-ade6-dbaea21acb31"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     Opinion                                  Race  count  \\\n",
              "0                    Refused                   White, non-Hispanic      8   \n",
              "1                    Refused                   Black, non-Hispanic      1   \n",
              "2                    Refused                              Hispanic      2   \n",
              "3                    Refused                 Asian/Native Hawaiian      1   \n",
              "4                 Don’t know                               Refused      1   \n",
              "5                 Don’t know                   White, non-Hispanic     15   \n",
              "6                 Don’t know                   Black, non-Hispanic      1   \n",
              "7                 Don’t know                              Hispanic      3   \n",
              "8                 Don’t know                 Asian/Native Hawaiian      1   \n",
              "9                 Don’t know          Multiple Races, Non-Hispanic      2   \n",
              "10              Inapplicable                               Refused      4   \n",
              "11              Inapplicable                   White, non-Hispanic    140   \n",
              "12              Inapplicable                   Black, non-Hispanic     15   \n",
              "13              Inapplicable                              Hispanic     14   \n",
              "14              Inapplicable                 Asian/Native Hawaiian      6   \n",
              "15              Inapplicable  Native American/Alaska Native, Other      2   \n",
              "16              Inapplicable          Multiple Races, Non-Hispanic      3   \n",
              "17                     Favor                               Refused      4   \n",
              "18                     Favor                   White, non-Hispanic    592   \n",
              "19                     Favor                   Black, non-Hispanic    110   \n",
              "20                     Favor                              Hispanic    122   \n",
              "21                     Favor                 Asian/Native Hawaiian     51   \n",
              "22                     Favor  Native American/Alaska Native, Other      5   \n",
              "23                     Favor          Multiple Races, Non-Hispanic     38   \n",
              "24                    Oppose                               Refused     13   \n",
              "25                    Oppose                                   NaN      1   \n",
              "26                    Oppose                   White, non-Hispanic    655   \n",
              "27                    Oppose                   Black, non-Hispanic     20   \n",
              "28                    Oppose                              Hispanic     50   \n",
              "29                    Oppose                 Asian/Native Hawaiian     27   \n",
              "30                    Oppose  Native American/Alaska Native, Other      4   \n",
              "31                    Oppose          Multiple Races, Non-Hispanic     35   \n",
              "32  Neither favor nor oppose                               Refused      9   \n",
              "33  Neither favor nor oppose                            Don’t know      1   \n",
              "34  Neither favor nor oppose                   White, non-Hispanic    608   \n",
              "35  Neither favor nor oppose                   Black, non-Hispanic     54   \n",
              "36  Neither favor nor oppose                              Hispanic    107   \n",
              "37  Neither favor nor oppose                 Asian/Native Hawaiian     25   \n",
              "38  Neither favor nor oppose  Native American/Alaska Native, Other      5   \n",
              "39  Neither favor nor oppose          Multiple Races, Non-Hispanic     28   \n",
              "\n",
              "    total  percentage  \n",
              "0      12   66.666667  \n",
              "1      12    8.333333  \n",
              "2      12   16.666667  \n",
              "3      12    8.333333  \n",
              "4      23    4.347826  \n",
              "5      23   65.217391  \n",
              "6      23    4.347826  \n",
              "7      23   13.043478  \n",
              "8      23    4.347826  \n",
              "9      23    8.695652  \n",
              "10    184    2.173913  \n",
              "11    184   76.086957  \n",
              "12    184    8.152174  \n",
              "13    184    7.608696  \n",
              "14    184    3.260870  \n",
              "15    184    1.086957  \n",
              "16    184    1.630435  \n",
              "17    922    0.433839  \n",
              "18    922   64.208243  \n",
              "19    922   11.930586  \n",
              "20    922   13.232104  \n",
              "21    922    5.531453  \n",
              "22    922    0.542299  \n",
              "23    922    4.121475  \n",
              "24    805    1.614907  \n",
              "25    805    0.124224  \n",
              "26    805   81.366460  \n",
              "27    805    2.484472  \n",
              "28    805    6.211180  \n",
              "29    805    3.354037  \n",
              "30    805    0.496894  \n",
              "31    805    4.347826  \n",
              "32    837    1.075269  \n",
              "33    837    0.119474  \n",
              "34    837   72.640382  \n",
              "35    837    6.451613  \n",
              "36    837   12.783751  \n",
              "37    837    2.986858  \n",
              "38    837    0.597372  \n",
              "39    837    3.345281  "
            ],
            "text/html": [
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              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Opinion</th>\n",
              "      <th>Race</th>\n",
              "      <th>count</th>\n",
              "      <th>total</th>\n",
              "      <th>percentage</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Refused</td>\n",
              "      <td>White, non-Hispanic</td>\n",
              "      <td>8</td>\n",
              "      <td>12</td>\n",
              "      <td>66.666667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Refused</td>\n",
              "      <td>Black, non-Hispanic</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
              "      <td>8.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Refused</td>\n",
              "      <td>Hispanic</td>\n",
              "      <td>2</td>\n",
              "      <td>12</td>\n",
              "      <td>16.666667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Refused</td>\n",
              "      <td>Asian/Native Hawaiian</td>\n",
              "      <td>1</td>\n",
              "      <td>12</td>\n",
              "      <td>8.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Don’t know</td>\n",
              "      <td>Refused</td>\n",
              "      <td>1</td>\n",
              "      <td>23</td>\n",
              "      <td>4.347826</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Don’t know</td>\n",
              "      <td>White, non-Hispanic</td>\n",
              "      <td>15</td>\n",
              "      <td>23</td>\n",
              "      <td>65.217391</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Don’t know</td>\n",
              "      <td>Black, non-Hispanic</td>\n",
              "      <td>1</td>\n",
              "      <td>23</td>\n",
              "      <td>4.347826</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Don’t know</td>\n",
              "      <td>Hispanic</td>\n",
              "      <td>3</td>\n",
              "      <td>23</td>\n",
              "      <td>13.043478</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Don’t know</td>\n",
              "      <td>Asian/Native Hawaiian</td>\n",
              "      <td>1</td>\n",
              "      <td>23</td>\n",
              "      <td>4.347826</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Don’t know</td>\n",
              "      <td>Multiple Races, Non-Hispanic</td>\n",
              "      <td>2</td>\n",
              "      <td>23</td>\n",
              "      <td>8.695652</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>Refused</td>\n",
              "      <td>4</td>\n",
              "      <td>184</td>\n",
              "      <td>2.173913</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>White, non-Hispanic</td>\n",
              "      <td>140</td>\n",
              "      <td>184</td>\n",
              "      <td>76.086957</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>Black, non-Hispanic</td>\n",
              "      <td>15</td>\n",
              "      <td>184</td>\n",
              "      <td>8.152174</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>Hispanic</td>\n",
              "      <td>14</td>\n",
              "      <td>184</td>\n",
              "      <td>7.608696</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>Asian/Native Hawaiian</td>\n",
              "      <td>6</td>\n",
              "      <td>184</td>\n",
              "      <td>3.260870</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>Native American/Alaska Native, Other</td>\n",
              "      <td>2</td>\n",
              "      <td>184</td>\n",
              "      <td>1.086957</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Inapplicable</td>\n",
              "      <td>Multiple Races, Non-Hispanic</td>\n",
              "      <td>3</td>\n",
              "      <td>184</td>\n",
              "      <td>1.630435</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Favor</td>\n",
              "      <td>Refused</td>\n",
              "      <td>4</td>\n",
              "      <td>922</td>\n",
              "      <td>0.433839</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Favor</td>\n",
              "      <td>White, non-Hispanic</td>\n",
              "      <td>592</td>\n",
              "      <td>922</td>\n",
              "      <td>64.208243</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Favor</td>\n",
              "      <td>Black, non-Hispanic</td>\n",
              "      <td>110</td>\n",
              "      <td>922</td>\n",
              "      <td>11.930586</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Favor</td>\n",
              "      <td>Hispanic</td>\n",
              "      <td>122</td>\n",
              "      <td>922</td>\n",
              "      <td>13.232104</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Favor</td>\n",
              "      <td>Asian/Native Hawaiian</td>\n",
              "      <td>51</td>\n",
              "      <td>922</td>\n",
              "      <td>5.531453</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Favor</td>\n",
              "      <td>Native American/Alaska Native, Other</td>\n",
              "      <td>5</td>\n",
              "      <td>922</td>\n",
              "      <td>0.542299</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>Favor</td>\n",
              "      <td>Multiple Races, Non-Hispanic</td>\n",
              "      <td>38</td>\n",
              "      <td>922</td>\n",
              "      <td>4.121475</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>Refused</td>\n",
              "      <td>13</td>\n",
              "      <td>805</td>\n",
              "      <td>1.614907</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>805</td>\n",
              "      <td>0.124224</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>White, non-Hispanic</td>\n",
              "      <td>655</td>\n",
              "      <td>805</td>\n",
              "      <td>81.366460</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>Black, non-Hispanic</td>\n",
              "      <td>20</td>\n",
              "      <td>805</td>\n",
              "      <td>2.484472</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>Hispanic</td>\n",
              "      <td>50</td>\n",
              "      <td>805</td>\n",
              "      <td>6.211180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>Asian/Native Hawaiian</td>\n",
              "      <td>27</td>\n",
              "      <td>805</td>\n",
              "      <td>3.354037</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>Native American/Alaska Native, Other</td>\n",
              "      <td>4</td>\n",
              "      <td>805</td>\n",
              "      <td>0.496894</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>Oppose</td>\n",
              "      <td>Multiple Races, Non-Hispanic</td>\n",
              "      <td>35</td>\n",
              "      <td>805</td>\n",
              "      <td>4.347826</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Refused</td>\n",
              "      <td>9</td>\n",
              "      <td>837</td>\n",
              "      <td>1.075269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Don’t know</td>\n",
              "      <td>1</td>\n",
              "      <td>837</td>\n",
              "      <td>0.119474</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>White, non-Hispanic</td>\n",
              "      <td>608</td>\n",
              "      <td>837</td>\n",
              "      <td>72.640382</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Black, non-Hispanic</td>\n",
              "      <td>54</td>\n",
              "      <td>837</td>\n",
              "      <td>6.451613</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Hispanic</td>\n",
              "      <td>107</td>\n",
              "      <td>837</td>\n",
              "      <td>12.783751</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Asian/Native Hawaiian</td>\n",
              "      <td>25</td>\n",
              "      <td>837</td>\n",
              "      <td>2.986858</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Native American/Alaska Native, Other</td>\n",
              "      <td>5</td>\n",
              "      <td>837</td>\n",
              "      <td>0.597372</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>Neither favor nor oppose</td>\n",
              "      <td>Multiple Races, Non-Hispanic</td>\n",
              "      <td>28</td>\n",
              "      <td>837</td>\n",
              "      <td>3.345281</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7c980e3d-43ec-4070-ae1c-c64dcd52e58e')\"\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 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-7c980e3d-43ec-4070-ae1c-c64dcd52e58e 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-7c980e3d-43ec-4070-ae1c-c64dcd52e58e');\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",
              "\n",
              "\n",
              "<div id=\"df-e589809d-3a5c-4c92-bb15-9622d1a0f1a2\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e589809d-3a5c-4c92-bb15-9622d1a0f1a2')\"\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",
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              "    </g>\n",
              "</svg>\n",
              "  </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",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    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-e589809d-3a5c-4c92-bb15-9622d1a0f1a2 button');\n",
              "      quickchartButtonEl.style.display =\n",
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              "            title=\"Generate code using this dataframe.\"\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "counts",
              "summary": "{\n  \"name\": \"counts\",\n  \"rows\": 40,\n  \"fields\": [\n    {\n      \"column\": \"Opinion\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"Refused\",\n          \"Don\\u2019t know\",\n          \"Neither favor nor oppose\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Race\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 8,\n        \"samples\": [\n          \"Black, non-Hispanic\",\n          \"Multiple Races, Non-Hispanic\",\n          \"White, non-Hispanic\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"count\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 162,\n        \"min\": 1,\n        \"max\": 655,\n        \"num_unique_values\": 27,\n        \"samples\": [\n          6,\n          5,\n          592\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"total\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 388,\n        \"min\": 12,\n        \"max\": 922,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          12,\n          23,\n          837\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"percentage\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 24.30544436260403,\n        \"min\": 0.11947431302270012,\n        \"max\": 81.36645962732919,\n        \"num_unique_values\": 36,\n        \"samples\": [\n          3.345280764635603,\n          1.6304347826086956,\n          3.354037267080745\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 107
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "co"
      ],
      "metadata": {
        "id": "xo6AuJKnXXYz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "counts.loc[counts['V241288'] == 2]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 568
        },
        "id": "Y9RJbIReSE71",
        "outputId": "17e53dfb-2155-421b-a0e2-f147b500e92b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "KeyError",
          "evalue": "'V241288'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
            "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3804\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3805\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3806\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32mindex.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mindex.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;31mKeyError\u001b[0m: 'V241288'",
            "\nThe above exception was the direct cause of the following exception:\n",
            "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-111-802d2ae4abf9>\u001b[0m in \u001b[0;36m<cell line: 0>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mcounts\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mcounts\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'V241288'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   4100\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4101\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4102\u001b[0;31m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4103\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4104\u001b[0m                 \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3810\u001b[0m             ):\n\u001b[1;32m   3811\u001b[0m                 \u001b[0;32mraise\u001b[0m \u001b[0mInvalidIndexError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3812\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3813\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3814\u001b[0m             \u001b[0;31m# If we have a listlike key, _check_indexing_error will raise\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyError\u001b[0m: 'V241288'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['V241289'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "o29bkZLrRwm3",
        "outputId": "d2a73764-9344-4eea-a6d5-b8f9b26da4ae"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([-1,  1,  2,  3, -8])"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    }
  ]
}