predec_survey_EDA.ipynb

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  "metadata": {
    "colab": {
      "name": "predec survey EDA",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": []
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      "name": "python3",
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      "metadata": {
        "id": "tOxPX0qLeTAm",
        "colab_type": "code",
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      "cell_type": "code",
      "source": [
        "!pip install --upgrade -q gspread"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "s5VN96lsH8tp",
        "colab_type": "code",
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      },
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "from google.colab import files\n",
        "import matplotlib.pyplot as plt\n",
        "plt.style.use('fivethirtyeight')\n",
        "\n",
        "pd.set_option('display.max_columns', 26)\n",
        "pd.set_option('display.max_rows', 20)\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
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        "outputId": "6c8c8838-a066-4751-81ab-41ff7a30bf40",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 445
        }
      },
      "cell_type": "code",
      "source": [
        "# Reading data from Google sheet instead of locally\n",
        "\n",
        "from google.colab import auth\n",
        "auth.authenticate_user()\n",
        "\n",
        "import gspread\n",
        "from oauth2client.client import GoogleCredentials\n",
        "\n",
        "gc = gspread.authorize(GoogleCredentials.get_application_default())\n",
        "\n",
        "worksheet = gc.open('predeclaration_responses_9262018').sheet1\n",
        "\n",
        "# get_all_values gives a list of rows.\n",
        "rows = worksheet.get_all_values()\n",
        "\n",
        "# Convert to a DataFrame and render.\n",
        "df = pd.DataFrame.from_records(rows)\n",
        "\n",
        "#Fixing column names\n",
        "df.columns = df.iloc[0]\n",
        "df = df.drop([0], axis=0)\n",
        "\n",
        "df = df.drop(columns=['Email Address', 'Score', 'Full Name:', 'Student Identification Number (SID):', 'CalNet ID:'])\n",
        "\n",
        "# Display just the first 5, so the output isn't large\n",
        "df.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
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          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Timestamp</th>\n",
              "      <th>Have you completed the Foundations of Data Science requirement?</th>\n",
              "      <th>Have you completed the Calculus I requirement?</th>\n",
              "      <th>Have you completed the Calculus II requirement?</th>\n",
              "      <th>Have you completed the Linear Algebra requirement?</th>\n",
              "      <th>Have you completed the Program Structures requirement?</th>\n",
              "      <th>Have you completed the Data Structures requirement?</th>\n",
              "      <th>Have you completed the Principles and Techniques of Data Science requirement?</th>\n",
              "      <th>Have you completed one course towards the Computational and Inferential Depth requirement?</th>\n",
              "      <th>Have you completed the second course towards the Computational and Inferential Depth requirement?</th>\n",
              "      <th>Have you completed the Probability requirement?</th>\n",
              "      <th>Have you completed the Human Contexts and Ethics requirement?</th>\n",
              "      <th>Have you completed the Modeling, Learning, and Decision-Making requirement?</th>\n",
              "      <th>Have you completed one lower-division course towards a Domain Emphasis?</th>\n",
              "      <th>Have you completed one upper-division course towards a Domain Emphasis?</th>\n",
              "      <th>Have you completed a second upper-division course towards a Domain Emphasis?</th>\n",
              "      <th>Are you a transfer student?</th>\n",
              "      <th>Are you expected to graduate in Fall 2018?</th>\n",
              "      <th>Are you expected to graduate in Spring or Summer 2019?</th>\n",
              "      <th>What is your current Expected Graduation Term?</th>\n",
              "      <th>Are you currently already declared in another major?</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>8/9/2018 15:33:24</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>In progress in Fall 2018</td>\n",
              "      <td>In progress in Fall 2018</td>\n",
              "      <td>No</td>\n",
              "      <td></td>\n",
              "      <td></td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>8/9/2018 15:34:04</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>In progress in Fall 2018</td>\n",
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              "      <td>In progress in Fall 2018</td>\n",
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              "      <td>In progress in Fall 2018</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td></td>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8/9/2018 15:34:21</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>In progress in Fall 2018</td>\n",
              "      <td>In progress in Fall 2018</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
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              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
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              "      <td>Yes</td>\n",
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              "      <td>In progress in Fall 2018</td>\n",
              "      <td>In progress in Fall 2018</td>\n",
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              "      <td>In progress in Fall 2018</td>\n",
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              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>8/9/2018 15:35:11</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>In progress in Fall 2018</td>\n",
              "      <td>In progress in Fall 2018</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>In progress in Fall 2018</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>No</td>\n",
              "    </tr>\n",
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              "0          Timestamp  \\\n",
              "1  8/9/2018 15:33:24   \n",
              "2  8/9/2018 15:34:04   \n",
              "3  8/9/2018 15:34:21   \n",
              "4  8/9/2018 15:35:11   \n",
              "5  8/9/2018 15:35:11   \n",
              "\n",
              "0 Have you completed the Foundations of Data Science requirement?  \\\n",
              "1                                                Yes                \n",
              "2                                                Yes                \n",
              "3                                                Yes                \n",
              "4                                                Yes                \n",
              "5                                                Yes                \n",
              "\n",
              "0 Have you completed the Calculus I requirement?  \\\n",
              "1                                            Yes   \n",
              "2                                            Yes   \n",
              "3                                            Yes   \n",
              "4                                            Yes   \n",
              "5                                            Yes   \n",
              "\n",
              "0 Have you completed the Calculus II requirement?  \\\n",
              "1                                             Yes   \n",
              "2                                             Yes   \n",
              "3                                             Yes   \n",
              "4                                             Yes   \n",
              "5                                             Yes   \n",
              "\n",
              "0 Have you completed the Linear Algebra requirement?  \\\n",
              "1                           In progress in Fall 2018   \n",
              "2                                                Yes   \n",
              "3                           In progress in Fall 2018   \n",
              "4                                                Yes   \n",
              "5                                                Yes   \n",
              "\n",
              "0 Have you completed the Program Structures requirement?  \\\n",
              "1                           In progress in Fall 2018       \n",
              "2                                                Yes       \n",
              "3                           In progress in Fall 2018       \n",
              "4                                                Yes       \n",
              "5                                                Yes       \n",
              "\n",
              "0 Have you completed the Data Structures requirement?  \\\n",
              "1                                                 No    \n",
              "2                                                Yes    \n",
              "3                                                 No    \n",
              "4                           In progress in Fall 2018    \n",
              "5                           In progress in Fall 2018    \n",
              "\n",
              "0 Have you completed the Principles and Techniques of Data Science requirement?  \\\n",
              "1                                                                                 \n",
              "2                                                Yes                              \n",
              "3                                                                                 \n",
              "4                           In progress in Fall 2018                              \n",
              "5                           In progress in Fall 2018                              \n",
              "\n",
              "0 Have you completed one course towards the Computational and Inferential Depth requirement?  \\\n",
              "1                                                                                              \n",
              "2                           In progress in Fall 2018                                           \n",
              "3                                                                                              \n",
              "4                                                 No                                           \n",
              "5                                                 No                                           \n",
              "\n",
              "0 Have you completed the second course towards the Computational and Inferential Depth requirement?  \\\n",
              "1                                                                                                     \n",
              "2                                                 No                                                  \n",
              "3                                                                                                     \n",
              "4                                                 No                                                  \n",
              "5                                                 No                                                  \n",
              "\n",
              "0 Have you completed the Probability requirement?  \\\n",
              "1                                                   \n",
              "2                                             Yes   \n",
              "3                                                   \n",
              "4                        In progress in Fall 2018   \n",
              "5                                              No   \n",
              "\n",
              "0 Have you completed the Human Contexts and Ethics requirement?  \\\n",
              "1                                                                 \n",
              "2                           In progress in Fall 2018              \n",
              "3                                                                 \n",
              "4                                                 No              \n",
              "5                                                 No              \n",
              "\n",
              "0 Have you completed the Modeling, Learning, and Decision-Making requirement?  \\\n",
              "1                                                                               \n",
              "2                                                 No                            \n",
              "3                                                                               \n",
              "4                                                 No                            \n",
              "5                                                 No                            \n",
              "\n",
              "0 Have you completed one lower-division course towards a Domain Emphasis?  \\\n",
              "1                                                                           \n",
              "2                                                Yes                        \n",
              "3                                                                           \n",
              "4                                                Yes                        \n",
              "5                                                Yes                        \n",
              "\n",
              "0 Have you completed one upper-division course towards a Domain Emphasis?  \\\n",
              "1                                                                           \n",
              "2                                                Yes                        \n",
              "3                                                                           \n",
              "4                                                Yes                        \n",
              "5                                                Yes                        \n",
              "\n",
              "0 Have you completed a second upper-division course towards a Domain Emphasis?  \\\n",
              "1                                                                                \n",
              "2                           In progress in Fall 2018                             \n",
              "3                                                                                \n",
              "4                                                 No                             \n",
              "5                           In progress in Fall 2018                             \n",
              "\n",
              "0 Are you a transfer student? Are you expected to graduate in Fall 2018?  \\\n",
              "1                                                                          \n",
              "2                          No                                         No   \n",
              "3                                                                          \n",
              "4                          No                                         No   \n",
              "5                          No                                         No   \n",
              "\n",
              "0 Are you expected to graduate in Spring or Summer 2019?  \\\n",
              "1                                                          \n",
              "2                                                Yes       \n",
              "3                                                          \n",
              "4                                                 No       \n",
              "5                                                 No       \n",
              "\n",
              "0 What is your current Expected Graduation Term?  \\\n",
              "1                                                  \n",
              "2                                                  \n",
              "3                                                  \n",
              "4                                    Spring 2020   \n",
              "5                                    Spring 2020   \n",
              "\n",
              "0 Are you currently already declared in another major?  \n",
              "1                                                       \n",
              "2                                                Yes    \n",
              "3                                                       \n",
              "4                                                 No    \n",
              "5                                                 No    "
            ]
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          "metadata": {
            "tags": []
          },
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        }
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    {
      "metadata": {
        "id": "TE9NSq7CQQq6",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# **HOTKEY ENCODING**"
      ]
    },
    {
      "metadata": {
        "id": "rd-HrqaYPyXj",
        "colab_type": "code",
        "outputId": "49777c92-139b-49fd-9983-193e7ae0b759",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1225
        }
      },
      "cell_type": "code",
      "source": [
        "#encoding yes and no to 0's and 1's\n",
        "#TODO: this method can only be run once per runtime, fix..\n",
        "def hot_encoding(df):\n",
        "  for col in list(df):\n",
        "    df[col].replace(('Yes', 'No', 'In progress in Fall 2018', ''), (1, 0, 1, 0), inplace=True)\n",
        "    \n",
        "hot_encoding(df)\n",
        "df"
      ],
      "execution_count": 0,
      "outputs": [
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              "      <th>Timestamp</th>\n",
              "      <th>Have you completed the Foundations of Data Science requirement?</th>\n",
              "      <th>Have you completed the Calculus I requirement?</th>\n",
              "      <th>Have you completed the Calculus II requirement?</th>\n",
              "      <th>Have you completed the Linear Algebra requirement?</th>\n",
              "      <th>Have you completed the Program Structures requirement?</th>\n",
              "      <th>Have you completed the Data Structures requirement?</th>\n",
              "      <th>Have you completed the Principles and Techniques of Data Science requirement?</th>\n",
              "      <th>Have you completed one course towards the Computational and Inferential Depth requirement?</th>\n",
              "      <th>Have you completed the second course towards the Computational and Inferential Depth requirement?</th>\n",
              "      <th>Have you completed the Probability requirement?</th>\n",
              "      <th>Have you completed the Human Contexts and Ethics requirement?</th>\n",
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              "      <td>Spring 2020</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>8/9/2018 15:35:40</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Fall 2019</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>8/9/2018 15:35:41</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>8/9/2018 15:35:41</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Fall 2019</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>8/9/2018 15:35:43</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>8/9/2018 15:35:46</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>778</th>\n",
              "      <td>9/24/2018 22:57:01</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2022</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>779</th>\n",
              "      <td>9/25/2018 10:26:39</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>780</th>\n",
              "      <td>9/25/2018 15:24:15</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>781</th>\n",
              "      <td>9/25/2018 15:26:12</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>782</th>\n",
              "      <td>9/25/2018 16:26:38</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>783</th>\n",
              "      <td>9/25/2018 16:38:24</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>784</th>\n",
              "      <td>9/26/2018 2:17:29</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2021</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>785</th>\n",
              "      <td>9/26/2018 10:20:10</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2022</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>786</th>\n",
              "      <td>9/26/2018 10:37:19</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>787</th>\n",
              "      <td>9/26/2018 12:08:25</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2021</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>787 rows × 21 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "0             Timestamp  \\\n",
              "1     8/9/2018 15:33:24   \n",
              "2     8/9/2018 15:34:04   \n",
              "3     8/9/2018 15:34:21   \n",
              "4     8/9/2018 15:35:11   \n",
              "5     8/9/2018 15:35:11   \n",
              "6     8/9/2018 15:35:40   \n",
              "7     8/9/2018 15:35:41   \n",
              "8     8/9/2018 15:35:41   \n",
              "9     8/9/2018 15:35:43   \n",
              "10    8/9/2018 15:35:46   \n",
              "..                  ...   \n",
              "778  9/24/2018 22:57:01   \n",
              "779  9/25/2018 10:26:39   \n",
              "780  9/25/2018 15:24:15   \n",
              "781  9/25/2018 15:26:12   \n",
              "782  9/25/2018 16:26:38   \n",
              "783  9/25/2018 16:38:24   \n",
              "784   9/26/2018 2:17:29   \n",
              "785  9/26/2018 10:20:10   \n",
              "786  9/26/2018 10:37:19   \n",
              "787  9/26/2018 12:08:25   \n",
              "\n",
              "0    Have you completed the Foundations of Data Science requirement?  \\\n",
              "1                                                    1                 \n",
              "2                                                    1                 \n",
              "3                                                    1                 \n",
              "4                                                    1                 \n",
              "5                                                    1                 \n",
              "6                                                    1                 \n",
              "7                                                    1                 \n",
              "8                                                    1                 \n",
              "9                                                    1                 \n",
              "10                                                   1                 \n",
              "..                                                 ...                 \n",
              "778                                                  1                 \n",
              "779                                                  0                 \n",
              "780                                                  1                 \n",
              "781                                                  1                 \n",
              "782                                                  0                 \n",
              "783                                                  0                 \n",
              "784                                                  1                 \n",
              "785                                                  1                 \n",
              "786                                                  1                 \n",
              "787                                                  1                 \n",
              "\n",
              "0    Have you completed the Calculus I requirement?  \\\n",
              "1                                                 1   \n",
              "2                                                 1   \n",
              "3                                                 1   \n",
              "4                                                 1   \n",
              "5                                                 1   \n",
              "6                                                 1   \n",
              "7                                                 1   \n",
              "8                                                 1   \n",
              "9                                                 1   \n",
              "10                                                1   \n",
              "..                                              ...   \n",
              "778                                               0   \n",
              "779                                               1   \n",
              "780                                               1   \n",
              "781                                               1   \n",
              "782                                               1   \n",
              "783                                               1   \n",
              "784                                               1   \n",
              "785                                               1   \n",
              "786                                               1   \n",
              "787                                               1   \n",
              "\n",
              "0    Have you completed the Calculus II requirement?  \\\n",
              "1                                                  1   \n",
              "2                                                  1   \n",
              "3                                                  1   \n",
              "4                                                  1   \n",
              "5                                                  1   \n",
              "6                                                  1   \n",
              "7                                                  1   \n",
              "8                                                  1   \n",
              "9                                                  1   \n",
              "10                                                 1   \n",
              "..                                               ...   \n",
              "778                                                0   \n",
              "779                                                1   \n",
              "780                                                1   \n",
              "781                                                1   \n",
              "782                                                1   \n",
              "783                                                1   \n",
              "784                                                1   \n",
              "785                                                1   \n",
              "786                                                0   \n",
              "787                                                1   \n",
              "\n",
              "0    Have you completed the Linear Algebra requirement?  \\\n",
              "1                                                    1    \n",
              "2                                                    1    \n",
              "3                                                    1    \n",
              "4                                                    1    \n",
              "5                                                    1    \n",
              "6                                                    1    \n",
              "7                                                    1    \n",
              "8                                                    1    \n",
              "9                                                    1    \n",
              "10                                                   1    \n",
              "..                                                 ...    \n",
              "778                                                  0    \n",
              "779                                                  1    \n",
              "780                                                  1    \n",
              "781                                                  0    \n",
              "782                                                  0    \n",
              "783                                                  1    \n",
              "784                                                  0    \n",
              "785                                                  1    \n",
              "786                                                  0    \n",
              "787                                                  1    \n",
              "\n",
              "0    Have you completed the Program Structures requirement?  \\\n",
              "1                                                    1        \n",
              "2                                                    1        \n",
              "3                                                    1        \n",
              "4                                                    1        \n",
              "5                                                    1        \n",
              "6                                                    1        \n",
              "7                                                    1        \n",
              "8                                                    1        \n",
              "9                                                    1        \n",
              "10                                                   1        \n",
              "..                                                 ...        \n",
              "778                                                  0        \n",
              "779                                                  1        \n",
              "780                                                  1        \n",
              "781                                                  1        \n",
              "782                                                  0        \n",
              "783                                                  1        \n",
              "784                                                  0        \n",
              "785                                                  1        \n",
              "786                                                  1        \n",
              "787                                                  1        \n",
              "\n",
              "0    Have you completed the Data Structures requirement?  \\\n",
              "1                                                    0     \n",
              "2                                                    1     \n",
              "3                                                    0     \n",
              "4                                                    1     \n",
              "5                                                    1     \n",
              "6                                                    1     \n",
              "7                                                    1     \n",
              "8                                                    1     \n",
              "9                                                    1     \n",
              "10                                                   1     \n",
              "..                                                 ...     \n",
              "778                                                  0     \n",
              "779                                                  0     \n",
              "780                                                  1     \n",
              "781                                                  0     \n",
              "782                                                  0     \n",
              "783                                                  1     \n",
              "784                                                  0     \n",
              "785                                                  1     \n",
              "786                                                  0     \n",
              "787                                                  1     \n",
              "\n",
              "0    Have you completed the Principles and Techniques of Data Science requirement?  \\\n",
              "1                                                    0                               \n",
              "2                                                    1                               \n",
              "3                                                    0                               \n",
              "4                                                    1                               \n",
              "5                                                    1                               \n",
              "6                                                    1                               \n",
              "7                                                    1                               \n",
              "8                                                    1                               \n",
              "9                                                    1                               \n",
              "10                                                   1                               \n",
              "..                                                 ...                               \n",
              "778                                                  0                               \n",
              "779                                                  0                               \n",
              "780                                                  1                               \n",
              "781                                                  0                               \n",
              "782                                                  0                               \n",
              "783                                                  0                               \n",
              "784                                                  0                               \n",
              "785                                                  0                               \n",
              "786                                                  0                               \n",
              "787                                                  0                               \n",
              "\n",
              "0    Have you completed one course towards the Computational and Inferential Depth requirement?  \\\n",
              "1                                                    0                                            \n",
              "2                                                    1                                            \n",
              "3                                                    0                                            \n",
              "4                                                    0                                            \n",
              "5                                                    0                                            \n",
              "6                                                    1                                            \n",
              "7                                                    1                                            \n",
              "8                                                    1                                            \n",
              "9                                                    1                                            \n",
              "10                                                   1                                            \n",
              "..                                                 ...                                            \n",
              "778                                                  0                                            \n",
              "779                                                  0                                            \n",
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              "785                                                  0                                            \n",
              "786                                                  1                                            \n",
              "787                                                  0                                            \n",
              "\n",
              "0    Have you completed the second course towards the Computational and Inferential Depth requirement?  \\\n",
              "1                                                    0                                                   \n",
              "2                                                    0                                                   \n",
              "3                                                    0                                                   \n",
              "4                                                    0                                                   \n",
              "5                                                    0                                                   \n",
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              "785                                                  0                                                   \n",
              "786                                                  0                                                   \n",
              "787                                                  0                                                   \n",
              "\n",
              "0    Have you completed the Probability requirement?  \\\n",
              "1                                                  0   \n",
              "2                                                  1   \n",
              "3                                                  0   \n",
              "4                                                  1   \n",
              "5                                                  0   \n",
              "6                                                  0   \n",
              "7                                                  1   \n",
              "8                                                  1   \n",
              "9                                                  0   \n",
              "10                                                 1   \n",
              "..                                               ...   \n",
              "778                                                0   \n",
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              "782                                                0   \n",
              "783                                                0   \n",
              "784                                                0   \n",
              "785                                                0   \n",
              "786                                                0   \n",
              "787                                                0   \n",
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              "0    Have you completed the Human Contexts and Ethics requirement?  \\\n",
              "1                                                    0               \n",
              "2                                                    1               \n",
              "3                                                    0               \n",
              "4                                                    0               \n",
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              "779                                                  0               \n",
              "780                                                  0               \n",
              "781                                                  0               \n",
              "782                                                  0               \n",
              "783                                                  0               \n",
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              "785                                                  0               \n",
              "786                                                  0               \n",
              "787                                                  0               \n",
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              "0    Have you completed the Modeling, Learning, and Decision-Making requirement?  \\\n",
              "1                                                    0                             \n",
              "2                                                    0                             \n",
              "3                                                    0                             \n",
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              "10                                                   1                             \n",
              "..                                                 ...                             \n",
              "778                                                  0                             \n",
              "779                                                  0                             \n",
              "780                                                  0                             \n",
              "781                                                  0                             \n",
              "782                                                  0                             \n",
              "783                                                  0                             \n",
              "784                                                  0                             \n",
              "785                                                  0                             \n",
              "786                                                  0                             \n",
              "787                                                  0                             \n",
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              "0    Have you completed one lower-division course towards a Domain Emphasis?  \\\n",
              "1                                                    0                         \n",
              "2                                                    1                         \n",
              "3                                                    0                         \n",
              "4                                                    1                         \n",
              "5                                                    1                         \n",
              "6                                                    1                         \n",
              "7                                                    1                         \n",
              "8                                                    0                         \n",
              "9                                                    1                         \n",
              "10                                                   1                         \n",
              "..                                                 ...                         \n",
              "778                                                  0                         \n",
              "779                                                  1                         \n",
              "780                                                  1                         \n",
              "781                                                  1                         \n",
              "782                                                  0                         \n",
              "783                                                  1                         \n",
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              "785                                                  0                         \n",
              "786                                                  1                         \n",
              "787                                                  1                         \n",
              "\n",
              "0    Have you completed one upper-division course towards a Domain Emphasis?  \\\n",
              "1                                                    0                         \n",
              "2                                                    1                         \n",
              "3                                                    0                         \n",
              "4                                                    1                         \n",
              "5                                                    1                         \n",
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              "7                                                    1                         \n",
              "8                                                    1                         \n",
              "9                                                    1                         \n",
              "10                                                   1                         \n",
              "..                                                 ...                         \n",
              "778                                                  0                         \n",
              "779                                                  1                         \n",
              "780                                                  1                         \n",
              "781                                                  1                         \n",
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              "783                                                  1                         \n",
              "784                                                  0                         \n",
              "785                                                  0                         \n",
              "786                                                  1                         \n",
              "787                                                  0                         \n",
              "\n",
              "0    Have you completed a second upper-division course towards a Domain Emphasis?  \\\n",
              "1                                                    0                              \n",
              "2                                                    1                              \n",
              "3                                                    0                              \n",
              "4                                                    0                              \n",
              "5                                                    1                              \n",
              "6                                                    0                              \n",
              "7                                                    0                              \n",
              "8                                                    1                              \n",
              "9                                                    0                              \n",
              "10                                                   0                              \n",
              "..                                                 ...                              \n",
              "778                                                  0                              \n",
              "779                                                  0                              \n",
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              "781                                                  1                              \n",
              "782                                                  0                              \n",
              "783                                                  1                              \n",
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              "785                                                  0                              \n",
              "786                                                  1                              \n",
              "787                                                  0                              \n",
              "\n",
              "0    Are you a transfer student?  Are you expected to graduate in Fall 2018?  \\\n",
              "1                              0                                           0   \n",
              "2                              0                                           0   \n",
              "3                              0                                           0   \n",
              "4                              0                                           0   \n",
              "5                              0                                           0   \n",
              "6                              0                                           0   \n",
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              "8                              0                                           0   \n",
              "9                              0                                           0   \n",
              "10                             0                                           0   \n",
              "..                           ...                                         ...   \n",
              "778                            0                                           0   \n",
              "779                            1                                           0   \n",
              "780                            1                                           0   \n",
              "781                            1                                           1   \n",
              "782                            1                                           0   \n",
              "783                            1                                           0   \n",
              "784                            0                                           0   \n",
              "785                            0                                           0   \n",
              "786                            0                                           0   \n",
              "787                            0                                           0   \n",
              "\n",
              "0    Are you expected to graduate in Spring or Summer 2019?  \\\n",
              "1                                                    0        \n",
              "2                                                    1        \n",
              "3                                                    0        \n",
              "4                                                    0        \n",
              "5                                                    0        \n",
              "6                                                    0        \n",
              "7                                                    1        \n",
              "8                                                    0        \n",
              "9                                                    0        \n",
              "10                                                   0        \n",
              "..                                                 ...        \n",
              "778                                                  0        \n",
              "779                                                  0        \n",
              "780                                                  1        \n",
              "781                                                  0        \n",
              "782                                                  0        \n",
              "783                                                  0        \n",
              "784                                                  0        \n",
              "785                                                  0        \n",
              "786                                                  0        \n",
              "787                                                  0        \n",
              "\n",
              "0   What is your current Expected Graduation Term?  \\\n",
              "1                                                0   \n",
              "2                                                0   \n",
              "3                                                0   \n",
              "4                                      Spring 2020   \n",
              "5                                      Spring 2020   \n",
              "6                                        Fall 2019   \n",
              "7                                                0   \n",
              "8                                        Fall 2019   \n",
              "9                                      Spring 2020   \n",
              "10                                     Spring 2020   \n",
              "..                                             ...   \n",
              "778                                    Spring 2022   \n",
              "779                                    Spring 2020   \n",
              "780                                              0   \n",
              "781                                              0   \n",
              "782                                    Spring 2020   \n",
              "783                                    Spring 2020   \n",
              "784                                    Spring 2021   \n",
              "785                                    Spring 2022   \n",
              "786                                    Spring 2020   \n",
              "787                                    Spring 2021   \n",
              "\n",
              "0    Are you currently already declared in another major?  \n",
              "1                                                    0     \n",
              "2                                                    1     \n",
              "3                                                    0     \n",
              "4                                                    0     \n",
              "5                                                    0     \n",
              "6                                                    0     \n",
              "7                                                    1     \n",
              "8                                                    1     \n",
              "9                                                    1     \n",
              "10                                                   1     \n",
              "..                                                 ...     \n",
              "778                                                  0     \n",
              "779                                                  0     \n",
              "780                                                  1     \n",
              "781                                                  1     \n",
              "782                                                  0     \n",
              "783                                                  1     \n",
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              "785                                                  0     \n",
              "786                                                  1     \n",
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              "\n",
              "[787 rows x 21 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "metadata": {
        "id": "5YTWnkhvQ9V5",
        "colab_type": "code",
        "outputId": "879afd04-dc1a-4adc-8b47-62d2667241e3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 586
        }
      },
      "cell_type": "code",
      "source": [
        "grouped_by_grad_term = df.groupby(df['What is your current Expected Graduation Term?'])\n",
        "grouped_by_grad_term.agg(sum)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Have you completed the Foundations of Data Science requirement?</th>\n",
              "      <th>Have you completed the Calculus I requirement?</th>\n",
              "      <th>Have you completed the Calculus II requirement?</th>\n",
              "      <th>Have you completed the Linear Algebra requirement?</th>\n",
              "      <th>Have you completed the Program Structures requirement?</th>\n",
              "      <th>Have you completed the Data Structures requirement?</th>\n",
              "      <th>Have you completed the Principles and Techniques of Data Science requirement?</th>\n",
              "      <th>Have you completed one course towards the Computational and Inferential Depth requirement?</th>\n",
              "      <th>Have you completed the second course towards the Computational and Inferential Depth requirement?</th>\n",
              "      <th>Have you completed the Probability requirement?</th>\n",
              "      <th>Have you completed the Human Contexts and Ethics requirement?</th>\n",
              "      <th>Have you completed the Modeling, Learning, and Decision-Making requirement?</th>\n",
              "      <th>Have you completed one lower-division course towards a Domain Emphasis?</th>\n",
              "      <th>Have you completed one upper-division course towards a Domain Emphasis?</th>\n",
              "      <th>Have you completed a second upper-division course towards a Domain Emphasis?</th>\n",
              "      <th>Are you a transfer student?</th>\n",
              "      <th>Are you expected to graduate in Fall 2018?</th>\n",
              "      <th>Are you expected to graduate in Spring or Summer 2019?</th>\n",
              "      <th>Are you currently already declared in another major?</th>\n",
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              "      <th>What is your current Expected Graduation Term?</th>\n",
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              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <td>327</td>\n",
              "      <td>303</td>\n",
              "      <td>272</td>\n",
              "      <td>288</td>\n",
              "      <td>173</td>\n",
              "      <td>141</td>\n",
              "      <td>158</td>\n",
              "      <td>110</td>\n",
              "      <td>137</td>\n",
              "      <td>95</td>\n",
              "      <td>66</td>\n",
              "      <td>160</td>\n",
              "      <td>130</td>\n",
              "      <td>85</td>\n",
              "      <td>54</td>\n",
              "      <td>22</td>\n",
              "      <td>161</td>\n",
              "      <td>146</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fall 2019</th>\n",
              "      <td>23</td>\n",
              "      <td>28</td>\n",
              "      <td>28</td>\n",
              "      <td>27</td>\n",
              "      <td>28</td>\n",
              "      <td>27</td>\n",
              "      <td>18</td>\n",
              "      <td>17</td>\n",
              "      <td>10</td>\n",
              "      <td>15</td>\n",
              "      <td>16</td>\n",
              "      <td>4</td>\n",
              "      <td>17</td>\n",
              "      <td>11</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fall 2020</th>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>5</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
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              "    <tr>\n",
              "      <th>Fall 2021</th>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>Spring 2020</th>\n",
              "      <td>271</td>\n",
              "      <td>290</td>\n",
              "      <td>281</td>\n",
              "      <td>282</td>\n",
              "      <td>285</td>\n",
              "      <td>279</td>\n",
              "      <td>200</td>\n",
              "      <td>162</td>\n",
              "      <td>71</td>\n",
              "      <td>149</td>\n",
              "      <td>94</td>\n",
              "      <td>14</td>\n",
              "      <td>211</td>\n",
              "      <td>131</td>\n",
              "      <td>35</td>\n",
              "      <td>13</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>143</td>\n",
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              "    <tr>\n",
              "      <th>Spring 2021</th>\n",
              "      <td>100</td>\n",
              "      <td>118</td>\n",
              "      <td>117</td>\n",
              "      <td>98</td>\n",
              "      <td>115</td>\n",
              "      <td>109</td>\n",
              "      <td>32</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>15</td>\n",
              "      <td>16</td>\n",
              "      <td>1</td>\n",
              "      <td>45</td>\n",
              "      <td>9</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Spring 2022</th>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Summer 2020</th>\n",
              "      <td>7</td>\n",
              "      <td>8</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
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              "</table>\n",
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            ],
            "text/plain": [
              "0                                               Have you completed the Foundations of Data Science requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                                    \n",
              "0                                                                                             286                 \n",
              "Fall 2019                                                                                      23                 \n",
              "Fall 2020                                                                                       6                 \n",
              "Fall 2021                                                                                       3                 \n",
              "Spring 2020                                                                                   271                 \n",
              "Spring 2021                                                                                   100                 \n",
              "Spring 2022                                                                                     2                 \n",
              "Summer 2020                                                                                     7                 \n",
              "\n",
              "0                                               Have you completed the Calculus I requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                   \n",
              "0                                                                                          327   \n",
              "Fall 2019                                                                                   28   \n",
              "Fall 2020                                                                                    6   \n",
              "Fall 2021                                                                                    3   \n",
              "Spring 2020                                                                                290   \n",
              "Spring 2021                                                                                118   \n",
              "Spring 2022                                                                                  3   \n",
              "Summer 2020                                                                                  8   \n",
              "\n",
              "0                                               Have you completed the Calculus II requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                    \n",
              "0                                                                                           303   \n",
              "Fall 2019                                                                                    28   \n",
              "Fall 2020                                                                                     6   \n",
              "Fall 2021                                                                                     3   \n",
              "Spring 2020                                                                                 281   \n",
              "Spring 2021                                                                                 117   \n",
              "Spring 2022                                                                                   2   \n",
              "Summer 2020                                                                                   6   \n",
              "\n",
              "0                                               Have you completed the Linear Algebra requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                       \n",
              "0                                                                                             272    \n",
              "Fall 2019                                                                                      27    \n",
              "Fall 2020                                                                                       6    \n",
              "Fall 2021                                                                                       3    \n",
              "Spring 2020                                                                                   282    \n",
              "Spring 2021                                                                                    98    \n",
              "Spring 2022                                                                                     1    \n",
              "Summer 2020                                                                                     6    \n",
              "\n",
              "0                                               Have you completed the Program Structures requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                           \n",
              "0                                                                                             288        \n",
              "Fall 2019                                                                                      28        \n",
              "Fall 2020                                                                                       6        \n",
              "Fall 2021                                                                                       3        \n",
              "Spring 2020                                                                                   285        \n",
              "Spring 2021                                                                                   115        \n",
              "Spring 2022                                                                                     1        \n",
              "Summer 2020                                                                                     7        \n",
              "\n",
              "0                                               Have you completed the Data Structures requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                        \n",
              "0                                                                                             173     \n",
              "Fall 2019                                                                                      27     \n",
              "Fall 2020                                                                                       5     \n",
              "Fall 2021                                                                                       3     \n",
              "Spring 2020                                                                                   279     \n",
              "Spring 2021                                                                                   109     \n",
              "Spring 2022                                                                                     1     \n",
              "Summer 2020                                                                                     5     \n",
              "\n",
              "0                                               Have you completed the Principles and Techniques of Data Science requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                                                  \n",
              "0                                                                                             141                               \n",
              "Fall 2019                                                                                      18                               \n",
              "Fall 2020                                                                                       4                               \n",
              "Fall 2021                                                                                       0                               \n",
              "Spring 2020                                                                                   200                               \n",
              "Spring 2021                                                                                    32                               \n",
              "Spring 2022                                                                                     0                               \n",
              "Summer 2020                                                                                     1                               \n",
              "\n",
              "0                                               Have you completed one course towards the Computational and Inferential Depth requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                                                               \n",
              "0                                                                                             158                                            \n",
              "Fall 2019                                                                                      17                                            \n",
              "Fall 2020                                                                                       1                                            \n",
              "Fall 2021                                                                                       0                                            \n",
              "Spring 2020                                                                                   162                                            \n",
              "Spring 2021                                                                                     7                                            \n",
              "Spring 2022                                                                                     0                                            \n",
              "Summer 2020                                                                                     2                                            \n",
              "\n",
              "0                                               Have you completed the second course towards the Computational and Inferential Depth requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                                                                      \n",
              "0                                                                                             110                                                   \n",
              "Fall 2019                                                                                      10                                                   \n",
              "Fall 2020                                                                                       0                                                   \n",
              "Fall 2021                                                                                       0                                                   \n",
              "Spring 2020                                                                                    71                                                   \n",
              "Spring 2021                                                                                     2                                                   \n",
              "Spring 2022                                                                                     0                                                   \n",
              "Summer 2020                                                                                     1                                                   \n",
              "\n",
              "0                                               Have you completed the Probability requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                    \n",
              "0                                                                                           137   \n",
              "Fall 2019                                                                                    15   \n",
              "Fall 2020                                                                                     4   \n",
              "Fall 2021                                                                                     0   \n",
              "Spring 2020                                                                                 149   \n",
              "Spring 2021                                                                                  15   \n",
              "Spring 2022                                                                                   0   \n",
              "Summer 2020                                                                                   3   \n",
              "\n",
              "0                                               Have you completed the Human Contexts and Ethics requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                                  \n",
              "0                                                                                              95               \n",
              "Fall 2019                                                                                      16               \n",
              "Fall 2020                                                                                       0               \n",
              "Fall 2021                                                                                       0               \n",
              "Spring 2020                                                                                    94               \n",
              "Spring 2021                                                                                    16               \n",
              "Spring 2022                                                                                     0               \n",
              "Summer 2020                                                                                     2               \n",
              "\n",
              "0                                               Have you completed the Modeling, Learning, and Decision-Making requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                                                \n",
              "0                                                                                              66                             \n",
              "Fall 2019                                                                                       4                             \n",
              "Fall 2020                                                                                       0                             \n",
              "Fall 2021                                                                                       0                             \n",
              "Spring 2020                                                                                    14                             \n",
              "Spring 2021                                                                                     1                             \n",
              "Spring 2022                                                                                     0                             \n",
              "Summer 2020                                                                                     0                             \n",
              "\n",
              "0                                               Have you completed one lower-division course towards a Domain Emphasis?  \\\n",
              "What is your current Expected Graduation Term?                                                                            \n",
              "0                                                                                             160                         \n",
              "Fall 2019                                                                                      17                         \n",
              "Fall 2020                                                                                       5                         \n",
              "Fall 2021                                                                                       1                         \n",
              "Spring 2020                                                                                   211                         \n",
              "Spring 2021                                                                                    45                         \n",
              "Spring 2022                                                                                     0                         \n",
              "Summer 2020                                                                                     5                         \n",
              "\n",
              "0                                               Have you completed one upper-division course towards a Domain Emphasis?  \\\n",
              "What is your current Expected Graduation Term?                                                                            \n",
              "0                                                                                             130                         \n",
              "Fall 2019                                                                                      11                         \n",
              "Fall 2020                                                                                       3                         \n",
              "Fall 2021                                                                                       0                         \n",
              "Spring 2020                                                                                   131                         \n",
              "Spring 2021                                                                                     9                         \n",
              "Spring 2022                                                                                     0                         \n",
              "Summer 2020                                                                                     1                         \n",
              "\n",
              "0                                               Have you completed a second upper-division course towards a Domain Emphasis?  \\\n",
              "What is your current Expected Graduation Term?                                                                                 \n",
              "0                                                                                              85                              \n",
              "Fall 2019                                                                                       5                              \n",
              "Fall 2020                                                                                       1                              \n",
              "Fall 2021                                                                                       0                              \n",
              "Spring 2020                                                                                    35                              \n",
              "Spring 2021                                                                                     0                              \n",
              "Spring 2022                                                                                     0                              \n",
              "Summer 2020                                                                                     1                              \n",
              "\n",
              "0                                               Are you a transfer student?  \\\n",
              "What is your current Expected Graduation Term?                                \n",
              "0                                                                        54   \n",
              "Fall 2019                                                                 6   \n",
              "Fall 2020                                                                 2   \n",
              "Fall 2021                                                                 0   \n",
              "Spring 2020                                                              13   \n",
              "Spring 2021                                                               1   \n",
              "Spring 2022                                                               0   \n",
              "Summer 2020                                                               5   \n",
              "\n",
              "0                                               Are you expected to graduate in Fall 2018?  \\\n",
              "What is your current Expected Graduation Term?                                               \n",
              "0                                                                                       22   \n",
              "Fall 2019                                                                                0   \n",
              "Fall 2020                                                                                0   \n",
              "Fall 2021                                                                                0   \n",
              "Spring 2020                                                                              0   \n",
              "Spring 2021                                                                              0   \n",
              "Spring 2022                                                                              0   \n",
              "Summer 2020                                                                              0   \n",
              "\n",
              "0                                               Are you expected to graduate in Spring or Summer 2019?  \\\n",
              "What is your current Expected Graduation Term?                                                           \n",
              "0                                                                                             161        \n",
              "Fall 2019                                                                                       0        \n",
              "Fall 2020                                                                                       0        \n",
              "Fall 2021                                                                                       0        \n",
              "Spring 2020                                                                                     0        \n",
              "Spring 2021                                                                                     0        \n",
              "Spring 2022                                                                                     0        \n",
              "Summer 2020                                                                                     0        \n",
              "\n",
              "0                                               Are you currently already declared in another major?  \n",
              "What is your current Expected Graduation Term?                                                        \n",
              "0                                                                                             146     \n",
              "Fall 2019                                                                                      16     \n",
              "Fall 2020                                                                                       4     \n",
              "Fall 2021                                                                                       0     \n",
              "Spring 2020                                                                                   143     \n",
              "Spring 2021                                                                                    20     \n",
              "Spring 2022                                                                                     0     \n",
              "Summer 2020                                                                                     3     "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "metadata": {
        "id": "jMzeVYBDu_wa",
        "colab_type": "code",
        "outputId": "8fb43352-407e-45d7-e463-e76e7c3d13cc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 586
        }
      },
      "cell_type": "code",
      "source": [
        "# Table of the number of students that answered NO.\n",
        "answered_no = grouped_by_grad_term.count().subtract(grouped_by_grad_term.agg(sum))\n",
        "\n",
        "answered_no"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Are you a transfer student?</th>\n",
              "      <th>Are you currently already declared in another major?</th>\n",
              "      <th>Are you expected to graduate in Fall 2018?</th>\n",
              "      <th>Are you expected to graduate in Spring or Summer 2019?</th>\n",
              "      <th>Have you completed a second upper-division course towards a Domain Emphasis?</th>\n",
              "      <th>Have you completed one course towards the Computational and Inferential Depth requirement?</th>\n",
              "      <th>Have you completed one lower-division course towards a Domain Emphasis?</th>\n",
              "      <th>Have you completed one upper-division course towards a Domain Emphasis?</th>\n",
              "      <th>Have you completed the Calculus I requirement?</th>\n",
              "      <th>Have you completed the Calculus II requirement?</th>\n",
              "      <th>Have you completed the Data Structures requirement?</th>\n",
              "      <th>Have you completed the Foundations of Data Science requirement?</th>\n",
              "      <th>Have you completed the Human Contexts and Ethics requirement?</th>\n",
              "      <th>Have you completed the Linear Algebra requirement?</th>\n",
              "      <th>Have you completed the Modeling, Learning, and Decision-Making requirement?</th>\n",
              "      <th>Have you completed the Principles and Techniques of Data Science requirement?</th>\n",
              "      <th>Have you completed the Probability requirement?</th>\n",
              "      <th>Have you completed the Program Structures requirement?</th>\n",
              "      <th>Have you completed the second course towards the Computational and Inferential Depth requirement?</th>\n",
              "      <th>Timestamp</th>\n",
              "      <th>What is your current Expected Graduation Term?</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>What is your current Expected Graduation Term?</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>274</td>\n",
              "      <td>182</td>\n",
              "      <td>306</td>\n",
              "      <td>167</td>\n",
              "      <td>243</td>\n",
              "      <td>170</td>\n",
              "      <td>168</td>\n",
              "      <td>198</td>\n",
              "      <td>1</td>\n",
              "      <td>25</td>\n",
              "      <td>155</td>\n",
              "      <td>42</td>\n",
              "      <td>233</td>\n",
              "      <td>56</td>\n",
              "      <td>262</td>\n",
              "      <td>187</td>\n",
              "      <td>191</td>\n",
              "      <td>40</td>\n",
              "      <td>218</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fall 2019</th>\n",
              "      <td>22</td>\n",
              "      <td>12</td>\n",
              "      <td>28</td>\n",
              "      <td>28</td>\n",
              "      <td>23</td>\n",
              "      <td>11</td>\n",
              "      <td>11</td>\n",
              "      <td>17</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "      <td>24</td>\n",
              "      <td>10</td>\n",
              "      <td>13</td>\n",
              "      <td>0</td>\n",
              "      <td>18</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fall 2020</th>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>Fall 2021</th>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Spring 2020</th>\n",
              "      <td>277</td>\n",
              "      <td>147</td>\n",
              "      <td>290</td>\n",
              "      <td>290</td>\n",
              "      <td>255</td>\n",
              "      <td>128</td>\n",
              "      <td>79</td>\n",
              "      <td>159</td>\n",
              "      <td>0</td>\n",
              "      <td>9</td>\n",
              "      <td>11</td>\n",
              "      <td>19</td>\n",
              "      <td>196</td>\n",
              "      <td>8</td>\n",
              "      <td>276</td>\n",
              "      <td>90</td>\n",
              "      <td>141</td>\n",
              "      <td>5</td>\n",
              "      <td>219</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Spring 2021</th>\n",
              "      <td>117</td>\n",
              "      <td>98</td>\n",
              "      <td>118</td>\n",
              "      <td>118</td>\n",
              "      <td>118</td>\n",
              "      <td>111</td>\n",
              "      <td>73</td>\n",
              "      <td>109</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>18</td>\n",
              "      <td>102</td>\n",
              "      <td>20</td>\n",
              "      <td>117</td>\n",
              "      <td>86</td>\n",
              "      <td>103</td>\n",
              "      <td>3</td>\n",
              "      <td>116</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Spring 2022</th>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Summer 2020</th>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>7</td>\n",
              "      <td>6</td>\n",
              "      <td>3</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>8</td>\n",
              "      <td>7</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "0                                               Are you a transfer student?  \\\n",
              "What is your current Expected Graduation Term?                                \n",
              "0                                                                       274   \n",
              "Fall 2019                                                                22   \n",
              "Fall 2020                                                                 5   \n",
              "Fall 2021                                                                 3   \n",
              "Spring 2020                                                             277   \n",
              "Spring 2021                                                             117   \n",
              "Spring 2022                                                               5   \n",
              "Summer 2020                                                               3   \n",
              "\n",
              "0                                               Are you currently already declared in another major?  \\\n",
              "What is your current Expected Graduation Term?                                                         \n",
              "0                                                                                             182      \n",
              "Fall 2019                                                                                      12      \n",
              "Fall 2020                                                                                       3      \n",
              "Fall 2021                                                                                       3      \n",
              "Spring 2020                                                                                   147      \n",
              "Spring 2021                                                                                    98      \n",
              "Spring 2022                                                                                     5      \n",
              "Summer 2020                                                                                     5      \n",
              "\n",
              "0                                               Are you expected to graduate in Fall 2018?  \\\n",
              "What is your current Expected Graduation Term?                                               \n",
              "0                                                                                      306   \n",
              "Fall 2019                                                                               28   \n",
              "Fall 2020                                                                                7   \n",
              "Fall 2021                                                                                3   \n",
              "Spring 2020                                                                            290   \n",
              "Spring 2021                                                                            118   \n",
              "Spring 2022                                                                              5   \n",
              "Summer 2020                                                                              8   \n",
              "\n",
              "0                                               Are you expected to graduate in Spring or Summer 2019?  \\\n",
              "What is your current Expected Graduation Term?                                                           \n",
              "0                                                                                             167        \n",
              "Fall 2019                                                                                      28        \n",
              "Fall 2020                                                                                       7        \n",
              "Fall 2021                                                                                       3        \n",
              "Spring 2020                                                                                   290        \n",
              "Spring 2021                                                                                   118        \n",
              "Spring 2022                                                                                     5        \n",
              "Summer 2020                                                                                     8        \n",
              "\n",
              "0                                               Have you completed a second upper-division course towards a Domain Emphasis?  \\\n",
              "What is your current Expected Graduation Term?                                                                                 \n",
              "0                                                                                             243                              \n",
              "Fall 2019                                                                                      23                              \n",
              "Fall 2020                                                                                       6                              \n",
              "Fall 2021                                                                                       3                              \n",
              "Spring 2020                                                                                   255                              \n",
              "Spring 2021                                                                                   118                              \n",
              "Spring 2022                                                                                     5                              \n",
              "Summer 2020                                                                                     7                              \n",
              "\n",
              "0                                               Have you completed one course towards the Computational and Inferential Depth requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                                                               \n",
              "0                                                                                             170                                            \n",
              "Fall 2019                                                                                      11                                            \n",
              "Fall 2020                                                                                       6                                            \n",
              "Fall 2021                                                                                       3                                            \n",
              "Spring 2020                                                                                   128                                            \n",
              "Spring 2021                                                                                   111                                            \n",
              "Spring 2022                                                                                     5                                            \n",
              "Summer 2020                                                                                     6                                            \n",
              "\n",
              "0                                               Have you completed one lower-division course towards a Domain Emphasis?  \\\n",
              "What is your current Expected Graduation Term?                                                                            \n",
              "0                                                                                             168                         \n",
              "Fall 2019                                                                                      11                         \n",
              "Fall 2020                                                                                       2                         \n",
              "Fall 2021                                                                                       2                         \n",
              "Spring 2020                                                                                    79                         \n",
              "Spring 2021                                                                                    73                         \n",
              "Spring 2022                                                                                     5                         \n",
              "Summer 2020                                                                                     3                         \n",
              "\n",
              "0                                               Have you completed one upper-division course towards a Domain Emphasis?  \\\n",
              "What is your current Expected Graduation Term?                                                                            \n",
              "0                                                                                             198                         \n",
              "Fall 2019                                                                                      17                         \n",
              "Fall 2020                                                                                       4                         \n",
              "Fall 2021                                                                                       3                         \n",
              "Spring 2020                                                                                   159                         \n",
              "Spring 2021                                                                                   109                         \n",
              "Spring 2022                                                                                     5                         \n",
              "Summer 2020                                                                                     7                         \n",
              "\n",
              "0                                               Have you completed the Calculus I requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                   \n",
              "0                                                                                            1   \n",
              "Fall 2019                                                                                    0   \n",
              "Fall 2020                                                                                    1   \n",
              "Fall 2021                                                                                    0   \n",
              "Spring 2020                                                                                  0   \n",
              "Spring 2021                                                                                  0   \n",
              "Spring 2022                                                                                  2   \n",
              "Summer 2020                                                                                  0   \n",
              "\n",
              "0                                               Have you completed the Calculus II requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                    \n",
              "0                                                                                            25   \n",
              "Fall 2019                                                                                     0   \n",
              "Fall 2020                                                                                     1   \n",
              "Fall 2021                                                                                     0   \n",
              "Spring 2020                                                                                   9   \n",
              "Spring 2021                                                                                   1   \n",
              "Spring 2022                                                                                   3   \n",
              "Summer 2020                                                                                   2   \n",
              "\n",
              "0                                               Have you completed the Data Structures requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                        \n",
              "0                                                                                             155     \n",
              "Fall 2019                                                                                       1     \n",
              "Fall 2020                                                                                       2     \n",
              "Fall 2021                                                                                       0     \n",
              "Spring 2020                                                                                    11     \n",
              "Spring 2021                                                                                     9     \n",
              "Spring 2022                                                                                     4     \n",
              "Summer 2020                                                                                     3     \n",
              "\n",
              "0                                               Have you completed the Foundations of Data Science requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                                    \n",
              "0                                                                                              42                 \n",
              "Fall 2019                                                                                       5                 \n",
              "Fall 2020                                                                                       1                 \n",
              "Fall 2021                                                                                       0                 \n",
              "Spring 2020                                                                                    19                 \n",
              "Spring 2021                                                                                    18                 \n",
              "Spring 2022                                                                                     3                 \n",
              "Summer 2020                                                                                     1                 \n",
              "\n",
              "0                                               Have you completed the Human Contexts and Ethics requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                                  \n",
              "0                                                                                             233               \n",
              "Fall 2019                                                                                      12               \n",
              "Fall 2020                                                                                       7               \n",
              "Fall 2021                                                                                       3               \n",
              "Spring 2020                                                                                   196               \n",
              "Spring 2021                                                                                   102               \n",
              "Spring 2022                                                                                     5               \n",
              "Summer 2020                                                                                     6               \n",
              "\n",
              "0                                               Have you completed the Linear Algebra requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                       \n",
              "0                                                                                              56    \n",
              "Fall 2019                                                                                       1    \n",
              "Fall 2020                                                                                       1    \n",
              "Fall 2021                                                                                       0    \n",
              "Spring 2020                                                                                     8    \n",
              "Spring 2021                                                                                    20    \n",
              "Spring 2022                                                                                     4    \n",
              "Summer 2020                                                                                     2    \n",
              "\n",
              "0                                               Have you completed the Modeling, Learning, and Decision-Making requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                                                \n",
              "0                                                                                             262                             \n",
              "Fall 2019                                                                                      24                             \n",
              "Fall 2020                                                                                       7                             \n",
              "Fall 2021                                                                                       3                             \n",
              "Spring 2020                                                                                   276                             \n",
              "Spring 2021                                                                                   117                             \n",
              "Spring 2022                                                                                     5                             \n",
              "Summer 2020                                                                                     8                             \n",
              "\n",
              "0                                               Have you completed the Principles and Techniques of Data Science requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                                                  \n",
              "0                                                                                             187                               \n",
              "Fall 2019                                                                                      10                               \n",
              "Fall 2020                                                                                       3                               \n",
              "Fall 2021                                                                                       3                               \n",
              "Spring 2020                                                                                    90                               \n",
              "Spring 2021                                                                                    86                               \n",
              "Spring 2022                                                                                     5                               \n",
              "Summer 2020                                                                                     7                               \n",
              "\n",
              "0                                               Have you completed the Probability requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                    \n",
              "0                                                                                           191   \n",
              "Fall 2019                                                                                    13   \n",
              "Fall 2020                                                                                     3   \n",
              "Fall 2021                                                                                     3   \n",
              "Spring 2020                                                                                 141   \n",
              "Spring 2021                                                                                 103   \n",
              "Spring 2022                                                                                   5   \n",
              "Summer 2020                                                                                   5   \n",
              "\n",
              "0                                               Have you completed the Program Structures requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                           \n",
              "0                                                                                              40        \n",
              "Fall 2019                                                                                       0        \n",
              "Fall 2020                                                                                       1        \n",
              "Fall 2021                                                                                       0        \n",
              "Spring 2020                                                                                     5        \n",
              "Spring 2021                                                                                     3        \n",
              "Spring 2022                                                                                     4        \n",
              "Summer 2020                                                                                     1        \n",
              "\n",
              "0                                               Have you completed the second course towards the Computational and Inferential Depth requirement?  \\\n",
              "What is your current Expected Graduation Term?                                                                                                      \n",
              "0                                                                                             218                                                   \n",
              "Fall 2019                                                                                      18                                                   \n",
              "Fall 2020                                                                                       7                                                   \n",
              "Fall 2021                                                                                       3                                                   \n",
              "Spring 2020                                                                                   219                                                   \n",
              "Spring 2021                                                                                   116                                                   \n",
              "Spring 2022                                                                                     5                                                   \n",
              "Summer 2020                                                                                     7                                                   \n",
              "\n",
              "0                                               Timestamp  \\\n",
              "What is your current Expected Graduation Term?              \n",
              "0                                                     NaN   \n",
              "Fall 2019                                             NaN   \n",
              "Fall 2020                                             NaN   \n",
              "Fall 2021                                             NaN   \n",
              "Spring 2020                                           NaN   \n",
              "Spring 2021                                           NaN   \n",
              "Spring 2022                                           NaN   \n",
              "Summer 2020                                           NaN   \n",
              "\n",
              "0                                               What is your current Expected Graduation Term?  \n",
              "What is your current Expected Graduation Term?                                                  \n",
              "0                                                                                          NaN  \n",
              "Fall 2019                                                                                  NaN  \n",
              "Fall 2020                                                                                  NaN  \n",
              "Fall 2021                                                                                  NaN  \n",
              "Spring 2020                                                                                NaN  \n",
              "Spring 2021                                                                                NaN  \n",
              "Spring 2022                                                                                NaN  \n",
              "Summer 2020                                                                                NaN  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "metadata": {
        "id": "DoQDue0lkNxw",
        "colab_type": "code",
        "outputId": "4b35f365-c7fc-4f36-ddb2-121c5993fb69",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1384
        }
      },
      "cell_type": "code",
      "source": [
        "#Plot a bar graph of data frame after hot key encoding\n",
        "sums = list(df.sum()[1:])[::-1]\n",
        "cols = list(df)[1:][::-1]\n",
        "\n",
        "# This question wasn't included in the sums, since it has variable answers that could not be encoded\n",
        "cols.remove('What is your current Expected Graduation Term?')\n",
        "\n",
        "df_plot = pd.DataFrame({'Survey question' : cols, 'Students that responded YES or IN PROGRESS' : sums})\n",
        "df_plot.plot.barh(x='Survey question', y='Students that responded YES or IN PROGRESS')\n",
        "\n",
        "df_plot['Students that responded NO'] = len(df) - df_plot['Students that responded YES or IN PROGRESS']\n",
        "df_plot.plot.barh(x='Survey question', y='Students that responded NO')\n",
        "\n",
        "df_plot[4:13].plot.barh(x='Survey question', y='Students that responded NO')\n",
        "df_plot[4:13]"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\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>Students that responded YES or IN PROGRESS</th>\n",
              "      <th>Survey question</th>\n",
              "      <th>Students that responded NO</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>127</td>\n",
              "      <td>Have you completed a second upper-division cou...</td>\n",
              "      <td>660</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>285</td>\n",
              "      <td>Have you completed one upper-division course t...</td>\n",
              "      <td>502</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>444</td>\n",
              "      <td>Have you completed one lower-division course t...</td>\n",
              "      <td>343</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>85</td>\n",
              "      <td>Have you completed the Modeling, Learning, and...</td>\n",
              "      <td>702</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>223</td>\n",
              "      <td>Have you completed the Human Contexts and Ethi...</td>\n",
              "      <td>564</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>323</td>\n",
              "      <td>Have you completed the Probability requirement?</td>\n",
              "      <td>464</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>194</td>\n",
              "      <td>Have you completed the second course towards t...</td>\n",
              "      <td>593</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>347</td>\n",
              "      <td>Have you completed one course towards the Comp...</td>\n",
              "      <td>440</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>396</td>\n",
              "      <td>Have you completed the Principles and Techniqu...</td>\n",
              "      <td>391</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    Students that responded YES or IN PROGRESS  \\\n",
              "4                                          127   \n",
              "5                                          285   \n",
              "6                                          444   \n",
              "7                                           85   \n",
              "8                                          223   \n",
              "9                                          323   \n",
              "10                                         194   \n",
              "11                                         347   \n",
              "12                                         396   \n",
              "\n",
              "                                      Survey question  \\\n",
              "4   Have you completed a second upper-division cou...   \n",
              "5   Have you completed one upper-division course t...   \n",
              "6   Have you completed one lower-division course t...   \n",
              "7   Have you completed the Modeling, Learning, and...   \n",
              "8   Have you completed the Human Contexts and Ethi...   \n",
              "9     Have you completed the Probability requirement?   \n",
              "10  Have you completed the second course towards t...   \n",
              "11  Have you completed one course towards the Comp...   \n",
              "12  Have you completed the Principles and Techniqu...   \n",
              "\n",
              "    Students that responded NO  \n",
              "4                          660  \n",
              "5                          502  \n",
              "6                          343  \n",
              "7                          702  \n",
              "8                          564  \n",
              "9                          464  \n",
              "10                         593  \n",
              "11                         440  \n",
              "12                         391  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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fnx+9evWie/fuhISEMG/ePHr27Mnu3buVJc4+Pj4sXLiQo0ePolKpmD9/foX6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\nTcwAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9546927d68>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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WKO16/fp1hgwZwrx58zAxMVFiCw4ORq1W06BBA2bPnk18fDw7d+7E0NCQxMRE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\nJ/l33DZ9FaeYAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9546d3da58>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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+++wzbG1tlcdoWrduzYgRI2jWrJkymYs+NjY2vPPOO4wbNw4DAwO6dOmCsbFx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09K9eHg4EBISAgdO3Ys99GG8lTUN8ClS5d49913CQ4OZtWqVcbnmjVrRkREBI888gixsbFcuXKF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\nTMO4iIiIiIiIiJ/9A1OUSmd3aIAxAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9546c79eb8>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "OE2xsM_jExIC",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#Select rows of students who have completed lower division requirements\n",
        "upper_div_labels = ['Timestamp', 'Have you completed the Principles and Techniques of Data Science requirement?', 'Have you completed one course towards the Computational and Inferential Depth requirement?', 'Have you completed the second course towards the Computational and Inferential Depth requirement?', 'Have you completed the Probability requirement?', 'Have you completed the Human Contexts and Ethics requirement?', 'Have you completed the Modeling, Learning, and Decision-Making requirement?', 'Have you completed one lower-division course towards a Domain Emphasis?', 'Have you completed one upper-division course towards a Domain Emphasis?', 'Have you completed a second upper-division course towards a Domain Emphasis?', 'Are you a transfer student?', 'Are you expected to graduate in Fall 2018?', 'Are you expected to graduate in Spring or Summer 2019?', 'What is your current Expected Graduation Term?', 'Are you currently already declared in another major?']\n",
        "number_lower_div = df[df == 1].drop(columns = upper_div_labels).dropna().shape[0]\n",
        "lower_div_labels = ['Have you completed the Foundations of Data Science requirement?', 'Have you completed the Calculus I requirement?', 'Have you completed the Calculus II requirement?', 'Have you completed the Linear Algebra requirement?', 'Have you completed the Program Structures requirement?', 'Have you completed the Data Structures requirement?']\n"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "7uS8VpyFtcC2",
        "colab_type": "code",
        "outputId": "74201b19-5d10-4ed6-b5ee-bf3d43c1238d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 937
        }
      },
      "cell_type": "code",
      "source": [
        "#sort through each column for only Yes values or 1's\n",
        "lower_div = df.loc[lambda df: df['Have you completed the Data Structures requirement?'] ==1]\n",
        "lower_div = lower_div.loc[lambda df: df['Have you completed the Foundations of Data Science requirement?'] ==1]\n",
        "lower_div = lower_div.loc[lambda df: df['Have you completed the Calculus I requirement?'] ==1]\n",
        "lower_div = lower_div.loc[lambda df: df['Have you completed the Calculus II requirement?'] ==1]\n",
        "lower_div = lower_div.loc[lambda df: df['Have you completed the Linear Algebra requirement?'] ==1]\n",
        "\n",
        "\n",
        "\n",
        "#Table with rows of students who have completed lower division requirements\n",
        "lower_div = lower_div.loc[lambda df: df['Have you completed the Program Structures requirement?'] ==1]\n",
        "\n",
        "#number of students who have completed lower division\n",
        "num_lower_div = lower_div.shape[0]\n",
        "\n",
        "#Table with rows of students who have also completed HCE\n",
        "lower_div_and_HCE = lower_div.loc[lambda df: df['Have you completed the Human Contexts and Ethics requirement?'] ==1]\n",
        "\n",
        "#number of students who have also completed HCE\n",
        "num_lower_div_and_HCE = lower_div_and_HCE.shape[0]\n",
        "\n",
        "#Table with rows of students who are declared in another major\n",
        "lower_div_and_declared = lower_div.loc[lambda df: df['Are you currently already declared in another major?'] ==1]\n",
        "\n",
        "#number of students who are declared in another major\n",
        "num_lower_div_and_declared = lower_div_and_declared.shape[0]\n",
        "\n",
        "lower_div"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Timestamp</th>\n",
              "      <th>Have you completed the Foundations of Data Science requirement?</th>\n",
              "      <th>Have you completed the Calculus I requirement?</th>\n",
              "      <th>Have you completed the Calculus II requirement?</th>\n",
              "      <th>Have you completed the Linear Algebra requirement?</th>\n",
              "      <th>Have you completed the Program Structures requirement?</th>\n",
              "      <th>Have you completed the Data Structures requirement?</th>\n",
              "      <th>Have you completed the Principles and Techniques of Data Science requirement?</th>\n",
              "      <th>Have you completed one course towards the Computational and Inferential Depth requirement?</th>\n",
              "      <th>Have you completed the second course towards the Computational and Inferential Depth requirement?</th>\n",
              "      <th>Have you completed the Probability requirement?</th>\n",
              "      <th>Have you completed the Human Contexts and Ethics requirement?</th>\n",
              "      <th>Have you completed the Modeling, Learning, and Decision-Making requirement?</th>\n",
              "      <th>Have you completed one lower-division course towards a Domain Emphasis?</th>\n",
              "      <th>Have you completed one upper-division course towards a Domain Emphasis?</th>\n",
              "      <th>Have you completed a second upper-division course towards a Domain Emphasis?</th>\n",
              "      <th>Are you a transfer student?</th>\n",
              "      <th>Are you expected to graduate in Fall 2018?</th>\n",
              "      <th>Are you expected to graduate in Spring or Summer 2019?</th>\n",
              "      <th>What is your current Expected Graduation Term?</th>\n",
              "      <th>Are you currently already declared in another major?</th>\n",
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              "      <th>2</th>\n",
              "      <td>8/9/2018 15:34:04</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>1</td>\n",
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              "      <td>1</td>\n",
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              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>8/9/2018 15:35:11</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>8/9/2018 15:35:11</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>8/9/2018 15:35:40</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Fall 2019</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>8/9/2018 15:35:41</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>8/9/2018 15:35:41</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Fall 2019</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>8/9/2018 15:35:43</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>768</th>\n",
              "      <td>9/23/2018 23:56:55</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>769</th>\n",
              "      <td>9/24/2018 10:31:26</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>771</th>\n",
              "      <td>9/24/2018 11:46:49</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>775</th>\n",
              "      <td>9/24/2018 20:34:34</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2020</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>780</th>\n",
              "      <td>9/25/2018 15:24:15</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>785</th>\n",
              "      <td>9/26/2018 10:20:10</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2022</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>787</th>\n",
              "      <td>9/26/2018 12:08:25</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>Spring 2021</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>525 rows × 21 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "0             Timestamp  \\\n",
              "2     8/9/2018 15:34:04   \n",
              "4     8/9/2018 15:35:11   \n",
              "5     8/9/2018 15:35:11   \n",
              "6     8/9/2018 15:35:40   \n",
              "7     8/9/2018 15:35:41   \n",
              "8     8/9/2018 15:35:41   \n",
              "9     8/9/2018 15:35:43   \n",
              "..                  ...   \n",
              "768  9/23/2018 23:56:55   \n",
              "769  9/24/2018 10:31:26   \n",
              "771  9/24/2018 11:46:49   \n",
              "775  9/24/2018 20:34:34   \n",
              "780  9/25/2018 15:24:15   \n",
              "785  9/26/2018 10:20:10   \n",
              "787  9/26/2018 12:08:25   \n",
              "\n",
              "0    Have you completed the Foundations of Data Science requirement?  \\\n",
              "2                                                    1                 \n",
              "4                                                    1                 \n",
              "5                                                    1                 \n",
              "6                                                    1                 \n",
              "7                                                    1                 \n",
              "8                                                    1                 \n",
              "9                                                    1                 \n",
              "..                                                 ...                 \n",
              "768                                                  1                 \n",
              "769                                                  1                 \n",
              "771                                                  1                 \n",
              "775                                                  1                 \n",
              "780                                                  1                 \n",
              "785                                                  1                 \n",
              "787                                                  1                 \n",
              "\n",
              "0    Have you completed the Calculus I requirement?  \\\n",
              "2                                                 1   \n",
              "4                                                 1   \n",
              "5                                                 1   \n",
              "6                                                 1   \n",
              "7                                                 1   \n",
              "8                                                 1   \n",
              "9                                                 1   \n",
              "..                                              ...   \n",
              "768                                               1   \n",
              "769                                               1   \n",
              "771                                               1   \n",
              "775                                               1   \n",
              "780                                               1   \n",
              "785                                               1   \n",
              "787                                               1   \n",
              "\n",
              "0    Have you completed the Calculus II requirement?  \\\n",
              "2                                                  1   \n",
              "4                                                  1   \n",
              "5                                                  1   \n",
              "6                                                  1   \n",
              "7                                                  1   \n",
              "8                                                  1   \n",
              "9                                                  1   \n",
              "..                                               ...   \n",
              "768                                                1   \n",
              "769                                                1   \n",
              "771                                                1   \n",
              "775                                                1   \n",
              "780                                                1   \n",
              "785                                                1   \n",
              "787                                                1   \n",
              "\n",
              "0    Have you completed the Linear Algebra requirement?  \\\n",
              "2                                                    1    \n",
              "4                                                    1    \n",
              "5                                                    1    \n",
              "6                                                    1    \n",
              "7                                                    1    \n",
              "8                                                    1    \n",
              "9                                                    1    \n",
              "..                                                 ...    \n",
              "768                                                  1    \n",
              "769                                                  1    \n",
              "771                                                  1    \n",
              "775                                                  1    \n",
              "780                                                  1    \n",
              "785                                                  1    \n",
              "787                                                  1    \n",
              "\n",
              "0    Have you completed the Program Structures requirement?  \\\n",
              "2                                                    1        \n",
              "4                                                    1        \n",
              "5                                                    1        \n",
              "6                                                    1        \n",
              "7                                                    1        \n",
              "8                                                    1        \n",
              "9                                                    1        \n",
              "..                                                 ...        \n",
              "768                                                  1        \n",
              "769                                                  1        \n",
              "771                                                  1        \n",
              "775                                                  1        \n",
              "780                                                  1        \n",
              "785                                                  1        \n",
              "787                                                  1        \n",
              "\n",
              "0    Have you completed the Data Structures requirement?  \\\n",
              "2                                                    1     \n",
              "4                                                    1     \n",
              "5                                                    1     \n",
              "6                                                    1     \n",
              "7                                                    1     \n",
              "8                                                    1     \n",
              "9                                                    1     \n",
              "..                                                 ...     \n",
              "768                                                  1     \n",
              "769                                                  1     \n",
              "771                                                  1     \n",
              "775                                                  1     \n",
              "780                                                  1     \n",
              "785                                                  1     \n",
              "787                                                  1     \n",
              "\n",
              "0    Have you completed the Principles and Techniques of Data Science requirement?  \\\n",
              "2                                                    1                               \n",
              "4                                                    1                               \n",
              "5                                                    1                               \n",
              "6                                                    1                               \n",
              "7                                                    1                               \n",
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              "9                                                    1                               \n",
              "..                                                 ...                               \n",
              "768                                                  1                               \n",
              "769                                                  1                               \n",
              "771                                                  0                               \n",
              "775                                                  1                               \n",
              "780                                                  1                               \n",
              "785                                                  0                               \n",
              "787                                                  0                               \n",
              "\n",
              "0    Have you completed one course towards the Computational and Inferential Depth requirement?  \\\n",
              "2                                                    1                                            \n",
              "4                                                    0                                            \n",
              "5                                                    0                                            \n",
              "6                                                    1                                            \n",
              "7                                                    1                                            \n",
              "8                                                    1                                            \n",
              "9                                                    1                                            \n",
              "..                                                 ...                                            \n",
              "768                                                  1                                            \n",
              "769                                                  1                                            \n",
              "771                                                  1                                            \n",
              "775                                                  1                                            \n",
              "780                                                  0                                            \n",
              "785                                                  0                                            \n",
              "787                                                  0                                            \n",
              "\n",
              "0    Have you completed the second course towards the Computational and Inferential Depth requirement?  \\\n",
              "2                                                    0                                                   \n",
              "4                                                    0                                                   \n",
              "5                                                    0                                                   \n",
              "6                                                    0                                                   \n",
              "7                                                    1                                                   \n",
              "8                                                    1                                                   \n",
              "9                                                    0                                                   \n",
              "..                                                 ...                                                   \n",
              "768                                                  0                                                   \n",
              "769                                                  0                                                   \n",
              "771                                                  0                                                   \n",
              "775                                                  1                                                   \n",
              "780                                                  0                                                   \n",
              "785                                                  0                                                   \n",
              "787                                                  0                                                   \n",
              "\n",
              "0    Have you completed the Probability requirement?  \\\n",
              "2                                                  1   \n",
              "4                                                  1   \n",
              "5                                                  0   \n",
              "6                                                  0   \n",
              "7                                                  1   \n",
              "8                                                  1   \n",
              "9                                                  0   \n",
              "..                                               ...   \n",
              "768                                                1   \n",
              "769                                                1   \n",
              "771                                                0   \n",
              "775                                                1   \n",
              "780                                                1   \n",
              "785                                                0   \n",
              "787                                                0   \n",
              "\n",
              "0    Have you completed the Human Contexts and Ethics requirement?  \\\n",
              "2                                                    1               \n",
              "4                                                    0               \n",
              "5                                                    0               \n",
              "6                                                    1               \n",
              "7                                                    1               \n",
              "8                                                    1               \n",
              "9                                                    0               \n",
              "..                                                 ...               \n",
              "768                                                  0               \n",
              "769                                                  0               \n",
              "771                                                  0               \n",
              "775                                                  0               \n",
              "780                                                  0               \n",
              "785                                                  0               \n",
              "787                                                  0               \n",
              "\n",
              "0    Have you completed the Modeling, Learning, and Decision-Making requirement?  \\\n",
              "2                                                    0                             \n",
              "4                                                    0                             \n",
              "5                                                    0                             \n",
              "6                                                    0                             \n",
              "7                                                    1                             \n",
              "8                                                    1                             \n",
              "9                                                    0                             \n",
              "..                                                 ...                             \n",
              "768                                                  0                             \n",
              "769                                                  0                             \n",
              "771                                                  0                             \n",
              "775                                                  0                             \n",
              "780                                                  0                             \n",
              "785                                                  0                             \n",
              "787                                                  0                             \n",
              "\n",
              "0    Have you completed one lower-division course towards a Domain Emphasis?  \\\n",
              "2                                                    1                         \n",
              "4                                                    1                         \n",
              "5                                                    1                         \n",
              "6                                                    1                         \n",
              "7                                                    1                         \n",
              "8                                                    0                         \n",
              "9                                                    1                         \n",
              "..                                                 ...                         \n",
              "768                                                  1                         \n",
              "769                                                  1                         \n",
              "771                                                  1                         \n",
              "775                                                  1                         \n",
              "780                                                  1                         \n",
              "785                                                  0                         \n",
              "787                                                  1                         \n",
              "\n",
              "0    Have you completed one upper-division course towards a Domain Emphasis?  \\\n",
              "2                                                    1                         \n",
              "4                                                    1                         \n",
              "5                                                    1                         \n",
              "6                                                    0                         \n",
              "7                                                    1                         \n",
              "8                                                    1                         \n",
              "9                                                    1                         \n",
              "..                                                 ...                         \n",
              "768                                                  1                         \n",
              "769                                                  0                         \n",
              "771                                                  0                         \n",
              "775                                                  0                         \n",
              "780                                                  1                         \n",
              "785                                                  0                         \n",
              "787                                                  0                         \n",
              "\n",
              "0    Have you completed a second upper-division course towards a Domain Emphasis?  \\\n",
              "2                                                    1                              \n",
              "4                                                    0                              \n",
              "5                                                    1                              \n",
              "6                                                    0                              \n",
              "7                                                    0                              \n",
              "8                                                    1                              \n",
              "9                                                    0                              \n",
              "..                                                 ...                              \n",
              "768                                                  1                              \n",
              "769                                                  0                              \n",
              "771                                                  0                              \n",
              "775                                                  0                              \n",
              "780                                                  0                              \n",
              "785                                                  0                              \n",
              "787                                                  0                              \n",
              "\n",
              "0    Are you a transfer student?  Are you expected to graduate in Fall 2018?  \\\n",
              "2                              0                                           0   \n",
              "4                              0                                           0   \n",
              "5                              0                                           0   \n",
              "6                              0                                           0   \n",
              "7                              0                                           0   \n",
              "8                              0                                           0   \n",
              "9                              0                                           0   \n",
              "..                           ...                                         ...   \n",
              "768                            0                                           0   \n",
              "769                            0                                           0   \n",
              "771                            0                                           0   \n",
              "775                            0                                           0   \n",
              "780                            1                                           0   \n",
              "785                            0                                           0   \n",
              "787                            0                                           0   \n",
              "\n",
              "0    Are you expected to graduate in Spring or Summer 2019?  \\\n",
              "2                                                    1        \n",
              "4                                                    0        \n",
              "5                                                    0        \n",
              "6                                                    0        \n",
              "7                                                    1        \n",
              "8                                                    0        \n",
              "9                                                    0        \n",
              "..                                                 ...        \n",
              "768                                                  0        \n",
              "769                                                  1        \n",
              "771                                                  0        \n",
              "775                                                  0        \n",
              "780                                                  1        \n",
              "785                                                  0        \n",
              "787                                                  0        \n",
              "\n",
              "0   What is your current Expected Graduation Term?  \\\n",
              "2                                                0   \n",
              "4                                      Spring 2020   \n",
              "5                                      Spring 2020   \n",
              "6                                        Fall 2019   \n",
              "7                                                0   \n",
              "8                                        Fall 2019   \n",
              "9                                      Spring 2020   \n",
              "..                                             ...   \n",
              "768                                    Spring 2020   \n",
              "769                                              0   \n",
              "771                                    Spring 2020   \n",
              "775                                    Spring 2020   \n",
              "780                                              0   \n",
              "785                                    Spring 2022   \n",
              "787                                    Spring 2021   \n",
              "\n",
              "0    Are you currently already declared in another major?  \n",
              "2                                                    1     \n",
              "4                                                    0     \n",
              "5                                                    0     \n",
              "6                                                    0     \n",
              "7                                                    1     \n",
              "8                                                    1     \n",
              "9                                                    1     \n",
              "..                                                 ...     \n",
              "768                                                  0     \n",
              "769                                                  1     \n",
              "771                                                  0     \n",
              "775                                                  1     \n",
              "780                                                  1     \n",
              "785                                                  0     \n",
              "787                                                  1     \n",
              "\n",
              "[525 rows x 21 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "metadata": {
        "id": "sy2h3dU1Ids6",
        "colab_type": "code",
        "outputId": "77ca7caa-fe9b-4efa-8673-87bd422a170f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        }
      },
      "cell_type": "code",
      "source": [
        "#plot comparing categories\n",
        "#drop_first_cols = lower_div.drop(columns = lower_div_labels)\n",
        "#sum_completed = drop_first_cols.sum()\n",
        "#cols_completed = len(list(drop_first_cols))\n",
        "#sum_completed\n",
        "#new_plot = pd.DataFrame({'Survey question' : cols_completed, 'Completed requirement' : sum_completed})\n",
        "lower_div_labels_total = ['Have you completed the Calculus I requirement?', 'Have you completed the Calculus II requirement?', 'Have you completed the Linear Algebra requirement?', 'Have you completed the Program Structures requirement?', 'Have you completed the Data Structures requirement?']\n",
        "\n",
        "drop_first_cols = lower_div.drop(columns = lower_div_labels_total)\n",
        "sum_completed = list(drop_first_cols.sum()[1:])[::-1]\n",
        "cols_completed = list(drop_first_cols)[1:][::-1]\n",
        "\n",
        "cols_completed.remove('What is your current Expected Graduation Term?')\n",
        "\n",
        "lowerdiv_plot = pd.DataFrame({'Survey question' : cols_completed, 'Students that responded YES or IN PROGRESS' : sum_completed})\n",
        "lowerdiv_plot.plot.barh(x='Survey question', y='Students that responded YES or IN PROGRESS')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f1b566d3d30>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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M7cgtpHT5HP2sFGr9+StFj6dD59dtRk7D9tTbtwhkMvLrOGF6/XduDQvG8F4M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\n2c9h9LoGAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f1b4ee522b0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "ia3WNIb4LuqS",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "\n",
        "sums_index = pd.Index(sums)\n",
        "cols_index = pd.Index(cols)\n",
        "sum_completed_index = pd.Index(sum_completed)\n",
        "cols_completed_index = pd.Index(cols_completed)\n",
        "\n",
        "non_lowerdiv_plot = pd.DataFrame({'Survey question' : cols_index - cols_completed_index, 'Students that responded YES or IN PROGRESS' : sums_index - sum_completed_index})\n",
        "non_lowerdiv_plot.plot.barh(x='Survey question', y='Students that responded YES or IN PROGRESS')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "mIi1-xtik0ky",
        "colab_type": "code",
        "outputId": "74072724-09d3-46fa-eceb-2bac36aba1e5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 446
        }
      },
      "cell_type": "code",
      "source": [
        "# Converting to pandas Timestamp objects\n",
        "df.Timestamp = df.Timestamp.apply(pd.to_datetime)\n",
        "\n",
        "# Plotting the counts of how many people submitted the form per day, for Mariah\n",
        "df.Timestamp.groupby(df['Timestamp'].dt.date).count().plot(kind=\"bar\")"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f95468df278>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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AYFmFOrLRsWNHjRs3Tr169VJWVpaGDx+ue++9VxMmTJDD4VCtWrXUpEkTT48VAABYUKGa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\nqnTp0ho8eLBGjhy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ndO7cuTzP2ncldseOHZoyZcpNn0izrwviapyVcmY7duxYjseu6+fM\nnTh39n358mVNnz5d/fr1y/UEGRsbqwkTJrgVZ8ecJri67507d2rixIlasmSJ83yXixcv6t1339Xa\ntWv1zTffOP/O1Vir5MyP15uNG11/VTNPxFklp93qsUpOu9XjjZyeesK1Ys7rZR8NupW4wu4bBfPE\n+tyqm70wuJVYq+S8476I7fqrmnkizio57VaPVXLarR5v5CxfvrzzeiMzZsy45Tgr5byeq4eU84sr\n7L5fe+01j8bZMacn1qew+86Oc+VJ2dVYq+TMdsc1Gzde9OhW46yS0271WCWn3erxdk4TD+hWydmu\nXTuPxnm7Hrvl9PT6uLNvq8yRiZzZvHoFUenaVdkuXbqkkiVL6ueff9alS5eUkZGR6wuqXI2zSk67\n1WOVnHarx9s5b3Tp0qUc31p8q3F3cs7k5GRt2rRJ27dv1969e50nz934Ss/VOG/XY7ecptfndtdj\n1ZzZvHrORlxcnH755RddunRJtWvX1vfff68GDRo4L1+e/YkUV+OsktNu9Vglp93q8XZO6doD9Y4d\nO3T27Fk5HA6VLVtWTZo0yfXdOa7GWSXnxx9/rM2bN6tx48batWuXypcvr2LFimnz5s3q2rWr85oL\nrsZ5ux675TSxPnabI1M5b8arH309cOCA5s2bpytXrqhDhw5auXKl81r0PXv2dDvOKjntVo9Vctqt\nHm/nzOuB+sKFC3r//fcLfEDPK85KOdevX6+5c+fKx8dHzz33nIYNG6YpU6aoW7du6tWrlzPW1Thv\n12O3nJ5eH2/XY5Wc+fHqORtZWVlyOBzKzMxUZmam0tPTJV37iNH133jnapxVctqtHqvktFs93s65\nfv16vfvuu3rhhRc0efJknThxQn379tXChQv1wQcfuB1npZyXL192fvPwiRMnlJaWJunamfnXf7On\nq3HersduOT29Pt6uxyo58+PVIxvt27dXhw4dFBAQoFdeeUU9e/ZUhQoV9Ouvv+qFF15wO84qOe1W\nj1Vy2q0eb+fMfqAuWbKkSw/oBcVZKWe3bt30t7/9TcWLF1d6erpGjRolSRozZox69Ojhdpy367Fb\nTk+vj7frsUrO/Hj9OhsXL16Uv7+/AgICdPHiRR0+fFhly5ZVqVKlChVnlZx2q8cqOe1Wjzdzfv31\n15o8eXKOB+oGDRpo4MCB6tChg/NLq1yNs1JO6dqVI1NSUpwX4boZV+K8XY/dcnp6fbxdj1Vy5ser\nzUZaWpqWLFmiHTt25Pgq3ubNm+tvf/ub82vmXY2zSk671WOVnHarx9s5Jc8/oFslp4l5t9sceTOn\nifXxZj1WynkzXm02Bg4cqDZt2ig6OlqlSpVyftPhhg0btHv3bk2ePNmtOKvktFs9Vslpt3q8ndNu\nzZM7OT09796ux245Tdwv7DZHpl6A3FRKSorDW/+effbZm/6uU6dObsdZJafd6rFKTrvV4+2cXbt2\ndSxevNjx888/O86ePes4c+aM4+DBg45Zs2Y5evTo4XaclXJ6et69XY/dcpq4X9htjkzkzO+fVz+N\nEhwcrA8//FDHjh3TxYsXdfHiRf322296//33c3x219U4q+S0Wz1WyWm3eryd8+LFi+rQoYPCwsJU\npEgR+fr6qkyZMnr++eedZ/i7E2elnJ6ed2/XY7ecJu4XdpsjEznz49W3US5cuKB//vOfio+P15kz\nZ+Tj46OwsDA1a9ZMnTp1cn6znqtxVslpt3qsktNu9Xg756BBg9S4cWO1adNGISEhkqQzZ87oP//5\njxISEvTOO++4FWelnJ6ed2/XY7ecJu4XdpsjEznz4/VPo9zo4MGDql69usfirJLTbvVYJafd6rmd\nOe3WPLmT09Pz7u167JbT0+vj7XqskjM/d1yz0adPH82ePdtjcVbJabd6rJLTbvV4O6eVm6dbzenp\nefd2PXbLaeJ+Ybc5MpEz2x33ra8ArGvatGkejbNSTk/zdj12y2mC3ebI5Lzfcc3GG2+84dE4q+S0\nWz1WyWm3eryd825mYt7hOayPd3n1bZQff/xRs2bNUkhIiHr16qVp06bp4MGDioiI0KBBg3T//fe7\nFWeVnHarxyo57VaPt3PmJSkpSWXLlr3p792Nu1Nzmph3b9Zjt5y3Y31uZz1WzunkyudjTf3r3Lmz\n43//938dn3/+uSM6OtqxZs0aR3JysmPTpk2O5557zu04q+S0Wz1WyWm3erydc/v27Y4uXbo4Xn75\nZUdCQoKjV69ejgcffNDxt7/9zbFr1y6346yU09Pz7u167JbTxP3CbnNkImd+/7z6RWw+Pj6qW7eu\nJCkoKEgtW7aUJNWvX79QcVbJabd6rJLTbvV4O2dcXJz69u2r1NRU9ezZU7GxsRo/frx++OEHTZ48\n2XmSnatxVsrp6Xn3dj12y2nifmG3OTKRMz9ebTYCAgK0cuVKnT9/Xv7+/lq8eLGaN2+u77//XoGB\ngW7HWSWn3eqxSk671ePtnHZrntzJ6el593Y9dstp4n5htzkykTM/vsOHDx/tcrSHRUVFafPmzSpa\ntKhGjhypvXv3as2aNXI4HOrfv7+CgoLcirNKTrvVY5WcdqvH2znXr1+vS5cuafv27Tp8+LDS0tJU\ntGhRbdq0SUlJSWrfvr1bcVbK6el593Y9dstp4n5htzkykTM/d9x1NrLt2rVLjRo18licVXLarR6r\n5LRbPbcj5+nTp7Vs2TKFhIToueee09KlS7Vv3z5FRESoS5cuCgsLcyvOSjk9Pe/ersduOT29Pt6u\nxyo583PHNht2u9iRFfZ9N+e0Wz3ezmnF5slTOT09796ux245Tdwv7DZHJnJ69ZyN2NjYPLc7HA79\n+uuvbsdZJafd6rFKTrvV4+2c+VmwYIFLD0Cuxt1pOU3M+62O0Z1Yu+e8nevjzjjvpDm63Tm92myk\np6erfv36qlevXo7tDodDx44dczvOKjntVo9VctqtHm/ntFvz5E5OT8+7t+uxW04T9wu7zdHtfgHi\n1WZj/Pjxmjhxojp37pzri1yCg4PdjrNKTrvVY5WcdqvH2znt1jy5k9PT8+7teuyW08T9wm5zZCJn\nfu7YczauXr2qIkUKvpq6q3FWyWm3eqyS02713I6caWlpmjhxokaMGJHrgfr697tdjbNSTlfnyNU4\nb9djt5z5Kez9wm5zdLvn3avNxpUrV7R69Wrt2LFDZ86ckSSFhYWpefPmevzxx+Xr6+tWnFVy2q0e\nq+S0Wz3ezpkfKzZP7sSZmHdv1mO3nLdzfW5HPXbI6dVm4/XXX1f58uXVqlUrlSpVSg6HQ6dOndLG\njRuVmpqqMWPGuBVnlZx2q8cqOe1Wj7dz2q15cienp+fd2/XYLaeJ+4Xd5uh2vwDxarPRq1cvzZ07\nt8DfuRpnlZx2q8cqOe1Wj7dz2q15cienp+fd2/XYLaeJ+4Xd5shEzvx49QTRIkWKaMOGDWrdurX8\n/K4N5fLly9qwYYMCAgLcjrNKTrvVY5WcdqvH2zlPnz6tN998M8ffVqhQQQ0bNlSvXr3cjrNSTk/P\nu7frsVtOE/cLu82RiZz58WqzMXr0aM2bN08zZsxQRkaGpGvXXY+KitKIESPcjrNKTrvVY5WcdqvH\n2znt1jy5k9PT8+7teuyW08T9wm5zZCJnfrz6NsrGjRsVFxenjIwMtWzZUq+++qqKFSsmKecZrq7G\nWSWn3eqxSk671ePtnCdPntS8efO0e/fuXA/U3bt3V+nSpd2Ks1JOT8+7t+uxW04T9wu7zZGJnPlx\n7XRTQ5YsWaKlS5dq3bp1ql+/vvr3768LFy4UOs4qOe1Wj1Vy2q0eb+dMSEhQfHy8Lly4oGbNmulf\n//qXPv30U8XGxmr06NFux1kpp6fn3dv12C2nifuF3ebIRM78eLXZKFKkiEqWLKkiRYqoQ4cO6tKl\niwYMGKCUlJRCxVklp93qsUpOu9Xj7Zx2a57cyenpefd2PXbLaeJ+Ybc5MpEzP15tNurVq6dBgwYp\nMzNTkvTggw8qJiZGffv21e+//+52nFVy2q0eq+S0Wz3ezmm35smdnJ6ed2/XY7ecJu4XdpsjEznz\n4zt8+PDRLkd7WNOmTRUeHq6IiAj5+PhIkiIiIvTYY48pJCRE1atXdyvOKjntVo9VctqtHm/nPHLk\niP75z3+qTZs28vPzU+XKlXXfffdp1KhRSk5O1vPPP+9WnJVyenrevV2P3XKauF/YbY5M5MzPHXu5\ncgB3vl27dqlhw4bOB2pJunDhgr766it16NDB7Tgr5fQ0b9djt5wm2G2Obue802wAAACjvHrOBgAA\nsD+aDQAAYJRXryAK4NaMGTNGa9asyTembNmyatiwoTZv3qz169ffppEBwH9xzgZgYRcuXHB+bE+S\n3nrrLf30009avHixc5uvr6/8/f11+fJllSpVygujzG3ChAkKCgrSyy+/7O2hALgNOLIBWFhwcLCC\ng4OdPwcEBMjX11dhYWFeHFXB9u3bp2bNmnl7GABuE5oN4C4wZsyYHG+jPPnkk4qOjla5cuW0bNky\npaamqnHjxho7dqzWrVunpUuXKiUlRXXq1NHIkSOd333gcDi0YsUK/b//9//0+++/65577lGrVq3U\nv39/hYSESLr2BU2zZs3Sxo0bdebMGQUHB6tZs2YaOHCgQkJC1KRJE0nSoUOH9OGHH2rlypUqV66c\n1q5dq2XLlumXX36Rv7+/7r//fvXu3VuNGzeWJB0/flwdOnTQmDFjtHPnTm3cuFFFihTRX//6V/Xu\n3VvTpk3T+vXr5XA49NBDD2nYsGHy8/Nz/t3rr7+uH3/8UevXr1dmZqYaNWqk4cOHq0yZMl5YEeDu\nwgmiwF3q22+/1bFjxzRr1iyNGjVKW7d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            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f9546734a90>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "Nxh5rcCFxLG4",
        "colab_type": "code",
        "outputId": "f0963df4-eb17-4493-fbc7-26850e20d8cf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        }
      },
      "cell_type": "code",
      "source": [
        "#Checking for incomplete surveys, seems like everything is answered\n",
        "df.loc[:,'Have you completed the Foundations of Data Science requirement?'].value_counts()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1    698\n",
              "0     89\n",
              "Name: Have you completed the Foundations of Data Science requirement?, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "metadata": {
        "id": "S4qhyFhS-l8H",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#use this for linear SVC (multi-feature linear regression model), dummydata should be Y values.\n",
        "#dummydata = (np.random.rand(787) > 0.1).astype(int)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "g5d-G9IK-sNO",
        "colab_type": "code",
        "outputId": "b939d8db-f1f4-4387-9841-eb8828e5eb60",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 369
        }
      },
      "cell_type": "code",
      "source": [
        "def completeddiff(df):\n",
        "  df_notime = df.drop(['Timestamp','What is your current Expected Graduation Term?'], axis=1)\n",
        "  sum_df_notime = df_notime.apply(sum)\n",
        "  return sum_df_notime.subtract(len(sum_df_notime)).apply(abs)\n",
        "  \n",
        "cdf_all = completeddiff(df)\n",
        "cdf_all.plot.barh(x='Survey question', y='Students that responded YES or IN PROGRESS')\n",
        "cdf_upperdivonly = completeddiff(lower_div)\n",
        "#cdf_upperdivonly.plot.barh(x='Survey question', y='Students that responded YES or IN PROGRESS')\n",
        "#cols_completed"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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5zzt8+DAFBQXP1Hbp0qXcvHnzmdru37+fMWPG4O3tzahRo4iNjX3mmL744gs0Gs0zt/9f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6M5d+4c9+/fZ/z48QwcOJAZM2bw8ccfA7WDw7y8PKZNm8aaNWuoqqrCwMCAFStW0KlTJymd5cuX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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f1b4ecbe2b0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "xuTd_jSs4ZGy",
        "colab_type": "code",
        "outputId": "845b15cd-c08b-495d-d6f5-837ec0cea845",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "#function to find difference of any two columns in a data frame using label names\n",
        "\n",
        "def completeddiffcols(df, colname_1, colname_2):\n",
        "  df_notime = df.drop(['Timestamp','What is your current Expected Graduation Term?'], axis=1)\n",
        "  sum_df_col1 = df.loc[:, colname_1].sum()\n",
        "  sum_df_col2 = df.loc[:, colname_2].sum()\n",
        "  return abs(sum_df_col1 - sum_df_col2)\n",
        "\n",
        "#find absolute value difference of two columns in df\n",
        "completeddiffcols(df, 'Have you completed a second upper-division course towards a Domain Emphasis?', 'Have you completed one upper-division course towards a Domain Emphasis?')\n",
        "\n",
        "#find absolute value difference of two columns in lower_div\n",
        "completeddiffcols(lower_div, 'Have you completed a second upper-division course towards a Domain Emphasis?', 'Have you completed one upper-division course towards a Domain Emphasis?')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "138"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "metadata": {
        "id": "FT_8-RDfxKFv",
        "colab_type": "code",
        "outputId": "f1d6ec5c-2f65-4775-d4f6-c8496c80b111",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "cell_type": "code",
      "source": [
        "#use this for linear SVC (multi-feature linear regression model), dummydata should be Y values.\n",
        "\n",
        "from sklearn import svm\n",
        "df_asmatrix = df.drop(['Timestamp','What is your current Expected Graduation Term?'], axis=1).values\n",
        "dummydata = (np.random.rand(787) > 0.1).astype(int)\n",
        "lin_clf = svm.LinearSVC()\n",
        "lin_clf.fit(df_asmatrix, dummydata)\n",
        "\n",
        "#df_asmatrix\n",
        "#lin_clf.predict(df_asmatrix)\n",
        "\n",
        "#sample dummydata 500 times\n",
        "dummydata\n",
        "\n",
        "# ???\n",
        "dd = pd.DataFrame(data=dummydata)\n",
        "dd_array = np.array\n",
        "for i in range(500):\n",
        "  dd_array = np.append(dd_array, dd.sample(n=len(dummydata),replace=True))\n",
        "  \n",
        "dd_array"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([<built-in function array>, 1, 1, ..., 1, 1, 1], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "metadata": {
        "id": "9_BlAMThaTzv",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}