explore_data_with_numpy_and_pandas.ipynb

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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/singhsourav0/DP100/blob/main/explore_data_with_numpy_and_pandas.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Js4Yr1VazpbR",
        "outputId": "0ce8fac9-94b4-4170-ddd9-b98aee360827"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[50, 50, 47, 97, 49, 3, 53, 42, 26, 74, 82, 62, 37, 15, 70, 27, 36, 35, 48, 52, 63, 64]\n"
          ]
        }
      ],
      "source": [
        "data = [50,50,47,97,49,3,53,42,26,74,82,62,37,15,70,27,36,35,48,52,63,64]\n",
        "print(data)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "\n",
        "grades = np.array(data)\n",
        "print(grades)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tWq8vEz2z3yS",
        "outputId": "e92be167-49e0-4c99-9714-15f651e3296e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[50 50 47 97 49  3 53 42 26 74 82 62 37 15 70 27 36 35 48 52 63 64]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print (type(data),'x 2:', data * 2)\n",
        "print('---')\n",
        "print (type(grades),'x 2:', grades * 2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fnS2HCZ60EKI",
        "outputId": "1a5afae4-ad68-4f46-ba71-18e2b3ef1088"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'list'> x 2: [50, 50, 47, 97, 49, 3, 53, 42, 26, 74, 82, 62, 37, 15, 70, 27, 36, 35, 48, 52, 63, 64, 50, 50, 47, 97, 49, 3, 53, 42, 26, 74, 82, 62, 37, 15, 70, 27, 36, 35, 48, 52, 63, 64]\n",
            "---\n",
            "<class 'numpy.ndarray'> x 2: [100 100  94 194  98   6 106  84  52 148 164 124  74  30 140  54  72  70\n",
            "  96 104 126 128]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "grades.shape"
      ],
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      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(22,)"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "grades.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zO0JFikl19y7",
        "outputId": "c139bf00-aaa8-4e18-f8f2-13a4921cd13f"
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      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "49.18181818181818"
            ]
          },
          "metadata": {},
          "execution_count": 5
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    {
      "cell_type": "code",
      "source": [
        "# Define an array of study hours\n",
        "study_hours = [10.0,11.5,9.0,16.0,9.25,1.0,11.5,9.0,8.5,14.5,15.5,\n",
        "               13.75,9.0,8.0,15.5,8.0,9.0,6.0,10.0,12.0,12.5,12.0]\n",
        "\n",
        "# Create a 2D array (an array of arrays)\n",
        "student_data = np.array([study_hours, grades])\n",
        "\n",
        "# display the array\n",
        "student_data"
      ],
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      "outputs": [
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          "data": {
            "text/plain": [
              "array([[10.  , 11.5 ,  9.  , 16.  ,  9.25,  1.  , 11.5 ,  9.  ,  8.5 ,\n",
              "        14.5 , 15.5 , 13.75,  9.  ,  8.  , 15.5 ,  8.  ,  9.  ,  6.  ,\n",
              "        10.  , 12.  , 12.5 , 12.  ],\n",
              "       [50.  , 50.  , 47.  , 97.  , 49.  ,  3.  , 53.  , 42.  , 26.  ,\n",
              "        74.  , 82.  , 62.  , 37.  , 15.  , 70.  , 27.  , 36.  , 35.  ,\n",
              "        48.  , 52.  , 63.  , 64.  ]])"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Show shape of 2D array\n",
        "student_data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7jNdP97c365b",
        "outputId": "4cf48104-38ef-4959-c755-bd9476f61607"
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      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2, 22)"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "df_students = pd.DataFrame({'Name': ['Dan', 'Joann', 'Pedro', 'Rosie', 'Ethan', 'Vicky', 'Frederic', 'Jimmie', \n",
        "                                     'Rhonda', 'Giovanni', 'Francesca', 'Rajab', 'Naiyana', 'Kian', 'Jenny',\n",
        "                                     'Jakeem','Helena','Ismat','Anila','Skye','Daniel','Aisha'],\n",
        "                            'StudyHours':student_data[0],\n",
        "                            'Grade':student_data[1]})\n",
        "\n",
        "df_students "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 571
        },
        "id": "I8hBcbSV38EG",
        "outputId": "4f8dae3c-ce6e-417a-93cf-0739230fcc70"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Name  StudyHours  Grade\n",
              "0         Dan       10.00   50.0\n",
              "1       Joann       11.50   50.0\n",
              "2       Pedro        9.00   47.0\n",
              "3       Rosie       16.00   97.0\n",
              "4       Ethan        9.25   49.0\n",
              "5       Vicky        1.00    3.0\n",
              "6    Frederic       11.50   53.0\n",
              "7      Jimmie        9.00   42.0\n",
              "8      Rhonda        8.50   26.0\n",
              "9    Giovanni       14.50   74.0\n",
              "10  Francesca       15.50   82.0\n",
              "11      Rajab       13.75   62.0\n",
              "12    Naiyana        9.00   37.0\n",
              "13       Kian        8.00   15.0\n",
              "14      Jenny       15.50   70.0\n",
              "15     Jakeem        8.00   27.0\n",
              "16     Helena        9.00   36.0\n",
              "17      Ismat        6.00   35.0\n",
              "18      Anila       10.00   48.0\n",
              "19       Skye       12.00   52.0\n",
              "20     Daniel       12.50   63.0\n",
              "21      Aisha       12.00   64.0"
            ],
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              "      <td>Pedro</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Rosie</td>\n",
              "      <td>16.00</td>\n",
              "      <td>97.0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Ethan</td>\n",
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              "      <td>49.0</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Vicky</td>\n",
              "      <td>1.00</td>\n",
              "      <td>3.0</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Frederic</td>\n",
              "      <td>11.50</td>\n",
              "      <td>53.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Jimmie</td>\n",
              "      <td>9.00</td>\n",
              "      <td>42.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Rhonda</td>\n",
              "      <td>8.50</td>\n",
              "      <td>26.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Giovanni</td>\n",
              "      <td>14.50</td>\n",
              "      <td>74.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Francesca</td>\n",
              "      <td>15.50</td>\n",
              "      <td>82.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Rajab</td>\n",
              "      <td>13.75</td>\n",
              "      <td>62.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Naiyana</td>\n",
              "      <td>9.00</td>\n",
              "      <td>37.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Kian</td>\n",
              "      <td>8.00</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Jenny</td>\n",
              "      <td>15.50</td>\n",
              "      <td>70.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Jakeem</td>\n",
              "      <td>8.00</td>\n",
              "      <td>27.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Helena</td>\n",
              "      <td>9.00</td>\n",
              "      <td>36.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Ismat</td>\n",
              "      <td>6.00</td>\n",
              "      <td>35.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Anila</td>\n",
              "      <td>10.00</td>\n",
              "      <td>48.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Skye</td>\n",
              "      <td>12.00</td>\n",
              "      <td>52.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Daniel</td>\n",
              "      <td>12.50</td>\n",
              "      <td>63.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Aisha</td>\n",
              "      <td>12.00</td>\n",
              "      <td>64.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Get the data for index value 5\n",
        "df_students.loc[5]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sdXuV9TT66X6",
        "outputId": "ed6edde0-e52f-4d65-a79a-b7c35d75eb9c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Name          Vicky\n",
              "StudyHours      1.0\n",
              "Grade           3.0\n",
              "Name: 5, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Get the rows with index values from 0 to 5\n",
        "df_students.loc[0:5]"
      ],
      "metadata": {
        "colab": {
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      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Name  StudyHours  Grade\n",
              "0    Dan       10.00   50.0\n",
              "1  Joann       11.50   50.0\n",
              "2  Pedro        9.00   47.0\n",
              "3  Rosie       16.00   97.0\n",
              "4  Ethan        9.25   49.0\n",
              "5  Vicky        1.00    3.0"
            ],
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              "      <th>0</th>\n",
              "      <td>Dan</td>\n",
              "      <td>10.00</td>\n",
              "      <td>50.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Joann</td>\n",
              "      <td>11.50</td>\n",
              "      <td>50.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Pedro</td>\n",
              "      <td>9.00</td>\n",
              "      <td>47.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Rosie</td>\n",
              "      <td>16.00</td>\n",
              "      <td>97.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Ethan</td>\n",
              "      <td>9.25</td>\n",
              "      <td>49.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Vicky</td>\n",
              "      <td>1.00</td>\n",
              "      <td>3.0</td>\n",
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              "  </tbody>\n",
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              "                                                     [key], {});\n",
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              "  "
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    {
      "cell_type": "code",
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        "# Get data in the first five rows\n",
        "df_students.iloc[0:5]"
      ],
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        "outputId": "e41dfa75-9906-4d05-ab8f-e7166e49b609"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Name  StudyHours  Grade\n",
              "0    Dan       10.00   50.0\n",
              "1  Joann       11.50   50.0\n",
              "2  Pedro        9.00   47.0\n",
              "3  Rosie       16.00   97.0\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
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              "            + ' to learn more about interactive tables.';\n",
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              "  "
            ]
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          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_students.iloc[0,[1,2]]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mhoqmsKN-IHu",
        "outputId": "fa82e0ad-9108-47ac-cf98-6fbce8aedde7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "StudyHours    10.0\n",
              "Grade         50.0\n",
              "Name: 0, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_students.loc[0,'Grade']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_afiNrkF-oAp",
        "outputId": "d0b24d44-3621-4c6d-a93d-05828a3029f4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "50.0"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_students.loc[df_students['Name']=='Aisha']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "id": "zFkC_G5g_Nd9",
        "outputId": "caa5d235-3206-493e-e2b8-c9a6406ddb1b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Name  StudyHours  Grade\n",
              "21  Aisha        12.0   64.0"
            ],
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              "\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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    {
      "cell_type": "code",
      "source": [
        "df_students[df_students['Name']=='Aisha']"
      ],
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        },
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        "outputId": "8d9ab162-a2c7-44e3-9b63-fb3736854a54"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Name  StudyHours  Grade\n",
              "21  Aisha        12.0   64.0"
            ],
            "text/html": [
              "\n",
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              "      <td>Aisha</td>\n",
              "      <td>12.0</td>\n",
              "      <td>64.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c9484329-2b3c-4d22-92d9-b384ab149add')\"\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_students.query('Name==\"Aisha\"')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "id": "_HaQv2nuAU1B",
        "outputId": "11840a83-d252-4eb6-d2c1-18a38e0cc12d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Name  StudyHours  Grade\n",
              "21  Aisha        12.0   64.0"
            ],
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              "      <td>Aisha</td>\n",
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              "      <td>64.0</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8a272371-f4d8-44a8-befc-5a1bdfde2863')\"\n",
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              "    [theme=dark] .colab-df-convert {\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  "
            ]
          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_students[df_students.Name == 'Aisha']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "id": "vzcOucUfAa5u",
        "outputId": "5a3a02d2-5fd2-4064-a0e7-26f394bd344a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Name  StudyHours  Grade\n",
              "21  Aisha        12.0   64.0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a16799b5-eeeb-4e59-86f2-aba287a4a96b\">\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <td>Aisha</td>\n",
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              "      <td>64.0</td>\n",
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              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a16799b5-eeeb-4e59-86f2-aba287a4a96b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a16799b5-eeeb-4e59-86f2-aba287a4a96b button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a16799b5-eeeb-4e59-86f2-aba287a4a96b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "          dataTable['output_type'] = 'display_data';\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!wget https://raw.githubusercontent.com/MicrosoftDocs/mslearn-introduction-to-machine-learning/main/Data/ml-basics/grades.csv\n",
        "df_students = pd.read_csv('grades.csv',delimiter=',',header='infer')\n",
        "df_students.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 397
        },
        "id": "RxeEGOg9AjXQ",
        "outputId": "0eeb2b0e-8def-422f-9ef9-bfa93567ffb2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2023-03-21 21:10:31--  https://raw.githubusercontent.com/MicrosoftDocs/mslearn-introduction-to-machine-learning/main/Data/ml-basics/grades.csv\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.108.133, 185.199.110.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 322 [text/plain]\n",
            "Saving to: ‘grades.csv’\n",
            "\n",
            "\rgrades.csv            0%[                    ]       0  --.-KB/s               \rgrades.csv          100%[===================>]     322  --.-KB/s    in 0s      \n",
            "\n",
            "2023-03-21 21:10:31 (16.7 MB/s) - ‘grades.csv’ saved [322/322]\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Name  StudyHours  Grade\n",
              "0    Dan       10.00   50.0\n",
              "1  Joann       11.50   50.0\n",
              "2  Pedro        9.00   47.0\n",
              "3  Rosie       16.00   97.0\n",
              "4  Ethan        9.25   49.0"
            ],
            "text/html": [
              "\n",
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              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th>0</th>\n",
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              "      <td>50.0</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Joann</td>\n",
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              "      <td>50.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Pedro</td>\n",
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              "      <td>47.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Rosie</td>\n",
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              "      <td>97.0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Ethan</td>\n",
              "      <td>9.25</td>\n",
              "      <td>49.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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    {
      "cell_type": "code",
      "source": [
        "!wget https://raw.githubusercontent.com/MicrosoftDocs/mslearn-introduction-to-machine-learning/main/Data/ml-basics/grades.csv\n",
        "df_students = pd.read_csv('grades.csv',delimiter=',',header='infer')\n",
        "df_students.head()"
      ],
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            "--2023-03-21 21:17:45--  https://raw.githubusercontent.com/MicrosoftDocs/mslearn-introduction-to-machine-learning/main/Data/ml-basics/grades.csv\n",
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            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.111.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 322 [text/plain]\n",
            "Saving to: ‘grades.csv.1’\n",
            "\n",
            "\rgrades.csv.1          0%[                    ]       0  --.-KB/s               \rgrades.csv.1        100%[===================>]     322  --.-KB/s    in 0s      \n",
            "\n",
            "2023-03-21 21:17:45 (25.1 MB/s) - ‘grades.csv.1’ saved [322/322]\n",
            "\n"
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              "    Name  StudyHours  Grade\n",
              "0    Dan       10.00   50.0\n",
              "1  Joann       11.50   50.0\n",
              "2  Pedro        9.00   47.0\n",
              "3  Rosie       16.00   97.0\n",
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        "df_students.isnull()"
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              "     Name  StudyHours  Grade\n",
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              "9   False       False  False\n",
              "10  False       False  False\n",
              "11  False       False  False\n",
              "12  False       False  False\n",
              "13  False       False  False\n",
              "14  False       False  False\n",
              "15  False       False  False\n",
              "16  False       False  False\n",
              "17  False       False  False\n",
              "18  False       False  False\n",
              "19  False       False  False\n",
              "20  False       False  False\n",
              "21  False       False  False\n",
              "22  False       False   True\n",
              "23  False        True   True"
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              "\n",
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              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_students.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "is5RBItZCexc",
        "outputId": "060b6cf3-0f7c-4b0a-bd05-347b91d3a713"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Name          0\n",
              "StudyHours    1\n",
              "Grade         2\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_students[df_students.isnull().any(axis=1)]"
      ],
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        },
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Name  StudyHours  Grade\n",
              "22  Bill         8.0    NaN\n",
              "23   Ted         NaN    NaN"
            ],
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              "                                                     [key], {});\n",
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              "\n",
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    {
      "cell_type": "code",
      "source": [
        "df_students.StudyHours = df_students.StudyHours.fillna(df_students.StudyHours.mean())\n",
        "df_students"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 802
        },
        "id": "4INnyH-tDp8c",
        "outputId": "54d282af-b761-4ff3-cfae-dda82bf12355"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Name  StudyHours  Grade\n",
              "0         Dan   10.000000   50.0\n",
              "1       Joann   11.500000   50.0\n",
              "2       Pedro    9.000000   47.0\n",
              "3       Rosie   16.000000   97.0\n",
              "4       Ethan    9.250000   49.0\n",
              "5       Vicky    1.000000    3.0\n",
              "6    Frederic   11.500000   53.0\n",
              "7      Jimmie    9.000000   42.0\n",
              "8      Rhonda    8.500000   26.0\n",
              "9    Giovanni   14.500000   74.0\n",
              "10  Francesca   15.500000   82.0\n",
              "11      Rajab   13.750000   62.0\n",
              "12    Naiyana    9.000000   37.0\n",
              "13       Kian    8.000000   15.0\n",
              "14      Jenny   15.500000   70.0\n",
              "15     Jakeem    8.000000   27.0\n",
              "16     Helena    9.000000   36.0\n",
              "17      Ismat    6.000000   35.0\n",
              "18      Anila   10.000000   48.0\n",
              "19       Skye   12.000000   52.0\n",
              "20     Daniel   12.500000   63.0\n",
              "21      Aisha   12.000000   64.0\n",
              "22       Bill    8.000000    NaN\n",
              "23        Ted   10.413043    NaN"
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              "      <th>6</th>\n",
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              "      <th>7</th>\n",
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              "      <td>26.0</td>\n",
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              "      <th>9</th>\n",
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              "      <th>10</th>\n",
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              "      <td>15.500000</td>\n",
              "      <td>82.0</td>\n",
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              "      <th>11</th>\n",
              "      <td>Rajab</td>\n",
              "      <td>13.750000</td>\n",
              "      <td>62.0</td>\n",
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              "      <th>12</th>\n",
              "      <td>Naiyana</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>37.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Kian</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Jenny</td>\n",
              "      <td>15.500000</td>\n",
              "      <td>70.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Jakeem</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>27.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Helena</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>36.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Ismat</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>35.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Anila</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>48.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Skye</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>52.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Daniel</td>\n",
              "      <td>12.500000</td>\n",
              "      <td>63.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Aisha</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>64.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Bill</td>\n",
              "      <td>8.000000</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>Ted</td>\n",
              "      <td>10.413043</td>\n",
              "      <td>NaN</td>\n",
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              "  </tbody>\n",
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              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-fb39f24f-3896-46b2-85f0-9fe6d6c3a45f button.colab-df-convert');\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_students = df_students.dropna(axis=0, how='any')\n",
        "df_students"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 739
        },
        "id": "PWtgluaGEOjC",
        "outputId": "c843f3ae-5e2f-4903-fb2e-9baf55048e6a"
      },
      "execution_count": null,
      "outputs": [
        {
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            "text/plain": [
              "         Name  StudyHours  Grade\n",
              "0         Dan       10.00   50.0\n",
              "1       Joann       11.50   50.0\n",
              "2       Pedro        9.00   47.0\n",
              "3       Rosie       16.00   97.0\n",
              "4       Ethan        9.25   49.0\n",
              "5       Vicky        1.00    3.0\n",
              "6    Frederic       11.50   53.0\n",
              "7      Jimmie        9.00   42.0\n",
              "8      Rhonda        8.50   26.0\n",
              "9    Giovanni       14.50   74.0\n",
              "10  Francesca       15.50   82.0\n",
              "11      Rajab       13.75   62.0\n",
              "12    Naiyana        9.00   37.0\n",
              "13       Kian        8.00   15.0\n",
              "14      Jenny       15.50   70.0\n",
              "15     Jakeem        8.00   27.0\n",
              "16     Helena        9.00   36.0\n",
              "17      Ismat        6.00   35.0\n",
              "18      Anila       10.00   48.0\n",
              "19       Skye       12.00   52.0\n",
              "20     Daniel       12.50   63.0\n",
              "21      Aisha       12.00   64.0"
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              "      <td>Rosie</td>\n",
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              "      <th>5</th>\n",
              "      <td>Vicky</td>\n",
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              "      <th>6</th>\n",
              "      <td>Frederic</td>\n",
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              "      <td>26.0</td>\n",
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              "      <th>9</th>\n",
              "      <td>Giovanni</td>\n",
              "      <td>14.50</td>\n",
              "      <td>74.0</td>\n",
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              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Francesca</td>\n",
              "      <td>15.50</td>\n",
              "      <td>82.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Rajab</td>\n",
              "      <td>13.75</td>\n",
              "      <td>62.0</td>\n",
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              "      <th>12</th>\n",
              "      <td>Naiyana</td>\n",
              "      <td>9.00</td>\n",
              "      <td>37.0</td>\n",
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              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Kian</td>\n",
              "      <td>8.00</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Jenny</td>\n",
              "      <td>15.50</td>\n",
              "      <td>70.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Jakeem</td>\n",
              "      <td>8.00</td>\n",
              "      <td>27.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Helena</td>\n",
              "      <td>9.00</td>\n",
              "      <td>36.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Ismat</td>\n",
              "      <td>6.00</td>\n",
              "      <td>35.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Anila</td>\n",
              "      <td>10.00</td>\n",
              "      <td>48.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Skye</td>\n",
              "      <td>12.00</td>\n",
              "      <td>52.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Daniel</td>\n",
              "      <td>12.50</td>\n",
              "      <td>63.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Aisha</td>\n",
              "      <td>12.00</td>\n",
              "      <td>64.0</td>\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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            ]
          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Get the mean study hours using to column name as an index\n",
        "mean_study = df_students['StudyHours'].mean()\n",
        "\n",
        "# Get the mean grade using the column name as a property (just to make the point!)\n",
        "mean_grade = df_students.Grade.mean()\n",
        "\n",
        "# Print the mean study hours and mean grade\n",
        "print('Average weekly study hours: {:.2f}\\nAverage grade: {:.2f}'.format(mean_study, mean_grade))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qc0dvhjlEde_",
        "outputId": "d5a6185c-0fd4-4e7d-8e59-e27c2a63fe7a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Average weekly study hours: 10.52\n",
            "Average grade: 49.18\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Get students who studied for the mean or more hours\n",
        "df_students[df_students.StudyHours > mean_study]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "W2FSJxJMG41u",
        "outputId": "2981967e-1e4e-496b-82ac-3dbc9e6b2834"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Name  StudyHours  Grade\n",
              "1       Joann       11.50   50.0\n",
              "3       Rosie       16.00   97.0\n",
              "6    Frederic       11.50   53.0\n",
              "9    Giovanni       14.50   74.0\n",
              "10  Francesca       15.50   82.0\n",
              "11      Rajab       13.75   62.0\n",
              "14      Jenny       15.50   70.0\n",
              "19       Skye       12.00   52.0\n",
              "20     Daniel       12.50   63.0\n",
              "21      Aisha       12.00   64.0"
            ],
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              "      <td>Joann</td>\n",
              "      <td>11.50</td>\n",
              "      <td>50.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Rosie</td>\n",
              "      <td>16.00</td>\n",
              "      <td>97.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Frederic</td>\n",
              "      <td>11.50</td>\n",
              "      <td>53.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Giovanni</td>\n",
              "      <td>14.50</td>\n",
              "      <td>74.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Francesca</td>\n",
              "      <td>15.50</td>\n",
              "      <td>82.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Rajab</td>\n",
              "      <td>13.75</td>\n",
              "      <td>62.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Jenny</td>\n",
              "      <td>15.50</td>\n",
              "      <td>70.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Skye</td>\n",
              "      <td>12.00</td>\n",
              "      <td>52.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Daniel</td>\n",
              "      <td>12.50</td>\n",
              "      <td>63.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Aisha</td>\n",
              "      <td>12.00</td>\n",
              "      <td>64.0</td>\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "            + ' to learn more about interactive tables.';\n",
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          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# What was their mean grade?\n",
        "df_students[df_students.StudyHours > mean_study].Grade.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H8DJoyh4HAjz",
        "outputId": "377492a2-f1cf-4dfb-87ae-09f4b49d0295"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "66.7"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "passes  = pd.Series(df_students['Grade'] >= 60)\n",
        "df_students = pd.concat([df_students, passes.rename(\"Pass\")], axis=1)\n",
        "\n",
        "df_students"
      ],
      "metadata": {
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              "         Name  StudyHours  Grade   Pass\n",
              "0         Dan       10.00   50.0  False\n",
              "1       Joann       11.50   50.0  False\n",
              "2       Pedro        9.00   47.0  False\n",
              "3       Rosie       16.00   97.0   True\n",
              "4       Ethan        9.25   49.0  False\n",
              "5       Vicky        1.00    3.0  False\n",
              "6    Frederic       11.50   53.0  False\n",
              "7      Jimmie        9.00   42.0  False\n",
              "8      Rhonda        8.50   26.0  False\n",
              "9    Giovanni       14.50   74.0   True\n",
              "10  Francesca       15.50   82.0   True\n",
              "11      Rajab       13.75   62.0   True\n",
              "12    Naiyana        9.00   37.0  False\n",
              "13       Kian        8.00   15.0  False\n",
              "14      Jenny       15.50   70.0   True\n",
              "15     Jakeem        8.00   27.0  False\n",
              "16     Helena        9.00   36.0  False\n",
              "17      Ismat        6.00   35.0  False\n",
              "18      Anila       10.00   48.0  False\n",
              "19       Skye       12.00   52.0  False\n",
              "20     Daniel       12.50   63.0   True\n",
              "21      Aisha       12.00   64.0   True"
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              "      <td>Ismat</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(df_students.groupby(df_students.Pass).Name.count())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BEDQG9S4HY-7",
        "outputId": "1e6cff38-5740-4aa4-8ba9-8d44a66853a7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Pass\n",
            "False    15\n",
            "True      7\n",
            "Name: Name, dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(df_students.groupby(df_students.Pass)['StudyHours', 'Grade'].mean())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8nRI6tQOIRwU",
        "outputId": "3dc53128-07af-422c-8973-860ba113fe48"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "       StudyHours      Grade\n",
            "Pass                        \n",
            "False    8.783333  38.000000\n",
            "True    14.250000  73.142857\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-32-8b15539b8d19>:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
            "  print(df_students.groupby(df_students.Pass)['StudyHours', 'Grade'].mean())\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Create a DataFrame with the data sorted by Grade (descending)\n",
        "df_students = df_students.sort_values('Grade', ascending=False)\n",
        "\n",
        "# Show the DataFrame\n",
        "df_students"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 739
        },
        "id": "nbVmtE82IVP0",
        "outputId": "23d590c1-e404-42c6-f6d0-a4c19d492590"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         Name  StudyHours  Grade   Pass\n",
              "3       Rosie       16.00   97.0   True\n",
              "10  Francesca       15.50   82.0   True\n",
              "9    Giovanni       14.50   74.0   True\n",
              "14      Jenny       15.50   70.0   True\n",
              "21      Aisha       12.00   64.0   True\n",
              "20     Daniel       12.50   63.0   True\n",
              "11      Rajab       13.75   62.0   True\n",
              "6    Frederic       11.50   53.0  False\n",
              "19       Skye       12.00   52.0  False\n",
              "1       Joann       11.50   50.0  False\n",
              "0         Dan       10.00   50.0  False\n",
              "4       Ethan        9.25   49.0  False\n",
              "18      Anila       10.00   48.0  False\n",
              "2       Pedro        9.00   47.0  False\n",
              "7      Jimmie        9.00   42.0  False\n",
              "12    Naiyana        9.00   37.0  False\n",
              "16     Helena        9.00   36.0  False\n",
              "17      Ismat        6.00   35.0  False\n",
              "15     Jakeem        8.00   27.0  False\n",
              "8      Rhonda        8.50   26.0  False\n",
              "13       Kian        8.00   15.0  False\n",
              "5       Vicky        1.00    3.0  False"
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              "      <th>1</th>\n",
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              "      <th>4</th>\n",
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              "      <td>False</td>\n",
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              "      <th>18</th>\n",
              "      <td>Anila</td>\n",
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              "      <th>2</th>\n",
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              "      <th>7</th>\n",
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              "      <td>False</td>\n",
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              "      <th>16</th>\n",
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              "      <td>False</td>\n",
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              "      <th>17</th>\n",
              "      <td>Ismat</td>\n",
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              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Jakeem</td>\n",
              "      <td>8.00</td>\n",
              "      <td>27.0</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Rhonda</td>\n",
              "      <td>8.50</td>\n",
              "      <td>26.0</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Kian</td>\n",
              "      <td>8.00</td>\n",
              "      <td>15.0</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Vicky</td>\n",
              "      <td>1.00</td>\n",
              "      <td>3.0</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d79e6914-67bb-4b0e-9801-73999c2c5d21')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "       width=\"24px\">\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-d79e6914-67bb-4b0e-9801-73999c2c5d21 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d79e6914-67bb-4b0e-9801-73999c2c5d21');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "jUO0GQsFIca1"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}