Monday_6th_Feb_2023.ipynb

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      "source": [
        "import pandas as pd"
      ]
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      "cell_type": "code",
      "source": [
        "df=pd.read_csv(\"CSVsales.csv\")"
      ],
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        "id": "l3n-zE8F12IL"
      },
      "execution_count": 4,
      "outputs": []
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      "cell_type": "code",
      "source": [
        "df=pd.read_csv(\"Supermarket_sales.csv\")"
      ],
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        "id": "ek4e-Sxp5cvb"
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      "execution_count": 5,
      "outputs": []
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              "       No    InvoiceID Branch       City Customertype  Gender  \\\n",
              "0       1  750-67-8428      A     Yangon       Member  Female   \n",
              "1       2  226-31-3081      C  Naypyitaw       Normal  Female   \n",
              "2       3  631-41-3108      A     Yangon       Normal    Male   \n",
              "3       4  123-19-1176      A     Yangon       Member    Male   \n",
              "4       5  373-73-7910      A     Yangon       Normal    Male   \n",
              "..    ...          ...    ...        ...          ...     ...   \n",
              "995   996  233-67-5758      C  Naypyitaw       Normal    Male   \n",
              "996   997  303-96-2227      B   Mandalay       Normal  Female   \n",
              "997   998  727-02-1313      A     Yangon       Member    Male   \n",
              "998   999  347-56-2442      A     Yangon       Normal    Male   \n",
              "999  1000  849-09-3807      A     Yangon       Member  Female   \n",
              "\n",
              "                Productline  Unitprice  Quantity      Tax      Total  \\\n",
              "0         Health and beauty      74.69         7  26.1415   548.9715   \n",
              "1    Electronic accessories      15.28         5   3.8200    80.2200   \n",
              "2        Home and lifestyle      46.33         7  16.2155   340.5255   \n",
              "3         Health and beauty      58.22         8  23.2880   489.0480   \n",
              "4         Sports and travel      86.31         7  30.2085   634.3785   \n",
              "..                      ...        ...       ...      ...        ...   \n",
              "995       Health and beauty      40.35         1   2.0175    42.3675   \n",
              "996      Home and lifestyle      97.38        10  48.6900  1022.4900   \n",
              "997      Food and beverages      31.84         1   1.5920    33.4320   \n",
              "998      Home and lifestyle      65.82         1   3.2910    69.1110   \n",
              "999     Fashion accessories      88.34         7  30.9190   649.2990   \n",
              "\n",
              "          Date   Time      Payment    cogs  gross_margin_percentage  \\\n",
              "0     1/5/2019  13:08      Ewallet  522.83                 4.761905   \n",
              "1     3/8/2019  10:29         Cash   76.40                 4.761905   \n",
              "2     3/3/2019  13:23  Credit card  324.31                 4.761905   \n",
              "3    1/27/2019  20:33      Ewallet  465.76                 4.761905   \n",
              "4     2/8/2019  10:37      Ewallet  604.17                 4.761905   \n",
              "..         ...    ...          ...     ...                      ...   \n",
              "995  1/29/2019  13:46      Ewallet   40.35                 4.761905   \n",
              "996   3/2/2019  17:16      Ewallet  973.80                 4.761905   \n",
              "997   2/9/2019  13:22         Cash   31.84                 4.761905   \n",
              "998  2/22/2019  15:33         Cash   65.82                 4.761905   \n",
              "999  2/18/2019  13:28         Cash  618.38                 4.761905   \n",
              "\n",
              "     gross_iincome  Rating  \n",
              "0          26.1415     9.1  \n",
              "1           3.8200     9.6  \n",
              "2          16.2155     7.4  \n",
              "3          23.2880     8.4  \n",
              "4          30.2085     5.3  \n",
              "..             ...     ...  \n",
              "995         2.0175     6.2  \n",
              "996        48.6900     4.4  \n",
              "997         1.5920     7.7  \n",
              "998         3.2910     4.1  \n",
              "999        30.9190     6.6  \n",
              "\n",
              "[1000 rows x 18 columns]"
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              "      <th></th>\n",
              "      <th>No</th>\n",
              "      <th>InvoiceID</th>\n",
              "      <th>Branch</th>\n",
              "      <th>City</th>\n",
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              "      <th>Date</th>\n",
              "      <th>Time</th>\n",
              "      <th>Payment</th>\n",
              "      <th>cogs</th>\n",
              "      <th>gross_margin_percentage</th>\n",
              "      <th>gross_iincome</th>\n",
              "      <th>Rating</th>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>750-67-8428</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Member</td>\n",
              "      <td>Female</td>\n",
              "      <td>Health and beauty</td>\n",
              "      <td>74.69</td>\n",
              "      <td>7</td>\n",
              "      <td>26.1415</td>\n",
              "      <td>548.9715</td>\n",
              "      <td>1/5/2019</td>\n",
              "      <td>13:08</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>522.83</td>\n",
              "      <td>4.761905</td>\n",
              "      <td>26.1415</td>\n",
              "      <td>9.1</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>226-31-3081</td>\n",
              "      <td>C</td>\n",
              "      <td>Naypyitaw</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Female</td>\n",
              "      <td>Electronic accessories</td>\n",
              "      <td>15.28</td>\n",
              "      <td>5</td>\n",
              "      <td>3.8200</td>\n",
              "      <td>80.2200</td>\n",
              "      <td>3/8/2019</td>\n",
              "      <td>10:29</td>\n",
              "      <td>Cash</td>\n",
              "      <td>76.40</td>\n",
              "      <td>4.761905</td>\n",
              "      <td>3.8200</td>\n",
              "      <td>9.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>631-41-3108</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Male</td>\n",
              "      <td>Home and lifestyle</td>\n",
              "      <td>46.33</td>\n",
              "      <td>7</td>\n",
              "      <td>16.2155</td>\n",
              "      <td>340.5255</td>\n",
              "      <td>3/3/2019</td>\n",
              "      <td>13:23</td>\n",
              "      <td>Credit card</td>\n",
              "      <td>324.31</td>\n",
              "      <td>4.761905</td>\n",
              "      <td>16.2155</td>\n",
              "      <td>7.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>123-19-1176</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Member</td>\n",
              "      <td>Male</td>\n",
              "      <td>Health and beauty</td>\n",
              "      <td>58.22</td>\n",
              "      <td>8</td>\n",
              "      <td>23.2880</td>\n",
              "      <td>489.0480</td>\n",
              "      <td>1/27/2019</td>\n",
              "      <td>20:33</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>465.76</td>\n",
              "      <td>4.761905</td>\n",
              "      <td>23.2880</td>\n",
              "      <td>8.4</td>\n",
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              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>373-73-7910</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Male</td>\n",
              "      <td>Sports and travel</td>\n",
              "      <td>86.31</td>\n",
              "      <td>7</td>\n",
              "      <td>30.2085</td>\n",
              "      <td>634.3785</td>\n",
              "      <td>2/8/2019</td>\n",
              "      <td>10:37</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>604.17</td>\n",
              "      <td>4.761905</td>\n",
              "      <td>30.2085</td>\n",
              "      <td>5.3</td>\n",
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              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>995</th>\n",
              "      <td>996</td>\n",
              "      <td>233-67-5758</td>\n",
              "      <td>C</td>\n",
              "      <td>Naypyitaw</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Male</td>\n",
              "      <td>Health and beauty</td>\n",
              "      <td>40.35</td>\n",
              "      <td>1</td>\n",
              "      <td>2.0175</td>\n",
              "      <td>42.3675</td>\n",
              "      <td>1/29/2019</td>\n",
              "      <td>13:46</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>40.35</td>\n",
              "      <td>4.761905</td>\n",
              "      <td>2.0175</td>\n",
              "      <td>6.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>996</th>\n",
              "      <td>997</td>\n",
              "      <td>303-96-2227</td>\n",
              "      <td>B</td>\n",
              "      <td>Mandalay</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Female</td>\n",
              "      <td>Home and lifestyle</td>\n",
              "      <td>97.38</td>\n",
              "      <td>10</td>\n",
              "      <td>48.6900</td>\n",
              "      <td>1022.4900</td>\n",
              "      <td>3/2/2019</td>\n",
              "      <td>17:16</td>\n",
              "      <td>Ewallet</td>\n",
              "      <td>973.80</td>\n",
              "      <td>4.761905</td>\n",
              "      <td>48.6900</td>\n",
              "      <td>4.4</td>\n",
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              "    <tr>\n",
              "      <th>997</th>\n",
              "      <td>998</td>\n",
              "      <td>727-02-1313</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Member</td>\n",
              "      <td>Male</td>\n",
              "      <td>Food and beverages</td>\n",
              "      <td>31.84</td>\n",
              "      <td>1</td>\n",
              "      <td>1.5920</td>\n",
              "      <td>33.4320</td>\n",
              "      <td>2/9/2019</td>\n",
              "      <td>13:22</td>\n",
              "      <td>Cash</td>\n",
              "      <td>31.84</td>\n",
              "      <td>4.761905</td>\n",
              "      <td>1.5920</td>\n",
              "      <td>7.7</td>\n",
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              "    <tr>\n",
              "      <th>998</th>\n",
              "      <td>999</td>\n",
              "      <td>347-56-2442</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Male</td>\n",
              "      <td>Home and lifestyle</td>\n",
              "      <td>65.82</td>\n",
              "      <td>1</td>\n",
              "      <td>3.2910</td>\n",
              "      <td>69.1110</td>\n",
              "      <td>2/22/2019</td>\n",
              "      <td>15:33</td>\n",
              "      <td>Cash</td>\n",
              "      <td>65.82</td>\n",
              "      <td>4.761905</td>\n",
              "      <td>3.2910</td>\n",
              "      <td>4.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>999</th>\n",
              "      <td>1000</td>\n",
              "      <td>849-09-3807</td>\n",
              "      <td>A</td>\n",
              "      <td>Yangon</td>\n",
              "      <td>Member</td>\n",
              "      <td>Female</td>\n",
              "      <td>Fashion accessories</td>\n",
              "      <td>88.34</td>\n",
              "      <td>7</td>\n",
              "      <td>30.9190</td>\n",
              "      <td>649.2990</td>\n",
              "      <td>2/18/2019</td>\n",
              "      <td>13:28</td>\n",
              "      <td>Cash</td>\n",
              "      <td>618.38</td>\n",
              "      <td>4.761905</td>\n",
              "      <td>30.9190</td>\n",
              "      <td>6.6</td>\n",
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              "<p>1000 rows × 18 columns</p>\n",
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          "data": {
            "text/plain": [
              "   No    InvoiceID Branch       City Customertype  Gender  \\\n",
              "0   1  750-67-8428      A     Yangon       Member  Female   \n",
              "1   2  226-31-3081      C  Naypyitaw       Normal  Female   \n",
              "2   3  631-41-3108      A     Yangon       Normal    Male   \n",
              "3   4  123-19-1176      A     Yangon       Member    Male   \n",
              "4   5  373-73-7910      A     Yangon       Normal    Male   \n",
              "\n",
              "              Productline  Unitprice  Quantity      Tax     Total       Date  \\\n",
              "0       Health and beauty      74.69         7  26.1415  548.9715   1/5/2019   \n",
              "1  Electronic accessories      15.28         5   3.8200   80.2200   3/8/2019   \n",
              "2      Home and lifestyle      46.33         7  16.2155  340.5255   3/3/2019   \n",
              "3       Health and beauty      58.22         8  23.2880  489.0480  1/27/2019   \n",
              "4       Sports and travel      86.31         7  30.2085  634.3785   2/8/2019   \n",
              "\n",
              "    Time      Payment    cogs  gross_margin_percentage  gross_iincome  Rating  \n",
              "0  13:08      Ewallet  522.83                 4.761905        26.1415     9.1  \n",
              "1  10:29         Cash   76.40                 4.761905         3.8200     9.6  \n",
              "2  13:23  Credit card  324.31                 4.761905        16.2155     7.4  \n",
              "3  20:33      Ewallet  465.76                 4.761905        23.2880     8.4  \n",
              "4  10:37      Ewallet  604.17                 4.761905        30.2085     5.3  "
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          "metadata": {},
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    {
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      "source": [
        "df.tail()"
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          "height": 357
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        "id": "syRzlb9d8_oD",
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      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       No    InvoiceID Branch       City Customertype  Gender  \\\n",
              "995   996  233-67-5758      C  Naypyitaw       Normal    Male   \n",
              "996   997  303-96-2227      B   Mandalay       Normal  Female   \n",
              "997   998  727-02-1313      A     Yangon       Member    Male   \n",
              "998   999  347-56-2442      A     Yangon       Normal    Male   \n",
              "999  1000  849-09-3807      A     Yangon       Member  Female   \n",
              "\n",
              "             Productline  Unitprice  Quantity      Tax      Total       Date  \\\n",
              "995    Health and beauty      40.35         1   2.0175    42.3675  1/29/2019   \n",
              "996   Home and lifestyle      97.38        10  48.6900  1022.4900   3/2/2019   \n",
              "997   Food and beverages      31.84         1   1.5920    33.4320   2/9/2019   \n",
              "998   Home and lifestyle      65.82         1   3.2910    69.1110  2/22/2019   \n",
              "999  Fashion accessories      88.34         7  30.9190   649.2990  2/18/2019   \n",
              "\n",
              "      Time  Payment    cogs  gross_margin_percentage  gross_iincome  Rating  \n",
              "995  13:46  Ewallet   40.35                 4.761905         2.0175     6.2  \n",
              "996  17:16  Ewallet  973.80                 4.761905        48.6900     4.4  \n",
              "997  13:22     Cash   31.84                 4.761905         1.5920     7.7  \n",
              "998  15:33     Cash   65.82                 4.761905         3.2910     4.1  \n",
              "999  13:28     Cash  618.38                 4.761905        30.9190     6.6  "
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              "      <td>7</td>\n",
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              "          document.querySelector('#df-557e6089-6558-4da1-a3d4-45a318b4c7f1 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-557e6089-6558-4da1-a3d4-45a318b4c7f1');\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": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.InvoiceID"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q6uvxXAt9Ebk",
        "outputId": "9c02d574-a6d3-4408-91a2-d83692cb8a15"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      750-67-8428\n",
              "1      226-31-3081\n",
              "2      631-41-3108\n",
              "3      123-19-1176\n",
              "4      373-73-7910\n",
              "          ...     \n",
              "995    233-67-5758\n",
              "996    303-96-2227\n",
              "997    727-02-1313\n",
              "998    347-56-2442\n",
              "999    849-09-3807\n",
              "Name: InvoiceID, Length: 1000, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.InvoiceID[1]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "-eBiLHFY-Fp-",
        "outputId": "08d3d609-3e9d-45a9-8f10-cc7b6a13a3b2"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'226-31-3081'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.City[48]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "V9eABeWr-S2G",
        "outputId": "558c2370-d977-47a0-82bd-cacc51bb1d82"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Mandalay'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Branch[99]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "8hH8lqbw-VRG",
        "outputId": "5dce0963-e708-48db-f322-5baeeb51c10c"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'B'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Customertype[999]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "ipkv_AEL-4Gm",
        "outputId": "86ab6a1d-a31f-4254-a045-79e64fdca875"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Member'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g_ho0OA4_KQG",
        "outputId": "9c4c7de5-e7d7-4a7a-c79e-449040d4feed"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1000, 18)"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "if df.City[18]==\"Yangon\":\n",
        "  print(df.Branch[18])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fN3CxM2JAAr9",
        "outputId": "6c016a42-111a-4119-a62f-78c10bddaafc"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "A\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "if df.Customertype[100]==\"Member\":\n",
        "  print(df.InvoiceID[100])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dfnq65NHAjru",
        "outputId": "2e59efcb-61fd-410e-d66f-11cc20784043"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "163-56-7055\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Unitprice.max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bHg2kea4A7Cj",
        "outputId": "1f701460-33e1-4182-94b1-6a52390279b7"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "99.96"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Unitprice.min()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hcj9eT70Bwqq",
        "outputId": "519ff33c-ad4d-415a-f441-94c8aa67d233"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10.08"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Unitprice.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I2EVk2z5CaWb",
        "outputId": "f098de79-32a5-4b3b-fc46-266ffab2f60d"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "55.67213"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Quantity.max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HoXq8CnbCjjr",
        "outputId": "e933e805-6767-4918-82ad-c33a1eb13385"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Quantity.min()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hg1neMXmCoXt",
        "outputId": "e48ac2b1-dd37-4641-f02b-e50b78936e10"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Quantity.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YWrMJrS_CrDF",
        "outputId": "41a54b82-60d2-4f23-8af5-b0d9ba1222b8"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "5.51"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Quantity.loc[df[\"Productline\"]==\"Health and beauty\"].max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7n0b6DkYCshN",
        "outputId": "fac7d929-2f8b-468f-f476-7b40808a614b"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Quantity.loc[df[\"Productline\"]==\"Health and beauty\"].min()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0N-Cw4zPDDWZ",
        "outputId": "6be12619-1ae4-4da8-da36-f9ce60883712"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Quantity.loc[df[\"Productline\"]==\"Health and beauty\"].mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YamMAjA3EAL3",
        "outputId": "4977f084-84cd-4a66-e7f3-8bdd81f53841"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "5.618421052631579"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Unitprice.loc[df['Productline']==\"Health and beauty\"].max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bcHvNWwZEBcf",
        "outputId": "96babac3-09c2-4647-c1b1-21e3addbc753"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "99.96"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Unitprice.loc[df['Productline']==\"Health and beauty\"].min()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V0z9ytDGEU0G",
        "outputId": "7d9d54e8-5f37-43ed-99b0-654a940cdd7b"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10.08"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Unitprice.loc[df['Productline']==\"Health and beauty\"].mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P-fQW9C9EwiN",
        "outputId": "5dfa84d3-93e5-4dff-d47c-214a5bc10ae5"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "54.85447368421053"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Quantity.loc[df[\"Productline\"]==\"Electronic accessories\"].max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dwVbnXj-ExtF",
        "outputId": "2bbe32d5-f544-4c6a-ce2f-aa267d71519d"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Quantity.loc[df[\"Productline\"]==\"Electronic accessories\"].min()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0SpA5C1GE_20",
        "outputId": "c765b15a-c85b-4c3e-c54e-29a0c0e2bf9f"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Quantity.loc[df[\"Productline\"]==\"Electronic accessories\"].mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xDxPNKq3FGTN",
        "outputId": "1e1c250c-04be-4069-acfd-6df444617d08"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "5.711764705882353"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Gender.loc[(df[\"Productline\"]==\"Health and beauty\") & (df[\"Gender\"]==\"Male\")].count()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2lxuBSZFFHot",
        "outputId": "b233e6ca-2085-4663-ba10-f824088ae961"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "88"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Gender.loc[(df[\"Productline\"]==\"Fashion accessories\") & (df[\"Gender\"]==\"Female\")].count()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yCL2q6BlFeA7",
        "outputId": "923139b2-b5e1-4f9b-ebac-eed5b0c750d3"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "96"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.Gender.loc[(df[\"Productline\"]==\"Fashion accessories\") | (df['Productline']==\"Sports and travel\") &(df[\"Gender\"]==\"Female\")].count()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sF9Um4hlIfLU",
        "outputId": "52b1f1bb-0fa3-4dd5-f242-92e4eda52b36"
      },
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "266"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ]
    }
  ]
}