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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Invoice ID</th>
      <th>Branch</th>
      <th>City</th>
      <th>Customer type</th>
      <th>Gender</th>
      <th>Product line</th>
      <th>Unit price</th>
      <th>Quantity</th>
      <th>Tax 5%</th>
      <th>Total</th>
      <th>Date</th>
      <th>Time</th>
      <th>Payment</th>
      <th>cogs</th>
      <th>gross margin percentage</th>
      <th>gross income</th>
      <th>Rating</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>750-67-8428</td>
      <td>A</td>
      <td>Yangon</td>
      <td>Member</td>
      <td>Female</td>
      <td>Health and beauty</td>
      <td>74.69</td>
      <td>7</td>
      <td>26.1415</td>
      <td>548.9715</td>
      <td>1/5/2019</td>
      <td>13:08</td>
      <td>Ewallet</td>
      <td>522.83</td>
      <td>4.761905</td>
      <td>26.1415</td>
      <td>9.1</td>
    </tr>
    <tr>
      <th>1</th>
      <td>226-31-3081</td>
      <td>C</td>
      <td>Naypyitaw</td>
      <td>Normal</td>
      <td>Female</td>
      <td>Electronic accessories</td>
      <td>15.28</td>
      <td>5</td>
      <td>3.8200</td>
      <td>80.2200</td>
      <td>3/8/2019</td>
      <td>10:29</td>
      <td>Cash</td>
      <td>76.40</td>
      <td>4.761905</td>
      <td>3.8200</td>
      <td>9.6</td>
    </tr>
    <tr>
      <th>2</th>
      <td>631-41-3108</td>
      <td>A</td>
      <td>Yangon</td>
      <td>Normal</td>
      <td>Male</td>
      <td>Home and lifestyle</td>
      <td>46.33</td>
      <td>7</td>
      <td>16.2155</td>
      <td>340.5255</td>
      <td>3/3/2019</td>
      <td>13:23</td>
      <td>Credit card</td>
      <td>324.31</td>
      <td>4.761905</td>
      <td>16.2155</td>
      <td>7.4</td>
    </tr>
    <tr>
      <th>3</th>
      <td>123-19-1176</td>
      <td>A</td>
      <td>Yangon</td>
      <td>Member</td>
      <td>Male</td>
      <td>Health and beauty</td>
      <td>58.22</td>
      <td>8</td>
      <td>23.2880</td>
      <td>489.0480</td>
      <td>1/27/2019</td>
      <td>20:33</td>
      <td>Ewallet</td>
      <td>465.76</td>
      <td>4.761905</td>
      <td>23.2880</td>
      <td>8.4</td>
    </tr>
    <tr>
      <th>4</th>
      <td>373-73-7910</td>
      <td>A</td>
      <td>Yangon</td>
      <td>Normal</td>
      <td>Male</td>
      <td>Sports and travel</td>
      <td>86.31</td>
      <td>7</td>
      <td>30.2085</td>
      <td>634.3785</td>
      <td>2/8/2019</td>
      <td>10:37</td>
      <td>Ewallet</td>
      <td>604.17</td>
      <td>4.761905</td>
      <td>30.2085</td>
      <td>5.3</td>
    </tr>
  </tbody>
</table>
</div>

    Invoice ID Branch       City Customer type  Gender  \
0  750-67-8428      A     Yangon        Member  Female   
1  226-31-3081      C  Naypyitaw        Normal  Female   
2  631-41-3108      A     Yangon        Normal    Male   
3  123-19-1176      A     Yangon        Member    Male   
4  373-73-7910      A     Yangon        Normal    Male   

             Product line  Unit price  Quantity   Tax 5%     Total       Date  \
0       Health and beauty       74.69         7  26.1415  548.9715   1/5/2019   
1  Electronic accessories       15.28         5   3.8200   80.2200   3/8/2019   
2      Home and lifestyle       46.33         7  16.2155  340.5255   3/3/2019   
3       Health and beauty       58.22         8  23.2880  489.0480  1/27/2019   
4       Sports and travel       86.31         7  30.2085  634.3785   2/8/2019   

    Time      Payment    cogs  gross margin percentage  gross income  Rating  
0  13:08      Ewallet  522.83                 4.761905       26.1415     9.1  
1  10:29         Cash   76.40                 4.761905        3.8200     9.6  
2  13:23  Credit card  324.31                 4.761905       16.2155     7.4  
3  20:33      Ewallet  465.76                 4.761905       23.2880     8.4  
4  10:37      Ewallet  604.17                 4.761905       30.2085     5.3  

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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Gender</th>
      <th>Product line</th>
      <th>Total Sales</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>Female</td>
      <td>Electronic accessories</td>
      <td>25811.45</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Female</td>
      <td>Fashion accessories</td>
      <td>28988.00</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Female</td>
      <td>Food and beverages</td>
      <td>31591.35</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Female</td>
      <td>Health and beauty</td>
      <td>17677.13</td>
    </tr>
    <tr>
      <th>4</th>
      <td>Female</td>
      <td>Home and lifestyle</td>
      <td>28606.55</td>
    </tr>
    <tr>
      <th>5</th>
      <td>Female</td>
      <td>Sports and travel</td>
      <td>27214.02</td>
    </tr>
    <tr>
      <th>6</th>
      <td>Male</td>
      <td>Electronic accessories</td>
      <td>25938.58</td>
    </tr>
    <tr>
      <th>7</th>
      <td>Male</td>
      <td>Fashion accessories</td>
      <td>22731.90</td>
    </tr>
    <tr>
      <th>8</th>
      <td>Male</td>
      <td>Food and beverages</td>
      <td>21879.93</td>
    </tr>
    <tr>
      <th>9</th>
      <td>Male</td>
      <td>Health and beauty</td>
      <td>29174.05</td>
    </tr>
    <tr>
      <th>10</th>
      <td>Male</td>
      <td>Home and lifestyle</td>
      <td>22690.51</td>
    </tr>
    <tr>
      <th>11</th>
      <td>Male</td>
      <td>Sports and travel</td>
      <td>25283.91</td>
    </tr>
  </tbody>
</table>
</div>

    Gender            Product line  Total Sales
0   Female  Electronic accessories     25811.45
1   Female     Fashion accessories     28988.00
2   Female      Food and beverages     31591.35
3   Female       Health and beauty     17677.13
4   Female      Home and lifestyle     28606.55
5   Female       Sports and travel     27214.02
6     Male  Electronic accessories     25938.58
7     Male     Fashion accessories     22731.90
8     Male      Food and beverages     21879.93
9     Male       Health and beauty     29174.05
10    Male      Home and lifestyle     22690.51
11    Male       Sports and travel     25283.91

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Vizly: AI-powered data analysis

Analyzing Customer Ratings Across Supermarket Locations

Distribution of customer ratings by location

Total sales by gender, by product category