<div>
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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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      <th>Gender</th>
      <th>Product line</th>
      <th>Total</th>
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      <th>0</th>
      <td>Female</td>
      <td>Electronic accessories</td>
      <td>27102.0225</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Female</td>
      <td>Fashion accessories</td>
      <td>30437.4000</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Female</td>
      <td>Food and beverages</td>
      <td>33170.9175</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Female</td>
      <td>Health and beauty</td>
      <td>18560.9865</td>
    </tr>
    <tr>
      <th>4</th>
      <td>Female</td>
      <td>Home and lifestyle</td>
      <td>30036.8775</td>
    </tr>
    <tr>
      <th>5</th>
      <td>Female</td>
      <td>Sports and travel</td>
      <td>28574.7210</td>
    </tr>
    <tr>
      <th>6</th>
      <td>Male</td>
      <td>Electronic accessories</td>
      <td>27235.5090</td>
    </tr>
    <tr>
      <th>7</th>
      <td>Male</td>
      <td>Fashion accessories</td>
      <td>23868.4950</td>
    </tr>
    <tr>
      <th>8</th>
      <td>Male</td>
      <td>Food and beverages</td>
      <td>22973.9265</td>
    </tr>
    <tr>
      <th>9</th>
      <td>Male</td>
      <td>Health and beauty</td>
      <td>30632.7525</td>
    </tr>
    <tr>
      <th>10</th>
      <td>Male</td>
      <td>Home and lifestyle</td>
      <td>23825.0355</td>
    </tr>
    <tr>
      <th>11</th>
      <td>Male</td>
      <td>Sports and travel</td>
      <td>26548.1055</td>
    </tr>
  </tbody>
</table>
</div>

    Gender            Product line       Total
0   Female  Electronic accessories  27102.0225
1   Female     Fashion accessories  30437.4000
2   Female      Food and beverages  33170.9175
3   Female       Health and beauty  18560.9865
4   Female      Home and lifestyle  30036.8775
5   Female       Sports and travel  28574.7210
6     Male  Electronic accessories  27235.5090
7     Male     Fashion accessories  23868.4950
8     Male      Food and beverages  22973.9265
9     Male       Health and beauty  30632.7525
10    Male      Home and lifestyle  23825.0355
11    Male       Sports and travel  26548.1055

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Vizly: AI-powered data analysis

Visualizing Customer Ratings Distribution in Supermarket Sales Data

Distribution of ratings

Explore ratings distribution by different branches

Total sales by gender, by product category

Total Sales by Gender and Product Category