<div>
<style scoped>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Retailer</th>
      <th>Retailer ID</th>
      <th>Invoice Date</th>
      <th>Region</th>
      <th>State</th>
      <th>City</th>
      <th>Product</th>
      <th>Price per Unit</th>
      <th>Units Sold</th>
      <th>Total Sales</th>
      <th>Operating Profit</th>
      <th>Operating Margin</th>
      <th>Sales Method</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>Foot Locker</td>
      <td>1185732</td>
      <td>1/1/20</td>
      <td>Northeast</td>
      <td>New York</td>
      <td>New York</td>
      <td>Men's Street Footwear</td>
      <td>$50.00</td>
      <td>1,200</td>
      <td>$600,000</td>
      <td>$300,000</td>
      <td>50%</td>
      <td>In-store</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Foot Locker</td>
      <td>1185732</td>
      <td>1/2/20</td>
      <td>Northeast</td>
      <td>New York</td>
      <td>New York</td>
      <td>Men's Athletic Footwear</td>
      <td>$50.00</td>
      <td>1,000</td>
      <td>$500,000</td>
      <td>$150,000</td>
      <td>30%</td>
      <td>In-store</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Foot Locker</td>
      <td>1185732</td>
      <td>1/3/20</td>
      <td>Northeast</td>
      <td>New York</td>
      <td>New York</td>
      <td>Women's Street Footwear</td>
      <td>$40.00</td>
      <td>1,000</td>
      <td>$400,000</td>
      <td>$140,000</td>
      <td>35%</td>
      <td>In-store</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Foot Locker</td>
      <td>1185732</td>
      <td>1/4/20</td>
      <td>Northeast</td>
      <td>New York</td>
      <td>New York</td>
      <td>Women's Athletic Footwear</td>
      <td>$45.00</td>
      <td>850</td>
      <td>$382,500</td>
      <td>$133,875</td>
      <td>35%</td>
      <td>In-store</td>
    </tr>
    <tr>
      <th>4</th>
      <td>Foot Locker</td>
      <td>1185732</td>
      <td>1/5/20</td>
      <td>Northeast</td>
      <td>New York</td>
      <td>New York</td>
      <td>Men's Apparel</td>
      <td>$60.00</td>
      <td>900</td>
      <td>$540,000</td>
      <td>$162,000</td>
      <td>30%</td>
      <td>In-store</td>
    </tr>
  </tbody>
</table>
</div>

      Retailer  Retailer ID Invoice Date     Region     State      City  \
0  Foot Locker      1185732       1/1/20  Northeast  New York  New York   
1  Foot Locker      1185732       1/2/20  Northeast  New York  New York   
2  Foot Locker      1185732       1/3/20  Northeast  New York  New York   
3  Foot Locker      1185732       1/4/20  Northeast  New York  New York   
4  Foot Locker      1185732       1/5/20  Northeast  New York  New York   

                     Product Price per Unit Units Sold Total Sales  \
0      Men's Street Footwear         $50.00      1,200    $600,000   
1    Men's Athletic Footwear         $50.00      1,000    $500,000   
2    Women's Street Footwear         $40.00      1,000    $400,000   
3  Women's Athletic Footwear         $45.00        850    $382,500   
4              Men's Apparel         $60.00        900    $540,000   

  Operating Profit Operating Margin Sales Method  
0         $300,000              50%     In-store  
1         $150,000              30%     In-store  
2         $140,000              35%     In-store  
3         $133,875              35%     In-store  
4         $162,000              30%     In-store  

<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Region</th>
      <th>Product</th>
      <th>Units Sold</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>2</th>
      <td>Midwest</td>
      <td>Men's Street Footwear</td>
      <td>19005</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Midwest</td>
      <td>Men's Athletic Footwear</td>
      <td>12650</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Midwest</td>
      <td>Women's Apparel</td>
      <td>11725</td>
    </tr>
    <tr>
      <th>5</th>
      <td>Midwest</td>
      <td>Women's Street Footwear</td>
      <td>10665</td>
    </tr>
    <tr>
      <th>4</th>
      <td>Midwest</td>
      <td>Women's Athletic Footwear</td>
      <td>8400</td>
    </tr>
    <tr>
      <th>0</th>
      <td>Midwest</td>
      <td>Men's Apparel</td>
      <td>7300</td>
    </tr>
    <tr>
      <th>8</th>
      <td>Northeast</td>
      <td>Men's Street Footwear</td>
      <td>19855</td>
    </tr>
    <tr>
      <th>9</th>
      <td>Northeast</td>
      <td>Women's Apparel</td>
      <td>15175</td>
    </tr>
    <tr>
      <th>7</th>
      <td>Northeast</td>
      <td>Men's Athletic Footwear</td>
      <td>14450</td>
    </tr>
    <tr>
      <th>11</th>
      <td>Northeast</td>
      <td>Women's Street Footwear</td>
      <td>13490</td>
    </tr>
    <tr>
      <th>6</th>
      <td>Northeast</td>
      <td>Men's Apparel</td>
      <td>12225</td>
    </tr>
    <tr>
      <th>10</th>
      <td>Northeast</td>
      <td>Women's Athletic Footwear</td>
      <td>11975</td>
    </tr>
    <tr>
      <th>14</th>
      <td>South</td>
      <td>Men's Street Footwear</td>
      <td>26200</td>
    </tr>
    <tr>
      <th>13</th>
      <td>South</td>
      <td>Men's Athletic Footwear</td>
      <td>25900</td>
    </tr>
    <tr>
      <th>15</th>
      <td>South</td>
      <td>Women's Apparel</td>
      <td>25075</td>
    </tr>
    <tr>
      <th>17</th>
      <td>South</td>
      <td>Women's Street Footwear</td>
      <td>24000</td>
    </tr>
    <tr>
      <th>16</th>
      <td>South</td>
      <td>Women's Athletic Footwear</td>
      <td>18000</td>
    </tr>
    <tr>
      <th>12</th>
      <td>South</td>
      <td>Men's Apparel</td>
      <td>16725</td>
    </tr>
    <tr>
      <th>20</th>
      <td>Southeast</td>
      <td>Men's Street Footwear</td>
      <td>12165</td>
    </tr>
    <tr>
      <th>21</th>
      <td>Southeast</td>
      <td>Women's Apparel</td>
      <td>10300</td>
    </tr>
    <tr>
      <th>19</th>
      <td>Southeast</td>
      <td>Men's Athletic Footwear</td>
      <td>9225</td>
    </tr>
    <tr>
      <th>18</th>
      <td>Southeast</td>
      <td>Men's Apparel</td>
      <td>8850</td>
    </tr>
    <tr>
      <th>23</th>
      <td>Southeast</td>
      <td>Women's Street Footwear</td>
      <td>8795</td>
    </tr>
    <tr>
      <th>22</th>
      <td>Southeast</td>
      <td>Women's Athletic Footwear</td>
      <td>8050</td>
    </tr>
    <tr>
      <th>26</th>
      <td>West</td>
      <td>Men's Street Footwear</td>
      <td>43000</td>
    </tr>
    <tr>
      <th>25</th>
      <td>West</td>
      <td>Men's Athletic Footwear</td>
      <td>37925</td>
    </tr>
    <tr>
      <th>29</th>
      <td>West</td>
      <td>Women's Street Footwear</td>
      <td>33950</td>
    </tr>
    <tr>
      <th>27</th>
      <td>West</td>
      <td>Women's Apparel</td>
      <td>33625</td>
    </tr>
    <tr>
      <th>28</th>
      <td>West</td>
      <td>Women's Athletic Footwear</td>
      <td>29075</td>
    </tr>
    <tr>
      <th>24</th>
      <td>West</td>
      <td>Men's Apparel</td>
      <td>25850</td>
    </tr>
  </tbody>
</table>
</div>

       Region                    Product  Units Sold
2     Midwest      Men's Street Footwear       19005
1     Midwest    Men's Athletic Footwear       12650
3     Midwest            Women's Apparel       11725
5     Midwest    Women's Street Footwear       10665
4     Midwest  Women's Athletic Footwear        8400
0     Midwest              Men's Apparel        7300
8   Northeast      Men's Street Footwear       19855
9   Northeast            Women's Apparel       15175
7   Northeast    Men's Athletic Footwear       14450
11  Northeast    Women's Street Footwear       13490
6   Northeast              Men's Apparel       12225
10  Northeast  Women's Athletic Footwear       11975
14      South      Men's Street Footwear       26200
13      South    Men's Athletic Footwear       25900
15      South            Women's Apparel       25075
17      South    Women's Street Footwear       24000
16      South  Women's Athletic Footwear       18000
12      South              Men's Apparel       16725
20  Southeast      Men's Street Footwear       12165
21  Southeast            Women's Apparel       10300
19  Southeast    Men's Athletic Footwear        9225
18  Southeast              Men's Apparel        8850
23  Southeast    Women's Street Footwear        8795
22  Southeast  Women's Athletic Footwear        8050
26       West      Men's Street Footwear       43000
25       West    Men's Athletic Footwear       37925
29       West    Women's Street Footwear       33950
27       West            Women's Apparel       33625
28       West  Women's Athletic Footwear       29075
24       West              Men's Apparel       25850

Analysis of Top-Selling Adidas Products by Region from Sales Data

What are the top-selling products by region?

Can you visualize the sales data?