<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>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>Product</th>
      <th>Units Sold</th>
      <th>Total Sales</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>Men's Street Footwear</td>
      <td>120225</td>
      <td>59786500.0</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Men's Athletic Footwear</td>
      <td>100150</td>
      <td>52045000.0</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Women's Apparel</td>
      <td>95900</td>
      <td>57406250.0</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Women's Street Footwear</td>
      <td>90900</td>
      <td>44861000.0</td>
    </tr>
    <tr>
      <th>4</th>
      <td>Women's Athletic Footwear</td>
      <td>75500</td>
      <td>37615000.0</td>
    </tr>
    <tr>
      <th>5</th>
      <td>Men's Apparel</td>
      <td>70950</td>
      <td>40957500.0</td>
    </tr>
  </tbody>
</table>
</div>

                     Product  Units Sold  Total Sales
0      Men's Street Footwear      120225   59786500.0
1    Men's Athletic Footwear      100150   52045000.0
2            Women's Apparel       95900   57406250.0
3    Women's Street Footwear       90900   44861000.0
4  Women's Athletic Footwear       75500   37615000.0
5              Men's Apparel       70950   40957500.0

Vizly: AI-powered data analysis

Analysis of Adidas US Sales Data: Top-Selling Products

What are the top-selling products?

Can you show a visual representation of the top-selling products?

Can you analyze the operating profit for each product?