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

    .dataframe tbody tr th {
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    }

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    }
</style>
<table border="1" class="dataframe">
  <thead>
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      <th></th>
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  </tbody>
</table>
</div>

<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>Column1</th>
      <th>Column2</th>
      <th>PRODUCT SOLD</th>
      <th>NET SALE</th>
      <th>AD COST</th>
      <th>COST PER SALE</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>WINTER</td>
      <td>2023</td>
      <td>70.000000</td>
      <td>11554.000000</td>
      <td>3025.000000</td>
      <td>43.214286</td>
    </tr>
    <tr>
      <th>1</th>
      <td>NaN</td>
      <td>2022</td>
      <td>27.000000</td>
      <td>5134.000000</td>
      <td>971.000000</td>
      <td>35.962963</td>
    </tr>
    <tr>
      <th>2</th>
      <td>NaN</td>
      <td>میزان رشد</td>
      <td>2.592593</td>
      <td>2.250487</td>
      <td>3.115345</td>
      <td>1.201633</td>
    </tr>
    <tr>
      <th>3</th>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>4</th>
      <td>SPRING</td>
      <td>2023</td>
      <td>55.000000</td>
      <td>9553.000000</td>
      <td>3090.000000</td>
      <td>56.181818</td>
    </tr>
  </tbody>
</table>
</div>

  Column1    Column2  PRODUCT SOLD      NET SALE      AD COST  COST PER SALE
0  WINTER       2023     70.000000  11554.000000  3025.000000      43.214286
1     NaN       2022     27.000000   5134.000000   971.000000      35.962963
2     NaN  میزان رشد      2.592593      2.250487     3.115345       1.201633
3     NaN        NaN           NaN           NaN          NaN            NaN
4  SPRING       2023     55.000000   9553.000000  3090.000000      56.181818

<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
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        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Year</th>
      <th>Average Cost Per Sale</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2023</td>
      <td>43.93577</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Column1</td>
      <td>NaN</td>
    </tr>
  </tbody>
</table>
</div>

      Year  Average Cost Per Sale
0     2023               43.93577
1  Column1                    NaN

Analyzing an Empty Excel File

What insights can we derive from this data?

Can you load a specific sheet from the Excel file?

2

Can you visualize the trends in PRODUCT SOLD over the years?

Can you calculate the average COST PER SALE for each year?

Column1	Column2	PRODUCT SOLD	NET SALE	AD COST	COST PER SALE
WINTER	2023	70.0	11554.0	3025.0	43.214286
NaN	2022	27.0	5134.0	971.0	35.962963
NaN	میزان رشد	2.592593	2.250487	3.115345	1.201633
NaN	NaN	NaN	NaN	NaN	NaN
SPRING	2023	55.0	9553.0	3090.0	56.181818