How to create a pandas table

import pandas as pd
# Create a sample DataFrame
data = {
    'Name': ['Anna', 'Ben', 'Charlie', 'Diana'],
    'Age': [23, 30, 35, 29],
    'Occupation': ['Engineer', 'Teacher', 'Doctor', 'Designer']
}
df = pd.DataFrame(data)
# Display the DataFrame as a table
print(df)Here, the pandas DataFrame is displayed as a simple table in the console. The output looks like this:

Name  Age    Occupation

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If you’re using **[Jupyter Notebook](t3://page?uid=2063)**, you don’t even need to use the `print()function. **Simply calling** the DataFrame will result in it being displayed in a tabular format.
</box-hinweis>
### `to_string()— DataFrames in full
The built-in pandas function `DataFrame.to_string()converts a **DataFrame into a [Python string](t3://page?uid=3826)**, ensuring that the DataFrame is shown in its entirety, no matter how large it is. Let’s take a look at how this option works using the example from above:
```python
# Show the entire DataFrame as a table
print(df.to_string())Here’s what the output looks like:

Name    Age    	Occupation

### `style` — Styling capabilities
With the `style` property, pandas also offers a built-in way to highlight and format DataFrames. In the following example, we’re going to highlight the maximum values of the dataset from above:
```python
# Display the DataFrame with the maximum values highlighted
df.style.highlight_max(axis=0)In a Jupyter Notebook, the DataFrame will be shown with the maximum values highlighted.
### `to_html()— Best for web frameworks
With `DataFrame.to_html(), you can represent your DataFrame as an [HTML table](t3://page?uid=36868) with just one function call. This makes it easy to directly embed DataFrames in web applications. All you need to do is call the function on the DataFrame:
```python
# Display the DataFrame as an HTML table
html_table = df.to_html()
print(html_table)You’ll then receive HTML code that you can embed in websites:
```html
<table border="1" class="dataframe">
    <thead>
        <tr style="text-align: right;">
            <th></th>
            <th>Name</th>
            <th>Age</th>
            <th>Occupation</th>
        </tr>
    </thead>
    <tbody>
        <tr>
            <th>0</th>
            <td>Anna</td>
            <td>23</td>
            <td>Engineer</td>
        </tr>
        <tr>
            <th>1</th>
            <td>Ben</td>
            <td>30</td>
            <td>Teacher</td>
        </tr>
        <tr>
            <th>2</th>
            <td>Charlie</td>
            <td>35</td>
            <td>Doctor</td>
        </tr>
        <tr>
            <th>3</th>
            <td>Diana</td>
            <td>29</td>
            <td>Designer</td>
        </tr>
    </tbody>
</table>

from tabulate import tabulate
# Display the DataFrame as a table in GitHub Markdown format
print(tabulate(df, headers='keys', tablefmt='github))Here’s the output: