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# Pandas FutureWarning: Passing literal html to 'read_html' is deprecated and will be removed in a future version
- URL: https://datascientyst.com/pandas-futurewarning-passing-literal-html-to-read_html-is-deprecated-and-will-be-removed-in-a-future-version/
- Published: 2025-07-24T19:40:08.000Z
- Updated: 2025-07-24T19:40:08.000Z
- Author: John D K
- Tags: Pandas Error

If you're seeing the warning:

`FutureWarning: Passing literal html to 'read_html' is deprecated and will be removed in a future version`

this means you're using pandas' `read_html()` function in a way that will soon be unsupported.

## Why the Change?

The pandas development team is deprecating the direct passing of HTML strings to `read_html()`. This change promotes better practices and prepares for future improvements to the function.

## How to Fix It

Instead of:

```python
pd.read_html("<table>...</table>")

```

which will raise warning and in future error:

`FutureWarning: Passing literal html to 'read_html' is deprecated and will be removed in a future version`

You should now use:

```python
from io import StringIO
pd.read_html(StringIO("<table>...</table>"))

```

Or for HTML files:

```python
pd.read_html("path/to/file.html")  # This is still valid

```

## Use StringIO for HTML strings

```python
import pandas as pd
from io import StringIO

html_data = """
<table>
    <tr><th>name</th><th>age</th></tr>
    <tr><td>Alice</td><td>25</td></tr>
    <tr><td>Bob</td><td>30</td></tr>
</table>
"""

df = pd.read_html(StringIO(html_data))[0]
print(df)

```

result:

```
    name  age
0  Alice   25
1    Bob   30

```

## Use requests for web content

```python
import requests
import pandas as pd

response = requests.get('https://example.com/data.html')
df = pd.read_html(StringIO(response.text))

```

## Why This Matters

Making this change now will:

1. Future-proof your code
2. Remove annoying warning messages
3. Ensure compatibility with upcoming pandas versions

**Security concerns** top the list, as accepting arbitrary HTML strings can potentially expose applications to security vulnerabilities. By requiring explicit file paths or URLs, pandas encourages safer data handling practices.

**API clarity** is another driving factor. Having a single function that accepts multiple input types can lead to confusion about expected behavior and error handling. Separating these concerns makes the API more predictable and easier to maintain.