Examples¶

Practical examples in Jupyter Notebooks to learn DataFrameIt.

Available Notebooks¶

Examples are organized from basic to advanced. We recommend following in order.

1. Basic¶

Introduction to DataFrameIt with sentiment analysis.

Create simple Pydantic model
Process basic DataFrame
Understand the output

from pydantic import BaseModel
from typing import Literal

class Sentiment(BaseModel):
    sentiment: Literal['positive', 'negative', 'neutral']

2. Error Handling¶

02_error_handling.ipynb

How to handle errors and configure retry.

Configure max_retries, base_delay, max_delay
Check _dataframeit_status column
Analyze _error_details

3. Incremental Processing¶

03_resume.ipynb

Continue processing from where it stopped.

Use resume=True
Save and load partial results
Reprocess only error rows

4. Custom Placeholder¶

04_custom_placeholder.ipynb

Control where text appears in the prompt.

Use {texto} in template
Create complex multi-part prompts

5. Advanced Case: Legal Analysis¶

05_advanced_legal.ipynb

Real example with complex Pydantic model.

Nested models
Optional fields
Lists of objects
Multiple entity extraction

class Party(BaseModel):
    name: str
    type: Literal['plaintiff', 'defendant']

class Decision(BaseModel):
    parties: List[Party]
    outcome: Literal['granted', 'denied']

6. Polars¶

06_polars.ipynb

Use DataFrameIt with Polars instead of Pandas.

Input with polars.DataFrame
Output preserves Polars type

7. Multiple Data Types¶

07_multiple_data_types.ipynb

Process different input types.

Lists
Dictionaries
Series

8. Rate Limiting¶

08_rate_limiting.ipynb

Control request rate.

Configure rate_limit_delay
Use parallel_requests
Combine for maximum efficiency

Running the Examples¶

1. Clone the Repository¶

git clone https://github.com/bdcdo/dataframeit.git
cd dataframeit

2. Install Dependencies¶

pip install dataframeit[google]
pip install jupyter

3. Configure your API Key¶

export GOOGLE_API_KEY="your-key"

4. Run Jupyter¶

jupyter notebook example/

Contributing Examples¶

If you created an interesting example, consider contributing! Open an issue or pull request on GitHub.