This project focuses on analyzing Uber trip data using Python. The dataset is processed and transformed into a structured format suitable for analysis and visualization.

The data pipeline involves several steps:

1. Data loading from an external API.
2. Transformation of raw data into structured formats.
3. Exporting the transformed data to a BigQuery warehouse.

• Uber Data Pipeline.ipynb: Jupyter Notebook containing the code for data processing and transformation.
• extract.py: Python script for loading data from an API.
• load.py: Python script for exporting data to BigQuery.
• transform.py: Python script for transforming raw data into structured formats.

To replicate the analysis:

1. Clone the repository.
2. Run the Jupyter Notebook Uber Data Pipeline.ipynb.
3. Ensure required Python packages are installed.

• Python
• Pandas
• Requests
• BigQuery