This repository contains code and resources for performing data analysis using PySpark, Pandas, Python, and Databricks. The project aims to explore, analyze, and gain insights from various datasets using different data processing and analysis frameworks.
- Clone the repository:
https://github.com/Pratikdomadiya/Databricks_workspace-
Install the required dependencies.
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Obtain the datasets and place them in proper directory. Ensure that the data is properly formatted and structured for analysis.
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Open the Databricks workspace and create a new notebook.
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Import the relevant notebook(s) from the git directory into the Databricks workspace.
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Run the notebooks in the recommended order to perform data exploration, preprocessing, analysis, and visualization using PySpark, Pandas, and Python.
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Modify and customize the code as per your specific dataset and analysis requirements.
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Document your findings, insights, and recommendations within the notebooks.
Contributions to this data analysis project are welcome. If you encounter any issues or have suggestions for improvement, feel free to open an issue or submit a pull request.
Please adhere to the existing code style and structure, and provide clear and concise commit messages for better collaboration.
Feel free to use the code and resources for your own analysis or modify them to suit your needs.
This project was made possible by the open-source community, PySpark, Pandas, Python, and Databricks. I extend my gratitude to the developers of these frameworks for their invaluable contributions.
For any questions or inquiries about this data analysis project, please contact pratikdomadiya123@gmail.com. I would be happy to assist you!
Happy analyzing!