This project focuses on the data slicing of a main file, primarily aimed at analyzing single events within a dataset. It is designed to guide users through the initial setup and subsequent analysis of specific events, with a keen emphasis on speed calculations and their implications on data visualization.
- CZĘŚĆ CIĘCIA GŁÓWNEGO PLIKU - PIERWSZE ODPALENIE: Start by slicing the main file. This step is crucial for preparing your dataset for detailed analysis. Follow the instructions within the notebook to correctly slice your main data file.
- Event-Specific Analysis: After the initial setup, the project shifts focus to the analysis of specific events. This involves changing parameters within the notebook to target individual events (from event_1 to event_5). It's important to note that the analysis is tailored to single impact events, and the correct file naming is critical for accurate speed calculation and visualization.
- Ensure you have Jupyter Notebook or JupyterLab installed to run the
.ipynbfile. - Familiarity with Python and basic data analysis libraries (e.g., pandas, matplotlib) is recommended.
To use this project, open the data slicing (1).ipynb notebook in Jupyter and follow the step-by-step instructions. The notebook is structured to guide you through the process, from initial data slicing to in-depth analysis of specific events.
Contributions to this project are welcome. Please feel free to fork the repository, make your changes, and submit a pull request.
This project is open-sourced under the MIT License. See the LICENSE file for more details.