RiverAnalyserPRO is a sophisticated data management system tailored for river catchment surveys and campaigns. Developed in Python, it facilitates the management and analysis of measurement data, supporting a range of functionalities to enhance data understanding and decision-making in hydrological research.
RiverAnalyserPRO offers an array of powerful features:
- Statistical Analysis: Perform basic statistical analyses to extract meaningful insights from your data.
- Multiple Format Support: Seamlessly work with measurement data in Comma-Separated Value (CSV), XML, and JSON formats.
- Data Visualization: Generate intuitive plots to visualize measurement data.
- Extensible Architecture: Leverage its Model-View-Controller architecture to easily extend analytical functions and views.
Before installing RiverAnalyserPRO, ensure you have the following Python packages installed:
- NumPy - makes use of NumPy's statistical functions
- Pandas - makes use of Panda's dataframes
- GeoPandas - makes use of GeoPanda's spatial operations
- Matplotlib - uses Matplotlib to generate statistical plots
The following optional packages are required to run RiverCatch's unit tests:
- pytest - RiverCatch's unit tests are written using pytest
- pytest-cov - Adds test coverage stats to unit testing
- Clone the Repository: First, clone the RiverAnalyserPRO repository to your local machine using Git.
git clone https://github.com/PriyaGordon/python-intermediate-rivercatchment/ RiverAnalyserPro
cd RiverAnalyserPRO- Set up a Virtual Environment: It's recommended to create a Python virtual environment for project dependencies.
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
- Install Dependencies: RiverAnalyserPRO utilizes Poetry for dependency management. Install all required packages using the following command:
poetry install
- Verify Installation: Ensure that all dependencies are correctly installed.
poetry check
- Running the Application: You can now run RiverAnalyserPRO using the following command:
python catchment-analysis.py path/to/your/input/file.csv --full-data-analysis
- Use Optional Flags: You can use the optional -m or --measurements flag to specify the name of the measurement data series to load:
python catchment-analysis.py path/to/your/input/file.csv --full-data-analysis -m variable