Airplanes have always been the most favored choice in traveling abroad due to their safety and speed. However, the COVID-19 pandemic that's been going on for the last two years has caused a break in ticket sales for almost all airlines, making the airline business sector suffer heavy losses.
With the pandemic starting to fade, the number of passengers has recovered substantially, and living standards have also improved. As the living standards went up, airline companies should also improve their services. This translates to a need for a decision-supporting system capable of analyzing passenger satisfaction.
This project uses data from airline passenger satisfaction survey to predict whether a passenger is satisfied with their flight. We divided the model design process into 2 phases: Data Analysis and Modelling.
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Create a virtual environment by typing
python -m venv envin the command prompt -
Use the Python interpreter from the virtual environment using ctrl+shift+p and selecting Python Interpreter
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Wait until the workspace's python interpreter changes into that of the venv
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Move to the Python (env) terminal install all requirements by typing
pip install -r requirements.txt -
Run the web application by typing
streamlit run main.py
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