Build a Streamlit web app diagnostic tool for ARIMA time series analysis
The repository contains working code for preparing time series data, building an ARIMA model, and deploying to a Streamlit app locally. Instructions are below.
A demo deployed to Heroku is available for viewing at the following address (it may take a few seconds to load for the Heroku dyno to spin up): http://autots-dash.herokuapp.com/
The demo data is the often used AirPassengers.csv dataset; it contains monthly passenger totals from 1949 to 1960.
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Run the following command to run the web app.
streamlit run app.py -
Go to http://127.0.0.1:8501/
This project utilizes default packages within the Anaconda distribution of Python. Streamlit and pmdarima were additionally installed.
After creating a virtual environment (recommended), you can install the dependencies with the following command:
pip install -r requirements.txt