This project was created during a short hackathon to try out Snowflake. It uses a public Kaggle dataset, Snowflake as the cloud data warehouse, and Streamlit for interactive data visualization.
The dataset was lightly cleaned and loaded into Snowflake tables. The Streamlit app queries Snowflake directly and provides basic filtering, charts, and simple anomaly detection.
Source: Kaggle - Natural Gas Usage
Description: 10 years of natural gas consumption in the United States.
To use this project, you will need your own Snowflake account and credentials.
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Download the dataset from Kaggle
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Load and clean the data in Snowflake
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Create the required database, schema, and tables
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Update the Snowflake connection details in the Streamlit app (Python code)
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Run the Streamlit app locally:
streamlit run app.py
Running this app requires the following Python packages:
- streamlit
- pandas
- plotly
- snowflake-connector-python