Please open this project in Colab for the best experience. It is a large file, so if the .ipynb file doesn't load on the first try, reload it. This project seeks to understand the real estate landscape of Seattle washington. I utilize descriptive and predictive analytics to create a linear regression that can be used to estimate the price of a home in Seattle based on key characteristics. I also utilize geomapping for visual understanding.
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Analysis using Python on Seattle housing prices. Includes geomapping, descriptive, and predictive analytics. Written in Python, uses Pandas and other libraries for dataframe creation/manipulation.
tytinkdev/real_estate_study
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Analysis using Python on Seattle housing prices. Includes geomapping, descriptive, and predictive analytics. Written in Python, uses Pandas and other libraries for dataframe creation/manipulation.
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