neli12/time-series-productivity-sp
Mapping sugarcane productivity in São Paulo. Project for the MBA in Data Science and Analytics.
This project helps agricultural analysts or researchers understand and predict sugarcane yield in São Paulo, Brazil. It processes publicly available historical data on sugarcane yield, planted area, weather, and remote sensing to reveal trends and predict future productivity. You would use this to gain insights into regional sugarcane output without needing to gather and process complex datasets yourself.
No commits in the last 6 months.
Use this if you need to analyze historical sugarcane productivity in São Paulo or generate predictions for future yields, leveraging diverse environmental data.
Not ideal if your focus is on real-time, very short-term, or highly localized (e.g., specific farm-level) sugarcane yield predictions, as it aggregates data annually at the municipality level.
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Language
Jupyter Notebook
License
GPL-3.0
Category
Last pushed
Nov 22, 2022
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