This is a Capstone 1 Project, where the focus was to get a basic understanding of the macro factors affecting agricultural production. Here we aimed to predict crop production, given the year, location and external factors, using data science techniques. The project followed the following steps;

• Data Wrangling: Collected Data from various sources USDA, BLS and NOAA websites for related information. In some cases build a web scrapper to extract data that was labor intensive.
• Exploratory Analysis: Answer few initial general questions about the data and the agricultural practice/results. To gain better understanding of the data and the subject.
• Machine Learning: To predict the production values for crops at county-level. Applying preprocessing like feature selection, Category encoding and normalization.

For further details please refer to the code in the Scripts folder, that Jupyter Notebook for easy viewing. All the related documentation is available on Google docs, with the links to each of them in the documents folder. All of the data used is also uploaded here.

Installation

A brew installation of GDAL is required before installating geopandas dependency.

brew install gdal

For MacOS big-sur if you come accross below error while install GDAL or geopandas, clang: error: invalid version number in 'MACOSX_DEPLOYMENT_TARGET=11.0' follow the below steps mentioned, reference here

1. Run the below command to if any software update fixes it.

   >>> softwareupdate --all --install --force
   Software Update Tool
   
   Finding available software
   No updates are available.

2. If the above doesn't fix it, try uninstalling and re-installing xcode-select as,

   sudo rm -rf /Library/Developer/CommandLineTools
   sudo xcode-select --install