⁠

Finding data is one thing. Getting it ready for analysis is another. Acquiring, cleaning, standardizing and importing publicly available data is time consuming because many datasets lack machine readable metadata and do not conform to established data structures and formats. The Data Retriever automates the first steps in the data analysis pipeline by downloading, cleaning, and standardizing datasets, and importing them into relational databases, flat files, or programming languages. The automation of this process reduces the time for a user to get most large datasets up and running by hours, and in some cases days.

• Project source code⁠
• Contributing guidelines⁠
• Project website⁠
• Organization website⁠