Project Description

In real-world data science, it's extremely rare to have an ideal data set to begin with. Instead data often has to be aggregated from disparate sources and a good amount of data cleaning has to be done before we can do any analysis and modeling work. In this project, we'll go through the first part of a complete data science project which begins with the acquisition of raw data. The primary focus in this project will be on data acquisition, preparation, cleaning, and aggregation followed by exploratory data analyis. We will combine several messy data sets into a single clean one before commencing analysis. For the purposes of this project, we'll be using data about New York City public schools.