Reading Data from Different Sources

One of the most valued and widely used skills of a data wrangling professional is the ability to extract and read data from a diverse array of sources into a structured format. Modern analytics pipelines depend on the ability and skills of those professionals to build a robust system that can scan and absorb a variety of data sources to build and analyze a pattern-rich model. Such kinds of feature-rich, multi-dimensional models will have high predictive and generalization accuracy. They will be valued by stakeholders and end users alike in any data-driven product. In the first part of this chapter, we will go through various data sources and how they can be imported into pandas DataFrames, thus imbuing data wrangling professionals with extremely valuable data ingestion knowledge.

Data Files Provided with This Chapter

As this topic is about reading from various data sources, we will use small files of various types in the following exercises...