ETL with Python
Sayan Mukhopadhyay, Pratip Samanta · Apress eBooks · 2022
Every data science professional has to extract, transform, and load (ETL) data from different data sources. In this chapter, we will discuss how to do ETL with Python for a selection of popular databases. For a relational database, we’ll cover MySQL. As an example of a document database, we will cover Elasticsearch. For a graph database, we’ll cover Neo4j, and for NoSQL, we’ll cover MongoDB. We will also discuss the Pandas framework, which was inspired by R’s data frame concept.