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