© Sayan Mukhopadhyay 2018
Sayan MukhopadhyayAdvanced Data Analytics Using Pythonhttps://doi.org/10.1007/978-1-4842-3450-1_2

2. ETL with Python (Structured Data)

Sayan Mukhopadhyay1 
Kolkata, West Bengal, India

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.


MySQLdb is an API in Python developed at the top of the MySQL ...

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