Advanced Data Analytics Using Python_ With Machine Learning, Deep Learning and NLP Examples ( 2023)

CHAPTER 2
ETL with Python
(Structured Data)
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.
MySQL
MySQLdb is an API in Python developed at the top of the MySQL C interface.
How to Install MySQLdb?
First you need to install the Python MySQLdb module on your machine.
Then run the following script:
#!/usr/bin/python
import MySQLdb
© Sayan Mukhopadhyay 2018
S. Mukhopadhyay, Advanced Data Analytics Using Python,
https://doi.org/10.1007/978-1-4842-3450-1_2
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