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SQL for Data Analytics

You're reading from   SQL for Data Analytics Harness the power of SQL to extract insights from data

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Product type Paperback
Published in Aug 2022
Publisher Packt
ISBN-13 9781801812870
Length 540 pages
Edition 3rd Edition
Languages
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Authors (4):
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Benjamin Johnston Benjamin Johnston
Author Profile Icon Benjamin Johnston
Benjamin Johnston
Matt Goldwasser Matt Goldwasser
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Matt Goldwasser
Jun Shan Jun Shan
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Jun Shan
Upom Malik Upom Malik
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Upom Malik
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Toc

Table of Contents (11) Chapters Close

Preface 1. Understanding and Describing Data 2. The Basics of SQL for Analytics FREE CHAPTER 3. SQL for Data Preparation 4. Aggregate Functions for Data Analysis 5. Window Functions for Data Analysis 6. Importing and Exporting Data 7. Analytics Using Complex Data Types 8. Performant SQL 9. Using SQL to Uncover the Truth: A Case Study Appendix

6. Importing and Exporting Data

Overview

In this chapter, you will learn techniques that will help you move data between your database and analytics tools. You will start by learning about the psql tool, which will enable you to quickly query data from a database. With psql, you can also leverage the COPY command, which allows the efficient importing and exporting of data. With these simple tools, you will be able to interact with the database and efficiently move data back and forth. Further, you will process and analyze data using Python. You will also explore Python libraries such as SQLAlchemy and pandas' advanced functionality for interacting with your database in Python.

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