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Data Wrangling with Python

You're reading from   Data Wrangling with Python Creating actionable data from raw sources

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789800111
Length 452 pages
Edition 1st Edition
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Authors (2):
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Shubhadeep Roychowdhury Shubhadeep Roychowdhury
Author Profile Icon Shubhadeep Roychowdhury
Shubhadeep Roychowdhury
Dr. Tirthajyoti Sarkar Dr. Tirthajyoti Sarkar
Author Profile Icon Dr. Tirthajyoti Sarkar
Dr. Tirthajyoti Sarkar
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Table of Contents (12) Chapters Close

Data Wrangling with Python
Preface
1. Introduction to Data Wrangling with Python FREE CHAPTER 2. Advanced Data Structures and File Handling 3. Introduction to NumPy, Pandas, and Matplotlib 4. A Deep Dive into Data Wrangling with Python 5. Getting Comfortable with Different Kinds of Data Sources 6. Learning the Hidden Secrets of Data Wrangling 7. Advanced Web Scraping and Data Gathering 8. RDBMS and SQL 9. Application of Data Wrangling in Real Life Appendix

Refresher of RDBMS and SQL


An RDBMS is a piece of software that manages data (represented for the end user in a tabular form) on physical hard disks and is built using the Codd's relational model. Most of the databases that we encounter today are RDBMS. In recent years, there has been a huge industry shift toward a newer kind of database management system, called NoSQL (MongoDB, CouchDB, Riak, and so on). These systems, although in some aspects they follow some of the rules of RDBMS, in most cases reject or modify them.

How is an RDBMS Structured?

The RDBMS structure consists of three main elements, namely the storage engine, query engine, and log management. Here is a diagram that shows the structure of a RDBMS:

Figure 8.2 RDBMS structure

The following are the main concepts of any RDBMS structure:

  • Storage engine: This is the part of the RDBMS that is responsible for storing the data in an efficient way and also to give it back when asked for, in an efficient way. As an end user of the RDBMS...

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