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Beschreibung
A beginner's guide to simplifying Extract, Transform, Load (ETL) processes with the help of hands-on tips, tricks, and best practices, in a fun and interactive way
Key Features
Explore data wrangling with the help of real-world examples and business use cases
Study various ways to extract the most value from your data in minimal time
Boost your knowledge with bonus topics, such as random data generation and data integrity checks
Book Description
While a huge amount of data is readily available to us, it is not useful in its raw form. For data to be meaningful, it must be curated and refined.
If you're a beginner, then The Data Wrangling Workshop will help to break down the process for you. You'll start with the basics and build your knowledge, progressing from the core aspects behind data wrangling, to using the most popular tools and techniques.
This book starts by showing you how to work with data structures using Python. Through examples and activities, you'll understand why you should stay away from traditional methods of data cleaning used in other languages and take advantage of the specialized pre-built routines in Python. Later, you'll learn how to use the same Python backend to extract and transform data from an array of sources, including the internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, the book teaches you how to handle missing or incorrect data, and reformat it based on the requirements from your downstream analytics tool.
By the end of this book, you will have developed a solid understanding of how to perform data wrangling with Python, and learned several techniques and best practices to extract, clean, transform, and format your data efficiently, from a diverse array of sources.
What you will learn
Get to grips with the fundamentals of data wrangling
Understand how to model data with random data generation and data integrity checks
Discover how to examine data with descriptive statistics and plotting techniques
Explore how to search and retrieve information with regular expressions
Delve into commonly-used Python data science libraries
Become well-versed with how to handle and compensate for missing data
Who this book is for
The Data Wrangling Workshop is designed for developers, data analysts, and business analysts who are looking to pursue a career as a full-fledged data scientist or analytics expert. Although this book is for beginners who want to start data wrangling, prior working knowledge of the Python programming language is necessary to easily grasp the concepts covered here. It will also help to have a rudimentary knowledge of relational databases and SQL.
Key Features
Explore data wrangling with the help of real-world examples and business use cases
Study various ways to extract the most value from your data in minimal time
Boost your knowledge with bonus topics, such as random data generation and data integrity checks
Book Description
While a huge amount of data is readily available to us, it is not useful in its raw form. For data to be meaningful, it must be curated and refined.
If you're a beginner, then The Data Wrangling Workshop will help to break down the process for you. You'll start with the basics and build your knowledge, progressing from the core aspects behind data wrangling, to using the most popular tools and techniques.
This book starts by showing you how to work with data structures using Python. Through examples and activities, you'll understand why you should stay away from traditional methods of data cleaning used in other languages and take advantage of the specialized pre-built routines in Python. Later, you'll learn how to use the same Python backend to extract and transform data from an array of sources, including the internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, the book teaches you how to handle missing or incorrect data, and reformat it based on the requirements from your downstream analytics tool.
By the end of this book, you will have developed a solid understanding of how to perform data wrangling with Python, and learned several techniques and best practices to extract, clean, transform, and format your data efficiently, from a diverse array of sources.
What you will learn
Get to grips with the fundamentals of data wrangling
Understand how to model data with random data generation and data integrity checks
Discover how to examine data with descriptive statistics and plotting techniques
Explore how to search and retrieve information with regular expressions
Delve into commonly-used Python data science libraries
Become well-versed with how to handle and compensate for missing data
Who this book is for
The Data Wrangling Workshop is designed for developers, data analysts, and business analysts who are looking to pursue a career as a full-fledged data scientist or analytics expert. Although this book is for beginners who want to start data wrangling, prior working knowledge of the Python programming language is necessary to easily grasp the concepts covered here. It will also help to have a rudimentary knowledge of relational databases and SQL.
A beginner's guide to simplifying Extract, Transform, Load (ETL) processes with the help of hands-on tips, tricks, and best practices, in a fun and interactive way
Key Features
Explore data wrangling with the help of real-world examples and business use cases
Study various ways to extract the most value from your data in minimal time
Boost your knowledge with bonus topics, such as random data generation and data integrity checks
Book Description
While a huge amount of data is readily available to us, it is not useful in its raw form. For data to be meaningful, it must be curated and refined.
If you're a beginner, then The Data Wrangling Workshop will help to break down the process for you. You'll start with the basics and build your knowledge, progressing from the core aspects behind data wrangling, to using the most popular tools and techniques.
This book starts by showing you how to work with data structures using Python. Through examples and activities, you'll understand why you should stay away from traditional methods of data cleaning used in other languages and take advantage of the specialized pre-built routines in Python. Later, you'll learn how to use the same Python backend to extract and transform data from an array of sources, including the internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, the book teaches you how to handle missing or incorrect data, and reformat it based on the requirements from your downstream analytics tool.
By the end of this book, you will have developed a solid understanding of how to perform data wrangling with Python, and learned several techniques and best practices to extract, clean, transform, and format your data efficiently, from a diverse array of sources.
What you will learn
Get to grips with the fundamentals of data wrangling
Understand how to model data with random data generation and data integrity checks
Discover how to examine data with descriptive statistics and plotting techniques
Explore how to search and retrieve information with regular expressions
Delve into commonly-used Python data science libraries
Become well-versed with how to handle and compensate for missing data
Who this book is for
The Data Wrangling Workshop is designed for developers, data analysts, and business analysts who are looking to pursue a career as a full-fledged data scientist or analytics expert. Although this book is for beginners who want to start data wrangling, prior working knowledge of the Python programming language is necessary to easily grasp the concepts covered here. It will also help to have a rudimentary knowledge of relational databases and SQL.
Key Features
Explore data wrangling with the help of real-world examples and business use cases
Study various ways to extract the most value from your data in minimal time
Boost your knowledge with bonus topics, such as random data generation and data integrity checks
Book Description
While a huge amount of data is readily available to us, it is not useful in its raw form. For data to be meaningful, it must be curated and refined.
If you're a beginner, then The Data Wrangling Workshop will help to break down the process for you. You'll start with the basics and build your knowledge, progressing from the core aspects behind data wrangling, to using the most popular tools and techniques.
This book starts by showing you how to work with data structures using Python. Through examples and activities, you'll understand why you should stay away from traditional methods of data cleaning used in other languages and take advantage of the specialized pre-built routines in Python. Later, you'll learn how to use the same Python backend to extract and transform data from an array of sources, including the internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, the book teaches you how to handle missing or incorrect data, and reformat it based on the requirements from your downstream analytics tool.
By the end of this book, you will have developed a solid understanding of how to perform data wrangling with Python, and learned several techniques and best practices to extract, clean, transform, and format your data efficiently, from a diverse array of sources.
What you will learn
Get to grips with the fundamentals of data wrangling
Understand how to model data with random data generation and data integrity checks
Discover how to examine data with descriptive statistics and plotting techniques
Explore how to search and retrieve information with regular expressions
Delve into commonly-used Python data science libraries
Become well-versed with how to handle and compensate for missing data
Who this book is for
The Data Wrangling Workshop is designed for developers, data analysts, and business analysts who are looking to pursue a career as a full-fledged data scientist or analytics expert. Although this book is for beginners who want to start data wrangling, prior working knowledge of the Python programming language is necessary to easily grasp the concepts covered here. It will also help to have a rudimentary knowledge of relational databases and SQL.
Über den Autor
Brian Lipp is a technology polygot who is always in search of interesting and innovative technology. His current languages of choice are Python, Go, and Scala.
Details
Erscheinungsjahr: | 2020 |
---|---|
Fachbereich: | Programmiersprachen |
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
ISBN-13: | 9781839215001 |
ISBN-10: | 1839215003 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Sarkar, Tirthajyoti |
Hersteller: | Packt Publishing |
Maße: | 235 x 191 x 31 mm |
Von/Mit: | Tirthajyoti Sarkar |
Erscheinungsdatum: | 28.07.2020 |
Gewicht: | 1,061 kg |
Über den Autor
Brian Lipp is a technology polygot who is always in search of interesting and innovative technology. His current languages of choice are Python, Go, and Scala.
Details
Erscheinungsjahr: | 2020 |
---|---|
Fachbereich: | Programmiersprachen |
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
ISBN-13: | 9781839215001 |
ISBN-10: | 1839215003 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Sarkar, Tirthajyoti |
Hersteller: | Packt Publishing |
Maße: | 235 x 191 x 31 mm |
Von/Mit: | Tirthajyoti Sarkar |
Erscheinungsdatum: | 28.07.2020 |
Gewicht: | 1,061 kg |
Warnhinweis