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Data
By Abha Belorkar, Sharath Chandra Guntuku and 2 more
zł129.99
BookOct 2019362 pages1st Edition
eBook
zł129.99
zł161.99
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Key benefits
- Study and use Python interactive libraries, such as Bokeh and Plotly
- Explore different visualization principles and understand when to use which one
- Create interactive data visualizations with real-world data
Book description
With so much data being continuously generated, developers, who can present data as impactful and interesting visualizations, are always in demand. Interactive Data Visualization with Python sharpens your data exploration skills, tells you everything there is to know about interactive data visualization in Python.You'll begin by learning how to draw various plots with Matplotlib and Seaborn, the non-interactive data visualization libraries. You'll study different types of visualizations, compare them, and find out how to select a particular type of visualization to suit your requirements. After you get a hang of the various non-interactive visualization libraries, you'll learn the principles of intuitive and persuasive data visualization, and use Bokeh and Plotly to transform your visuals into strong stories. You'll also gain insight into how interactive data and model visualization can optimize the performance of a regression model.By the end of the course, you'll have a new skill set that'll make you the go-to person for transforming data visualizations into engaging and interesting stories.
Who is this book for?
This book intends to provide a solid training ground for Python developers, data analysts and data scientists to enable them to present critical data insights in a way that best captures the user's attention and imagination. It serves as a simple step-by-step guide that demonstrates the different types and components of visualization, the principles, and techniques of effective interactivity, as well as common pitfalls to avoid when creating interactive data visualizations. Students should have an intermediate level of competency in writing Python code, as well as some familiarity with using libraries such as pandas.
What you will learn
Explore and apply different static and interactive data visualization techniquesMake effective use of plot types and features from the Matplotlib, Seaborn, Altair, Bokeh, and Plotly librariesMaster the art of selecting appropriate plotting parameters and styles to create attractive plotsChoose meaningful and informative ways to present your stories through dataCustomize data visualization for specific scenarios, contexts, and audiencesAvoid common errors and slip-ups in visualizing data
What do you get with eBook?
Instant access to your Digital eBook purchase
Download this book in EPUB and PDF formats
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Product Details
Publication date :
Oct 24, 2019
Length :
362 pages
Edition :
1st Edition
Language :
English
ISBN-13 :
9781838648350
Category :
Data
Languages :
Python (Intermediate)
Concepts :
Data Visualization
Tools :
Matplotlib (Beginner),Pandas (Beginner)
Product Details
Publication date :
Oct 24, 2019
Length :
362 pages
Edition :
1st Edition
Language :
English
ISBN-13 :
9781838648350
Category :
Data
Languages :
Python (Intermediate)
Concepts :
Data Visualization
Tools :
Matplotlib (Beginner),Pandas (Beginner)
What do you get with eBook?
Instant access to your Digital eBook purchase
Download this book in EPUB and PDF formats
AI Assistant (beta) to help accelerate your development
Access this title in our online reader with advanced features
DRM FREE - Read whenever, wherever and however you want
Product Details
Publication date :
Oct 24, 2019
Length :
362 pages
Edition :
1st Edition
Language :
English
ISBN-13 :
9781838648350
Category :
Data
Languages :
Python (Intermediate)
Concepts :
Data Visualization
Tools :
Matplotlib (Beginner),Pandas (Beginner)
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Authors (4)
(1-1 of 4)
Abha Belorkar is an educator and researcher in computer science. She received her bachelor's degree in computer science from Birla Institute of Technology and Science Pilani, India and her Ph.D. from the National University of Singapore. Her current research work involves the development of methods powered by statistics, machine learning, and data visualization techniques to derive insights from heterogeneous genomics data on neurodegenerative diseases.
See other products by Abha Belorkar
Sharath Chandra Guntuku is a researcher in natural language processing and multimedia computing. He received his bachelor's degree in computer science from Birla Institute of Technology and Science, Pilani, India and his Ph.D. from Nanyang Technological University, Singapore. His research aims to leverage large-scale social media image and text data to model social health outcomes and psychological traits. He uses machine learning, statistical analysis, natural language processing, and computer vision to answer questions pertaining to health an...
Read more
See other products by Sharath Chandra Guntuku
Shubhangi Hora is a data scientist, Python developer, and published writer. With a background in computer science and psychology, she is particularly passionate about healthcare-related AI, including mental health. Shubhangi is also a trained musician.
See other products by Shubhangi Hora
Anshu Kumar is a data scientist with over 5 years of experience in solving complex problems in natural language processing and recommendation systems. He has an M.Tech. from IIT Madras in computer science. He is also a mentor at SpringBoard. His current interests are building semantic search, text summarization, and content recommendations for large-scale multilingual datasets.
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