Data Literacy with Python / / OSWALD CAMPESATO.

The purpose of this book is to usher readers into the world of data, ensuring a comprehensive understanding of its nuances, intricacies, and complexities. With Python 3 as the primary medium, the book underscores the pivotal role of data in modern industries, and how its adept management can lead to...

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Place / Publishing House:Dulles, VA : : Mercury Learning and Information, , [2023]
©2024
Year of Publication:2023
Language:English
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Physical Description:1 online resource (XX, 300 p.)
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record_format marc
spelling CAMPESATO, OSWALD, author. aut http://id.loc.gov/vocabulary/relators/aut
Data Literacy with Python / OSWALD CAMPESATO.
Dulles, VA : Mercury Learning and Information, [2023]
©2024
1 online resource (XX, 300 p.)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
text file PDF rda
Frontmatter -- Contents -- Preface -- Chapter 1: Working With Data -- Chapter 2: Outlier and Anomaly Detection -- Chapter 3: Cleaning Datasets -- Chapter 4: Introduction to Statistics -- Chapter 5: Matplotlib and Seaborn -- Appendix A: Introduction to Python -- Appendix B: Introduction to Pandas -- Index
restricted access http://purl.org/coar/access_right/c_16ec online access with authorization star
The purpose of this book is to usher readers into the world of data, ensuring a comprehensive understanding of its nuances, intricacies, and complexities. With Python 3 as the primary medium, the book underscores the pivotal role of data in modern industries, and how its adept management can lead to insightful decision-making. The book provides a quick introduction to foundational data-related tasks, priming the readers for more advanced concepts of model training introduced later on. Through detailed, step-by-step Python code examples, the reader will master training models, beginning with the kNN algorithm, and then smoothly transitioning to other classifiers, by tweaking mere lines of code. Tools like Sweetviz, Skimpy, Matplotlib, and Seaborn are introduced, offering readers a hands-on experience in rendering charts and graphs. Companion files with source code and data sets are available by writing to the publisher.
Issued also in print.
Mode of access: Internet via World Wide Web.
In English.
Description based on online resource; title from PDF title page (publisher's Web site, viewed 06. Mrz 2024)
Python 3, Sweetviz, Skimpy, Matplotlib, Seaborn, data analysis,.
EPUB 9781501518683
print 9781501521997
https://doi.org/10.1515/9781501518652
https://www.degruyter.com/isbn/9781501518652
Cover https://www.degruyter.com/document/cover/isbn/9781501518652/original
language English
format eBook
author CAMPESATO, OSWALD,
CAMPESATO, OSWALD,
spellingShingle CAMPESATO, OSWALD,
CAMPESATO, OSWALD,
Data Literacy with Python /
Frontmatter --
Contents --
Preface --
Chapter 1: Working With Data --
Chapter 2: Outlier and Anomaly Detection --
Chapter 3: Cleaning Datasets --
Chapter 4: Introduction to Statistics --
Chapter 5: Matplotlib and Seaborn --
Appendix A: Introduction to Python --
Appendix B: Introduction to Pandas --
Index
author_facet CAMPESATO, OSWALD,
CAMPESATO, OSWALD,
author_variant o c oc
o c oc
author_role VerfasserIn
VerfasserIn
author_sort CAMPESATO, OSWALD,
title Data Literacy with Python /
title_full Data Literacy with Python / OSWALD CAMPESATO.
title_fullStr Data Literacy with Python / OSWALD CAMPESATO.
title_full_unstemmed Data Literacy with Python / OSWALD CAMPESATO.
title_auth Data Literacy with Python /
title_alt Frontmatter --
Contents --
Preface --
Chapter 1: Working With Data --
Chapter 2: Outlier and Anomaly Detection --
Chapter 3: Cleaning Datasets --
Chapter 4: Introduction to Statistics --
Chapter 5: Matplotlib and Seaborn --
Appendix A: Introduction to Python --
Appendix B: Introduction to Pandas --
Index
title_new Data Literacy with Python /
title_sort data literacy with python /
publisher Mercury Learning and Information,
publishDate 2023
physical 1 online resource (XX, 300 p.)
Issued also in print.
contents Frontmatter --
Contents --
Preface --
Chapter 1: Working With Data --
Chapter 2: Outlier and Anomaly Detection --
Chapter 3: Cleaning Datasets --
Chapter 4: Introduction to Statistics --
Chapter 5: Matplotlib and Seaborn --
Appendix A: Introduction to Python --
Appendix B: Introduction to Pandas --
Index
isbn 9781501518652
9781501518683
9781501521997
url https://doi.org/10.1515/9781501518652
https://www.degruyter.com/isbn/9781501518652
https://www.degruyter.com/document/cover/isbn/9781501518652/original
illustrated Not Illustrated
doi_str_mv 10.1515/9781501518652
work_keys_str_mv AT campesatooswald dataliteracywithpython
status_str n
ids_txt_mv (DE-B1597)667010
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is_hierarchy_title Data Literacy with Python /
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