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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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 |
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CAMPESATO, OSWALD, CAMPESATO, OSWALD, |
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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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Data Literacy with Python / |
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1795090193744658432 |
fullrecord |
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