Python 3 and Data Analytics Pocket Primer:
As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data analytics using Python 3. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, and data cle...
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Dulles, VA
Mercury Learning and Information
[2021]
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| Series: | Pocket Primer
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| Subjects: | |
| Online Access: | DE-1046 DE-1043 DE-858 DE-859 DE-860 DE-739 Volltext |
| Summary: | As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data analytics using Python 3. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, and data cleaning. The book includes numerous code samples using NumPy, Pandas, Matplotlib, Seaborn, and features an appendix on regular expressions. Companion files with source code and color figures are available online by emailing the publisher with proof of purchase at info@merclearning.com. FEATURES: Includes a concise introduction to Python 3Provides a thorough introduction to data and data cleaningCovers NumPy and PandasIntroduces statistical concepts and data visualization (Matplotlib/Seaborn)Features an appendix on regular expressionsIncludes companion files with source code and figures |
| Item Description: | Description based on online resource; title from PDF title page (publisher's Web site, viewed 06. Mrz 2024) |
| Physical Description: | 1 Online-Ressource (238 Seiten) |
| ISBN: | 9781683926535 |
| DOI: | 10.1515/9781683926535 |
Staff View
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| isbn | 9781683926535 |
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| spelling | Campesato, Oswald Verfasser aut Python 3 and Data Analytics Pocket Primer Oswald Campesato Dulles, VA Mercury Learning and Information [2021] © 2021 1 Online-Ressource (238 Seiten) txt rdacontent c rdamedia cr rdacarrier Pocket Primer Description based on online resource; title from PDF title page (publisher's Web site, viewed 06. Mrz 2024) As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data analytics using Python 3. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, and data cleaning. The book includes numerous code samples using NumPy, Pandas, Matplotlib, Seaborn, and features an appendix on regular expressions. Companion files with source code and color figures are available online by emailing the publisher with proof of purchase at info@merclearning.com. FEATURES: Includes a concise introduction to Python 3Provides a thorough introduction to data and data cleaningCovers NumPy and PandasIntroduces statistical concepts and data visualization (Matplotlib/Seaborn)Features an appendix on regular expressionsIncludes companion files with source code and figures In English Data Programming COMPUTERS / Programming Languages / Python bisacsh Data mining Erscheint auch als Druck-Ausgabe 9781683926542 https://doi.org/10.1515/9781683926535 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Campesato, Oswald Python 3 and Data Analytics Pocket Primer Data Programming COMPUTERS / Programming Languages / Python bisacsh Data mining |
| title | Python 3 and Data Analytics Pocket Primer |
| title_auth | Python 3 and Data Analytics Pocket Primer |
| title_exact_search | Python 3 and Data Analytics Pocket Primer |
| title_exact_search_txtP | Python 3 and Data Analytics Pocket Primer |
| title_full | Python 3 and Data Analytics Pocket Primer Oswald Campesato |
| title_fullStr | Python 3 and Data Analytics Pocket Primer Oswald Campesato |
| title_full_unstemmed | Python 3 and Data Analytics Pocket Primer Oswald Campesato |
| title_short | Python 3 and Data Analytics Pocket Primer |
| title_sort | python 3 and data analytics pocket primer |
| topic | Data Programming COMPUTERS / Programming Languages / Python bisacsh Data mining |
| topic_facet | Data Programming COMPUTERS / Programming Languages / Python Data mining |
| url | https://doi.org/10.1515/9781683926535 |
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