Practical python data wrangling and data quality: getting started with reading, cleaning, and analyzing data
There are awesome discoveries to be made and valuable stories to be told in datasets--and this book will help you uncover them. Whether you already work with data or just want to understand its possibilities, the techniques and advice in this practical book will help you learn how to better clean, e...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Körperschaften: | , |
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Sebastpol, CA
O'Reilly Media
2021
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| Ausgabe: | First edition. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781492091493/?ar |
| Zusammenfassung: | There are awesome discoveries to be made and valuable stories to be told in datasets--and this book will help you uncover them. Whether you already work with data or just want to understand its possibilities, the techniques and advice in this practical book will help you learn how to better clean, evaluate, and analyze data to generate meaningful insights and compelling visualizations. Through foundational concepts and worked examples, author Susan McGregor provides the concepts and tools you need to evaluate and analyze all kinds of data and communicate your findings effectively. This book provides a methodical, jargon-free way for practitioners of all levels to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources Understand and use programming basics in Python to wrangle data at scale Organize, document, and structure your code using best practices Complete exercises either on your own machine or on the web Collect data from structured data files, web pages, and APIs Perform basic statistical analysis to make meaning from data sets Visualize and present data in clear and compelling ways. |
| Beschreibung: | Includes index. - Description based on online resource; title from digital title page (viewed on February 01, 2022) |
| Umfang: | 1 Online-Ressource (65 Seiten) |
| ISBN: | 9781492091493 1492091499 9781492091479 1492091472 9781492091455 1492091456 |
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| spelling | McGregor, Susan VerfasserIn aut Practical python data wrangling and data quality getting started with reading, cleaning, and analyzing data Susan E. McGregor First edition. Sebastpol, CA O'Reilly Media 2021 ©2022 1 Online-Ressource (65 Seiten) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes index. - Description based on online resource; title from digital title page (viewed on February 01, 2022) There are awesome discoveries to be made and valuable stories to be told in datasets--and this book will help you uncover them. Whether you already work with data or just want to understand its possibilities, the techniques and advice in this practical book will help you learn how to better clean, evaluate, and analyze data to generate meaningful insights and compelling visualizations. Through foundational concepts and worked examples, author Susan McGregor provides the concepts and tools you need to evaluate and analyze all kinds of data and communicate your findings effectively. This book provides a methodical, jargon-free way for practitioners of all levels to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources Understand and use programming basics in Python to wrangle data at scale Organize, document, and structure your code using best practices Complete exercises either on your own machine or on the web Collect data from structured data files, web pages, and APIs Perform basic statistical analysis to make meaning from data sets Visualize and present data in clear and compelling ways. Data mining Electronic data processing Data preparation Python (Computer program language) Data Mining Exploration de données (Informatique) Préparation des données (Informatique) Python (Langage de programmation) Electronic data processing ; Data preparation O'Reilly for Higher Education (Firm), MitwirkendeR ctb Safari, an O'Reilly Media Company. MitwirkendeR ctb 1492091502 Erscheint auch als Druck-Ausgabe 1492091502 |
| spellingShingle | McGregor, Susan Practical python data wrangling and data quality getting started with reading, cleaning, and analyzing data Data mining Electronic data processing Data preparation Python (Computer program language) Data Mining Exploration de données (Informatique) Préparation des données (Informatique) Python (Langage de programmation) Electronic data processing ; Data preparation |
| title | Practical python data wrangling and data quality getting started with reading, cleaning, and analyzing data |
| title_auth | Practical python data wrangling and data quality getting started with reading, cleaning, and analyzing data |
| title_exact_search | Practical python data wrangling and data quality getting started with reading, cleaning, and analyzing data |
| title_full | Practical python data wrangling and data quality getting started with reading, cleaning, and analyzing data Susan E. McGregor |
| title_fullStr | Practical python data wrangling and data quality getting started with reading, cleaning, and analyzing data Susan E. McGregor |
| title_full_unstemmed | Practical python data wrangling and data quality getting started with reading, cleaning, and analyzing data Susan E. McGregor |
| title_short | Practical python data wrangling and data quality |
| title_sort | practical python data wrangling and data quality getting started with reading cleaning and analyzing data |
| title_sub | getting started with reading, cleaning, and analyzing data |
| topic | Data mining Electronic data processing Data preparation Python (Computer program language) Data Mining Exploration de données (Informatique) Préparation des données (Informatique) Python (Langage de programmation) Electronic data processing ; Data preparation |
| topic_facet | Data mining Electronic data processing Data preparation Python (Computer program language) Data Mining Exploration de données (Informatique) Préparation des données (Informatique) Python (Langage de programmation) Electronic data processing ; Data preparation |
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