Python data cleaning cookbook: prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn and OpenAI
Jumping into data analysis without proper data cleaning will certainly lead to incorrect results. The Python Data Cleaning Cookbook - Second Edition will show you tools and techniques for cleaning and handling data with Python for better outcomes. Fully updated to the latest version of Python and al...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Birmingham, UK
Packt Publishing Ltd.
2024
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| Ausgabe: | Second edition. |
| Schriftenreihe: | Expert insight
|
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781803239873/?ar |
| Zusammenfassung: | Jumping into data analysis without proper data cleaning will certainly lead to incorrect results. The Python Data Cleaning Cookbook - Second Edition will show you tools and techniques for cleaning and handling data with Python for better outcomes. Fully updated to the latest version of Python and all relevant tools, this book will teach you how to manipulate and clean data to get it into a useful form. he current edition focuses on advanced techniques like machine learning and AI-specific approaches and tools for data cleaning along with the conventional ones. The book also delves into tips and techniques to process and clean data for ML, AI, and NLP models. You will learn how to filter and summarize data to gain insights and better understand what makes sense and what does not, along with discovering how to operate on data to address the issues you've identified. Next, you'll cover recipes for using supervised learning and Naive Bayes analysis to identify unexpected values and classification errors and generate visualizations for exploratory data analysis (EDA) to identify unexpected values. Finally, you'll build functions and classes that you can reuse without modification when you have new data. By the end of this Data Cleaning book, you'll know how to clean data and diagnose problems within it. |
| Beschreibung: | Includes index |
| Umfang: | 1 Online-Ressource (486 Seiten) illustrations |
| ISBN: | 9781803239873 |
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| 520 | |a Jumping into data analysis without proper data cleaning will certainly lead to incorrect results. The Python Data Cleaning Cookbook - Second Edition will show you tools and techniques for cleaning and handling data with Python for better outcomes. Fully updated to the latest version of Python and all relevant tools, this book will teach you how to manipulate and clean data to get it into a useful form. he current edition focuses on advanced techniques like machine learning and AI-specific approaches and tools for data cleaning along with the conventional ones. The book also delves into tips and techniques to process and clean data for ML, AI, and NLP models. You will learn how to filter and summarize data to gain insights and better understand what makes sense and what does not, along with discovering how to operate on data to address the issues you've identified. Next, you'll cover recipes for using supervised learning and Naive Bayes analysis to identify unexpected values and classification errors and generate visualizations for exploratory data analysis (EDA) to identify unexpected values. Finally, you'll build functions and classes that you can reuse without modification when you have new data. By the end of this Data Cleaning book, you'll know how to clean data and diagnose problems within it. | ||
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| spelling | Walker, Michael VerfasserIn aut Python data cleaning cookbook prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn and OpenAI Michael Walker Second edition. Birmingham, UK Packt Publishing Ltd. 2024 1 Online-Ressource (486 Seiten) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Expert insight Includes index Jumping into data analysis without proper data cleaning will certainly lead to incorrect results. The Python Data Cleaning Cookbook - Second Edition will show you tools and techniques for cleaning and handling data with Python for better outcomes. Fully updated to the latest version of Python and all relevant tools, this book will teach you how to manipulate and clean data to get it into a useful form. he current edition focuses on advanced techniques like machine learning and AI-specific approaches and tools for data cleaning along with the conventional ones. The book also delves into tips and techniques to process and clean data for ML, AI, and NLP models. You will learn how to filter and summarize data to gain insights and better understand what makes sense and what does not, along with discovering how to operate on data to address the issues you've identified. Next, you'll cover recipes for using supervised learning and Naive Bayes analysis to identify unexpected values and classification errors and generate visualizations for exploratory data analysis (EDA) to identify unexpected values. Finally, you'll build functions and classes that you can reuse without modification when you have new data. By the end of this Data Cleaning book, you'll know how to clean data and diagnose problems within it. Analysis of variance Database management Data mining Python (Computer program language) Analyse de variance Bases de données ; Gestion Exploration de données (Informatique) Python (Langage de programmation) |
| spellingShingle | Walker, Michael Python data cleaning cookbook prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn and OpenAI Analysis of variance Database management Data mining Python (Computer program language) Analyse de variance Bases de données ; Gestion Exploration de données (Informatique) Python (Langage de programmation) |
| title | Python data cleaning cookbook prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn and OpenAI |
| title_auth | Python data cleaning cookbook prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn and OpenAI |
| title_exact_search | Python data cleaning cookbook prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn and OpenAI |
| title_full | Python data cleaning cookbook prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn and OpenAI Michael Walker |
| title_fullStr | Python data cleaning cookbook prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn and OpenAI Michael Walker |
| title_full_unstemmed | Python data cleaning cookbook prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn and OpenAI Michael Walker |
| title_short | Python data cleaning cookbook |
| title_sort | python data cleaning cookbook prepare your data for analysis with pandas numpy matplotlib scikit learn and openai |
| title_sub | prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn and OpenAI |
| topic | Analysis of variance Database management Data mining Python (Computer program language) Analyse de variance Bases de données ; Gestion Exploration de données (Informatique) Python (Langage de programmation) |
| topic_facet | Analysis of variance Database management Data mining Python (Computer program language) Analyse de variance Bases de données ; Gestion Exploration de données (Informatique) Python (Langage de programmation) |
| work_keys_str_mv | AT walkermichael pythondatacleaningcookbookprepareyourdataforanalysiswithpandasnumpymatplotlibscikitlearnandopenai |