Data Wrangling with Python: Tips and Tools to Make Your Life Easier

Kazil, Jacqueline,Jarmul, Katharine

ISBN 10: 1491948817 / ISBN 13: 9781491948811

Verlag: O'Reilly Media, 2016

Beschreibung

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Bibliografische Details

Titel: Data Wrangling with Python: Tips and Tools ...

Verlag: O'Reilly Media

Erscheinungsdatum: 2016

Einband: paperback

Zustand: Very Good

Über diesen Titel

Inhaltsangabe:

How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done. This hands-on guide shows non-programmers like you how to process information that's initially too messy or difficult to access. You don't need to know a thing about the Python programming language to get started., Through various step-by-step exercises, you'll learn how to acquire, clean, analyze, and present data efficiently. You'll also discover how to automate your data process, schedule file- editing and clean-up tasks, process larger datasets, and create compelling stories with data you obtain. Quickly learn basic Python syntax, data types, and language concepts Work with both machine-readable and human-consumable data Scrape websites and APIs to find a bounty of useful information Clean and format data to eliminate duplicates and errors in your datasets Learn when to standardize data and when to test and script data cleanup Explore and analyze your datasets with new Python libraries and techniques Use Python solutions to automate your entire data-wrangling process

Reseña del editor:

Digging into data does not have to be painful. With this book, you'll learn how to clean and analyze data, create compelling stories, and scale that data as necessary. There are awesome discoveries to be made in unassuming datasets and stories to be told. You don’t have to be a programmer to tell them. What you need is to understand the context of the data and to know a few of the techniques found in this book. You'll learn enough Python to be empowered to engage with your data, through a series of examples that grow in complexity throughout the book.