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Cover of Data Wrangling with Python: Tips and Tools to Make Your Life Easier
English Intermediate Software Engineering

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

Jacqueline Kazil,Katharine Jarmul

Katharine Jarmul

5.0 / 5

1 reviews

2016

Published

501

pages

404

views

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 th

About this book

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

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Reader reviews

1 reviews · 5.0 average out of 5

nandan6

2025/07/21

5 / 5

Good introductory book. Provides sufficient depth to python fundamentals, followed by several practical data wrangling examples. Later chapters provide a high level overview of more advanced applications (less code here). I deducted off two stars for two reasons, one for using python 2 instead of 3 (for an introductory book this choice is perplexing). Pretty much all topics, with the exception of the chapter on Scrapy, could have been explained using python 3. Another star deducted for barely a passing mention of the pandas package. Most wrangling examples in the book could be much easier implemented through pandas (although that's a mater of opinion, I feel like there should have been more than just a passing mention of one of python's oft used data wrangling packages)

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