Pandas in Action - by Boris Paskhaver (Paperback)
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<p/><br></br><p><b> About the Book </b></p></br></br>"For readers experienced with spreadsheets and basic Python programming"--Back cover.<p/><br></br><p><b> Book Synopsis </b></p></br></br><b>Take the next steps in your data science career! This friendly and hands-on guide shows you how to start mastering Pandas with skills you already know from spreadsheet software.</b> <p/>In <i>Pandas in Action</i> you will learn how to: <p/> Import datasets, identify issues with their data structures, and optimize them for efficiency<br> Sort, filter, pivot, and draw conclusions from a dataset and its subsets<br> Identify trends from text-based and time-based data<br> Organize, group, merge, and join separate datasets<br> Use a GroupBy object to store multiple DataFrames <p/>Pandas has rapidly become one of Python's most popular data analysis libraries. In <i>Pandas in Action</i>, a friendly and example-rich introduction, author Boris Paskhaver shows you how to master this versatile tool and take the next steps in your data science career. You'll learn how easy Pandas makes it to efficiently sort, analyze, filter and munge almost any type of data. <p/>Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. <p/>About the technology<br> Data analysis with Python doesn't have to be hard. If you can use a spreadsheet, you can learn pandas! While its grid-style layouts may remind you of Excel, pandas is far more flexible and powerful. This Python library quickly performs operations on millions of rows, and it interfaces easily with other tools in the Python data ecosystem. It's a perfect way to up your data game. <p/>About the book<br> <i>Pandas in Action</i> introduces Python-based data analysis using the amazing pandas library. You'll learn to automate repetitive operations and gain deeper insights into your data that would be impractical--or impossible--in Excel. Each chapter is a self-contained tutorial. Realistic downloadable datasets help you learn from the kind of messy data you'll find in the real world. <p/>What's inside <p/> Organize, group, merge, split, and join datasets<br> Find trends in text-based and time-based data<br> Sort, filter, pivot, optimize, and draw conclusions<br> Apply aggregate operations <p/>About the reader<br> For readers experienced with spreadsheets and basic Python programming. <p/>About the author<br> <b>Boris Paskhaver</b> is a software engineer, Agile consultant, and online educator. His programming courses have been taken by 300,000 students across 190 countries. <p/>Table of Contents<br> PART 1 CORE PANDAS<br> 1 Introducing pandas<br> 2 The Series object<br> 3 Series methods<br> 4 The DataFrame object<br> 5 Filtering a DataFrame<br> PART 2 APPLIED PANDAS<br> 6 Working with text data<br> 7 MultiIndex DataFrames<br> 8 Reshaping and pivoting<br> 9 The GroupBy object<br> 10 Merging, joining, and concatenating<br> 11 Working with dates and times<br> 12 Imports and exports<br> 13 Configuring pandas<br> 14 Visualization<p/><br></br><p><b> About the Author </b></p></br></br><b>Boris Paskhaver</b> is a software engineer, Agile consultant, and educator. His six programming courses on Udemy have amassed 236,000 students, with an average course rating of 4.59 out of 5. He first used Python and the pandas library to derive a variety of business insights at the world's #1 jobs site, Indeed.com.
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