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. In Pandas in Action you will learn how to: Import datasets, identify issues with their data structures, and optimize them for efficiency Sort, filter, pivot, and draw conclusions from a dataset and its subsets Identify trends from text-based and time-based data Organize, group, merge, and join separate datasets Use a GroupBy object to store multiple DataFrames Pandas has rapidly become one of Python's most popular data analysis libraries. In Pandas in Action, 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. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology 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. About the book Pandas in Action 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. What's inside Organize, group, merge, split, and join datasets Find trends in text-based and time-based data Sort, filter, pivot, optimize, and draw conclusions Apply aggregate operations About the reader For readers experienced with spreadsheets and basic Python programming. About the author Boris Paskhaver is a software engineer, Agile consultant, and online educator. His programming courses have been taken by 300,000 students across 190 countries. Table of Contents PART 1 CORE PANDAS 1 Introducing pandas 2 The Series object 3 Series methods 4 The DataFrame object 5 Filtering a DataFrame PART 2 APPLIED PANDAS 6 Working with text data 7 MultiIndex DataFrames 8 Reshaping and pivoting 9 The GroupBy object 10 Merging, joining, and concatenating 11 Working with dates and times 12 Imports and exports 13 Configuring pandas 14 Visualization
Pandas has rapidly become one of Python''s most popular data analysis libraries. With pandas you can efficiently sort, analyze, filter and munge almost any type of data. In Pandas in Action, 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. about the technology Anyone who''s used spreadsheet software will find pandas familiar. While its column-based grids might remind you of Excel or Google Sheets, pandas is more flexible and far more powerful. It can efficiently perform operations on millions of rows and be used in tandem with other Python libraries for statistics, machine learning, and more. And best of all, using pandas doesn''t mean sacrificing user productivity or needing to write tons of complex code. It''s clean, intuitive, and fast. about the book Pandas in Action makes it easy to dive into Python-based data analysis. You''ll learn to use pandas to automate repetitive spreadsheet functionality and derive insight from data by sorting columns, filtering data subsets, and creating multi-leveled indices. Each chapter is a self-contained tutorial, letting you dip in when you need to troubleshoot tricky problems. Best of all, you won''t be learning from sterile or randomly created data. You''ll start with a variety of datasets that are big, small, incomplete, broken, and messy and learn how to clean and format them for proper analysis. what''s inside Import a CSV, identify issues with its data structures, and convert it to the proper format Sort, filter, pivot, and draw conclusions from a dataset and its subsets Identify trends from text-based and time-based data Organize, group, merge, and join separate datasets Real-world datasets that are easy to download and explore about the reader For readers experienced with spreadsheet software who know the basics of Python. about the author Boris Paskhaver 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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