Pandas In Action Av Boris Paskhover

<div><div> 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 <span> </span><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. </div></div><div style="color: rgb(51,51,51);text-transform: none;text-indent: 0.0px;letter-spacin normal;font-size: 17.25px;font-style: normal;font-weight: 300;word-spacin 0.0px;white-space: normal;orphans: 2;widows: 2;background-color: rgb(255,255,255);"

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 technologyAnyone 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 readerFor readers experienced with spreadsheet software who know the basics of Python.