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.

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

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