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Pandas in Action
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
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
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
In Pandas in Action you will learn how
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
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
- GenresSoftware
440 pages, Paperback
Published October 5, 2021
Ratings & Reviews
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Displaying 1 - 2 of 2 reviews
May 3, 2022
Good practical introduction
December 31, 2021
I needed a Pandas refresher, so I've reached out for this book.
It does quite well in many areas, but there were just too many drawbacks to rate it higher than 3.5 stars:
- nearly zero visuals (except 2-3 diagrams to illustrate joins) - some concepts like melting or multi-index data frames nearly scream for some graphical depicting
- I really dislike the way multi-index data frames were described: IMHO it was unclear, sloppy, w/o setting up the good background
- formatting of the (ALL) examples in mobi version was abysmal (on Kindle Oasys) - all tables were broken and skewed - trying to figure out the results was a huge pain
- the big part of the book is "refreshers" (Python, RegEx, NumPy, etc.) - TBH only NumPy makes sense here, the rest is just gap fillers (honestly, can you imagine a person who reaches for this book w/o Python skills)?
- this book is very tutorialesque - its flow feels very natural for learning theory, but it's quite far from how the practical work with Pandas look alike: topics like sampling or cleansing are not covered at all
What about pros?
- if you're looking for a gentle, step-by-step, theoretical intro (the "old way"), it's not bad
- the chapter about configuration is quite useful
It does quite well in many areas, but there were just too many drawbacks to rate it higher than 3.5 stars:
- nearly zero visuals (except 2-3 diagrams to illustrate joins) - some concepts like melting or multi-index data frames nearly scream for some graphical depicting
- I really dislike the way multi-index data frames were described: IMHO it was unclear, sloppy, w/o setting up the good background
- formatting of the (ALL) examples in mobi version was abysmal (on Kindle Oasys) - all tables were broken and skewed - trying to figure out the results was a huge pain
- the big part of the book is "refreshers" (Python, RegEx, NumPy, etc.) - TBH only NumPy makes sense here, the rest is just gap fillers (honestly, can you imagine a person who reaches for this book w/o Python skills)?
- this book is very tutorialesque - its flow feels very natural for learning theory, but it's quite far from how the practical work with Pandas look alike: topics like sampling or cleansing are not covered at all
What about pros?
- if you're looking for a gentle, step-by-step, theoretical intro (the "old way"), it's not bad
- the chapter about configuration is quite useful
Displaying 1 - 2 of 2 reviews