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Hands-On Data Analysis with Pandas
Hands-On Data Analysis with Pandas

Hands-On Data Analysis with Pandas: A Python data science handbook for data collection, wrangling, analysis, and visualization , Second Edition

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Profile Icon Stefanie Molin
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$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.6 (14 Ratings)
Paperback Apr 2021 788 pages 2nd Edition
eBook
$51.99
Paperback
$64.99
Subscription
Free Trial
Renews at $12.99p/m
Arrow left icon
Profile Icon Stefanie Molin
Arrow right icon
$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.6 (14 Ratings)
Paperback Apr 2021 788 pages 2nd Edition
eBook
$51.99
Paperback
$64.99
Subscription
Free Trial
Renews at $12.99p/m
eBook
$51.99
Paperback
$64.99
Subscription
Free Trial
Renews at $12.99p/m

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Key benefits

  • Perform efficient data analysis and manipulation tasks using pandas 1.x
  • Apply pandas to different real-world domains with the help of step-by-step examples
  • Make the most of pandas as an effective data exploration tool

Description

Extracting valuable business insights is no longer a ‘nice-to-have’, but an essential skill for anyone who handles data in their enterprise. Hands-On Data Analysis with Pandas is here to help beginners and those who are migrating their skills into data science get up to speed in no time. This book will show you how to analyze your data, get started with machine learning, and work effectively with the Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. This updated edition will equip you with the skills you need to use pandas 1.x to efficiently perform various data manipulation tasks, reliably reproduce analyses, and visualize your data for effective decision making – valuable knowledge that can be applied across multiple domains.

Who is this book for?

This book is for data science beginners, data analysts, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. Data scientists looking to implement pandas in their machine learning workflow will also find plenty of valuable know-how as they progress. You’ll find it easier to follow along with this book if you have a working knowledge of the Python programming language, but a Python crash-course tutorial is provided in the code bundle for anyone who needs a refresher.

What you will learn

  • Understand how data analysts and scientists gather and analyze data
  • Perform data analysis and data wrangling using Python
  • Combine, group, and aggregate data from multiple sources
  • Create data visualizations with pandas, matplotlib, and seaborn
  • Apply machine learning algorithms to identify patterns and make predictions
  • Use Python data science libraries to analyze real-world datasets
  • Solve common data representation and analysis problems using pandas
  • Build Python scripts, modules, and packages for reusable analysis code

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Apr 29, 2021
Length: 788 pages
Edition : 2nd
Language : English
ISBN-13 : 9781800563452
Vendor :
Microsoft
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Product Details

Publication date : Apr 29, 2021
Length: 788 pages
Edition : 2nd
Language : English
ISBN-13 : 9781800563452
Vendor :
Microsoft
Category :
Languages :
Concepts :
Tools :

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.6
(14 Ratings)
5 star 78.6%
4 star 7.1%
3 star 7.1%
2 star 7.1%
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Felipe M. Jun 14, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Hands on Data Analysis with Pandas is one of the best books I have read recently. What I like the most about it is the structure: combine chapters explaining the different parts of pandas with chapters that have complete practical examples of analysis. This allows you to see detailed examples about the functionality but also see how they fit in the larger picture of a full analysis.Also, it approaches the teaching of pandas with both a data analyst perspective and a software engineer perspective. To be successful in data science today we need to wear both of those hats, so for someone coming from an analysis background without formal software engineering training, the book helps demystify concepts like virtualenv, simulations, source control, etc.It’s not only about learning Pandas but about using pandas in the right away.
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WDM Jul 31, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
it breaks it down and explains the why behind it
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Vanesa Magar May 27, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is a good pandas reference. I got the kindle edition and it is very convenient when you are on the move and you have to work!
Amazon Verified review Amazon
Brenton Chang Aug 04, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
As an analyst in a cyber security operation center role, I live and breathe data. The more, the better. Pandas is a natural fit for organizing, navigating and analyzing diverse data at scale. However, if you’ve ever tried leveraging Pandas to do this, you quickly realize how difficult it can be. The documentation is ambiguous and due to the diversity of the how others leverage Pandas it’s difficult to find scenarios and code examples that line up with your needs. Enter “Hands-On Data Analysis with Pandas”. Molin does a great job at organizing and presenting all you need to get started leveraging both pandas and Jupyter notebooks. She also clearly and concisely explains the fundamental of machine learning and statistical analysis. Her mastery is in both understanding the discipline and the libraries used to get the work done. I not only reference the book to help with organizing and analyzing my data, I also reference the book to support my visualization and plotting requirements. There aren’t many books out there that are both this comprehensive and good at teaching a very complex subject. If you are in cyber security you need this book.
Amazon Verified review Amazon
John Renne May 24, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This easy to follow book is exactly what I needed at this stage of my learning curve. I love how the author takes the reader through accessing real world data that are messy and in some cases missing. Accessing real world data with APIs is a tool I appreciate leaning and then seeing the shortcomings of the real world data has been what most other books are missing. This book will better allow me to translate the lessons to my own needs. Well done!
Amazon Verified review Amazon
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