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Stefanie Molin

Hands-On Data Analysis with Pandas: Efficiently perform data collection, wrangling, analysis, and visualization using Python

by Stefanie Molin (Author)

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Hands-On Data Analysis with Pandas: A Python data science handbook for data collection, wrangling, analysis, and visualization, 2nd Edition
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Get to grips with pandas―a versatile and high-performance Python library for data manipulation, analysis, and discovery
Key Features

Perform efficient data analysis and manipulation tasks using pandas
Apply pandas to different real-world domains using step-by-step demonstrations
Get accustomed to using pandas as an effective data exploration tool

Book DescriptionData analysis has become a necessary skill in a variety of positions where knowing how to work with data and extract insights can generate significant value.
Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with 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 powerful 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.
By the end of this book, you will be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets.
What you will learn

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

Who this book is forThis book is for data analysts, data science beginners, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. You will also find this book useful if you are a data scientist who is looking to implement pandas in your machine learning workflow. Working knowledge of the Python programming language will be beneficial.Table of Contents

Introduction to Data Analysis
Working with Pandas DataFrames
Data Wrangling with Pandas
Aggregating Pandas DataFrames
Visualizing Data with Pandas and Matplotlib
Plotting with Seaborn and Customization Techniques
Financial Analysis - Bitcoin and the Stock Market
Rule-based Anomaly Detection
Getting Started with Machine Learning in Python
Making Better Predictions - Optimizing ML Models
Machine Learning Anomaly Detection
The Road Ahead

ISBN-10

1789615321
ISBN-13

978-1789615326
Publisher

Packt Publishing
Publication date

July 26, 2019
Language

English
Dimensions

7.5 x 1.67 x 9.25 inches
Print length

740 pages
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Editorial Reviews

About the Author

Stefanie Molin is a data scientist and software engineer at Bloomberg LP in NYC, tackling tough problems in information security, particularly revolving around anomaly detection, building tools for gathering data, and knowledge sharing. She has extensive experience in data science, designing anomaly detection solutions, and utilizing machine learning in both R and Python in the AdTech and FinTech industries. She holds a B.S. in operations research from Columbia University's Fu Foundation School of Engineering and Applied Science, with minors in economics, and entrepreneurship and innovation. In her free time, she enjoys traveling the world, inventing new recipes, and learning new languages spoken among both people and computers.

Product details

Publisher ‏ : ‎ Packt Publishing (July 26, 2019)
Language ‏ : ‎ English
Paperback ‏ : ‎ 740 pages
ISBN-10 ‏ : ‎ 1789615321
ISBN-13 ‏ : ‎ 978-1789615326
Item Weight ‏ : ‎ 2.67 pounds
Dimensions ‏ : ‎ 7.5 x 1.67 x 9.25 inches

Best Sellers Rank: #1,085,610 in Books (See Top 100 in Books)
- #258 in Database Storage & Design
- #493 in Data Mining (Books)
- #813 in Data Processing

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Stefanie Molin

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Stefanie Molin is a software engineer and data scientist at Bloomberg in New York City, where she tackles tough problems in information security, particularly those revolving around data wrangling/visualization, building tools for gathering data, and knowledge sharing. She holds a bachelor’s of science degree in operations research from Columbia University's Fu Foundation School of Engineering and Applied Science. She is currently pursuing a master’s degree in computer science, with a specialization in machine learning, from Georgia Tech. In her free time, she enjoys traveling the world, inventing new recipes, and learning new languages spoken among both people and computers.

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Felipe M.

If you are a python programmer learning Pandas this is all you need

Reviewed in the United States on September 21, 2019

Verified Purchase

If you are new to Pandas and looking for a way to get up to speed fast this is a great book. Lots of good examples to see how to apply the concepts in real life, which helps a lot to understand how the different dataframe methods work. You can see the author payed a lot of attention to the detail, from the way to breakdown the chapters to the choice of exercises at the end of each chapter.

As a Python programmer Learning Pandas I also appreciate a lot the quality of the code. Usually the code you find in data science examples get things done but it’s far from being of good quality. It’s very refreshing to see good examples written in a very pythonic way.

I keep this book next to my desk and I have the feeling I will be coming back to use it as a reference a lot in the coming weeks. The only way this could be improved would be to have the author sit next to you every time you need to use Pandas :)

10 people found this helpful

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Adam

Great foundational book

Reviewed in the United States on March 23, 2021

Verified Purchase

Amazing read. Very thorough, covering a broad range of topics in the data science space. I would highly recommend starting with this book for anyone interested in building a foundation in Data Science.

2 people found this helpful

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Nikolaos Antimisiaris

Better approach to data science learning

Reviewed in the United States on May 8, 2020

Verified Purchase

Very good resource. Does a great job in providing the fundamentals and guiding you to learn. After 2 other book purchases (and returns) on Python / Data Science topics that disappointed me, this one is spot on.

2 people found this helpful

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Tattonchantry

Great book

Reviewed in the United States on December 22, 2019

Verified Purchase

Great book. I haven't gotten very far, but I have learned a lot.

One person found this helpful

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CryptoKnight

Another good book for python programmers/data scientists

Reviewed in the United States on August 30, 2019

I really enjoyed this book. This book is great for python programmers who want to learn/implement something cool with data using Pandas (of-course). With some programming background in python/R/C, this book is perfect for the data scientist wannabe. Every chapter has a very interesting exercise set. Easy to follow. I am glad that the author has provided the github repo for this too, way better than reading code from the book alone! The book starts from easy steps e.g., import data, transform, basic computations, more fancy topics like plotting, to more advanced and application-specific like finance, machine learning (yes the book also talked about this in practical aspect!, using sklearn), security analytics!

I can't say enough good things about this book and about how effective it is. I started 10 days ago with a skill of python but no data science background. Now, nearly two weeks later, I'm making my scripts do all kinds of things that are complicated if you don't know Pandas e.g., aggregate statistics based on duration (day, week, ..). I genuinely found this book and the exercises a truly beneficial experience/resource. Honestly I usually don't trust this publisher. Most Packt books I own I think weren't worth their price. This book is surprisingly good quality. Finally they have a good author.

6 people found this helpful

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NoWar3355

Example Bonanza

Reviewed in the United States on September 19, 2019

I love it. The author supplied a lot of examples in her GitHub. I am R person, so understanding Pandas is essential to me because it allows me to move between R and Py.

3 people found this helpful

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Amazon Customer

Really helpful and simple to understand

Reviewed in the United Kingdom on November 16, 2021

Verified Purchase

Having just started on my Pandas journey and coming from a non technical background, I find this book simple and the exercises relatable .

Ali Assad

Great

Reviewed in the United Kingdom on April 6, 2021

Verified Purchase

Excellent book! If you are looking to sharpen up on pandas and data analysis in python in general (not only pandas) this is a very solid. In my case I needed a strong refresher and this book was a great choice going beyond that. The accompanying notebooks are great too.

One person found this helpful

Hugo Paulo

Muito Bom.

Reviewed in Brazil on September 23, 2019

Verified Purchase

É um livro com muito conteúdo, tanto técnico quanto prático. Tem uma pequena introdução sobre Análise de Dados e Revisão de Tópicos de Estatística. E, em seguida, inicia um amplo e detalhado curso de Pandas. Tem teoria, exercícios e exemplos de aplicações práticas.

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Hands-On Data Analysis with Pandas: Efficiently perform data collection, wrangling, analysis, and visualization using Python

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