Exploring Data In Python 3
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Python for Everybody
Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.This book uses the Python 3 language. The earlier Python 2 version of this book is titled "Python for Informatics: Exploring Information".There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www.pythonlearn.com. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course.
Exploratory Data Analysis with Python Cookbook
Author: Ayodele Oluleye
language: en
Publisher: Packt Publishing Ltd
Release Date: 2023-06-30
Extract valuable insights from data by leveraging various analysis and visualization techniques with this comprehensive guide Purchase of the print or Kindle book includes a free PDF eBook Key Features Gain practical experience in conducting EDA on a single variable of interest in Python Learn the different techniques for analyzing and exploring tabular, time series, and textual data in Python Get well versed in data visualization using leading Python libraries like Matplotlib and seaborn Book DescriptionIn today's data-centric world, the ability to extract meaningful insights from vast amounts of data has become a valuable skill across industries. Exploratory Data Analysis (EDA) lies at the heart of this process, enabling us to comprehend, visualize, and derive valuable insights from various forms of data. This book is a comprehensive guide to Exploratory Data Analysis using the Python programming language. It provides practical steps needed to effectively explore, analyze, and visualize structured and unstructured data. It offers hands-on guidance and code for concepts such as generating summary statistics, analyzing single and multiple variables, visualizing data, analyzing text data, handling outliers, handling missing values and automating the EDA process. It is suited for data scientists, data analysts, researchers or curious learners looking to gain essential knowledge and practical steps for analyzing vast amounts of data to uncover insights. Python is an open-source general purpose programming language which is used widely for data science and data analysis given its simplicity and versatility. It offers several libraries which can be used to clean, analyze, and visualize data. In this book, we will explore popular Python libraries such as Pandas, Matplotlib, and Seaborn and provide workable code for analyzing data in Python using these libraries. By the end of this book, you will have gained comprehensive knowledge about EDA and mastered the powerful set of EDA techniques and tools required for analyzing both structured and unstructured data to derive valuable insights.What you will learn Perform EDA with leading python data visualization libraries Execute univariate, bivariate and multivariate analysis on tabular data Uncover patterns and relationships within time series data Identify hidden patterns within textual data Learn different techniques to prepare data for analysis Overcome challenge of outliers and missing values during data analysis Leverage automated EDA for fast and efficient analysis Who this book is forWhether you are a data analyst, data scientist, researcher or a curious learner looking to analyze structured and unstructured data, this book will appeal to you. It aims to empower you with essential knowledge and practical skills for analyzing and visualizing data to uncover insights. It covers several EDA concepts and provides hands-on instructions on how these can be applied using various Python libraries. Familiarity with basic statistical concepts and foundational knowledge of python programming will help you understand the content better and maximize your learning experience.
Exploring Data Science: Concepts, Techniques and Tools
Author: Dr. A.P. Siva Kumar
language: en
Publisher: IIP Iterative International Publishers
Release Date: 2025-06-24
Welcome to "Data Science with Python"! Whether you're a student, a professional looking to switch careers, or an enthusiast eager to explore the world of data science, this book is designed to take you on an exciting journey through one of the most rapidly growing fields in the world. Data science is the key to unlocking the potential of vast amounts of data in today's digital age. With Python emerging as the leading language for data analysis, machine learning, and visualization, this book leverages Python's rich ecosystem of libraries to provide a hands-on and practical approach to learning data science concepts. Throughout the chapters, you will gain a solid foundation in the essential techniques used in data science, including data manipulation, exploration, statistical analysis, machine learning, and data visualization. You’ll also find real-world examples, case studies, and step-by-step tutorials that will guide you in solving complex problems using Python. The book assumes no prior knowledge of data science or Python, making it suitable for beginners. As you progress, you will gradually move into more advanced topics, empowering you to build your own data-driven solutions with confidence. By the end of this book, you will not only have a deep understanding of the core principles of data science but also be equipped with practical skills to tackle real-world challenges using Python’s powerful data science tools. Whether you're analyzing business data, building machine learning models, or visualizing complex datasets, you'll find the skills you need to succeed. Data science is an ever-evolving field, and as you embark on this journey, remembers that learning is continuous. This book serves as a foundation for that journey, and the possibilities are endless as you dive deeper into data science with Python.