Learn to master data analysis with Pandas, covering Python basics to advanced techniques, including data cleaning, preprocessing, and visualization.

Key Features

• Comprehensive coverage of Python basics and Pandas
• Practical examples and code samples for hands-on learning
• Detailed sections on data preprocessing, statistical concepts, and data visualization

Book Description

This book is essential for aspiring data scientists and anyone needing to perform data cleaning using Pandas and NumPy. It offers numerous code samples and comprehensive coverage of NumPy and Pandas features, including writing regular expressions. Chapter 3 introduces fundamental statistical concepts, while Chapter 7 delves into data visualization using Matplotlib and Seaborn. Companion files with code are available for download from the publisher.Starting with an introduction to Python, the course progresses through working with data, and then moves into Pandas, covering its functionalities in three detailed chapters. The statistical concepts provided are crucial for analyzing data effectively, while the visualization techniques enhance the ability to present data insights clearly.By the end of this course, users will have a solid foundation in data manipulation and cleaning, statistical analysis, and data visualization, enabling them to tackle real-world data science tasks confidently and efficiently.

What you will learn

• Learn to install and configure Python and Pandas
• Perform data preprocessing and cleaning tasks
• Understand statistical concepts and their application
• Create data visualizations with Matplotlib and Seaborn
• Handle missing data and outliers effectively
• Utilize Pandas for advanced data manipulation

Who this book is for

The ideal audience for this book is software developers with a solid background in programming, specifically in Python. Complete beginners might not find this book very helpful. Readers should have a basic understanding of programming concepts.

Learn to master data analysis with Pandas, covering Python basics to advanced techniques, including data cleaning, preprocessing, and visualization.

Key Features

• Comprehensive coverage of Python basics and Pandas
• Practical examples and code samples for hands-on learning
• Detailed sections on data preprocessing, statistical concepts, and data visualization

Book Description

This book is essential for aspiring data scientists and anyone needing to perform data cleaning using Pandas and NumPy. It offers numerous code samples and comprehensive coverage of NumPy and Pandas features, including writing regular expressions. Chapter 3 introduces fundamental statistical concepts, while Chapter 7 delves into data visualization using Matplotlib and Seaborn. Companion files with code are available for download from the publisher.Starting with an introduction to Python, the course progresses through working with data, and then moves into Pandas, covering its functionalities in three detailed chapters. The statistical concepts provided are crucial for analyzing data effectively, while the visualization techniques enhance the ability to present data insights clearly.By the end of this course, users will have a solid foundation in data manipulation and cleaning, statistical analysis, and data visualization, enabling them to tackle real-world data science tasks confidently and efficiently.

What you will learn

• Learn to install and configure Python and Pandas
• Perform data preprocessing and cleaning tasks
• Understand statistical concepts and their application
• Create data visualizations with Matplotlib and Seaborn
• Handle missing data and outliers effectively
• Utilize Pandas for advanced data manipulation

Who this book is for

The ideal audience for this book is software developers with a solid background in programming, specifically in Python. Complete beginners might not find this book very helpful. Readers should have a basic understanding of programming concepts.

Learn to master data analysis with Pandas, covering Python basics to advanced techniques, including data cleaning, preprocessing, and visualization.

Key Features

• Comprehensive coverage of Python basics and Pandas
• Practical examples and code samples for hands-on learning
• Detailed sections on data preprocessing, statistical concepts, and data visualization

Book Description

This book is essential for aspiring data scientists and anyone needing to perform data cleaning using Pandas and NumPy. It offers numerous code samples and comprehensive coverage of NumPy and Pandas features, including writing regular expressions. Chapter 3 introduces fundamental statistical concepts, while Chapter 7 delves into data visualization using Matplotlib and Seaborn. Companion files with code are available for download from the publisher.Starting with an introduction to Python, the course progresses through working with data, and then moves into Pandas, covering its functionalities in three detailed chapters. The statistical concepts provided are crucial for analyzing data effectively, while the visualization techniques enhance the ability to present data insights clearly.By the end of this course, users will have a solid foundation in data manipulation and cleaning, statistical analysis, and data visualization, enabling them to tackle real-world data science tasks confidently and efficiently.

What you will learn

• Learn to install and configure Python and Pandas
• Perform data preprocessing and cleaning tasks
• Understand statistical concepts and their application
• Create data visualizations with Matplotlib and Seaborn
• Handle missing data and outliers effectively
• Utilize Pandas for advanced data manipulation

Who this book is for

The ideal audience for this book is software developers with a solid background in programming, specifically in Python. Complete beginners might not find this book very helpful. Readers should have a basic understanding of programming concepts.