Hands-On Data Preprocessing in Python
Whether you're a data analyst new to programming or already familiar with it, this book will teach you the optimum techniques for data preprocessing from both technical and analytical perspectives. You'll explore the world of advanced data manipulation and preprocessing techniques to create successful data analytic solutions.
Offered by
Difficulty Level
Intermediate
Completion Time
20h4m
Language
English
About Book
Who Is This Book For?
This book is for junior and senior data analysts, business intelligence professionals, engineering undergraduates, and data enthusiasts looking to perform preprocessing and data cleaning on large amounts of data. You don’t need any prior experience with data preprocessing to get started with this book. However, basic programming skills, such as working with variables, conditionals, and loops, along with beginner-level knowledge of Python and simple analytics experience, are a prerequisite.
Hands-On Data Preprocessing in Python
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 20h4m total length
Review of the Core Modules of NumPy and Pandas
Review of Another Core Module - Matplotlib
Data – What Is It Really?
Databases
Data Visualization
Prediction
Classification
Clustering Analysis
Data Cleaning Level I - Cleaning Up the Table
Data Cleaning Level II - Unpacking, Restructuring, and Reformulating the Table
Data Cleaning Level III- Missing Values, Outliers, and Errors
Data Fusion and Data Integration
Data Reduction
Data Transformation and Massaging
Case Study 1 - Mental Health in Tech
Case Study 2 - Predicting COVID-19 Hospitalizations
Case Study 3: United States Counties Clustering Analysis
Summary, Practice Case Studies, and Conclusions
Related Resources
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