期刊全稱 | A Python Data Analyst’s Toolkit | 期刊簡稱 | Learn Python and Pyt | 影響因子2023 | Gayathri Rajagopalan | 視頻video | http://file.papertrans.cn/142/141977/141977.mp4 | 發(fā)行地址 | Explains important data analytics concepts with real-life applications using Python.Includes multiple-choice and practice questions to bridge the gap between theory and practice.Contains case studies | 圖書封面 |  | 影響因子 | Explore the fundamentals of data analysis, and statistics with case studies using Python. This book will show you how to confidently write code in Python, and use various Python libraries and functions for analyzing any dataset. The code is presented in Jupyter notebooks that can further be adapted and extended..This book is divided into three parts – programming with Python, data analysis and visualization, and statistics. You‘ll start with an introduction to Python – the syntax, functions, conditional statements, data types, and different types of containers.? You‘ll then review more advanced concepts like regular expressions, handling of files, and solving mathematical problems with Python.?.The second part of the book, will cover Python libraries used for data analysis. There will be an introductory chapter covering basic concepts and terminology, and one chapter each on NumPy(the scientific computation library), Pandas (the data wrangling library) and visualization libraries like Matplotlib and Seaborn. Case studies will be included as examples to help readers understand some real-world applications of data analysis.?.The final chapters of book focus on statistics, elucidating | Pindex | Book 2021 |
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