A Python Data Analyst's Toolkit: Learn Python and Python-Based Libraries with Applications in Data Analysis and Statistics
暫譯: Python 數據分析師工具包：學習 Python 及基於 Python 的庫在數據分析和統計中的應用

Rajagopalan, Gayathri

A Python Data Analyst's Toolkit: Learn Python and Python-Based Libraries with Applications in Data Analysis and Statistics

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商品描述

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 important principles in statistics that are relevant to data science. These topics include probability, Bayes theorem, permutations and combinations, and hypothesis testing (ANOVA, Chi-squared test, z-test, and t-test), and how the Scipy library enables simplification of tedious calculations involved in statistics.
What You'll Learn
  • Further your programming and analytical skills with Python
  • Solve mathematical problems in calculus, and set theory and algebra with Python
  • Work with various libraries in Python to structure, analyze, and visualize data
  • Tackle real-life case studies using Python
  • Review essential statistical concepts and use the Scipy library to solve problems in statistics
Who This Book Is For
Professionals working in the field of data science interested in enhancing skills in Python, data analysis and statistics.

商品描述(中文翻譯)

探索數據分析和統計的基本原理，並通過使用 Python 的案例研究進行學習。本書將向您展示如何自信地編寫 Python 代碼，並使用各種 Python 庫和函數來分析任何數據集。代碼以 Jupyter notebooks 的形式呈現，您可以進一步調整和擴展。

本書分為三個部分 - 使用 Python 編程、數據分析與可視化，以及統計學。您將從 Python 的介紹開始，包括語法、函數、條件語句、數據類型和不同類型的容器。接著，您將回顧更高級的概念，如正則表達式、文件處理，以及使用 Python 解決數學問題。

本書的第二部分將涵蓋用於數據分析的 Python 庫。將有一章介紹基本概念和術語，並分別有一章介紹 NumPy（科學計算庫）、Pandas（數據處理庫）以及可視化庫如 Matplotlib 和 Seaborn。案例研究將作為示例，幫助讀者理解數據分析的一些實際應用。

本書的最後幾章專注於統計學，闡明與數據科學相關的重要統計原則。這些主題包括概率、貝葉斯定理、排列與組合，以及假設檢驗（ANOVA、卡方檢驗、z 檢驗和 t 檢驗），以及 Scipy 庫如何簡化統計中繁瑣的計算。

您將學到的內容


  • 提升您在 Python 中的編程和分析技能

  • 使用 Python 解決微積分、集合論和代數中的數學問題

  • 使用 Python 中的各種庫來結構化、分析和可視化數據

  • 使用 Python 解決現實生活中的案例研究

  • 回顧基本的統計概念，並使用 Scipy 庫解決統計問題

本書適合誰閱讀


對提升 Python、數據分析和統計技能感興趣的數據科學領域專業人士。

作者簡介

Gayathri Rajagopalan works for a leading Indian multi-national organization, with ten years of experience in the software and information technology industry. A computer engineer and a certified Project Management Professional (PMP), some of her key focus areas include Python, data analytics, machine learning, and deep learning. She is proficient in Python, Java, and C/C++ programming. Her hobbies include reading, music, and teaching data science to beginners.

作者簡介(中文翻譯)

Gayathri Rajagopalan 在一家領先的印度跨國公司工作，擁有十年的軟體和資訊科技產業經驗。她是一名電腦工程師及認證的專案管理專業人士（PMP），其主要專注領域包括 Python、數據分析、機器學習和深度學習。她精通 Python、Java 和 C/C++ 程式設計。她的興趣包括閱讀、音樂以及教導初學者數據科學。

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