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

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)

探索使用Python進行數據分析和統計的基礎知識，並通過案例研究來學習。本書將向您展示如何自信地使用Python編寫代碼，並使用各種Python庫和函數來分析任何數據集。代碼以Jupyter筆記本的形式呈現，可以進一步適應和擴展。
本書分為三個部分-使用Python進行編程、數據分析和可視化以及統計學。您將從Python的介紹開始-語法、函數、條件語句、數據類型和不同類型的容器。然後，您將複習更高級的概念，如正則表達式、文件處理和使用Python解決數學問題。
本書的第二部分將介紹用於數據分析的Python庫。將有一個介紹性章節介紹基本概念和術語，以及一章介紹NumPy（科學計算庫）、Pandas（數據整理庫）和Matplotlib和Seaborn等可視化庫。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、排列組合和假設檢驗（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。
您將學到什麼


  • 進一步提升Python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解決真實案例研究

  • 複習基本統計概念，並使用Scipy庫解決統計問題

本書適合對象
從事數據科學領域工作並有興趣提升Python、數據分析和統計技能的專業人士。

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 在一家印度領先的跨國組織工作，擁有軟體和資訊科技行業十年的經驗。她是一位電腦工程師和持有專案管理專業人士（PMP）認證，她的主要專注領域包括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。她的嗜好包括閱讀、音樂和教授初學者數據科學。

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