Python: Data Analytics and Visualization

Phuong Vo.T.H, Martin Czygan, Ashish Kumar

  • 出版商: Packt Publishing
  • 出版日期: 2017-04-11
  • 售價: $3,700
  • 貴賓價: 9.5$3,515
  • 語言: 英文
  • 頁數: 866
  • 裝訂: Paperback
  • ISBN: 1788290097
  • ISBN-13: 9781788290098
  • 相關分類: Python程式語言Data Science
  • 海外代購書籍(需單獨結帳)

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商品描述

Understand, evaluate, and visualize data About This Book - Learn basic steps of data analysis and how to use Python and its packages - A step-by-step guide to predictive modeling including tips, tricks, and best practices - Effectively visualize a broad set of analyzed data and generate effective results Who This Book Is For This book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner. What You Will Learn - Get acquainted with NumPy and use arrays and array-oriented computing in data analysis - Process and analyze data using the time-series capabilities of Pandas - Understand the statistical and mathematical concepts behind predictive analytics algorithms - Data visualization with Matplotlib - Interactive plotting with NumPy, Scipy, and MKL functions - Build financial models using Monte-Carlo simulations - Create directed graphs and multi-graphs - Advanced visualization with D3 In Detail You will start the course with an introduction to the principles of data analysis and supported libraries, along with NumPy basics for statistics and data processing. Next, you will overview the Pandas package and use its powerful features to solve data-processing problems. Moving on, you will get a brief overview of the Matplotlib API .Next, you will learn to manipulate time and data structures, and load and store data in a file or database using Python packages. You will learn how to apply powerful packages in Python to process raw data into pure and helpful data using examples. You will also get a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or building helpful products such as recommendations and predictions using Scikit-learn. After this, you will move on to a data analytics specialization-predictive analytics. Social media and IOT have resulted in an avalanche of data. You will get started with predictive analytics using Python. You will see how to create predictive models from data. You will get balanced information on statistical and mathematical concepts, and implement them in Python using libraries such as Pandas, scikit-learn, and NumPy. You'll learn more about the best predictive modeling algorithms such as Linear Regression, Decision Tree, and Logistic Regression. Finally, you will master best practices in predictive modeling. After this, you will get all the practical guidance you need to help you on the journey to effective data visualization. Starting with a chapter on data frameworks, which explains the transformation of data into information and eventually knowledge, this path subsequently cover the complete visualization process using the most popular Python libraries with working examples This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: ? Getting Started with Python Data Analysis, Phuong Vo.T.H &Martin Czygan ? Learning Predictive Analytics with Python, Ashish Kumar ? Mastering Python Data Visualization, Kirthi Raman Style and approach The course acts as a step-by-step guide to get you familiar with data analysis and the libraries supported by Python with the help of real-world examples and datasets. It also helps you gain practical insights into predictive modeling by implementing predictive-analytics algorithms on public datasets with Python. The course offers a wealth of practical guidance to help you on this journey to data visualization

商品描述(中文翻譯)

了解、評估和視覺化數據 關於本書 - 學習數據分析的基本步驟以及如何使用Python及其套件 - 逐步指南,包括預測建模的技巧、技巧和最佳實踐 - 有效地視覺化廣泛分析的數據集並生成有效結果 本書適合對進行數據分析並希望以更高效和深入的方式視覺化其分析數據的Python開發人員。 您將學到什麼 - 熟悉NumPy並在數據分析中使用數組和面向數組的計算 - 使用Pandas的時間序列功能處理和分析數據 - 了解預測分析算法背後的統計和數學概念 - 使用Matplotlib進行數據可視化 - 使用NumPy、Scipy和MKL函數進行交互式繪圖 - 使用蒙特卡羅模擬建立金融模型 - 創建有向圖和多圖 - 使用D3進行高級可視化 詳細內容 您將從數據分析和支持庫的原則介紹開始課程,以及用於統計和數據處理的NumPy基礎知識。 接下來,您將概述Pandas套件並使用其強大功能解決數據處理問題。 接著,您將簡要介紹Matplotlib API。然後,您將學習如何操作時間和數據結構,以及使用Python套件將數據加載和存儲到文件或數據庫中。 您將學習如何應用Python中的強大套件將原始數據處理為純淨且有用的數據,並通過示例進行演示。 您還將簡要介紹機器學習算法,即應用數據分析結果進行決策或使用Scikit-learn構建有用產品(例如推薦和預測)。 在此之後,您將進入數據分析專業領域-預測分析。 社交媒體和物聯網導致了大量數據的產生。 您將使用Python開始進行預測分析。 您將了解如何從數據創建預測模型。 您將獲得有關統計和數學概念的平衡信息,並使用Pandas、scikit-learn和NumPy等庫在Python中實現它們。 您將更多地了解最佳預測建模算法,例如線性回歸、決策樹和邏輯回歸。 最後,您將掌握預測建模的最佳實踐。 在此之後,您將獲得所有實用的指導,以幫助您進行有效的數據可視化。 從數據框架開始,該章節解釋了將數據轉化為信息,最終轉化為知識的過程,然後使用最流行的Python庫進行完整的可視化過程,並提供實際示例。 這個學習路徑將Packt的一些最佳內容結合在一個完整的、精選的包裡。 它包括以下Packt產品的內容: ? Getting Started with Python Data Analysis, Phuong Vo.T.H &Martin Czygan ? Learning Predictive Analytics with Python, Ashish Kumar ? Mastering Python Data Visualization, Kirthi Raman 風格和方法 該課程作為一個逐步指南,通過真實世界的示例和數據集,使您熟悉數據分析和Python支持的庫。 它還通過在公共數據集上使用Python實現預測分析算法,幫助您獲得實際的預測建模見解。 該課程提供了豐富的實用指導,以幫助您在數據可視化的旅程中取得成功。