Graph Data Modeling in Python: A practical guide to curating, analyzing, and modeling data with graphs
暫譯: Python中的圖形數據建模:實用指南,涵蓋圖形數據的策劃、分析與建模

Hutson, Gary, Jackson, Matt

  • 出版商: Packt Publishing
  • 出版日期: 2023-06-30
  • 售價: $1,880
  • 貴賓價: 9.5$1,786
  • 語言: 英文
  • 頁數: 236
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1804618039
  • ISBN-13: 9781804618035
  • 相關分類: Python程式語言
  • 海外代購書籍(需單獨結帳)

商品描述

Learn how to transform, store, evolve, refactor, model, and create graph projections using the Python programming language

Purchase of the print or Kindle book includes a free PDF eBook

 

Key Features:

  • Transform relational data models into graph data model while learning key applications along the way
  • Discover common challenges in graph modeling and analysis, and learn how to overcome them
  • Practice real-world use cases of community detection, knowledge graph, and recommendation network

 

Book Description:

Graphs have become increasingly integral to powering the products and services we use in our daily lives, driving social media, online shopping recommendations, and even fraud detection. With this book, you'll see how a good graph data model can help enhance efficiency and unlock hidden insights through complex network analysis.

 

Graph Data Modeling in Python will guide you through designing, implementing, and harnessing a variety of graph data models using the popular open source Python libraries NetworkX and igraph. Following practical use cases and examples, you'll find out how to design optimal graph models capable of supporting a wide range of queries and features. Moreover, you'll seamlessly transition from traditional relational databases and tabular data to the dynamic world of graph data structures that allow powerful, path-based analyses. As well as learning how to manage a persistent graph database using Neo4j, you'll also get to grips with adapting your network model to evolving data requirements.

 

By the end of this book, you'll be able to transform tabular data into powerful graph data models. In essence, you'll build your knowledge from beginner to advanced-level practitioner in no time.

 

What You Will Learn:

  • Design graph data models and master schema design best practices
  • Work with the NetworkX and igraph frameworks in Python
  • Store, query, ingest, and refactor graph data
  • Store your graphs in memory with Neo4j
  • Build and work with projections and put them into practice
  • Refactor schemas and learn tactics for managing an evolved graph data model

 

Who this book is for:

If you are a data analyst or database developer interested in learning graph databases and how to curate and extract data from them, this is the book for you. It is also beneficial for data scientists and Python developers looking to get started with graph data modeling. Although knowledge of Python is assumed, no prior experience in graph data modeling theory and techniques is required.

商品描述(中文翻譯)

學習如何使用 Python 程式語言轉換、儲存、演進、重構、建模和創建圖形投影

購買印刷版或 Kindle 版書籍包括免費 PDF 電子書

主要特色:


  • 在學習關鍵應用的同時,將關聯數據模型轉換為圖形數據模型

  • 發現圖形建模和分析中的常見挑戰,並學習如何克服它們

  • 實踐社群檢測、知識圖譜和推薦網絡的真實案例

書籍描述:

圖形在推動我們日常生活中使用的產品和服務方面變得越來越重要,驅動社交媒體、在線購物推薦,甚至詐騙檢測。通過這本書,您將看到良好的圖形數據模型如何通過複雜的網絡分析來提高效率並揭示隱藏的見解。

《Python 中的圖形數據建模》將指導您設計、實施和利用各種圖形數據模型,使用流行的開源 Python 庫 NetworkX 和 igraph。通過實際的使用案例和範例,您將了解如何設計能夠支持廣泛查詢和功能的最佳圖形模型。此外,您將無縫地從傳統的關聯數據庫和表格數據過渡到動態的圖形數據結構,這些結構允許強大的基於路徑的分析。在學習如何使用 Neo4j 管理持久的圖形數據庫的同時,您還將掌握如何根據不斷演變的數據需求調整您的網絡模型。

在本書結束時,您將能夠將表格數據轉換為強大的圖形數據模型。實質上,您將在短時間內從初學者成長為高級實踐者。

您將學到的內容:


  • 設計圖形數據模型並掌握架構設計最佳實踐

  • 在 Python 中使用 NetworkX 和 igraph 框架

  • 儲存、查詢、攝取和重構圖形數據

  • 使用 Neo4j 將圖形儲存在記憶體中

  • 構建和使用投影並將其付諸實踐

  • 重構架構並學習管理演變的圖形數據模型的策略

本書適合誰:

如果您是數據分析師或數據庫開發人員,對學習圖形數據庫及如何策劃和提取數據感興趣,那麼這本書適合您。對於希望開始學習圖形數據建模的數據科學家和 Python 開發人員也非常有幫助。雖然假設您具備 Python 知識,但不需要具備圖形數據建模理論和技術的先前經驗。