Python for Geospatial Data Analysis: Theory, Tools, and Practice for Location Intelligence (Paperback)

In spatial data science, things in closer proximity to one another likely have more in common than things that are farther apart. With this practical book, geospatial professionals, data scientists, business analysts, geographers, geologists, and others familiar with data analysis and visualization will learn the fundamentals of spatial data analysis to gain a deeper understanding of their data questions.

Author Bonny P. McClain demonstrates why detecting and quantifying patterns in geospatial data is vital. Both proprietary and open source platforms allow you to process and visualize spatial information. This book is for people familiar with data analysis or visualization who are eager to explore geospatial integration with Python.

This book helps you:

• Understand the importance of applying spatial relationships in data science
• Select and apply data layering of both raster and vector graphics
• Apply location data to leverage spatial analytics
• Design informative and accurate maps
• Automate geographic data with Python scripts
• Explore Python packages for additional functionality
• Work with atypical data types such as polygons, shape files, and projections
• Understand the graphical syntax of spatial data science to stimulate curiosity

在空間數據科學中，彼此靠近的事物往往比遠離的事物更有共同之處。這本實用書籍針對地理空間專業人士、數據科學家、業務分析師、地理學家、地質學家以及其他熟悉數據分析和可視化的人士，介紹了空間數據分析的基礎知識，以深入了解他們的數據問題。

作者Bonny P. McClain展示了在地理空間數據中檢測和量化模式的重要性。無論是專有平台還是開源平台，都可以處理和可視化空間信息。這本書適用於熟悉數據分析或可視化並渴望探索Python與地理空間整合的人士。

這本書可以幫助您：

- 理解在數據科學中應用空間關係的重要性
- 選擇並應用光柵和矢量圖形的數據分層
- 應用位置數據來利用空間分析
- 設計信息豐富且準確的地圖
- 使用Python腳本自動處理地理數據
- 探索Python套件以獲得額外功能
- 處理非典型數據類型，如多邊形、形狀文件和投影
- 理解空間數據科學的圖形語法，激發好奇心