May 2025
Intermediate to advanced
282 pages
4h 2m
Chinese
Overview
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在空间数据科学中，彼此距离较近的事物往往具有更多共同点，而距离较远的事物则差异更大。通过这本实用书籍，地理空间专业人士、数据科学家、商业分析师、地理学家、地质学家以及其他熟悉数据分析和可视化的人士，将学习空间数据分析的基础知识，从而更深入地理解数据问题。
作者 Bonny P. McClain 阐述了检测和量化地理空间数据中的模式为何至关重要。专有和开源平台均可用于处理和可视化空间信息。本书适合熟悉数据分析或可视化，并渴望探索 Python 与地理空间整合的人士阅读。
本书将帮助您：
- 理解在数据科学中应用空间关系的重要性
- 选择并应用栅格和矢量图形数据的分层技术
- 应用位置数据以利用空间分析
- 设计信息丰富且准确的地图
- 使用 Python 脚本实现地理数据自动化
- 探索 Python 包以获得更多功能
- 处理多边形、shape文件和投影等非典型数据类型
- 理解空间数据科学的图形语法以激发好奇心
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