Multi-dimensional Data Analysis with Xarray
18. Multi-dimensional Data Analysis with Xarray
18.2. Learning Objectives
18.3. Understanding Xarray’s Data Model
18.3.1. Core Data Structures
18.3.2. Why This Structure Matters
18.4. Setting Up Your Environment
18.4.1. Installing Required Packages
18.4.2. Importing Libraries and Configuration
18.5. Loading and Exploring Real Climate Data
18.5.1. Loading Tutorial Data
18.6. Working with DataArrays
18.6.1. Accessing DataArrays from Datasets
18.6.2. Exploring DataArray Components
18.7. Intuitive Data Selection and Indexing
18.7.1. Label-Based Selection
18.7.2. Time Range Selection
18.7.3. Nearest Neighbor Selection
18.9. Data Visualization with Xarray
18.9.1. Plotting 2D Spatial Data
18.9.2. Customizing Spatial Plots
18.9.3. Time Series Visualization
18.10. Working with Datasets: Multiple Variables
18.10.1. Exploring Dataset Structure
18.10.2. Dataset-Level Operations
18.11. The Power of Label-Based Operations
18.11.1. The NumPy Approach: Index-Based Selection
18.11.2. The Xarray Approach: Label-Based Selection
18.12. Advanced Indexing Techniques
18.12.1. Position-Based vs. Label-Based Indexing
18.12.2. Boolean Indexing and Conditional Selection
18.13. High-Level Computational Operations
18.13.1. GroupBy Operations for Temporal Analysis
18.13.2. Rolling Window Operations
18.13.3. Weighted Operations
18.17. Exercises
18.17.1. Exercise 1: Exploring a New Dataset
18.17.2. Exercise 2: Data Selection and Indexing
18.17.4. Exercise 4: GroupBy and Temporal Analysis
18.17.5. Exercise 5: Data Storage and Retrieval
