pydata/xarray
Xarray
Xarray este o bibliotecă Python pentru array-uri multidimensionale și un framework pentru seturi de date etichetate. Extinde structura de date NumPy prin adăugarea de etichete la array-uri, permițând organizarea datelor complexe N-dimensionale folosind dimensiuni și coordonate denumite.
Biblioteca oferă o interfață de date NetCDF pentru citirea și scrierea formatelor de date științifice precum NetCDF și Zarr. Permite calculul științific pe array-uri prin menținerea relației dintre date și coordonatele fizice în timpul operațiunilor matematice.
Proiectul acoperă analiza datelor multidimensionale, manipularea datelor geospațiale și procesarea datelor climatice. De asemenea, suportă analiza seriilor temporale pentru gestionarea secvențelor de observații în timp.
Features
- Labeled Array Management - Provides a framework for organizing multidimensional datasets using named dimensions and coordinates to avoid integer indexing.
- Labeled Dataset Aggregations - Groups multiple labeled arrays into a single container using a shared set of coordinates and global attributes.
- Labeled Dataset Frameworks - Provides a system for organizing complex multidimensional data with metadata and coordinate-based alignment.
- Dimension Coordinate Mapping - Maps named dimensions to integer axis indices to automate coordinate alignment and array slicing.
- Multidimensional Arrays - Enables analysis of large arrays of data using named dimensions and labels instead of raw integer indexing.
- Scientific Computing - Performs mathematical operations on labeled N-dimensional arrays while maintaining the relationship between data and physical coordinates.
- N-Dimensional Array Libraries - Provides a library for managing labeled N-dimensional arrays and datasets using named dimensions and coordinates.
- NumPy Array Integration - Uses NumPy arrays as the underlying data container to leverage efficient contiguous memory and vectorised operations.
- Labeled Array Extensions - Extends the NumPy data structure by adding labels to arrays to simplify indexing and data analysis.
- Deferred Computation Integration - Wraps Dask arrays to defer computation until a result is explicitly requested.
- Time Series Analysis - Manages sequences of multidimensional observations over time, allowing for easy resampling and alignment of temporal data.
- Array Broadcasting - Implements array broadcasting to automatically align datasets by matching labels across dimensions during arithmetic operations.
- Climate Data Processing - Handles complex atmospheric or oceanic datasets that use coordinates like latitude, longitude, and time.
- Geospatial Data Manipulation - Works with spatially referenced grids and datasets to slice, dice, and align data based on geographic coordinates.
- Scientific Data Export Formats - Provides a data interface for reading and writing scientific data formats such as NetCDF and Zarr.
- Data Containers - N-dimensional labeled arrays and datasets for complex data.
- Data Manipulation - Multidimensional data selection and analysis.
- Data Processing Libraries - N-dimensional array structures with labeled dimensions.
