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+---
+title: 'Xarray indexes: unleash the power of coordinates'
+date: '2025-06-05'
+authors:
+ - name: Benoît Bovy
+ github: benbovy
+ - name: Scott Henderson
+ github: scottyhq
+summary: 'It is now possible to take full advantage of coordinate data via Xarray explicit and flexible indexes'
+---
+
+_TLDR: Xarray has been through a major refactoring of its internals that makes coordinate-based data selection and alignment more customizable, via built-in and/or 3rd party indexes! In this post we highlight a few examples that take advantage of this new superpower_
+
+## Introduction
+
+Xarray is a large project that is constantly evolving to meet needs of users and stay relevant to work with novel data formats and use-cases. One area of improvement identified in the [Development Roadmap](https://docs.xarray.dev/en/stable/roadmap.html#flexible-indexes) is the ability add new coordinate indexing capabilities beyond the original `pandas.Index`. Let's look at a few examples to understand what is now possible!
+
+TODO: Insert Benoit's awesome schematic from indexing sprint :)
+
+## Alternatives to pandas.Index
+
+Generally-useful index alternatives are already part of Xarray!
+
+### RangeIndex
+
+By default a `pandas.Index` calculates all coordinates and holds them in-memory. There are many use-cases where for 1-D coordinates where it's more efficient to store the start,stop,and step and calculate specific coordinate values on-the-fly. THis is what RangeIndex accomplishes:
+
+```python
+import xarray as xr
+from xarray.indexes import RangeIndex
+
+index = RangeIndex.arange(0.0, 100_000, 0.1, dim='x')
+ds = xr.Dataset(coords=xr.Coordinates.from_xindex(index))
+ds
+```
+
+
<xarray.Dataset> Size: 8MB +Dimensions: (x: 1000000) +Coordinates: + * x (x) float64 8MB 0.0 0.1 0.2 0.3 0.4 ... 1e+05 1e+05 1e+05 1e+05 +Data variables: + *empty* +Indexes: + x RangeIndex (start=0, stop=1e+05, step=0.1)