Collections
Learn about time series dataset collections
Collections group data points within a dataset. They help represent logical groupings of data points that are commonly queried together. For example, if your dataset includes data from a specific instrument on different satellites, you can group the data points from each satellite into a collection.
Overview
This section provides a quick overview of the API for listing and accessing collections. Below are some usage examples for different scenarios.
Method | API Reference | Description |
---|---|---|
dataset.collections | Listing collections | List all available collections for a dataset. |
dataset.collection | Accessing a collection | Access an individual collection by its name. |
collection.info | Collection information | Request information about a collection. |
Refer to the examples below for common use cases when working with collections. These examples assume that you have already created a client and listed the available datasets.
Listing collections
To list the collections for a dataset, use the collections
method on the dataset object.
dataset.collections returns a dictionary mapping collection names to their corresponding collection objects. Each collection has a unique name within its dataset.
Accessing individual collections
Once you have listed the collections for a dataset using dataset.collections(), you can access a specific collection by retrieving it from the resulting dictionary with its name. Use collection.info() to get details (name, availability, and count) about it.
You can also access a specific collection directly using the dataset.collection method on the dataset object. This method allows you to get the collection without having to list all collections first.
Errors you may encounter
NotFoundError
If you attempt to access a collection with a non-existent name, a NotFoundError
is raised. For example:
Next steps
Was this page helpful?