Introduction
Learn about Tilebox Datasets
Time series datasets refer to datasets where each data point is linked to a timestamp. This format is common for data collected over time, such as satellite data.
This section covers:
Available Datasets
Discover available time series datasets and learn how to list them.
Common Fields
Understand the common fields shared by all time series datasets.
Collections
Learn what collections are and how to access them.
Loading Data
Find out how to access data from a collection for specific time intervals.
For a quick reference to API methods or specific parameter meanings, check out the complete time series API Reference.
Terminology
Get familiar with some key terms when working with time series datasets.
Creating a datasets client
Prerequisites
After meeting these prerequisites, you can create a client instance to interact with Tilebox Datasets.
You can also set the TILEBOX_API_KEY environment variable to your API key. You can then instantiate the client without passing the token argument. Python will automatically use this environment variable for authentication.
Tilebox datasets provide a standard synchronous API by default but also offers an asynchronous client if needed.
Exploring datasets
After creating a client instance, you can start exploring available datasets. A straightforward way to do this in an interactive environment is to list all datasets and use the autocomplete feature in your Jupyter notebook.
The Console also provides an overview of all available datasets.
Errors you might encounter
AuthenticationError
AuthenticationError occurs when the client fails to authenticate with the Tilebox API. This may happen if the provided API key is invalid or expired. A client instantiated with an invalid API key won’t raise an error immediately, but an error will occur when making a request to the API.
Next steps
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