Amazon FinSpace Examples.

This repository contains example notebooks and python scripts that show how to work with Amazon FinSpace.

Examples

Notebooks: Inside Amazon FinSpace

These notebooks are intended to be run from the FinSpace managed notebook environment. Notebooks will reference a dataset (and others a permission group as well) found in FinSpace, be sure you have entered the empty identifiers for dataset_id, view_id, and basicPermissionGroupId found in your environment installation. All example notebooks assume that the Capital Markets Sample Data bundle was installed with the FinSpace environment. Some example notebooks make use of Utility classes found in the Utilities folder (e.g. finspace.py and finspace_spak.py) be sure to have run the '%load' for the python files twice, first to load the file contents into the notebook, and a second time to ensure the code is run and pushed onto your Spark cluster.

Analyzing petabytes of trade and quote data with Amazon FinSpace shows how to use the FinSpace Time Series Library.
Cluster Management demonstrates using the cluster management APIs from within a notebook.
Collect Timebars and Summarize demonstrates how to create a summary time-bar dataset and add it to FinSpace.
Compute and Plot Volatility from TAQ demonstrates how to compute and plot volatility using the FinSpace Time Series Libraries.
Technical Indicators demonstrates the creation of a Spark DataFrame that uses all the FinSpace technical indicators.
S3 Import shows how to import data from an external (to FinSpace) S3 bucket into a FinSpace dataset
Using Third Party APIs shows how you can install and use third party APIs from FinSpace
Custom Calendars shows how you can create a custom calendar for the time series fill and filter stage

Python: Helper Code

Utility Classes facilitates the use of the FinSpace APIs.

Blogs

Analyze daily trading activity using transaction data from Amazon Redshift in Amazon FinSpace
How to connect Amazon FinSpace to a Redshift cluster, import tables into FinSpace datasets, and pull data in tables from Redshift directly into Spark DataFrames.

Webinars

Making Financial Data More Accessible in the Cloud
Notebooks used to demonstrate integration of Snowflake tables with Amazon FinSpace. Presented at Snowflake Financial Services Summit Sept 14, 2021: Making Financial Data More Accessible in the Cloud

FAQ

How do I contribute my own example notebook?

Although we're extremely excited to receive contributions from the community, we're still working on the best mechanism to take in examples from external sources. Please bare with us in the short-term if pull requests take longer than expected or are closed.

License

This library is licensed under the MIT-0 License. See the LICENSE file.

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