> For the complete documentation index, see [llms.txt](https://docs.os.uk/more-than-maps/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.os.uk/more-than-maps/using-os-mapping-apis/using-os-apis-with-epc-api.md).
# Using OS APIs with EPC API
This tutorial, using the python notebook below, is to help with using various OS APIs in python to access Ordnance Survey data. To ensure that multiple OS APIs are used, the notebook has been created with a use case of obtaining Energy Performance Certificates for properties in a specified postcode and visualising these on a map with their building footprints.
Example output from using the python notebook code
{% file src="/files/BHGm8wWLEbRum7jAbE7f" %}
This will show you how to obtain address data with EPC ratings from the OS Places API and EPC Domestic Rates API, TOIDs for these addresses using the OS Linked Identifiers API, obtaining building footprints (building\_part) using the OS NGD Features API and finally visualising these building footprints which are colour coded based on their energy performance rating on an OS basemap using the OS Maps API.
## What will be needed to use this:
* A Premium OS Datahub account – OS API Key
* An EPC Domestic Rates API Key
* A specified postcode that you would like to view
* Python installed on your machine
* The following python libraries to be installed to your environment:
* Json
* GeoPandas
* Pandas
* Requests
* Time
* Warnings
* OS
* Folium
* Matplotlib
## Disclaimers
Please note that OS API throttling may cause errors in this notebook. To avoid these errors, then specify a postal code with less 600 or less addresses (unless you have different access). For further information on OS API throttling please visit [here](https://osdatahub.os.uk/support/plans#apiThrottling).
This is for domestic rates only; therefore commercial property EPC ratings will not be returned
---
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