The Open Data Blend July 2023 update includes updates to the prescribing dataset, a significant usability enhancement in our dataset UI, and Open Data Blend for Python 1.3.0.

Open Data Blend Datasets

English Prescribing Data for May 2023

We updated the Prescribing dataset with the latest available NHS English Prescribing data including activity up until May 2023.

You can download the data from the Open Data Blend Datasets Prescribing page, analyse it directly in supported BI tools through the Open Data Blend Analytics service, or instantly explore insights through the Pharma Market Insights report.

Floating Table of Contents on Dataset Pages

Some of our datasets have a large collection of data files. To improve the browsing experience, we introduced a floating table of contents that you can use to quickly jump to the sections of interest on a dataset page. A great benefit of this feature is that the sections right at the bottom of the page, like Useful Resources, are now more discoverable.

You can try this feature out right now by browsing through any of our datasets.

Open Data Blend for Python 1.3.0

We released Open Data Blend for Python 1.3.0. This new version introduces the get_data_files function which simplifies the task of getting collections of data files from one of our datasets onto your PC or into your data lake.

Now, with just a few lines of code, you can grab the data files that you need, like in the following example:

import opendatablend as odb
import pandas as pd

dataset_path = 'https://packages.opendatablend.io/v1/open-data-blend-road-safety/datapackage.json'
access_key = '<ACCESS_KEY>'

# Specify the resource names of the data files. In this example, a subset of the available data files will be requested in Parquet format.
resource_names = [
    'date-parquet',
    'time-of-day-parquet',
    'geolocation-parquet',
    'road-safety-accident-info-parquet',
    'road-safety-accident-location-parquet',
    'road-safety-accident-2021-parquet'
    ]

# Get the data files and store the output object
output = odb.get_data_files(dataset_path, resource_names, access_key=access_key)

# Print the file locations
print(output.data_file_names)
print(output.metadata_file_name)

You can learn more about Open Data Blend for Python and how to start using it here.

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