Data analysis pipelines to investigate distinct user journey behaviour across GOV.UK:
Visualisation displaying entry and exit data of a GOV.UK page of interest, over a date range and device category(ies). This data is broken down further by internal/external links, and the individual entry/exit pages paired with the count and proportion of page views. Answers the question, ‘In regards to page X, which page have users come from, and which page do they go to next?’
A CSV file presenting the previous page paths that reached a GOV.UK page of interest, over a date range and device category(ies). The count and proportion of sessions visiting distinct, subsetted journeys are compiled together, and returned as a sorted list in descending order. Answers the question, ‘Which pages do users visit before arriving at page X?’
A CSV file presenting the following page paths that reached a GOV.UK page of interest., over a date range and device category(ies). The count and proportion of sessions visiting distinct, subsetted journeys are compiled together, and returned as a sorted list in descending order. Answers the question, ‘Which pages do users visit following page X?’
Getting started
⚠️ This repository is for version control purposes only. You are expected to run the notebooks in
Google Colab! For further information, see the Background section.
To run the tools, make sure you meet the requirements first, and then follow the tool’s README instructions detailed in here.
Requirements
The following are the minimum requirements to use all tools:
- Access to Google Colab
- Access rights to your Google BigQuery dataset of choice
If you would like to contribute to this project, see the Contributing section.
Background
Google Colab is a new research project from Google, which allows you to run Jupyter notebooks in a
cloud environment at no extra cost. Jupyter Notebook in turn is an open-source web application that allows
for the creation of documents with live code, which can be run to generate results on-the-fly. Data scientists at GDS
are regular uses of Jupyter notebooks, as they can use them to clean data, test out new ideas and fine tune existing
models.
Licence
Unless stated otherwise, the codebase is released under the MIT License. This covers
both the codebase and any sample code in the documentation. The documentation is ©
Crown copyright and available under the terms of the Open Government 3.0 licence.
Contributing
If you want to help us build, and improve these tools, view our contributing guidelines.
Acknowledgements
This project structure is based on the govcookiecutter template project.