Interact with the 'Google Tag Manager' API <https://developers.google.com/tag-platform/tag-manager/api/v2>, enabling scripted deployments and updates across multiple tags, triggers, variables and containers.

Create geographically referenced traffic data from the Google Maps JavaScript API <https://developers.google.com/maps/documentation/javascript/examples/layer-traffic>.

R interface to Google's chart tools, allowing users
    to create interactive charts based on data frames. Charts
    are displayed locally via the R HTTP help server. A modern
    browser with an Internet connection is required. The data 
    remains local and is not uploaded to Google.

Provides a mechanism to plot a 'Google Map' from 'R' and overlay
    it with shapes and markers. Also provides access to 'Google Maps' APIs,
    including places, directions, roads, distances, geocoding, elevation and
    timezone.

Seamless integration between R and 'Goose' AI capabilities
    including memory management, visualization enhancements, and workflow
    automation. Save R objects to 'Goose' memory, apply Block branding to
    visualizations, and manage data science project workflows. 
    For more information about 'Goose' AI, see <https://github.com/block/goose>.

Implementation of multilayered visualizations for enhanced
    graphical representation of functional analysis data. It combines and integrates
    omics data derived from expression and functional annotation enrichment
    analyses. Its plotting functions have been developed with an hierarchical
    structure in mind: starting from a general overview to identify the most
    enriched categories (modified bar plot, bubble plot) to a more detailed one
    displaying different types of relevant information for the molecules in a given
    set of categories (circle plot, chord plot, cluster plot, Venn diagram, heatmap).

Informal implementation of some algorithms from Graph
  Theory and Combinatorial Optimization which arise in the subject
  "Graphs and Network Optimization" from first course of the EUPLA
  degree of Data Engineering in Industrial Processes.