Support for simple features, a standardized way to encode spatial vector data. Binds to GDAL for reading and writing data, to GEOS for geometrical operations, and to PROJ for projection conversions and datum transformations. Optionally uses the s2 package for spherical geometry operations on geographic coordinates.
Interactive Viewing of Spatial Data in R • mapview
Quickly and conveniently create interactive visualisations of spatial data with or without background maps. Attributes of displayed features are fully queryable via pop-up windows. Additional functionality includes methods to visualise true- and false-color raster images and bounding boxes.
Critical features for your website: design and development
Critical features for your website: design and development. When designing a new product we pay a lot of attention to the effectiveness of the web service.
The concept of containerization itself is pretty old. But the emergence of the Docker Engine in 2013 has made it much easier to containerize your applications. According to the Stack Overflow Developer Survey - 2020, Docker is the #1 most wanted platform, #2 most loved platform, and also the #3
What are my hybrid and multicloud deployment options with Anthos?
Anthos is a managed application platform that extends Google Cloud services and engineering practices to your environments so you can modernize apps faster and establish operational consistency across them. Anthos offers multiple deployment options to choose from, depending on where your infrastructure and applications live today. In this article we are outlining the Anthos deployment options.
Developing a complex R Shiny app – the good, the bad and the ugly | WZB Dat
Together with Clara Bicalho (UC Berkeley) and Sisi Huang (WZB), I recently developed a web application that acts as a convenient interface to the DeclareDesign R package and its repository of resea…
In this article, we'll examine how Blue Oceans are created and how your organization can create Blue Oceans with Data Science too. We'll finish with a roadmap for your organization to build Blue Oceans with Data Science.
Debugging in R: How to Easily and Efficiently Conquer Errors in Your Code
When you write code, you’re sure to run into problems from time to time. Here are some advanced tips and tricks for handling these errors, explained accessibly.
Building a Strong Data Science Team from the Ground Up
Business is changing as a result of the increasing quantity and variety of data available. Significant new opportunities can be realized by harnessing the knowledge contained in these data - if you know where to look. A data science team can help to bring raw data through the analysis process and derive insights that …
In this article we look at how to build a shiny app with clear code, reusable and automatically tested modules. For that, we first go into the package structure and testing a shiny app before we focus on the actual modules.
No Framework, No Problem! Structuring your project folder and creating cust
Pedro Coutinho Silva is a software engineer at Appsilon Data Science. It is not always possible to create a dashboard that fully meets your expectations or requirements using only existing libraries. Maybe you want a specific function that needs to be custom built, or maybe you want to add your own style or company branding. Whatever the case, a moment might come when you need to expand and organize your code base, and dive into creating a custom solution for your project; but where to start?