No Clocks

Microsoft Azure Management Portal

This is a tutorial post about building a webapp with user form and leaflet map visualization using R Shiny. The webapp I built aims to collect crowdsourced data of how sustainable are the eateries …

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Shiny is a package that makes it easy to create interactive web apps using R and Python.

MapX, an online platform for managing geospatial data on natural resources

Paths contain responses. When 200 responses are available, use those to define a parser function. Specs might (probably will) be repeated, so refine to just one copy of each. Names will have to be ...

Use response examples to build "mocked" responses for use in tests. While implementing this I'll have to figure out what to do about args. Some set of standard args (by type) that I encourage users...

So far I've had to do manual work to cleanly parse responses. Document that process. It's POSSIBLE the result of this ticket will actually be functionality to implement this automatically, but righ...

Provides an extensible framework for the efficient calculation of auto- and cross-proximities, along with implementations of the most popular ones.

Enhance your CRE and development business with a lightweight Zoning API. Access robust Zoning information in our comprehensive developer portal to maximize ROI

Power your real estate applications with our property data API, which gives you instant access to nationwide property and rental data in the US.

Exponentially faster builds for everyone.

Upload, download, and edit internet maps with the Felt API (). Allows users to create new maps, edit existing maps, and extract data. Provides tools for working with layers, which represent geographic data, and elements, which are interactive annotations. Spatial data accessed from the API is transformed to work with sf.

A convenient logger for R, shiny, and plumber.

R wrapper for styler

Provides a minimal R and C++ API for parsing well-known binary and well-known text representation of geometries to and from R-native formats. Well-known binary is compact and fast to parse; well-known text is human-readable and is useful for writing tests. These formats are useful in R only if the information they contain can be accessed in R, for which high-performance functions are provided here.