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Discover the world with Google Maps. Experience Street View, 3D Mapping, turn-by-turn directions, indoor maps and more across your devices.

When using shiny in production, often you will want to have some sort of database interactions for storing and accessing data. The DBI package provides an easy way to do the database interactions with a variety of SQL database flavors. In this example, I’m going to use a SQLite ...

[Disclaimer] The package presented in this blog post is stillexperimental at the time of writing these lines (2021-02-28), so itmight face some API changes in the future.Yesterday Jacqueline’s tweeted about her need to add POST requests toa {shiny} application.I'm astounded that it doesn't seem like a Shiny app is able to acceptPOST requests. I have data I wanna pass to my server :/— Dr. Jacqueline Nolis (@skyetetra)February27, 2021This is actually one of the things I had in mind when building{brochure}: more flexibility with the HTTP requests and how they arehandled.So here is a working ex...

When using shiny in production, often you will want to have some sort of database interactions for storing and accessing data. The DBI package provides an easy way to do the database interactions with a variety of SQL database flavors. In this example, I’m going to use a SQLite in memory database for reproducibility. In practice, you will just switch to the code to use a persistent database. Let’s start by creating a table to right to.

In this guide you’ll find both original content and curated resources to: + Build R shiny apps from scratch + Select the optimal dashboard framework for your R shiny app dashboard + R packages to build interactive, professional quality data visualization + Improve the user experience and dashboard speed tricks + All the ways you can deploy and share R shiny app dashboards + Lessons from a dashboard veteran for better R shiny app dashboards

"R in Production " is a blog that talks about Security, Automation, Scalability in the R environment. Furthermore, Software Engineering teaches us proven methodologies to bring a prototype into production and to facilitate the work process in all its aspects. (Click on the title to read more ...)

Véritables outils de visualisation des données, les tables interactives permettent de trier, colorer, éditer, rechercher, paginer les données

In this guide you’ll find both original content and curated resources to: + Build R shiny apps from scratch + Select the optimal dashboard framework for your R shiny app dashboard + R packages to build interactive, professional quality data visualization + Improve the user experience and dashboard speed tricks + All the ways you can deploy and share R shiny app dashboards + Lessons from a dashboard veteran for better R shiny app dashboards

SQL. Contribute to Uppalapa/Database-Projects development by creating an account on GitHub.

2.1. Introduction This chapter provides an overview of how to use SQL to perform simple operations. This tutorial is only intended …

Read this e-book to learn how to deploy, scale, orchestrate, and manage containerized applications using Kubernetes with Docker.

This course will teach you how to analyse and model spatial data using R.

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 …

Build native Windows & macOS apps with Javascript and React

A framework for building native Windows apps with React. - microsoft/react-native-windows

validate your data and create nice reports straight from R - Appsilon/data.validator

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.

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.

We continue our series of articles about MVP development. Today we would like to tell you about 10 steps to build an MVP in details.