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awesome-react-components

Curated List of React Components & Libraries.

awesome-rshiny

An awesome R-shiny list!

awesome-shiny-apps-for-statistics

🌟 A curated list of Awesome Shiny Apps for Statistics (ASAS)🌟

awesome-shiny-extensions

🐝 Awesome R packages that offer extended UI or server components for the R web framework Shiny

bs4dash-demo

bs4Dash demo as presented in the One Package Per Meetup Series at the R User Group Tunis

ccdr-world-bank

The repo maintains the code for CCDR shiny dashboard

census-with-r-book

Source for Analyzing US Census Data: Methods, Maps, and Models in R by Kyle Walker, forthcoming with CRC Press

coronavirus-data

covid19-event-risk-planner

COVID19 risk planner R-Shiny application

demo-shiny-modules

A demo of and argument for using Shiny modules even for simple Shiny applications

devptipack

dhs-analysis-code

dhs-indicators-r

R code to produce Demographic and Health Survey Indicators

dhs-indicators-stata

Stata code to produce Demographic and Health Survey Indicators

dime-r-training

Dime Analytics R Training

eduanalyticstoolkit

EduAnalytics Team Toolkit for Data Management, Documentation and Analytics

geo4dev-ct-map

crop type mapping

glad

Global Learning Assessment Database: a collection of harmonized learning assessments datasets at the student and country level.

golemtest

golemtest

hlo_glads

GLADs for assessments in HLO but not in LP

italy_dash

A summary dashboard of the covid19 cases in Italy

kp_servicesaccessibility

Services accessibility analyses of Khyber Pakhtunkhwa

learningpoverty

Learning Poverty: an indicator with global coverage that combines schooling and learning.

monthapp

testing shinyr package

pakeducationdashboard

Pakistan Education Dashboard

people-analytics-rstats

peskas.timor.portal

Peskas web app for East Timor

rainfall_conflcits

Analysis of manuscript "The impact of rainfall variability on conflict outbreaks at the monthly level

regression

This application constitutes a didactic modeling process. The user can try to perform a linear regression model based on the ordinary least squares method step by step. The application addresses a safety problem in the rural areas of Antioquia - Colombia. Through variables related to education, sport and safety itself, we seek to obtain a statistically valid model with a good adjusted R squared.

shiny-examples