Introduction to Maps in R Shiny and Leaflet
What you'll learn
- R Programming
- Web Mapping
- Web GIS Programming
- Working with dataframes
- Web mapping with the Leaflet library
- Building a GIS application
- Little or no understanding of GIS
- Basic understanding of dataframes
- Very basic understanding of programming
- Very basic understanding of R programming
- Be able to install and setup R Studio
Welcome to the Introduction to Maps in R Shiny and Leaflet course. In this course we will be
creating a fully functional web gis application using the R programming language. This application
will be comprised of different types of maps ranging from point maps to heatmaps, to choropleth maps.
We will also be using different datasets ranging from dataframes to spatial dataframes, which we
will use to transform and visualize our data on different types of maps, depending on the use case.
Once we have completed the course we will be equipped with extremely valuable skills, that we can
use to build sophisticated web map applications of any kind and tell spatial data stories that almost anyone
can interpret and understand.
Some of the skills you will acquire from taking this course range from:
Working with spatial data in the R programming language
Installing and using R studio
Using the leaflet web mapping library
Creating a variety of maps and integrating it into a single application
Building a dashboard in R Shiny
Creating map legends and colour palettes
Styling maps using embedded html functions
Working with dataframes
Using R terminal operations
Who this course is for:
- R programmers at any level
- GIS Developers at any level
- Developers at any level
- An interest in spatial data story telling through Maps
- Anyone who wants to learn GIS programming using R
- The curious mind
Big Data Engineering and Consulting, involved in multiple projects ranging from Business Intelligence, Software Engineering, IoT and Big data analytics. Expertise are in building data processing pipelines in the Hadoop and Cloud ecosystems and software development.
Currently consulting at one of the top business intelligence consultancies helping clients build data warehouses, data lakes, cloud data processing pipelines and machine learning pipelines. The technologies he uses to accomplish client requirements range from Hadoop, Amazon S3, Python, Django, Apache Spark, MSBI, Microsoft Azure, SQL Server Data Tools, Talend and Elastic MapReduce.