Interactive Maps with leaflet in R
Learn how to produce interactive web maps with ease using leaflet.Start Course for Free
4 Hours16 Videos55 Exercises12,898 Learners4500 XPInteractive Data Visualization in R TrackSpatial Data with R Track
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Get ready to have some fun with maps! Interactive Maps with leaflet in R will give you the tools to make attractive and interactive web maps using spatial data and the tidyverse. In this course, you will create maps using the IPEDS dataset, which contains data on U.S. colleges and universities. Along the way, you will customize our maps using labels, popups, and custom markers, and add layers to enhance interactivity. Following the course, you will be able to create and customize your own interactive web maps to reveal patterns in your data.
Setting Up Interactive Web MapsFree
Chapter 1 will introduce students to the htmlwidgets package and the leaflet package. Following this introduction, students will build their first interactive web map using leaflet. Through the process of creating this first map students will be introduced to many of the core features of the leaflet package, including adding different map tiles, setting the center point and zoom level, plotting single points based on latitude and longitude coordinates, and storing leaflet maps as objects. Chapter 1 will conclude with students geocoding DataCamp’s headquarters, and creating a leaflet map that plots the headquarters and displays a popup describing the location.Introduction to leaflet50 xpLoading the leaflet Library50 xpCreating an Interactive Web Map100 xpMap Tiles50 xpProvider Tiles100 xpAdding a Custom Map Tile100 xpSetting the Default Map View50 xpA Map with a View I100 xpA Map with a Narrower View100 xpPlotting DataCamp HQ50 xpMark it100 xpAdding Popups and Storing your Map100 xp
In chapter 2 students will build on the leaflet map they created in chapter 1 to create an interactive web map of every four year college in California. After plotting hundreds of points on an interactive leaflet map, students will learn to customize the markers on their leaflet map. This chapter will also how to color code markers based on a factor variable.Introduction to IPEDS Data50 xpCleaning up the Base Map100 xpExploring the IPEDS Data50 xpExploring the IPEDS Data II100 xpMapping California Colleges50 xpCalifornia Colleges100 xpThe City of Colleges100 xpCircle Markers100 xpLabels and Pop-ups50 xpMaking our Map Pop100 xpWhat is California's Northernmost College?50 xpBuilding a Better Pop-up100 xpSwapping Popups for Labels100 xpColor Coding Colleges50 xpCreating a Color Palette using colorFactor100 xpA Legendary Map100 xp
Groups, Layers, and Extras
In chapter 3 students will expand on their map of all four year colleges in California to create a map of all American colleges. First, in section 3.1 students will review and build on the material from Chapter 2 to create a map of all American colleges. Then students will re-plot the colleges on their leaflet map by sector (public, private, or for-profit) using groups to enable users to toggle the colleges that are displayed on the map. In section 3.3 students will learn to add multiple base maps so that users can toggle between multiple map tiles.The Leaflet Extras Package50 xpMiddle America100 xpBuilding a Base100 xpDown South50 xpOverlay Groups50 xpMapping Public Colleges100 xpMapping Public and Private Colleges100 xpMapping All Colleges100 xpBase Groups50 xpChange up the Base100 xpPutting it all Together100 xpPieces of Flair50 xpAdding a Piece of Flair100 xpA Cluster Approach100 xp
In Chapter 4 students will learn to map polygons, which can be used to define geographic regions (e.g., zip codes, states, countries, etc.). Chapter 4 will start by plotting the zip codes in North Carolina that fall in the top quartile of mean family incomes. Students will learn to customize the polygons with color palettes and labels. Chapter 4 will conclude with adding a new layer to the map of every college in America that displays every zip code with a mean income of $200,000 or more during the 2015 tax year. Through the process of mapping zip codes students will learn about spatial data generally, geoJSON data, the @ symbol, and the addPolygons() function. Furthermore, students will have an opportunity to practice applying many of the options that they learned about in the previous chapters, such as popups and labels, as well as new ways to customize their maps, such as the highlight option in addPolygons().Spatial Data50 xpIntroduction to Spatial Data100 xpExploring Spatial Data100 xpJoining Spatial Data100 xpMapping Polygons50 xpaddPolygons() Function100 xpNC High Income Zips100 xpaddPolygon() Options100 xpLet's do some Logging100 xpPutting it All Together50 xpWealthiest Zip Codes in America100 xpFinal Map100 xpThank you!50 xp
In the following tracksInteractive Data Visualization in RSpatial Data with R
DatasetsIPEDS All 4-Year CollegesNC Zipcode Income dataNC Zipcode PolygonsAmerica's Wealthiest Zipcodes
PrerequisitesIntroduction to the Tidyverse
Assistant Vice President at Colby College
Rich Majerus is Assistant Vice President of Donor Relations and Advancement Strategy at Colby College. At Colby, he develops new approaches to modeling and visualizing fundraising data. He regularly teaches R workshops and is listed in RStudio’s directory of instructors. Prior to his work at Colby, Rich was a founder of Third Coast Analytics, a successful and profitable data science consulting firm (Third Coast’s IP was acquired by Capture Higher Ed in 2016).
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