Where Have All the Prospects Gone?

Rich Majerus

 

 

View slides on your device: https://goo.gl/2DUJCb

Fundraising Work is Spatial

How do you work with spatial data?

Alumni Relations:

We are planning an event in Boston. Can we get a list of all of our rated prospects there? 

New Major Gifts Director:

I want to realign our team's portfolios. How are our prospects distributed across the country?  

Major Gift Officer:

I'm in L.A. and need an extra visit or two. Who should I reach out to? 

# load leaflet library
library(leaflet)

# initialize html widget
# add default map tile
leaflet() %>%
    addTiles()
    

# load tidyverse
library(tidyverse)

# load ipeds data on all four-year colleges
colleges <- read_csv("https://raw.githubusercontent.com/majerus/NEDRA2018/master/four_year_colleges_2017.csv")



# load leaflet library
library(leaflet)

# pipe college data into chain of R functions
colleges %>% 
  # initialize htmlwidget
  leaflet() %>% 
  # add map tile
  addTiles() %>% 
  # add circles to mark the location of each four-year college
  addCircleMarkers()

colleges %>% 
  leaflet() %>% 
  addTiles() %>% 
  addCircleMarkers(
    # add college names as labels that appear on hover    
    label = ~institution.name,
    # cluster markers 
    clusterOptions = markerClusterOptions())
library(ggmap)

geocode("Colby College")


Information from URL: 
http://maps.googleapis.com/maps/api/geocode/json?address=Colby%20College&sensor=false

       lon      lat
 -69.66264 44.56387

lon             lat
-69.66264       44.56387 

type            address
establishment   4000 mayflower hill dr, waterville, me 04901, usa

level_2         level_1
Kennebec County Maine

country         postal_code
United States   04901
geocode(location = "Colby College",
        output = "more",
        source = "google")


leaflet() %>% 
  addTiles() %>% 
  addPopups(lng = -69.66264,
            lat = 44.56387,
            popup = "Colby College!")

Unlocking our Data

with Visualization

Source Data for Visualization

Same Data           Served Data           Shared Data

Approach #1: Same Data

Approach #2: Served Data

R is a free open-source statistical software.

RStudio is an interface to using R.

Shiny transforms R code into web applications 

How this works...

Data

Application Code

Place to deploy apps

What you will need...

Database 

Data warehouse

Excel, json, csv, etc.

 

User interface code

Server code

 

Shinyapps.io 

Open source server

Professional server

RStudio Connect

 

Approach #3: Shared Data

Approach #3: Shared Data

  • Linked interactive visualizations
  • Filtering and personalization capability
  • No server required

Where to go from here...

Rich Majerus

www.richmajerus.com

rmajerus@colby.edu

@richmajerus

Credits

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 smashicons from Flaticon licensed by Creative Commons BY 3.0

 Freepik from Flaticon licensed by Creative Commons BY 3.0

 Freepik from Flaticon licensed by Creative Commons BY 3.0

 Dave Gandy from Flaticon licensed by Creative Commons BY 3.0

 smashicons from Flaticon licensed by Creative Commons BY 3.0

 photos from unsplash.com