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Data Analytics using R
  -- mapping statistical data: part 1
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Put data to work more effectively.
Certificate in Data Analytics





Visual analysis with ProximityOne tools
click graphic for info; hover to pause

 
visually analyze clients/markets
site analysis using 1 mile radius

S1

$median household income
patterns by census tract - Houston

hover to pause

113th Congressional Districts

Click for info

US Asian Indian population 2010

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geocoded students and school
McKinney ISD, TX

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geocoded students and school
with tax parcels & streets

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high school attendance zones
with schools by type

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%high school graduates by
census tract - Puerto Rico

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Austin, TX MSA counties &
places 10K+ population markers

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Appalachia counties (green) &
coalfield counties (orange)

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China provinces percent urban &
cities (markers) by state plan

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Honolulu census tracts (red)
& census blocks


Central Park area NYC

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Kansas City Metro & Counties
Home Depot locations (markers)

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World Cities; focus on Spain

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Data Analytics Blog
Mapping Statistical Data

Support & Technical Assistance
help using these resources





The world of visual and geospatial analysis continues to morph and evolve. So it is with R's geospatial analysis evolvement.

R (more about R) is an open source language and environment for statistical computing and graphics. R has many similarities with the Statistical Analysis System (SAS), but is free ... and widely used by an ever increasing user base. R is used throughout the ProximityOne Certificate in Data Analytics course.

For now, in the areas of mapping and geospatial analysis, R is best used in a companion role with Geographic Information System (GIS) software like CV XE GIS. Maybe it will always be that way. R's features to 1) perform wide-ranging statistical analysis operations and 2) to process and manage shapefiles and relate those and other data to many, many types of data structures are among R's key strengths.

Mapping with R
The following Web-based interactive map has been developed totally using R. Aside from satellite imagery, which can be added, this application has the look and feel of a Google maps application. Yet the steps to develop the application are far different and much closer to more traditional GIS software and data structures .. and there are no proprietary constraints. Mapping with R is not a geospatial panacea. See these considerations & FAQs. Join us in weekly Data Analytics Lab sessions to learn about developing this type of mapping application and geospatial analysis. See more about this application in narrative below the map.

Create & publish this interactive map or variation - details below