Producing a map with 5 lines of code

Over the past year, I have been exploring the geospatial capabilities of various R packages.  Today, I want to share the most basic of geospatial capabilities, which is producing a map.  Using R, you can do this in just 5 lines of code.

Let's produce a map of Boston, Massachusetts.  Boston has a longitude of -71.0588801 and a latitude of 42.3600825.  Since we list x and y coordinates in order (i.e. we list y after x), we list longitude (the horizontal coordinate) before latitude (the vertical coordinate).  Let's create our map!

Code line 1:


This command installs the ggmap package in your R environment.

Code line 2:


This command loads the ggmap package in your R environment.

Code line 3:

boston <- c(lon = -71.0588801, lat = 42.3600825)

This line creates a variable called "boston" and assigns the lon and lat coordinates in it.

Code line 4:

boston_map <- get_map(boston, zoom = 13, scale = 1)

This line creates a varia…

IBM SPSS and Entity Analytics at work


Testing Senzing's Entity Resolution Workbench

I have the great honor of knowing ex-IBM Fellow Jeff Jonas, the co-Founder, CEO and Chief Scientist of Senzing.  Apart from being exceptionally talented, Jeff is also an amazing human being who is always willing to help others.  I have personally been the beneficiary of his generosity and continue to benefit from his counsel every day.  Jeff is one of the main reasons why I have chosen to follow a technical career path at IBM.

Jeff left IBM in 2016 to start a new venture called Senzing.  Senzing has built the first real-time AI software product for Entity Resolution (ER), a space that Jeff is the world's #1 expert in.  Senzing's new offering has huge implications in the post-GDPR world and has the potential to increase trust in Blockchain networks.  Jeff recently gave a keynote at the IBM Think conference where he described what Senzing does and its potential applications (including as part of IBM Blockchain).  I strongly recommend watching it.

When I spoke with Jeff yesterda…

Watson Analytics, SPSS Modeler and Esri ArcGIS


Visualization of the 1854 London Cholera Outbreak

This post attempts to visualize the 1854 London Cholera Outbreak based on data collected by Dr. John Snow and provided in the HistData R package. Dr. Snow was able to identify that cholera was a water borne disease by visualizing his data in 1854 and was able to bring the Cholera outbreak to an end. This dataset and analysis speaks to power of geospatial data and its importance in decision making.

What caused the Challenger disaster?

The motivation for this blog is to examine the reasons behind the explosion of the USA Space Shuttle Challenger on 28 January, 1986. The night before the launch a decision had to be made regarding launch safety and engineers recommended that the launch be postponed in the event the temperature at launch was below freezing as this adversely impacted the integrity of O-rings, a key component holding in field joints. The engineers advice was ignored and disaster ensued. Let's dive in!

Regression in R

My latest publicly available R notebook created in IBM's Data Science Experience is here!  This notebook provides a tutorial on:

This notebook covers:
Fitting and interpreting linear models;Evaluating model assumptions; andSelecting among competing models.I hope you enjoy this notebook.  Please feel free to share and let me know your thoughts.

My latest notebook: Regression in R h/t — Venky Rao (@VRaoRao) October 15, 2017