NHL Stats - Regular Season 2013/2014
Legends, Stars and Bench-Warmers....
OVERVIEW - these visualizations are created in R Programming Language and use a specific library (Kohonen) that is developed to ingest data sets and visualize the data. Self Organizing Maps.
and with commentary...
## R Source Code - Ryan Anderson - Dream to Learn - May 1st 2014
## Playing around with supervised pattern recognition, and self organizing maps
## Figured NHL player stats could be interesting (and can check if the viz is 'meaningful')
# Load the kohonen package
setwd("C:/Users/Home/Documents/DTL Data Viz Community/Canada")
players <- read.csv("HockeyStats2014CSV.csv")
## data source: http://sports.yahoo.com/nhl/stats/byposition?pos=C,RW,LW,D&conference=NHL&year=season_2013&qualified=1
## or here https://drive.google.com/file/d/0BwjxYjWyopXhWVM0N19zSExINzA/edit?usp=sharing (CSV)
## and with player names and teams https://drive.google.com/file/d/0BwjxYjWyopXhUWlHcGJzdS1ZVEk/edit?usp=sharing
players.sc <- scale(players)
players.som <- som(players.sc, grid = somgrid(10, 6, "hexagonal"))
plot(players.som, main = "NHL Player Stats - 2013/2014 - Regular Season")
-- end of code
Here is what data looked like on Yahoo Stats board - I removed the player name and team, and a few columns in CSV..
## From Kohonen library PDF Abstract...
# "In this age of ever-increasing data set sizes, especially in the natural sciences, visualisation
# becomes more and more important. Self-organizing maps have many features
# that make them attractive in this respect: they do not rely on distributional assumptions,
# can handle huge data sets with ease, and have shown their worth in a large number of
# applications. We highlight the kohonen package for R, which implements
# self-organizing maps and extensions for supervised pattern recognition and data fusion.
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Created: July 25, 2014Englishfrançais