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Category Archives: Data Science
The popularity of R is rapidly increasing and is well on its way to being a top 10 programming language. The TIOBE index is a standard indicator of the popularity of all programming languages. The TIOBE index confirms that a subset of languages – those for computational statistics and data analysis – are gaining increased attention. The clear winner of the pack is the open source programming language R.
There are many reasons to work with binary data in R. Solar resource data, solar PV performance data, and real-time grid monitoring data are typically stored and transmitted in binary data formats.
In practice, the ability to access binary data in R is impossible in the absence of a vender or format specific “can opener” and a properly configured scientific programming environment. As a result, many business applications often bypass binary data use altogether or, instead, rely on secondary sources and summary statistics with no ability to validate data integrity and accuracy.
The standard function for correlation plots in R is pairs(), which generates a matrix of scatter plots based on all pairwise combinations of variables in a data object. The standard graph looks something like this after a little color enhancement:” Click to enlarge
The code behind this plot is simple:
main = "Anderson's Iris Data",
pch = 21,
bg = c("red", "green2", "steelblue4")[unclass(iris$Species)])