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Monday, December 1, 2014
Book Review: R Object-oriented Programming
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Friday, November 14, 2014
Scatter Plot Matrices in R
One of our graduate student ask me on how he can check for correlated variables on his dataset. Using R, his problem can be done is three (3) ways. First, he can use the cor function of the stat package to calculate correlation coefficient between variables. Second, he can use functions such as pairs (graphics) to visually check possible correlated variables. Third, he can combine the first two approach following the example of vinux in stackoverflow or using ggpairs function of GGally package.
First Approach
Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length 1.0000000 -0.1175698 0.8717538 0.8179411
Sepal.Width -0.1175698 1.0000000 -0.4284401 -0.3661259
Petal.Length 0.8717538 -0.4284401 1.0000000 0.9628654
Petal.Width 0.8179411 -0.3661259 0.9628654 1.0000000
Second Approach
Third Approach
First Approach
Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length 1.0000000 -0.1175698 0.8717538 0.8179411
Sepal.Width -0.1175698 1.0000000 -0.4284401 -0.3661259
Petal.Length 0.8717538 -0.4284401 1.0000000 0.9628654
Petal.Width 0.8179411 -0.3661259 0.9628654 1.0000000
Second Approach
Third Approach
Saturday, August 9, 2014
Book Review: Bioinformatics with R Cookbook
On the other hand, the book is somehow lacking in the
discussion of the basics of R software (i.e. intro to the language and data
type). The book assumes that the readers have already acquired these basic know
how about the language.
Overall, the book is a good reference material especially for
individuals dealing with data on biology and genomics.
Sunday, June 15, 2014
Creating Inset Map with ggplot2
According to wiki.GIS.com one of the reason for using inset map is to provide a reference for an area for unfamiliar readers. Inset map is also considered a great asset for cartographers. Most of the GIS software available in the market have a provision for non-cartographer and beginners to create inset map. However, for R users who are into making maps, creating inset map is a bit challenging. Thanks to the post of Pascal Mickelson and Scott Chamberlain which gave users like me a guide on how to create inset map in R using ggplot2. Below is an example of map with inset created using R.
Monday, June 2, 2014
Social Media Mining with R (Book Review)
The book is useful as complementary material. Major books on social media mining and learning R are still necessary.
Sunday, June 1, 2014
Malawi Animated Rainfall Map
Couple of months ago, Charles Langton Vanya of Malawi contacted me on how to make animated rainfall map in R. I was very busy that I was not able to respond. Anyway, to Mr. Vanya, here is the code you can play on to produce a similar map as below.
Saturday, May 31, 2014
Mindoro Digital Elevation Map Updated
Almost 2 years ago, I made a post on creating digital elevation map using R. For that post, I used the basic R plotting function to create the map. Recently, I started learning to use ggplot2 package for visualizing data. Today, I created the same map that I did two years ago, using raster and gpplot2, its for you guys to tell the difference.
Happy Coding! Use R!
Before
After
Happy Coding! Use R!
Before
After
Labels:
DEM,
ggplot2,
Mapping with R,
Mindoro,
Philippines,
R,
raster
Sunday, March 2, 2014
Introduction to R for Quantitative Finance Introduction to R for Quantitative Finance (Book Review)
For individuals with little background in quantitative methods in finance, the theoretical and application discussion in the start of each chapter provided a good overview and basics of the method being discussed. Also, the problem-solution approached used by the authors added practicality on the used of the book for quantitative analysis. However, for individuals (i.e. finance people) with little R background, the book somehow lacks the basic introduction to the R language and environment commonly found in most R books and tutorials. I think for finance individuals who are R beginners, it will be handy to use this book along with R introductory books/websites (e.g. Instant R, Quick R)
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