Category Archives: Learn R

R Script to Build Animation of Arctic Sea Ice Extent – Update 12/20/13

In my previous post I showed an animation of Arctic Sea Ice Extent from the 1980′s through August, 2012 (link).  In this post, I show how to build this Arctic Sea ice Extent  animated chart.

Source Data

The Arctic Ice Sea Monitor (link)   updates their daily csv file with the latest satellite based arctic sea ice measurements.  Here is the daily csv file link.

R script

To develop my animation of the daily Arctic Sea Ice extent, I decided to produce a plot for each year that showed the current year in red and the previous years in grey.  I go this idea from Tamino at Open Mind.

Here is my R script:
Be sure to set your working directory to appropriate location!!

library(animation)
  ani.options(convert=shQuote('C:\\Program Files (x86)\\ImageMagick-6.7.9-Q16\\convert.exe'))
## Use setwd() to specify directory where you want png images to be saved
  setwd("<strong>C:\\R_Home\\Charts & Graphs Blog\\RClimateTools\\Arctic_sea-ice_extent</strong><em>")
# use png_yn to toggle between plot output to png file or screen
  png_yn <- "y"
# Establish chart series patterns and colors to be able to distinguish current yr from previous years in plot
  pattern <- c(rep("dashed", 5), rep("solid", 12))
  ser_col <- c(rep("black",5),rep("grey",12))
# Establish chart annotations for date, chart title,
  what_date <- format(Sys.Date(), "%b %d, %Y")  # with month as a word
  title <- paste("IARC-JAXA Daily Arctic Sea Ice Extent*\n", what_date)
  note_1 <- "*Extent - Area of Ocean with at least 15% Sea Ice"
  par(oma=c(2,1,1,1)); par(mar=c(2,4,2,1))
#  Day of year axis setup
## Set up basic day of year vectors (mon_names, 1st day of mon)
  mon_names <- c("Jan", "Feb", "Mar", "April", "May", "June", "July", "Aug", "Sept", "Oct","Nov","Dec")
  mon_doy <- c(1,32,60,91,121,151,182,213,244,274,305,335,366)
  mon_pos <- c(16, 46, 75, 106,135, 165, 200, 228, 255, 289, 320, 355)
# Read JAXA Arctic Sea ice Extent csv file
# Data File: Month,Day,1980's Avg,1990's Avg,2000's Average,2002:2012
  link <- "http://www.ijis.iarc.uaf.edu/seaice/extent/plot.csv"
  j_data <- read.csv(link, header = F, skip=1, na.strings = c(-9999))
 series_id <-  c("mo", "day", "1980s", "1990s", "2000s","2002", "2003", "2004", "2005", "2006", "2007", "2008", "2009",
                "2010", "2011", "2012", "2013")
 colnames(j_data) <- series_id
# File has data for each day in 366 day year
# Establish Day of year
  for (i in 1:366)   j_data$yr_frac[i] <- i
    #convert ASIE to millions Km^2
   j_data[,c(3:17)] <- j_data[,c(3:17)]/1000000
# Loop through years
   for (j in 3:17)
  {
     png_name <- paste("asie",series_id[j],".png",sep="")
      if (png_yn =="y") png(filename=png_name)
      which_yr <- j
      no_yrs <- j
  # Calc min asie for year
    min_asie <- min(j_data[,j], na.rm = T)  # must remove na's to get valid answer
    lab_asie <- round(min_asie,3)
    min_r <- which(j_data[,j] == min_asie)
    min_d <- j_data[min_r,2]
    min_m <- j_data[min_r,1]
    min_date <- paste(min_m,"/",min_d,"/",series_id[j], sep="")
    plot(j_data[,17],  type="n", col = "grey",axes=F, xlab="",
       ylab="Arctic Sea Ice Extent - Millions Sq KM",
       ylim=c(0,15),xaxs="i", yaxs = "i",
       main=title)
    text(20, 1.5, note_1, cex = 0.8, adj=0, col = "black")
    text(20,1,"Data Source: http://www.ijis.iarc.uaf.edu/seaice/extent/plot.csv", cex = 0.8, adj=0,col = "black")
    mtext("D Kelly O'Day - http://chartsgraphs.wordpress.com", 1,0.5, adj = 0, cex = 0.8, outer=T)
  # custom x & y axes
    axis(side = 1, at=mon_doy, labels=F, xaxs="i")
    axis(side=1, at= mon_pos, labels=mon_names, tick=F, line=F, xaxs="i")
    axis(side=2,  yaxs="i", las=1)
    points(70, min_asie, col = "red",pch=19, cex = 2)
  # Add each previous yr data series as light grey line
  for (n in 3:no_yrs)
  {
    points(j_data[,18], j_data[,n], type="l",lwd=1,lty=pattern[j], col=ser_col[j])
    text(182,14,series_id[j], col = "red", cex = 1.1)
  }
  points(j_data[,18], j_data[,j], col="red", type="l",lwd=2.5)
  text(182,14,series_id[j], col = "red", cex = 1.1)
  text(120,min_asie+0.5, min_date, col="red", cex=0.9)
  text(120,min_asie, lab_asie, col="red", cex=0.9)
  if(png_yn == "y") dev.off()
}
## copy last png file 3 times to provide pause in animation
if(png_yn== "y")
{
  for (c in 1:2)
  {
    file_name <- paste("asie2012",c, ".png",sep="")
    file.copy(from= "asie2012.png", to = file_name, overwrite=T)
  }
  ani.options(outdir = getwd())    # direct gif output file to working dir
  ani.options(interval= 0.80)
  im.convert("asie*.png", "last_animation.gif")
}

LearnR Toolkit To Help Excel Users Move Up To R

As a former  Excel chart user, I want to help current Excel users make the transition to more advanced charting R with as little difficulty as possible. This post introduces my LearnR Toolkit to help Excel users move up to R in a systematic, step by step fashion.

Introduction

As an Excel chart user, I wanted to produce panel charts like this:

Continue reading

Learn R Toolkit Update

My Learn R Toolkit went on-line in April, 2009. I’m happy to announce that the 10,000th  file download benchmark was reached on October 30.

Here are a few comments that Learn R Toolkit users have submitted:

  • “… I think your instructional material is simply excellent. Your explanations are uncomplicated, unhurried and clear.”
  • “I’ve enjoyed your R tutorial series. Thank you. It was worth the $19.”
  • “You’ve given me some fishing poles to catch what I want to catch.”
  • “Your tutorials are a good starting point for learning about R. I’m interested in manipulating data … and find myself referencing your tutorials on different issues.”

The first 3 modules are free, so be sure  to check out my Learn R Toolkit for yourself.

Learn R Toolkit Videos

My list of free Learn R Toolkit videos is growing. Here’s the latest list of free videos:

Modules 3-6 of the toolkit includes video training, working R scripts and data files to get you started writing R chart scripts in less than a day. Modules 3 – 6 are available for $19 with my  money back guarantee.

So there’s no reason for you to put off learning R. You now have a risk free way to start using R  for your advanced charts.