CalendaR 2012 with ggplot2

December 14, 2011
By

(This article was first published on Knowledge Discovery » R, and kindly contributed to R-bloggers)

Season’s Greetings

Hi, dear R-bloggers and its readers. Here in Japan it’s very cold now.
The end of one year is coming soon.

How was your year 2011 ?

As for me, I started to learn R on september this year, and found it very enjoyable.
So I posted a few blog on R-bloggers, e.g. “Japan Quake Map“.

By the way, I made a “CalendaR 2012 with ggplot2″.
With best wishes for next year.

CalendaR2012.png

The image were rendered at 1920 × 1080 pixels, to be seen in HD.

Appendix

Sample script of “CalendaR 2012 with ggplot2″ is as follows:

library(ggplot2)

# setting a parameter
year <- 2012
d <- seq.Date(as.Date(paste(year, "-01-01", sep = "")), as.Date(paste(year, "-12-31", sep = "")), by="days")
z <- data.frame(Y = format(d, "%Y"), M = as.numeric(format(d, "%m")), D = as.numeric(format(d, "%d")), W = format(d, "%w"))

# creating a image with ggplot2.
c <- ggplot(z, aes(D, M))
c + geom_text(aes(label=z$D, colour=factor(W), size = 20)) +
scale_colour_manual(values = c(“magenta”, rep(“black”, 5),”darkturquoise”))+
scale_y_continuous(trans = “reverse”, breaks = 1:12) +
labs(x=””, y=””) +
opts(
title = paste(“CalendaR”, year, “\n”, sep = ” “),
plot.title = theme_text(colour = “black”),
legend.position = “none”
)

To leave a comment for the author, please follow the link and comment on their blog: Knowledge Discovery » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Sponsors

Mango solutions



plotly webpage

dominolab webpage



Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training

datasociety

http://www.eoda.de







ODSC

ODSC

CRC R books series





Six Sigma Online Training









Contact us if you wish to help support R-bloggers, and place your banner here.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)