Visualizing Tables with plot.table

October 6, 2011

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

plot.table function in the Systematic Investor Toolbox is a flexible table drawing routine. plot.table has a simple interface and takes following parameters:

  • plot.matrix – matrix with data you want to plot
  • smain – text to draw in (top, left) cell; default value is blank string
  • highlight – Either TRUE/FALSE to indicate if you want to color each cell based on its numeric value Or a matrix with colors for each cell
  • colorbar – TRUE/FALSE flag to indicate if you want to draw colorbar

Here is a few examples how you can use plot.table function to create summary reports.

First, let’s load Systematic Investor Toolbox:

# load Systematic Investor Toolbox
source(gzcon(url('', 'rb')))

To create basic plot.table:

# define row and column titles
mrownames = spl('row one,row two,row 3')
mcolnames = spl('col 1,col 2,col 3,col 4')

# create temp matrix with data you want to plot
temp = matrix(NA, len(mrownames), len(mcolnames))
	rownames(temp) = mrownames
	colnames(temp) = mcolnames
	temp[,] = matrix(1:12,3,4)

# plot temp, display current date in (top, left) cell
plot.table(temp, format(as.Date(Sys.time()), '%d %b %Y'))

To create plot.table with colorbar:

# generate 1,000 random numbers from Normal(0,1) distribution
data =  matrix(rnorm(1000), nc=10)
	colnames(data) = paste('data', 1:10, sep='')

# compute Pearson correlation of data and format it nicely
temp = compute.cor(data, 'pearson')
	temp[] = plota.format(100 * temp, 0, '', '%')

# plot temp with colorbar, display Correlation in (top, left) cell
plot.table(temp, smain='Correlation', highlight = TRUE, colorbar = TRUE)

Next, I want to show a more practical example of plot.table function. I want to create a report page that will display a chart of IBM for 2010:2011 and a table with Valuation Measures from Key Statistics Yahoo Finance webpage.

# Load quantmod package to download price history for IBM

Symbol = 'IBM'

# download IBM price history from Yahoo
data = getSymbols(Symbol, from = '1980-01-01', auto.assign = FALSE)

# download Key Statistics from yahoo
url = paste('', Symbol, sep = '')
txt = join(readLines(url))

# extract Valuation Measures table from this page
temp = extract.table.from.webpage(txt, 'Market Cap', hasHeader = F)
	temp = rbind(c('', Symbol), temp)	# add header row

# prepare IBM data for 2010:2011 and compute 50 days moving average
y = data['2010::2011']
sma50 = SMA(Cl(y), 50)

# plote candles and volume and table

plota(y, type = 'candle', main = Symbol, plotX = F)
	plota.lines(sma50, col='blue')
	plota.legend(c(Symbol,'SMA 50'), 'green,blue', list(y,sma50))

y = plota.scale.volume(y)
plota(y, type = 'volume')


I will show more examples of plot.table in the future posts.

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

Search R-bloggers


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)