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.

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