Convert quartile plots into standard error plots hacking qTable function from NMOF package
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If you remember there is a nice version of table conceived by Tufte that include small quartile plots running next to the corresponding data rows:

![enter image description here][1]

There is an implementation of such solution in R using [package NMOF][2] and function `qTable`, which basically creates the table shown above and outputs it as a LaTeX code:

    require(NMOF)
    x <- rnorm(100, mean = 0, sd = 2)
    y <- rnorm(100, mean = 1, sd = 2)
    z <- rnorm(100, mean = 1, sd = 0.5)
    X <- cbind(x, y, z)
    qTable(X,filename="res.tex")#this will save qTable in tex format in current dir

This method of visualization seem to be especially useful if you have a small amount of information to present, and you don't want to waste a space for the full graph. But I would like to hack `qTable` a bit. Instead of displaying quantile plots, I would prefer to display standard errors of the mean. I am not great in hacking such functions, and I used brute force to do it. I replaced the line from the `qTable` function which computes quantiles:

    A <- apply(X, 2L, quantile, c(0.25, 0.5, 0.75))

with something very brutal, that computes standard errors: 

    require(psych)#got 'SE' function to compute columns standard deviation     
    M = colMeans(X)#column means
    SE = SD(X)/sqrt(nrow(X))#standard error
    SELo = M-SE#lower bound
    SEHi = M+SE#upper bound
    A = t(data.frame(SELo,M,SEHi))#combines it together

I know, I know it's possibly unsustainable approach, but it actually works to some extend - it plots standard errors but keeps this gap in the plot:

![enter image description here][3]

and I would like this gap to disappear.

[Here is a qTable function with modification discussed above][4].


  [1]: http://i.stack.imgur.com/yB0p9.jpg
  [2]: http://cran.r-project.org/web/packages/NMOF/index.html
  [3]: http://i.stack.imgur.com/x4kTY.jpg
  [4]: https://gist.github.com/3078746