---
title: "Including a table in an opencpu app"
date: "2016-08-27"
---
```{r setup, include=FALSE}
knitr::knit_engines$set(pygmentize = function (options)
{
f = basename(tempfile("pygmentize", ".", ".txt"))
writeLines(options$code, f)
on.exit(unlink(f))
code = paste("-f html", options$engine.opts, f)
message("running: pygmentize ", code)
out = tryCatch(system2("pygmentize", code, stdout = TRUE, stderr = FALSE),
error = function(e) {
if (!options$error)
stop(e)
"Error in running pygmentize"
})
if (!options$error && !is.null(attr(out, "status")))
stop(paste(out, collapse = "\n"))
knitr::engine_output(options, options$code, out)
}
)
knitr::opts_chunk$set(engine="pygmentize", engine.opts="-l html", echo=FALSE, results='asis')
```
We give three ways to make a table in an opencpu app from a dataframe returned by a call to a R function.
The `getDF` function used for the example has no argument and returns a dataframe only:
```{r, engine.opts="-l r"}
getDF <- function(){
df <- iris
colnames(df) <- sub(".", "_", colnames(df), fixed=TRUE)
return(df)
}
```
## Using jsonTable
This way uses the [jsonTable](https://github.com/omkarkhair/jsonTable) library. I use the following Javascript function based on this library.
```{r, engine.opts="-l js" }
// js/jsontotable.js
function jsontotable(selector, data, columns, colnames=columns, rowclass="classy", callback=function(){}){
var options = {
source: data,
rowClass: rowclass,
callback: callback
};
$(selector).jsonTable({
head : colnames,
json : columns
});
$(selector).jsonTableUpdate(options);
}
```
I also use [bootstrap](http://www.w3schools.com/bootstrap/bootstrap_tables.asp) in order to get a nice style.
```{r}
```
The output:
## Using datatables
Here is the way to render a `datatables` table in an `opencpu` application.
```{r}
```
The output:
## Using angular.js (with sorting feature)
```{r}