Markdown tables

OK, my good people…
I’ve rewritten the whole thing (here). It now supports all three types of pandoc tables (simple_tables, multiline_tables, and grid_tables but not pipe_tables), and therefore cells with multiple lines as well. I didn’t bother with alignment.
Why is this half-:horse:ed? Because @ExpandingMan was right:
Even if I populate my table with the actual values I want in the resulting document, and the resulting table contains actual data instead of differently sized tags (for Mustache.jl to replace), I get hit by including a link. So the actual link is typically much wider than how it gets rendered in the resulting document (where it turns into a hyperlink). So the table still doesn’t look close to how I want it. So I will be abandoning this markdown method and listen to wiser people than me…

But, for what it’s worth, the code is out there, fork it!

julia> using MDtables

julia> a = [string(round(rand(), rand(1:6))) for i in 1:3, j in 1:5]
3×5 Array{String,2}:
 "0.9"    "0.69741"  "0.1"    "0.55514"   "0.9299"
 "0.32"   "0.354"    "0.759"  "0.4579"    "0.4"   
 "0.873"  "0.2069"   "0.1"    "0.292993"  "0.86"  

julia> a[1,2] = "row 1\nrow 2"
"row 1\nrow 2"

julia> open("a.md", "w") do o
       print(o, print(GridTable, a))
       end

results in this:

+--------+------+--------+--------+--------+
|0.86284 |row 1 |0.044129|0.946186|0.3     |
|        |row 2 |        |        |        |
+========+======+========+========+========+
|0.235   |0.249 |0.295207|0.081   |0.764316|
+--------+------+--------+--------+--------+
|0.418278|0.8516|0.82    |0.38    |0.27575 |
+--------+------+--------+--------+--------+
4 Likes

@Ronis_BR permanently solved this. See https://discourse.julialang.org/t/ann-prettytables-jl-v2-3-0-markdown-back-end

I’ve therefore archived GitHub - yakir12/MDtables.jl

1 Like

Just wanted to mention a few package in the R ecosystem which I find really good with no good alternative even in the python ecosystem:

Other packages for Reproducible Research: https://cran.r-project.org/web/views/ReproducibleResearch.html

The above is probably amongst one of the few reasons I am still using R.