TableScraper.jl

In this package, there is only one function

scrape_tables(url)

which lets you scrape for tables wrapped in <table> tags and return them in a vector of Tables.jl compatible row-tables.

By default the function uses Cascadia.nodeText to extract the text from each <td> node.

However, if you wish to extract more than the text node you may want to use

scrape_tables(url, identity)

to keep the cells as Gumbo.HTMLNodes and do more advanced extraction.

Also, you can put any callable into the cell_transform argument to do custom transformation of the <td> nodes before returning.

E.g.

scrape_tables(url, cell_transform)

The returned table is TableScraper.Table which is defined as below

struct Table
    rows
    columnnames
end

So if you need to scrape some malformed tables, you can directly manipulate the data as in the below example

url = "https://www.ssa.gov/oact/NOTES/as120/images/LD_fig5.html"
tbl = only(TableScraper.scrape_tables(url, strip ∘ nodeText))

rows = tbl.rows[3:end]
header = tbl.rows[2]

df = DataFrame(TableScraper.Table(rows, header))