With pandas I can read a table into a dataframe, as follows:
import pandas as pd
dfs = pd.read_html('http://stats.ioinformatics.org/countries/')#returns a list of tables
df=dfs[0]
df.head()#inspect header
I searched for a similar method in DataFrames.jl (more precisely in the forthcomming book, Julia for Data Analysis, v_10, which I have pre-ordered), as well in the Julia for Data Science, but there is no approach or example of such a task. Following a suggestion given as answer to the same question, posted here, two years ago: [Any equivalent to Pandas read_html() in DataFrames.jl?)(Any equivalent to Pandas read_html() in DataFrames.jl?), I tried something like this:
using DataFrames, CSV, HTTP
read_remote_csv(url) = DataFrame(CSV.File(HTTP.get(url).body))
df = read_remote_csv("http://stats.ioinformatics.org/countries/")
but it displays the html contents, not a dataframe having as columns the table columns.
My answer was for situations where the remote url returns a delimited file, which is what CSV.File parses. You are looking to extract a table from html, so need a library that parses html rather than delimited files, see:
Thank you for the link to Scraping a html table from a url. Unfortunately I have a low level of knowledge and skills in html/CSS. For the moment I will read the tables with pd.read_html(url), save the corresponding dataframe as csv and re-read it in Julia.