numeroteca

#to use it write "$ ./parse_kiosko.pl <lang>" where 'lang' is the language: en, es or fr
#it will output a csv. see example at http://brownbag.me:9001/p/pageonex-kiosko-newspaper-names

#!/usr/bin/env perl

use strict;
use warnings;
use utf8;
use LWP::UserAgent;
use HTML::TreeBuilder 5 -weak;

numeroteca

license: gpl-3.0
height: 500
scrolling: no
border: no

numeroteca

license: gpl-3.0
height: 950
scrolling: no
border: no

numeroteca

license: gpl-3.0
height: 510
scrolling: no
border: no

numeroteca

license: gpl-3.0
height: 950
scrolling: no
border: no

numeroteca

# load library
library(tidyverse)

data <- read.csv("centros-escolares-euskadi-valores-aleatorios.csv", sep = "," )

# -----------Calcula índice de Gorard por municipio -----------

# Unmelt data to make it easier for segregation index calculation. Based sonÑ
# https://ojs.uv.es/index.php/RASE/article/view/10129/10853
# http://journals.sagepub.com/doi/abs/10.1177/003803850203600405

numeroteca

#!/usr/bin/python2.7
# -*- coding: utf-8 -*-

#Load required modules
import twitter
import csv
from datetime import datetime
#from time import sleep
import time
from dateutil.relativedelta import relativedelta

numeroteca

license: gpl-3.0
height: 960
scrolling: no
border: no

numeroteca

#!/usr/bin/env python

# build a reply, quote, retweet network from a file of tweets and write it
# out as a gexf, dot, json or  html file. You will need to have networkx
# installed and pydotplus if you want to use dot. The html presentation
# uses d3 to display the network graph in your browser.
#
#   ./network.py tweets.jsonl network.html
#
# or