François Briatte briatte

## incomes.r
## Top incomes data by Piketty and Saez, Sep 2013 update.
## 2014-10-16

## source

# T. Piketty and E. Saez, "Income Inequality in the United States, 1913-1998"
# Quarterly Journal of Economics, 118(1), 2003, 1-39 [ fig. 1, enhanced ]

## packages

## incomes.csv

          
            NA.
            P90.100
            P95.100
            P99.100
            P99.5.100
            P99.9.100
            P99.99.100

            
              1913
              NA
              NA
              17.9600418618677
              14.7264569314871
              8.61660817145581
              2.75501620545077

            
              1914
              NA
              NA
              18.1579410592163
              15.0802622430197
              8.60334089140613
              2.72920847365446

            
              1915
              NA
              NA
              17.577725
              14.57755
              9.21885
              4.36035

            
              1916
              NA
              NA
              18.5730667754062
              15.6036449461324
              9.86653043001581
              4.40493410443468

            
              1917
              40.2870418752226
              30.3345483573205
              17.5994874581952
              14.2341917768497
              8.35788084805983
              3.33076913805183

            
              1918
              39.9037275120226
              29.2979482993876
              15.8832204355484
              12.3854950735275
              6.74116426024008
              2.44816293043196

            
              1919
              39.4813240153393
              29.307649555521
              15.8674148545227
              12.2339651877482
              6.45397884830736
              2.22020659211262

            
              1920
              38.1003874377692
              27.4694503319667
              14.4590420554394
              10.9532629518181
              5.37143303444607
              1.67163862642264

            
              1921
              42.8597266399737
              30.457060858318
              15.4729299864716
              11.5988330223682
              5.60216500839064
              1.68921038823408

## an-votes.r
library(XML)
library(stringr)

# demo page
h = htmlParse("http://www2.assemblee-nationale.fr/scrutins/detail/(legislature)/14/(num)/947")

g = c("SRC", "UMP", "UDI", "ECOLO", "RAD", "GDR")
k = c("socialiste", "mouvement populaire", "démocrates", "écologiste", "radical", "gauche")

for(i in k) {

## example.md

      
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                Example cosponsorship network (Iceland 2003–2007)
              
          
## 5_trust.r

## IDA Exercise 5
## --------------


# This exercise replicates PCA plots using World Values Survey data on
# aggregate confidence in public institutions.

# The data is taken from the Quality of Government dataset. The functions
# contain a mix of base functions and custom packages.

## bills1998-2002.html

		<!DOCTYPE html>


## ergm.r
m = sum(n %e% "raw") / network.dyadcount(n)
init.sum = log(m)

npar = length(summary(f, response = "raw"))

M = ergm(f, response = "raw",
         reference = ~Poisson,
         control = control.ergm(seed = 9042,
                                parallel = parallel::detectCores(),
                                #

## README.md

      
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                Modélisation de la modularité des réseaux de cosignatures législatives de ce dossier : https://github.com/briatte/parlnet
              
          
    Replication archive for François Briatte, "Les réseaux de cosignatures législatives de quinze parlements européens", 2015.
Get the paper and its appendix at http://f.briatte.org/research/ferney-paper.pdf.
DATA

The data.csv file contains information on the networks produced by the parlnet repository available at https://github.com/briatte/parlnet.
Observations are cosponsorship networks from 19 parliamentary chambers in 15 countries over 96 legislatures. Variables are:

  
## charlie-data.r
#
# download 338 Charlie Hebdo covers with keywords
#

library(dplyr)
library(XML)
library(lubridate)
library(stringr)
library(ggplot2)

## revues-data.r
data = "revues-soc.csv"

if(!file.exists(data)) {

  dir.create("rev", showWarnings = FALSE)
  dir.create("num", showWarnings = FALSE)

  r = "http://www.cairn.info/"

  download.file(paste0(r, "discipline.php?POS=11&TITRE=ALL"),
	## Top incomes data by Piketty and Saez, Sep 2013 update.
	## 2014-10-16

	## source

	# T. Piketty and E. Saez, "Income Inequality in the United States, 1913-1998"
	# Quarterly Journal of Economics, 118(1), 2003, 1-39 [ fig. 1, enhanced ]

	## packages
NA.	P90.100	P95.100	P99.100	P99.5.100	P99.9.100	P99.99.100
1913	NA	NA	17.9600418618677	14.7264569314871	8.61660817145581	2.75501620545077
1914	NA	NA	18.1579410592163	15.0802622430197	8.60334089140613	2.72920847365446
1915	NA	NA	17.577725	14.57755	9.21885	4.36035
1916	NA	NA	18.5730667754062	15.6036449461324	9.86653043001581	4.40493410443468
1917	40.2870418752226	30.3345483573205	17.5994874581952	14.2341917768497	8.35788084805983	3.33076913805183
1918	39.9037275120226	29.2979482993876	15.8832204355484	12.3854950735275	6.74116426024008	2.44816293043196
1919	39.4813240153393	29.307649555521	15.8674148545227	12.2339651877482	6.45397884830736	2.22020659211262
1920	38.1003874377692	27.4694503319667	14.4590420554394	10.9532629518181	5.37143303444607	1.67163862642264
1921	42.8597266399737	30.457060858318	15.4729299864716	11.5988330223682	5.60216500839064	1.68921038823408
	library(XML)
	library(stringr)

	# demo page
	h = htmlParse("http://www2.assemblee-nationale.fr/scrutins/detail/(legislature)/14/(num)/947")

	g = c("SRC", "UMP", "UDI", "ECOLO", "RAD", "GDR")
	k = c("socialiste", "mouvement populaire", "démocrates", "écologiste", "radical", "gauche")

	for(i in k) {

	## IDA Exercise 5
	## --------------


	# This exercise replicates PCA plots using World Values Survey data on
	# aggregate confidence in public institutions.

	# The data is taken from the Quality of Government dataset. The functions
	# contain a mix of base functions and custom packages.
	m = sum(n %e% "raw") / network.dyadcount(n)
	init.sum = log(m)

	npar = length(summary(f, response = "raw"))

	M = ergm(f, response = "raw",
	reference = ~Poisson,
	control = control.ergm(seed = 9042,
	parallel = parallel::detectCores(),
	#
	#
	# download 338 Charlie Hebdo covers with keywords
	#

	library(dplyr)
	library(XML)
	library(lubridate)
	library(stringr)
	library(ggplot2)
	data = "revues-soc.csv"

	if(!file.exists(data)) {

	dir.create("rev", showWarnings = FALSE)
	dir.create("num", showWarnings = FALSE)

	r = "http://www.cairn.info/"

	download.file(paste0(r, "discipline.php?POS=11&TITRE=ALL"),