.Rhistory

# IOM FILE
iomfile = "MissingMigrants-Global-2020-12-18T11-50-25.csv"
# Fields
fields <- c("year","date_fr","date_en","latitude","longitude","nb","route","children")
mois <- c("janvier","février","mars","avril","mai","juin","juillet","août","septembre","octobre","novembre","décembre")
months <- c("January","February","March","April","May","June","July","August","September","October","November","December")
# United (1993 -> 1999)
united <- read.csv( "input/united/Event_before2000.csv",header=TRUE,sep="\t",dec=",",encoding="latin1",comment.char = "",quote = "\"")
united$route <- NA
united$children <- NA
united$date <- NA
united$date_fr <- paste0("En ",united$year)
united$date_en <- paste0("In ",united$year)
united <- united[,c("year","date_fr","date_en","latitude","longitude","dead_and_missing","route","children")]
colnames(united) <- fields
# The Migrant's file (2000 -> 2013)
migrantsfile <- read.csv( "input/migrantsfile/DISCONTINUED ON JUNE 24, 2016 - Events during which someone died trying to reach or stay in Europe - Events.csv",header=TRUE,sep=",",dec=".",encoding="latin1",comment.char = "",quote = "\"", stringsAsFactors = FALSE)
migrantsfile <- migrantsfile[migrantsfile$Year <= 2013,]
migrantsfile <- migrantsfile[!is.na(migrantsfile$dead_and_missing),]
migrantsfile$date_fr <- ""
nb <- nrow(migrantsfile)
for (i in 1:nb){
chaine <- migrantsfile$date[i]
j <- substr(chaine,9,10)
m <- mois[as.numeric(substr(chaine,6,7))]
m2 <- months[as.numeric(substr(chaine,6,7))]
a <- substr(chaine,1,4)
migrantsfile$date_fr[i] <- paste(j,m,a, sep =" ")
migrantsfile$date_en[i] <- paste0(m2," ",j,", ",a)
}
migrantsfile <- migrantsfile[,c("Year","date_fr","date_en","latitude","longitude","dead_and_missing","route..Frontex.")]
migrantsfile$children <- NA
migrantsfile$latitude <- as.numeric(migrantsfile$latitude)
migrantsfile$longitude <- as.numeric(migrantsfile$longitude)
colnames(migrantsfile) <- fields
# IOM
iom <- read.csv( paste("input/oim/",iomfile,sep=""),header=TRUE,sep=",",dec=".",encoding="latin1",comment.char = "",quote = "\"", stringsAsFactors = FALSE)
iom <- iom[!is.na(iom$Location.Coordinates),]
iom[is.na(iom$Number.Dead),"Number.Dead"] <- 0
iom[is.na(iom$Minimum.Estimated.Number.of.Missing),"Minimum.Estimated.Number.of.Missing"] <- 0
iom$nb <- as.numeric(iom$Number.Dead) + as.numeric(iom$Minimum.Estimated.Number.of.Missing)
iom <- iom[iom$nb >0,]
iom$Location.Coordinates <- as.character(iom$Location.Coordinates)
iom[,c("latitude","longitude")] <- matrix(as.numeric(unlist(strsplit(iom$Location.Coordinates, split = ", "))), ncol = 2, byrow = T)
iom$date_fr <- NA
nb <- nrow(iom)
for (i in 1:nb){
chaine <- iom$Reported.Date[i]
tmp <- strsplit(chaine," ")[[1]]
j <- substr(tmp[2],1,2)
m <- mois[which(months==tmp[1])[1]]
y <- tmp[3]
iom$date_fr[i] <- paste(j,m,a, sep =" ")
}
iom <- iom[,c("Reported.Year","date_fr","Reported.Date","latitude","longitude","nb","Migration.Route","Number.of.Children")]
colnames(iom) <- fields
# Merge & handling
mdm <- rbind(united, migrantsfile, iom)
write.csv(mdm,"output/mdm.csv", row.names = FALSE)
# Seuillage
# latitudemin = 15
# latitudemax = 65
# longitudemin = -20
# longitudemax = 47
#
# mdm <- mdm[mdm$latitude >= latitudemin & mdm$latitude <= latitudemax,]
# mdm <- mdm[mdm$longitude >= longitudemin & mdm$longitude <= longitudemax,]
# write.csv(mdm,"output/mdm_eu.csv", row.names = FALSE)
# IOM FILE
iomfile = "MissingMigrants-Global-2021-01-04T13-16-25.csv"
# Fields
fields <- c("year","date_fr","date_en","latitude","longitude","nb","route","children")
mois <- c("janvier","février","mars","avril","mai","juin","juillet","août","septembre","octobre","novembre","décembre")
months <- c("January","February","March","April","May","June","July","August","September","October","November","December")
# United (1993 -> 1999)
united <- read.csv( "input/united/Event_before2000.csv",header=TRUE,sep="\t",dec=",",encoding="latin1",comment.char = "",quote = "\"")
united$route <- NA
united$children <- NA
united$date <- NA
united$date_fr <- paste0("En ",united$year)
united$date_en <- paste0("In ",united$year)
united <- united[,c("year","date_fr","date_en","latitude","longitude","dead_and_missing","route","children")]
colnames(united) <- fields
# The Migrant's file (2000 -> 2013)
migrantsfile <- read.csv( "input/migrantsfile/DISCONTINUED ON JUNE 24, 2016 - Events during which someone died trying to reach or stay in Europe - Events.csv",header=TRUE,sep=",",dec=".",encoding="latin1",comment.char = "",quote = "\"", stringsAsFactors = FALSE)
migrantsfile <- migrantsfile[migrantsfile$Year <= 2013,]
migrantsfile <- migrantsfile[!is.na(migrantsfile$dead_and_missing),]
migrantsfile$date_fr <- ""
nb <- nrow(migrantsfile)
for (i in 1:nb){
chaine <- migrantsfile$date[i]
j <- substr(chaine,9,10)
m <- mois[as.numeric(substr(chaine,6,7))]
m2 <- months[as.numeric(substr(chaine,6,7))]
a <- substr(chaine,1,4)
migrantsfile$date_fr[i] <- paste(j,m,a, sep =" ")
migrantsfile$date_en[i] <- paste0(m2," ",j,", ",a)
}
migrantsfile <- migrantsfile[,c("Year","date_fr","date_en","latitude","longitude","dead_and_missing","route..Frontex.")]
migrantsfile$children <- NA
migrantsfile$latitude <- as.numeric(migrantsfile$latitude)
migrantsfile$longitude <- as.numeric(migrantsfile$longitude)
colnames(migrantsfile) <- fields
# IOM
iom <- read.csv( paste("input/oim/",iomfile,sep=""),header=TRUE,sep=",",dec=".",encoding="latin1",comment.char = "",quote = "\"", stringsAsFactors = FALSE)
iom <- iom[!is.na(iom$Location.Coordinates),]
iom[is.na(iom$Number.Dead),"Number.Dead"] <- 0
iom[is.na(iom$Minimum.Estimated.Number.of.Missing),"Minimum.Estimated.Number.of.Missing"] <- 0
iom$nb <- as.numeric(iom$Number.Dead) + as.numeric(iom$Minimum.Estimated.Number.of.Missing)
iom <- iom[iom$nb >0,]
iom$Location.Coordinates <- as.character(iom$Location.Coordinates)
iom[,c("latitude","longitude")] <- matrix(as.numeric(unlist(strsplit(iom$Location.Coordinates, split = ", "))), ncol = 2, byrow = T)
iom$date_fr <- NA
nb <- nrow(iom)
for (i in 1:nb){
chaine <- iom$Reported.Date[i]
tmp <- strsplit(chaine," ")[[1]]
j <- substr(tmp[2],1,2)
m <- mois[which(months==tmp[1])[1]]
y <- tmp[3]
iom$date_fr[i] <- paste(j,m,a, sep =" ")
}
iom <- iom[,c("Reported.Year","date_fr","Reported.Date","latitude","longitude","nb","Migration.Route","Number.of.Children")]
colnames(iom) <- fields
# Merge & handling
mdm <- rbind(united, migrantsfile, iom)
write.csv(mdm,"output/mdm.csv", row.names = FALSE)
# Seuillage
# latitudemin = 15
# latitudemax = 65
# longitudemin = -20
# longitudemax = 47
#
# mdm <- mdm[mdm$latitude >= latitudemin & mdm$latitude <= latitudemax,]
# mdm <- mdm[mdm$longitude >= longitudemin & mdm$longitude <= longitudemax,]
# write.csv(mdm,"output/mdm_eu.csv", row.names = FALSE)
# IOM FILE
iomfile = "MissingMigrants-Global-2021-01-04T13-16-25.csv"
# Fields
fields <- c("year","date_fr","date_en","latitude","longitude","nb","route","children")
mois <- c("janvier","février","mars","avril","mai","juin","juillet","août","septembre","octobre","novembre","décembre")
months <- c("January","February","March","April","May","June","July","August","September","October","November","December")
# United (1993 -> 1999)
united <- read.csv( "input/united/Event_before2000.csv",header=TRUE,sep="\t",dec=",",encoding="latin1",comment.char = "",quote = "\"")
united$route <- NA
united$children <- NA
united$date <- NA
united$date_fr <- paste0("En ",united$year)
united$date_en <- paste0("In ",united$year)
united <- united[,c("year","date_fr","date_en","latitude","longitude","dead_and_missing","route","children")]
colnames(united) <- fields
# The Migrant's file (2000 -> 2013)
migrantsfile <- read.csv( "input/migrantsfile/DISCONTINUED ON JUNE 24, 2016 - Events during which someone died trying to reach or stay in Europe - Events.csv",header=TRUE,sep=",",dec=".",encoding="latin1",comment.char = "",quote = "\"", stringsAsFactors = FALSE)
migrantsfile <- migrantsfile[migrantsfile$Year <= 2013,]
migrantsfile <- migrantsfile[!is.na(migrantsfile$dead_and_missing),]
migrantsfile$date_fr <- ""
nb <- nrow(migrantsfile)
for (i in 1:nb){
chaine <- migrantsfile$date[i]
j <- substr(chaine,9,10)
m <- mois[as.numeric(substr(chaine,6,7))]
m2 <- months[as.numeric(substr(chaine,6,7))]
a <- substr(chaine,1,4)
migrantsfile$date_fr[i] <- paste(j,m,a, sep =" ")
migrantsfile$date_en[i] <- paste0(m2," ",j,", ",a)
}
migrantsfile <- migrantsfile[,c("Year","date_fr","date_en","latitude","longitude","dead_and_missing","route..Frontex.")]
migrantsfile$children <- NA
migrantsfile$latitude <- as.numeric(migrantsfile$latitude)
migrantsfile$longitude <- as.numeric(migrantsfile$longitude)
colnames(migrantsfile) <- fields
iom <- read.csv( paste("input/oim/",iomfile,sep=""),header=TRUE,sep=",",dec=".",encoding="latin1",comment.char = "",quote = "\"", stringsAsFactors = FALSE)
View(migrantsfile)
iom <- read.csv( paste("input/oim/",iomfile,sep=""),header=TRUE,sep=",",dec=".",encoding="latin1",comment.char = "",quote = "\"", stringsAsFactors = FALSE)
iom <- iom[!is.na(iom$Location.Coordinates),]
iom[is.na(iom$Number.Dead),"Number.Dead"] <- 0
iom[is.na(iom$Minimum.Estimated.Number.of.Missing),"Minimum.Estimated.Number.of.Missing"] <- 0
iom$nb <- as.numeric(iom$Number.Dead) + as.numeric(iom$Minimum.Estimated.Number.of.Missing)
iom <- iom[iom$nb >0,]
iom$Location.Coordinates <- as.character(iom$Location.Coordinates)
iom[,c("latitude","longitude")] <- matrix(as.numeric(unlist(strsplit(iom$Location.Coordinates, split = ", "))), ncol = 2, byrow = T)
View(iom)
iom$date_fr <- NA
nb <- nrow(iom)
for (i in 1:nb){
chaine <- iom$Reported.Date[i]
tmp <- strsplit(chaine," ")[[1]]
j <- substr(tmp[2],1,2)
m <- mois[which(months==tmp[1])[1]]
y <- tmp[3]
iom$date_fr[i] <- paste(j,m,a, sep =" ")
}
View(iom)
iom <- iom[,c("Reported.Year","date_fr","Reported.Date","latitude","longitude","nb","Migration.Route","Number.of.Children")]
colnames(iom) <- fields
View(iom)
mdm <- rbind(united, migrantsfile, iom)
# IOM FILE
iomfile = "MissingMigrants-Global-2021-01-04T13-16-25.csv"
# Fields
fields <- c("year","date_fr","date_en","latitude","longitude","nb","route","children")
mois <- c("janvier","février","mars","avril","mai","juin","juillet","août","septembre","octobre","novembre","décembre")
months <- c("January","February","March","April","May","June","July","August","September","October","November","December")
# United (1993 -> 1999)
united <- read.csv( "input/united/Event_before2000.csv",header=TRUE,sep="\t",dec=",",encoding="latin1",comment.char = "",quote = "\"")
united$route <- NA
united$children <- NA
united$date <- NA
united$date_fr <- paste0("En ",united$year)
united$date_en <- paste0("In ",united$year)
united <- united[,c("year","date_fr","date_en","latitude","longitude","dead_and_missing","route","children")]
colnames(united) <- fields
# The Migrant's file (2000 -> 2013)
migrantsfile <- read.csv( "input/migrantsfile/DISCONTINUED ON JUNE 24, 2016 - Events during which someone died trying to reach or stay in Europe - Events.csv",header=TRUE,sep=",",dec=".",encoding="latin1",comment.char = "",quote = "\"", stringsAsFactors = FALSE)
migrantsfile <- migrantsfile[migrantsfile$Year <= 2013,]
migrantsfile <- migrantsfile[!is.na(migrantsfile$dead_and_missing),]
migrantsfile$date_fr <- ""
nb <- nrow(migrantsfile)
for (i in 1:nb){
chaine <- migrantsfile$date[i]
j <- substr(chaine,9,10)
m <- mois[as.numeric(substr(chaine,6,7))]
m2 <- months[as.numeric(substr(chaine,6,7))]
a <- substr(chaine,1,4)
migrantsfile$date_fr[i] <- paste(j,m,a, sep =" ")
migrantsfile$date_en[i] <- paste0(m2," ",j,", ",a)
}
migrantsfile <- migrantsfile[,c("Year","date_fr","date_en","latitude","longitude","dead_and_missing","route..Frontex.")]
migrantsfile$children <- NA
migrantsfile$latitude <- as.numeric(migrantsfile$latitude)
migrantsfile$longitude <- as.numeric(migrantsfile$longitude)
colnames(migrantsfile) <- fields
# IOM
iom <- read.csv( paste("input/oim/",iomfile,sep=""),header=TRUE,sep=",",dec=".",encoding="latin1",comment.char = "",quote = "\"", stringsAsFactors = FALSE)
iom <- iom[!is.na(iom$Location.Coordinates),]
iom[is.na(iom$Number.Dead),"Number.Dead"] <- 0
iom[is.na(iom$Minimum.Estimated.Number.of.Missing),"Minimum.Estimated.Number.of.Missing"] <- 0
iom$nb <- as.numeric(iom$Number.Dead) + as.numeric(iom$Minimum.Estimated.Number.of.Missing)
iom <- iom[iom$nb >0,]
iom$Location.Coordinates <- as.character(iom$Location.Coordinates)
iom[,c("latitude","longitude")] <- matrix(as.numeric(unlist(strsplit(iom$Location.Coordinates, split = ", "))), ncol = 2, byrow = T)
iom$date_fr <- NA
nb <- nrow(iom)
for (i in 1:nb){
chaine <- iom$Reported.Date[i]
tmp <- strsplit(chaine," ")[[1]]
j <- substr(tmp[2],1,2)
m <- mois[which(months==tmp[1])[1]]
y <- tmp[3]
iom$date_fr[i] <- paste(j,m,a, sep =" ")
}
iom <- iom[,c("Reported.Year","date_fr","Reported.Date","latitude","longitude","nb","Migration.Route","Number.of.Children")]
colnames(iom) <- fields
# Merge & handling
mdm <- rbind(united, migrantsfile, iom)
write.csv(mdm,"output/mdm.csv", row.names = FALSE)
# Seuillage
# latitudemin = 15
# latitudemax = 65
# longitudemin = -20
# longitudemax = 47
#
# mdm <- mdm[mdm$latitude >= latitudemin & mdm$latitude <= latitudemax,]
# mdm <- mdm[mdm$longitude >= longitudemin & mdm$longitude <= longitudemax,]
# write.csv(mdm,"output/mdm_eu.csv", row.names = FALSE)
View(mdm)
write.csv(mdm,"output/mdm.csv", row.names = FALSE)
iom <- read.csv( paste("input/oim/",iomfile,sep=""),header=TRUE,sep=",",dec=".",encoding="latin1",comment.char = "",quote = "\"", stringsAsFactors = FALSE)
iom <- iom[!is.na(iom$Location.Coordinates),]
iom[is.na(iom$Number.Dead),"Number.Dead"] <- 0
iom[is.na(iom$Minimum.Estimated.Number.of.Missing),"Minimum.Estimated.Number.of.Missing"] <- 0
iom$nb <- as.numeric(iom$Number.Dead) + as.numeric(iom$Minimum.Estimated.Number.of.Missing)
iom <- iom[iom$nb >0,]
iom$Location.Coordinates <- as.character(iom$Location.Coordinates)
iom[,c("latitude","longitude")] <- matrix(as.numeric(unlist(strsplit(iom$Location.Coordinates, split = ", "))), ncol = 2, byrow = T)
iom$date_fr <- NA
nb <- nrow(iom)
i = 1
chaine <- iom$Reported.Date[i]
chaine
tmp <- strsplit(chaine," ")[[1]]
tmp
j <- substr(tmp[2],1,2)
j
m <- mois[which(months==tmp[1])[1]]
m
y <- tmp[3]
y
i = 10
chaine <- iom$Reported.Date[i]
chaine
i = 100
chaine
i = 500
chaine <- iom$Reported.Date[i]
chaine
nb
i = 5000
chaine <- iom$Reported.Date[i]
chaine
tmp <- strsplit(chaine," ")[[1]]
tmp
j <- substr(tmp[2],1,2)
j
m <- mois[which(months==tmp[1])[1]]
m
y <- tmp[3]
y
# IOM FILE
iomfile = "MissingMigrants-Global-2021-01-04T13-16-25.csv"
# Fields
fields <- c("year","date_fr","date_en","latitude","longitude","nb","route","children")
mois <- c("janvier","février","mars","avril","mai","juin","juillet","août","septembre","octobre","novembre","décembre")
months <- c("January","February","March","April","May","June","July","August","September","October","November","December")
# United (1993 -> 1999)
united <- read.csv( "input/united/Event_before2000.csv",header=TRUE,sep="\t",dec=",",encoding="latin1",comment.char = "",quote = "\"")
united$route <- NA
united$children <- NA
united$date <- NA
united$date_fr <- paste0("En ",united$year)
united$date_en <- paste0("In ",united$year)
united <- united[,c("year","date_fr","date_en","latitude","longitude","dead_and_missing","route","children")]
colnames(united) <- fields
# The Migrant's file (2000 -> 2013)
migrantsfile <- read.csv( "input/migrantsfile/DISCONTINUED ON JUNE 24, 2016 - Events during which someone died trying to reach or stay in Europe - Events.csv",header=TRUE,sep=",",dec=".",encoding="latin1",comment.char = "",quote = "\"", stringsAsFactors = FALSE)
migrantsfile <- migrantsfile[migrantsfile$Year <= 2013,]
migrantsfile <- migrantsfile[!is.na(migrantsfile$dead_and_missing),]
migrantsfile$date_fr <- ""
nb <- nrow(migrantsfile)
for (i in 1:nb){
chaine <- migrantsfile$date[i]
j <- substr(chaine,9,10)
m <- mois[as.numeric(substr(chaine,6,7))]
m2 <- months[as.numeric(substr(chaine,6,7))]
a <- substr(chaine,1,4)
migrantsfile$date_fr[i] <- paste(j,m,a, sep =" ")
migrantsfile$date_en[i] <- paste0(m2," ",j,", ",a)
}
migrantsfile <- migrantsfile[,c("Year","date_fr","date_en","latitude","longitude","dead_and_missing","route..Frontex.")]
migrantsfile$children <- NA
migrantsfile$latitude <- as.numeric(migrantsfile$latitude)
migrantsfile$longitude <- as.numeric(migrantsfile$longitude)
colnames(migrantsfile) <- fields
# IOM
iom <- read.csv( paste("input/oim/",iomfile,sep=""),header=TRUE,sep=",",dec=".",encoding="latin1",comment.char = "",quote = "\"", stringsAsFactors = FALSE)
iom <- iom[!is.na(iom$Location.Coordinates),]
iom[is.na(iom$Number.Dead),"Number.Dead"] <- 0
iom[is.na(iom$Minimum.Estimated.Number.of.Missing),"Minimum.Estimated.Number.of.Missing"] <- 0
iom$nb <- as.numeric(iom$Number.Dead) + as.numeric(iom$Minimum.Estimated.Number.of.Missing)
iom <- iom[iom$nb >0,]
iom$Location.Coordinates <- as.character(iom$Location.Coordinates)
iom[,c("latitude","longitude")] <- matrix(as.numeric(unlist(strsplit(iom$Location.Coordinates, split = ", "))), ncol = 2, byrow = T)
iom$date_fr <- NA
nb <- nrow(iom)
for (i in 1:nb){
chaine <- iom$Reported.Date[i]
tmp <- strsplit(chaine," ")[[1]]
j <- substr(tmp[2],1,2)
m <- mois[which(months==tmp[1])[1]]
y <- tmp[3]
iom$date_fr[i] <- paste(j,m,y, sep =" ")
}
iom <- iom[,c("Reported.Year","date_fr","Reported.Date","latitude","longitude","nb","Migration.Route","Number.of.Children")]
colnames(iom) <- fields
# Merge & handling
mdm <- rbind(united, migrantsfile, iom)
write.csv(mdm,"output/mdm.csv", row.names = FALSE)
View(mdm)
# Seuillage
# latitudemin = 15
# latitudemax = 65
# longitudemin = -20
# longitudemax = 47
#
# mdm <- mdm[mdm$latitude >= latitudemin & mdm$latitude <= latitudemax,]
# mdm <- mdm[mdm$longitude >= longitudemin & mdm$longitude <= longitudemax,]
# write.csv(mdm,"output/mdm_eu.csv", row.names = FALSE)