mypath <- "C://Users//np83zg//OneDrive - Aalborg Universitet//Skrivebord//kommunedata//data"
setwd(mypath)
library(data.table)
library(tmap)
library(sf)
## Linking to GEOS 3.8.0, GDAL 3.0.4, PROJ 6.3.1
library(cartogram)
## Warning: package 'cartogram' was built under R version 4.0.3
library(gganimate)
## Warning: package 'gganimate' was built under R version 4.0.3
## Loading required package: ggplot2
library(ggplot2)
mydata <- as.data.table(read.table("bef_tab2.txt"))
mydata2 <- as.data.table(read.table("wage_tab1.txt"))
mydata3 <- as.data.table(read.table("mundata.txt"))
mydata <- merge(mydata,mydata2,by=c("year","residence"))
mydata <- merge(mydata,mydata3,by.x=c("residence"),by.y="nr")
remove(mydata2)
remove(mydata3)
setkey(mydata,density,year)
T <- length(table(mydata$year))
mydata[,dm_wage:=m_wage-m_wage[1],by=.(residence)]
mydata[,index:=-dm_wage[T],by=.(residence)]
setkey(mydata,index,year)
mydata[,id:=rep(1:98,each=T)]
theme_set(theme_bw())
p <- ggplot(
mydata,
aes(x =id, y=dm_wage, size=density,colour = as.factor(residence))
) +
geom_point(show.legend = FALSE, alpha = 0.7) +
scale_color_viridis_d() +
scale_size(range = c(2, 12)) +
labs(x = "Municipality ID", y = "Change in mean wage relative to year 1990") +
transition_time(year) +
labs(title = "Year: {frame_time}") +
shadow_mark(alpha = 0.3, size = 0.5)
mypath <- "C://Users//np83zg//OneDrive - Aalborg Universitet//Skrivebord//kommunedata//scripts"
setwd(mypath)
anim_save("p.gif",p)
mypath <- "C://Users//np83zg//OneDrive - Aalborg Universitet//Skrivebord//kommunedata//data"
setwd(mypath)
library(data.table)
library(tmap)
library(sf)
library(cartogram)
library(gganimate)
library(ggplot2)
mydata <- as.data.table(read.table("bef_tab3.txt"))
setkey(mydata,residence,year)
T <- length(table(mydata$year))
cities <- c(101,751,461,851,561)
mydata[,s:=age_16+age_16_60+age_60]
mydata[,s1:=age_16/s]
mydata[,s2:=age_16_60/s]
mydata[,s3:=age_60/s]
mydata[,ds2:=s2-s2[1],by=.(residence)]
theme_set(theme_bw())
p <- ggplot(
mydata,
aes(x =residence, y=ds2,size=s, colour = as.factor(residence))
) +
geom_point(show.legend = FALSE, alpha = 0.9) +
scale_color_viridis_d() +
scale_size(range = c(2, 12)) +
labs(x = "Municipality ID", y = "Change in share in agegroup 16-60 relative 1987") +
transition_time(year) +
labs(title = "Year: {frame_time}") +
shadow_mark(alpha = 0.3, size = 0.5)
mypath <- "C://Users//np83zg//OneDrive - Aalborg Universitet//Skrivebord//kommunedata//scripts"
setwd(mypath)
anim_save("p2.gif",p)
theme_set(theme_bw())
p <- ggplot(
mydata,
aes(x =residence, y=s2,size=s, colour = as.factor(residence))
) +
geom_point(show.legend = FALSE, alpha = 0.9) +
scale_color_viridis_d() +
scale_size(range = c(2, 12)) +
labs(x = "Municipality ID", y = "Share in agegroup 16-60 relative 1987") +
transition_time(year) +
labs(title = "Year: {frame_time}") +
shadow_mark(alpha = 0.3, size = 0.5)
mypath <- "C://Users//np83zg//OneDrive - Aalborg Universitet//Skrivebord//kommunedata//scripts"
setwd(mypath)
anim_save("p3.gif",p)
mypath <- "C://Users//np83zg//OneDrive - Aalborg Universitet//Skrivebord//kommunedata//data"
setwd(mypath)
library(knitr)
library(egg)
## Warning: package 'egg' was built under R version 4.0.3
## Loading required package: gridExtra
library(forcats)
## Warning: package 'forcats' was built under R version 4.0.3
library(data.table)
library(tmap)
library(sf)
library(ggplot2)
library(dplyr)
##
## Attaching package: 'dplyr'
## The following object is masked from 'package:gridExtra':
##
## combine
## The following objects are masked from 'package:data.table':
##
## between, first, last
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(hrbrthemes)
## Warning: package 'hrbrthemes' was built under R version 4.0.3
library(cartogram)
library(gganimate)
mydata_1 <- as.data.table(read.table("mundata.txt"))
mydata_2 <- as.data.table(read.table("mydata.txt"))
dt <- merge(mydata_2,mydata_1,by.x=c("residence"),by.y="nr")
setkey(dt,density,year)
T <- length(table(dt$year))
dt[,ss:=s-s[1],by=.(residence)]
theme_set(theme_bw())
p <- ggplot(
dt,
aes(x =residence, y=s,size=density, colour = as.factor(residence))
) +
geom_point(show.legend = FALSE, alpha = 0.9) +
scale_color_viridis_d() +
scale_size(range = c(2, 12)) +
labs(x = "Municipality", y = "Share of labour force with high education") +
transition_time(year) +
labs(title = "Year: {frame_time}") +
shadow_mark(alpha = 0.3, size = 0.5)
mypath <- "C://Users//np83zg//OneDrive - Aalborg Universitet//Skrivebord//kommunedata//scripts"
setwd(mypath)
anim_save("p4.gif",p)
