Composite Leading Indicator - OECD

# download csv from oecd(https://data.oecd.org/leadind/composite-leading-indicator-cli.htm)
# store it in CLI3.csv
# this file contains multiple regions data. you have to specify the name of the region.
# extract USA only entries
# sed -n '/USA/p' CLI3.csv |awk -F, '{print $6"-01,"$7}'  |sed 's/\"//g' |awk 'BEGIN{print "DATE,DATA"}{print $0}' > usa.csv
# extract OECD entries and exclude OECDE
# sed -n '/OECD[^E]/p' CLI3.csv |awk -F, '{print $6"-01,"$7}'  |sed 's/\"//g' |awk 'BEGIN{print "DATE,DATA"}{print $0}' > oecd.csv

cli_xts <- merge(as.xts(read.zoo(read.csv("~/Downloads/oecd.csv"))),as.xts(read.zoo(read.csv("~/Downloads/usa.csv"))),suffixes = c("oecd","usa"))

plot.default((cli_xts$usa["2012-07::2018-08"]   / as.vector(cli_xts$usa["2012-01::2018-02"])-1)*100,cli_xts$usa["2012-07::2018-08"])
tmp <- par('usr')
plot.default((cli_xts$usa["2012-07::2018-08"] / as.vector(cli_xts$usa["2012-01::2018-02"])-1)*100,cli_xts$usa["2012-07::2018-08"] ,xlim=c( tmp[1],tmp[2]), ylim=c(tmp[3], tmp[4]))
plot.default((cli_xts$usa["2012-07::2018-08"] / as.vector(cli_xts$usa["2012-01::2018-02"])-1)*100,cli_xts$usa["2012-07::2018-08"] ,xlim=c( tmp[1],tmp[2]), ylim=c(tmp[3], tmp[4]))
par(new=T)
plot.default((cli_xts$usa["2017-09::2018-08"] / as.vector(cli_xts$usa["2017-03::2018-02"])-1)*100,cli_xts$usa["2017-09::2018-08"] ,xlim=c( tmp[1],tmp[2]), ylim=c(tmp[3], tmp[4]),col=2)
par(new=T)
plot.default((cli_xts$usa["2016-09::2017-08"] / as.vector(cli_xts$usa["2016-03::2017-02"])-1)*100,cli_xts$usa["2016-09::2017-08"], xlim=c( tmp[1],tmp[2]), ylim=c(tmp[3], tmp[4]),col=3)
par(new=T)
plot.default((cli_xts$usa["2015-09::2016-08"] / as.vector(cli_xts$usa["2015-03::2016-02"])-1)*100,cli_xts$usa["2015-09::2016-08"], xlim=c( tmp[1],tmp[2]), ylim=c(tmp[3], tmp[4]),col=4)