Download Composite Leading Indicator from OECD site. Early Bird Version

# go to OECD site and download CSV from Export menu.
# assume download file name is  "MEI_CLI.csv".
# pick up amplitute justfied OECD total data from CSV

$sed -n '/OECD\ -\ Total/p' MEI_CLI_13112019035737453.csv |grep LOLITOAA | grep Ampli | awk -F, 'BEGIN{ORS = ""}{print $(NF-2)","}'

the improved version is below to integrate all query string into one criteria.

sed -n '/LOLITOAA.*Ampli.*OECD\ -\ Total/p' MEI_CLI.csv | awk -F, 'BEGIN{ORS = "";print "c("}{print $(NF-2)","}END{print $(NF-2)")\n"}'

OR do as below.

awk -F, 'BEGIN{ORS = "";print "w <- c("}/LOLITOAA.*Ampli.*OECD\ -\ Total/{print $(NF-2)","}END{print $(NF-2)")\n length(w)\n"}' MEI_CLI.csv 

output sample is like below. now output is in the from of R statement. Construct vector in c() and substitute to w().

100.7565,100.7652,100.7551,100.7274,100.6736,100.5974,100.512,100.4191,100.3163,100.2006,100.0703,99.93036,99.79047,99.6553,99.53469,99.43623,99.36298,99.30513,99.25108,99.20237,99.15969,99.12648,99.10692

w <- c(100.7565,100.7652,100.7551,100.7274,100.6736,100.5974,100.512,100.4191,100.3163,100.2006,100.0703,99.93036,99.79047,99.6553,99.53469,99.43623,99.36298,99.30513,99.25108,99.20237,99.15969,99.12648,99.10692)

length(w)
[1] 23

# The last month will be found in this way.

sed -n '/LOLITOAA.*Ampli.*OECD\ -\ Total/p' MEI_CLI.csv  | awk -F, 'END{print $7}'
"2019-09"

# as the last entry is "2019-09-01" do as below

w <- as.xts(w,last(seq(as.Date("2010-01-01"),as.Date("2019-09-01"),by='months'),length(w))