library(WDI)
df = WDI(indicator='NY.GDP.MKTP.CD', country=c('JP'), start=1960, end=2018)
head(df)
## iso2c country NY.GDP.MKTP.CD year
## 1 JP Japan 5.036892e+12 2018
## 2 JP Japan 4.930837e+12 2017
## 3 JP Japan 5.003678e+12 2016
## 4 JP Japan 4.444931e+12 2015
## 5 JP Japan 4.896994e+12 2014
## 6 JP Japan 5.212328e+12 2013
## 2
library(WDI)
df = WDI(indicator=c(un='SL.UEM.TOTL.ZS', enf='FP.CPI.TOTL.ZG' ), country=c('TR'), start=1992, end=2020)
library(dynlm)
## Loading required package: zoo
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
df.ts <- ts(df, start=c(1992), end=c(2020),frequency=1)
head(df.ts)
## iso2c country year un enf
## [1,] 1 1 1992 8.51 70.07610
## [2,] 1 1 1993 8.96 66.09384
## [3,] 1 1 1994 8.58 105.21499
## [4,] 1 1 1995 7.64 89.11332
## [5,] 1 1 1996 6.63 80.41215
## [6,] 1 1 1997 6.84 85.66936
plot(df.ts[,"un"], ylab="işsizlik")
plot(df.ts[,"enf"], ylab="enflasyon")
##3
library(WDI)
gsyh <- WDI(country=c("US", "TR","JP"), indicator=c("NY.GDP.PCAP.CD"), start=1960, end=2020)
names(gsyh) <- c("iso2c", "Ülke", "KisiBasiGSYH", "Sene")
head(gsyh)
## iso2c Ülke KisiBasiGSYH Sene
## 1 JP Japan 40193.25 2020
## 2 JP Japan 40777.61 2019
## 3 JP Japan 39808.17 2018
## 4 JP Japan 38891.09 2017
## 5 JP Japan 39400.74 2016
## 6 JP Japan 34960.64 2015
TR <- cbind(gsyh$KisiBasiGSYH[gsyh$Ülke == "Turkey"], gsyh$Sene[gsyh$Ülke == "Turkey"])
TR <- TR[order(TR[,2]),]
TR
## [,1] [,2]
## [1,] 509.4240 1960
## [2,] 283.8283 1961
## [3,] 309.4466 1962
## [4,] 350.6630 1963
## [5,] 369.5835 1964
## [6,] 386.3581 1965
## [7,] 444.5495 1966
## [8,] 481.6937 1967
## [9,] 526.2135 1968
## [10,] 571.6178 1969
## [11,] 489.9304 1970
## [12,] 455.1049 1971
## [13,] 558.4209 1972
## [14,] 686.4901 1973
## [15,] 927.7992 1974
## [16,] 1136.3756 1975
## [17,] 1275.9566 1976
## [18,] 1427.3718 1977
## [19,] 1549.6444 1978
## [20,] 2079.2203 1979
## [21,] 1564.2472 1980
## [22,] 1579.0738 1981
## [23,] 1402.4064 1982
## [24,] 1310.2557 1983
## [25,] 1246.8245 1984
## [26,] 1368.4017 1985
## [27,] 1510.6763 1986
## [28,] 1705.8944 1987
## [29,] 1745.3649 1988
## [30,] 2021.8595 1989
## [31,] 2794.3505 1990
## [32,] 2735.7076 1991
## [33,] 2842.3700 1992
## [34,] 3180.1876 1993
## [35,] 2270.3373 1994
## [36,] 2897.8666 1995
## [37,] 3053.9472 1996
## [38,] 3144.3857 1997
## [39,] 4499.7375 1998
## [40,] 4116.1706 1999
## [41,] 4337.4780 2000
## [42,] 3142.9210 2001
## [43,] 3687.9561 2002
## [44,] 4760.1040 2003
## [45,] 6101.6321 2004
## [46,] 7456.2961 2005
## [47,] 8101.8569 2006
## [48,] 9791.8825 2007
## [49,] 10941.1721 2008
## [50,] 9103.4741 2009
## [51,] 10742.7750 2010
## [52,] 11420.5555 2011
## [53,] 11795.6335 2012
## [54,] 12614.7816 2013
## [55,] 12157.9904 2014
## [56,] 11006.2795 2015
## [57,] 10894.6034 2016
## [58,] 10589.6677 2017
## [59,] 9454.3484 2018
## [60,] 9121.5152 2019
## [61,] 8536.4333 2020
plot(TR, ylab="Kişi başı GSYH", xlab="Sene")
`
You can also embed plots, for example: