a<- 4 + 2
b<- a + 15
c<- b/a
d<- b*c
a
## [1] 6
b
## [1] 21
c
## [1] 3.5
d
## [1] 73.5
x=c(1,2,3)
y=c("ayse", "fatma", "ali")
g= 10:12
seq (2,8)
## [1] 2 3 4 5 6 7 8
x=c(1, 2, 3)
y=c(4,5,6)
mtcars
## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
## Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
## Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
mtcars[[1]]
## [1] 21.0 21.0 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 17.8 16.4 17.3 15.2 10.4
## [16] 10.4 14.7 32.4 30.4 33.9 21.5 15.5 15.2 13.3 19.2 27.3 26.0 30.4 15.8 19.7
## [31] 15.0 21.4
mtcars[[3]]
## [1] 160.0 160.0 108.0 258.0 360.0 225.0 360.0 146.7 140.8 167.6 167.6 275.8
## [13] 275.8 275.8 472.0 460.0 440.0 78.7 75.7 71.1 120.1 318.0 304.0 350.0
## [25] 400.0 79.0 120.3 95.1 351.0 145.0 301.0 121.0
mtcars[c(1,2,3)]
## mpg cyl disp
## Mazda RX4 21.0 6 160.0
## Mazda RX4 Wag 21.0 6 160.0
## Datsun 710 22.8 4 108.0
## Hornet 4 Drive 21.4 6 258.0
## Hornet Sportabout 18.7 8 360.0
## Valiant 18.1 6 225.0
## Duster 360 14.3 8 360.0
## Merc 240D 24.4 4 146.7
## Merc 230 22.8 4 140.8
## Merc 280 19.2 6 167.6
## Merc 280C 17.8 6 167.6
## Merc 450SE 16.4 8 275.8
## Merc 450SL 17.3 8 275.8
## Merc 450SLC 15.2 8 275.8
## Cadillac Fleetwood 10.4 8 472.0
## Lincoln Continental 10.4 8 460.0
## Chrysler Imperial 14.7 8 440.0
## Fiat 128 32.4 4 78.7
## Honda Civic 30.4 4 75.7
## Toyota Corolla 33.9 4 71.1
## Toyota Corona 21.5 4 120.1
## Dodge Challenger 15.5 8 318.0
## AMC Javelin 15.2 8 304.0
## Camaro Z28 13.3 8 350.0
## Pontiac Firebird 19.2 8 400.0
## Fiat X1-9 27.3 4 79.0
## Porsche 914-2 26.0 4 120.3
## Lotus Europa 30.4 4 95.1
## Ford Pantera L 15.8 8 351.0
## Ferrari Dino 19.7 6 145.0
## Maserati Bora 15.0 8 301.0
## Volvo 142E 21.4 4 121.0
mtcars[ ,3]
## [1] 160.0 160.0 108.0 258.0 360.0 225.0 360.0 146.7 140.8 167.6 167.6 275.8
## [13] 275.8 275.8 472.0 460.0 440.0 78.7 75.7 71.1 120.1 318.0 304.0 350.0
## [25] 400.0 79.0 120.3 95.1 351.0 145.0 301.0 121.0
mtcars[2,4]
## [1] 110
mtcars[ ,c(1,2,3)]
## mpg cyl disp
## Mazda RX4 21.0 6 160.0
## Mazda RX4 Wag 21.0 6 160.0
## Datsun 710 22.8 4 108.0
## Hornet 4 Drive 21.4 6 258.0
## Hornet Sportabout 18.7 8 360.0
## Valiant 18.1 6 225.0
## Duster 360 14.3 8 360.0
## Merc 240D 24.4 4 146.7
## Merc 230 22.8 4 140.8
## Merc 280 19.2 6 167.6
## Merc 280C 17.8 6 167.6
## Merc 450SE 16.4 8 275.8
## Merc 450SL 17.3 8 275.8
## Merc 450SLC 15.2 8 275.8
## Cadillac Fleetwood 10.4 8 472.0
## Lincoln Continental 10.4 8 460.0
## Chrysler Imperial 14.7 8 440.0
## Fiat 128 32.4 4 78.7
## Honda Civic 30.4 4 75.7
## Toyota Corolla 33.9 4 71.1
## Toyota Corona 21.5 4 120.1
## Dodge Challenger 15.5 8 318.0
## AMC Javelin 15.2 8 304.0
## Camaro Z28 13.3 8 350.0
## Pontiac Firebird 19.2 8 400.0
## Fiat X1-9 27.3 4 79.0
## Porsche 914-2 26.0 4 120.3
## Lotus Europa 30.4 4 95.1
## Ford Pantera L 15.8 8 351.0
## Ferrari Dino 19.7 6 145.0
## Maserati Bora 15.0 8 301.0
## Volvo 142E 21.4 4 121.0
mtcars[1:5]
## mpg cyl disp hp drat
## Mazda RX4 21.0 6 160.0 110 3.90
## Mazda RX4 Wag 21.0 6 160.0 110 3.90
## Datsun 710 22.8 4 108.0 93 3.85
## Hornet 4 Drive 21.4 6 258.0 110 3.08
## Hornet Sportabout 18.7 8 360.0 175 3.15
## Valiant 18.1 6 225.0 105 2.76
## Duster 360 14.3 8 360.0 245 3.21
## Merc 240D 24.4 4 146.7 62 3.69
## Merc 230 22.8 4 140.8 95 3.92
## Merc 280 19.2 6 167.6 123 3.92
## Merc 280C 17.8 6 167.6 123 3.92
## Merc 450SE 16.4 8 275.8 180 3.07
## Merc 450SL 17.3 8 275.8 180 3.07
## Merc 450SLC 15.2 8 275.8 180 3.07
## Cadillac Fleetwood 10.4 8 472.0 205 2.93
## Lincoln Continental 10.4 8 460.0 215 3.00
## Chrysler Imperial 14.7 8 440.0 230 3.23
## Fiat 128 32.4 4 78.7 66 4.08
## Honda Civic 30.4 4 75.7 52 4.93
## Toyota Corolla 33.9 4 71.1 65 4.22
## Toyota Corona 21.5 4 120.1 97 3.70
## Dodge Challenger 15.5 8 318.0 150 2.76
## AMC Javelin 15.2 8 304.0 150 3.15
## Camaro Z28 13.3 8 350.0 245 3.73
## Pontiac Firebird 19.2 8 400.0 175 3.08
## Fiat X1-9 27.3 4 79.0 66 4.08
## Porsche 914-2 26.0 4 120.3 91 4.43
## Lotus Europa 30.4 4 95.1 113 3.77
## Ford Pantera L 15.8 8 351.0 264 4.22
## Ferrari Dino 19.7 6 145.0 175 3.62
## Maserati Bora 15.0 8 301.0 335 3.54
## Volvo 142E 21.4 4 121.0 109 4.11
names(mtcars)
## [1] "mpg" "cyl" "disp" "hp" "drat" "wt" "qsec" "vs" "am" "gear"
## [11] "carb"
mtcars["hp"]
## hp
## Mazda RX4 110
## Mazda RX4 Wag 110
## Datsun 710 93
## Hornet 4 Drive 110
## Hornet Sportabout 175
## Valiant 105
## Duster 360 245
## Merc 240D 62
## Merc 230 95
## Merc 280 123
## Merc 280C 123
## Merc 450SE 180
## Merc 450SL 180
## Merc 450SLC 180
## Cadillac Fleetwood 205
## Lincoln Continental 215
## Chrysler Imperial 230
## Fiat 128 66
## Honda Civic 52
## Toyota Corolla 65
## Toyota Corona 97
## Dodge Challenger 150
## AMC Javelin 150
## Camaro Z28 245
## Pontiac Firebird 175
## Fiat X1-9 66
## Porsche 914-2 91
## Lotus Europa 113
## Ford Pantera L 264
## Ferrari Dino 175
## Maserati Bora 335
## Volvo 142E 109
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)
df.ts<-df.ts[,c("un","enf")]