Importación de datos

datos2=scan("http://robjhyndman.com/tsdldata/data/nybirths.dat")
datos3=scan("http://robjhyndman.com/tsdldata/data/fancy.dat")
head(datos3)
## [1] 1664.81 2397.53 2840.71 3547.29 3752.96 3714.74
datos3
##  [1]   1664.81   2397.53   2840.71   3547.29   3752.96   3714.74   4349.61
##  [8]   3566.34   5021.82   6423.48   7600.60  19756.21   2499.81   5198.24
## [15]   7225.14   4806.03   5900.88   4951.34   6179.12   4752.15   5496.43
## [22]   5835.10  12600.08  28541.72   4717.02   5702.63   9957.58   5304.78
## [29]   6492.43   6630.80   7349.62   8176.62   8573.17   9690.50  15151.84
## [36]  34061.01   5921.10   5814.58  12421.25   6369.77   7609.12   7224.75
## [43]   8121.22   7979.25   8093.06   8476.70  17914.66  30114.41   4826.64
## [50]   6470.23   9638.77   8821.17   8722.37  10209.48  11276.55  12552.22
## [57]  11637.39  13606.89  21822.11  45060.69   7615.03   9849.69  14558.40
## [64]  11587.33   9332.56  13082.09  16732.78  19888.61  23933.38  25391.35
## [71]  36024.80  80721.71  10243.24  11266.88  21826.84  17357.33  15997.79
## [78]  18601.53  26155.15  28586.52  30505.41  30821.33  46634.38 104660.67
length(datos3)
## [1] 84

Conversion de datos

st=ts(datos3,start = c(1987,1),frequency = 12)
plot(st)

st
##            Jan       Feb       Mar       Apr       May       Jun       Jul
## 1987   1664.81   2397.53   2840.71   3547.29   3752.96   3714.74   4349.61
## 1988   2499.81   5198.24   7225.14   4806.03   5900.88   4951.34   6179.12
## 1989   4717.02   5702.63   9957.58   5304.78   6492.43   6630.80   7349.62
## 1990   5921.10   5814.58  12421.25   6369.77   7609.12   7224.75   8121.22
## 1991   4826.64   6470.23   9638.77   8821.17   8722.37  10209.48  11276.55
## 1992   7615.03   9849.69  14558.40  11587.33   9332.56  13082.09  16732.78
## 1993  10243.24  11266.88  21826.84  17357.33  15997.79  18601.53  26155.15
##            Aug       Sep       Oct       Nov       Dec
## 1987   3566.34   5021.82   6423.48   7600.60  19756.21
## 1988   4752.15   5496.43   5835.10  12600.08  28541.72
## 1989   8176.62   8573.17   9690.50  15151.84  34061.01
## 1990   7979.25   8093.06   8476.70  17914.66  30114.41
## 1991  12552.22  11637.39  13606.89  21822.11  45060.69
## 1992  19888.61  23933.38  25391.35  36024.80  80721.71
## 1993  28586.52  30505.41  30821.33  46634.38 104660.67

Interpretación

desde enero a diciembre de 1987 se obserba un increnmento en las ventas seguido por una caida estrepitosa y asi constantemente en los siguientes años, con el mes de noviembre y diciembre es dode observamos más ventas de recuerdos. se observa una lijera tendencia.

Exportar los datos

library(writexl)
## Warning: package 'writexl' was built under R version 4.5.1
write_xlsx(as.data.frame(datos2),"datos2_examen1.xlsx")
write_xlsx(as.data.frame(datos3),"datos3_examen1.xlsx")

Diferencias

st1d=diff(st,1)
plot(st1d)

st1d12=diff(st1d,12)
plot(st1d12)