E3 - Series de tiempo
VFAC
29/11/2020
library(ggcorrplot)
library(tidyverse)
library(visdat)
library(highcharter)
euro_tc <- read_csv("euro-daily-hist_1999_2020.csv")
summary(euro_tc)
Period\\Unit: [Australian dollar ] [Bulgarian lev ] [Brazilian real ]
Min. :1999-01-04 Min. :1.164 Min. :1.944 Min. :1.563
1st Qu.:2004-06-08 1st Qu.:1.473 1st Qu.:1.956 1st Qu.:2.535
Median :2009-11-11 Median :1.605 Median :1.956 Median :2.974
Mean :2009-11-23 Mean :1.579 Mean :1.954 Mean :3.153
3rd Qu.:2015-05-12 3rd Qu.:1.678 3rd Qu.:1.956 3rd Qu.:3.657
Max. :2020-11-20 Max. :2.074 Max. :1.962 Max. :6.768
NA's :62 NA's :460 NA's :329
[Canadian dollar ] [Swiss franc ] [Chinese yuan renminbi ] [Cypriot pound ]
Min. :1.214 Min. :0.9816 Min. : 6.555 Mode:logical
1st Qu.:1.398 1st Qu.:1.1613 1st Qu.: 7.701 NA's:5666
Median :1.467 Median :1.4602 Median : 8.233
Mean :1.469 Mean :1.3621 Mean : 8.611
3rd Qu.:1.544 3rd Qu.:1.5486 3rd Qu.: 9.670
Max. :1.812 Max. :1.6803 Max. :11.284
NA's :62 NA's :62 NA's :329
[Czech koruna ] [Danish krone ] [Estonian kroon ] [UK pound sterling ]
Min. :22.97 Min. :7.423 Mode:logical Min. :0.5711
1st Qu.:25.70 1st Qu.:7.440 NA's:5666 1st Qu.:0.6774
Median :27.11 Median :7.449 Median :0.7880
Mean :28.44 Mean :7.449 Mean :0.7672
3rd Qu.:30.63 3rd Qu.:7.459 3rd Qu.:0.8619
Max. :38.58 Max. :7.473 Max. :0.9786
NA's :62 NA's :62 NA's :62
[Greek drachma ] [Hong Kong dollar ] [Croatian kuna ] [Hungarian forint ]
Mode:logical Min. : 6.436 Min. :7.100 Min. :228.2
NA's:5666 1st Qu.: 8.533 1st Qu.:7.369 1st Qu.:253.5
Median : 9.349 Median :7.445 Median :272.8
Mean : 9.333 Mean :7.460 Mean :280.9
3rd Qu.:10.267 3rd Qu.:7.564 3rd Qu.:309.0
Max. :12.470 Max. :7.770 Max. :369.4
NA's :62 NA's :329 NA's :62
[Indonesian rupiah ] [Israeli shekel ] [Indian rupee ] [Iceland krona ]
Min. : 6708 Min. :3.416 Min. :38.50 Min. : 68.07
1st Qu.:10966 1st Qu.:4.176 1st Qu.:55.19 1st Qu.: 80.92
Median :12454 Median :4.800 Median :65.16 Median : 87.77
Mean :12680 Mean :4.741 Mean :64.38 Mean :100.20
3rd Qu.:15004 3rd Qu.:5.356 3rd Qu.:75.17 3rd Qu.:121.97
Max. :18240 Max. :5.954 Max. :92.06 Max. :305.00
NA's :62 NA's :330 NA's :329 NA's :2407
[Japanese yen ] [Korean won ] [Lithuanian litas ] [Latvian lats ]
Min. : 89.3 Min. : 938.7 Mode:logical Mode:logical
1st Qu.:115.9 1st Qu.:1240.3 NA's:5666 NA's:5666
Median :127.8 Median :1321.3
Mean :127.0 Mean :1349.2
3rd Qu.:135.7 3rd Qu.:1444.0
Max. :169.8 Max. :1994.0
NA's :62 NA's :62
[Maltese lira ] [Mexican peso ] [Malaysian ringgit ] [Norwegian krone ]
Mode:logical Min. : 7.624 Min. :3.155 Min. : 7.223
NA's:5666 1st Qu.:13.112 1st Qu.:4.059 1st Qu.: 7.925
Median :16.562 Median :4.517 Median : 8.194
Mean :16.051 Mean :4.379 Mean : 8.469
3rd Qu.:18.858 3rd Qu.:4.726 3rd Qu.: 8.986
Max. :27.090 Max. :5.186 Max. :12.316
NA's :62 NA's :62 NA's :62
[New Zealand dollar ] [Philippine peso ] [Polish zloty ] [Romanian leu ]
Min. :1.388 Min. :36.84 Min. :3.205 Min. :1.291
1st Qu.:1.665 1st Qu.:52.48 1st Qu.:3.954 1st Qu.:3.515
Median :1.800 Median :58.46 Median :4.171 Median :4.209
Mean :1.829 Mean :57.36 Mean :4.122 Mean :3.862
3rd Qu.:1.986 3rd Qu.:63.08 3rd Qu.:4.297 3rd Qu.:4.474
Max. :2.554 Max. :76.76 Max. :4.935 Max. :4.877
NA's :62 NA's :62 NA's :62 NA's :62
[Russian rouble ] [Swedish krona ] [Singapore dollar ] [Slovenian tolar ]
Min. :23.19 Min. : 8.055 Min. :1.440 Mode:logical
1st Qu.:34.35 1st Qu.: 9.035 1st Qu.:1.585 NA's:5666
Median :39.69 Median : 9.250 Median :1.704
Mean :45.94 Mean : 9.394 Mean :1.765
3rd Qu.:62.54 3rd Qu.: 9.589 3rd Qu.:1.993
Max. :93.75 Max. :11.713 Max. :2.232
NA's :62 NA's :62 NA's :62
[Slovak koruna ] [Thai baht ] [Turkish lira ] [US dollar ]
Mode:logical Min. :33.20 Min. : 0.3701 Min. :0.8252
NA's:5666 1st Qu.:38.54 1st Qu.: 1.6774 1st Qu.:1.0978
Median :40.83 Median : 2.0953 Median :1.2014
Mean :42.09 Mean : 2.6509 Mean :1.1996
3rd Qu.:46.12 3rd Qu.: 3.0377 3rd Qu.:1.3212
Max. :53.54 Max. :10.1489 Max. :1.5990
NA's :62 NA's :62 NA's :62
[South African rand ]
Min. : 6.079
1st Qu.: 8.377
Median :10.395
Mean :11.350
3rd Qu.:14.413
Max. :20.845
NA's :62
euro_tc2 <- euro_tc %>% select(-"[Cypriot pound ]", - "[Estonian kroon ]", -"[Greek drachma ]", -"[Lithuanian litas ]", -"[Latvian lats ]", -"[Maltese lira ]", -"[Slovenian tolar ]", -"[Slovak koruna ]")
euro_tc2 <- euro_tc2 %>% rename(Date = "Period\\Unit:") %>%
mutate(Date = as.Date(Date)) %>% rename(AusDollar = "[Australian dollar ]")
euro_tc3 <- euro_tc2 %>% mutate(Date = as.numeric(Date))
correlacion <- cor(euro_tc3[1:33], method = "spearman")
ggcorrplot(correlacion)
ggplot(data = euro_tc2, aes(x = Date, y = AusDollar )) +
geom_line(colour="red") +
theme_minimal()
