Search series
Banco de España (BdE) provides several time-series,either produced by the institution itself or compiled for anothersources, asEurostat orINE.
The basic entry point for searching time-series are the catalogs(indexes) of information. You can search any series byname:
library(tidyBdE)library(ggplot2)library(dplyr)library(tidyr)# Search GBP on "TC" (exchange rate) catalogXR_GBP<-bde_catalog_search("GBP",catalog ="TC")XR_GBP%>%select(Numero_secuencial, Descripcion_de_la_serie)%>%# To table on document knitr::kable()
| Numero_secuencial | Descripcion_de_la_serie |
|---|
| 573214 | Tipo de cambio. Libras esterlinas por euro(GBP/EUR).Datos diarios |
Note that BdE files are only provided in Spanish, for thetime being, the organism is working on the English version. Bynow, search terms should be provided in Spanish in order to get searchresults.
After we have found our series, we can load the series for theGBP/EUR exchange rate using the sequential number reference(Numero_Secuencial) as:
seq_number<- XR_GBP%>%# First recordslice(1)%>%# Get idselect(Numero_secuencial)%>%# Convert to numas.double()seq_number#> [1] 573214time_series<-bde_series_load(seq_number,series_label ="EUR_GBP_XR")%>%filter(Date>="2010-01-01"& Date<="2020-12-31")%>%drop_na()
Plot series
The package also provides a customggplot2 themebased on the publications of BdE:
ggplot(time_series,aes(x = Date,y = EUR_GBP_XR))+geom_line(colour =bde_tidy_palettes(n =1))+geom_smooth(method ="gam",colour =bde_tidy_palettes(n =2)[2])+labs(title ="EUR/GBP Exchange Rate (2010-2020)",subtitle ="%",caption ="Source: BdE" )+geom_vline(xintercept =as.Date("2016-06-23"),linetype ="dotted" )+geom_label(aes(x =as.Date("2016-06-23"),y = .95,label ="Brexit" ))+coord_cartesian(ylim =c(0.7,1))+theme_tidybde()
EUR/GBP Exchange Rate (2010-2020)
The package provides also several “shortcut” functions for aselection of the most relevant macroeconomic series, so there is no needto look for them in advance:
# Data in "long" formatplotseries<-bde_ind_gdp_var("GDP YoY",out_format ="long")%>%bind_rows(bde_ind_unemployment_rate("Unemployment Rate",out_format ="long") )%>%drop_na()%>%filter(Date>="2010-01-01"& Date<="2019-12-31")ggplot(plotseries,aes(x = Date,y = serie_value))+geom_line(aes(color = serie_name),linewidth =1)+labs(title ="Spanish Economic Indicators (2010-2019)",subtitle ="%",caption ="Source: BdE" )+theme_tidybde()+scale_color_bde_d(palette ="bde_vivid_pal")# Custom palette on the package
Spanish Economic Indicators (2010-2019)
A note on caching
You can usetidyBdE to create your own localrepository at a given local directory passing the following option:
options(bde_cache_dir ="./path/to/location")
When this option is set,tidyBdE would look for thecached file on thebde_cache_dir directory and it will loadit, speeding up the process.
It is possible to update the data (i.e. after every monthly orquarterly data release) with the following commands:
bde_catalog_update()# On most of the functions using the option update_cache = TRUEbde_series_load("SOME ID",update_cache =TRUE)