An R interface to download data from Banxico's (Bank of Mexico) SIE (Sistema de Información Económica)
This package is loosely based on the syntax and ideas behind inegiR.
However, the Bank of Mexico does not have an API, so this package basically uses
rvest to scrape iqy calls.
These return html tables and the package does what it can to save it in a convenient
list (same as inegiR).
A few caveats:
- I do not control the data definitions at the source (Banxico), so I can't guarantee continuos use.
- Finding the ID of each series has proven a manual, slow and tedious process because they are not available in the webpage. I'm trying to contact Banxico about getting a catalog, and I'll probably save a dataset in the package, but a lot of indicators will probably be missing. Use at your own risk.
Finding series ID's
To find a specific series ID, I would recommend going to the SIE webpage, navigating towards the desired indicators and then consulting them via HTML. The column name should be the series id (they are usually in this format: "SF60653", with two characters followed by numbers). The package includes a small and non exhaustive catalog of series in spanish. You can access this by
Then you can find some id's...
library(banxicoR) library(dplyr) data("BanxicoCatalog") # To see how many id's by parent subject BanxicoCatalog %>% group_by(PARENT) %>% summarise("Id's" = n()) # Source: local data frame [4 x 2] # PARENT Id's # (chr) (int) # 1 Billetes y Monedas 45 # 2 Intermediarios Financierios 37 # 3 Sistemas de Pago 49 # 4 Tipo de Cambio 2 # to bring the specific id of the average duration of 200 peso bills... BanxicoCatalog %>% filter(PARENT == "Billetes y Monedas") %>% filter(LEVEL_1 == "Duración promedio del billete") %>% filter(LEVEL_2 == "200 pesos") %>% select(ID) # Source: local data frame [1 x 1] # ID # (chr) #1 SM32
Now that you have some id's to download, we can use the
# Download the Bank of Mexico international reserves rsv <- banxico_series(series = "SF110168") tail(rsv) # DATE SF110168 # 2016-01-01 176321.4 # 2016-02-01 178408.8 # 2016-03-01 179708.0 # 2016-04-01 182118.8 # 2016-05-01 179351.0 # 2016-06-01 178829.9
If you want some other fancy things, you can use the options...
rsv <- banxico_series(series = "SF110168", metadata = TRUE, verbose = TRUE) #  "Data series: SF110168 downloaded" #  "Data series in monthly frequency" #  "Parsing data with 198 rows" str(rsv) #List of 2 # $ MetaData:List of 6 # ..$ IndicatorName: chr "I. Official Reserve Assets And Other Foreign Currency Assets - A. Official Reserve Assets" # ..$ IndicatorId : chr "SF110168" # ..$ Units : chr "millions of u.s. dollar" # ..$ DataType : chr "market value/price" # ..$ Period : chr "jan 2000 - jun 2016" # ..$ Frequency : chr "monthly" # $ Data :'data.frame': 198 obs. of 2 variables: # ..$ Dates : Date[1:198], format: "2000-01-01" ... # ..$ SF110168: num [1:198] 33689 33382 36435 34749 33624 ...
Finally, we can graph this...
library(ggplot2) library(eem) # theme from: https://github.com/Eflores89/eem ggplot(rsv$Data, aes(x = Dates, y = SF110168))+ geom_path(colour = eem_colors)+ theme_eem()+ labs(x = "Dates", y = paste0("Reserves in U.S. Dollars \n (", rsv$MetaData$Units, ")"), title = "Bank of Mexico International Reserves")
This data series is also available at INEGI and can be downloaded with inegiR but Banxico has other interesting series exclusive to them, like financial loans or money in circulation, which I encourage everyone to check out!
Tweet me up if you have any suggestions / improvements.