DBnomics: the world’s economic database

Explore all the economic data from different providers (national and international statistical institutes, central banks, etc.), for free, following the link db.nomics.world.

You can also retrieve all the economic data through the rdbnomics package here. This blog post describes the different ways to do so.

Fetch time series by ids

First, let’s assume that we know which series we want to download. A series identifier (ids) is defined by three values, formatted like this: provider_code/dataset_code/series_code.

Fetch one series from dataset ‘Unemployment rate’ (ZUTN) of AMECO provider

df <- rdb(ids = 'AMECO/ZUTN/EA19.1.0.0.0.ZUTN') %>%
  filter(!is.na(value))

In such data.frame (data.table or tibble), you will always find at least ten columns:

• provider_code
• dataset_code
• dataset_name
• series_code
• series_name
• original_period (character string)
• period (date of the first day of original_period)
• original_value (character string)
• value
• @frequency (harmonized frequency generated by DBnomics)

The other columns depend on the provider and on the dataset. They always come in pairs (for the code and the name). In the data.frame df, you have:

• unit (code) and Unit (name)
• geo (code) and Country (name)
• freq (code) and Frequency (name)

ggplot(df, aes(x = period, y = value, color = series_name)) +
  geom_line(size = 1.2) +
  geom_point(size = 2) +
  dbnomics()

In the event that you only use the argument ids, you can drop it and run:

df <- rdb('AMECO/ZUTN/EA19.1.0.0.0.ZUTN')

Fetch two series from dataset ‘Unemployment rate’ (ZUTN) of AMECO provider

df <- rdb(ids = c('AMECO/ZUTN/EA19.1.0.0.0.ZUTN', 'AMECO/ZUTN/DNK.1.0.0.0.ZUTN')) %>%
  filter(!is.na(value))

ggplot(df, aes(x = period, y = value, color = series_name)) +
  geom_line(size = 1.2) +
  geom_point(size = 2) +
  dbnomics()

Fetch two series from different datasets of different providers

df <- rdb(ids = c('AMECO/ZUTN/EA19.1.0.0.0.ZUTN', 'Eurostat/une_rt_q/Q.SA.Y15-74.PC_ACT.T.EA19')) %>%
  filter(!is.na(value))