library(ChileDataAPI)
library(ggplot2)
library(dplyr)
#>
#> Adjuntando el paquete: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
The ChileDataAPI
package provides a unified interface to
access open data from the FINDIC API and the REST Countries
API, with a focus on Chile. It allows users to easily retrieve
up-to-date time series data on financial indicators such as the
UF, UTM, Dollar, Euro, Yen, Copper price per pound, Bitcoin, and
the IPSA index, as well as international metadata on countries
via standardized API calls.
All API-based functions return data as tidy tibble objects, making
them ready for immediate use in data pipelines. The financial indicator
functions, such as get_chile_dollar()
,
get_chile_uf()
, and get_chile_bitcoin()
,
provide real-time series of daily or monthly values, with each row
representing a timestamped observation. This makes
ChileDataAPI
a valuable tool for working with economic time
series data in a reproducible manner.
In addition to API-access functions, the package includes a collection of curated datasets related to Chile, covering diverse topics such as:
Demographics
: sample microdata from the 2017 Chilean
Census
Elections
: data from the 2021 presidential elections
and national plebiscites
Public health
: individual-level records from
national health surveys
Human rights
: detailed accounts of violations during
the Pinochet regime
Seismology
: geolocated data on earthquakes in
Chile
Geopolitical data
: official territorial codes for
communes, provinces, and regions
Environmental history
: tree-ring based climate
series from Malleco forest
ChileDataAPI
is designed to support research, teaching,
and data analysis focused on Chile by integrating public
RESTful APIs with high-quality, domain-specific datasets into a single,
easy-to-use R package.
The ChileDataAPI
package provides several core functions
to access real-time and structured information about Chile from public
APIs such as FINDIC and REST Countries. Below is a list of
the main functions included in the package:
get_chile_bitcoin()
: Retrieves the daily Bitcoin
price in Chilean Pesos over the last month.
get_chile_copper_pound()
: Returns historical daily
copper prices (per pound).
get_chile_dollar()
: Provides the exchange rate of
the U.S. Dollar in CLP.
get_chile_euro()
: Provides the exchange rate of the
Euro in CLP.
get_chile_ipsa()
: Retrieves daily values of the IPSA
(Chile’s stock market index).
get_chile_uf()
: Returns daily values of the Unidad
de Fomento (UF).
get_chile_utm()
: Returns monthly values of the
Unidad Tributaria Mensual (UTM).
get_chile_yen()
: Provides the exchange rate of the
Japanese Yen in CLP.
get_country_info(name)
: Get essential information
about Chile or any other country by its full name Example:
get_country_info(“Chile”),get_country_info(“chile”),get_country_info(“Peru”)
view_datasets_ChileDataAPI()
: Lists all curated
datasets included in the ChileDataAPI
package
These functions return real-time data in tidy tibble
format and represent time series that are updated daily
or monthly depending on the source.
These functions allow users to access high-quality and structured
information on Chile
, which can be combined with tools like
dplyr
, tidyr
, and ggplot2
to
support a wide range of data analysis and visualization tasks. In the
following sections, you’ll find examples on how to work with
ChileDataAPI
in practical scenarios.
chile_copper_price <- head(get_chile_copper_pound(),n=10)
print(chile_copper_price)
#> # A tibble: 10 × 2
#> fecha valor
#> <chr> <dbl>
#> 1 2025-07-11 4.38
#> 2 2025-07-10 4.46
#> 3 2025-07-09 4.49
#> 4 2025-07-08 4.52
#> 5 2025-07-07 4.56
#> 6 2025-07-04 4.59
#> 7 2025-07-03 4.56
#> 8 2025-07-02 4.56
#> 9 2025-07-01 4.59
#> 10 2025-06-30 4.64
chile_dollar_price <- head(get_chile_dollar(),n=10)
print(chile_dollar_price)
#> # A tibble: 10 × 2
#> fecha valor
#> <chr> <dbl>
#> 1 2025-07-11 950.
#> 2 2025-07-10 948.
#> 3 2025-07-09 945.
#> 4 2025-07-08 940.
#> 5 2025-07-07 932.
#> 6 2025-07-04 928.
#> 7 2025-07-03 927.
#> 8 2025-07-02 927.
#> 9 2025-07-01 933.
#> 10 2025-06-30 936.
chile_euro_price <- head(get_chile_euro(),n=10)
print(chile_euro_price)
#> # A tibble: 10 × 2
#> fecha valor
#> <chr> <dbl>
#> 1 2025-07-11 1111.
#> 2 2025-07-10 1111.
#> 3 2025-07-09 1108.
#> 4 2025-07-08 1101.
#> 5 2025-07-07 1098.
#> 6 2025-07-04 1090.
#> 7 2025-07-03 1093.
#> 8 2025-07-02 1091.
#> 9 2025-07-01 1099.
#> 10 2025-06-30 1094.
# Clean data: remove missing values from key variables
health_clean <- chile_health_survey_df %>%
filter(!is.na(age), !is.na(pas), !is.na(male))
# Create gender variable
health_clean <- health_clean %>%
mutate(gender = ifelse(male == 1, "Male", "Female"))
# Plot: Systolic Blood Pressure vs Age by Gender
ggplot(health_clean, aes(x = age, y = pas, color = gender)) +
geom_point(alpha = 0.4) +
geom_smooth(method = "lm", se = FALSE) +
labs(
title = "Systolic Blood Pressure (PAS) by Age and Gender",
x = "Age (years)",
y = "Systolic Blood Pressure (mm Hg)",
color = "Gender"
) +
theme_minimal()
Each dataset in ChileDataAPI
is labeled with a
suffix to indicate its structure and type:
_df
: A standard data frame.
_ts
: A time series object.
_tbl_df
: A tibble data frame object.
In addition to API access functions, ChileDataAPI
provides several curated datasets offering valuable insights into
Chile’s recent history, population health, territorial
divisions, electoral processes, and seismic activity. Here are some
featured examples:
census_chile_2017_df
: Data frame containing
microdata from the 2017 Chilean census, specifically from the commune of
San Pablo. The dataset includes 7,512 observations, all variable names
and data values are in Spanish.
chile_earthquakes_tbl_df
: Tibble containing
information about significant (perceptible) earthquakes that occurred in
Chile from January 1st, 2012 to the present.
malleco_tree_rings_ts
: Time series object
(ts
) containing the average annual tree ring width,
measured in millimeters, for Araucaria Araucana trees located in the
Malleco region of Chile.
The ChileDataAPI
package provides a robust set of tools
to access open data about Chile through RESTful APIs
and curated datasets. It includes functions to retrieve real-time
financial indicators—such as the value of the dollar, euro, yen, copper,
UF, UTM, and Bitcoin—via the FINDIC API, as well as
international country information through the REST Countries
API. Additionally, it offers preloaded datasets covering
Chile’s recent history and socio-political context, including
the 2017 census sample, the 2021 presidential election, public health
survey data, territorial codes, seismic events, and records of human
rights violations during the Pinochet regime.