Title: | Simplify Access to Data from the Amazon Region |
Version: | 1.1.0 |
Description: | Functions to download and treat data regarding the Brazilian Amazon region from a variety of official sources. |
License: | MIT + file LICENSE |
URL: | https://www.econ.puc-rio.br/datazoom/ |
Depends: | R (≥ 4.0) |
Imports: | data.table, dplyr, Hmisc, janitor, magrittr, purrr, readr, readxl, sf, sidrar, stringi, stringr, tibble, tidyr, utils, XML |
Suggests: | foreign, googledrive, knitr, RCurl, rmarkdown, terra |
LinkingTo: | Rcpp |
VignetteBuilder: | knitr |
Encoding: | UTF-8 |
LazyData: | true |
RoxygenNote: | 7.2.3 |
NeedsCompilation: | yes |
Packaged: | 2023-12-12 20:09:24 UTC; igorr |
Author: | Igor Rigolon Veiga [aut, cre], DataZoom (PUC-Rio) [fnd], Guilherme Jardim [aut], Daniel AC Barbosa [aut], Bruno Alcantara Duarte [aut], Fredie Didier [aut], Tito Bruni [aut], Luiz Guilherme Lopes Moussatche [aut], Victor Aliende da Matta [aut], Anna Carolina Dutra Saraiva [aut], Arthur Carvalho Brito [aut], Francisco de Lima Cavalcanti [aut], Maria Mittelbach [aut] |
Maintainer: | Igor Rigolon Veiga <igor.rilave@hotmail.com> |
Repository: | CRAN |
Date/Publication: | 2023-12-12 21:20:06 UTC |
Decompress a DBC (compressed DBF) file
Description
This function allows you decompress a DBC file into its DBF counterpart. Please note that this is the file format used by the Brazilian Ministry of Health (DATASUS), and it is not related to the FoxPro or CANdb DBC file formats.
Usage
dbc2dbf(input.file, output.file)
Arguments
input.file |
The name of the DBC file (including extension) |
output.file |
The output file name (including extension) |
Details
DBC is the extension for compressed DBF files (from the 'XBASE' family of databases). This is a proprietary file format used by the brazilian government to make available public healthcare datasets (by it's agency called DATASUS).
It uses internally the PKWare's Data Compression Library (DCL) "implode" compression algorithm. When decompressed, it becomes a regular DBF file.
Value
Return TRUE if succeded, FALSE otherwise.
Author(s)
Daniela Petruzalek, daniela.petruzalek@gmail.com
Source
The internal C code for dbc2dbf
is based on blast
decompressor and blast-dbf
(see References).
References
The PKWare ZIP file format documentation (contains the "implode" algorithm specification) available at https://support.pkware.com, current version https://pkware.cachefly.net/webdocs/casestudies/APPNOTE.TXT.
blast
source code in C: https://github.com/madler/zlib/tree/master/contrib/blast
blast-dbf
, DBC to DBF command-line decompression tool: https://github.com/eaglebh/blast-dbf
See Also
read.dbc
Examples
## Not run:
# Input file name
in.f <- system.file("files/sids.dbc", package = "read.dbc")
# Output file name
out.f <- tempfile(fileext = ".dbc")
# The call return logi = TRUE on success
if (dbc2dbf(input.file = in.f, output.file = out.f)) {
print("File decompressed!")
file.remove(out.f)
}
## End(Not run)
ANEEL
Description
National Electric Energy Agency - ANEEL
Usage
load_aneel(dataset, raw_data = FALSE, language = "eng")
Arguments
dataset |
A dataset name ("energy_development_budget", "energy_generation" or "energy_enterprises_distributed") |
raw_data |
A |
language |
A |
Examples
## Not run:
# download treated data about energy generation
clean_aneel <- load_aneel(
dataset = "energy_generation",
raw_data = FALSE
)
## End(Not run)
BACI - Global international trade
Description
Loads disaggregated data on bilateral trade flows for more than 5000 products and 200 countries.
Usage
load_baci(dataset = "HS92", raw_data = FALSE, time_period, language = "eng")
Arguments
dataset |
A dataset name ("HS92"). |
raw_data |
A |
time_period |
A |
language |
A |
Value
A tibble
.
Examples
## Not run:
# download treated data for 2016 (takes a long time to download)
clean_baci <- load_baci(
raw_data = FALSE,
time_period = 2016
)
## End(Not run)
Comex - Brazilian external trade
Description
Loads data on all products imported to or exported from Brazil.
Usage
load_br_trade(dataset, raw_data = FALSE, time_period, language = "eng")
Arguments
dataset |
A dataset name ("comex_export_mun", "comex_import_mun", "comex_export_prod" or "comex_import_prod"). |
raw_data |
A |
time_period |
A |
language |
A |
Value
A tibble
.
Examples
## Not run:
# download treated (raw_data = FALSE) exports data by municipality (dataset = "comex_export_mun")
# from 2020 to 2021 (time_period = 2020:2021)
data <- load_br_trade(
dataset = "comex_export_mun",
raw_data = FALSE,
time_period = 2020:2021
)
# download treated(raw_data = FALSE) imports data by municipality (dataset = "comex_import_mun")
# from 2020 to 2021 (time_period = 2020:2021)
data <- load_br_trade(
dataset = "comex_import_mun",
raw_data = FALSE,
time_period = 2020:2021
)
## End(Not run)
CEMPRE - Central Register of Companies
Description
Loads information on companies and other organizations and their respective formally constituted local units, registered with the CNPJ - National Register of Legal Entities.
Usage
load_cempre(
dataset = "cempre",
raw_data = FALSE,
geo_level,
time_period,
language = "eng",
sectors = FALSE
)
Arguments
dataset |
A dataset name ("cempre"). |
raw_data |
A |
geo_level |
A |
time_period |
A |
language |
A |
sectors |
A |
Value
A tibble
.
Examples
## Not run:
# Download raw data (raw_data = TRUE) at the country level
# from 2008 to 2010 (time_period = 2008:2010).
data <- load_cempre(
raw_data = TRUE,
geo_level = "country",
time_period = 2008:2010
)
# Download treted data (raw_data = FALSE) by state (geo_level = "state")
# from 2008 to 2010 (time_period = 2008:2010) in portuguese (language = "pt").
# In this example, data is split by sector (sectors = TRUE)
data <- load_cempre(
raw_data = FALSE,
geo_level = "state",
time_period = 2008:2010,
language = "pt",
sectors = TRUE
)
## End(Not run)
Censo Agropecuario
Description
Loads information on agricultural establishments and activities
Usage
load_censoagro(
dataset,
raw_data = FALSE,
geo_level,
time_period,
language = "eng"
)
Arguments
dataset |
A dataset name ("agricultural_land_area", "agricultural_area_use", "agricultural_employees_tractors", "agricultural_producer_condition", "animal_species", "animal_products", "vegetable_production_area", "vegetable_production_permanent", "vegetable_production_temporary", "livestock_production"). |
raw_data |
A |
geo_level |
A
|
time_period |
A |
language |
A |
Value
A tibble
.
Examples
## Not run:
# Download total land area data at the country level in year 2006
data <- load_censoagro(
dataset = "agricultural_land_area",
raw_data = TRUE,
geo_level = "country",
time_period = 2006
)
# Download temporary production crops data by state (geo_level = "state") in year 2006
in portuguese (language = "pt").
data <- load_censoagro(
dataset = "vegetable_production_temporary",
raw_data = FALSE,
geo_level = "state",
time_period = 1996,
language = "pt"
)
## End(Not run)
## We should include support for microregion/mesoregion
TerraClimate - Climate monitoring
Description
Spatial data on climate variables, extracted from Climatology Lab's TerraClimate.
Usage
load_climate(
dataset,
raw_data = FALSE,
time_period,
language = "eng",
legal_amazon_only = FALSE
)
Arguments
dataset |
A dataset name, choosing which variable will be loaded. One of ("max_temperature", "min_temperature", "wind_speed", "vapor_pressure_deficit", "vapor_pressure", "snow_water_equivalent", "shortwave_radiation_flux", "soil_moisture", "runoff", "precipitation", "potential_evaporation", "climatic_water_deficit", "water_evaporation", "palmer_drought_severity_index"). For extra details, try |
raw_data |
A |
time_period |
A |
language |
A |
legal_amazon_only |
A |
Value
A tibble
.
Examples
## Not run:
# Downloading maximum temperature data from 2000 to 2001
max_temp <- load_climate(dataset = "max_temperature", time_period = 2000:2001)
# Downloading precipitation data only for the legal Amazon in 2010
amz_precipitation <- load_climate(
dataset = "precipitation",
time_period = 2010,
legal_amazon_only = TRUE
)
## End(Not run)
DATASUS - Mortality, hospitalizations and hospital beds
Description
Loads DATASUS data on health establishments, mortality, access to health services and several health indicators.
Usage
load_datasus(
dataset,
time_period,
states = "all",
raw_data = FALSE,
keep_all = FALSE,
language = "eng"
)
Arguments
dataset |
A dataset name, can be one of ("datasus_sim_do", "datasus_sih", "datasus_cnes_lt"), or more. For more details, try |
time_period |
A |
states |
A |
raw_data |
A |
keep_all |
A |
language |
A |
Value
A tibble
.
Examples
## Not run:
# download raw data for the year 2010 in the state of AM.
data <- load_datasus(
dataset = "datasus_sim_do",
time_period = 2010,
states = "AM",
raw_data = TRUE
)
# download treated data with the number of deaths by cause in AM and PA.
data <- load_datasus(
dataset = "datasus_sim_do",
time_period = 2010,
states = c("AM", "PA"),
raw_data = FALSE
)
# download treated data with the number of deaths by cause in AM and PA
# keeping all individual variables.
data <- load_datasus(
dataset = "datasus_sim_do",
time_period = 2010,
states = c("AM", "PA"),
raw_data = FALSE,
keep_all = TRUE
)
## End(Not run)
Degrad - Forest Degradation in the Brazilian Amazon
Description
Loads information on forest degradation in the Brazilian Amazon, replaced by DETER-B in December 2016.
Usage
load_degrad(
dataset = "degrad",
raw_data = FALSE,
time_period,
language = "eng"
)
Arguments
dataset |
A dataset name ("degrad"). |
raw_data |
A |
time_period |
A |
language |
A |
Value
A list
of tibbles (if raw_data
= TRUE
) or a tibble (if raw_data
= FALSE
).
Examples
## Not run:
# download treated data (raw_data = TRUE) related to forest degradation
# from 2010 to 2012 (time_period = 2010:2012).
data <- load_degrad(
dataset = "degrad",
raw_data = FALSE,
time_period = 2010:2012
)
## End(Not run)
DETER - Forest Degradation in the Brazilian Amazon
Description
Loads data on changes in forest cover in the Legal Amazon and the Cerrado biome.
Usage
load_deter(dataset, raw_data = FALSE, language = "eng")
Arguments
dataset |
A dataset name ("deter_amz", "deter_cerrado") with information about the Legal Amazon and Cerrado, respectively |
raw_data |
A |
language |
A |
Value
A sf
object.
Examples
## Not run:
# Download treated data (raw_data = FALSE) from Amazonia (dataset = "deter_amz")
deter_amz <- load_deter(
dataset = "deter_amz",
raw_data = FALSE
)
## End(Not run)
EPE
Description
Electrical Energy Monthly Consumption per Class
Usage
load_epe(dataset, raw_data = FALSE, geo_level = "state", language = "eng")
Arguments
dataset |
A dataset name, ("energy_consumption_per_class") or ("national_energy_balance") |
raw_data |
A |
geo_level |
A geographical level, ("state") or ("subsystem"), only available for "energy_consumption_per_class" |
language |
A |
Examples
## Not run:
# download treated data about energy consumption at the state level
clean_epe <- load_epe(
dataset = "energy_consumption_per_class",
geo_level = "state",
raw_data = FALSE
)
## End(Not run)
IBAMA - Brazilian Institute for the Environment and Renewable Natural Resources
Description
Loads information on environmental fines in the Amazon region
Usage
load_ibama(dataset, raw_data = FALSE, states = "all", language = "eng")
Arguments
dataset |
A dataset name ("embargoed_areas", "distributed_fines", or "collected_fines") |
raw_data |
A |
states |
A |
language |
A |
Value
A tibble
.
Examples
## Not run:
# Download treated embargoes data (raw_data = FALSE) in english (language = "eng")
data <- load_ibama(
dataset = "embargoed_areas", raw_data = FALSE,
language = "eng"
)
# Download treated collected fines data from "BA"
data <- load_ibama(
dataset = "collected_fines", raw_data = FALSE,
states = "BA", language = "pt"
)
## End(Not run)
IEMA - Institute of Environment and Water Resources
Description
Loads information on electric energy access at the municipality level in the Amazon region
Usage
load_iema(dataset = "iema", raw_data = FALSE, language = "eng")
Arguments
dataset |
A dataset name ("iema") |
raw_data |
A |
language |
A |
Value
A tibble
.
Examples
## Not run:
# Download treated data
data <- load_iema(raw_data = FALSE)
## End(Not run)
IMAZON - Deforestation pressure by municipality
Description
Loads data categorizing each municipality by the level of deforestation pressure it faces
Usage
load_imazon(dataset = "imazon_shp", raw_data = FALSE, language = "eng")
Arguments
dataset |
There is one dataset available ("imazon_shp") |
raw_data |
A |
language |
A |
Value
A tibble
.
Examples
## Not run:
# Download treated data
data <- load_imazon(raw_data = FALSE)
## End(Not run)
IPS - Amazon Social Progress Index
Description
Loads information on the social and environmental performance of the Legal Amazon.
Usage
load_ips(
dataset = "all",
raw_data = FALSE,
time_period = c(2014, 2018, 2021, 2023),
language = "eng"
)
Arguments
dataset |
A dataset name ("all", "life_quality", "sanit_habit", "violence", "educ", "communic", "mortality", or "deforest") |
raw_data |
A |
time_period |
Year to download. Can be 2014, 2018, 2021, 2023, or a vector with some combination thereof |
language |
A |
Value
A tibble
.
Examples
## Not run:
# Download raw data from 2014
data <- load_ips(dataset = "all", raw_data = TRUE, time_period = 2014)
# Download treated deforest data from 2018 in portuguese
data <- load_ips(
dataset = "deforest", raw_data = FALSE,
time_period = 2018, language = "pt"
)
## End(Not run)
MAPBIOMAS - The Annual Land Cover and Use Mapping Project in Brazil
Description
Loads information about land cover and use
Usage
load_mapbiomas(
dataset,
raw_data = FALSE,
geo_level = "municipality",
language = "eng"
)
Arguments
dataset |
A dataset name ("mapbiomas_cover", "mapbiomas_transition", "mapbiomas_irrigation", "mapbiomas_deforestation_regeneration", "mapbiomas_mining", "mapbiomas_water" or "mapbiomas_fire") |
raw_data |
A |
geo_level |
A
|
language |
A |
Value
A tibble
.
Examples
## Not run:
# download treated Mapbiomas Cover data in English
data <- load_mapbiomas(
dataset = "mapbiomas_cover",
raw_data = FALSE,
geo_level = "municipality",
language = "eng"
)
# download treated data on mining on indigenous lands
data <- load_mapbiomas("mapbiomas_mining",
raw_data = FALSE,
geo_level = "indigenous_land"
)
## End(Not run)
PAM - Municipal Agricultural Production
Description
Loads information on the quantity, value and area of temporary and permanent crops cultivated.
Usage
load_pam(dataset, raw_data = FALSE, geo_level, time_period, language = "eng")
Arguments
dataset |
A dataset name ("all_crops", "permanent_crops", "temporary_crops" or many individual crop possibilities (see |
raw_data |
A |
geo_level |
A |
time_period |
A |
language |
A |
Value
A tibble
consisting of geographic units that present positive values for any of the variables in the dataset.
Examples
## Not run:
# download treated data at the state level from 2010 to 2011 for all crops
data <- load_pam(
dataset = "all_crops",
raw_data = FALSE,
geo_level = "state",
time_period = 2010:2011,
language = "eng"
)
## End(Not run)
PEVS - Forestry Activities
Description
Loads information on the amount and value of the production of the exploitation of native plant resources and planted forest massifs, as well as existing total and harvested areas of forest crops.
Usage
load_pevs(dataset, raw_data = FALSE, geo_level, time_period, language = "eng")
Arguments
dataset |
A dataset name ("pevs_forest_crops", "pevs_silviculture" or "pevs_silviculture_area"). You can also use SIDRA codes (see https://sidra.ibge.gov.br/pesquisa/pevs/quadros/brasil/2019) |
raw_data |
A |
geo_level |
A |
time_period |
A |
language |
A |
Value
A tibble
consisting of geographic units that present positive values for any of the variables in the dataset.
Examples
## Not run:
# Download treated (raw_data = FALSE) silviculture data (dataset = 'pevs_silviculture')
# by state (geo_level = 'state') from 2012 (time_period = 2012)
# in portuguese (language = "pt")
data <- load_pevs(
dataset = "pevs_silviculture",
raw_data = FALSE,
geo_level = "state",
time_period = 2012,
language = "pt"
)
# Download raw (raw_data = TRUE) forest crops data by region from 2012 to 2013 in english
data <- load_pevs(
dataset = "pevs_forest_crops",
raw_data = TRUE,
geo_level = "region",
time_period = 2012:2013
)
## End(Not run)
PIB MUNICIPAL - Municipal GDP
Description
Loads information on gross domestic product at current prices, taxes, net of subsidies, on products at current prices and gross value added at current prices, total and by economic activity, and respective shares.
Usage
load_pibmunic(
dataset = "pibmunic",
raw_data = FALSE,
geo_level,
time_period,
language = "eng"
)
Arguments
dataset |
A dataset name ("pibmunic") with Municipal GDP information. You can also use SIDRA codes (See https://sidra.ibge.gov.br/pesquisa/pib-munic/tabelas) |
raw_data |
A |
geo_level |
A |
time_period |
A |
language |
A |
Value
A tibble
.
Examples
## Not run:
# download treated municipal GDP data at the state level for 2010 to 2012
data <- load_pibmunic(
raw_data = FALSE,
geo_level = "state",
time_period = 2010:2012
)
## End(Not run)
Population
Description
Loads information on (estimated) population
Usage
load_population(
dataset = "population",
raw_data = FALSE,
geo_level,
time_period,
language = "eng"
)
Arguments
dataset |
A dataset name ("population"). |
raw_data |
A |
geo_level |
A |
time_period |
A |
language |
A |
Value
A tibble
.
Examples
## Not run:
# Download raw data (raw_data = TRUE) at the country level
# from 2008 to 2010 (time_period = 2008:2010).
data <- load_population(
raw_data = TRUE,
geo_level = "country",
time_period = 2008:2010
)
# Download treted data (raw_data = FALSE) by state (geo_level = "state")
# from 2008 to 2010 (time_period = 2008:2010) in portuguese (language = "pt").
data <- load_population(
raw_data = FALSE,
geo_level = "state",
time_period = 2008:2010,
language = "pt"
)
## End(Not run)
PPM - Municipal Livestock Production
Description
Loads information on animal farming inventories and livestock products (IBGE).
Usage
load_ppm(dataset, raw_data = FALSE, geo_level, time_period, language = "eng")
Arguments
dataset |
A dataset name ("ppm_livestock_inventory", "ppm_sheep_farming", "ppm_animal_orig_production", "ppm_cow_farming" or "ppm_aquaculture". You can also use SIDRA codes (see https://sidra.ibge.gov.br/pesquisa/ppm/tabelas/brasil/2021) |
raw_data |
A |
geo_level |
A |
time_period |
A |
language |
A |
Value
A tibble
consisting of geographic units that present positive values for any of the variables in the dataset.
Examples
## Not run:
# Download treated data (raw_data = FALSE) about aquaculture (dataset = "ppm_aquaculture")
# from 2013 to 2015 (time_period = 2013:2015) in english
# with the level of aggregation being the country (geo_level = "country").
data <- load_ppm(
dataset = "ppm_aquaculture",
raw_data = FALSE,
geo_level = "country",
time_period = 2013:2015
)
# Download raw data about sheep farming by state from 1980 to 1995 in portuguese (language = "pt")
data <- load_ppm(
dataset = "ppm_sheep_farming",
raw_data = TRUE,
geo_level = "state",
time_period = 1980:1995,
language = "pt"
)
## End(Not run)
PRODES - Deforestation Monitoring Project in the Legal Amazon by Satellite
Description
Loads data on deforestation in the Legal Amazon region.
Usage
load_prodes(dataset, raw_data = FALSE, language = "eng")
Arguments
dataset |
A dataset name ("deforestation"). |
raw_data |
A |
language |
A |
Value
A tibble
with the selected data.
Examples
## Not run:
# Download treated data (raw_data = FALSE)
# in portuguese (language = 'pt').
data <- load_prodes(
raw_data = FALSE,
language = "pt"
)
## End(Not run)
Greenhouse gas emission estimates (SEEG)
Description
Loads data of estimates of emission of greenhouse gases
Usage
load_seeg(dataset, raw_data = FALSE, geo_level, language = "eng")
Arguments
dataset |
A dataset name ("seeg", seeg_farming", "seeg_industry", "seeg_energy", "seeg_land", "seeg_residuals"). On which "seeg" contains all five sectors (only works with raw_data = TRUE) and the others are filtered specifically by a main source of emission. |
raw_data |
A |
geo_level |
A |
language |
A |
Value
A tibble
.
Examples
## Not run:
# Download raw data (raw_data = TRUE) of greenhouse gases (dataset = "seeg")
# by state (geo_level = "state")
data <- load_seeg(
dataset = "seeg",
raw_data = TRUE,
geo_level = "state"
)
# Download treated data (raw_data = FALSE) of industry greenhouse gases (dataset = "seeg_industry")
data <- load_seeg(
dataset = "seeg_industry",
raw_data = FALSE,
geo_level = "state"
)
## End(Not run)
SIGMINE - Mining Geographic Information System
Description
Loads information the mines being explored legally in Brazil, including their location, status, product being mined and area in square meters.
Usage
load_sigmine(dataset = "sigmine_active", raw_data = FALSE, language = "eng")
Arguments
dataset |
A dataset name ("sigmine_active") |
raw_data |
A |
language |
A |
Value
A tibble
.
Examples
## Not run:
# Download treated data (raw_data = FALSE) in portuguese (language = "pt").
data <- load_sigmine(
dataset = "sigmine_active",
raw_data = FALSE,
language = "pt"
)
## End(Not run)
IBGE codes and Legal Amazon identification of Brazilian municipalities
Description
A dataset containing each municipality's IBGE code, state, mesoregion, microregion, as well as a binary variable for whether it is part of the Legal Amazon. Mostly for our functions' internal use.
Usage
municipalities
Format
A data frame with 5570 rows and 12 variables:
- code_muni
IBGE 7-digit municipality code
- name_muni
municipality name
- code_state
2-digit state code
- abbrev_state
state abbreviations (e.g. "AM")
- name_state
full name of the states
- code_region
1-digit regional code
- name_region
name of the region
- legal_amazon
takes value 1 for municipalities in the legal amazon, 0 otherwise
- municipality_mapbiomas
municipality name in MAPBIOMAS data
- code_micro
5-digit microregion code
- name_micro
name of the microregion
- code_meso
4-digit mesoregion code
- name_meso
name of the mesoregion
Source
Package geobr
and https://www.ibge.gov.br/geociencias/cartas-e-mapas/mapas-regionais/15819-amazonia-legal.html?=&t=acesso-ao-produto
IBGE codes and MAPBIOMAS id of Brazilian municipalities and biomes
Description
A dataset containing each municipality-biome's IBGE code, state, biome, name and MAPBIOMAS ID. Mostly for our functions' internal use.
Usage
municipalities_biomes
Format
A data frame with 6537 rows and 4 variables:
- feature_id
MAPBIOMAS biome-municipality ID
- code_muni
IBGE 7-digit municipality code
- abbrev_state
state abbreviations (e.g. "AM")
- municipality_mapbiomas
municipality name in MAPBIOMAS data
- biome
biome
Source
Package geobr
and https://mapbiomas.org/
Read Data Stored in DBC (Compressed DBF) Files
Description
This function allows you to read a DBC (compressed DBF) file into a data frame. Please note that this is the file format used by the Brazilian Ministry of Health (DATASUS), and it is not related to the FoxPro or CANdb DBC file formats.
Usage
read.dbc(file, ...)
Arguments
file |
The name of the DBC file (including extension) |
... |
Further arguments to be passed to |
Details
DBC is the extension for compressed DBF files (from the 'XBASE' family of databases). This is a proprietary file format used by the brazilian government to make available public healthcare datasets (by it's agency called DATASUS).
read.dbc
relies on the dbc2dbf
function to decompress the DBC into a temporary DBF file.
After decompressing, it reads the temporary DBF file into a data.frame
using read.dbf
from the foreign
package.
Value
A data.frame of the data from the DBC file.
Note
DATASUS is the name of the Department of Informatics of the Brazilian Health System and is responsible for publishing public healthcare data. Besides the DATASUS, the Brazilian National Agency for Supplementary Health (ANS) also uses this file format for its public data.
This function was tested using files from both DATASUS and ANS to ensure compliance with the format, and hence ensure its usability by researchers.
As a final note, neither this project, nor its author, has any association with the brazilian government.
Author(s)
Daniela Petruzalek, daniela.petruzalek@gmail.com
See Also
dbc2dbf
Examples
## Not run:
# The 'sids.dbc' file is the compressed version of 'sids.dbf' from the "foreign" package.
x <- read.dbc(system.file("files/sids.dbc", package = "read.dbc"))
str(x)
summary(x)
# This is a small subset of U.S. NOAA storm database.
storm <- read.dbc(system.file("files/storm.dbc", package = "read.dbc"))
head(x)
str(x)
## Don't run!
## The following code will download data from the "Declarations of Death" database for
## the Brazilian state of Parana, year 2013. Source: DATASUS / Brazilian Ministry of Health
url <- "ftp://ftp.datasus.gov.br/dissemin/publicos/SIM/CID10/DORES/DOPR2013.dbc"
download.file(url, destfile = "DOPR2013.dbc")
dopr <- read.dbc("DOPR2013.dbc")
head(dopr)
str(dopr)
## End(Not run)