Integrating Data, Research, and Education • amazonasdatahub

The goal of amazonasdatahub is to aggregate databases from the State of Amazonas (AM), Brazil, for conducting studies and preparing educational materials, as well as to facilitate access to organized and processed data, thereby supporting research and teaching and enabling the application of statistical methods.

Full documentation of both Python and R versions is available in the following languages/Documentação das versões em Python e R estão disponíveis nos seguintes idiomas:

R only documentation and vignettes:

Overview

This amazonasdatahub package provides databases from various types and sources, all of which concern the State of Amazonas.

List of available datasets:

Dataset	Area	Source
agriculture_amazonas	Agriculture and Livestock	Institute of Agricultural and Sustainable Forestry Development of the State of Amazonas - 2024
aids_amazonas	Health	Department of HIV, AIDS, Tuberculosis, Viral Hepatitis, and Sexually Transmitted Infections, 2024
gdp_amazonas	Economy	Scientific Journal of Applied Social and Clinical Science - TIME SERIES ANALYSIS FOR THE QUARTERLY GROSS DOMESTIC PRODUCT OF AMAZONAS
humidity_manaus	Climate	NASCIMENTO, Leonardo Brandão Freitas; LIMA, Max Sousa; DUCZMAL, Luiz H. P-min-stable regression models for time series with extreme values of limited range. Environmetrics, Issue 2, v. 36, 2025.
malaria_amazonas	Health	Lais Baroni, M. P. (2020). An Integrated Dataset of Malaria Notifications in the Legal Amazon (Dataset). Synapse. https://doi.org/10.7303/SYN21552203
prf_amazonas	Road Safety	Brasil. Polícia Rodoviária Federal (PRF). Dados Abertos da PRF: Acidentes de Trânsito
rionegro_amazonas	Environment	Porto de Manaus. Nível do Rio Negro
srl_muni	Education	ALMEIDA, Thiago da Cruz de. Physical Literacy e desempenho em leitura de escolares amazônicos: um estudo de associação. 2024. 104 f. Dissertação (Mestrado em Educação) - Universidade Federal do Amazonas, Manaus, 2024.

Installation

To install amazonasdatahub, you need to have the following tools installed on your computer or development environment:

R version 4.41.1 (2024-06-14) or above;
remotes package from R.

You can install the CRAN version that will be published with:

install.packages("amazonasdatahub")

Or you can install the development version of amazonasdatahub with:

# Install remotes package
install.packages("remotes")

# Load remotes
library(remotes)

# installing amazonasdatahub
remotes::install_github("onelsoncarvalho/amazonasdatahub")

Usage and Examples

Loading `amazonasdatahub`

Use library() or require() to load the package.

library(amazonasdatahub)

You can check the documentation of each dataset using the help operator “?”.

?agriculture_amazonas
?aids_amazonas
?gdp_amazonas
?humidity_manaus
?malaria_amazonas
?prf_amazonas
?rionegro_amazonas
?slr_muni

Examples

Disease occurrence

The dataset aids_amazonas contains data of the AIDS occurrences in each municipality from Amazonas.

One of the analysis that can be made is: visualize the time series of counts filtered by municipality, where each case is grouped by the sex/gender of each observation. To do this, we will use the dplyr package to structure the data and the ggplot2 package to create and customize the chart.

# Loading dplyr and ggplot to structure the data
require(dplyr)
require(ggplot2)

# Filtering by municipality and plotting case count by gender
aids_amazonas %>%
  filter(name_muni == "Manaus") %>%
  group_by(gender) %>%
  ggplot(aes(x = year, y = cases, group = gender, color = gender)) +
  geom_line() +
  scale_color_manual(values = c("blue", "red")) +
  theme_minimal() +
  labs(
    title = "AIDS occurrences in Manaus (2011-2023)",
    x = "Year",
    y = "Case count",
    color = "Gender"
  )

Time Series

The humidity_manaus consists of the minimum relative humidity observed in the city of Manaus from January 2009 to December 2020. We can visualize the time series of the relative humidity during this time interval.

Using dplyr, it is possible to create a date column, which will be composed of the month and year. Usingggplot2, the time series chart can be plotted.

# Loading dplyr and ggplot to structure the data
require(dplyr)
require(ggplot2)

# Creating date column and plotting the time series
humidity_manaus %>%
  mutate(date = as.Date(paste0(year, "-", month, "-","01"))) %>%
  ggplot(aes(x = date, y = rh)) +
  geom_line() +
  theme_minimal() +
  labs(
    title = "Relative Humidity of Amazonas (2009-2020)",
    x = "Date",
    y = "Relative Humidity"
  )

Citation

To cite amazonasdatahub in publications, please use:

Carvalho, N., & Nascimento, Leonardo. (2026). amazonasdatahub: Integrating Data, Research and Education. R package version 1.2.1. Available at: https://onelsoncarvalho.github.io/amazonasdatahub/

A BibTeX entry for LaTeX users is:

@Manual{amazonasdatahub2026,
  title  = {amazonasdatahub: Integrating Data, Research and Education},
  author = {Nelson Carvalho and Leonardo Nascimento},
  year   = {2026},
  note   = {R package version 1.2.1},
  url    = {https://onelsoncarvalho.github.io/amazonasdatahub/}
}

amazonasdatahub