datapubliclu

Overview

The datapubliclu R package provides a convenient interface for accessing datasets from data.public.lu, the open data portal of Luxembourg. It simplifies the process of downloading and importing data directly into your R environment.

Installation

You can install the development version of datapubliclu from GitHub using remotes.

# install.packages("remotes")
remotes::install_github("cavrilionis/datapubliclu")

Usage

The package provides functions to list available datasets, download specific datasets, and import them into R.

Listing Datasets

Use the list_datasets() function to retrieve a list of available datasets.

library(datapubliclu)

datasets <- list_datasets()
print(datasets)

Downloading and Importing a Dataset

To download and import a specific dataset, use the get_dataset() function, providing the dataset ID.

# Example: Downloading the "Population par commune" dataset
population_data <- get_dataset("population-par-commune")
head(population_data)

Searching for Datasets

Use the search_datasets() function to search for datasets based on keywords.

# Example: Searching for datasets related to "housing"
housing_datasets <- search_datasets("housing")
print(housing_datasets)

Retrieving Dataset Metadata

Use the get_dataset_metadata() function to retrieve metadata for a specific dataset.

# Example: Retrieving metadata for the
# "Prix de vente des appartements par commune" dataset
metadata <- get_dataset_metadata("prix-de-vente-des-appartements-par-commune")
print(metadata)

Working with Specific File Formats

get_dataset() automatically detects and handles common file formats (e.g., CSV, XLSX, JSON). You can also specify the file format explicitly.

# Example: Importing a CSV file
csv_data <- get_dataset("some-dataset-id", format = "csv")

# Example: Importing an Excel file
excel_data <- get_dataset("another-dataset-id", format = "xlsx")

Example: Analyzing Population Data

library(datapubliclu)
library(dplyr)
library(ggplot2)

population_data <- get_dataset("population-par-commune")

population_summary <- population_data |>
  group_by(Commune) |>
  summarise(Total_Population = sum(Population)) |>
  arrange(desc(Total_Population))

print(head(population_summary))

ggplot(head(population_summary, 10),
       aes(x = reorder(Commune, Total_Population), y = Total_Population)) +
  geom_bar(stat = "identity") +
  coord_flip() +
  labs(title = "Top 10 Communes by Population",
       x = "Commune",
       y = "Total Population")

Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them.
4. Push your changes to your fork.
5. Submit a pull request.

Please ensure that your code follows the package’s style guidelines and includes appropriate tests.

Code of Conduct

Please note that the datapubliclu project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

This package is licensed under the MIT License.

Issues and Support

If you encounter any issues or have questions, please open an issue.