Provides functions to access historical and real-time national 'hydrometric'
    data from Water Survey of Canada data sources (<https://dd.weather.gc.ca/hydrometric/csv/> and
    <https://collaboration.cmc.ec.gc.ca/cmc/hydrometrics/www/>) and then applies tidy data principles.

Construct and analyse indexes in a pipeline tidy workflow.
    'tidyindex' contains modules for transforming variables, aggregating 
    variables across time, reducing data dimension through weighting, and 
    fitting distributions. A manuscript describing the methodology can be 
    found at <https://github.com/huizezhang-sherry/paper-tidyindex>.

Turn complex 'JSON' data into tidy data frames.

Loading the Korea Labor Institute's KLIPS (Korea Labor & Income Panel Study) panel data and returning data frames. Users must download 26 years of panel data from the Korea Labor Institute website and save it in a folder in an appropriate path. Afterwards, users can easily convert the data into a data frame using this package.

Implements an algorithm for Latent Dirichlet
    Allocation (LDA), Blei et at. (2003) <https://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf>,
    using style conventions from the 'tidyverse',
    Wickham et al. (2019)<doi:10.21105/joss.01686>,
    and 'tidymodels', Kuhn et al.<https://tidymodels.github.io/model-implementation-principles/>.
    Fitting is done via collapsed Gibbs sampling.
    Also implements several novel features for LDA such as guided models and
    transfer learning based on ongoing and, as yet, unpublished research.

A tidy interface for integrating large language model (LLM) APIs such as 'Claude', 'Openai', 'Gemini','Mistral' and local models via 'Ollama' into R workflows. The package supports text and media-based interactions, interactive message history, batch request APIs, and a tidy, pipeline-oriented interface for streamlined integration into data workflows. Web services are available at <https://www.anthropic.com>, <https://openai.com>, <https://aistudio.google.com/>, <https://mistral.ai/> and <https://ollama.com>.