Allow R users to interact with the 'Canvas' Learning Management System (LMS) API (see
    <https://canvas.instructure.com/doc/api/all_resources.html> for details).
    It provides a set of functions to access and manipulate course data, assignments, grades, users, 
    and other resources available through the 'Canvas' API.

Provides a set of functions for data transformations.
    Transformations are performed on character and numeric data. As the scope of the package is
    within Student Analytics, there are functions focused around the academic year.

Provides a user-friendly R 'shiny' app for performing various statistical tests on datasets. 
  It allows users to upload data in numerous formats and perform statistical analyses. 
  The app dynamically adapts its options based on the selected columns and supports both single and multiple column comparisons.
  The app's user interface is designed to streamline the process of selecting datasets, columns, and test options, 
  making it easy for users to explore and interpret their data. The underlying functions for statistical tests are well-organized and can be used independently within other R scripts.

Provides numerous functions to fill data.
    These can be applied either to missing or skewed data.
    The functions are designed within the scope of Student Analytics.

Offers a wide range of functions for reading and writing data in various file formats, 
    including CSV, RDS, Excel and ZIP files. 
    Additionally, it provides functions for retrieving metadata associated with files, 
    such as file size and creation date, making it easy to manage and organize large data sets. 
    This package is designed to simplify data import and export tasks, 
    and provide users with a comprehensive set of tools to work with different types of data files.

Provides a set of functions for manipulating data frames in accordance with specific business rules. 
    In addition, it includes wrapper functions for commonly used functions from the popular 'tidyverse' package, 
    making it easy to integrate these functions into data analysis workflows. 
    The package is designed to streamline data preprocessing and help users quickly and efficiently 
    perform data transformations that are specific to their business needs.