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RSQLiteAdmin Visualisation Tools

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Oliver Vu edited this page Mar 2, 2023 · 8 revisions

Background

RSQLiteAdmin is a GUI tool written in R Shiny to explore, manage and update SQLite Databases. Currently, it supports :

  1. Creating/Deleting Databases.
  2. Importing/Exporting data from delimited files.
  3. Viewing/Editing data within tables.
  4. Querying and Searching a database.

The usefulness of the package would be benefited greatly if some descriptive statistics and visualisation tools are added. Such statistics and distinct types of plots would help in exploring data and allow users to detect patterns and irregularities that are commonly present in large datasets.

Related work

Other R packages support plotting data via writing code and are domain specific to the kind of functionality they provide. For eg: package PerformanceAnalytics provides plots for risk analysis. This project aims to implement tools that could be used to explore the data and give a general idea of the information present. These explorations are not meant to offer detailed analysis but rather to help users in initial steps of data visualization and/or data cleaning procedures.

Details of your coding project

The contributor will need to implement functions (both back-end and front-end) for the following:

  1. Summarise selected columns in the database by providing stats about any column (take a look at describe() function from package psych):
  2. Filter rows by criteria:
    1. Logical comparisons
    2. Logical operators
  3. Implement plotting charts for selected columns, with options for multiple variables to be plotted in a single plot or plotting different variables in different plots. The plots should also be customizable in terms of their properties like colour palette, ticks, axis names, titles etc.

Expected impact

This project will help users gauge a general summary about the data through a GUI along with plotting customisable graphs without the need for writing code.

Mentors

Contributors, please contact mentors below after completing at least one of the tests below.

  • EVALUATING MENTOR: Vijay Barve [email protected] is a biodiversity data scientist and has been a GSoC contributor and mentor since 2012 with the R project organization. Vijay has contributed to several packages on CRAN.
  • Narayani Barve [email protected] is a biodiversity informatics scientist and was a GSoC contributor (2014) as well as a mentor (2016-2019) with the R project organization. She developed the package ENMGadgets and has contributed to various other R packages. She has extensive experience working with spatial information and large scale databases.
  • Marlon Cobos [email protected] is an ecologist and biogeographer that has developed and contributed to various R packages related to species distributions and macroecology (e.g., rangemap, nichevol, kuenm). He has participated in GSoC as a contributor and mentor since 2018.
  • Divyansh Chawla [email protected] designed and implemented the rsqliteadmin package as a contributor developer in GSOC 2020.

Tests

Contributors, please do one or more of the following tests before contacting the mentors above.

  • Easy: Install the package rsqliteadmin from CRAN and play around with all the features. Create a database, add a table and import some data. Edit, search, and export it.
  • Medium 1: Plot a time-series line chart on a dataset of your choice with different variables in a single chart. Customize it to make it clear and insightful.
  • Medium 2: Create a simple package using the Golem R package that contains a Shiny application to view the chart above.
  • Hard: Implement a “select/deselect all” button in the export data module of the rsqliteadmin package. Submit a pull request for the same.

Solutions of tests

Contributors, please post a link to your test results here.

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