ggEDA: Visualisations for exploratory data analysis using tiled one-dimensional graphics and parallel coordinate...

Exploratory data analysis (EDA) involves summarising trends within a dataset to help uncover data quality issues and generate hypotheses. However, identifying relationships between multiple features often requires extensive coding, manual inspection and statistical modelling. Here, we introduce the ggEDA R package, which streamlines multidimensional data exploration by providing two turnkey and complementary visualisation strategies. ggEDA generates interactive parallel coordinate plots (PCPs) well suited for examining large datasets with mostly quantitative features, and introduces tiled one-dimensional plots that more effectively show missingness and reveal categorical relationships in smaller datasets. ggEDA reduces the amount of code and time required to detect multi-feature relationships that may otherwise require statistical modelling or thorough manual review to identify. To make ggEDA visualisations accessible to a wider audience we also developed interactiveEDA, a web app that enables non-programmers to explore and interpret data patterns interactively. ggEDA and interactiveEDA are available at https://github.com/CCICB/ggEDA and https://github.com/CCICB/interactiveEDA respectively.