This article describes how create easily an interactive web framework for exploring data in R using the datadigest package.
This tool provides a concise summary of every variable in a data frame and includes interactive features such as real-time filters, grouping, and highlighting.
This might be very helpful in exploring clinical trial data.
Required R packages and key functions
Load the datadigest package:
Key R functions
#Summarize a single file codebook(data = airquality) # Explore multiple files explorer(data = list(Cars = mtcars, Iris = iris), addEnv = FALSE) # Run a shiny application # Makes it possible to upload files explorerApp()
Explore interactively a data table
The main view available in the framework, include:
- CODEBOOK VIEW
- Shows a concise summary for each variable in the loaded data set.
- Users can click any variable to see additional details.
- Appropriate summary statistics, frequency tables and charts are provided.
- Histograms with box plots are drawn for continuous variables and bar charts for categorical variables. Variable level metadata is also shown beneath the chart if provided by the user.
- DATA LISTING VIEW
- Provides a simple tabular output so that the user can interact with the raw data.
- The listing is exportable, sortable and searchable.
- SETTINGS VIEW
- Lets users customize labels, hide variables and specify which columns should be used as interactive groups and filters.
- CHARTS VIEW
- Create simple bivariate data visualizations.
- The system automatically uses an appropriate visualization based on the types of the x and y variables selected.
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