Rguroo features tools for simple data upload, data viewing, and data manipulations. With Rguroo you upload your data to a secure storage space on the cloud and access them anywhere the Internet is available. Rguroo facilitates the use of sophisticated R functions to subset, transform, merge, and append your data. These tasks are all performed by use of menus and point-and-clicks. Moreover, Rguroo has a powerful Variable Type Editors that allows you to set variable types, deal with missing data, and order and label factors in your dataset.
Upload text(white space), csv, Excel, tab-delimited, or user-defined delimited files from your local computer/storage or from a web URL into Rguroo’s secure cloud storage. The Data Upload menu in Rguroo provides a flexible environment with many features.
Select data from any of the existing repositories available in Rguroo or create your own data repository to share data with other Rguroo users. The Rguroo’s public data repository consists of all R datasets, R package datasets, and Rguroo datasets.
Variable Type Editor
Variable Type editor allows for overwriting the Rguroo’s default variable types of numerical, categorical/ID, and factors. Moreover, levels of factor variables can be re-ordered and labeled.
View your data using a powerful data viewer. Select any subset of rows or columns to view. Rearrange columns by drag and drop. View data grouped by values of a variable. Save any view of the data to your local storage or to Rguroo’s cloud storage.
Subset your data using Rguroo’s versatile subset builder. Construct subsets based on row and column numbers, values of variables, comparison of variable values and a combination of all of these using set operations.
Use functions in R to transform existing variables and create new ones for your analyses.
Sort your data based on the values of one or more variables.
Merge two datasets with a variety of options including inner join, outer join, with flexibility in ordering the final result.
Append two datasets with various options to include variables from one or both datasets, or to include common variables, with flexibility in ordering the final result.
Select any size random subset of your data from any subset of your data, with or without replacement.