Interactive 'dplyr' Data Transformation Blocks

Extends 'blockr.core' with interactive blocks for visual data wrangling using 'dplyr' and 'tidyr' operations. Users can build data transformation pipelines through a graphical interface without writing code directly. Includes blocks for filtering, selecting, mutating, summarizing, joining, and arranging data, with support for complex expressions, grouping operations, and real-time validation.

blockr.dplyr

blockr.dplyr provides interactive blocks for data transformation. Filter, sort, summarize, join, and manipulate data through visual interfaces.

Overview

blockr.dplyr is part of the blockr ecosystem and provides data transformation blocks.

Installation

install.packages("blockr.dplyr")

Or install the development version from GitHub:

# install.packages("pak")
pak::pak("BristolMyersSquibb/blockr.dplyr")

Getting Started

Create and launch an empty dashboard:

library(blockr.dplyr)
serve(new_board())

This opens a visual interface in your web browser. Add blocks using the "+" button, connect them by dragging, and configure each block through its settings. Data transformations update in real-time as you build your workflow.

Available Blocks

blockr.dplyr provides 16 data transformation blocks:

Core Operations

• select: choose which columns to keep
• rename: change column names
• arrange: sort rows by column values
• slice: select specific rows by position or value

Filtering

• filter: filter by selecting values from dropdowns (simple, no-code)
• filter expression: keep rows that meet conditions (advanced, R expressions)

Creating & Modifying Columns

• mutate expression: create or modify columns using R expressions

Summarizing

• summarize: calculate statistics using dropdown selections (simple, no-code)
• summarize expression: calculate statistics using R expressions (advanced)

Combining Data

• join: combine two datasets based on common columns
• bind_rows: stack datasets vertically
• bind_cols: combine datasets side-by-side

Reshaping

• pivot_longer: reshape data from wide to long format
• pivot_wider: reshape data from long to wide format
• unite: combine multiple columns into one
• separate: split one column into multiple columns

See vignette("blockr-dplyr-showcase") for a complete showcase with screenshots and detailed explanations of each block.

Learn More

The blockr.dplyr website includes full documentation and the showcase vignette. For information on the workflow engine, see blockr.core.