You can write R language to transform data in blocks.

Add R block to pipeline

  1. Create a new pipeline or open an existing pipeline.
  2. Add a data loader, transformer, or data exporter block.
  3. Select R.

Example pipeline

  1. Data loader
    load_data <- function() {
        # Specify your data loading logic here
        # Return value: loaded dataframe
        df <- read.csv(url(''))
  2. Transformer
    transform <- function(df_1, ...) {
        # Specify your transformation logic here
        # Return value: transformed dataframe.
        df_1 <- filter(df_1, Pclass < 3)
  3. Data exporter
    export_data <- function(df_1, ...) {
        # Specify your data exporting logic here
        # Return value: exported dataframe
        write.csv(df_1, "titanic_filtered.csv", row.names = FALSE)

Install R packages

Add the following at the start of your code in your R block:

pacman::p_load(package1, package2, package3)




When you run the R block for the 1st time, the package will be installed. The 2nd time you run the R block, the package won’t need to be installed again.

What is pacman?

pacman is an R package management tool. You can use p_library() to view all the available packages.

Here is the documentation for pacman where you can find more useful methods:

Runtime variables

Runtime variables can be accessed via global_vars vector, like global_vars['execution_date'].

Example code:

load_data <- function() {
    df <- read.csv(file='titanic_clean.csv')
    df['date'] <- global_vars['execution_date']