以编程方式从 RData 文件集合中提取 object

Question

We work in a production environment, with large datasets assembled from API calls saved as RData files to retain the full environment and subsequent data summaries. The RData files are very large, and contain multiple dataframe objects generated with a standard analysis workflow with similar names and structures.

I'm looking for a clean way to walk through the collection of RData files, pull a named object from each, then assemble into an AllCohorts dataframe for analysis.

Answer 1

We found a useful solution.

1. An extractor function

 extractorRData <- function(file, object) {
      #' Function for extracting an object from a .RData file created by R's save() command
      #' Inputs: RData file, object name
      E <- new.env()
      load(file=file, envir=E)
      return(get(object, envir=E, inherits=F))
    }

2. Extract a data frame "allParams" from RData file "priorRun.RData" without loading the entire environment.

      allParams.prior <- extractorRData("priorRun.RData", "allParams")

This approach has proven to be both fast, and flexible. Useful with large data frames that would be slow to reconstruct.