How to Dynamically Create Dataframes Based on File Names Using R

Creating a Dynamic DataFrame Based on File Name Using R

In this article, we will explore how to create a dynamic function in R that can automatically name dataframes based on the file names provided as input. This technique is particularly useful when working with large datasets or when you need to perform data analysis tasks without explicitly naming the output.

Introduction

When working with files and data manipulation in R, it’s common to encounter scenarios where you need to create variables or objects that can be easily referenced later in your code. One popular approach to achieve this is by using the file function from the here package, which allows you to create file paths based on a base path and a variable name.

In this article, we’ll discuss how to use the assign function to dynamically create dataframes based on the file names provided as input. This technique can be particularly useful in scenarios where you need to perform data analysis tasks without explicitly naming the output.

Background

Before diving into the solution, let’s take a brief look at the key concepts and packages involved:

R: A popular programming language and environment for statistical computing and graphics.
readr and stringr: Two popular R packages that provide functions for reading and manipulating data, as well as performing string operations.
here: An R package that provides a convenient way to create file paths based on a base path and a variable name.

Problem Statement

The problem we’re trying to solve is how to use the file function from the here package to dynamically create dataframes based on the file names provided as input. The following code snippet illustrates this issue:

library(here)
library(readr)
library(stringr)

file_survey <- here("my_survey_2019.rds")

my_read_rds <- function(file){
  name <- deparse(substitute(file))
  name <- stringr::str_remove(name, "^file_")
  eval(name) <- readr::read_rds(file) # Does not work
}

my_read_rds(file_survey)

As you can see from the code snippet above, even though we provide a file path as input to the my_read_rds function, R still tries to evaluate name as a valid R expression instead of using it as a filename. This is where the assign function comes into play.

Solution

One way to solve this problem is by using the assign function from the base R package. Here’s how you can modify the my_read_rds function to use assign:

library(here)
library(readr)
library(stringr)

file_survey <- here("my_survey_2019.rds")

my_read_rds <- function(file){
  name <- deparse(substitute(file))
  name <- stringr::str_remove(name, "^file_")
  assign(name, readr::read_rds(file), envir=globalenv())
}

my_read_rds(file_survey)

In this modified version of the my_read_rds function, we use the assign function to dynamically create a variable named after the file name. The envir argument is used to specify that the assignment should be made in the global environment.

Explanation

Here’s what happens when you call assign(name, readr::read_rds(file), envir=globalenv()):

name: This is the variable name that we want to create. We use stringr::str_remove(name, "^file_") to remove any prefix from the file name.
readr::read_rds(file): This reads the RDS file specified by file.
envir=globalenv(): This specifies that we want to create a new variable in the global environment.

When you call my_read_rds(file_survey), it will dynamically create a variable named after the file name, and assign it the result of reading the RDS file.

Example Usage

Here’s an example usage of the modified my_read_rds function:

library(here)
library(readr)
library(stringr)

file_survey <- here("my_survey_2019.rds")
file_poll <- here("my_poll_2020.rds")

# Read and assign to dataframes
my_read_rds(file_survey) # Creates a dataframe named survey
my_read_rds(file_poll)  # Creates a dataframe named poll

In this example, we create two file paths using the here package: file_survey and file_poll. We then call the modified my_read_rds function to read the corresponding RDS files and assign them to dataframes.

Conclusion

In this article, we discussed how to use the assign function in R to dynamically create variables based on file names. This technique can be particularly useful when working with large datasets or when you need to perform data analysis tasks without explicitly naming the output.

We hope that this article has provided a comprehensive guide to creating dynamic dataframes using the assign function in R. If you have any further questions or need additional assistance, feel free to ask!

Last modified on 2023-09-09