Merging Data Frames with Wildcard Patterns

Introduction

In this article, we will explore the process of merging two data frames using wildcard patterns. We’ll start by creating a scenario that illustrates the problem we want to solve and then outline the steps required to achieve it.

Creating the Scenario

Let’s begin by defining our two data frames: Wild_Cards and Values.

# Create Wild_Cards
Wild_Cards <- data.frame(Var = c("Var A[*]", "Var B[*, X1]", "Var C[X2, *]", "Var D[*, *]", "Var E"),
                         A = c(1, 0.5, 0.8, 0, -1),
                         B = c(2, 1.5, 1.8, 1, 0))

# Create Values
Values <- data.frame(Var = c("Var A[Y]", "Var A[Z]", "Var B[Y, X1]", "Var B[Z, X1]", "Var C[X2, Y]", "Var C[X2, Z]", "Var D[A, Y]", "Var D[B, Z]", "Var E"),
                     D = c(1.5, 1.8, 1, 1.4, 1, 1, 0, 0.5, -0.5))

We need to merge these data frames by matching the variable names in Wild_Cards with wildcard patterns from Values. However, our patterns appear to be more “glob”-style wildcards than true-regex patterns.

Converting Glob Patterns to Regex

Luckily, we can easily convert from the former to the latter using utils::glob2rz.

# Convert glob patterns to regex
Wild_Cards$ptn <- glob2rx(Wild_Cards$Var)

Now that our patterns are in true-regex format, we can proceed with the merge.

Merging Data Frames Using Regex Join

We’ll use fuzzyjoin::regex_right_join to perform the merge. This function allows us to specify a join type (left, right, or full) and a set of variables to match.

# Perform regex right join
Result <- fuzzyjoin::regex_right_join(Values, Wild_Cards, by = c(Var = "ptn"))

The resulting data frame will have the desired variable names, with the relevant values from both Wild_Cards and Values.

Cleanup and Output

We’ll need to perform some cleanup on the column names in the resulting data frame.

# Rename columns for better readability
Result <- Result[, c("Var.x", "D", "Var.y", "A", "B")]

Now we can view our final result:

# View final result
print(Result)

Final Output

Here is the final output of our merged data frame:

Conclusion

In this article, we explored the process of merging two data frames using wildcard patterns. We created a scenario that illustrated the problem we wanted to solve and outlined the steps required to achieve it. With utils::glob2rz and fuzzyjoin::regex_*_join, we were able to convert glob patterns into true-regex formats and perform a successful merge.

We hope this article has been informative and helpful for those looking to merge data frames using wildcard patterns in R.

Last modified on 2024-07-14