Create Inverse Strings from a List of Selected Words

Learn how to generate `inverse strings` from a list of selected words using R programming in the `tidyverse` package. This solution effectively leverages set operations to provide an easy way to find the remaining words from a dictionary.
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How to Create Inverse Strings from Selected Words in R

When working with strings in R, particularly with lists of words, you might face situations where you want to derive a complementary or "inverse" set of words based on a given dictionary. This process involves comparing a list of selected strings against a full set of potential words and then returning the words that do not appear in the selected list.

In this guide, we'll explore how to accomplish this task using the tidyverse suite of libraries in R, specifically by employing functions from the dplyr and purrr packages.

The Problem

Let's consider an example where we have:

A full_string consisting of several words:

[[See Video to Reveal this Text or Code Snippet]]

A list of selected_strings that might contain one or more of these words. For instance:

""

"Apple"

"Apple, Cranberry"

"Cranberry, Apple, Banana"

"Banana"

"Cranberry"

Our goal is to produce an inverse_string for each entry in selected_strings. This inverse_string will contain all of the words from the full_string that do not appear in the corresponding selected_strings.

The Solution

Setup

We start by creating a data frame using tribble (from the tibble package), which holds our selected_strings and full_string data:

[[See Video to Reveal this Text or Code Snippet]]

Using the mutate and map2_chr Functions

To create the inverse_string, we can use the mutate function from dplyr alongside map2_chr from purrr. Here's how:

Split the selected_strings and full_string into separate elements.

Use setdiff to find the difference between the two sets of strings.

Convert the result back into a string format.

The complete R code snippet is as follows:

[[See Video to Reveal this Text or Code Snippet]]

Output

Once you run the above code, your data frame will look like this, including the new inverse_str column:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

Now you have successfully created inverse strings for each entry in your selected list based on the provided dictionary. This approach is not only efficient but also leverages the power of the tidyverse, making your data manipulations easier.

By understanding how to manage string comparisons and leveraging R's powerful data manipulation libraries, you can solve similar problems in your data processing tasks.

Feel free to test out this method with your own datasets, and happy coding!

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