Consider a dataframe td_new. What does executing the following R Code acheive:

grep("[B][u][s][h]", td_new$movie_title, value = T)

Question

Consider a dataframe td_new. What does executing the following R Code acheive:

grep("[B][u][s][h]", td_new$movie_title, value = T)

BlackTom AI · Accepted Answer

We start by restating the question in our own words to ground the analysis: The R code grep("[B][u][s][h]", td_new$movie_title, value = T) is applied to the movie_title column of the data frame td_new, and it uses grep with value = TRUE. Now, let's evaluate each option carefully.

Option 1: 'This code will find instances (such as lines, cells, etc.) in the column movie_title that have the letter "T" and will replace it with "Bush".' This is incorrect for a couple of reasons. First, grep searches for patterns and returns the matching elements (or their indices), it does not perform replacements. Second, the pattern "[B][u][s][h]" does not represent just the letter T; it represents the sequence B, u, s, h, each as separate literal characters. Therefore, there is no mechanism here that replaces a T with Bush. The claim about replacing is thus unfounded.

Option 2: 'This code will find instances (such as lines, cells, etc.) in the column movie_title, that have any combination of the word "BUSH" such as BUSH, USHB, USBH, etc.' This is incorrect because the pattern "[B][u][s][h]" means the four characters B, u, s, h in that exact order, each as individual character matches. It does not describe permutations or any rearrangements of those characters; grep would only match the literal sequence Bush in that exact case, not arbitrary shuffles or combinations. Therefore, this option misstates the pattern semantics.

Option 3: 'This code will find instances (such as lines, cells, etc.) in the column movie_title, that have the word "Bush".' This aligns with the intended use of grep here: searching for the exact string Bush in the movie_title field. The square-bracketed notation [B][u][s][h] in a grep pattern matches the characters B, u, s, h in that order, effectively matching the substring Bush. With value = TRUE, grep returns the actual matching values from the vector, i.e., the elements of td_new$movie_title that contain the substring Bush. This option correctly captures both the search target and the behavior of returning matches rather than indices or replacements.

Option 4: 'This code will find instances (such as lines, cells, etc.) in the column movie_title, that have the word "Bush", and will replace these with "T".' This is incorrect for two reasons: grep does not replace content; it finds or reports matches. Even if one were to replace, the code as written does not specify a replacement operation and would not transform the matches into the letter T. The pattern does not imply any replacement behavior, so this interpretation is inaccurate.

In summary, option 3 correctly describes the behavior: the code searches for the substring Bush within each element of the movie_title column and returns the matching values when value = TRUE. The other options either misinterpret the pattern semantics, confuse searching with replacement, or overgeneralize the pattern to permutations or substitutions that are not supported by the code as written.

BSYS847_2025_V1 Assessment 1: In-Class Quiz

Consider a dataframe td_new. What does executing the following R Code acheive: grep("[B][u][s][h]", td_new$movie_title, value = T)

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