What is the difference between the complete() function and specialized functions like summarize() ?

The main difference between the complete() function and the summarize() function lies in their purpose and level of detail:

• Complete Function:

  • Goal: Checks for missing values (often represented by NA or NULL) in a data set.
  • Output: Typically a logical value (TRUE or FALSE) indicating if there are any missing values in the entire data set or specific columns.
  • Focus: Provides a high-level overview of data completeness.

• Summarize Function:

  • Goal: Creates a summary of the data set based on user-defined calculations.
  • Output: A new data frame with one row for each group (if used with group_by beforehand) containing summary statistics like mean, median, count, etc. for specified columns.
  • Focus: Offers a detailed look at various aspects of the data set.

Here's an analogy:

Imagine you have a library with books.

• complete() is like checking if any books are missing from the shelves.
• summarize() is like calculating the average number of pages per book, the number of books in each genre, or the most popular author.

In short, complete() gives a yes/no answer about missing data, while summarize() provides a rich analysis of the data's characteristics.