- Arrange rows by column values
- Subset distinct/unique rows
- Subset rows using column values
- Get a glimpse of your data
- Extract a single column
- Change column order
- Subset columns using their names and types
- Objects exported from other packages
- Set operations
- Nest join
- Select grouping variables
- Group input by rows
- Combine values from multiple columns
- Do values in a numeric vector fall in specified range?
- A general vectorised if
- Find first non-missing element
- Descending order
- Vectorised if
- A helper function for ordering window function output
- Context dependent expressions
- Efficiently count the number of unique values in a set of vectors
- Convert values to NA
- Compare two numeric vectors
- Starwars characters
- Storm tracks data
- Copy tables to same source, if necessary
- Copy a local data frame to a remote src
- Flag a character vector as SQL identifiers
- SQL escaping.
Experimental functions are a testing ground for new approaches that we believe to be worthy of greater exposure. There is no guarantee that these functions will stay around in the future, so please reach out if you find them useful.
- Trim grouping structure
- Split data frame by groups
- Perform an operation with temporary groups
We have our doubts about questioning functions. We’re not certain that they’re inadequate, or we don’t have a good replacement in mind, but these functions are at risk of removal in the future.
- Flexible equality comparison for data frames
Superseded functions have been replaced by new approaches that we believe to be superior, but we don’t want to force you to change until you’re ready, so the existing functions will stay around for several years.