Keep or drop columns using their names and types — select

Select (and optionally rename) variables in a data frame, using a concise mini-language that makes it easy to refer to variables based on their name (e.g. a:f selects all columns from a on the left to f on the right) or type (e.g. where(is.numeric) selects all numeric columns). Overview of selection features Tidyverse selections implement a dialect of R where operators make it easy to select variables: : for selecting a range of consecutive variables. ! for taking the complement of a set of variables. & and | for selecting the intersection or the union of two sets of variables. c() for combining selections. In addition, you can use selection helpers. Some helpers select specific columns: everything(): Matches all variables. last_col(): Select last variable, possibly with an offset. group_cols(): Select all grouping columns. Other helpers select variables by matching patterns in their names: starts_with(): Starts with a prefix. ends_with(): Ends with a suffix. contains(): Contains a literal string. matches(): Matches a regular expression. num_range(): Matches a numerical range like x01, x02, x03. Or from variables stored in a character vector: all_of(): Matches variable names in a character vector. All names must be present, otherwise an out-of-bounds error is thrown. any_of(): Same as all_of(), except that no error is thrown for names that don't exist. Or using a predicate function: where(): Applies a function to all variables and selects those for which the function returns TRUE.