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**purrr**: Functional Programming Tools**flatmap**: Map a function and flatten the result by one-level

# Map a function and flatten the result by one-level

### Description

Deprecated: please use `map()`

followed by `flatten()`

.

### Usage

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- accumulate: Accumulate recursive folds across a list
- along: Helper to create vectors with matching length.
- array-coercion: Coerce array to list
- as_function: Convert an object into a function.
- as_vector: Coerce a list to a vector
- at_depth: Map a function over lower levels of a nested list
- bare-type-predicates: Bare type predicates
- by_row: Apply a function to each row of a data frame
- by_slice: Apply a function to slices of a data frame
- compose: Compose multiple functions
- conditional-map: Modify elements conditionally
- contains: Does a list contain an object?
- cross_n: Produce all combinations of list elements
- detect: Find the value or position of the first match.
- dmap: Map over the columns of a data frame
- every: Do every or some elements of a list satisfy a predicate?
- flatmap: Map a function and flatten the result by one-level
- flatten: Flatten a list of lists into a simple vector.
- get-attr: Infix attribute accessor
- head_while: Find head/tail that all satisfies a predicate.
- invoke: Invoke functions.
- is_empty: Is a vector/list empty?
- is_formula: Is a formula?
- keep: Keep or discard elements using a predicate function.
- lift: Lift the domain of a function
- lmap: Apply a function to list-elements of a list
- map: Apply a function to each element of a vector
- map2: Map over multiple inputs simultaneously.
- negate: Negate a predicate function.
- null-default: Default value for 'NULL'.
- partial: Partial apply a function, filling in some arguments.
- pipe: Pipe operator
- prepend: Prepend a vector
- rbernoulli: Generate random samples from a Bernoulli distribution
- rdunif: Generate random samples from a discrete uniform distribution
- reduce: Reduce a list to a single value by iteratively applying a...
- rerun: Re-run expressions multiple times.
- safely: Capture side effects.
- scalar-type-predicates: Scalar type predicates
- set_names: Set names in a vector
- slice_rows: Slice a data frame into groups of rows
- splice: Splice objects and lists of objects into a list
- split_by: Split, order and sort lists by their components.
- transpose: Transpose a list.
- type-predicates: Type predicates
- update_list: Modify a list
- when: Match/validate a set of conditions for an object and continue...