Package index • reuseme

Worflow helpers

With these usethis-inspired functions, you can speed-up your workflow.

Project Management

file_outline() proj_outline() dir_outline(): Print interactive outline of file sections

proj_file(): Access the file outline within other project

proj_list(): Specify proj in functions

proj_switch(): Opens a RStudio project in a new session

proj-reuseme: Interact with different RStudio projects

Package browsing / management

browse_pkg(): Browse pkgdown site if it exists

quarto_help(): Show links to Quarto documentation of interest

outdated_pkgs(): Looks for outdated packages

Interact with documents

use_todo(): Add a TODO list by project to a TODO.R file in the base directory

screenshot(): Save the current image in clipboard to png in your active directory

rename_files2() experimental: Rename an output or a data file and watch for references

active_rs_doc_copy(): Copy the active document to the same location

active_rs_doc_delete() experimental: Delete the active RStudio document safely

active_rs_doc_nav(): Open Files Pane at current document location

open_rs_doc() active_rs_doc(): Open a Document in RStudio

Data analysis helpers / EDA

These functions are to be used when analysing new data

Extra goodies to work with vectors or data

Some are wrappers around dplyr functions, some fix base R inconsistencies.

min_named() max_named() unique_named(): Helpers that can return a named vector

slice_min_max(): Subset rows using their positions

count_pct(): Count observations by group and compute percentage

case_if_any(): case-when, but checks for all matches, returns a character

filter_if_any(): Keep rows that match one of the conditions

filter_detect(): Filter rows by pattern

extract_cell_value(): Elegant wrapper around filter and pull

slice_group_sample(): Explore all rows in a random group

na_if2(): Transform to NA any of the condition

summarise_with_total(): Compute a summary for groups with the total included.

dplyr and base identity

These wrappers can improve interactive data analysis, always return themselves, but are really useful as you can make your data analysis as chatty as you want interactively.

names_identity() count_identity() mutate_identity() slice_identity() slice_min_identity() slice_max_identity() arrange_identity() distinct_identity() filter_identity() slice_sample_identity() filter_if_any_identity() slice_min_max_identity() slice_group_sample_identity(): Helpers that return the same value