Why is {dplyr} so huge, and are there any alternatives or a {dplyr} 'lite' that I can use for the basic mutate, group_by, summarize, etc?

This page summarizes the projects mentioned and recommended in the original post on reddit.com/r/rstats

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  • poorman

    A poor man's dependency free grammar of data manipulation

    You might find the poorman package interesting: https://github.com/nathaneastwood/poorman

  • pak

    A fresh approach to package installation (by r-lib)

    For installation, check out pak https://github.com/r-lib/pak, it's able to install in parallel.

  • InfluxDB

    Access the most powerful time series database as a service. Ingest, store, & analyze all types of time series data in a fully-managed, purpose-built database. Keep data forever with low-cost storage and superior data compression.

  • tidytable

    Tidy interface to 'data.table'

    Tidytable is what you might be looking for: https://markfairbanks.github.io/tidytable/, this will require a bit of refactoring (e.g group-bys happen as arguments in summarise/mutate). You'll get data.table like speed in a very compact & complete package.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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