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 /r/rstats
R base-r data-manipulation Grammar

InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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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

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • 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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