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m61r: The Pure Base R Data Engine 🌌

m61r provides dependency-free tabular and time-series manipulation for R. It is designed for the Base R purist who demands modern syntax and high performance.

Why m61r?

Zero Dependencies: No dplyr, no tidyverse. It runs on any vanilla R installation.
Unified Logic: Treat tabular and time series as one.
High Performance: Optimized Base R verbs for tabular accounting.
Fluent API: A clean, object-oriented API inspired by the best modern data tools
Transparent: Written in 100% Base R

Quick Start

Tabular Manipulation


library(m61r)

# Initialize with the built-in CO2 dataset

co2 <- m61r(CO2)

co2$filter(~uptake > 30)$
    select(~c(Plant, Type, uptake))$
    group_by(~Type)$
    summarise(mean_uptake = ~mean(uptake))

print(co2[])

Temporal Data Manipulation

ts_data <- data.frame(
  time = as.POSIXct("2025-01-01 00:00:00") + runif(50, 0, 86400),
  consumption = rnorm(50, 500, 100)
)

p_agg <- m61r(ts_data)

p_agg$mutate(hour_bin = ~format(time, "%Y-%m-%d %H:00"))
p_agg$group_by(~hour_bin)
p_agg$summarise(
  n_obs = ~length(consumption),
  avg_load = ~mean(consumption)
)
p_agg$head(5)

Benchmarks

filter, mutate, head

library(microbenchmark)
library(m61r)

set.seed(42)
n <- 1e6
df_large <- data.frame(
  id = 1:n,
  group = sample(letters, n, replace = TRUE),
  val = rnorm(n)
)

p <- m61r(df_large)

results <- microbenchmark(
  # Approche Base R classique
  base_r = {
    tmp <- df_large[df_large$val > 0, ]
    tmp$new_val <- tmp$val * 2
    head(tmp)
  },
  
  # Approche m61r
  m61r_pipe = {    
    p$filter(~val > 0)
    p$mutate(new_val = ~val * 2)
    p$head()
  },
  times = 50 
)

print(results)

Unit: milliseconds

`expr`	`min`	`lq`	`mean`	`median`	`uq`	`max`	`neval`
base_r	37.79	42.08	49.75	44.39	59.48	92.38	50
m61r_pipe	20.11	21.94	27.10	23.78	26.19	55.45	50

group_by, summarise

results_group <- microbenchmark(
  # Base R avec aggregate
  base_aggregate = {
    aggregate(val ~ group, data = df_large, FUN = mean)
  },
  
  # m61r
  m61r_grouped = {
    p$group_by(~group)
    p$summarise(avg = ~mean(val))
    p[]
  },
  times = 20
)

print(results_group)

Unit: milliseconds

`expr`	`min`	`lq`	`mean`	`median`	`uq`	`max`	`neval`
base_aggregate	329.80	350.84	361.70	354.05	372.74	442.04	20
m61r_grouped	146.57	147.70	154.79	149.88	165.77	172.25	20

Installation

Installation from CRAN

install.packages("m61r")

Installation from GITHUB in Base R

setwd("~")

download.file("https://github.com/pv71u98h1/m61r/archive/0.1..zip",destfile="m61r-0.1.0.zip")
unzip("m61r-0.1.0.zip")

# install
install.packages("m61r", repos=NULL, type='source')

unlink(file.path("~","m61r-0.1.0"),recursive=TRUE)
file.remove(file.path("~","m61r-0.1.0.zip"))

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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