library(cheapr)
sequence(1:3)
sequence_(1:3)
sequence(1:3, by = 0.1)
sequence_(1:3, by = 0.1)
# Add IDs to the sequences
sequence_(1:3, by = 0.1, add_id = TRUE)
# Turn this quickly into a data frame
seqs <- sequence_(1:3, by = 0.1, add_id = TRUE)
new_df(name = names(seqs), seq = seqs)
sequence(c(3, 2), by = c(-0.1, 0.1))
sequence_(c(3, 2), by = c(-0.1, 0.1))
# Vectorised version of seq()
seq_(1, 10, by = c(1, 0.5))
# Same as below
c(seq(1, 10, 1), seq(1, 10, 0.5))
# Programmers may use seq_size() to determine final sequence lengths
sizes <- seq_size(1, 10, by = c(1, 0.5))
print(paste(c("sequence sizes: (", sizes, ") total size:", sum(sizes)),
collapse = " "))
# We can group sequences using seq_id
from <- Sys.Date()
to <- from + 10
by <- c(1, 2, 3)
x <- seq_(from, to, by, add_id = TRUE)
class(x) <- "Date"
x
# Utilities for rolling calculations
window_sequence(c(3, 5), 3)
window_sequence(c(3, 5), 3, partial = FALSE)
window_sequence(c(3, 5), 3, partial = TRUE, ascending = FALSE)
# One can for example use these in data.table::frollsum
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