Davis Vaughan

A two column tidy tibble may make sense ``` r # devtools::install_github("tidyverse/dplyr", ref = "across_simpler") library(dplyr, warn.conflicts = FALSE) library(tibble) library(tidyr) tidy_quantile % group_by(Species) %>% summarise(tidy_quantile(Sepal.Length)) #> # A tibble:...

Also think about rolling variants of these, and how the cumulative + rolling variants could be unified under the idea of "window functions", where cumulative is just sliding with an...

A specialized `incremental_any()` is probably still a decent bit faster than `slide_any(x, ..., before = Inf)`, since the latter does much more than cumulative windows

Backed by `vctrs:::vec_rank()`

People also seem to enjoy https://hughjonesd.github.io/santoku/index.html

Adding a note that `pmin()` is much slower than `min()`. I don't think we need it here ``` r bench::mark(pmin(1, 2), min(1, 2)) #> # A tibble: 2 x 6...

`shift()`

Potential full implementation using `vec_shift()` as the base for `vec_lag()` and `vec_lead()` (we can drop the vec_) ```r library(vctrs) library(rlang) vec_lag

I have not yet exposed a way to convert from low level types (like a C `int64_t`) to the pair of doubles that clock expects. I think you found it...

I am somewhat confident this is doing the "right" thing, but it just doesn't match what you are trying to do, and I don't think there is a feature that...