Implement pivot_longer()

DESCRIPTION

@@ -39,6 +39,6 @@ VignetteBuilder:
     knitr
 Encoding: UTF-8
 LazyData: true
-Roxygen: list(markdown = TRUE)
+Roxygen: {library(tidyr); list(markdown = TRUE)}
 RoxygenNote: 7.1.1
 Config/testthat/edition: 3

NEWS.md

@@ -6,6 +6,8 @@
 
   * `fill()` (@markfairbanks, #197)
 
+  * `pivot_longer()` (@markfairbanks, #204)
+
   * `replace_na()` (@markfairbanks, #202)
 
 # dtplyr 1.1.0

R/step-call-pivot_longer.R

@@ -0,0 +1,366 @@
+#' Pivot data from wide to long
+#'
+#' @description
+#' This is a method for the tidyr `pivot_longer()` generic. It is translated to
+#' [data.table::melt()]
+#'
+#' @param data A [lazy_dt()].
+#' @inheritParams tidyr::pivot_longer
+#' @param names_ptypes,names_transform,values_ptypes,values_transform
+#'   Not currently supported by dtplyr.
+#' @examples
+#' library(tidyr)
+#'
+#' # Simplest case where column names are character data
+#' relig_income_dt <- lazy_dt(relig_income)
+#' relig_income_dt %>%
+#'   pivot_longer(!religion, names_to = "income", values_to = "count")
+#'
+#' # Slightly more complex case where columns have common prefix,
+#' # and missing missings are structural so should be dropped.
+#' billboard_dt <- lazy_dt(billboard)
+#' billboard %>%
+#'  pivot_longer(
+#'    cols = starts_with("wk"),
+#'    names_to = "week",
+#'    names_prefix = "wk",
+#'    values_to = "rank",
+#'    values_drop_na = TRUE
+#'  )
+#'
+#' # Multiple variables stored in column names
+#' lazy_dt(who) %>%
+#'   pivot_longer(
+#'     cols = new_sp_m014:newrel_f65,
+#'     names_to = c("diagnosis", "gender", "age"),
+#'     names_pattern = "new_?(.*)_(.)(.*)",
+#'     values_to = "count"
+#'   )
+#'
+#' # Multiple observations per row
+#' anscombe_dt <- lazy_dt(anscombe)
+#' anscombe_dt %>%
+#'  pivot_longer(
+#'    everything(),
+#'    names_to = c(".value", "set"),
+#'    names_pattern = "(.)(.)"
+#'  )
+# exported onLoad
+pivot_longer.dtplyr_step <- function(data,
+                                     cols,
+                                     names_to = "name",
+                                     names_prefix = NULL,
+                                     names_sep = NULL,
+                                     names_pattern = NULL,
+                                     names_ptypes = NULL,
+                                     names_transform = NULL,
+                                     names_repair = "check_unique",
+                                     values_to = "value",
+                                     values_drop_na = FALSE,
+                                     values_ptypes = NULL,
+                                     values_transform = NULL,
+                                     ...) {
+
+  if (!is.null(names_ptypes)) {
+    abort("`names_ptypes` is not supported by dtplyr")
+  }
+
+  if (!is.null(names_transform)) {
+    abort("`names_transform` is not supported by dtplyr")
+  }
+
+  if (!is.null(values_ptypes)) {
+    abort("`values_ptypes` is not supported by dtplyr")
+  }
+
+  if (!is.null(values_transform)) {
+    abort("`values_transform` is not supported by dtplyr")
+  }
+
+  sim_data <- simulate_vars(data)
+  measure_vars <- names(tidyselect::eval_select(enquo(cols), sim_data))
+  if (length(measure_vars) == 0) {
+    abort("`cols` must select at least one column.")
+  }
+
+  multiple_names_to <- length(names_to) > 1
+  uses_dot_value <- ".value" %in% names_to
+
+  variable_name <- "variable"
+
+  if (uses_dot_value) {
+    if (!is.null(names_sep)) {
+      .value <- str_separate(measure_vars, into = names_to, sep = names_sep)$.value
+    } else if (!is.null(names_pattern)) {
+      .value <- str_extract(measure_vars, into = names_to, names_pattern)$.value
+    } else {
+      abort("If you use '.value' in `names_to` you must also supply
+            `names_sep' or `names_pattern")
+    }
+
+    v_fct <- factor(.value, levels = unique(.value))
+    measure_vars <- split(measure_vars, v_fct)
+    values_to <- names(measure_vars)
+    names(measure_vars) <- NULL
+
+    if (multiple_names_to) {
+      variable_name <- names_to[!names_to == ".value"]
+    }
+  } else if (multiple_names_to) {
+    if (is.null(names_sep) && is.null(names_pattern)) {
+      abort("If you supply multiple names in `names_to` you must also
+            supply `names_sep` or `names_pattern`")
+    } else if (!is.null(names_sep) && !is.null(names_pattern)) {
+      abort("only one of names_sep or names_pattern should be provided")
+    }
+  } else {
+    variable_name <- names_to
+  }
+
+  args <- list(
+    measure.vars = measure_vars,
+    variable.name = variable_name,
+    value.name = values_to,
+    na.rm = values_drop_na,
+    variable.factor = FALSE
+  )
+
+  # Clean up call args if defaults are used
+  if (variable_name == "variable") {
+    args$variable.name <- NULL
+  }
+
+  if (identical(values_to, "value")) {
+    args$value.name <- NULL
+  }
+
+  if (is_false(values_drop_na)) {
+    args$na.rm <- NULL
+  }
+
+  sim_vars <- names(sim_data)
+  id_vars <- sim_vars[!sim_vars %in% unlist(measure_vars)]
+
+  out <- step_call(
+    data,
+    "melt",
+    args = args,
+    vars = c(id_vars, variable_name, values_to)
+  )
+
+  if (!is.null(names_prefix)) {
+    out <- mutate(out, !!variable_name := gsub(paste0("^", names_prefix), "", !!sym(variable_name)))
+  }
+
+  if (multiple_names_to && !uses_dot_value) {
+    if (!is.null(names_sep)) {
+      into_cols <- str_separate(pull(out, !!sym(variable_name)), names_to, sep = names_sep)
+    } else {
+      into_cols <- str_extract(pull(out, !!sym(variable_name)), into = names_to, regex = names_pattern)
+    }
+    out <- mutate(out, !!!into_cols)
+
+    # Need to drop variable_name and move names_to vars to correct position
+    # Recreates relocate logic so only select is necessary, not relocate + select
+    out_vars <- out$vars
+    var_idx <- which(out_vars == variable_name)
+    before_vars <- out_vars[seq_along(out_vars) < var_idx]
+    after_vars <- out_vars[seq_along(out_vars) > var_idx]
+
+    out <- select(out, !!!syms(before_vars), !!!syms(names_to), !!!syms(after_vars))
+  } else if (!multiple_names_to && uses_dot_value) {
+    out <- mutate(out, variable = NULL)
+  }
+
+  step_repair(out, repair = names_repair)
+}
+
+# exported onLoad
+pivot_longer.data.table <- function(data,
+                                    cols,
+                                    names_to = "name",
+                                    names_prefix = NULL,
+                                    names_sep = NULL,
+                                    names_pattern = NULL,
+                                    names_ptypes = NULL,
+                                    names_transform = NULL,
+                                    names_repair = "check_unique",
+                                    values_to = "value",
+                                    values_drop_na = FALSE,
+                                    values_ptypes = NULL,
+                                    values_transform = NULL,
+                                    ...) {
+  data <- lazy_dt(data)
+  tidyr::pivot_longer(
+    data = data,
+    cols = {{ cols }},
+    names_to = names_to,
+    names_prefix = names_prefix,
+    names_sep = names_sep,
+    names_pattern = names_pattern,
+    names_ptypes = names_ptypes,
+    names_transform = names_transform,
+    names_repair = names_repair,
+    values_to = values_to,
+    values_drop_na = values_drop_na,
+    values_ptypes = values_ptypes,
+    values_transform = values_transform,
+    ...
+  )
+}
+
+# ==============================================================================
+# inlined from tidyr
+# https://github.com/tidyverse/tidyr/issues/1103
+# ==============================================================================
+# nocov start
+
+# str_extract()  -----------------------------------------------------------------
+str_extract <- function(x, into, regex, convert = FALSE) {
+  stopifnot(
+    is_string(regex),
+    is_character(into)
+  )
+
+  out <- str_match_first(x, regex)
+  if (length(out) != length(into)) {
+    stop(
+      "`regex` should define ", length(into), " groups; ", ncol(out), " found.",
+      call. = FALSE
+    )
+  }
+
+  # Handle duplicated names
+  if (anyDuplicated(into)) {
+    pieces <- split(out, into)
+    into <- names(pieces)
+    out <- lapply(pieces, pmap_chr, paste0, sep = "")
+  }
+
+  into <- as_utf8_character(into)
+
+  non_na_into <- !is.na(into)
+  out <- out[non_na_into]
+  names(out) <- into[non_na_into]
+
+  if (convert) {
+    out[] <- lapply(out, utils::type.convert, as.is = TRUE)
+  }
+
+  out
+}
+
+str_match_first <- function(string, regex) {
+  loc <- regexpr(regex, string, perl = TRUE)
+  loc <- group_loc(loc)
+
+  out <- lapply(
+    seq_len(loc$matches),
+    function(i) substr(string, loc$start[, i], loc$end[, i])
+  )
+  out[-1]
+}
+
+group_loc <- function(x) {
+  start <- cbind(as.vector(x), attr(x, "capture.start"))
+  end <- start + cbind(attr(x, "match.length"), attr(x, "capture.length")) - 1L
+
+  no_match <- start == -1L
+  start[no_match] <- NA
+  end[no_match] <- NA
+
+  list(matches = ncol(start), start = start, end = end)
+}
+
+# str_separate()  -----------------------------------------------------------------
+
+str_separate <- function(x, into, sep, convert = FALSE, extra = "warn", fill = "warn") {
+  if (!is.character(into)) {
+    abort("`into` must be a character vector")
+  }
+
+  if (is.numeric(sep)) {
+    out <- strsep(x, sep)
+  } else if (is_character(sep)) {
+    out <- data.table::tstrsplit(x, sep, fixed = TRUE, names = TRUE)
+    out <- as_tibble(out)
+  } else {
+    abort("`sep` must be either numeric or character")
+  }
+
+  names(out) <- as_utf8_character(into)
+  out <- out[!is.na(names(out))]
+  if (convert) {
+    out[] <- lapply(out, utils::type.convert, as.is = TRUE)
+  }
+  out
+}
+
+strsep <- function(x, sep) {
+  nchar <- nchar(x)
+  pos <- lapply(sep, function(i) {
+    if (i >= 0) return(i)
+    pmax(0, nchar + i)
+  })
+  pos <- c(list(0), pos, list(nchar))
+
+  lapply(1:(length(pos) - 1), function(i) {
+    substr(x, pos[[i]] + 1, pos[[i + 1]])
+  })
+}
+
+str_split_n <- function(x, pattern, n_max = -1) {
+  if (is.factor(x)) {
+    x <- as.character(x)
+  }
+  m <- gregexpr(pattern, x, perl = TRUE)
+  if (n_max > 0) {
+    m <- lapply(m, function(x) slice_match(x, seq_along(x) < n_max))
+  }
+  regmatches(x, m, invert = TRUE)
+}
+
+slice_match <- function(x, i) {
+  structure(
+    x[i],
+    match.length = attr(x, "match.length")[i],
+    index.type = attr(x, "index.type"),
+    useBytes = attr(x, "useBytes")
+  )
+}
+
+list_indices <- function(x, max = 20) {
+  if (length(x) > max) {
+    x <- c(x[seq_len(max)], "...")
+  }
+
+  paste(x, collapse = ", ")
+}
+
+# pmap()/pmap_chr()  -----------------------------------------------------------------
+
+args_recycle <- function(args) {
+  lengths <- vapply(args, length, integer(1))
+  n <- max(lengths)
+
+  stopifnot(all(lengths == 1L | lengths == n))
+  to_recycle <- lengths == 1L
+  args[to_recycle] <- lapply(args[to_recycle], function(x) rep.int(x, n))
+
+  args
+}
+
+pmap <- function(.l, .f, ...) {
+  args <- args_recycle(.l)
+  do.call("mapply", c(
+    FUN = list(quote(.f)),
+    args, MoreArgs = quote(list(...)),
+    SIMPLIFY = FALSE, USE.NAMES = FALSE
+  ))
+}
+
+pmap_chr <- function(.l, .f, ...) {
+  as.character(pmap(.l, .f, ...))
+}
+
+# nocov end

R/tidyeval.R

@@ -14,7 +14,7 @@ dt_eval <- function(x) {
 # Make sure data.table functions are available so dtplyr still works
 # even when data.table isn't attached
 dt_funs <- c(
-  "copy", "dcast", "nafill",
+  "copy", "dcast", "melt", "nafill",
   "fcase", "fcoalesce", "fintersect", "frank", "frankv", "fsetdiff", "funion",
   "setcolorder", "setnames"
 )