fix minor typing mistakes

R/check.R

@@ -18,7 +18,7 @@
 #'   all key combinations
 #' @param inconsistent_factor_levels What to do if the key columns from both sides
 #'   have inconsistent factor levels
-#' @param inconsistent_type What to do if we joined keys have a different type
+#' @param inconsistent_type What to do if the joined keys have a different type
 #' @param grouped_input What to do if one or both of the tables are grouped
 #' @param na_keys What to do if keys contain missing values
 #' @return A character vector of class `"powerjoin_check"`

R/generics_and_methods.R

@@ -11,7 +11,7 @@
 #' @param check A list created with `check_specs()`
 #' @param conflict A function, formula, the special value amongst `"patch"`,
 #'   or a named list of such items. If the LHS of the formula is `rw` the rhs will
-#'   be applied rowwise. Note that the columns will be subsetted with `[` so for
+#'   be applied rowwise. Note that the columns will be subset with `[` so for
 #'   list columns `.x` or `.y` will refer to length 1 lists and you might sometimes
 #'   need `.x[[1]]` or `.y[[1]]`.
 #' @param fill Values used to replace missing values originating in unmatched keys,
@@ -32,11 +32,11 @@
 #'
 #' @section fuzzy joins:
 #'
-#' To specify fuzzy matching conditions we use formulas in which the we refer to
+#' To specify fuzzy matching conditions we use formulas in which we refer to
 #' the columns from the left side data frame using `.x` and the right side data frame
 #' using `.y`, for instance `by = ~ .x$col1 > .y$col2`.
 #'
-#' We can specify several condition and even mix equi condition with fuzzy condition,
+#' We can specify several conditions and even mix equi condition with fuzzy condition,
 #' for instance `by = c(col1 = "col2", ~ .x$col3 > .y$col4)`
 #'
 #' To fuzzy match strings we can leverage the functions from the \pkg{stringr}

R/preprocess.R

@@ -1,6 +1,6 @@
 #' Preprocess powerjoin inputs
 #'
-#' These functions are named after the tidyverse functions `select`, `summarize`,
+#' These functions are named after the tidyverse (dplyr and tidyr) functions `select`, `summarize`,
 #' `nest`, `pack`, `pivot_wider` and `pivot_longer` and are designed to avoid
 #' repetition of key columns when preprocessing the data for a join. They should
 #' only be used in the `x` and `y` arguments of \pkg{powerjoin} join functions. No