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grep rough audit - static analysis tool
v2.8 written by @Wireghoul
=================================[justanotherhacker.com]===
r-cran-dplyr-1.0.2/tests/testthat/test-join-rows.txt-1-> join_rows(data.frame(x = 1), data.frame(x = factor("a")))
r-cran-dplyr-1.0.2/tests/testthat/test-join-rows.txt:2:Error: Can't join on `x$x` x `y$x` because of incompatible types.
r-cran-dplyr-1.0.2/tests/testthat/test-join-rows.txt:3:i `x$x` is of type <double>>.
r-cran-dplyr-1.0.2/tests/testthat/test-join-rows.txt:4:i `y$x` is of type <factor<127a2>>>.
r-cran-dplyr-1.0.2/tests/testthat/test-join-rows.txt-5-
##############################################
r-cran-dplyr-1.0.2/tests/testthat/test-summarise-errors.txt-105-x Column `b` not found in `.data`
r-cran-dplyr-1.0.2/tests/testthat/test-summarise-errors.txt:106:i Input `c` is `.data$b`.
r-cran-dplyr-1.0.2/tests/testthat/test-summarise-errors.txt-107-
##############################################
r-cran-dplyr-1.0.2/tests/testthat/test-summarise-errors.txt-110-x Column `b` not found in `.data`
r-cran-dplyr-1.0.2/tests/testthat/test-summarise-errors.txt:111:i Input `c` is `.data$b`.
r-cran-dplyr-1.0.2/tests/testthat/test-summarise-errors.txt-112-i The error occurred in group 1: a = 1.
##############################################
r-cran-dplyr-1.0.2/tests/testthat/test-mutate-errors.txt-113-x Column `b` not found in `.data`
r-cran-dplyr-1.0.2/tests/testthat/test-mutate-errors.txt:114:i Input `c` is `.data$b`.
r-cran-dplyr-1.0.2/tests/testthat/test-mutate-errors.txt-115-
##############################################
r-cran-dplyr-1.0.2/tests/testthat/test-mutate-errors.txt-118-x Column `b` not found in `.data`
r-cran-dplyr-1.0.2/tests/testthat/test-mutate-errors.txt:119:i Input `c` is `.data$b`.
r-cran-dplyr-1.0.2/tests/testthat/test-mutate-errors.txt-120-i The error occurred in group 1: a = 1.
##############################################
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt-25-> bind_rows(df1, df2)
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt:26:Error: Can't combine `..1$a` <factor<127a2>> and `..2$a` <integer>.
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt-27-
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt-28-> bind_rows(df1, df3)
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt:29:Error: Can't combine `..1$a` <factor<127a2>> and `..2$a` <double>.
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt-30-
##############################################
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt-35-> bind_rows(df1, df3)
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt:36:Error: Can't combine `..1$b` <double> and `..2$b` <factor<4c40e>>.
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt-37-
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt-38-> bind_rows(df1, df4)
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt:39:Error: Can't combine `..1$b` <double> and `..2$b` <character>.
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt-40-
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt-41-> bind_rows(df2, df3)
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt:42:Error: Can't combine `..1$b` <integer> and `..2$b` <factor<4c40e>>.
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt-43-
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt-44-> bind_rows(df2, df4)
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt:45:Error: Can't combine `..1$b` <integer> and `..2$b` <character>.
r-cran-dplyr-1.0.2/tests/testthat/test-bind-errors.txt-46-
##############################################
r-cran-dplyr-1.0.2/tests/testthat/test-filter-errors.txt-68-Error: Problem with `filter()` input `..1`.
r-cran-dplyr-1.0.2/tests/testthat/test-filter-errors.txt:69:x Input `..1$X1.n..` must be a logical vector, not a integer.
r-cran-dplyr-1.0.2/tests/testthat/test-filter-errors.txt-70-i Input `..1` is `data.frame(Sepal.Length > 3, 1:n())`.
##############################################
r-cran-dplyr-1.0.2/tests/testthat/test-filter-errors.txt-74-Error: Problem with `filter()` input `..1`.
r-cran-dplyr-1.0.2/tests/testthat/test-filter-errors.txt:75:x Input `..1$X1.n..` must be a logical vector, not a integer.
r-cran-dplyr-1.0.2/tests/testthat/test-filter-errors.txt-76-i Input `..1` is `data.frame(Sepal.Length > 3, 1:n())`.
##############################################
r-cran-dplyr-1.0.2/tests/testthat/test-grouped-df.r-47- # value has to be past the ellipsis in $<-()
r-cran-dplyr-1.0.2/tests/testthat/test-grouped-df.r:48: expect_equal(group_data(`$<-`(gf, "x", value = 2))$x, 2)
r-cran-dplyr-1.0.2/tests/testthat/test-grouped-df.r:49: expect_equal(group_data(`$<-`(gf, "y", value = 2))$x, 1)
r-cran-dplyr-1.0.2/tests/testthat/test-grouped-df.r-50-
##############################################
r-cran-dplyr-1.0.2/src/filter.cpp-26- } else {
r-cran-dplyr-1.0.2/src/filter.cpp:27: DPLYR_ERROR_MSG_SET(0, "Input `..{index}${column_name}` must be a logical vector, not a {vec_ptype_full(result)}.");
r-cran-dplyr-1.0.2/src/filter.cpp-28- }
##############################################
r-cran-dplyr-1.0.2/vignettes/base.Rmd-50-| `filter(df, x)` | `df[which(x), , drop = FALSE]`, `subset()` |
r-cran-dplyr-1.0.2/vignettes/base.Rmd:51:| `mutate(df, z = x + y)` | `df$z <- df$x + df$y`, `transform()` |
r-cran-dplyr-1.0.2/vignettes/base.Rmd-52-| `pull(df, 1)` | `df[[1]]` |
r-cran-dplyr-1.0.2/vignettes/base.Rmd:53:| `pull(df, x)` | `df$x` |
r-cran-dplyr-1.0.2/vignettes/base.Rmd-54-| `rename(df, y = x)` | `names(df)[names(df) == "x"] <- "y"` |
##############################################
r-cran-dplyr-1.0.2/vignettes/base.Rmd-57-| `select(df, starts_with("x")` | `df[grepl(names(df), "^x")]` |
r-cran-dplyr-1.0.2/vignettes/base.Rmd:58:| `summarise(df, mean(x))` | `mean(df$x)`, `tapply()`, `aggregate()`, `by()` |
r-cran-dplyr-1.0.2/vignettes/base.Rmd-59-| `slice(df, c(1, 2, 5))` | `df[c(1, 2, 5), , drop = FALSE]` |
##############################################
r-cran-dplyr-1.0.2/vignettes/base.Rmd-160-```
r-cran-dplyr-1.0.2/vignettes/base.Rmd:161:Alternatively, you can use `$<-`:
r-cran-dplyr-1.0.2/vignettes/base.Rmd-162-
##############################################
r-cran-dplyr-1.0.2/vignettes/base.Rmd-355-| `full_join(df1, df2)` |`merge(df1, df2, all = TRUE)` |
r-cran-dplyr-1.0.2/vignettes/base.Rmd:356:| `semi_join(df1, df2)` |`df1[df1$x %in% df2$x, , drop = FALSE]` |
r-cran-dplyr-1.0.2/vignettes/base.Rmd:357:| `anti_join(df1, df2)` |`df1[!df1$x %in% df2$x, , drop = FALSE]` |
r-cran-dplyr-1.0.2/vignettes/base.Rmd-358-
##############################################
r-cran-dplyr-1.0.2/vignettes/programming.Rmd-27- they were variables in the environment (i.e. you write `my_variable` not
r-cran-dplyr-1.0.2/vignettes/programming.Rmd:28: `df$myvariable`).
r-cran-dplyr-1.0.2/vignettes/programming.Rmd-29-
##############################################
r-cran-dplyr-1.0.2/vignettes/programming.Rmd-120- that allows you to access the current variables either directly, with
r-cran-dplyr-1.0.2/vignettes/programming.Rmd:121: `.data$x` or indirectly with `.data[[var]]`. Don't expect other functions
r-cran-dplyr-1.0.2/vignettes/programming.Rmd-122- to work with it.
##############################################
r-cran-dplyr-1.0.2/vignettes/programming.Rmd-215-
r-cran-dplyr-1.0.2/vignettes/programming.Rmd:216:You can eliminate this by using `.data$var` and importing `.data` from its source in the [rlang](https://rlang.r-lib.org/) package (the underlying package that implements tidy evaluation):
r-cran-dplyr-1.0.2/vignettes/programming.Rmd-217-
##############################################
r-cran-dplyr-1.0.2/vignettes/programming.Rmd-350-
r-cran-dplyr-1.0.2/vignettes/programming.Rmd:351:Many Shiny input controls return character vectors, so you can use the same approach as above: `.data[[input$var]]`.
r-cran-dplyr-1.0.2/vignettes/programming.Rmd-352-
##############################################
r-cran-dplyr-1.0.2/R/join-rows.R-13- abort(c(
r-cran-dplyr-1.0.2/R/join-rows.R:14: glue("Can't join on `x${x_name}` x `y${y_name}` because of incompatible types."),
r-cran-dplyr-1.0.2/R/join-rows.R:15: i = glue("`x${x_name}` is of type <{x_type}>>.", x_type = vec_ptype_full(cnd$x)),
r-cran-dplyr-1.0.2/R/join-rows.R:16: i = glue("`y${y_name}` is of type <{y_type}>>.", y_type = vec_ptype_full(cnd$y))
r-cran-dplyr-1.0.2/R/join-rows.R-17- ))
##############################################
r-cran-dplyr-1.0.2/R/deprec-location.R-36- structure(list(
r-cran-dplyr-1.0.2/R/deprec-location.R:37: df = lobstr::obj_addr(df),
r-cran-dplyr-1.0.2/R/deprec-location.R-38- vars = set_names(lobstr::obj_addrs(df), names(df)),
##############################################
r-cran-dplyr-1.0.2/R/join.r-51-#' To join by different variables on `x` and `y`, use a named vector.
r-cran-dplyr-1.0.2/R/join.r:52:#' For example, `by = c("a" = "b")` will match `x$a` to `y$b`.
r-cran-dplyr-1.0.2/R/join.r-53-#'
r-cran-dplyr-1.0.2/R/join.r-54-#' To join by multiple variables, use a vector with length > 1.
r-cran-dplyr-1.0.2/R/join.r:55:#' For example, `by = c("a", "b")` will match `x$a` to `y$a` and `x$b` to
r-cran-dplyr-1.0.2/R/join.r:56:#' `y$b`. Use a named vector to match different variables in `x` and `y`.
r-cran-dplyr-1.0.2/R/join.r:57:#' For example, `by = c("a" = "b", "c" = "d")` will match `x$a` to `y$b` and
r-cran-dplyr-1.0.2/R/join.r:58:#' `x$c` to `y$d`.
r-cran-dplyr-1.0.2/R/join.r-59-#'
##############################################
r-cran-dplyr-1.0.2/R/doc-params.R-27-#' It's what allows you to type (e.g.) `filter(diamonds, x == 0 & y == 0 & z == 0)`
r-cran-dplyr-1.0.2/R/doc-params.R:28:#' instead of `diamonds[diamonds$x == 0 & diamonds$y == 0 & diamonds$z == 0, ]`.
r-cran-dplyr-1.0.2/R/doc-params.R-29-#'
##############################################
r-cran-dplyr-1.0.2/R/grouped-df.r-230-#' @export
r-cran-dplyr-1.0.2/R/grouped-df.r:231:`$<-.grouped_df` <- function(x, name, ..., value) {
r-cran-dplyr-1.0.2/R/grouped-df.r-232- out <- NextMethod()
##############################################
r-cran-dplyr-1.0.2/NEWS.md-198-
r-cran-dplyr-1.0.2/NEWS.md:199:* Grouped data frames now have `names<-`, `[[<-`, `[<-` and `$<-` methods that
r-cran-dplyr-1.0.2/NEWS.md-200- re-generate the underlying grouping. Note that modifying grouping variables
r-cran-dplyr-1.0.2/NEWS.md:201: in multiple steps (i.e. `df$grp1 <- 1; df$grp2 <- 1`) will be inefficient
r-cran-dplyr-1.0.2/NEWS.md-202- since the data frame will be regrouped after each modification.
##############################################
r-cran-dplyr-1.0.2/NEWS.md-1136-* [API] The new `.data` and `.env` environments can be used inside
r-cran-dplyr-1.0.2/NEWS.md:1137: all verbs that operate on data: `.data$column_name` accesses the column
r-cran-dplyr-1.0.2/NEWS.md:1138: `column_name`, whereas `.env$var` accesses the external variable `var`.
r-cran-dplyr-1.0.2/NEWS.md-1139- Columns or external variables named `.data` or `.env` are shadowed, use
r-cran-dplyr-1.0.2/NEWS.md:1140: `.data$...` and/or `.env$...` to access them. (`.data` implements strict
r-cran-dplyr-1.0.2/NEWS.md-1141- matching also for the `$` operator (#2591).)
##############################################
r-cran-dplyr-1.0.2/inst/doc/base.Rmd-50-| `filter(df, x)` | `df[which(x), , drop = FALSE]`, `subset()` |
r-cran-dplyr-1.0.2/inst/doc/base.Rmd:51:| `mutate(df, z = x + y)` | `df$z <- df$x + df$y`, `transform()` |
r-cran-dplyr-1.0.2/inst/doc/base.Rmd-52-| `pull(df, 1)` | `df[[1]]` |
r-cran-dplyr-1.0.2/inst/doc/base.Rmd:53:| `pull(df, x)` | `df$x` |
r-cran-dplyr-1.0.2/inst/doc/base.Rmd-54-| `rename(df, y = x)` | `names(df)[names(df) == "x"] <- "y"` |
##############################################
r-cran-dplyr-1.0.2/inst/doc/base.Rmd-57-| `select(df, starts_with("x")` | `df[grepl(names(df), "^x")]` |
r-cran-dplyr-1.0.2/inst/doc/base.Rmd:58:| `summarise(df, mean(x))` | `mean(df$x)`, `tapply()`, `aggregate()`, `by()` |
r-cran-dplyr-1.0.2/inst/doc/base.Rmd-59-| `slice(df, c(1, 2, 5))` | `df[c(1, 2, 5), , drop = FALSE]` |
##############################################
r-cran-dplyr-1.0.2/inst/doc/base.Rmd-160-```
r-cran-dplyr-1.0.2/inst/doc/base.Rmd:161:Alternatively, you can use `$<-`:
r-cran-dplyr-1.0.2/inst/doc/base.Rmd-162-
##############################################
r-cran-dplyr-1.0.2/inst/doc/base.Rmd-355-| `full_join(df1, df2)` |`merge(df1, df2, all = TRUE)` |
r-cran-dplyr-1.0.2/inst/doc/base.Rmd:356:| `semi_join(df1, df2)` |`df1[df1$x %in% df2$x, , drop = FALSE]` |
r-cran-dplyr-1.0.2/inst/doc/base.Rmd:357:| `anti_join(df1, df2)` |`df1[!df1$x %in% df2$x, , drop = FALSE]` |
r-cran-dplyr-1.0.2/inst/doc/base.Rmd-358-
##############################################
r-cran-dplyr-1.0.2/inst/doc/programming.Rmd-27- they were variables in the environment (i.e. you write `my_variable` not
r-cran-dplyr-1.0.2/inst/doc/programming.Rmd:28: `df$myvariable`).
r-cran-dplyr-1.0.2/inst/doc/programming.Rmd-29-
##############################################
r-cran-dplyr-1.0.2/inst/doc/programming.Rmd-120- that allows you to access the current variables either directly, with
r-cran-dplyr-1.0.2/inst/doc/programming.Rmd:121: `.data$x` or indirectly with `.data[[var]]`. Don't expect other functions
r-cran-dplyr-1.0.2/inst/doc/programming.Rmd-122- to work with it.
##############################################
r-cran-dplyr-1.0.2/inst/doc/programming.Rmd-215-
r-cran-dplyr-1.0.2/inst/doc/programming.Rmd:216:You can eliminate this by using `.data$var` and importing `.data` from its source in the [rlang](https://rlang.r-lib.org/) package (the underlying package that implements tidy evaluation):
r-cran-dplyr-1.0.2/inst/doc/programming.Rmd-217-
##############################################
r-cran-dplyr-1.0.2/inst/doc/programming.Rmd-350-
r-cran-dplyr-1.0.2/inst/doc/programming.Rmd:351:Many Shiny input controls return character vectors, so you can use the same approach as above: `.data[[input$var]]`.
r-cran-dplyr-1.0.2/inst/doc/programming.Rmd-352-
##############################################
r-cran-dplyr-1.0.2/debian/tests/run-unit-test-3-oname=dplyr
r-cran-dplyr-1.0.2/debian/tests/run-unit-test:4:pkg=r-cran-`echo $oname | tr '[A-Z]' '[a-z]'`
r-cran-dplyr-1.0.2/debian/tests/run-unit-test-5-
r-cran-dplyr-1.0.2/debian/tests/run-unit-test-6-if [ "$AUTOPKGTEST_TMP" = "" ] ; then
r-cran-dplyr-1.0.2/debian/tests/run-unit-test:7: AUTOPKGTEST_TMP=`mktemp -d /tmp/${pkg}-test.XXXXXX`
r-cran-dplyr-1.0.2/debian/tests/run-unit-test-8- trap "rm -rf $AUTOPKGTEST_TMP" 0 INT QUIT ABRT PIPE TERM