Replace term 'dataframe' by 'data frame' anywhere

.github/CONTRIBUTING.md

@@ -94,12 +94,12 @@ Recommended resources to get started are:
 - have a quick look at the [tidyverse style guide](https://style.tidyverse.org/).
 There you see how to style object, variable and function names, as well as the documentation.
 At least keep in mind: **use lower case and 'snake_case'** for object, variable and function names.
-- if your function returns a dataframe, use `dplyr::as_tibble()` to return it as a tibble instead.
-A tibble is a dataframe that makes working in the tidyverse a little [easier](https://r4ds.had.co.nz/tibbles.html).
+- if your function returns a data frame, use `dplyr::as_tibble()` to return it as a tibble instead.
+A tibble is a data frame that makes working in the tidyverse a little [easier](https://r4ds.had.co.nz/tibbles.html).
 - functions that read or process data should return data as much as possible internationalized:
     - availability of English names for types, environmental pressures, ...
     Other languages can be accommodated as well;
-    - English names for table headings (dataframe variables).
+    - English names for table headings (data frame variables).
 
 
 ### How to contribute code? 

NEWS.md

@@ -6,7 +6,7 @@ For the moment not taking further measures to protect against it, as the package
 
 # watina 0.4.1 (2021-06-11)
 
-- Fixed non-working `get_xg3()` and `get_chem()` for dataframe input, by avoiding the currently defunct `dbplyr::db_drop_table()` (#89, [08bc66d](https://github.com/inbo/watina/commit/08bc66d)).
+- Fixed non-working `get_xg3()` and `get_chem()` for data frame input, by avoiding the currently defunct `dbplyr::db_drop_table()` (#89, [08bc66d](https://github.com/inbo/watina/commit/08bc66d)).
 - Various maintenance (#81, #86, #87, #88, [c382499](https://github.com/inbo/watina/commit/c382499)).
 
 # watina 0.4.0 (2021-01-18)

R/cluster.R

@@ -1,7 +1,7 @@
 #' Detect (spatial) groundwater well clusters
 #'
 #' \code{cluster_locs()} accepts as input a
-#' dataframe with X/Y coordinates, or an \code{sf} object
+#' data frame with X/Y coordinates, or an \code{sf} object
 #' of geometry type \code{POINT}.
 #' The function adds an integer variable that defines cluster membership.
 #' The intention is to detect spatial groundwater well clusters; hence it uses a
@@ -18,9 +18,9 @@
 #'
 #' The function's code was partly inspired by unpublished code from Ivy Jansen.
 #'
-#' @param input A dataframe with X/Y coordinates, or an \code{sf} object of
+#' @param input A data frame with X/Y coordinates, or an \code{sf} object of
 #' geometry type \code{POINT}.
-#' A typical input dataframe is the collected output of \code{\link{get_locs}}.
+#' A typical input data frame is the collected output of \code{\link{get_locs}}.
 #' @param max_dist The maximum geospatial distance between two points to make
 #' them belong to the same cluster.
 #' The default value is sensible for many usecases,
@@ -32,11 +32,11 @@
 #' \code{input}.
 #' @param xvar String.
 #' The X coordinate variable name; only considered when \code{input} is a
-#' dataframe.
+#' data frame.
 #' Defaults to \code{"x"}.
 #' @param yvar String.
 #' The Y coordinate variable name; only considered when \code{input} is a
-#' dataframe.
+#' data frame.
 #' Defaults to \code{"y"}.
 #'
 #' @return

R/eval.R

@@ -657,7 +657,7 @@ eval_chem <- function(data,
     type <- match.arg(type)
 
     assert_that(inherits(data, what = c("tbl_lazy", "data.frame")),
-                msg = "data must be a lazy object or a dataframe.")
+                msg = "data must be a lazy object or a data frame.")
     assert_that(all(c("loc_code",
                       "date",
                       "lab_sample_id",

R/get.R

@@ -717,7 +717,7 @@ get_locs <- function(con,
 #' If you like to print the lazy object in a sorted manner, you must add
 #' `%>% arrange(...)` yourself.
 #'
-#' @param locs A \code{tbl_lazy} object or a dataframe, with at least a column
+#' @param locs A \code{tbl_lazy} object or a data frame, with at least a column
 #' \code{loc_code} that defines the locations for which values are to be
 #' returned.
 #' Typically, this will be the object returned by \code{\link{get_locs}}.

R/selectlocs.R

@@ -20,7 +20,7 @@
 #' Hence, the result will depend both on the XG3 \emph{types} (HG3, LG3 and/or
 #' VG3) for which statistics have been computed (specified by \code{xg3_type}),
 #' and on the conditions, specified by \code{conditions}.
-#' See the devoted section on the \code{conditions} dataframe.
+#' See the devoted section on the \code{conditions} data frame.
 #'
 #' Only locations are returned:
 #' \itemize{
@@ -34,7 +34,7 @@
 #' conditions are met;
 #' }
 #' }
-#' As the conditions imposed by the \code{conditions} dataframe are always
+#' As the conditions imposed by the \code{conditions} data frame are always
 #' evaluated as a
 #' required combination of conditions ('and'), the user must make different
 #' calls to \code{selectlocs_xg3()}
@@ -50,7 +50,7 @@
 #'
 #' \code{selectlocs_xg3()} joins the long-formatted results of
 #' \code{\link{eval_xg3_avail}} and \code{\link{eval_xg3_series}}
-#' with the \code{conditions} dataframe in order to evaluate the conditions.
+#' with the \code{conditions} data frame in order to evaluate the conditions.
 #' Often, this join in itself already leads to dropping specific
 #' combinations of \code{loc_code} and \code{xg3_variable}.
 #' At least the locations that are completely dropped in this step are reported
@@ -69,13 +69,13 @@
 #' \code{xg3_type}, \code{max_gap} and \code{min_dur} are not needed
 #' (they will be ignored).
 #'
-#' @section Specification of the conditions dataframe:
+#' @section Specification of the conditions data frame:
 #' Conditions can be specified for each of the summary statistics returned
 #' by \code{\link{eval_xg3_avail}} and \code{\link{eval_xg3_series}}.
 #' Consequently, XG3 availability conditions and
 #' XG3 series conditions can be distinguished.
 #'
-#' The \code{conditions} parameter takes a dataframe that must have the
+#' The \code{conditions} parameter takes a data frame that must have the
 #' following columns:
 #' \describe{
 #' \item{\code{xg3_variable}}{One of: \code{"combined","lg3_lcl","lg3_ost",
@@ -95,8 +95,8 @@
 #' }
 #' }
 #'
-#' Each condition is one row of the dataframe.
-#' The dataframe should have at least one, and may have many.
+#' Each condition is one row of the data frame.
+#' The data frame should have at least one, and may have many.
 #' Each combination of \code{xg3_variable} and \code{statistic} must be
 #' unique.
 #' Conditions on XG3 variables, absent from \code{data} or not implied by
@@ -130,7 +130,7 @@
 #' Specifies the 'X' in 'XG3': either \code{"L"}, \code{"H"} and/or \code{"V"}.
 #' Together with the available variables in \code{data},
 #' \code{xg3_type} determines the meaning of the variable \code{"combined"}.
-#' @param conditions A dataframe.
+#' @param conditions A data frame.
 #' See the devoted section below.
 #' @param verbose Logical.
 #' If \code{TRUE}, give feedback on dropped locations because of
@@ -368,13 +368,13 @@ selectlocs_xg3 <- function(data,
                   "criterion",
                   "direction") %in%
                       colnames(conditions)),
-                msg = "The conditions dataframe does not have the required column names.")
+                msg = "The conditions data frame does not have the required column names.")
 
     assert_that(nrow(conditions) > 0,
-        msg = "You must at least provide one condition in the conditions dataframe.")
+        msg = "You must at least provide one condition in the conditions data frame.")
 
     assert_that(all(!is.na(conditions)),
-                msg = "You must not leave empty cells in the conditions dataframe.")
+                msg = "You must not leave empty cells in the conditions data frame.")
 
     assert_that(all(conditions$xg3_variable %in% c("combined",
                                                  "lg3_lcl",
@@ -383,22 +383,22 @@ selectlocs_xg3 <- function(data,
                                                  "vg3_ost",
                                                  "hg3_lcl",
                                                  "hg3_ost")),
-                msg = "You specified unknown XG3 variables in the conditions dataframe. Please fix.")
+                msg = "You specified unknown XG3 variables in the conditions data frame. Please fix.")
 
     assert_that(is.numeric(conditions$criterion),
-                msg = "The 'criterion' variable of the conditions dataframe must be numeric. Please fix.")
+                msg = "The 'criterion' variable of the conditions data frame must be numeric. Please fix.")
 
     assert_that(all(conditions$direction %in% c("min",
                                               "max",
                                               "equal")),
-                msg = "Directions in the conditions dataframe must be 'min', 'max' or 'equal'. Please fix.")
+                msg = "Directions in the conditions data frame must be 'min', 'max' or 'equal'. Please fix.")
 
     assert_that({
         conditions %>%
             count(.data$xg3_variable, .data$statistic) %>%
             filter(.data$n > 1) %>%
             nrow(.) == 0},
-        msg = "You cannot repeat the same combination of xg3_variable and statistic in the conditions dataframe.")
+        msg = "You cannot repeat the same combination of xg3_variable and statistic in the conditions data frame.")
 
     unknown_statnames <-
         conditions %>%
@@ -422,7 +422,7 @@ selectlocs_xg3 <- function(data,
 
     assert_that(length(unknown_statnames) == 0,
         msg = paste0(
-                "The following 'statistic' names in the conditions dataframe are unknown: ",
+                "The following 'statistic' names in the conditions data frame are unknown: ",
                 paste(unknown_statnames, collapse = ", "),
                 ". Please fix."
                 )
@@ -436,7 +436,7 @@ selectlocs_xg3 <- function(data,
         if (any(str_detect(unique(conditions$statistic), "ser_"))) TRUE else FALSE
 
     assert_that(cond_has_avail | cond_has_ser,
-                msg = "The conditions dataframe has no known 'statistic' names.")
+                msg = "The conditions data frame has no known 'statistic' names.")
 
     ## 1. Collecting statistics
 
@@ -730,7 +730,7 @@ selectlocs_xg3 <- function(data,
 #' Hence, the result will depend both on the \emph{chemical variables} for
 #' which statistics have been computed (specified by \code{chem_var}),
 #' and on the conditions, specified by \code{conditions}.
-#' See the devoted section on the \code{conditions} dataframe.
+#' See the devoted section on the \code{conditions} data frame.
 #'
 #' Only locations are returned:
 #' \itemize{
@@ -744,7 +744,7 @@ selectlocs_xg3 <- function(data,
 #' conditions are met;
 #' }
 #' }
-#' As the conditions imposed by the \code{conditions} dataframe are always
+#' As the conditions imposed by the \code{conditions} data frame are always
 #' evaluated as a
 #' required combination of conditions ('and'), the user must make different
 #' calls to \code{selectlocs_chem()}
@@ -753,11 +753,11 @@ selectlocs_xg3 <- function(data,
 #' If \code{data_type = "data"}, \code{selectlocs_chem()} calls
 #' \code{\link{eval_chem}}.
 #' Its \code{type} and \code{uniformity_test} arguments are derived from the
-#' user-specified \code{conditions} dataframe.
+#' user-specified \code{conditions} data frame.
 #'
 #' \code{selectlocs_chem()} joins the long-formatted results of
 #' \code{\link{eval_chem}}
-#' with the \code{conditions} dataframe in order to evaluate the conditions.
+#' with the \code{conditions} data frame in order to evaluate the conditions.
 #' Often, this join in itself already leads to dropping specific
 #' combinations of \code{loc_code} and \code{chem_variable}.
 #' At least the locations that are completely dropped in this step are reported
@@ -772,11 +772,11 @@ selectlocs_xg3 <- function(data,
 #' with \code{data_type = "summary"}.
 #' In that case the argument \code{chem_var} is ignored.
 #'
-#' @section Specification of the conditions dataframe:
+#' @section Specification of the conditions data frame:
 #' Conditions can be specified for each of the summary statistics returned
 #' by \code{\link{eval_chem}}.
 #'
-#' The \code{conditions} parameter takes a dataframe that must have the
+#' The \code{conditions} parameter takes a data frame that must have the
 #' following columns:
 #' \describe{
 #' \item{\code{chem_variable}}{Can be any chemical variable code,
@@ -802,8 +802,8 @@ selectlocs_xg3 <- function(data,
 #' }
 #' }
 #'
-#' Each condition is one row of the dataframe.
-#' The dataframe should have at least one, and may have many.
+#' Each condition is one row of the data frame.
+#' The data frame should have at least one, and may have many.
 #' Each combination of \code{chem_variable} and \code{statistic} must be
 #' unique.
 #' Conditions on chemical variables, absent from \code{data} or not implied by
@@ -825,7 +825,7 @@ selectlocs_xg3 <- function(data,
 #' codes from the column \code{chem_variable} in \code{data}.
 #' Together with the available variables in \code{data},
 #' \code{chem_var} determines the meaning of the variable \code{"combined"}.
-#' @param conditions A dataframe.
+#' @param conditions A data frame.
 #' See the devoted section below.
 #' @param verbose Logical.
 #' If \code{TRUE}, give feedback on dropped locations because of
@@ -975,10 +975,10 @@ selectlocs_chem <- function(data,
                       "criterion",
                       "direction") %in%
                         colnames(conditions)),
-                msg = "The conditions dataframe does not have the required column names.")
+                msg = "The conditions data frame does not have the required column names.")
 
     assert_that(nrow(conditions) > 0,
-                msg = "You must at least provide one condition in the conditions dataframe.")
+                msg = "You must at least provide one condition in the conditions data frame.")
 
     selectlocs(data = data,
                data_type = data_type,
@@ -1038,19 +1038,19 @@ selectlocs_chem <- function(data,
 #'
 #' Generic (helper) function to select locations that comply with
 #' user-specified conditions,
-#' from either a dataset (dataframe or lazy object) with the variable's values or
-#' from a dataframe with summary statistics.
+#' from either a dataset (data frame or lazy object) with the variable's values or
+#' from a data frame with summary statistics.
 #'
 #' The result of the evaluation function (\code{eval_fun}) must produce a
-#' dataframe, formatted as declared by the second bullet under the
+#' data frame, formatted as declared by the second bullet under the
 #' \code{data} argument.
 #'
 #' @param data Either:
 #' \itemize{
-#' \item{a dataset (dataframe or lazy object) with the variable's values}:
+#' \item{a dataset (data frame or lazy object) with the variable's values}:
 #' with at least a column \code{loc_code}, a column with the variable name,
 #' and a column \code{value};
-#' \item{a dataframe with summary statistics}:
+#' \item{a data frame with summary statistics}:
 #' with a first column \code{loc_code} and a second column with the evaluated
 #' variable names or codes.
 #' The column name of the second column can vary.
@@ -1064,7 +1064,7 @@ selectlocs_chem <- function(data,
 #' dataset.
 #' @param eval_args The arguments of the evaluation function, as a named list,
 #' if \code{data} is a dataset.
-#' @param conditions A dataframe.
+#' @param conditions A data frame.
 #' It must have the
 #' following columns:
 #' \describe{
@@ -1084,8 +1084,8 @@ selectlocs_chem <- function(data,
 #' }
 #' }
 #'
-#' Each condition is one row of the dataframe.
-#' The dataframe should have at least one, and may have many.
+#' Each condition is one row of the data frame.
+#' The data frame should have at least one, and may have many.
 #' Each combination of \code{chem_variable} and \code{statistic} must be
 #' unique.
 #' Conditions on chemical variables, absent from \code{data} or not implied by
@@ -1175,28 +1175,28 @@ selectlocs <- function(data,
                       "criterion",
                       "direction") %in%
                         colnames(conditions)),
-                msg = "The conditions dataframe does not have the required column names.")
+                msg = "The conditions data frame does not have the required column names.")
 
     assert_that(nrow(conditions) > 0,
-                msg = "You must at least provide one condition in the conditions dataframe.")
+                msg = "You must at least provide one condition in the conditions data frame.")
 
     assert_that(all(!is.na(conditions)),
-                msg = "You must not leave empty cells in the conditions dataframe.")
+                msg = "You must not leave empty cells in the conditions data frame.")
 
     assert_that(is.numeric(conditions$criterion),
-                msg = "The 'criterion' variable of the conditions dataframe must be numeric. Please fix.")
+                msg = "The 'criterion' variable of the conditions data frame must be numeric. Please fix.")
 
     assert_that(all(conditions$direction %in% c("min",
                                                 "max",
                                                 "equal")),
-                msg = "Directions in the conditions dataframe must be 'min', 'max' or 'equal'. Please fix.")
+                msg = "Directions in the conditions data frame must be 'min', 'max' or 'equal'. Please fix.")
 
     assert_that({
         conditions %>%
             count(.data$variable, .data$statistic) %>%
             filter(.data$n > 1) %>%
             nrow(.) == 0},
-        msg = "You cannot repeat the same combination of variable and statistic in the conditions dataframe.")
+        msg = "You cannot repeat the same combination of variable and statistic in the conditions data frame.")
 
     ## 1. Collecting statistics
 

R/sf.R

@@ -1,22 +1,22 @@
-#' Convert a dataframe with X and Y coordinates to a geospatial points object
+#' Convert a data frame with X and Y coordinates to a geospatial points object
 #'
-#' \code{as_points} is a convenience function which accepts as input a dataframe
+#' \code{as_points} is a convenience function which accepts as input a data frame
 #' with X/Y coordinates (in meters), assumed to come from the coordinate
 #' reference system (CRS)
 #' 'Belge 1972 / Belgian Lambert 72' (EPSG \href{https://epsg.io/31370}{31370}).
-#' It converts the dataframe into an \code{sf} points object in the same CRS.
+#' It converts the data frame into an \code{sf} points object in the same CRS.
 #'
 #' As locations in Watina are typically defined by their X/Y coordinates,
 #' this function eases the conversion to spatial data.
 #' To later remove all spatial information from the result, you can use
 #' \code{\link[sf:st_geometry]{sf::st_drop_geometry()}}.
 #'
-#' @param df A dataframe with X and Y coordinates in meters, assumed to be in
+#' @param df A data frame with X and Y coordinates in meters, assumed to be in
 #' the Belgian Lambert 72 CRS (EPSG-code 31370).
 #' @param xvar String. The X coordinate variable name. Defaults to \code{"x"}.
 #' @param yvar String. The Y coordinate variable name. Defaults to \code{"y"}.
 #' @param remove Logical. Should the X and Y coordinates be removed from the
-#' dataframe after conversion to a spatial object?
+#' data frame after conversion to a spatial object?
 #' @param warn_dupl Logical.
 #' Defaults to \code{TRUE}.
 #' Should the user be warned when duplicated coordinates are present in the