add rlang

DESCRIPTION

@@ -17,6 +17,7 @@ Imports:
     lazyeval,
     matrixStats,
     methods,
+    rlang,
     stringr,
     tidyr
 Suggests:

R/fill_gap.R

@@ -30,7 +30,7 @@ fill_gap <- function(x, ...,  full = FALSE, roll = FALSE, rollends = if (roll=="
 	originalattributes <- attributes(x)$class
 
 	# check byvars, timevar form a panel
-	stopifnot(is.panel(x, !!as.name(timevar)))
+	stopifnot(is.panel(x, !!rlang::sym(timevar)))
 
 	# create id x time 
 	ans <- dplyr::select_at(x, c(byvars, timevar))

R/is.panel.R

@@ -30,7 +30,7 @@ is.panel <- function(x, ..., .dots){
         message(paste0("Variable ", timevar, " has missing values in ", length(ans)," row(s): ", paste(as.character(ans),collapse = ",")))
         out <- FALSE
     }
-    overall = x %>% group_by(..., add = TRUE) %>% group_indices()
+    overall = x %>% group_by(..., add = TRUE) %>% dplyr::group_indices()
     if (anyDuplicated(overall)){
         groups <- split(seq_along(overall), overall)
         groups <- groups[vapply(groups, length, integer(1)) > 1]

R/join.R

@@ -65,8 +65,8 @@ join =  function(x, y, kind ,on = intersect(names(x),names(y)), suffixes = c(".x
       if (length(intersect(paste0(common_names, suffixes[2]), setdiff(names(y),common_names)))>0) stop(paste("Adding the suffix",suffixes[2],"in", common_names,"would create duplicates names in y"), call. = FALSE)
       if (length(common_names)>0){
         for (name in common_names){
-          x <- rename(x, !!paste0(name, suffixes[1]) := !!as.name(name))
-          y <- rename(y, !!paste0(name, suffixes[2]) := !!as.name(name))
+          x <- rename(x, !!paste0(name, suffixes[1]) := !!rlang::sym(name))
+          y <- rename(y, !!paste0(name, suffixes[2]) := !!rlang::sym(name))
         }
       }
     }
@@ -95,8 +95,6 @@ join =  function(x, y, kind ,on = intersect(names(x),names(y)), suffixes = c(".x
         x <- dplyr::mutate(x, !!idm := 1L)
         idu <- tempname(c(names(x), names(y), gen, idm))
         y <- dplyr::mutate(y, !!idu := 1L)
-        idm_symbol = quo(!!as.name(idm))
-        idu_symbol = quo(!!as.name(idu))
       }
       all.x <- FALSE
       all.y <- FALSE
@@ -111,22 +109,19 @@ join =  function(x, y, kind ,on = intersect(names(x),names(y)), suffixes = c(".x
       }
 
       if (gen != FALSE){
-        gen_symbol = quo(!!as.name(gen))
         out <- dplyr::mutate(out, !!gen := 3L)
-        out <- dplyr::mutate(out, !!gen := ifelse(is.na(!!idu_symbol), 1, !!gen_symbol))
-        out <- dplyr::mutate(out, !!gen := ifelse(is.na(!!idm_symbol), 1, !!gen_symbol))
+        out <- dplyr::mutate(out, !!gen := ifelse(is.na(!!rlang::sym(idu)), 1, !!rlang::sym(gen)))
+        out <- dplyr::mutate(out, !!gen := ifelse(is.na(!!rlang::sym(idm)), 1, !!rlang::sym(gen)))
         out <- dplyr::select_at(out, setdiff(names(out), c(idm, idu)))
       }
 
       if (update){
         for (v in common_names){
           newvx <- paste0(v, suffixes[1])
           newvy <- paste0(v, suffixes[2])
-          newvx_symbol = quo(!!as.name(newvx))
-          newvy_symbol = quo(!!as.name(newvy))
-          out <- dplyr::mutate(out, !!newvx := ifelse(is.na(!!newvx_symbol) & !is.na(!!newvy_symbol), !!newvy_symbol, !!newvx_symbol))
+          out <- dplyr::mutate(out, !!newvx := ifelse(is.na(!!rlang::sym(newvx)) & !is.na(!!rlang::sym(newvy)), !!rlang::sym(newvy), !!rlang::sym(newvx)))
           out <- select_at(out, setdiff(names(out), newvy))
-          out <- rename(out, !!v := !!newvx_symbol)
+          out <- rename(out, !!v := !!rlang::sym(newvx))
         }
       }
       return(out)

R/sum_up.R

@@ -2,7 +2,7 @@
 #' 
 #' @param x a data.frame
 #' @param ... Variables to include. Defaults to all non-grouping variables. See the \link[dplyr]{select} documentation.
-#' @param w Weights. Default to NULL. 
+#' @param wt Weights. Default to NULL. 
 #' @param d Should detailed summary statistics be printed?
 #' @param .dots Used to work around non-standard evaluation.
 #' @examples
@@ -105,7 +105,7 @@ describe <- function(df, d = FALSE, wtvar = character(0),  byvars = character(0)
         sum_higher[1] <- sqrt(sum_higher[1])
         sum_higher[2] <- sum_higher[2]/sum_higher[1]^3
         sum_higher[3] <- sum_higher[3]/sum_higher[1]^4
-        sum_quantile <- pctile(x_omit, c(0, 0.01, 0.05, 0.1, 0.25, 0.50, 0.75, 0.9, 0.95, 0.99, 1), w = w_omit)
+        sum_quantile <- pctile(x_omit, c(0, 0.01, 0.05, 0.1, 0.25, 0.50, 0.75, 0.9, 0.95, 0.99, 1), wt = w_omit)
       } else{
         x_omit <- na.omit(x)
         m <- mean(x_omit)