## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----eval=FALSE, echo=TRUE---------------------------------------------------- # # Create sample vectors # v1 <- c(27, 43, 22, 56) # v2 <- c(18.24324, 29.05405, 14.86486, 37.83784) # # # Create data frame # dat <- data.frame("Counts" = v1, "Percents" = v2) # # # Format and Combine # dat$CntPct <- fapply2(dat$Counts, dat$Percents, "%d", "(%.1f%%)") # # # View results # dat # # Counts Percents CntPct # # 1 27 18.24324 27 (18.2%) # # 2 43 29.05405 43 (29.1%) # # 3 22 14.86486 22 (14.9%) # # 4 56 37.83784 56 (37.8%) # ## ----eval=FALSE, echo=TRUE---------------------------------------------------- # library(dplyr) # # # Create sample vectors # v1 <- c(27, 43, 22, 56) # v2 <- c(18.24324, 29.05405, 14.86486, 37.83784) # # # Create data frame # dat <- data.frame("Counts" = v1, "Percents" = v2) # # # Format and Combine # dat <- dat |> # mutate(CntPct = fapply2(dat$Counts, dat$Percents, "%d", "(%.1f%%)")) # # # View results # dat # # Counts Percents CntPct # # 1 27 18.24324 27 (18.2%) # # 2 43 29.05405 43 (29.1%) # # 3 22 14.86486 22 (14.9%) # # 4 56 37.83784 56 (37.8%) # ## ----eval=FALSE, echo=TRUE---------------------------------------------------- # library(libr) # # # Create sample vectors # v1 <- c(27, 43, 22, 56) # v2 <- c(18.24324, 29.05405, 14.86486, 37.83784) # # # Create data frame # dat <- data.frame("Counts" = v1, "Percents" = v2) # # # Format and Combine # dat <- datastep(dat, # { # CntPct <- fapply2(Counts, Percents, "%d", "(%.1f%%)") # }) # # # View results # dat # # Counts Percents CntPct # # 1 27 18.24324 27 (18.2%) # # 2 43 29.05405 43 (29.1%) # # 3 22 14.86486 22 (14.9%) # # 4 56 37.83784 56 (37.8%) # ## ----eval=FALSE, echo=TRUE---------------------------------------------------- # # Create sample vectors # v1 <- c(27, 43, 22, 56) # v2 <- c(18.24324, 29.05405, 14.86486, 37.83784) # # # Create data frame # dat <- data.frame("Counts" = v1, "Percents" = v2) # # formats(dat) <- list(Counts = "%d", Percents = "(%.1f%%)") # # # Format and Combine - Formats already assigned # dat$CntPct <- fapply2(dat$Counts, dat$Percents) # # # View results # dat # # Counts Percents CntPct # # 1 27 18.24324 27 (18.2%) # # 2 43 29.05405 43 (29.1%) # # 3 22 14.86486 22 (14.9%) # # 4 56 37.83784 56 (37.8%) # ## ----eval=FALSE, echo=TRUE---------------------------------------------------- # library(libr) # # # Create sample vectors # grp <- c("Group1", "Group2", "Group3", "Group4") # v1 <- c(27, 43, 22, 56) # v2 <- c(18.24324, 29.05405, 14.86486, 37.83784) # v3 <- c(5.24883, 8.83724, 2.39483, 9.12542) # v4 <- c(2.97632, 3.32845, 0.29784, 4.22156) # # # Create data frame # dat <- data.frame("Group" = grp, "Counts" = v1, "Percents" = v2, # "Mean" = v3, "SD" = v4) # # # View original data # dat # # Group Counts Percents Mean SD # # 1 Group1 27 18.24324 5.24883 2.97632 # # 2 Group2 43 29.05405 8.83724 3.32845 # # 3 Group3 22 14.86486 2.39483 0.29784 # # 4 Group4 56 37.83784 9.12542 4.22156 # # # Create format catalog # fc <- fcat(Counts = "%d", Percents = "(%03.1f%%)", # Mean = "%.1f", SD = "(%04.2f)") # # # Format and Combine columns using Format catalog # dat2 <- datastep(dat, format = fc, # keep = v(Group, CntPct, MeanSD), # { # # CntPct <- fapply2(Counts, Percents) # MeanSD <- fapply2(Mean, SD) # # }) # # View results # dat2 # # Group CntPct MeanSD # # 1 Group1 27 (18.2%) 5.2 (2.98) # # 2 Group2 43 (29.1%) 8.8 (3.33) # # 3 Group3 22 (14.9%) 2.4 (0.30) # # 4 Group4 56 (37.8%) 9.1 (4.22) #