## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----------------------------------------------------------------------------- library(diffdf) LENGTH <- 30 suppressWarnings(RNGversion("3.5.0")) set.seed(12334) test_data <- tibble::tibble( ID = 1:LENGTH, GROUP1 = rep(c(1, 2), each = LENGTH / 2), GROUP2 = rep(c(1:(LENGTH / 2)), 2), INTEGER = rpois(LENGTH, 40), BINARY = sample(c("M", "F"), LENGTH, replace = TRUE), DATE = lubridate::ymd("2000-01-01") + rnorm(LENGTH, 0, 7000), DATETIME = lubridate::ymd_hms("2000-01-01 00:00:00") + rnorm(LENGTH, 0, 200000000), CONTINUOUS = rnorm(LENGTH, 30, 12), CATEGORICAL = factor(sample(c("A", "B", "C"), LENGTH, replace = TRUE)), LOGICAL = sample(c(TRUE, FALSE), LENGTH, replace = TRUE), CHARACTER = stringi::stri_rand_strings(LENGTH, rpois(LENGTH, 13), pattern = "[ A-Za-z0-9]") ) test_data diffdf(test_data, test_data) ## ----------------------------------------------------------------------------- test_data2 <- test_data test_data2 <- test_data2[, -6] diffdf(test_data, test_data2, suppress_warnings = TRUE) ## ----------------------------------------------------------------------------- test_data2 <- test_data test_data2 <- test_data2[1:(nrow(test_data2) - 2), ] diffdf(test_data, test_data2, suppress_warnings = TRUE) ## ----------------------------------------------------------------------------- test_data2 <- test_data test_data2[5, 2] <- 6 diffdf(test_data, test_data2, suppress_warnings = TRUE) ## ----------------------------------------------------------------------------- test_data2 <- test_data test_data2[, 2] <- as.character(test_data2[, 2]) diffdf(test_data, test_data2, suppress_warnings = TRUE) ## ----------------------------------------------------------------------------- test_data2 <- test_data attr(test_data$ID, "label") <- "This is a interesting label" attr(test_data2$ID, "label") <- "what do I type here?" diffdf(test_data, test_data2, suppress_warnings = TRUE) ## ----------------------------------------------------------------------------- test_data2 <- test_data levels(test_data2$CATEGORICAL) <- c(1, 2, 3) diffdf(test_data, test_data2, suppress_warnings = TRUE) ## ----------------------------------------------------------------------------- test_data2 <- test_data test_data2$INTEGER[c(5, 2, 15)] <- 99L diffdf(test_data, test_data2, keys = c("GROUP1", "GROUP2"), suppress_warnings = TRUE) ## ----------------------------------------------------------------------------- iris2 <- iris for (i in 1:3) iris2[i, i] <- 99 diff <- diffdf(iris, iris2, suppress_warnings = TRUE) diffdf_issuerows(iris, diff) diffdf_issuerows(iris2, diff) ## ----------------------------------------------------------------------------- diffdf_issuerows(iris2, diff, vars = "Sepal.Length") diffdf_issuerows(iris2, diff, vars = c("Sepal.Length", "Sepal.Width")) ## ----------------------------------------------------------------------------- iris2 <- iris for (i in 1:3) iris2[i, i] <- 99 diff <- diffdf(iris, iris2, suppress_warnings = TRUE) diffdf_has_issues(diff) ## ----eval = FALSE------------------------------------------------------------- # if (diffdf_has_issues(diff)) { # # # } ## ----------------------------------------------------------------------------- dsin1 <- data.frame(x = 1.1e-06) dsin2 <- data.frame(x = 1.1e-07) diffdf(dsin1, dsin2, suppress_warnings = TRUE) diffdf(dsin1, dsin2, tolerance = 0.001, suppress_warnings = TRUE) ## ----------------------------------------------------------------------------- dsin1 <- data.frame(x = as.integer(c(1, 2, 3))) dsin2 <- data.frame(x = as.numeric(c(1, 2, 3))) diffdf(dsin1, dsin2, suppress_warnings = TRUE) diffdf(dsin1, dsin2, suppress_warnings = TRUE, strict_numeric = FALSE) dsin1 <- data.frame(x = as.character(c(1, 2, 3)), stringsAsFactors = FALSE) dsin2 <- data.frame(x = as.factor(c(1, 2, 3))) diffdf(dsin1, dsin2, suppress_warnings = TRUE) diffdf(dsin1, dsin2, suppress_warnings = TRUE, strict_factor = FALSE)