## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, eval = FALSE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- # library(mrap) ## ----------------------------------------------------------------------------- # "package::function(Petal.Length ~ Species), data = iris" # "package::function(iris$Petal.Length ~ iris$Species), data = iris" ## ----------------------------------------------------------------------------- # "package::function(cbind(Petal.Length, Petal.Width) ~ Species), data = iris" ## ----------------------------------------------------------------------------- # "package::function(setosa$Petal.Length, virginica$Petal.Length)" ## ----------------------------------------------------------------------------- # "package::function(one_vector, another_vector)" ## ----------------------------------------------------------------------------- # "lme4::lmer(Reaction ~ Days + (Days | Subject), data = sleepstudy)" # "lme4::lmer(Reaction ~ Days + (Days || Subject), data = sleepstudy)" ## ----------------------------------------------------------------------------- # "lme4::lmer(math ~ homework + (homework | schid) + (class_size | schid))" ## ----------------------------------------------------------------------------- # "lme4::lmer(math ~ homework + (1 | schid) + (1 | classid))" ## ----------------------------------------------------------------------------- # is.character("ABC") ## ----------------------------------------------------------------------------- # is.data.frame(iris) ## ----------------------------------------------------------------------------- # species_list <- list("setosa" = setosa, "virginica" = virginica) # # check it is a list # is.list(species_list) # # check that the list is named # names(species_list) ## ----------------------------------------------------------------------------- # is.data.frame(iris) ## ----------------------------------------------------------------------------- # # assume you have a few data frames in a list # iris_new <- iris[, -1] # my_results <- list(iris, iris_new) # # check each of them in a loop # for (element in my_results) { # print(is.data.frame(element)) # } ## ----------------------------------------------------------------------------- # inst_gc <- # mrap::group_comparison( # "stats::t.test(setosa, virginica, var.equal = FALSE)", # list("setosa" = setosa, "virginica" = virginica), # df_results # ) ## ----------------------------------------------------------------------------- # inst_gc$targets <- "Petal.Length" ## ----------------------------------------------------------------------------- # inst_da <- mrap::data_analysis(inst_gc) ## ----------------------------------------------------------------------------- # inst_da_all <- mrap::data_analysis(list(inst_preprocessing, inst_regression)) ## ----------------------------------------------------------------------------- # json <- mrap::to_jsonld(inst_da) # write(json, "data-analysis-1.json") ## ----------------------------------------------------------------------------- # data(iris) # library(dplyr) # setosa <- iris |> # dplyr::filter(Species == "setosa") |> # dplyr::select(Petal.Length) # virginica <- iris |> # dplyr::filter(Species == "virginica") |> # dplyr::select(Petal.Length) # tt <- stats::t.test(setosa, virginica, var.equal = FALSE) ## ----------------------------------------------------------------------------- # df_results <- data.frame( # t.statistic = tt$statistic, # df = tt$parameter, # p.value = tt$p.value # ) # rownames(df_results) <- "value" ## ----------------------------------------------------------------------------- # inst_gc <- # mrap::group_comparison( # "stats::t.test(setosa, virginica, var.equal = FALSE)", # list("setosa" = setosa, "virginica" = virginica), # df_results # ) # # inst_gc$targets <- "Petal.Length" # inst_da <- mrap::data_analysis(inst_gc) # json <- mrap::to_jsonld(inst_da) # write(json, "data-analysis-1.json") ## ----------------------------------------------------------------------------- # eval_results <- list(F1 = 0.46, recall = 0.51) ## ----------------------------------------------------------------------------- # inst_ae <- algorithm_evaluation("N/A", "data_url", eval_results) ## ----------------------------------------------------------------------------- # inst_ae$evaluates <- "my_algorithm_name" # inst_ae$evaluates_for <- "Classification" ## ----------------------------------------------------------------------------- # data(iris) # anova_stats_results <- stats::aov(Petal.Length ~ Species, data = iris) ## ----------------------------------------------------------------------------- # aov <- mrap::stats_aov(Petal.Length ~ Species, data = iris) ## ----------------------------------------------------------------------------- # anova_mrap_results <- aov$anova ## ----------------------------------------------------------------------------- # inst_gc_anova <- aov$dtreg_object ## ----------------------------------------------------------------------------- # inst_gc_anova$label <- "my_fancy_results"