Could someone who comes from R language and SAS programming help me? I need to execute the code below programmatically in SAS. The code below was developed in R Spark on databricks. The goal is to run SAS through PROC, but as is little known in SAS Transfers. If anyone can help me with any suggestions. 6 for(i in 1:nrow(distinct_cluster)){ grupo=distinct_cluster[[i]] dados<-dados_cluster dados<-dados%>%filter(grupos==grupo) variaveis_clusters <- dados %>% filter(DATIPRNOTFSC<'2019-01-01', DATIPRNOTFSC>='2018-01-01')%>% group_by(DESATICLI, Calculation)%>% summarize(qtde=n())%>% sdf_pivot(DESATICLI ~ Calculation, fun.aggregate = list(qtde = "sum")) stats <- variaveis_clusters %>% select(-DESATICLI) %>% summarise_all(funs(avg, min, max)) %>% collect() cols <- variaveis_clusters%>% select(-DESATICLI) %>% colnames() avgs <- stats %>% select(ends_with("avg")) %>% unlist mins <- stats %>% select(ends_with("min")) %>% unlist maxs <- stats %>% select(ends_with("max")) %>% unlist exprs <- glue("(`{cols}` - {avgs}) / ({maxs} - {mins})") %>% setNames(cols) %>% lapply(parse_quosure) variaveis_escaladas<-variaveis_clusters %>% mutate(!!! exprs) variaveis_clusters_tratado <- na.replace(variaveis_escaladas,0) variaveis_clusters_tratado <- sdf_copy_to(sc, variaveis_clusters_tratado, name = "variaveis_clusters_tratado", overwrite = TRUE) set.seed(364221) cluster <- ml_kmeans(variaveis_clusters_tratado, DESATICLI ~ ., k = 6) clusters <- ml_predict(cluster, variaveis_clusters_tratado) clusters <- clusters%>%mutate(grupos = case_when( prediction==0 ~ "A", prediction==1 ~ "B", prediction==2 ~ "C", prediction==3 ~ "D", prediction==4 ~ "E", prediction==5 ~ "F")) if(i==1){ saida<-clusters%>%select(DESATICLI,grupos)%>%mutate(grupos_1=grupo) }else{ saida<-sdf_bind_rows(saida,clusters%>%select(DESATICLI,grupos)%>%mutate(grupos_1=grupo)) } }
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