GINI calculation R code

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R code to calculate GINI index

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  setwd( c:/amit ) dataset1 <- modeling_data_22ndMarch2017_yes_signal_thinfile.csv   data1 <- read.csv(file = dataset1, header = TRUE,na.strings='NULL', sep = , ) filename <- Rank1 and Plots_Indifi_15Feb_2 dep_var <- decision groups <- 10 vars <- c( new_score_bureau_only )  library(Hmisc) library(R2HTML) fl <- paste(filename, .xls ,sep = ) rankNplot_sub <- function(temp1,groups,tag) { temp1$buckets <- as.numeric(cut2(temp1[,2] ,g=groups)) df = data.frame(matrix(mat.or.vec(groups,7), groups, 7, dimnames=list(c(), c( Group , Mtestvar , Mlongbad , Min , Max , Nobs , nbad ))),stringsAsFactors=F) for (i in 1:groups) { subset <- temp1[which(temp1[,3] == i),] df$Group[i] <- i df$Mtestvar[i] <- mean(subset[,2]) df$Mlongbad[i] <- mean(subset[,1]) df$Min[i] <- min(subset[,2]) df$Max[i] <- max(subset[,2]) df$Nobs[i] <- nrow(subset) df$nbad[i] <- sum(subset[,1]) } M = max(temp1$buckets,na.rm=TRUE) df <- df[1:M,] par(mar = rep(2, 4)) p.plot <- plot(df$Mtestvar,df$Mlongbad) d.data <- df return(list(p.plot,d.data)) } for (j in 1:length(vars)) { ind_var <- vars[j] print( ind_var ) print(ind_var) svars <- c(dep_var,ind_var) temp1 <- data1[,svars] temp1$buckets <- as.numeric(cut2(temp1[,2] ,g=groups)) M = max(temp1$buckets,na.rm=TRUE) temp_min <- temp1[which(temp1$buckets == 1),svars] temp_max <- temp1[which(temp1$buckets == M),svars] title1 <- paste(ind_var, vs ,dep_var, sep= ) title2 <- paste( Min Bucket of ,ind_var, vs ,dep_var, sep= ) title3 <- paste( Max Bucket of ,ind_var, vs ,dep_var, sep= ) HTML.title(title1, HR=3 ,file=fl, append = TRUE ) d1 <- rankNplot_sub(temp1[,svars],groups, overall ) html.data.frame(d1[[2]],file=fl, append = TRUE ) HTML.title(title2, HR=3 ,file=fl, append = TRUE ) d2 <- rankNplot_sub(temp_min,groups, min ) html.data.frame(d2[[2]],file=fl, append = TRUE )   HTML.title(title3, HR=3 ,file=fl, append = TRUE ) d3 <- rankNplot_sub(temp_max,groups, max ) html.data.frame(d3[[2]],file=fl, append = TRUE ) } dep_var <- Bureau_thickness groups <- 20  
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