bonehead
diff --git a/‎standard_cleaning.R‎ ‎processing_basic.R‎standard_cleaning.R renamed to processing_basic.R b/‎standard_cleaning.R‎ ‎processing_basic.R‎standard_cleaning.R renamed to processing_basic.R
diff --git a/‎processing_categorical.R‎
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+### functions for categorical data processing
+# 1. One-hot encoding categorical features
+
+
+## loading libraries
+library(dummies)
+library(plyr)
+
+
+## function for one-hot encoding categorical features
+onehot_encode_categories <- function(X_train,X_test=data.frame())
+{
+	# creating panel
+	cat("Creating panel\n")
+
+	if (nrow(X_test) > 0)
+	{
+		panel <- rbind(X_train,X_test)
+	}else
+	{
+		panel <- X_train
+	}
+
+	# extracting categorical columns
+	categorical_columns <- NULL
+
+	for (i in 1:ncol(panel))
+	{
+		if (class(panel[,i]) %in% c("character", "factor"))
+		{
+			categorical_columns <- c(categorical_columns, colnames(panel)[i])
+		}
+	}
+
+	# creating dummy variables
+	cat("One-hot encoding the categorical variables")
+
+	if (length(categorical_columns) > 0)
+	{
+		panel <- dummy.data.frame(panel, names=categorical_columns, sep="_")
+		colnames(panel) <- gsub("[[:punct:]]", "", colnames(panel))
+		colnames(panel) <- gsub("[[:space:]]+", " ", colnames(panel))
+		colnames(panel) <- gsub(" ", "_", colnames(panel))
+	}
+
+	X_train <- panel[1:nrow(X_train),]
+	X_test <- panel[(nrow(X_train)+1):nrow(panel),]
+
+	return(list(X_train,X_test))
+}
+