diff --git a/base/csv.go b/base/csv.go
index 307cfc2..c782036 100644
--- a/base/csv.go
+++ b/base/csv.go
@@ -6,7 +6,6 @@ import (
 	"io"
 	"os"
 	"regexp"
-	"strconv"
 	"strings"
 )
 
@@ -211,49 +210,3 @@ func ParseCSVToInstances(filepath string, hasHeaders bool) (instances *DenseInst
 
 	return instances, nil
 }
-
-//ParseCSV parses a CSV file and returns the number of columns and rows, the headers, the labels associated with
-//classification, and the data that will be used for training.
-func ParseCSV(filepath string, label int, columns []int) (int, int, []string, []string, []float64) {
-	labels := make([]string, 0)
-	data := make([]float64, 0)
-	headers := make([]string, 0)
-	rows := 0
-
-	file, err := os.Open(filepath)
-	if err != nil {
-		fmt.Println("Error:", err)
-	}
-	defer file.Close()
-
-	reader := csv.NewReader(file)
-
-	headerrow, _ := reader.Read()
-
-	for _, col := range columns {
-		entry := headerrow[col]
-		headers = append(headers, entry)
-	}
-
-	for {
-		record, err := reader.Read()
-		if err == io.EOF {
-			break
-		} else if err != nil {
-			fmt.Println("Error:", err)
-		}
-
-		//
-		labels = append(labels, record[label])
-
-		//Iterate over our rows and append the values to a slice
-		for _, col := range columns {
-			entry := record[col]
-			number, _ := strconv.ParseFloat(entry, 64)
-			data = append(data, number)
-		}
-		rows++
-	}
-	cols := len(columns)
-	return cols, rows, headers, labels, data
-}