Rewrite ParseCSV, add DataFrame Structure.

data/csv.go

@@ -4,33 +4,39 @@ package data
 
 import (
 	"encoding/csv"
-	"fmt"
 	"io"
 	"os"
 	"strconv"
+
+	"github.com/gonum/matrix/mat64"
 )
 
 //Parses a CSV file, returning 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)
+func ParseCSV(filepath string, featureCols []int, labelCols []int, header bool) *DataFrame {
 	headers := make([]string, 0)
+	data := make([]float64, 0)
+	labels := make([]string, 0)
 	rows := 0
 
 	file, err := os.Open(filepath)
 	if err != nil {
-		fmt.Println("Error:", err)
+		panic(err)
 	}
 	defer file.Close()
 
 	reader := csv.NewReader(file)
 
-	headerrow, _ := reader.Read()
+	if header {
+		record, err := reader.Read()
+		if err != nil {
+			panic(err)
+		}
 
-	for _, col := range columns {
-		entry := headerrow[col]
-		headers = append(headers, entry)
+		for _, col := range append(featureCols, labelCols...) {
+			headers = append(headers, record[col])
+		}
+		rows += 1
 	}
 
 	for {
@@ -38,20 +44,29 @@ func ParseCsv(filepath string, label int, columns []int) (int, int, []string, []
 		if err == io.EOF {
 			break
 		} else if err != nil {
-			fmt.Println("Error:", err)
+			panic(err)
 		}
 
-		//
-		labels = append(labels, record[label])
-
 		//Iterate over our rows and append the values to a slice
-		for _, col := range columns {
+		for _, col := range featureCols {
 			entry := record[col]
 			number, _ := strconv.ParseFloat(entry, 64)
 			data = append(data, number)
 		}
+
+		for _, col := range labelCols {
+			labels = append(labels, record[col])
+		}
+
 		rows += 1
 	}
-	cols := len(columns)
-	return cols, rows, headers, labels, data
+
+	return &DataFrame{
+		Headers:  headers,
+		Labels:   labels,
+		Values:   mat64.NewDense(rows, len(featureCols), data),
+		NRow:     rows,
+		NFeature: len(featureCols),
+		NLabel:   len(labelCols),
+	}
 }

data/data.go

@@ -0,0 +1,14 @@
+/* Data - consists of helper functions for parsing different data formats */
+
+package data
+
+import "github.com/gonum/matrix/mat64"
+
+type DataFrame struct {
+	Headers  []string
+	Labels   []string
+	Values   *mat64.Dense // We first focus on numeric values for now
+	NRow     int
+	NFeature int
+	NLabel   int
+}

data/data_test.go

@@ -0,0 +1,38 @@
+package data
+
+import (
+	"testing"
+	. "github.com/smartystreets/goconvey/convey"
+)
+
+func TestParseCSV(t *testing.T) {
+
+	Convey("Parse IRIS dataset", t, func() {
+		dataFrame := ParseCSV("../examples/datasets/iris.csv", []int{0, 1, 3}, []int{4}, false)
+
+		Convey("First row should be {5.1, 3.5, 0.2}", func() {
+			So(dataFrame.Values.RowView(0), ShouldResemble, []float64{5.1, 3.5, 0.2})
+		})
+
+		Convey("First label should be Iris-setosa", func() {
+			So(dataFrame.Labels[0], ShouldEqual, "Iris-setosa")
+		})
+
+		Convey("Headers should be empty", func() {
+			So(dataFrame.Headers, ShouldResemble, []string{})
+		})
+
+		Convey("Number of features should be 3", func() {
+			So(dataFrame.NFeature, ShouldEqual, 3)
+		})
+
+		Convey("Number of labels should be 1", func() {
+			So(dataFrame.NLabel, ShouldEqual, 1)
+		})
+
+		Convey("Number of rows should be 150", func() {
+			So(dataFrame.NRow, ShouldEqual, 150)
+		})
+
+	})
+}