readCSV.go

// Read a time series from a CSV file
package main

// @dev config goLang folder
// go env -w GO111MODULE=auto
// go mod init aibull.io/goTimeSeriesPrediction
// go mod tidy

// @dev Running
// go run predictor.go

import (
	"bytes"
	"encoding/csv"
	"fmt"
	"io"
	"os"
	"strconv"
	"strings"
)

type TimeSeries struct {
	Day   string  `csv:"Day"`
	Price float32 `csv:"Price"`
}

func main() {
	// Read CSV file
	in, err := os.Open("../../Bitcoin price prediction - Data.csv")
	if err != nil {
		panic(err)
	}
	defer in.Close()

	// Convert *os.File to string
	var buf bytes.Buffer
	io.Copy(&buf, in)
	asString := string(buf.Bytes())

	// Parse CSV using goLang standard library encoding/csv
	r := csv.NewReader(strings.NewReader(asString))
	records, err := r.ReadAll()
	if err != nil {
		panic(err)
	}

	// Check headers are as expected
	if records[0][0] != "Day" {
		panic("Column header Day not found")
	}
	if records[0][1] != "Price" {
		panic("Column header Price not found")
	}

	// Loop data rows to populate bitcoinData struct
	bitcoinData := []TimeSeries{} // golang dynamic slice
	var priceString string
	var priceFloat float64
	for i, row := range records {
		if i == 0 { // Skip header row
			continue
		}

		// Transform price string into float (it has a "," for thousands)
		priceString = strings.ReplaceAll(row[1], ",", "") // Remove the "," for thousands
		priceFloat, err = strconv.ParseFloat(priceString, 32)
		if err == nil {
			// fmt.Println("Parsing done...")
			// fmt.Printf("%T, %v\n", priceFloat, priceFloat)
		} else {
			fmt.Println("Parsing failed...")
			fmt.Printf("Error:%v\n", err)
		}

		// Using append to increase the golang dynamic slice
		bitcoinData = append(bitcoinData, TimeSeries{row[0], float32(priceFloat)})

		// Output time series on screen
		fmt.Print("\n", bitcoinData[len(bitcoinData)-1].Day, " ", bitcoinData[len(bitcoinData)-1].Price)
	}
}