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使用 strconv 将 csv 数据（[]string）转换为 float64，然后对数据求和

慕神8447489 2022-08-01 15:35:08

我正在尝试从我从上一个函数创建的CSV文件中的数据进行汇总。下面是该文件的一个片段：datetime,open,high,low,close,volume2020-11-09 00:00,69.58,137.45,69.00,100.00,273517274.002020-11-10 00:00,104.65,128.80,101.75,107.00,141284399.002020-11-11 00:00,109.00,114.45,96.76,98.42,96648953.002020-11-12 00:00,95.98,106.60,89.15,90.00,149794913.00[对于上下文：这是雅虎财经的劳斯莱斯控股股价的历史价格数据。我计划使用最多 200 行]。我面临的问题是将数据从CSV转换为float64。该函数正在尝试转换我的标题，显然不能，因为它是“无效语法”。下面是错误代码：[]stringParseFloat()Error converting string: strconv.ParseFloat: parsing "open": invalid syntaxError converting string: strconv.ParseFloat: parsing "high": invalid syntaxError converting string: strconv.ParseFloat: parsing "low": invalid syntaxError converting string: strconv.ParseFloat: parsing "close": invalid syntaxError converting string: strconv.ParseFloat: parsing "volume": invalid syntax&{ 0 0 0 0 0}我的代码如下，以供参考：package mainimport ( "encoding/csv" "fmt" "log" "os" "strconv")const file = "./rr.csv"// Data struct is the data from the csv filetype Data struct { datetime string open float64 high float64 low float64 close float64 volume float64}func readAmounts(r []string) (d *Data, err error) { d = new(Data) open := r[1] d.open, err = strconv.ParseFloat(open, 64) if err != nil { fmt.Printf("Error converting string: %v", err) } high := r[2] d.high, err = strconv.ParseFloat(high, 64) if err != nil { fmt.Printf("Error converting string: %v", err) } low := r[3] d.low, err = strconv.ParseFloat(low, 64) if err != nil { fmt.Printf("Error converting string: %v", err) } close := r[4] d.close, err = strconv.ParseFloat(close, 64) if err != nil { fmt.Printf("Error converting string: %v", err) }我只是打印数据以查看ParseFloat（）是否有效，然后我将创建一个函数来对列求和。所以，我要问的是;我如何忽略标题行，只是通读数字行。仅供参考：我读过其他答案（例如：FieldsPerRecord），但它们没有为我的具体问题工作，因为我随后试图对整个列进行求和。

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3 回答

紫衣仙女

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一些不同的选项：

跳过解析第一行。这假设每个文件都以标头开头。
跳过存在解析错误的行。最简单的方法，但在出现问题时很难调试。
如果第一行有解析错误，请跳过它，因为它可能是标题行。

另外，您应该在代码中正确处理错误，而您当前没有这样做。

反对回复 2022-08-01

慕田峪4524236

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我已经注释掉了程序，所以很容易理解。基本思想是忽略标头。此外，当您编制索引并获取记录的字段时;最好检查记录中存在的字段数（）。FieldsPerRecord

package main

import (

"encoding/csv"

"errors"

"fmt"

"io"

"log"

"os"

"strconv"

)

// file stores the filepath

const file = "./rr.csv"

// Data store metadata

type Data struct {

datetime string

open float64

high float64

low float64

close float64

volume float64

}

// s2f converts string to float64

func s2f(str string) (float64, error) {

f, err := strconv.ParseFloat(str, 64)

if err != nil {

return 0, fmt.Errorf("Error converting string \"%v\" to float", err)

}

return f, nil

}

// ReadAmounts processes the fields from the record and stores them in Data

func ReadAmounts(r []string) (*Data, error) {

var (

dt = r[0]

open = r[1]

high = r[2]

low = r[3]

close = r[4]

volume = r[5]

d = new(Data)

err error

)

d.datetime = dt

d.open, err = s2f(open)

if err != nil {

return nil, err

}

d.high, err = s2f(high)

if err != nil {

return nil, err

}

d.low, err = s2f(low)

if err != nil {

return nil, err

}

d.close, err = s2f(close)

if err != nil {

return nil, err

}

d.volume, err = s2f(volume)

if err != nil {

return nil, err

}

return d, nil

}

func main() {

// Open the file

file, err := os.Open(file)

if err != nil {

log.Fatalln(err)

}

// CSV Reader

r := csv.NewReader(file)

// Set Options for the reader

{

r.Comma = ',' // Delimiter

r.TrimLeadingSpace = true // Trim the leading spaces

r.FieldsPerRecord = 0 // Rows should have same number of columns as header

r.ReuseRecord = true // Reuse the same backing array (Efficient)

}

// Alternatively, r.ReadAll() could be also used and slicing it using [1:] ignores

// the header as well.

// Ignore header

_, _ = r.Read()

for {

// Read record (one by one)

record, err := r.Read()

if err != nil {

// Exit out. Done!

if errors.Is(err, io.EOF) {

break

}

// Log and continue

log.Printf("Error reading record: %v\n", err)

continue

}

// Process

data, err := ReadAmounts(record)

if err != nil {

// Log and continue

fmt.Printf("Error reading record: %v\n", err)

continue

}

// Print the filled Data struct

fmt.Printf("Record: %+v\n", *data)

}

输出：

Record: {datetime:2020-11-09 00:00 open:69.58 high:137.45 low:69 close:100 volume:2.73517274e+08}

Record: {datetime:2020-11-10 00:00 open:104.65 high:128.8 low:101.75 close:107 volume:1.41284399e+08}

Record: {datetime:2020-11-11 00:00 open:109 high:114.45 low:96.76 close:98.42 volume:9.6648953e+07}

Record: {datetime:2020-11-12 00:00 open:95.98 high:106.6 low:89.15 close:90 volume:1.49794913e+08}

反对回复 2022-08-01

婷婷同学_

TA贡献1844条经验获得超8个赞

您可以将文件加载到 CSV 中，然后逐行处理该文件：

package main

import (

"bytes"

"encoding/csv"

"fmt"

"io/ioutil"

"strconv"

)

const file = "./data.csv"

// Data struct is the data from the csv file

type Data struct {

datetime string

open float64

high float64

low float64

close float64

volume float64

}

func main() {

f, err := ioutil.ReadFile(file)

if err != nil {

panic(err)

}

rawData, err := readCsv(f, ',')

if err != nil {

panic(err)

}

amounts, err := readAmounts(rawData[1:])

if err != nil {

panic(err)

}

fmt.Printf("%+v\n", amounts)

}

func readAmounts(r [][]string) ([]Data, error) {

var d []Data = make([]Data, len(r))

var err error

for i, row := range r {

d[i].datetime = row[0]

if err != nil {