使用Java从文本文件中逐列提取数据 [英] extract data column-wise from text file using Java

问题描述

我在Java下工作并希望根据文本文件中的列提取数据。

myfile.txt内容：

I'm working under Java and want to extract data according to column from a text file.
"myfile.txt" contents:

    ID     SALARY RANK  
    065    12000   1
    023    15000   2
    035    25000   3
    076    40000   4

我想根据任何列分别提取数据，即ID，SALARY，RANK等


基本上我想要执行根据列对单个数据进行操作。

I want to extract the data individually according to any Column i.e ID, SALARY, RANK etc
Basically I want to perform operations on individual data according to columns.

我通过使用while循环并逐行读取来列出myfile.txt中的数据：

I've listed the data from "myfile.txt" by using while loop and reading line-by-line:

    while((line = b.readLine()) != null) {
          stringBuff.append(line + "\n");
       }

link：将选择性列数据从文本文件读入Java列表

在bove链接下，编写使用以下内容：
String [] columns = line.split（）;

Under bove link it is written to use the following: String[] columns = line.split(" ");

但如何正确使用它，请提供任何提示或帮助？

But how to use it correctly, please any hint or help?

推荐答案

您可以使用正则表达式来检测更长的空格，例如：

You can use a regex to detect longer spaces, example:

String text = "ID     SALARY RANK\n" +  
            "065    12000   1\n" +
            "023    15000   2\n" +
            "035    25000   3\n" +
            "076    40000   4\n";

Scanner scanner = new Scanner(text);

//reading the first line, always have header
//I suppose
String nextLine = scanner.nextLine();
//regex to break on any ammount of spaces
String regex = "(\\s)+";


String[] header = nextLine.split(regex);

//this is printing all columns, you can 
//access each column from row using the array
//indexes, example header[0], header[1], header[2]...
System.out.println(Arrays.toString(header));

//reading the rows
while (scanner.hasNext()) {
    String[] row = scanner.nextLine().split(regex);

    //this is printing all columns, you can 
    //access each column from row using the array
    //indexes, example row[0], row[1], row[2]...
    System.out.println(Arrays.toString(row));
    System.out.println(row[0]);//first column (ID)
}

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