r-Java将二维数组信息转换为sumarization的关键

Question

我有一组从hadoop中提取的数据作为

1234567 ask     13
1234567 death   2
1234567 freek   15
1234567 hurt    2
1234567 pain    10
9999999 death   15
9999999 frerik  14
9999999 hurt    1
9999999 lisa    2
9999999 pain    12

我需要将其转换为的数据帧

        death   freek   frerik  hurt    lisa    pain
1234567    2    15      0        2      0       10
9999999   15    0       14       1      2       12

我应该用什么最好的方法。

Answer 1

另一种选择是使用library(reshape2)（使用@Richard Scriven帖子中的示例df）

  library(reshape2) 
  as.data.frame(acast(df, V1~V2, value.var="V3", fill=0))
  #       ask death freek frerik hurt lisa pain
  #1234567  13     2    15      0    2    0   10
  #9999999   0    15     0     14    1    2   12

或使用tidyr

  library(dplyr)
  library(tidyr)
  df %>% 
      spread(V2, V3, fill=0)
  #       V1 ask death freek frerik hurt lisa pain
  #1 1234567  13     2    15      0    2    0   10
  #2 9999999   0    15     0     14    1    2   12

Answer 2

我通过实现ARRAYLIST来存储A&B，并将它们复制到形成标题行和1列的2D矩阵中；B…

让我知道是否有更好的方式代码低于

CSVReader reader=null；

     try {  reader = new CSVReader(new FileReader(args[0]));
                } catch (FileNotFoundException e) { e.printStackTrace();
                }
     String [] field_name;
     ArrayList<String> listRows = new ArrayList<String>();
     ArrayList<String> listCols = new ArrayList<String>();
     ArrayList<String> report = new ArrayList<String>();
     try {

        String hold_var = new String();
        String hold_var2 = new String();
            while ((field_name = reader.readNext()) != null) 
            {  

                        if(!hold_var.equals(field_name[0]))
                        {
                            listRows.add(field_name[0]);
                            report.add(field_name[2]);
                            // stores from 0
                        }
                        hold_var = field_name[0];

                        if(!hold_var2.equals(field_name[1]))
                        {
                            listCols.add(field_name[1]);
                        }
                        hold_var2 = field_name[1];
            }
        reader.close();     
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }
    String[][] table = new String[listRows.size()+1][listCols.size()+2];
    table[0][0] = new String(" ");
    int i=0; 
    for ( String str: listRows)
    {
        table[++i][0]= str ;
    }
    i=0;
    for ( String str: report)
    {
        table[++i][1]= str ;
    }
    table[0][1]="report";
    // leaving the first column to fill the fda codes
    for (int cols=2;cols<=listCols.size();cols++)
    {
        table[0][cols] = listCols.get(cols-2);   // we need to traverse from 0
    }

     try {  reader = new CSVReader(new FileReader(args[0]));
        } catch (FileNotFoundException e) { e.printStackTrace();
        }

    try {
            while ((field_name = reader.readNext()) != null) 
            {  

                for ( int rows=0;rows<listRows.size();rows++)
                {
                    if (!field_name[0].equals(table[rows+1][0]))                            
                        continue;     
                    for (int cols=0;cols<listCols.size();cols++)
                    {
                        if(!field_name[1].equals(table[0][cols+2]))
                            continue;
                        table[rows+1][cols+2]=field_name[3].trim();             
                    }
                }
            }
            reader.close();     
    } catch (IOException e) {
        // TODO Auto-generated catch block
        e.printStackTrace();
    }
     PrintWriter pout = null;
     try {
            pout = new PrintWriter(args[1]);
        } catch (FileNotFoundException e1) {
            // TODO Auto-generated catch block
            e1.printStackTrace();
        }

    for ( int rows=0;rows<listRows.size()+1;rows++)
    {
        for (int cols=0;cols<listCols.size()+1;cols++)
        {
            if(table[rows][cols] == null)
            {
                table[rows][cols]=new String("0");
            }

            // writing to a csv file.
            pout.write(table[rows][cols] +",");
        }
        pout.write("n");
        pout.flush();
    }
    System.out.print("done");
}
}