数据集SQL的预处理

发布于 2025-01-01 17:53:26 字数 752 浏览 0 评论 0原文

我有一个包含 100 行和 2001 个属性的数据集的平面文件,如下所示:

att1,att2,att4,att5,att6,att7,att8,att9,att10,....,att2000,type
5,3,4,4,1,5,1,3,2,4,...,12,Agresti
4,4,2,0,1,0,2,0,0,0,...,22,bbresti
0,0,0,0,0,0,0,0,1,0,...,34,bbresti
0,0,0,1,0,0,0,1,1,1,...,45,Agresti
...
0,6,0,0,0,0,1,0,3.5,...,1,Agresti

我想将此数据预处理为

i,j,val
1,1,5
1,2,4
1,3,0
1,4,0
...
1,100,0
2,1,3
2,2,4
2,3,0
2,4,0
...
2,100,6
3,1,4
3,2,2
3,3,0
3,4,0
...
...
2000,100,1

所以我摆脱了最后一个列类型,我知道在 sql 中我会做类似的事情:

CREATE TABLE matrix (Row int NOT NULL, Column int NOT NULL, Value <datatype> NOT NULL)

SELECT Row AS Column
       ,Column AS Row
       ,Value
FROM matrix

但是当我只想在 SQL 中导入表,但是 C# 中的代码是什么样的

I have a flat file of a dataset with 100 rows and 2001 attributes like this:

att1,att2,att4,att5,att6,att7,att8,att9,att10,....,att2000,type
5,3,4,4,1,5,1,3,2,4,...,12,Agresti
4,4,2,0,1,0,2,0,0,0,...,22,bbresti
0,0,0,0,0,0,0,0,1,0,...,34,bbresti
0,0,0,1,0,0,0,1,1,1,...,45,Agresti
...
0,6,0,0,0,0,1,0,3.5,...,1,Agresti

And I would like to preprocess this data as

i,j,val
1,1,5
1,2,4
1,3,0
1,4,0
...
1,100,0
2,1,3
2,2,4
2,3,0
2,4,0
...
2,100,6
3,1,4
3,2,2
3,3,0
3,4,0
...
...
2000,100,1

So i get rid of the last column type, I kmow that in sql I would do something like:

CREATE TABLE matrix (Row int NOT NULL, Column int NOT NULL, Value <datatype> NOT NULL)

SELECT Row AS Column
       ,Column AS Row
       ,Value
FROM matrix

But as I would like to just import the table in SQL, but How does the code look like in c#

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别忘他 2025-01-08 17:53:26

下面是一些 C# 的想法,它将获取您的输入文件并重新格式化您所请求的格式。然后使用 SqlBulkCopy 类将数据推送到 SQLServer 中的表中。

希望有帮助。

using System.IO;

namespace ConsoleApplication1
{
     class Program
     {
          static void Main(string[] args)
          {
                string[] parts;
                //string[] lines = System.IO.File.ReadAllLines(@"somefile.csv");
                string[] lines = new string[] { 
                     "a1,a2,a3,a4,type", 
                     "22,33,44,55,t1", 
                     "222,333,444,555,t2", 
                     "2222,3333,4444,5555,t3" };
                int lineno = 1;

                string path = @"c:\output.csv";
                using (TextWriter writer = File.CreateText(path))
                {
                     foreach (string line in lines)
                     {
                          if (lineno > 1)
                          {
                                parts = line.Split(',');
                                for (int a = 0; a < parts.Length - 1; a++)
                                     writer.WriteLine(lineno.ToString() + "," + (a+1).ToString() + "," + parts[a]);
                          }
                          lineno++;
                     }
                }
          }
     }
}

Here's an idea of some C# that will take your input file and reformat you're requesting. Then use the SqlBulkCopy class to push your data up into a table in SQLServer.

Hope it helps.

using System.IO;

namespace ConsoleApplication1
{
     class Program
     {
          static void Main(string[] args)
          {
                string[] parts;
                //string[] lines = System.IO.File.ReadAllLines(@"somefile.csv");
                string[] lines = new string[] { 
                     "a1,a2,a3,a4,type", 
                     "22,33,44,55,t1", 
                     "222,333,444,555,t2", 
                     "2222,3333,4444,5555,t3" };
                int lineno = 1;

                string path = @"c:\output.csv";
                using (TextWriter writer = File.CreateText(path))
                {
                     foreach (string line in lines)
                     {
                          if (lineno > 1)
                          {
                                parts = line.Split(',');
                                for (int a = 0; a < parts.Length - 1; a++)
                                     writer.WriteLine(lineno.ToString() + "," + (a+1).ToString() + "," + parts[a]);
                          }
                          lineno++;
                     }
                }
          }
     }
}
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