在datagridview c#中读取两个文本文件并连接列

我假设你已经有了这些类，或者你将创建

public class Data1
{
    public string Campionato { get; set; }
    public string Data { get; set; }
    public string Home { get; set; }
    public string Away { get; set; }
    public int HSFT { get; set; }
    public int ASFT { get; set; }
    public int HSHT { get; set; }
    public int HSHT2 { get; set; }
}
public class Data2 //you can use inheritance and reduce duplication of properties
{
    public string Data { get; set; }
    public string Home { get; set; }
    public string Away { get; set; }
    public double HODD { get; set; }
    public double AODD { get; set; }
    public double XODD { get; set; } //no name in sample
}
public class CombinedData //you can use inheritance here too
{
    public string Campionato { get; set; }
    public string Data { get; set; }
    public string Home { get; set; }
    public string Away { get; set; }
    public int HSFT { get; set; }
    public int ASFT { get; set; }
    public int HSHT { get; set; }
    public int HSHT2 { get; set; }
    public double HODD { get; set; }
    public double AODD { get; set; }
    public double XODD { get; set; } //some name
}

你可以像这样读取原始数据

var data1 = File.ReadAllLines(@"C:'YourFolder'Data1.txt").ToList();
data1.RemoveAt(0); //reamoving the header
var data2 = File.ReadAllLines(@"C:'YourFolder'Data2.txt").ToList();
data2.RemoveAt(0); //reamoving the header

现在将它们映射到正确的(键入的)数据列表

var dataList1 = new List<Data1>();
foreach(var data in data1)
{
    var columns = data.Split(';'); //add data validations
    dataList1.Add(new Data1
    {
        Campionato = columns[0],
        Data = columns[1],
        Home = columns[2],
        //other string properties
        HSFT = int.Parse(columns[4])
        //other int properties
    });
}
var dataList2 = new List<Data2>();
foreach (var data in data2)
{
    var columns = data.Split(';'); //add data validations
    dataList2.Add(new Data2
    {
        Data = columns[0],
        Home = columns[1],
        //other string properties
        HODD = double.Parse(columns[3])
        //other double properties
    });
}

现在你可以加入它们并绑定到你的网格中。

注意:这是对Data列的连接，这将导致总共5行。

var combinedDataList = from d1 in dataList1 //Joining on Data here, use the key you have
                        join d2 in dataList2 on d1.Data equals d2.Data
                        select new CombinedData { Campionato = d1.Campionato, 
                                                    Data = d1.Data, 
                                                    HSFT = d1.HSFT, 
                                                    HODD = d2.HODD }; //map all properties
yourDataGrid.DataSource = combinedDataList; //check syntax here, not tested
yourDataGrid.Bind();

如果你想连接多个列(例如Data &Home)，使用以下语法

var combinedDataList = from d1 in dataList1 //Joining on Data & Home, yields 3 rows
                        join d2 in dataList2 on new { d1.Data, d1.Home } equals new { d2.Data, d2.Home }
                        select new CombinedData
                        {
                            Campionato = d1.Campionato,
                            Data = d1.Data,
                            HSFT = d1.HSFT,
                            HODD = d2.HODD //map rest of the properties
                        };

数据类如下:

public class MyData
{
    public String Campionato { get; set; }
    public DateTime Data { get; set; }
    public String Home { get; set; }
    public String Away { get; set; }
    public int Hsft { get; set; }
    public int Asft { get; set; }
    public int Hsht { get; set; }
    public int Hsht_2 { get; set; }
    public float Hodd { get; set; }
    public float Aodd { get; set; }
    public float Unknown { get; set; }
}

这里是读取文件和连接数据的代码:

var file1Data = File.ReadLines(@"File1.csv")
                    .Skip(1) // Skip header
                    .Select(line => line.Split(';'))
                    .Select(elements => new MyData
                    {
                        Campionato = elements[0],
                        Data = DateTime.ParseExact(elements[1], "MM'.'dd'.'yyyy", CultureInfo.InvariantCulture),
                        Home = elements[2],
                        Away = elements[3],
                        Hsft = Int32.Parse(elements[4]),
                        Asft = Int32.Parse(elements[5]),
                        Hsht = Int32.Parse(elements[6]),
                        Hsht_2 = Int32.Parse(elements[7])
                    });
var file2Data = File.ReadLines(@"File2.csv")
                    .Skip(1) // Skip header
                    .Select(line => line.Split(';'))
                    .Select(elements => new MyData
                    {
                        Data = DateTime.ParseExact(elements[0], "MM'.'dd'.'yyyy", CultureInfo.InvariantCulture),
                        Home = elements[1],
                        Away = elements[2],
                        Hodd = float.Parse(elements[3]),
                        Aodd = float.Parse(elements[4])
                    });
var joinedData = file1Data.Join(
                        file2Data,
                        // Key generation should be optimized. Maybe take a look at http://stackoverflow.com/q/263400/1838048
                        myData => myData.Data.GetHashCode() + myData.Home.GetHashCode() + myData.Away.GetHashCode(),
                        myData => myData.Data.GetHashCode() + myData.Home.GetHashCode() + myData.Away.GetHashCode(),
                        (file1, file2) => new MyData
                        {
                            Campionato = file1.Campionato,
                            Data = file1.Data,
                            Home = file1.Home,
                            Away = file1.Away,
                            Hsft = file1.Hsft,
                            Asft = file1.Asft,
                            Hsht = file1.Hsht,
                            Hsht_2 = file1.Hsht_2,
                            Hodd = file2.Hodd,
                            Aodd = file2.Aodd,
                            Unknown = file2.Unknown
                        });

myDataGridView.DataSource = joinedData.ToList();

有很多硬编码的东西，没有任何类型的错误检查。所以对你自己有很大的改进，但它应该给你一个很好的起点。