我是LINQ的新手,但我想知道是否可以使用LINQ来转移以下布局中的数据:
CustID | OrderDate | Qty
1 | 1/1/2008 | 100
2 | 1/2/2008 | 200
1 | 2/2/2008 | 350
2 | 2/28/2008 | 221
1 | 3/12/2008 | 250
2 | 3/15/2008 | 2150
这样的事情:
CustID | Jan- 2008 | Feb- 2008 | Mar - 2008 |
1 | 100 | 350 | 250
2 | 200 | 221 | 2150
答案 0 :(得分:180)
这样的东西?
List<CustData> myList = GetCustData();
var query = myList
.GroupBy(c => c.CustId)
.Select(g => new {
CustId = g.Key,
Jan = g.Where(c => c.OrderDate.Month == 1).Sum(c => c.Qty),
Feb = g.Where(c => c.OrderDate.Month == 2).Sum(c => c.Qty),
March = g.Where(c => c.OrderDate.Month == 3).Sum(c => c.Qty)
});
Linq中的 GroupBy
与SQL的工作方式不同。在SQL中,您获得密钥和聚合(行/列形状)。在Linq中,您可以获得键和任何元素作为键的子元素(层次结构形状)。要进行透视,您必须将层次结构投影回您选择的行/列形式。
答案 1 :(得分:12)
我使用linq扩展方法回答similar question:
// order s(ource) by OrderDate to have proper column ordering
var r = s.Pivot3(e => e.custID, e => e.OrderDate.ToString("MMM-yyyy")
, lst => lst.Sum(e => e.Qty));
// order r(esult) by CustID
(+)通用实施
( - )肯定比大卫B的慢
任何人都可以改进我的实现(即该方法是否对列和行进行排序)?
答案 2 :(得分:6)
我认为最好的方法是使用查找:
var query =
from c in myList
group c by c.CustId into gcs
let lookup = gcs.ToLookup(y => y.OrderDate.Month, y => y.Qty)
select new
{
CustId = gcs.Key,
Jan = lookup[1].Sum(),
Feb = lookup[2].Sum(),
Mar = lookup[3].Sum(),
};
答案 3 :(得分:2)
以下是使用LINQ如何转换数据的更通用的方法:
IEnumerable<CustData> s;
var groupedData = s.ToLookup(
k => new ValueKey(
k.CustID, // 1st dimension
String.Format("{0}-{1}", k.OrderDate.Month, k.OrderDate.Year // 2nd dimension
) ) );
var rowKeys = groupedData.Select(g => (int)g.Key.DimKeys[0]).Distinct().OrderBy(k=>k);
var columnKeys = groupedData.Select(g => (string)g.Key.DimKeys[1]).Distinct().OrderBy(k=>k);
foreach (var row in rowKeys) {
Console.Write("CustID {0}: ", row);
foreach (var column in columnKeys) {
Console.Write("{0:####} ", groupedData[new ValueKey(row,column)].Sum(r=>r.Qty) );
}
Console.WriteLine();
}
其中ValueKey是一个表示多维键的特殊类:
public sealed class ValueKey {
public readonly object[] DimKeys;
public ValueKey(params object[] dimKeys) {
DimKeys = dimKeys;
}
public override int GetHashCode() {
if (DimKeys==null) return 0;
int hashCode = DimKeys.Length;
for (int i = 0; i < DimKeys.Length; i++) {
hashCode ^= DimKeys[i].GetHashCode();
}
return hashCode;
}
public override bool Equals(object obj) {
if ( obj==null || !(obj is ValueKey))
return false;
var x = DimKeys;
var y = ((ValueKey)obj).DimKeys;
if (ReferenceEquals(x,y))
return true;
if (x.Length!=y.Length)
return false;
for (int i = 0; i < x.Length; i++) {
if (!x[i].Equals(y[i]))
return false;
}
return true;
}
}
此方法可用于按N维(n> 2)进行分组,并且对于相当小的数据集可以正常工作。对于大型数据集(最多1百万条记录等)或者对于无法硬编码数据透视配置的情况,我编写了特殊的PivotData库(它是免费的):
var pvtData = new PivotData(new []{"CustID","OrderDate"}, new SumAggregatorFactory("Qty"));
pvtData.ProcessData(s, (o, f) => {
var custData = (TT)o;
switch (f) {
case "CustID": return custData.CustID;
case "OrderDate":
return String.Format("{0}-{1}", custData.OrderDate.Month, custData.OrderDate.Year);
case "Qty": return custData.Qty;
}
return null;
} );
Console.WriteLine( pvtData[1, "1-2008"].Value );
答案 4 :(得分:2)
这是最有效的方法:
检查以下方法。而不是每个月每次都遍历客户组。
var query = myList
.GroupBy(c => c.CustId)
.Select(g => {
var results = new CustomerStatistics();
foreach (var customer in g)
{
switch (customer.OrderDate.Month)
{
case 1:
results.Jan += customer.Qty;
break;
case 2:
results.Feb += customer.Qty;
break;
case 3:
results.March += customer.Qty;
break;
default:
break;
}
}
return new
{
CustId = g.Key,
results.Jan,
results.Feb,
results.March
};
});
或者这个:
var query = myList
.GroupBy(c => c.CustId)
.Select(g => {
var results = g.Aggregate(new CustomerStatistics(), (result, customer) => result.Accumulate(customer), customerStatistics => customerStatistics.Compute());
return new
{
CustId = g.Key,
results.Jan,
results.Feb,
results.March
};
});
完整的解决方案:
using System;
using System.Collections.Generic;
using System.Linq;
namespace ConsoleApp
{
internal class Program
{
private static void Main(string[] args)
{
IEnumerable<CustData> myList = GetCustData().Take(100);
var query = myList
.GroupBy(c => c.CustId)
.Select(g =>
{
CustomerStatistics results = g.Aggregate(new CustomerStatistics(), (result, customer) => result.Accumulate(customer), customerStatistics => customerStatistics.Compute());
return new
{
CustId = g.Key,
results.Jan,
results.Feb,
results.March
};
});
Console.ReadKey();
}
private static IEnumerable<CustData> GetCustData()
{
Random random = new Random();
int custId = 0;
while (true)
{
custId++;
yield return new CustData { CustId = custId, OrderDate = new DateTime(2018, random.Next(1, 4), 1), Qty = random.Next(1, 50) };
}
}
}
public class CustData
{
public int CustId { get; set; }
public DateTime OrderDate { get; set; }
public int Qty { get; set; }
}
public class CustomerStatistics
{
public int Jan { get; set; }
public int Feb { get; set; }
public int March { get; set; }
internal CustomerStatistics Accumulate(CustData customer)
{
switch (customer.OrderDate.Month)
{
case 1:
Jan += customer.Qty;
break;
case 2:
Feb += customer.Qty;
break;
case 3:
March += customer.Qty;
break;
default:
break;
}
return this;
}
public CustomerStatistics Compute()
{
return this;
}
}
}
答案 5 :(得分:-4)
按月对数据进行分组,然后将其投影到每个月包含列的新数据表中。新表将是您的数据透视表。