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List,DataTable实现行转列的通用方案

2017-03-02 08:29 169 查看
　　最近在做报表统计方面的需求，涉及到行转列报表。根据以往经验使用SQL可以比较容易完成，这次决定挑战一下直接通过代码方式完成行转列。期间遇到几个问题和用到的新知识这里整理记录一下。

阅读目录

问题介绍

动态Linq

System.Linq.Dynamic其它用法

DataTable行转列

总结

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问题介绍

　　以家庭月度费用为例，可以在[Name,Area,Month]三个维度上随意组合进行分组，三个维度中选择一个做为列显示。

/// <summary>
/// 家庭费用情况
/// </summary>
public class House
{
/// <summary>
/// 户主姓名
/// </summary>
public string Name { get; set; }

/// <summary>
/// 所属行政区域
/// </summary>
public string Area { get; set; }

/// <summary>
/// 月份
/// </summary>
public string Month { get; set; }

/// <summary>
/// 电费金额
/// </summary>
public double DfMoney { get; set; }

/// <summary>
/// 水费金额
/// </summary>
public double SfMoney { get; set; }

/// <summary>
/// 燃气金额
/// </summary>
public double RqfMoney { get; set; }
}


户主-月明细报表
户主姓名2016-012016-02
电费水费燃气费电费水费燃气费
张三240.9302516724.517.9
李四56.724.713.265.218.914.9
区域-月明细报表
区域2016-012016-02
电费水费燃气费电费水费燃气费
江夏区2240.93304255167264.5177.9
洪山区576.7264.7173.2665.2108.9184.9
区域月份-户明细报表
区域月份张三李四
燃气费电费水费燃气费电费水费
江夏区2016-012240.93304255167264.5177.9
洪山区2016-01576.7264.7173.2665.2108.9184.9
江夏区2016-023240.94305256167364.5277.9
洪山区2016-02676.7364.7273.2765.2208.9284.9
现在后台查出来的数据是List<House>类型，前台传过来分组维度和动态列字段。
第1个表格前台传给后台参数

{DimensionList:['Name'],DynamicColumn:'Month'}


第2个表格前台传给后台参数

{DimensionList:['Area'],DynamicColumn:'Month'}


第3个表格前台传给后台参数

{DimensionList:['Area','Month'],DynamicColumn:'Name'}


问题描述清楚后，仔细分析后你就会发现这里的难题在于动态分组，也就是怎么根据前台传过来的多个维度对List进行分组。
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动态Linq

下面使用System.Linq.Dynamic完成行转列功能，Nuget上搜索System.Linq.Dynamic即可下载该包。

代码进行了封装，实现了通用的List<T>行转列功能。

/// <summary>
/// 动态Linq方式实现行转列
/// </summary>
/// <param name="list">数据</param>
/// <param name="DimensionList">维度列</param>
/// <param name="DynamicColumn">动态列</param>
/// <returns>行转列后数据</returns>
private static List<dynamic> DynamicLinq<T>(List<T> list, List<string> DimensionList, string DynamicColumn, out List<string> AllDynamicColumn) where T : class
{
//获取所有动态列
    var columnGroup = list.GroupBy(DynamicColumn, "new(it as Vm)") as IEnumerable<IGrouping<dynamic, dynamic>>;
List<string> AllColumnList = new List<string>();
foreach (var item in columnGroup)
{
if (!string.IsNullOrEmpty(item.Key))
{
AllColumnList.Add(item.Key);
}
}
AllDynamicColumn = AllColumnList;
var dictFunc = new Dictionary<string, Func<T, bool>>();
foreach (var column in AllColumnList)
{
var func = DynamicExpression.ParseLambda<T, bool>(string.Format("{0}==\"{1}\"", DynamicColumn, column)).Compile();
dictFunc[column] = func;
}

//获取实体所有属性
Dictionary<string, PropertyInfo> PropertyInfoDict = new Dictionary<string, PropertyInfo>();
Type type = typeof(T);
var propertyInfos = type.GetProperties(BindingFlags.Instance | BindingFlags.Public);
//数值列
List<string> AllNumberField = new List<string>();
foreach (var item in propertyInfos)
{
PropertyInfoDict[item.Name] = item;
if (item.PropertyType == typeof(int) || item.PropertyType == typeof(double) || item.PropertyType == typeof(float))
{
AllNumberField.Add(item.Name);
}
}

//分组
    var dataGroup = list.GroupBy(string.Format("new ({0})", string.Join(",", DimensionList)), "new(it as Vm)") as IEnumerable<IGrouping<dynamic, dynamic>>;
List<dynamic> listResult = new List<dynamic>();
IDictionary<string, object> itemObj = null;
T vm2 = default(T);
foreach (var group in dataGroup)
{
itemObj = new ExpandoObject();
var listVm = group.Select(e => e.Vm as T).ToList();
//维度列赋值
vm2 = listVm.FirstOrDefault();
foreach (var key in DimensionList)
{
itemObj[key] = PropertyInfoDict[key].GetValue(vm2);
}

foreach (var column in AllColumnList)
{
vm2 = listVm.FirstOrDefault(dictFunc[column]);
if (vm2 != null)
{
foreach (string name in AllNumberField)
{
itemObj[name + column] = PropertyInfoDict[name].GetValue(vm2);
}
}
}
listResult.Add(itemObj);
}
return listResult;
}




标红部分使用了System.Linq.Dynamic动态分组功能，传入字符串即可分组。使用了dynamic类型，关于dynamic介绍可以参考其它文章介绍哦。

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System.Linq.Dynamic其它用法

上面行转列代码见识了System.Linq.Dynamic的强大，下面再介绍一下会在开发中用到的方法。

Where过滤

list.Where("Name=@0", "张三")




上面用到了参数化查询，实现了查找姓名是张三的数据，通过这段代码你或许感受不到它的好处。但是和EntityFramework结合起来就可以实现动态拼接SQL的功能了。

/// <summary>
/// EF实体查询封装
/// </summary>
/// <typeparam name="T">实体类型</typeparam>
/// <param name="Query">IQueryable对象</param>
/// <param name="gridParam">过滤条件</param>
/// <returns>查询结果</returns>
public static EFPaginationResult<T> PageQuery<T>(this IQueryable<T> Query, QueryCondition gridParam)
{
//查询条件
EFFilter filter = GetParameterSQL<T>(gridParam);
var query = Query.Where(filter.Filter, filter.ListArgs.ToArray());
//查询结果
EFPaginationResult<T> result = new EFPaginationResult<T>();
if (gridParam.IsPagination)
{
int PageSize = gridParam.PageSize;
int PageIndex = gridParam.PageIndex < 0 ? 0 : gridParam.PageIndex;
//获取排序信息
string sort = GetSort(gridParam, typeof(T).FullName);
result.Data = query.OrderBy(sort).Skip(PageIndex * PageSize).Take(PageSize).ToList<T>();
if (gridParam.IsCalcTotal)
{
result.Total = query.Count();
result.TotalPage = Convert.ToInt32(Math.Ceiling(result.Total * 1.0 / PageSize));
}
else
{
result.Total = result.Data.Count();
}
}
else
{
result.Data = query.ToList();
result.Total = result.Data.Count();
}
return result;
}


/// <summary>
/// 通过查询条件,获取参数化查询SQL
/// </summary>
/// <param name="gridParam">过滤条件</param>
/// <returns>过滤条件字符</returns>
private static EFFilter GetParameterSQL<T>(QueryCondition gridParam)
{
EFFilter result = new EFFilter();
//参数值集合
List<object> listArgs = new List<object>();
string filter = "1=1";

#region "处理动态过滤条件"
if (gridParam.FilterList != null && gridParam.FilterList.Count > 0)
{
StringBuilder sb = new StringBuilder();

int paramCount = 0;
DateTime dateTime;
//操作符
string strOperator = string.Empty;
foreach (var item in gridParam.FilterList)
{
//字段名称为空则跳过
if (string.IsNullOrEmpty(item.FieldName))
{
continue;
}
//匹配枚举，防止SQL注入
Operator operatorEnum = (Operator)Enum.Parse(typeof(Operator), item.Operator, true);

//跳过字段值为空的
if (operatorEnum != Operator.Null && operatorEnum != Operator.NotNull && string.IsNullOrEmpty(item.FieldValue))
{
continue;
}
strOperator = operatorEnum.GetDescription();
if (item.IgnoreCase && !item.IsDateTime)
{
//2016-07-19添加查询时忽略大小写比较
item.FieldValue = item.FieldValue.ToLower();
item.FieldName = string.Format("{0}.ToLower()", item.FieldName);
}
switch (operatorEnum)
{
//等于,不等于，小于，大于，小于等于，大于等于
case Operator.EQ:
case Operator.NE:
case Operator.GT:
case Operator.GE:
case Operator.LT:
case Operator.LE:
if (item.IsDateTime)
{
if (DateTime.TryParse(item.FieldValue, out dateTime))
{
if (!item.FieldValue.Contains("00:00:00") && dateTime.ToString("HH:mm:ss") == "00:00:00")
{
if (operatorEnum == Operator.LE)
{
listArgs.Add(DateTime.Parse(dateTime.ToString("yyyy-MM-dd") + " 23:59:59"));
}
else
{
listArgs.Add(dateTime);
}
}
else
{
listArgs.Add(dateTime);
}
sb.AppendFormat(" AND {0} {1} @{2}", item.FieldName, strOperator, paramCount);
}
}
else
{
listArgs.Add(ConvertToType(item.FieldValue, GetPropType<T>(item.FieldName)));
sb.AppendFormat(" AND {0} {1} @{2}", item.FieldName, strOperator, paramCount);
}
paramCount++;
break;
case Operator.Like:
case Operator.NotLike:
case Operator.LLike:
case Operator.RLike:
listArgs.Add(item.FieldValue);
if (operatorEnum == Operator.Like)
{
sb.AppendFormat(" AND {0}.Contains(@{1})", item.FieldName, paramCount);
}
else if (operatorEnum == Operator.NotLike)
{
sb.AppendFormat(" AND !{0}.Contains(@{1})", item.FieldName, paramCount);
}
else if (operatorEnum == Operator.LLike)
{
sb.AppendFormat(" AND {0}.EndsWith(@{1})", item.FieldName, paramCount);
}
else if (operatorEnum == Operator.RLike)
{
sb.AppendFormat(" AND {0}.StartsWith(@{1})", item.FieldName, paramCount);
}
paramCount++;
break;
case Operator.Null:
listArgs.Add(item.FieldValue);
sb.AppendFormat(" AND {0}=null", item.FieldName);
paramCount++;
break;
case Operator.NotNull:
listArgs.Add(item.FieldValue);
sb.AppendFormat(" AND {0}!=null", item.FieldName);
paramCount++;
break;
case Operator.In:
sb.AppendFormat(" AND (");
foreach (var schar in item.FieldValue.Split(','))
{
listArgs.Add(schar);
sb.AppendFormat("{0}=@{1} or ", item.FieldName, paramCount);
paramCount++;
}
sb.Remove(sb.Length - 3, 3);
sb.AppendFormat(" )");
break;
case Operator.NotIn:
sb.AppendFormat(" AND (");
foreach (var schar in item.FieldValue.Split(','))
{
listArgs.Add(schar);
sb.AppendFormat("{0}!=@{1} and ", item.FieldName, paramCount);
paramCount++;
}
sb.Remove(sb.Length - 3, 3);
sb.AppendFormat(" )");
break;
}
if (sb.ToString().Length > 0)
{
filter = sb.ToString().Substring(4, sb.Length - 4);
}
}
#endregion

}
result.Filter = filter;
result.ListArgs = listArgs;
return result;
}


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DataTable行转列

　　该部分是根据网友反馈后期再补充上的内容，意在完善行转列。下面给出实现代码

using Newtonsoft.Json;
using System;
using System.Collections.Generic;
using System.Data;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace DataTable_RowToColumn
{
class Program
{
static void Main(string[] args)
{
DataTable dt = InitTable();
List<string> DimensionList = new List<string>() { "Area", "Month" };
string DynamicColumn = "Name";
List<string> AllDynamicColumn = null;
DataTable dtResult = RowToColumn(dt, DimensionList, DynamicColumn, out AllDynamicColumn);
Console.WriteLine(JsonConvert.SerializeObject(dtResult, Formatting.Indented));
Console.Read();
}

/// <summary>
/// 动态Linq方式实现行转列
/// </summary>
/// <param name="list">数据</param>
/// <param name="DimensionList">维度列</param>
/// <param name="DynamicColumn">动态列</param>
/// <returns>行转列后数据</returns>
private static DataTable RowToColumn(DataTable dt, List<string> DimensionList, string DynamicColumn, out List<string> AllDynamicColumn)
{
//获取所有动态列
AllDynamicColumn = new List<string>();
foreach (DataRow dr in dt.DefaultView.ToTable(true, DynamicColumn).Rows)
{
if (dr[DynamicColumn] != null && !string.IsNullOrEmpty(dr[DynamicColumn].ToString()))
{
AllDynamicColumn.Add(dr[DynamicColumn].ToString());
}
}

//数值列
Dictionary<string, Type> AllNumberColumn = new Dictionary<string, Type>();
foreach (DataColumn item in dt.Columns)
{
if (item.DataType == typeof(int) || item.DataType == typeof(double) || item.DataType == typeof(float))
{
AllNumberColumn.Add(item.ColumnName, item.DataType);
}
}

//结果DataTable创建
DataTable dtResult = new DataTable();
foreach (var item in DimensionList)
{
dtResult.Columns.Add(item, typeof(string));
}
//动态列
foreach (var dynamicValue in AllDynamicColumn)
{
foreach (var item in AllNumberColumn.Keys)
{
dtResult.Columns.Add(item + dynamicValue, AllNumberColumn[item]);
}
}

//分组
var dtGroup = dt.DefaultView.ToTable(true, DimensionList.ToArray());
foreach (DataRow dr in dtGroup.Rows)
{
DataRow drReult = dtResult.NewRow();
string filter = "";
foreach (var key in DimensionList)
{
drReult[key] = dr[key];
filter += key + "='" + dr[key] + "' AND ";
}
string dynamicFilter = "";
foreach (var dynamicValue in AllDynamicColumn)
{
dynamicFilter = DynamicColumn + "='" + dynamicValue + "'";
foreach (var numColumn in AllNumberColumn.Keys)
{
drReult[numColumn + dynamicValue] = dt.Compute("sum(" + numColumn + ")", filter + dynamicFilter);
}
}
dtResult.Rows.Add(drReult);
}

return dtResult;
}

private static DataTable InitTable()
{
DataTable dt = new DataTable();
dt.Columns.Add("Name", typeof(string));
dt.Columns.Add("Area", typeof(string));
dt.Columns.Add("Month", typeof(string));
dt.Columns.Add("DfMoney", typeof(double));
dt.Columns.Add("SfMoney", typeof(double));
dt.Columns.Add("RqfMoney", typeof(double));

DataRow row = dt.NewRow();
row["Name"] = "张三";
row["Month"] = "2016-01";
row["Area"] = "江夏区";
row["DfMoney"] = 240.9;
row["SfMoney"] = 30;
row["RqfMoney"] = 25;
dt.Rows.Add(row);

row = dt.NewRow();
row["Name"] = "张三";
row["Month"] = "2016-02";
row["Area"] = "江夏区";
row["DfMoney"] = 167;
row["SfMoney"] = 24.5;
row["RqfMoney"] = 17.9;
dt.Rows.Add(row);

row = dt.NewRow();
row["Name"] = "小燕子";
row["Month"] = "2016-01";
row["Area"] = "江夏区";
row["DfMoney"] = 340.9;
row["SfMoney"] = 20;
row["RqfMoney"] = 55;
dt.Rows.Add(row);

row = dt.NewRow();
row["Name"] = "小燕子";
row["Month"] = "2016-02";
row["Area"] = "江夏区";
row["DfMoney"] = 67;
row["SfMoney"] = 64.5;
row["RqfMoney"] = 77.9;
dt.Rows.Add(row);

row = dt.NewRow();
row["Name"] = "李四";
row["Month"] = "2016-01";
row["Area"] = "洪山区";
row["DfMoney"] = 56.7;
row["SfMoney"] = 24.7;
row["RqfMoney"] = 13.2;
dt.Rows.Add(row);

row = dt.NewRow();
row["Name"] = "李四";
row["Month"] = "2016-02";
row["Area"] = "洪山区";
row["DfMoney"] = 65.2;
row["SfMoney"] = 18.9;
row["RqfMoney"] = 14.9;
dt.Rows.Add(row);

row = dt.NewRow();
row["Name"] = "尔康";
row["Month"] = "2016-01";
row["Area"] = "洪山区";
row["DfMoney"] = 156.7;
row["SfMoney"] = 124.7;
row["RqfMoney"] = 33.2;
dt.Rows.Add(row);

row = dt.NewRow();
row["Name"] = "尔康";
row["Month"] = "2016-02";
row["Area"] = "洪山区";
row["DfMoney"] = 35.2;
row["SfMoney"] = 28.9;
row["RqfMoney"] = 44.9;
dt.Rows.Add(row);
return dt;
}
}
}


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总结

本篇通过行转列引出了System.Linq.Dynamic，并且介绍了过滤功能，其实它的用处还有很多，等待大家发掘。下面给出本文示例代码：DynamicLinq

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