java版:https://github.com/abel533/ECharts
echart:http://echarts.baidu.com/
演示地址:http://echarts.idoku.cn/
本项目是一个.Net版的ECharts开发包,参考@abel1533的java版本,主要目的是方便在.NET中构件Echarts中可能用的全部数据结构,完整的Option结构. ChartOption中的数据Series,包含Line-折线图,Bar-柱状图,Pie-饼图,Scatter-散点图等,支持Echarts中所有图表.支持所有Style类,如AreaStyle,ItemStyle,LineStyle等.支持多种Data数据类型,一个通用的Data数据,以及PieData,PolarData,TreeData等个性化数据结构. 你可以使用本项目直接构件一个Option对象,使用方法JsonTools.ObjectToJson2(option),(直接使用Json方式返回存在问题,因为function不是标准化的json格式,转换会报错).
图表类型3.x版本(2.x版本支持的图表不一样)
- Line 折线（面积）图
- Bar 柱状（条形）图
- Scatter 散点（气泡）图
- K K线图
- Candlestick K线图
- Pie 饼（圆环）图
- Radar 雷达（面积）图
- Force 力导向布局图
- Map 地图
- Gauge 仪表盘
- Funnel 漏斗图
- Heatmap 热力图
- Treemap 矩形树图
- EffectScatter - 涟漪效果散点图
- Boxplot - 箱线图
- Graph - 关系图,可以实现force
- Parallel - 平行坐标系
- Sankey - 桑基图
- PictorialBar - 象形柱图
- ThemeRiver - 主题河流图
- Calendar - 日历图
- Map - 地图
Echarts组件
- Axis 坐标轴
- Grid 网格
- Title 标题
- Tooltip 提示
- Legend 图例
- DataZoom 数据区域缩放
- DataRange 值域漫游
- Toolbox 工具箱
- Timeline 时间线
- visualMap 视觉映射组件
3.x版本相比2.x版本改动很大，除了部分图表不一样外，少数api也有改动，因此如果要从2.x升级3.x，一定要做好测试! 3.6.1 2017.5.26
- 3.0版本去掉了k(改为candlestick),radar(雷达图),chord(和弦图),force(使用graph,layout=force替代),island(孤岛),eventRiver(事件河流图),venn(韦恩图),wordCloud(词云),Tree(树图)
- 3.0版本新增了lines(线图),effectScatter(涟漪效果散点图),candlestick(新的k线图),graph(关系图,可以实现force),boxplot(箱形图),parallel(平行坐标系),sankey(桑基图)
- 新增大量相关类，部分已有类增加大量属性
- ChartOption 是echarts的主要类.
- 使用JsonTools.ObjectToJson2方法返回给前端时,需要使用eval('(' + data + ')')转换为JSON结构.
由于json标准中不包含function类型,一般json库都不支持这种类型,处理这种类型最简单的方式是转换json字符串时,对字符串进行处理. 读者可以自行使用其他自定义方式实现,本项目使用的.net自带的JRaw()方式.不管是:
"formatter": function(params) {
// for text color
var color = colorList[params[0].dataIndex];
var res = '<div style="color:' + color + '">';
res += '<strong>' + params[0].name + '消费（元）</strong>'
for (var i = 0, l = params.length; i < l; i++) {
res += '<br/>' + params[i].seriesName + ' : ' + params[i].value
}
res += '</div>';
return res;
},和
"color": (function (){
var zrColor = require('zrender/tool/color');
return zrColor.getLinearGradient(
0, 400, 0, 300,
[[0, 'green'],[1, 'yellow']]
)
})(),都可以利用JRaw来实现.
option.ToolTip().Trigger(TriggerType.axis)
.BackgroundColor("rgba(255,255,255,0.7)")
.Formatter(new JRaw(@"function(params) {
// for text color
var color = colorList[params[0].dataIndex];
var res = '<div style=""color:' + color + '"">';
res += '<strong>' + params[0].name + '消费（元）</strong>'
for (var i = 0, l = params.length; i < l; i++) {
res += '<br/>' + params[i].seriesName + ' : ' + params[i].value
}
res += '</div>';
return res;
}"))和
style.Emphasis().BarBorderColor("green").BarBorderWidth(5)
.Color(new JRaw(@"(function (){
var zrColor = require('zrender/tool/color');
return zrColor.getLinearGradient(
0, 400, 0, 300,
[[0, 'red'],[1, 'orange']]
)
})()"))
本项目通过ASP.NET MVC和ASP.NET web api模拟了echarts官网网站中的全部示例,主要目的是方便大家参考使用和调整结构.
1.简单Line示例
演示地址: http://echarts.idoku.cn/home/example?api=line1
例子中给出的json结构.
{
"calculable": true,
"title": {
"text": "未来一周天气变化",
"subtext": "纯虚构数据",
"show": true
},
"tooltip": {
"trigger": "axis"
},
"legend": {
"data": [
"最高温度",
"最低温度"
]
},
"xAxis": [
{
"data": [
"周一",
"周二",
"周三",
"周四",
"周五",
"周六",
"周日"
],
"boundaryGap": false,
"type": "category"
}
],
"yAxis": [
{
"type": "value",
"axisLabel": {
"formatter": "{value} ℃"
}
}
],
"series": [
{
"data": [
13,
10,
12,
10,
13,
13,
14
],
"type": "line",
"name": "最高温度",
"markPoint": {
"data": [
{
"name": "最大值",
"type": "max"
},
{
"name": "最小值",
"type": "min"
}
]
},
"markLine": {
"data": [
{
"name": "平均值",
"type": "average"
}
]
}
},
{
"data": [
3,
-1,
1,
-1,
3,
3,
4
],
"type": "line",
"name": "最低温度",
"markPoint": {
"data": [
{
"name": "周最低",
"value": -1,
"xAxis": 1,
"yAxis": -0.5
}
]
},
"markLine": {
"data": [
{
"name": "平均值",
"type": "average"
}
]
}
}
]
}对应的源码:
[AcceptVerbs("GET", "POST")]
[ActionName("line1")]
public string StdLine()
{
IList<string> weeks = ChartsUtil.Weeks();
IList<int> datas1 = ChartsUtil.Datas(7, 10, 15);
IList<int> datas2 = ChartsUtil.Datas(7, -2, 5);
int min = datas2.Min();
int index = datas2.IndexOf(min);
ChartOption option = new ChartOption();
option.title = new Title()
{
show = true,
text = "未来一周天气变化",
subtext = "纯虚构数据"
};
option.tooltip = new ToolTip()
{
trigger = TriggerType.axis
};
option.legend = new Legend()
{
data = new List<object>(){
"最高温度",
"最低温度"
}
};
option.calculable = true;
option.xAxis = new List<Axis>()
{
new CategoryAxis()
{
type = AxisType.category,
boundaryGap= false,
data = new List<object>(weeks)
}
};
option.yAxis = new List<Axis>()
{
new ValueAxis()
{
type = AxisType.value,
axisLabel = new AxisLabel(){
formatter=new JRaw("{value} ℃").ToString()
}
}
};
option.series = new List<object>()
{
new Line()
{
name = "最高温度",
type = ChartType.line,
data = datas1,
markPoint = new MarkPoint()
{
data = new List<object>()
{
new MarkData()
{
name = "最大值",
type= MarkType.max,
},
new MarkData()
{
name = "最小值",
type= MarkType.min,
}
}
},
markLine = new MarkLine()
{
data = new List<object>()
{
new MarkData()
{
name = "平均值",
type = MarkType.average
}
}
}
},
new Line(){
name="最低温度",
type = ChartType.line,
data = datas2,
markPoint= new MarkPoint(){
data = new List<object>(){
new MarkData(){
name="周最低",
value = min,
xAxis = index,
yAxis = min+0.5,
}
}
},
markLine = new MarkLine(){
data = new List<object>(){
new MarkData(){
type = MarkType.average,
name = "平均值"
}
}
}
}
};
var result = JsonTools.ObjectToJson2(option);
return result;
}-
使用function的bar示例.
演示地址: http://echarts.idoku.cn/home/example?api=bar10#
给出的json代码:
{
"title": {
"text": "温度计式图表",
"subtext": "Form ExcelHome",
"sublink": "http://e.weibo.com/1341556070/AizJXrAEa"
},
"toolbox": {
"feature": {
"mark": {
"show": true
},
"dataView": {
"show": true,
"readOnly": false
},
"restore": {
"show": true
},
"saveAsImage": {
"show": true
}
},
"show": true
},
"tooltip": {
"trigger": "axis",
"formatter": function (params){
return params[0].name + '<br/>'
+ params[0].seriesName + ' : ' + params[0].value + '<br/>'
+ params[1].seriesName + ' : ' + (params[1].value + params[0].value);
},
"axisPointer": {
"type": "shadow"
}
},
"legend": {
"data": [
"Acutal",
"Forecast"
]
},
"grid": {
"y2": 30,
"y": 80
},
"xAxis": [
{
"data": [
"Cosco",
"CMA",
"APL",
"OOCL",
"Wanhai",
"Zim"
],
"type": "category"
}
],
"yAxis": [
{
"boundaryGap": [
0.0,
0.1
],
"type": "value"
}
],
"series": [
{
"stack": "sum",
"data": [
260,
200,
220,
120,
100,
80
],
"type": "bar",
"name": "Acutal",
"itemStyle": {
"normal": {
"color": "tomato",
"barBorderColor": "tomato",
"barBorderRadius": 0,
"barBorderWidth": 6,
"label": {
"show": true,
"position": "insideTop"
}
}
}
},
{
"stack": "sum",
"data": [
40,
80,
50,
80,
80,
70
],
"type": "bar",
"name": "Forecast",
"itemStyle": {
"normal": {
"color": "#fff",
"barBorderColor": "tomato",
"barBorderRadius": 0,
"barBorderWidth": 6,
"label": {
"show": true,
"position": "top",
"formatter": function (params) {
for (var i = 0, l = option.xAxis[0].data.length; i < l; i++) {
if (option.xAxis[0].data[i] == params.name) {
return option.series[0].data[i] + params.value;
}
}
},
"textStyle": {
"color": "tomato"
}
}
}
}
}
]
}对应的源码:
[AcceptVerbs("GET", "POST")]
[ActionName("bar10")]
public string TemperatureBar()
{
ChartOption option = new ChartOption();
option.Title().Text("温度计式图表").Subtext("Form ExcelHome").
Sublink("http://e.weibo.com/1341556070/AizJXrAEa");
option.ToolTip().Trigger(TriggerType.axis)
.Formatter(new JRaw(@"function (params){
return params[0].name + '<br/>'
+ params[0].seriesName + ' : ' + params[0].value + '<br/>'
+ params[1].seriesName + ' : ' + (params[1].value + params[0].value);
}"))
.AxisPointer().Type(AxisPointType.shadow);
option.Legend().Data("Acutal","Forecast");
Feature feature = new Feature();
feature.Mark().Show(true);
feature.DataView().Show(true).ReadOnly(false);
feature.Restore().Show(true);
feature.SaveAsImage().Show(true);
option.ToolBox().Show(true).SetFeature(feature);
option.Grid().Y(80).Y2(30);
CategoryAxis x = new CategoryAxis();
x.Data("Cosco", "CMA", "APL", "OOCL", "Wanhai", "Zim");
option.XAxis(x);
ValueAxis y = new ValueAxis();
y.BoundaryGap(new List<double>() { 0,0.1 });
option.YAxis(y);
var tomatoStyle = new ItemStyle();
tomatoStyle.Normal().Color("tomato").BarBorderRadius(0)
.BarBorderColor("tomato").BarBorderWidth(6)
.Label().Show(true).Position(StyleLabelTyle.insideTop);
Bar b1 = new Bar("Acutal");
b1.Stack("sum");
b1.SetItemStyle(tomatoStyle);
b1.Data(260, 200, 220, 120, 100, 80);
var forecastStyle = new ItemStyle();
forecastStyle.Normal().Color("#fff").BarBorderRadius(0)
.BarBorderColor("tomato").BarBorderWidth(6)
.Label().Show(true).Position(StyleLabelTyle.top)
.Formatter(new JRaw(@"function (params) {
for (var i = 0, l = option.xAxis[0].data.length; i < l; i++) {
if (option.xAxis[0].data[i] == params.name) {
return option.series[0].data[i] + params.value;
}
}
}"))
.TextStyle().Color("tomato");
Bar b2 = new Bar("Forecast");
b2.Stack("sum");
b2.SetItemStyle(forecastStyle);
b2.Data(40, 80, 50, 80, 80, 70);
option.Series(b1, b2);
var result = JsonTools.ObjectToJson2(option);
return result;
}
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