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本篇內(nèi)容介紹了“什么是Kendo UI Chart集成”的有關(guān)知識,在實際案例的操作過程中,不少人都會遇到這樣的困境,接下來就讓小編帶領(lǐng)大家學(xué)習(xí)一下如何處理這些情況吧!希望大家仔細閱讀,能夠?qū)W有所成!
Kendo UI for jQuery R1 2021 SP2試用版下載
Kendo UI是帶有jQuery、Angular、React和Vue庫的JavaScript UI組件的最終集合,無論選擇哪種JavaScript框架,都可以快速構(gòu)建高性能響應(yīng)式Web應(yīng)用程序。通過可自定義的UI組件,Kendo UI可以創(chuàng)建數(shù)據(jù)豐富的桌面、平板和移動Web應(yīng)用程序。通過響應(yīng)式的布局、強大的數(shù)據(jù)綁定、跨瀏覽器兼容性和即時使用的主題,Kendo UI將開發(fā)時間加快了50%。
下面的示例演示如何將Kendo UI PivotGrid小部件與Kendo UI圖表小部件集成。
<div id="example"> <div id="pivotgrid"></div> <div id="chart"></div> <script> //function flatten the tree of tuples that datasource returns function flattenTree(tuples) { tuples = tuples.slice(); var result = []; var tuple = tuples.shift(); var idx, length, spliceIndex, children, member; while (tuple) { //required for multiple measures if(tuple.dataIndex !== undefined) { result.push(tuple); } spliceIndex = 0; for (idx = 0, length = tuple.members.length; idx < length; idx++) { member = tuple.members[idx]; children = member.children; if (member.measure) { [].splice.apply(tuples, [0, 0].concat(expandMeasures(children, tuple))); } else { [].splice.apply(tuples, [spliceIndex, 0].concat(children)); } spliceIndex += children.length; } tuple = tuples.shift(); } return result; } function clone(tuple, dataIndex) { var members = tuple.members.slice(); return { dataIndex: dataIndex, members: $.map(members, function(m) { return $.extend({}, m, { children: [] }); }) }; } function replaceLastMember(tuple, member) { tuple.members[tuple.members.length - 1] = member; return tuple; }; function expandMeasures(measures, tuple) { return $.map(measures, function(measure) { return replaceLastMember(clone(tuple, measure.dataIndex), measure); }); } //Check whether the tuple has been collapsed function isCollapsed(tuple, collapsed) { var members = tuple.members; for (var idx = 0, length = collapsed.length; idx < length; idx++) { var collapsedPath = collapsed[idx]; if (indexOfPath(fullPath(members, collapsedPath.length -1), [collapsedPath]) !== -1) { return true; } } return false; } //Work with tuple names/captions function indexOfPath(path, paths) { var path = path.join(","); for (var idx = 0; idx < paths.length; idx++) { if (paths[idx].join(",") === path) { return idx; } } return -1; } function fullPath(members, idx) { var path = []; var parentName = members[idx].parentName; idx -= 1; while (idx > -1) { path.push(members[idx].name); idx -= 1; } path.push(parentName); return path; } function memberCaption(member) { return member.caption }; function extractCaption(members) { return $.map(members, memberCaption).join(" "); }; function fullPathCaptionName(members, dLength, idx) { var result = extractCaption(members.slice(0, idx + 1)); var measureName = extractCaption(members.slice(dLength, members.mLength)); if (measureName) { result += " - " + measureName; } return result; } //the main function that convert PivotDataSource data into understandable for the Chart widget format function convertData(dataSource, collapsed) { var columnDimensionsLength = dataSource.columns().length; var rowDimensionsLength = dataSource.rows().length; var columnTuples = flattenTree(dataSource.axes().columns.tuples || [], collapsed.columns); var rowTuples = flattenTree(dataSource.axes().rows.tuples || [], collapsed.rows); var data = dataSource.data(); var rowTuple, columnTuple; var idx = 0; var result = []; var columnsLength = columnTuples.length; for (var i = 0; i < rowTuples.length; i++) { rowTuple = rowTuples[i]; if (!isCollapsed(rowTuple, collapsed.rows)) { for (var j = 0; j < columnsLength; j++) { columnTuple = columnTuples[j]; if (!isCollapsed(columnTuple, collapsed.columns)) { if (idx > columnsLength && idx % columnsLength !== 0) { for (var ri = 0; ri < rowTuple.members.length; ri++) { for (var ci = 0; ci < columnTuple.members.length; ci++) { //do not add root tuple members, e.g. [CY 2005, All Employees] //Add only children if (!columnTuple.members[ci].parentName || !rowTuple.members[ri].parentName) { continue; } result.push({ measure: Number(data[idx].value), column: fullPathCaptionName(columnTuple.members, columnDimensionsLength, ci), row: fullPathCaptionName(rowTuple.members, rowDimensionsLength, ri) }); } } } } idx += 1; } } } return result; } </script> <script> $(document).ready(function () { var collapsed = { columns: [], rows: [] }; var pivotgrid = $("#pivotgrid").kendoPivotGrid({ filterable: true, //gather the collapsed members collapseMember: function(e) { var axis = collapsed[e.axis]; var path = e.path; if (indexOfPath(path, axis) === -1) { axis.push(path); } }, //gather the expanded members expandMember: function(e) { var axis = collapsed[e.axis]; var index = indexOfPath(e.path, axis); if (index !== -1) { axis.splice(index, 1); } }, columnWidth: 100, height: 330, dataSource: { type: "xmla", columns: [{ name: "[Date].[Calendar]", expand: true }, { name: "[Employee].[Gender]" }], rows: [{ name: "[Product].[Category]", expand: true }], measures: ["[Measures].[Reseller Freight Cost]", "[Measures].[Internet Order Quantity]"], transport: { connection: { catalog: "Adventure Works DW 2008R2", cube: "Adventure Works" }, read: "https://demos.telerik.com/olap/msmdpump.dll" }, schema: { type: "xmla" }, error: function (e) { alert("error: " + kendo.stringify(e.errors[0])); } }, dataBound: function() { //create/bind the chart widget initChart(convertData(this.dataSource, collapsed)); } }).data("kendoPivotGrid"); function initChart(data) { var chart = $("#chart").data("kendoChart"); if (!chart) { $("#chart").kendoChart({ dataSource: { data: data, group: "row" }, series: [{ type: "column", field: "measure", name: "#= group.value # (category)", categoryField: "column" }], legend: { position: "bottom" }, categoryAxis: { labels: { rotation: 310 } }, valueAxis: { labels: { format: "${0}" } }, dataBound: function(e) { var categoryAxis = e.sender.options.categoryAxis; if (categoryAxis && categoryAxis.categories) { categoryAxis.categories.sort(); } } }); } else { chart.dataSource.data(data); } } }); </script> </div>
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