我使用您在一个相关问题中提供的示例数据为您制作了一个演示。如果你去这个演示页面并上传你最初提供的 CSV,你应该得到这个图表:
ZingChart 包含一个用于基本图表的 CSV 解析器,但是像这样的更复杂的情况需要一些预处理才能将数据放在需要的位置。我在这个演示中使用了 PapaParse,但还有其他可用的解析库。
这是JavaScript。我在 HTML 中使用简单的文件输入来获取 CSV。
var csvData;
var limit = [],
normal = [],
excess = [],
dates = [];
var myConfig = {
theme: "none",
"type": "mixed",
"scale-x": {
"items-overlap":true,
"max-items":9999,
values: dates,
guide: {
visible: 0
},
item:{
angle:45
}
},
"series": [{
"type": "bar",
"values": normal,
"stacked": true,
"background-color": "#4372C1",
"hover-state": {
"visible": 0
}
}, {
"type": "bar",
"values": excess,
"stacked": true,
"background-color": "#EB7D33",
"hover-state": {
"visible": 0
}
}, {
"type": "line",
"values": limit
}]
};
/* Get the file and parse with PapaParse */
function parseFile(e) {
var file = e.target.files[0];
Papa.parse(file, {
delimiter: ",",
complete: function(results) {
results.data.shift(); //the first array is header values, we don't need these
csvData = results.data;
prepChart(csvData);
}
});
}
/* Process the results from the PapaParse(d) CSV and populate
** the arrays for each chart series and scale-x values
*/
function prepChart(data) {
var excessVal;
//PapaParse data is in a 2d array
for (var i = 0; i < data.length; i++) {
//save reference to your excess value
//cast all numeric values to int (they're originally strings)
var excessVal = parseInt(data[i][4]);
//date, limit value, and normal value can all be pushed to their arrays
dates.push(data[i][0]);
limit.push(parseInt(data[i][1]));
normal.push(parseInt(data[i][3]));
/* we must push a null value into the excess
** series if there is no excess for this node
*/
if (excessVal == 0) {
excess.push(null);
} else {
excess.push(excessVal);
}
}
//render your chart
zingchart.render({
id: 'myChart',
data: myConfig,
height: 500,
width: 725
});
}
$(document).ready(function() {
$('#csv-file').change(parseFile);
});