怎么调用一个pythonapi或者本地数据到js库google.visualization.DataTable()?
How do you call a python api or local data into the js lib google.visualization.DataTable()?
我已经工作了 2 周来尝试获取 CSV 文件(本地)以加载 google.visualization.DataTable()。或者我希望我们 Ajax 调用我创建的 Python 烧瓶 API。我想动态创建甘特图。
我的代码:
<script type="text/javascript" src="https://www.gstatic.com/charts/loader.js"></script>
<script src="https://code.jquery.com/jquery-3.6.0.min.js" ></script>
<script type="text/javascript">
// Load the Visualization API and the piechart package.
google.charts.load('current', {'packages':['gantt']});
google.charts.setOnLoadCallback(drawChart);
function daysToMilliseconds(days) {
return days * 24 * 60 * 60 * 1000;
}
function drawChart() {
var jsonData = $.ajax({
url: "http://127.0.0.1:5042/crudSEapi/D3test",
dataType: "json",
async: false
}).responseText;
var jsonData = JSON.parse(jsonData);
// Create our data table out of JSON data loaded from server.
var data = new google.visualization.DataTable(jsonData);
// Create our data table out of JSON data loaded from server.
console.log(jsonData["Column 0"])
data.addColumn('string',jsonData["Column 0"]);
data.addColumn(jsonData["Column 1"][1], jsonData["Column 1"][0]);
data.addRows([
[jsonData["Column 1"][2]]
]);
// Instantiate and draw our chart, passing in some options.
var options = {
height: 275,
gantt: {
criticalPathEnabled: false, // Critical path arrows will be the same as other arrows.
arrow: {
angle: 100,
width: 5,
color: 'green',
radius: 0
}
}
};
var container = document.getElementById('chart_div');
var chart = new google.visualization.Gantt(container);
// throw error for testing
google.visualization.events.addListener(chart, 'ready', function () {
throw new Error('Test Google Error');
});
// listen for error
google.visualization.events.addListener(chart, 'error', function (err) {
// check error
});
chart.draw(data, options);
}
</script>
<main id="main">
<section id="data-section">
<h2>Data Input</h2>
<div id="data"></div>
</section>
</main>
<h2>chart output</h2>
<div id="chart_div"></div>
<script>
function apicall(url) {
$.ajax({
type:"POST", url:url,
success: (data) => { $("#data").html(data); }
});
}
window.onload = function () {
apicall("http://127.0.0.1:5042/crudSEapi/D3test");
}
</script>
无论我观看了多少 YouTube 视频,我都无法理解如何从我的 Python Flask API 进行 Ajax 调用并将所需数据加载到 google.visualization.DataTable() 用于动态创建甘特图:) 请帮助
我的问题确实是缺乏对 JS 的掌握。如何从 API 或本地 CSV 导入数据?我如何解析数据,然后组织要在 google.visualization.DataTable() 中使用的数据。我希望我能找到一个简单的例子。请帮助...
我的Python烧瓶Api代码:
import json
@crudSEapi.route("/D3test", methods=["GET", "POST"])
def d3():
df = pd.read_csv("SkillBook/static/Sheet4.csv")
chartdata = df.to_json()
data = json.dumps(chartdata, indent=2)
print(data)
return Response(data)
CSV 文件:
id,title,start,end,dependencies,completed
m1,milestone 1,addDuration(startOfDay(new Date()),addDuration(startOfDay(new Date()),m2: start-to-start,0.6
m2,milestone 2,addDuration(startOfDay(new Date()),addDuration(startOfDay(new Date()),[m3: end-to-start,m4: end-to-end],0
m3,milestone 3,addDuration(startOfDay(new Date()),addDuration(startOfDay(new Date()),,0.75
m4,milestone 4,addDuration(startOfDay(new Date()),addDuration(startOfDay(new Date()),,0.2
输出应如下所示:
感谢@WhiteHat,我弄明白了。
<script src="https://www.gstatic.com/charts/loader.js"></script>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.3/jquery.min.js"></script>
<script src="https://unpkg.com/jquery-csv@1.0.21/src/jquery.csv.js"></script>
<div id="chart_div"></div>
<li><input></li>
<li><input></li>
<li><input></li>
<button>update data in chart</button>
<button>print SVG</button>
<script>
function toMilliseconds(minutes) {
return minutes * 60 * 1000;
}
google.charts.load('current', {
callback: function () {
$.get("/static/Sheet4.csv", function(csvString) {
var arrayData = $.csv.toArrays(csvString, {onParseValue: $.csv.hooks.castToScalar});
console.log(arrayData[6][1])
var data = new google.visualization.DataTable();
data.addColumn(arrayData[2][1], arrayData[1][1]);
data.addColumn(arrayData[2][2], arrayData[1][2]);
data.addColumn(arrayData[2][4], arrayData[1][4]);
data.addColumn(arrayData[2][5], arrayData[1][5]);
data.addColumn(arrayData[2][6], arrayData[1][6]);
data.addColumn(arrayData[2][7], arrayData[1][7]);
data.addColumn(arrayData[2][8], arrayData[1][8]);
data.addRows([
[
arrayData[3][1],
arrayData[3][2],
null,
null,
toMilliseconds(5),
100,
null,
],
[
arrayData[4][1],
arrayData[4][2],
null,
null,
toMilliseconds(70),
100,
null,
],
[
arrayData[5][1],
arrayData[5][2],
null,
null,
toMilliseconds(10),
100,
arrayData[3][1],
],
[
arrayData[6][1],
arrayData[6][2],
null,
null,
toMilliseconds(45),
75,
arrayData[5][1],
],
[
arrayData[7][1],
arrayData[7][2],
null,
null,
toMilliseconds(10),
0,
arrayData[6][1],
],
[
arrayData[8][1],
arrayData[8][2],
null,
null,
toMilliseconds(2),
0,
arrayData[5][1],
],
]);
var options = {
height: 275,
gantt: {
criticalPathEnabled: false, // Critical path arrows will be the same as other arrows.
arrow: {
angle: 100,
width: 5,
color: 'green',
radius: 0
}
}
};
var container = document.getElementById('chart_div');
var chart = new google.visualization.Gantt(container);
chart.draw(data, options);
});
},
packages: ['gantt']
});
</script>
还有我的 CSV:
step0,step1,step2,step3,step4,step5,Step6,step7,step8
Purpose,Task ID,Task Name,Resource ID,Start,End,Duration,Percent Complete,Dependencies
Data Type,string,string,string,date,date,number,number,string
Prject1data1,Test1,test1x,test1y,test1z,0,1,2,test1a
Prject1data2,Test2,test2x,test2y,test2z,0,1,2,test2a
Prject1data3,Test3,test3x,test3y,test3z,0,1,2,test3a
Prject1data4,Test4,test4x,test4y,test4z,0,1,2,test4a
Prject1data5,Test5,test5x,test5y,test5z,0,1,2,test4a
Prject1data6,Test6,test6x,test6y,test6z,0,1,2,test4a
Prject1data7,Test7,test7x,test7y,test7z,0,1,2,test4a
下一步:
将输入更改为动态。我将在网站上创建输入表单以更改数据
无论 CSV 文件的大小如何,我都将允许上传和解析 CSV
我已经工作了 2 周来尝试获取 CSV 文件(本地)以加载 google.visualization.DataTable()。或者我希望我们 Ajax 调用我创建的 Python 烧瓶 API。我想动态创建甘特图。
我的代码:
<script type="text/javascript" src="https://www.gstatic.com/charts/loader.js"></script>
<script src="https://code.jquery.com/jquery-3.6.0.min.js" ></script>
<script type="text/javascript">
// Load the Visualization API and the piechart package.
google.charts.load('current', {'packages':['gantt']});
google.charts.setOnLoadCallback(drawChart);
function daysToMilliseconds(days) {
return days * 24 * 60 * 60 * 1000;
}
function drawChart() {
var jsonData = $.ajax({
url: "http://127.0.0.1:5042/crudSEapi/D3test",
dataType: "json",
async: false
}).responseText;
var jsonData = JSON.parse(jsonData);
// Create our data table out of JSON data loaded from server.
var data = new google.visualization.DataTable(jsonData);
// Create our data table out of JSON data loaded from server.
console.log(jsonData["Column 0"])
data.addColumn('string',jsonData["Column 0"]);
data.addColumn(jsonData["Column 1"][1], jsonData["Column 1"][0]);
data.addRows([
[jsonData["Column 1"][2]]
]);
// Instantiate and draw our chart, passing in some options.
var options = {
height: 275,
gantt: {
criticalPathEnabled: false, // Critical path arrows will be the same as other arrows.
arrow: {
angle: 100,
width: 5,
color: 'green',
radius: 0
}
}
};
var container = document.getElementById('chart_div');
var chart = new google.visualization.Gantt(container);
// throw error for testing
google.visualization.events.addListener(chart, 'ready', function () {
throw new Error('Test Google Error');
});
// listen for error
google.visualization.events.addListener(chart, 'error', function (err) {
// check error
});
chart.draw(data, options);
}
</script>
<main id="main">
<section id="data-section">
<h2>Data Input</h2>
<div id="data"></div>
</section>
</main>
<h2>chart output</h2>
<div id="chart_div"></div>
<script>
function apicall(url) {
$.ajax({
type:"POST", url:url,
success: (data) => { $("#data").html(data); }
});
}
window.onload = function () {
apicall("http://127.0.0.1:5042/crudSEapi/D3test");
}
</script>
无论我观看了多少 YouTube 视频,我都无法理解如何从我的 Python Flask API 进行 Ajax 调用并将所需数据加载到 google.visualization.DataTable() 用于动态创建甘特图:) 请帮助
我的问题确实是缺乏对 JS 的掌握。如何从 API 或本地 CSV 导入数据?我如何解析数据,然后组织要在 google.visualization.DataTable() 中使用的数据。我希望我能找到一个简单的例子。请帮助...
我的Python烧瓶Api代码:
import json
@crudSEapi.route("/D3test", methods=["GET", "POST"])
def d3():
df = pd.read_csv("SkillBook/static/Sheet4.csv")
chartdata = df.to_json()
data = json.dumps(chartdata, indent=2)
print(data)
return Response(data)
CSV 文件:
id,title,start,end,dependencies,completed
m1,milestone 1,addDuration(startOfDay(new Date()),addDuration(startOfDay(new Date()),m2: start-to-start,0.6
m2,milestone 2,addDuration(startOfDay(new Date()),addDuration(startOfDay(new Date()),[m3: end-to-start,m4: end-to-end],0
m3,milestone 3,addDuration(startOfDay(new Date()),addDuration(startOfDay(new Date()),,0.75
m4,milestone 4,addDuration(startOfDay(new Date()),addDuration(startOfDay(new Date()),,0.2
输出应如下所示:
感谢@WhiteHat,我弄明白了。
<script src="https://www.gstatic.com/charts/loader.js"></script>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.3/jquery.min.js"></script>
<script src="https://unpkg.com/jquery-csv@1.0.21/src/jquery.csv.js"></script>
<div id="chart_div"></div>
<li><input></li>
<li><input></li>
<li><input></li>
<button>update data in chart</button>
<button>print SVG</button>
<script>
function toMilliseconds(minutes) {
return minutes * 60 * 1000;
}
google.charts.load('current', {
callback: function () {
$.get("/static/Sheet4.csv", function(csvString) {
var arrayData = $.csv.toArrays(csvString, {onParseValue: $.csv.hooks.castToScalar});
console.log(arrayData[6][1])
var data = new google.visualization.DataTable();
data.addColumn(arrayData[2][1], arrayData[1][1]);
data.addColumn(arrayData[2][2], arrayData[1][2]);
data.addColumn(arrayData[2][4], arrayData[1][4]);
data.addColumn(arrayData[2][5], arrayData[1][5]);
data.addColumn(arrayData[2][6], arrayData[1][6]);
data.addColumn(arrayData[2][7], arrayData[1][7]);
data.addColumn(arrayData[2][8], arrayData[1][8]);
data.addRows([
[
arrayData[3][1],
arrayData[3][2],
null,
null,
toMilliseconds(5),
100,
null,
],
[
arrayData[4][1],
arrayData[4][2],
null,
null,
toMilliseconds(70),
100,
null,
],
[
arrayData[5][1],
arrayData[5][2],
null,
null,
toMilliseconds(10),
100,
arrayData[3][1],
],
[
arrayData[6][1],
arrayData[6][2],
null,
null,
toMilliseconds(45),
75,
arrayData[5][1],
],
[
arrayData[7][1],
arrayData[7][2],
null,
null,
toMilliseconds(10),
0,
arrayData[6][1],
],
[
arrayData[8][1],
arrayData[8][2],
null,
null,
toMilliseconds(2),
0,
arrayData[5][1],
],
]);
var options = {
height: 275,
gantt: {
criticalPathEnabled: false, // Critical path arrows will be the same as other arrows.
arrow: {
angle: 100,
width: 5,
color: 'green',
radius: 0
}
}
};
var container = document.getElementById('chart_div');
var chart = new google.visualization.Gantt(container);
chart.draw(data, options);
});
},
packages: ['gantt']
});
</script>
还有我的 CSV:
step0,step1,step2,step3,step4,step5,Step6,step7,step8
Purpose,Task ID,Task Name,Resource ID,Start,End,Duration,Percent Complete,Dependencies
Data Type,string,string,string,date,date,number,number,string
Prject1data1,Test1,test1x,test1y,test1z,0,1,2,test1a
Prject1data2,Test2,test2x,test2y,test2z,0,1,2,test2a
Prject1data3,Test3,test3x,test3y,test3z,0,1,2,test3a
Prject1data4,Test4,test4x,test4y,test4z,0,1,2,test4a
Prject1data5,Test5,test5x,test5y,test5z,0,1,2,test4a
Prject1data6,Test6,test6x,test6y,test6z,0,1,2,test4a
Prject1data7,Test7,test7x,test7y,test7z,0,1,2,test4a
下一步: 将输入更改为动态。我将在网站上创建输入表单以更改数据
无论 CSV 文件的大小如何,我都将允许上传和解析 CSV