Echarts使用dataset数据集管理数据
1、可以看官网api的入门例子
使用常见的对象数组的格式
option = {
legend: {},
tooltip: {},
dataset: {
// 这里指定了维度名的顺序,从而可以利用默认的维度到坐标轴的映射。
// 如果不指定 dimensions,也可以通过指定 series.encode 完成映射,参见后文。
dimensions: ['product', '', '', ''],
source: [
{product: 'Matcha Latte', '': 43.3, '': 85.8, '': 93.7},
{product: 'Milk Tea', '': 83.1, '': 73.4, '': 55.1},
{product: 'Cheese Cocoa', '': 86.4, '': 65.2, '': 82.5},
{product: 'Walnut Brownie', '': 72.4, '': 53.9, '': 39.1}
]
},
xAxis: {type: 'category'},
yAxis: {},
series: [
{type: 'bar'},
{type: 'bar'},
{type: 'bar'}
]
};
第一个默认时x轴,后面是y轴
2、项目应用:
数据格式:
aaarticlea/png;base64,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" alt="" width="423" height="404" />
数据:
//5种不同维度
dimensions:[
['snap_time','active','idle','total'],
['snap_time','commits','rollbacks','transactions'],
['snap_time','inserts','updates','deletes'],
['snap_time','fetched','returned'],
['snap_time','reads','hits']
], //dataset数据
dataset:{
dimensions:this.lineDime,
source:this.lineSeries//source取的全部数据
},
series: this.series //series数据
let _obj = {
type:'line'
}
this.series.length = this.lineDime.length -
this.series.fill(_obj)
效果:
Echarts使用dataset数据集管理数据的更多相关文章
- C#操作Dataset数据集与SQLite数据库
近日有需要写点C#程序,有用到Dataset数据集和SQLite数据库,由于我从来就不擅长记各种编程语言的语法,所以在查阅一堆资料后,留下以下内容备忘: 一.SQLite操作,直接贴代码,很简 ...
- 使用DataSet数据集插入记录
使用INSERT语句能够完成数据插入,使用DataSet对象也可以完成数据插入.为了将数据库的数据填充到DataSet中,则必须先使用DataAdapter对象的方法实现填充,当数据填充完成后,开发人 ...
- tvtk管线技术、数据集与数据加载
管线技术也称流水线技术(Pipeline)每个对象只实现相对简单的任务,整个管线进行复杂的可视化处理在tvtk中分为可视化管线和图形管线 可视化管线(Visualization Pipeline):将 ...
- SAS学习笔记之《SAS编程与数据挖掘商业案例》(3)变量操作、观测值操作、SAS数据集管理
SAS学习笔记之<SAS编程与数据挖掘商业案例>(3)变量操作.观测值操作.SAS数据集管理 1. SAS变量操作的常用语句 ASSIGNMENT 创建或修改变量 SUM 累加变量或表达式 ...
- 【观隅】数据集管理与可视化平台-NABCD分析
项目 内容 这个作业属于哪个课程 2021春季软件工程(罗杰 任健) 这个作业的要求在哪里 团队项目-初次邂逅,需求分析 项目介绍 观隅 数据集管理与可视化平台(取"观一隅而知全局" ...
- 读取Simulink中Dataset类型的数据
http://files.cnblogs.com/files/pursuiting/%E5%80%92%E7%AB%8B%E6%91%86%E6%8E%A7%E5%88%B6%E7%B3%BB%E7% ...
- 用ORBSLAM2运行TUM Dataset数据集
参照https://github.com/raulmur/ORB_SLAM2/blob/master/README.md 运行 4. Monocular Examples TUM Dataset 数据 ...
- 遍历Dataset并输出数据实例
转自:http://www.cnblogs.com/csdm/archive/2010/02/02/1661808.html <%@ Page Language="C#" A ...
- 使用DataSet数据集删除记录
使用DataSet删除记录和使用DataSet更新记录非常的相似,DataSet删除记录的步骤如下所示. q 创建一个Connection对象. q 创建一个DataAdapter对象. q 初 ...
随机推荐
- JQuery中$.ajax()方法参数详解 ASP.NET jquery ajax传递参数
url: 要求为String类型的参数,(默认为当前页地址)发送请求的地址. type: 要求为String类型的参数,请求方式(post或get)默认为get.注意其他http请求方法,例如put和 ...
- Vue 2.0学习(一)简介
简介 Vue是一套用于构建用户界面的渐进式框架.简单小巧( 压缩后仅17KB),Vue.js 的目标是通过尽可能简单的 API 实现响应的数据绑定和组合的视图组件.它不仅易于上手,还便于与第三方库或既 ...
- 【最小割】BZOJ3894-文理分科
[题目大意] 给定一个m*n的矩阵,每个格子的人可以学文或者学理,学文和学理各有一个满意度,如果以某人为中心的十字内所有人都学文或者学理还会得到一个额外满意度,求最大满意度之和. [思路] 发现这道题 ...
- JNI介绍
JNI是在学习Android HAL时必须要面临一个知识点,如果你不了解它的机制,不了解它的使用方式,你会被本地代码绕的晕头转向,JNI作为一个中间语言的翻译官在运行Java代码的Android中有着 ...
- ThinkPHP -- 基础入门
ThinkPHP文件结构说明: |——ThinkPHP.php 框架入口文件 |——Common 框架公共文件目录 |——Conf ...
- [转]android 自定义圆形imageview控件
android布局 首先,定义定义圆形Imageview类: import android.content.Context; import android.graphics.Bitmap; imp ...
- VS2015启动拷贝过来的项目无法启动IIS Express
最近将VS2015开发的项目考给同事,告知无法启动,大概分析了一下原因: 1.查看端口是否占用冲突 2.在解决方案上右键选择,清理解决方案->重建解决方案 3.以上两个方法还不生效的话,在Web ...
- 稀疏编码直方图----一种超越HOG的轮廓特征
该论文是一篇来自CMU 的CVPR2013文章,提出了一种基于稀疏编码的轮廓特征,简称HSC(Histogram of Sparse Code),并在目标检测中全面超越了HOG(Histogram o ...
- WEB安全扫描器Netsparker推荐给大家
Netsparker是一款综合型的web应用安全漏洞扫描工具,它分为专业版和免费版,免费版的功能也比较强大. Netsparker与其他综合 性的web应用安全扫描工具相比的一个特点是它能够更好的检测 ...
- AR(Average Recall, 平均查全率), ANMRR(Average Normalized Modified Retrieval Rate, 平均归一化检索秩)
AR(Average Recall, 平均查全率), ANMRR(Average Normalized Modified Retrieval Rate, 平均归一化检索秩)