Steps to draw dashboard using ECharts and Python interface

The steps to draw a dashboard using ECharts and Python interface require specific code examples

Abstract: ECharts is an excellent data visualization tool that can be easily accessed through the Python interface for data processing and graphics rendering. This article will introduce the specific steps to draw a dashboard using ECharts and Python interface, and provide sample code.

Keywords: ECharts, Python interface, dashboard, data visualization

1. Introduction
   Dashboard is a commonly used form of data visualization, which displays data through intuitive charts various indicators and their changing trends. ECharts is an open source visualization library based on Javascript that provides rich chart types and flexible configuration options. Through the Python interface, data can be passed to ECharts and a variety of charts can be generated.
2. Installing ECharts and Python interface
   First you need to install the relevant libraries of ECharts and Python interface. Use the command line or Anaconda Prompt to execute the following command to install:

pip install pyecharts

3. Prepare data
   Before using ECharts to draw a dashboard, you need to prepare the data to be displayed. You can obtain data from a database, API interface or local file, and then use Python to process and organize it. The following is a sample data:

data = {
    'value': 75,
    'name': '指标名称',
    'unit': '百分比',
    'min': 0,
    'max': 100,
}

4. Create and configure the dashboard
   Use the Python interface of ECharts to create a dashboard instance and configure its related parameters. The following is a sample code:

from pyecharts import Gauge

gauge = Gauge("仪表盘示例", "数据来源：指标名称")
gauge.add("", "", data['value'], min_=data['min'], max_=data['max'])
gauge.render("gauge.html")

In the above code, Gauge means creating a dashboard instance, the first parameter is the title, and the second parameter is the subtitle;# The ##add method is used to add a pointer. The first parameter is the name of the pointer, the second parameter is empty, and the third parameter is the value of the pointer, min_ and max_ represents the minimum and maximum value of the pointer respectively; the render method is used to render the chart into an HTML file.

Run the program
5. After executing the above code, an HTML file named "gauge.html" will be generated. The file can be opened through a browser to view the generated dashboard chart.
   

To sum up, by using ECharts and Python interface, various types of dashboards can be drawn quickly and easily. By configuring relevant parameters, you can customize the style and display effect of the dashboard. I hope this article will be helpful to everyone in learning to use ECharts and Python interfaces to draw dashboards.

References:

[ECharts official document](https://echarts.apache.org/zh/index.html)
• [pyecharts official document ](https://pyecharts.org/)

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