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How to generate polar coordinate plots using ECharts and Python interfaces

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Dec 17, 2023 am 08:26 AM

pythonechartsPolar plot

How to generate polar coordinate plots using ECharts and Python interfaces

The method of using ECharts and Python interface to generate polar plots requires specific code examples

ECharts is a very powerful and easy-to-use open source data visualization tool. It is fast, beautiful, and customizable, and can quickly draw various charts. ECharts supports many chart types, including bar charts, line charts, pie charts, scatter charts, etc., including polar coordinate charts. ECharts provides a very convenient solution to the problem of making polar coordinate charts, and its use with the Python interface makes the work more efficient.

This article will introduce the specific method of using ECharts and the Python interface to generate polar coordinate charts, including how to install ECharts, how to use the Python interface to call ECharts to generate polar coordinate charts, and how to customize the chart style.

1. Install ECharts

Download the ECharts source code package or packaging file

On the ECharts official website https://echarts.apache.org/zh /index.html Download the source code package or package file of ECharts, unzip or unzip it and enter the directory of the corresponding version.

Create a Web directory

Create a Web directory locally or on the server to store ECharts related files.

Copy ECharts files to the Web directory

Copy ECharts files and folders to the Web directory, usually including css, js, images, fonts and other files and folders.

Introduce ECharts files

Introduce ECharts files into HTML files, usually including echarts.js and theme files, the code is as follows:

<!DOCTYPE html>
<html>
<head>
    <meta charset="UTF-8">
    <title>How to generate polar coordinate plots using ECharts and Python interfaces</title>
    <link rel="stylesheet" href="css/echarts.css">
</head>
<body>
    <div id="main" style="height: 500px"></div>
    <script src="js/echarts.js"></script>
    <script src="js/theme.js"></script>
</body>
</html>

2. Use the Python interface to call ECharts

Install Python

If you have not installed Python, you need to install it on the official website https://www.python.org/downloads/ Download Python and install it.

Install pyecharts library

Use pip command to install pyecharts library:

pip install pyecharts

Create a blank Python file

Create a Python file in the Web directory, the code is as follows:

from pyecharts.charts import Polar
from pyecharts import options as opts

# 构造数据
data = [('rose1', [10, 20, 30, 40, 50, 40, 30, 20, 10]),
        ('rose2', [20, 30, 10, 40, 60, 30, 20, 30, 20])]

# 构造极坐标图
polar = Polar().add_schema(radius_axis_opts=opts.PolarRadiusAxisOpts(),
                           angle_axis_opts=opts.PolarAngleAxisOpts(),
                           )

# 添加数据
for name, values in data:
    polar.add(name, values, type_='barAngle', stack='stack1')

# 设置全局配置项
polar.set_global_opts(title_opts=opts.TitleOpts(title='极坐标图'))

# 生成HTML文件
polar.render('polar.html')

3. Custom chart style

After using ECharts and Python interface to generate polar coordinate chart, you can customize the chart Style to beautify the chart, here is some sample code.

Customized polar axis labels

By adjusting parameters such as the text size and color of the polar axis labels, you can beautify the display effect of the polar coordinate chart, for example:

polar.set_global_opts(title_opts=opts.TitleOpts(title='极坐标图'),
                      legend_opts=opts.LegendOpts(is_show=False),
                      polar_opts=opts.PolarOpts(radius='60%'),
                      angle_axis_opts=opts.PolarAngleAxisOpts(
                          axislabel_opts=opts.LabelOpts(
                              font_size=12, color='blue'
                          )
                      ),
                      radius_axis_opts=opts.PolarRadiusAxisOpts(
                          axislabel_opts=opts.LabelOpts(
                              font_size=16, color='red'
                          )
                      )
                      )

Modify the legend position

By controlling the position and style of the legend (Legend), you can beautify the display effect of the chart, for example:

polar.set_global_opts(title_opts=opts.TitleOpts(title='极坐标图'),
                      legend_opts=opts.LegendOpts(is_show=True, pos_top='5%', pos_right='5%'),
                      polar_opts=opts.PolarOpts(radius='60%'),
                      angle_axis_opts=opts.PolarAngleAxisOpts(
                          axislabel_opts=opts.LabelOpts(
                              font_size=12, color='blue'
                          )
                      ),
                      radius_axis_opts=opts.PolarRadiusAxisOpts(
                          axislabel_opts=opts.LabelOpts(
                              font_size=16, color='red'
                          )
                      )
                      )

Modify Background color and gradient color

By adjusting parameters such as background color and gradient color, you can beautify the display effect of the chart, for example:

polar.set_global_opts(title_opts=opts.TitleOpts(title='极坐标图'),
                      legend_opts=opts.LegendOpts(is_show=True, pos_top='5%', pos_right='5%'),
                      polar_opts=opts.PolarOpts(radius='60%', background_color='#f2f2f2'),
                      angle_axis_opts=opts.PolarAngleAxisOpts(
                          axislabel_opts=opts.LabelOpts(
                              font_size=12, color='blue'
                          )
                      ),
                      radius_axis_opts=opts.PolarRadiusAxisOpts(
                          axislabel_opts=opts.LabelOpts(
                              font_size=16, color='red'
                          )
                      ),
                      tooltip_opts=opts.TooltipOpts(
                          formatter="{b} ({c})",
                          trigger='axis',
                          axis_pointer_type='cross'
                      ),
                      visualmap_opts=opts.VisualMapOpts(
                          type_="continuous",
                          is_piecewise=False,
                          pos_right='5%',
                          pos_top='15%',
                          min_=10,
                          max_=60,
                          range_text=['High', 'Low'],
                          range_color=['#d7e4bd', '#b02b2c'],
                      )
                      )

Summary:

Use ECharts It is very simple to generate polar plots with the Python interface. You only need to install the ECharts and pyecharts libraries and write some simple Python codes to achieve various complex data visualizations. Among them, custom chart styles can make polar coordinate charts more beautiful and personalized, and can be adjusted according to your own needs.

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