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HomeBackend DevelopmentPython TutorialHow to draw box plots using ECharts and Python interface

How to draw box plots using ECharts and Python interface

How to use ECharts and Python interface to draw box plots, specific code examples are required

Introduction:
Box plot (Box plot) is commonly used in statistics is a visualization method for displaying the distribution of real-number data by plotting a five-number summary of the data (minimum, lower quartile, median, upper quartile, and maximum) as well as outliers. You can intuitively understand the skewness, dispersion and outliers of the data. This article will introduce how to use ECharts and Python interfaces to draw box plots, and give specific code examples.

Step 1: Install ECharts and Python interface
First, install the dependency packages of ECharts and Python interface in the Python environment. Open the command line window and enter the following command to install the dependent package:

pip install echarts-python

Step 2: Prepare data
Before using ECharts to draw a box plot, you need to prepare data. Suppose we have a set of sample data, we will use Python lists to represent this set of data. The following is a sample data:

data = [12, 5, 7, 18, 8, 15, 9, 21, 13, 16, 7, 14]

Step 3: Use ECharts to draw box plots
Next, we draw box plots through ECharts and Python interfaces. First, import the relevant libraries and create an ECharts instance:

from echarts import Echart, Boxplot

chart = Echart('箱线图示例')

Then, create a Boxplot instance and set the title of the box plot and the data of the X-axis:

boxplot = Boxplot('数据分布')
boxplot.add('样本数据', data)

Through the above code, we A simple boxplot has been created. Next, we can make some custom configurations. For example, we can set the scale and range of the Y-axis:

boxplot.yAxis = {'name': '数据值', 'scale': True}
boxplot.xAxis = {'name': '样本'}

We can also set the style, color and size of the box plot, as shown below:

boxplot.itemStyle = {'borderColor': '#999', 'borderWidth': 1, 'color': '#ccc'}
boxplot.effectOpts = {'show': True, 'color': '#999', 'trailLength': 0.2, 'symbolSize': 3}

Finally, add the box plot Add the figure to the ECharts instance and save the ECharts instance as an HTML page:

chart.use(boxplot)
chart.save('boxplot.html')

Running the above code will generate an HTML file named boxplot.html, which contains the box Display of line graph.

Conclusion:
Through ECharts and Python interfaces, we can easily draw box plots and perform some customized configurations. This article introduces the basic steps of drawing a boxplot and gives specific code examples. I hope this article can help readers make better use of ECharts and Python interfaces for data visualization analysis.

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