Learn to draw dendrograms and radar charts in Python in five minutes

Learn to draw dendrograms and radar charts with Python in five minutes

In data visualization, dendrograms and radar charts are two commonly used chart forms. Treemaps are used to show hierarchical structures, while radar charts are used to compare data across multiple dimensions. This article will introduce how to draw these two charts using Python and provide specific code examples.

1. Drawing dendrograms

There are multiple libraries in Python that can be used to draw dendrograms, such as matplotlib and graphviz. The following uses the matplotlib library as an example to demonstrate how to draw a tree diagram.

First, we need to install the matplotlib library. You can use the pip command to install:

pip install matplotlib

After the installation is complete, you can use the following code to draw a simple tree diagram:

import matplotlib.pyplot as plt

# 创建数据
data = {'A': ['B', 'C'],
        'B': ['D', 'E'],
        'C': ['F', 'G']}

# 递归函数，遍历数据字典，并绘制树状图
def plot_tree(data, parent=None, depth=0):
    for node in data.get(parent, []):
        plt.plot([parent, node], [depth, depth + 1], 'bo-')  # 绘制节点连接线
        plot_tree(data, node, depth + 1)  # 递归调用，遍历子节点

# 绘制树状图
plot_tree(data)
plt.show()

Run the above code to display a simple tree diagram on the screen. Tree diagram, in which A is the root node, B and C are child nodes, and D, E, F and G are leaf nodes.

2. Drawing radar charts

To draw radar charts, you need to use another sub-library of the matplotlib library, mpl_toolkits.mplot3d. The following uses the mpl_toolkits library as an example to demonstrate how to draw a radar chart.

First, we need to install the mpl_toolkits library. You can use the pip command to install:

pip install mpl_toolkits

After the installation is complete, you can use the following code to draw a simple radar chart:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np

# 创建数据
labels = ['A', 'B', 'C', 'D', 'E']
values = np.random.randint(1, 10, len(labels))

# 绘制雷达图
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.plot(np.cos(np.linspace(0, 2*np.pi, len(labels)+1))[:-1],
        np.sin(np.linspace(0, 2*np.pi, len(labels)+1))[:-1],
        np.zeros(len(labels)), 'k-')  # 绘制雷达图主轴
ax.fill_between(np.cos(np.linspace(0, 2*np.pi, len(labels)+1))[:-1],
                np.sin(np.linspace(0, 2*np.pi, len(labels)+1))[:-1],
                np.zeros(len(labels)), alpha=0.25)  # 绘制雷达图背景

ax.plot(np.cos(np.linspace(0, 2*np.pi, len(labels)+1))[:-1],
        np.sin(np.linspace(0, 2*np.pi, len(labels)+1))[:-1],
        values, 'bo-')  # 绘制雷达图数据点

# 设置坐标轴标签
ax.set_xticks(np.cos(np.linspace(0, 2*np.pi, len(labels)+1))[:-1])
ax.set_yticks(np.sin(np.linspace(0, 2*np.pi, len(labels)+1))[:-1])
ax.set_xticklabels(labels)
ax.set_yticklabels([])

plt.show()

Run the above code to display a simple radar on the screen Figure, where A, B, C, D, and E are different dimensions, and values ​​are the data points of the corresponding dimensions.

Summary

Through the introduction of this article, we have learned how to use Python to draw dendrograms and radar charts. Treemaps are used to show hierarchical structures, while radar charts are used to compare data across multiple dimensions. Through the functions and methods in the matplotlib library and mpl_toolkits library, we can easily draw a variety of tree diagrams and radar charts to achieve visual display of data.

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