Python使用Matplotlib绘制热力图详解

阿橙

发布时间：2026-10-13| 3人浏览过

原创

本文介绍如何使用Python的Matplotlib库绘制热力图，通过皮尔逊相关系数分析变量关联性。示例代码包含中文显示设置、坐标轴标签定义及颜色映射配置，适用于数据相关性可视化场景。

本文提供了Python绘制热力图的具体实现代码，供读者参考学习。

在Python中，热力图通常用于展示变量间的皮尔逊相关系数，从而直观反映两者之间的关联程度。

#encoding:utf-8
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from matplotlib import cm
from matplotlib import axes
import pylab
pylab.mpl.rcParams['font.sans-serif'] = ['SimHei']#防止中文乱码
pylab.mpl.rcParams['axes.unicode_minus'] = False#防止中文乱码
def draw_heatmap(data,xlabels,ylabels):
 cmap = cm.Blues
 figure=plt.figure(facecolor='w')
 ax=figure.add_subplot(2,1,1,position=[0.1,0.15,0.8,0.8])
 ax.set_yticks(range(len(ylabels)))
 ax.set_yticklabels(ylabels)
 ax.set_xticks(range(len(xlabels)))
 ax.set_xticklabels(xlabels)
 vmax=data[0][0]
 vmin=data[0][0]
 for i in data:
  for j in i:
   if j>vmax:
    vmax=j
   if j<vmin:
    vmin=j
 map=ax.imshow(data,interpolation='nearest',cmap=cmap,aspect='auto',vmin=vmin,vmax=vmax)
 cb = plt.colorbar(mappable=map,cax=None,ax=None,shrink=0.5)
 plt.xticks(rotation=90) # 将字体进行旋转
 plt.yticks(rotation=360)
 plt.show()
data = pd.read_csv('test.csv',encoding='gbk')
a = [[1063620,291288,213322,120233,972752,1896180,483012,1609664,413538,778350,420643,212472,2599510,1574470,254141],[258914,48064,31948,19534,142792,295841,69143,291524,78926,90238,79336,47938,454656,271486,35304],[517687,135483,68418,66670,301544,777798,307562,810314,234086,238859,145959,125258,1480672,764612,153237],[277377,38581,31145,17612,121162,254534,60746,253148,62054,93499,63346,36422,356036,212109,27758],[19030,2835,2174,1575,7325,18258,6837,23457,5340,5277,5120,4017,34122,21314,2961],[351720,107299,57186,55485,337368,563436,188368,563515,128047,178664,117886,72451,798121,444825,65599]]
 
 
xlabels= [u'3C电子',u'房产家居',u'服饰',u'健康保健',u'金融财经',u'旅游',u'美容美体',u'汽车',u'求职&教育',u'奢侈品',u'体育健身',u'网游',u'休闲&爱好',u'影视娱乐',u'孕婴育儿']
ylabels= ['iphoneX','mix2','oppor11','samsang','vivo','mate10']
draw_heatmap(a,xlabels,ylabels)

运行上述代码后的输出结果如下所示。