本文實例為大家分享了python繪制熱力圖的具體代碼，供大家參考，具體內容如下

python的熱力圖是用皮爾遜相關系數來查看兩者之間的關聯性。

#encoding:utf-8import numpy as npimport pandas as pdfrom matplotlib import pyplot as pltfrom matplotlib import cmfrom matplotlib import axesimport pylabpylab.mpl.rcParams['font.sans-serif'] = ['SimHei']#防止中文亂碼pylab.mpl.rcParams['axes.unicode_minus'] = False#防止中文亂碼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) # 將字體進行旋轉  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電子',u'房產家居',u'服飾',u'健康保健',u'金融財經',u'旅游',u'美容美體',u'汽車',u'求職&教育',u'奢侈品',u'體育健身',u'網游',u'休閑&愛好',u'影視娛樂',u'孕嬰育兒']ylabels= ['iphoneX','mix2','oppor11','samsang','vivo','mate10']draw_heatmap(a,xlabels,ylabels)

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