数据可视化库Seaborn（3）热力图绘制

%matplotlib inline
import numpy as np
import pandas as pd
import seaborn as sns
uniform_data = np.random.rand(3,3)
print(uniform_data)
heatmap = sns.heatmap(uniform_data)  #3x3矩阵热力图表现

 [[0.42899731 0.39260745 0.58101009]
 [0.1538906  0.42498579 0.28899658]
 [0.68043676 0.40942948 0.33891072]]

 

ax = sns.heatmap(uniform_data,vmin=.2,vmax=.5)

设置调色板最大值和最小值

normal_data = np.random.randn(3,3)    #这样初始化的矩阵有正有负    randn()
print(normal_data)
ax = sns.heatmap(normal_data,center=0) #center=0 对于有正有负的数据而言颜色差异更大

 

 

flights = sns.load_dataset('flights')
# 取出这三个属性画热力图，座标点的位置是passengers
flights = flights.pivot('month', 'year', 'passengers')
ax = sns.heatmap(flights)
plt.show()


flights = sns.load_dataset('flights')
# 取出这三个属性画热力图，座标点的位置是passengers
flights = flights.pivot('month', 'year', 'passengers')
ax = sns.heatmap(flights, annot=True, fmt='d')  #实际的数值注解在图上
plt.show()

 

flights = sns.load_dataset('flights')
# 取出这三个属性画热力图，座标点的位置是passengers
flights = flights.pivot('month', 'year', 'passengers')
ax = sns.heatmap(flights, linewidths=0.5, cmap='YlGnBu', cbar=False)
plt.show()

 linewidths=0.5  设置格间距为0.5

cmap='YlGnBu'  设置调色板

cbar=False 隐藏colorbar