Python-Seaborn热图绘制的实现方法

Python  /  管理员 发布于 7年前   399

制图环境：
pycharm
python-3.6
Seaborn-0.8

热图

import numpy as npimport seaborn as snsimport matplotlib.pyplot as pltsns.set()np.random.seed(0)uniform_data = np.random.rand(10, 12)ax = sns.heatmap(uniform_data)plt.show()

# 改变颜色映射的值范围ax = sns.heatmap(uniform_data, vmin=0, vmax=1)plt.show()

uniform_data = np.random.randn(10, 12)#为以0为中心的数据绘制一张热图ax = sns.heatmap(uniform_data, center=0)plt.show()

import matplotlib.pyplot as pltimport seaborn as snssns.set()#用行和列标签绘制flights_long = sns.load_dataset("flights")flights = flights_long.pivot("month", "year", "passengers")# 绘制x-y-z的热力图，比如 年-月-销量 的热力图f, ax = plt.subplots(figsize=(9, 6))sns.heatmap(flights, ax=ax)#设置坐标字体方向label_y = ax.get_yticklabels()plt.setp(label_y, rotation=360, horizontalalignment='right')label_x = ax.get_xticklabels()plt.setp(label_x, rotation=45, horizontalalignment='right')plt.show()

import matplotlib.pyplot as pltimport seaborn as snssns.set()flights_long = sns.load_dataset("flights")flights = flights_long.pivot("month", "year", "passengers")# 绘制x-y-z的热力图，比如 年-月-销量 的热力图f, ax = plt.subplots(figsize=(9, 6))#使用不同的颜色sns.heatmap(flights, fmt="d",cmap='YlGnBu', ax=ax)#设置坐标字体方向label_y = ax.get_yticklabels()plt.setp(label_y, rotation=360, horizontalalignment='right')label_x = ax.get_xticklabels()plt.setp(label_x, rotation=45, horizontalalignment='right')plt.show()

注释热图

import matplotlib.pyplot as pltimport seaborn as snssns.set()flights_long = sns.load_dataset("flights")flights = flights_long.pivot("month", "year", "passengers")# 绘制x-y-z的热力图，比如 年-月-销量 的热力图f, ax = plt.subplots(figsize=(9, 6))#绘制热力图，还要将数值写到热力图上sns.heatmap(flights, annot=True, fmt="d", ax=ax)#设置坐标字体方向label_y = ax.get_yticklabels()plt.setp(label_y, rotation=360, horizontalalignment='right')label_x = ax.get_xticklabels()plt.setp(label_x, rotation=45, horizontalalignment='right')plt.show()

import matplotlib.pyplot as pltimport seaborn as snssns.set()flights_long = sns.load_dataset("flights")flights = flights_long.pivot("month", "year", "passengers")# 绘制x-y-z的热力图，比如 年-月-销量 的热力图f, ax = plt.subplots(figsize=(9, 6))#绘制热力图，还要将数值写到热力图上#每个网格上用线隔开sns.heatmap(flights, annot=True, fmt="d", linewidths=.5, ax=ax)#设置坐标字体方向label_y = ax.get_yticklabels()plt.setp(label_y, rotation=360, horizontalalignment='right')label_x = ax.get_xticklabels()plt.setp(label_x, rotation=45, horizontalalignment='right')plt.show()

聚类热图

import matplotlib.pyplot as pltimport seaborn as snssns.set()flights_long = sns.load_dataset("flights")flights = flights_long.pivot("month", "year", "passengers")# 绘制x-y-z的热力图，比如 年-月-销量 的聚类热图g= sns.clustermap(flights, fmt="d",cmap='YlGnBu')ax = g.ax_heatmaplabel_y = ax.get_yticklabels()plt.setp(label_y, rotation=360, horizontalalignment='left')plt.show()

import matplotlib.pyplot as pltimport seaborn as snssns.set(color_codes=True)iris = sns.load_dataset("iris")species = iris.pop("species")#设置图片大小g= sns.clustermap(iris, fmt="d",cmap='YlGnBu',figsize=(6,9))ax = g.ax_heatmaplabel_y = ax.get_yticklabels()plt.setp(label_y, rotation=360, horizontalalignment='left')#设置图片名称，分辨率，并保存plt.savefig('cluster.tif',dpi = 300)plt.show()

注：更多参数的用法请查阅官方文档

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