制图环境：

pycharm

python-3.6

Seaborn-0.8

热图

import numpy as np

import seaborn as sns

import matplotlib.pyplot as plt

sns.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 plt

import seaborn as sns

sns.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 plt

import seaborn as sns

sns.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 plt

import seaborn as sns

sns.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 plt

import seaborn as sns

sns.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 plt

import seaborn as sns

sns.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_heatmap

label_y = ax.get_yticklabels()

plt.setp(label_y, rotation=360, horizontalalignment='left')

plt.show()

import matplotlib.pyplot as plt

import seaborn as sns

sns.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_heatmap

label_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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