Python-Seaborn热图绘制的实现方法
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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