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()
          

            
# 改變顏色映射的值范圍
ax = sns.heatmap(uniform_data, vmin=0, vmax=1)
plt.show()
          

            
uniform_data = np.random.randn(10, 12)
#為以0為中心的數據繪制一張熱圖
ax = sns.heatmap(uniform_data, center=0)
plt.show()
          

            
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
#用行和列標簽繪制
flights_long = sns.load_dataset("flights")
flights = flights_long.pivot("month", "year", "passengers")
# 繪制x-y-z的熱力圖，比如 年-月-銷量 的熱力圖
f, ax = plt.subplots(figsize=(9, 6))
sns.heatmap(flights, ax=ax)
#設置坐標字體方向
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")
# 繪制x-y-z的熱力圖，比如 年-月-銷量 的熱力圖
f, ax = plt.subplots(figsize=(9, 6))
#使用不同的顏色
sns.heatmap(flights, fmt="d",cmap='YlGnBu', ax=ax)
#設置坐標字體方向
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")
# 繪制x-y-z的熱力圖，比如 年-月-銷量 的熱力圖
f, ax = plt.subplots(figsize=(9, 6))
#繪制熱力圖，還要將數值寫到熱力圖上
sns.heatmap(flights, annot=True, fmt="d", ax=ax)
#設置坐標字體方向
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")
# 繪制x-y-z的熱力圖，比如 年-月-銷量 的熱力圖
f, ax = plt.subplots(figsize=(9, 6))
#繪制熱力圖，還要將數值寫到熱力圖上
#每個網格上用線隔開
sns.heatmap(flights, annot=True, fmt="d", linewidths=.5, ax=ax)
#設置坐標字體方向
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")
# 繪制x-y-z的熱力圖，比如 年-月-銷量 的聚類熱圖
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")
#設置圖片大小
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')
#設置圖片名稱，分辨率，并保存
plt.savefig('cluster.tif',dpi = 300)
plt.show()