聚類分析樹狀圖的初探

參考官方文檔：https://docs.scipy.org/doc/scipy/reference/index.html

　　此次使用聚類分析是因為文章需要，然后參考官方文檔簡單制作滿足分析要求的樹狀圖。

　　因為到時候在A4紙上需要把三個圖排版一下，所以在輸出的時候就把圖片設置的比較小。

import pandas as pd
import matplotlib.pyplot as plt
from scipy.cluster import hierarchy

plt.rcParams['font.sans-serif'] = ['SimHei'] #解決中文顯示
plt.rcParams['axes.unicode_minus'] = False #解決符號無法顯示
#設置顏色
#hierarchy.set_link_color_palette(['m', 'c', 'y', 'k'])

df = pd.read_excel('品種日產量聚類.xlsx',sheet_name='zaoju')
fig, axes = plt.subplots(1,figsize=(4,4))
Z = hierarchy.linkage(df,'centroid',metric='euclidean')
names = ['E1','E2','E3','E4','E5','E6','E7','E8','E9','E10','E11','E12','E13','E14','E15','E16','E17','E18','E19','E20','E21','E22','E23','E24','E25','E26','E27','E28']

dn=hierarchy.dendrogram(Z,orientation='right',labels=names)
print(dn['color_list'])

plt.show()
#plt.savefig('早稻聚類01.jpg',dpi=300)

 

import pandas as pd
import matplotlib.pyplot as plt
from scipy.cluster import hierarchy

fig, axes = plt.subplots(1,figsize=(4,4))

# 晚粳聚
df3 = pd.read_excel('品種日產量聚類.xlsx',sheet_name='晚粳聚')
Z3 = hierarchy.linkage(df3,'centroid',metric='euclidean')
names3 = ['L24','L25','L26','L27','L28','L29',
          'L30','L31','L32','L33','L34','L35',
          'L36','L37','L38','L39','L40','L41',
          'L42','L43','L44','L45','L46','L47','L48','L49']
dn3=hierarchy.dendrogram(Z3,orientation='right',labels=names3)
#dn3=hierarchy.dendrogram(Z3,orientation='right')
#plt.show()
plt.savefig('晚粳聚01.jpg',dpi=300)

 

import pandas as pd
import matplotlib.pyplot as plt
from scipy.cluster import hierarchy

fig, axes = plt.subplots(1,figsize=(4,4))

# 晚秈聚
df2 = pd.read_excel('品種日產量聚類.xlsx',sheet_name='晚秈聚')
Z2 = hierarchy.linkage(df2,'centroid',metric='euclidean')
names2 = ['L1','L2','L3','L4','L5','L6','L7',
          'L8','L9','L10','L11','L12','L13','L14',
          'L15','L16','L17','L18','L19','L20','L21',
         'L22','23']
dn2=hierarchy.dendrogram(Z2,orientation='right',labels=names2)

#plt.show()
plt.savefig('晚秈01.jpg',dpi=300)