【代码模板】T-SNE 绘图

import matplotlib.pyplot as plt #绘图
from sklearn.manifold import TSNE #降维

df_ma = pd.read_excel('PNAS_HCC.xlsx',sheet_name='ma')

#标准化
df_ma_filtered = (df_ma_filtered - df_ma_filtered.mean()) / df_ma_filtered.std()

#tsne-降维
tsne = TSNE(n_components=2,perplexity=30,random_state=2024)
tsne_result = tsne.fit_transform(df_ma_filtered)

#保存
df_tsne = pd.DataFrame(data=tsne_result,columns=['Dim1','Dim2'])
df_tsne.to_excel("df_tsne.xlsx",index=False)

#可视化
plt.figure(figsize=(10,6))
plt.scatter(df_tsne['Dim1'],df_tsne['Dim2'],alpha=0.7)
plt.grid()
plt.show()