plt.tight_layout()
Automatically adjust the sub-picture spacing
Before
adjustment : After adjustment
fig = plt.figure(figsize=(12,5))
for i in range(5):
ax = fig.add_subplot(5, 1, i+1) # 3行3列的第一个位置
word_pro = lda.get_topic_terms(i, topn=10000)
word_pro_x = list(map(lambda x: x[0],word_pro))
word_pro_y = list(map(lambda x: x[1],word_pro))
ax.scatter(word_pro_x, word_pro_y,s=10)
plt.ylim([0,0.08]); plt.xlim(0,3300)
ax.set_title(f'topic{i+1}') # 设置小图标题
plt.tight_layout() # 自动调整子图间距
plt.xlabel('number of word') # 不设置总标题
fig.suptitle(None) # 设置大图标题
Set sub-picture title: ax.set_title()
Set the overall picture title:fig.suptitle
fig.add_subplot(1, 3, 1).set_ylabel(r'$Score_{nlp}$')
Specify a subgraph to set the total x-axis label title
# 不同星级的情感评分
fig = plt.figure(dpi=150) # dpi=150
for n, df in enumerate([df_m,df_p,df_h]):
ax = fig.add_subplot(1, 3, n+1) # 3行3列的第一个位置
df.boxplot(column='final_score',by=['star_rating'],ax=ax)
ax.set_title(f'{df.index.name}') # 不设置子标题
ax.set_xlabel(None)
ax.set_xlabel(' Star rating ')
fig.add_subplot(1, 3, 1).set_ylabel(r'$Score_{nlp}$') # 单独设置某个
plt.tight_layout() # 自动调整子图间距
fig.suptitle(None) # 不设置总标题