%%time
import gensim
import warnings
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
warnings.filterwarnings("ignore")
lda = gensim.models.LdaModel.load('./top10.model')

Wall time: 1.01 s

fiz=plt.figure(figsize=(15,30))
for i in range(10):
    df=pd.DataFrame(lda.show_topic(i), columns=['term','prob']).set_index('term')
#     df=df.sort_values('prob')
    
    plt.subplot(5,2,i+1)
    plt.title('topic '+str(i+1))
    sns.barplot(x='prob', y=df.index, data=df, label='Cities', palette='Reds_d')
    plt.xlabel('probability')
    

plt.show()