File size: 2,193 Bytes
5df90c0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e025c13
5df90c0
e025c13
5df90c0
e025c13
5df90c0
 
 
 
 
 
 
 
e025c13
5df90c0
 
e025c13
5df90c0
 
 
 
 
 
e025c13
5df90c0
 
 
 
 
 
e025c13
5df90c0
1325cc2
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt
import pandas_bokeh


# 글 쓰기(링크 삽입)
st.title('VIETNAM DONGDAEMUN FOOOOOOOOOD!!!!!!!!!')

st.header('Selection of Vietnamese Restaurants in Dongdaemun Area')
st.subheader('Variety of dishes from different region in Vietnam, made affordable and delicious for local taste')
st.subheader('Items such as Pho Soup, Bun Bo Hue, Cha Gio or Com Chien')
st.write('''Write something here about the booming of Vietnamese Restaurant in Korea - particularly the fast growing food scene in Dongdaemun [푸드트럭](https://namu.wiki/w/%EB%B2%A0%ED%8A%B8%EB%82%A8%20%EC%9A%94%EB%A6%AC)
.''' )

# 사진 삽입
st.image('final_image_2.jpg', caption='A Spread of Vietnamese Dishes You Might Be Able To Find')

st.image('final_image_4.jpg', caption='A popular choice everywhere: Vietnamese Pho Soup')

st.image('final_image_3.jpg', caption='Hidden Gem: Banh Xeo')


st.header('Cheap and Delicious: One can find a variety of Vietnamese Restaurant in Dongdaemun Area')
st.subheader('Hosting dishes from North to South Vietnam')
st.subheader('The almost infinite choices will leave you looking for reviews!')
st.write('''Before deciding on which dish you'd want ~ carefully browse through the Blog section for an intimate look at the local food joints''' )

# 데이터 보여주기
df_경희대맛집 = pd.read_excel('vietnam_food_dongdaemun_BLOGS.xlsx', index_col=0)
st.write('We have narrowed down to 150 most relevant blogs!!', df_경희대맛집)

df_경희대맛집_keyword = pd.read_excel('vietnam_food_KEYWORDS.xlsx', index_col=0)
st.write('블로그 글에서 가장 많이 출현한 단어는 ~~~ 설명~~~', df_경희대맛집_keyword)



# 워드클라우드 - WORDCLOUD
st.write('주요  단어들을 워드클라우드로 보여주면 다음과 같다')
st.image('final_WORDCLOUD.png')



# 연결망 분석 - NETWORK
st.write('''취재팀은 주요  단어들 간에 공동출현하는 관계를 바탕으로 의미연결망을 그려보았다.
        분석결과, ~~설명~~''')
st.image('final_NETWORK.png')