Upload 10 files
Browse files- .gitattributes +5 -0
- Dockerfile +21 -21
- app.py +68 -0
- bokeh_example.html +0 -0
- data_traffic_accidents.xlsx +3 -0
- folium_example.html +127 -0
- network.png +3 -0
- photo1.jpg +3 -0
- photo2.jpg +3 -0
- requirements.txt +10 -3
- wordcloud.png +3 -0
.gitattributes
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@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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data_traffic_accidents.xlsx filter=lfs diff=lfs merge=lfs -text
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network.png filter=lfs diff=lfs merge=lfs -text
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photo1.jpg filter=lfs diff=lfs merge=lfs -text
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photo2.jpg filter=lfs diff=lfs merge=lfs -text
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wordcloud.png filter=lfs diff=lfs merge=lfs -text
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Dockerfile
CHANGED
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@@ -1,21 +1,21 @@
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FROM python:3.9-slim
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WORKDIR /app
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RUN apt-get update && apt-get install -y \
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build-essential \
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curl \
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software-properties-common \
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git \
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&& rm -rf /var/lib/apt/lists/*
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COPY requirements.txt
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EXPOSE 8501
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HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
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ENTRYPOINT ["streamlit", "run", "
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FROM python:3.9-slim
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WORKDIR /app
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RUN apt-get update && apt-get install -y \
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build-essential \
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curl \
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software-properties-common \
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git \
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&& rm -rf /var/lib/apt/lists/*
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COPY requirements.txt .
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RUN pip3 install -r requirements.txt
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COPY . .
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EXPOSE 8501
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HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
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ENTRYPOINT ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]
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app.py
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@@ -0,0 +1,68 @@
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import streamlit as st
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import pandas as pd
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import matplotlib.pyplot as plt
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import pandas_bokeh
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import folium
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from streamlit_folium import st_folium
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import requests
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st.markdown("# κ²½ν¬λ μΈκ·Ό κ°μ±λΉ μ’μ λ§μ§ λμ΄ ... 건κ°μμ 'κΈμ'")
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st.markdown("#### 'λΆμ, μ€μ, νμμ μΌμκΉμ§ λ€μν μμ μΈκ² μ 곡")
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st.markdown("#### μΆμ νμ¬μ νλ²κ±°-ν«λκ·Έ νΈλνΈλλ λ±μ₯")
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st.write('''κ²½ν¬λ μΈκ·Όμλ μ΅κ·Ό κ°μ±λΉ μ’μ λ§μ§λ€μ΄ μμ λ€μ΄μλ©° νμλ€ μ¬μ΄μμ μΈκΈ°λ₯Ό λκ³ μλ€. νμ λ λνμ μ§κ°μ¬μ μ λ§λ μ λ ΄ν κ°κ²©κ³Ό λ€μνκ³ νλ¦¬ν° λμ λ©λ΄λ‘ μ
μλ¬Έμ΄ λλ©΄μ μ±μ
μ€μΈ κ²μ΄λ€.
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μ΄μ²λΌ κ²½ν¬λ μ£Όλ³μλ νμλ€ μ¬μ΄μμ μ
μλ¬Έμ΄ μμν κ°μ±λΉ λ§μ§λ€μ΄ λ§λ€. λΏλ§ μλλΌ λν μΆμ λλ©΄ λ€μν [νΈλνΈλ](https://namu.wiki/w/%ED%91%B8%EB%93%9C%20%ED%8A%B8%EB%9F%AD)λ€λ μ°Ύμμ μ λ ΄νκ³ λ§μλ λ©λ΄λ₯Ό μ 보μ΄λ©° ν° μΈκΈ°λ₯Ό λλ€.
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μ΅κ·Ό λ¬Όκ°μμΉμΌλ‘ μΈν΄ μΈμλΉ λΆλ΄μ΄ ν° λνμλ€μκ² μ΄λ° κ°μ±λΉ λμ λ§μ§κ³Ό νΈλνΈλμ νμλ°μ λ§νλ€.''' )
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st.write("<br><br><br>", unsafe_allow_html=True) # 3μ€ λμ΄μ°κΈ°
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st.markdown("#### μΌ κ² λΉμ§λ‘? 건κ°μμ μ 보μ΄λ€")
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st.markdown("#### μ λ ΄νκ³ νΈμ§νμ§λ§ μμκ³Ό 건κ°μ μ€μ’
")
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st.write('''κ²½ν¬λ μΈκ·Ό λ§μ§λ€μ λ©λ΄λ₯Ό μμΈν 보면 건κ°ν μμ¬λ£λ μμμ ν¬κ² κ³ λ €λμ§ μμ κ² κ°μ μμ¬μμ΄ λ¨λλ€.
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λνκ°μμ 건κ°μ λν κ³ λ―Όλ³΄λ€ μΈκ³ λ°°λΆλ₯΄κ² λ¨Ήμ μ μλ κ³³μ΄ μΈκΈ°μΈ μ μ μ΄ν΄λλ€. νμ§λ§ νλ²μ―€μ μμκ³Ό 건κ°μ μκ°ν΄λ΄μΌ νλ€.
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μ²λ
λλΆν° 건κ°μμ μμ·¨νκ³ μ¬λ°λ₯Έ μμ΅κ΄μ κ°μ ΈμΌνκΈ° λλ¬Έμ΄λ€.''' )
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st.markdown("#### λνκ° λ¨Ήκ±°λ¦¬, 건κ°μ κ· νμ μ‘μμΌ ν λ")
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st.write(''' μ λ¬Έκ° OOOμ λ°λ₯΄λ©΄ ~~~~~''')
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# μ¬μ§ μ½μ
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st.image('photo1.jpg', caption='μ§λ 4μ20μΌ κ²½ν¬λ κ΅λ΄μμ νμλ€μ΄ νΈλνΈλμμ μμμ ꡬ맀νκ³ μλ€')
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st.image('photo2.jpg', caption='κ²½ν¬λ κ·Όμ² λ§μ§ μ§λ(--- μ 곡)')
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# λ°μ΄ν° λΆλ¬μ€κΈ°
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df = pd.read_excel('data_traffic_accidents.xlsx', index_col=0)
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st.write('λ€μ λ°μ΄ν°λ μ κ΅μ κ΅ν΅μ¬κ³ λ₯Ό μ§μλ³λ‘ μ§κ³ν κ²μ΄λ€')
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#st.write(df)
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# κ²μμ΄ μ
λ ₯ λ°μ λ°μ΄ν° μ νμ μΌλ‘ μΆλ ₯
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query = st.text_input('μ΄ κ³³μ μ§μλͺ
(μꡰꡬλμλ©΄)μ μ
λ ₯νλ©΄ κ΄λ ¨ λ°μ΄ν°λ§ κ²μν΄ λ³΄μ¬μ€λλ€', key='region1_input')
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df['select1']=df['μ¬κ³ μ§μμμΉλͺ
'].apply(lambda x: 1 if query in x else 0)
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st.write('κ²μ κ²°κ³Ό:', df[df['select1']==1])
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# κ΅ν΅μ¬κ³ μ νκ³Ό μ°λμ λ°λ₯Έ pivot table 보μ¬μ£ΌκΈ°
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df_pivot=df.pivot_table(index='μ¬κ³ μ νꡬλΆ', columns='μ¬κ³ μ°λ', values='μ¬κ³ 건μ', aggfunc='sum')
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df_heatmap=df_pivot.style.background_gradient(cmap='Oranges').format("{:.2f}")
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st.write('λ€μ νλ κ΅ν΅μ¬κ³ 건μλ₯Ό μ νκ³Ό μ°λμ λ°λΌ ꡬλΆν κ²μ΄λ€', df_heatmap)
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# μλν΄λΌμ°λ 보μ¬μ£ΌκΈ°
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st.write('μ£Όμ λ¨μ΄λ€μ μλν΄λΌμ°λλ‘ λ³΄μ¬μ£Όλ©΄ λ€μκ³Ό κ°λ€')
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st.image('wordcloud.png')
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# μ°κ²°λ§κ·Έλ¦Ό 보μ¬μ£ΌκΈ°
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st.write('''μ·¨μ¬νμ μ£Όμ λ¨μ΄λ€ κ°μ 곡λμΆννλ κ΄κ³λ₯Ό λ°νμΌλ‘ μλ―Έμ°κ²°λ§μ κ·Έλ €λ³΄μλ€.
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λΆμκ²°κ³Ό, ~~μ€λͺ
~~''')
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st.image('network.png')
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# κ·Έλν html 보μ¬μ£ΌκΈ°
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st.write('''μ·¨μ¬νμ κ΅ν΅μ¬κ³ μ¬κ³ 건μμ μ¬λ§μμ κ°μ κ΄κ³λ₯Ό κ·Έλνλ‘ νμνλ€ λΆμκ²°κ³Ό, ~~μ€λͺ
~~
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κ·Έλν κ° μ μ λ§μ°μ€λ₯Ό λμΌλ©΄ μ§μ μ λ³΄κ° λνλλ€''')
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with open('bokeh_example.html', 'r', encoding='utf-8') as f:
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html_content1 = f.read()
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st.components.v1.html(html_content1, height=500) # markdownλ³΄λ€ λ³΅μ‘ν html νμΌ μλμ κ°ν¨
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# μ§λ html 보μ¬μ£ΌκΈ°
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st.write('''μ·¨μ¬νμ μμΈμ μ£Όμ λνμ μμΉμ μ 보λ₯Ό μ§λμ νκΈ°ν΄ λ³΄μλ€. λΆμκ²°κ³Ό, ~~μ€λͺ
~~
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μ§λ μ νκΈ° μ§μ μ λ§μ°μ€λ₯Ό λμΌλ©΄ κ΄λ ¨ μ λ³΄κ° λνλλ€''')
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with open('folium_example.html', 'r', encoding='utf-8') as f:
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html_content2 = f.read()
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st.components.v1.html(html_content2, height=500)
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bokeh_example.html
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The diff for this file is too large to render.
See raw diff
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data_traffic_accidents.xlsx
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version https://git-lfs.github.com/spec/v1
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oid sha256:6cbe09c6afa2d36d525aaf0e9efd7a726c296f8b59ab50b2703979e52d478469
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size 5148724
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folium_example.html
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<!DOCTYPE html>
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<html>
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<head>
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<meta http-equiv="content-type" content="text/html; charset=UTF-8" />
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<script>
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L_NO_TOUCH = false;
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L_DISABLE_3D = false;
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</script>
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<style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
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<style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
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<script src="https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js"></script>
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| 15 |
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<script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
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| 16 |
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<script src="https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js"></script>
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<script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
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| 18 |
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css"/>
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| 19 |
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css"/>
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| 20 |
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<link rel="stylesheet" href="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css"/>
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| 21 |
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css"/>
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| 22 |
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<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
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| 23 |
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css"/>
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<meta name="viewport" content="width=device-width,
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initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
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<style>
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| 28 |
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#map_ed45e426e4e625d1487296ea56b9516c {
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| 29 |
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position: relative;
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| 30 |
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width: 100.0%;
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| 31 |
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height: 100.0%;
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| 32 |
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left: 0.0%;
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| 33 |
+
top: 0.0%;
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| 34 |
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}
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| 35 |
+
.leaflet-container { font-size: 1rem; }
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| 36 |
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</style>
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| 37 |
+
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| 38 |
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</head>
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| 39 |
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<body>
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| 40 |
+
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| 41 |
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<div class="folium-map" id="map_ed45e426e4e625d1487296ea56b9516c" ></div>
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| 43 |
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</body>
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<script>
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| 46 |
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var map_ed45e426e4e625d1487296ea56b9516c = L.map(
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| 49 |
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"map_ed45e426e4e625d1487296ea56b9516c",
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| 50 |
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{
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| 51 |
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center: [37.567, 126.978],
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| 52 |
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crs: L.CRS.EPSG3857,
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| 53 |
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zoom: 12,
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| 54 |
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zoomControl: true,
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| 55 |
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preferCanvas: false,
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| 56 |
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}
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| 57 |
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);
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| 58 |
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| 61 |
+
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| 62 |
+
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var tile_layer_41a0f1aae01a4ef313b7f6ff18d8d25a = L.tileLayer(
|
| 64 |
+
"https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
|
| 65 |
+
{"attribution": "Data by \u0026copy; \u003ca target=\"_blank\" href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca target=\"_blank\" href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
|
| 66 |
+
).addTo(map_ed45e426e4e625d1487296ea56b9516c);
|
| 67 |
+
|
| 68 |
+
|
| 69 |
+
var marker_40a0d3b3071e46ce44c855dd28b7197e = L.marker(
|
| 70 |
+
[37.592, 127.052],
|
| 71 |
+
{}
|
| 72 |
+
).addTo(map_ed45e426e4e625d1487296ea56b9516c);
|
| 73 |
+
|
| 74 |
+
|
| 75 |
+
var popup_c08cc328a5125b3fad894b79123b4297 = L.popup({"maxWidth": 500});
|
| 76 |
+
|
| 77 |
+
|
| 78 |
+
|
| 79 |
+
var html_b3968776944b9326f1cbe8befde69049 = $(`<div id="html_b3968776944b9326f1cbe8befde69049" style="width: 100.0%; height: 100.0%;">κ²½ν¬λ</div>`)[0];
|
| 80 |
+
popup_c08cc328a5125b3fad894b79123b4297.setContent(html_b3968776944b9326f1cbe8befde69049);
|
| 81 |
+
|
| 82 |
+
|
| 83 |
+
|
| 84 |
+
marker_40a0d3b3071e46ce44c855dd28b7197e.bindPopup(popup_c08cc328a5125b3fad894b79123b4297)
|
| 85 |
+
;
|
| 86 |
+
|
| 87 |
+
|
| 88 |
+
|
| 89 |
+
|
| 90 |
+
marker_40a0d3b3071e46ce44c855dd28b7197e.bindTooltip(
|
| 91 |
+
`<div>
|
| 92 |
+
ν΄λ¦
|
| 93 |
+
</div>`,
|
| 94 |
+
{"sticky": true}
|
| 95 |
+
);
|
| 96 |
+
|
| 97 |
+
|
| 98 |
+
var marker_d35363d0a8fe53316869ae36187a1457 = L.marker(
|
| 99 |
+
[37.56, 126.937],
|
| 100 |
+
{}
|
| 101 |
+
).addTo(map_ed45e426e4e625d1487296ea56b9516c);
|
| 102 |
+
|
| 103 |
+
|
| 104 |
+
var popup_d92fbb3aa56507683aedb49a771e3e7a = L.popup({"maxWidth": 500});
|
| 105 |
+
|
| 106 |
+
|
| 107 |
+
|
| 108 |
+
var html_81e8244e5d4ab9b0ada91f9b0c8ffa5e = $(`<div id="html_81e8244e5d4ab9b0ada91f9b0c8ffa5e" style="width: 100.0%; height: 100.0%;">μ°μΈλ</div>`)[0];
|
| 109 |
+
popup_d92fbb3aa56507683aedb49a771e3e7a.setContent(html_81e8244e5d4ab9b0ada91f9b0c8ffa5e);
|
| 110 |
+
|
| 111 |
+
|
| 112 |
+
|
| 113 |
+
marker_d35363d0a8fe53316869ae36187a1457.bindPopup(popup_d92fbb3aa56507683aedb49a771e3e7a)
|
| 114 |
+
;
|
| 115 |
+
|
| 116 |
+
|
| 117 |
+
|
| 118 |
+
|
| 119 |
+
marker_d35363d0a8fe53316869ae36187a1457.bindTooltip(
|
| 120 |
+
`<div>
|
| 121 |
+
ν΄λ¦
|
| 122 |
+
</div>`,
|
| 123 |
+
{"sticky": true}
|
| 124 |
+
);
|
| 125 |
+
|
| 126 |
+
</script>
|
| 127 |
+
</html>
|
network.png
ADDED
|
Git LFS Details
|
photo1.jpg
ADDED
|
Git LFS Details
|
photo2.jpg
ADDED
|
Git LFS Details
|
requirements.txt
CHANGED
|
@@ -1,3 +1,10 @@
|
|
| 1 |
-
|
| 2 |
-
pandas
|
| 3 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
numpy==1.23.5 # bool8 λ¬Έμ μλ λ§μ§λ§ λ²μ
|
| 2 |
+
pandas==1.5.3 # numpy 1.23.xμ μ λ§μ
|
| 3 |
+
openpyxl==3.1.2
|
| 4 |
+
bokeh==2.4.3 # pandas-bokehλ λ§λ λ²μ
|
| 5 |
+
pandas-bokeh==0.5.5 # bokeh 2.4.3μ λ§λ μμ λ²μ
|
| 6 |
+
matplotlib==3.7.3
|
| 7 |
+
folium==0.14.0
|
| 8 |
+
streamlit-folium==0.10.0 # Python 3.10 μ§μ λ§μ§λ§ λ²μ
|
| 9 |
+
streamlit==1.26.0 # 3.10μ΄λ μ λ§λ μμ λ²μ
|
| 10 |
+
requests==2.31.0
|
wordcloud.png
ADDED
|
Git LFS Details
|