Create app.py

app.py

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+import pandas as pd
+import requests
+import plotly.express as px
+import streamlit as st
+import matplotlib.font_manager as fm
+import matplotlib as mpl
+
+# Download and set custom font
+font_url = "https://drive.google.com/uc?id=1eGAsTN1HBpJAkeVM57_C7ccp7hbgSz3_&export=download"
+font_response = requests.get(font_url)
+with open("TaipeiSansTCBeta-Regular.ttf", "wb") as font_file:
+    font_file.write(font_response.content)
+
+# Register the font with matplotlib
+fm.fontManager.addfont("TaipeiSansTCBeta-Regular.ttf")
+mpl.rc('font', family='Taipei Sans TC Beta')
+
+# Function to download and load CSV into a DataFrame
+def download_csv(url, filename):
+    response = requests.get(url)
+    with open(filename, "wb") as file:
+        file.write(response.content)
+    df = pd.read_csv(filename)
+    df = df.fillna(0)  # Fill missing values with 0
+    return df
+
+# URLs to download data from
+urls = [
+    "https://mopsfin.twse.com.tw/opendata/t187ap46_L_1.csv",  # Original file - ESG
+    "https://mopsfin.twse.com.tw/opendata/t187ap46_O_2.csv",  # Renewable Energy
+    "https://mopsfin.twse.com.tw/opendata/t187ap46_L_6.csv"   # Board of Directors
+]
+
+# Filenames to save CSV data
+filenames = ["data01.csv", "data02.csv", "data03.csv"]
+
+# Download and process each CSV
+dfs = [download_csv(url, filename) for url, filename in zip(urls, filenames)]
+
+# Streamlit app title
+st.title("ESG Data Visualization with Streamlit")
+
+# Pie Chart for the first DataFrame
+st.header("Pie Chart for ESG Data")
+fig_pie = px.pie(
+    dfs[0], 
+    names=dfs[0].columns[0], 
+    values=dfs[0].columns[1], 
+    title="Pie Chart for ESG Data"
+)
+fig_pie.update_layout(font_family="Taipei Sans TC Beta")
+st.plotly_chart(fig_pie)
+
+# Bar Chart for the second DataFrame
+st.header("Bar Chart for Renewable Energy Data")
+fig_bar = px.bar(
+    dfs[1], 
+    x=dfs[1].columns[0], 
+    y=dfs[1].columns[1], 
+    title="Bar Chart for Renewable Energy Data"
+)
+fig_bar.update_layout(font_family="Taipei Sans TC Beta")
+st.plotly_chart(fig_bar)
+
+# Optionally, show the raw DataFrames
+st.header("Raw DataFrames")
+for i, df in enumerate(dfs):
+    st.subheader(f"DataFrame {i + 1}")
+    st.dataframe(df)