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Update app.py
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app.py
CHANGED
@@ -7,6 +7,7 @@ import matplotlib.pyplot as plt
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import streamlit as st
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import json
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import time
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# Set up Streamlit app title
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st.title("🐣MOMO 🆚 PCHOME 商品搜索和價格分析👁️🗨️")
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@@ -59,7 +60,7 @@ if st.button("開始搜索"):
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st.write(f"MOMO 最高價格: {momo_df['price'].max():.2f}")
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st.write(f"MOMO 最低價格: {momo_df['price'].min():.2f}")
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# MOMO visualization
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font_url = "https://drive.google.com/uc?id=1eGAsTN1HBpJAkeVM57_C7ccp7hbgSz3_&export=download"
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font_response = requests.get(font_url)
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with open("TaipeiSansTCBeta-Regular.ttf", "wb") as font_file:
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@@ -93,7 +94,6 @@ if st.button("開始搜索"):
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pchome_json_data = json.loads(pchome_response.content)
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pchome_df = pd.DataFrame(pchome_json_data['prods'])
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# Safely select only available columns
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available_columns = ['name', 'describe', 'price', 'orig']
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selected_columns = [col for col in available_columns if col in pchome_df.columns]
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pchome_df = pchome_df[selected_columns]
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@@ -141,4 +141,27 @@ if st.button("開始搜索"):
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)
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end_time = time.time()
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st.write(f"Execution time: {end_time - start_time:.2f} seconds")
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import streamlit as st
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import json
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import time
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from pytrends.request import TrendReq
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# Set up Streamlit app title
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st.title("🐣MOMO 🆚 PCHOME 商品搜索和價格分析👁️🗨️")
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st.write(f"MOMO 最高價格: {momo_df['price'].max():.2f}")
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st.write(f"MOMO 最低價格: {momo_df['price'].min():.2f}")
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# MOMO visualization
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font_url = "https://drive.google.com/uc?id=1eGAsTN1HBpJAkeVM57_C7ccp7hbgSz3_&export=download"
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font_response = requests.get(font_url)
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with open("TaipeiSansTCBeta-Regular.ttf", "wb") as font_file:
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pchome_json_data = json.loads(pchome_response.content)
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pchome_df = pd.DataFrame(pchome_json_data['prods'])
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available_columns = ['name', 'describe', 'price', 'orig']
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selected_columns = [col for col in available_columns if col in pchome_df.columns]
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pchome_df = pchome_df[selected_columns]
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)
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end_time = time.time()
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st.write(f"Execution time: {end_time - start_time:.2f} seconds")
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# Pytrends Analysis
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pytrend = TrendReq(hl="zh-TW", tz=-480)
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keywords = ["鴻屋"] #20240204換關鍵字
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pytrend.build_payload(
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kw_list=keywords,
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cat=3,
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timeframe="2024-06-18 2024-06-24",
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geo="TW",
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gprop="")
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df = pytrend.interest_over_time()
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df = df.drop(["isPartial"], axis=1)
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# Plotting Trend Data
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fig, ax = plt.subplots(figsize=(12, 8), dpi=80)
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ax.plot(df.index, df[keywords[0]], label=keywords[0], lw=3.0, marker='o', markersize=8, color='#4285F4', linestyle='-')
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ax.set_title("Interest Over Time for 鴻屋", fontsize=20, fontweight='bold', color='#4285F4')
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ax.set_xlabel("時間", fontsize=14, fontweight='bold', color='#4285F4')
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ax.set_ylabel("熱搜度", fontsize=14, fontweight='bold', color='#4285F4')
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ax.legend()
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ax.grid(True, linestyle
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