Update app.py
Browse files
app.py
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@@ -1,7 +1,7 @@
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import requests
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from bs4 import BeautifulSoup
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import pandas as pd
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import
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# ๋ค์ด๋ฒ ์ฆ๊ถ URL
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url = "https://finance.naver.com/sise/sise_rise.naver?sosok=1"
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@@ -35,19 +35,19 @@ def scrape_naver_finance():
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rate = columns[4].text.strip()
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volume = columns[5].text.strip()
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# ๊ฐ ์ด์ ๋ฐ์ดํฐ๋ฅผ ๋ฆฌ์คํธ๋ก ์ ์ฅ
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data.append([rank, name, price,
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# DataFrame์ผ๋ก ๋ณํ
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df = pd.DataFrame(data, columns=["์์", "์ข
๋ชฉ๋ช
", "ํ์ฌ๊ฐ", "์ ์ผ๋น", "๋ฑ๋ฝ๋ฅ ", "๊ฑฐ๋๋"])
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# ๊ทธ๋ผ๋์ค ์ธํฐํ์ด์ค ์ ์
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def get_top_stocks():
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df = scrape_naver_finance()
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return df
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#
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iface.launch()
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import requests
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from bs4 import BeautifulSoup
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import pandas as pd
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import re
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# ๋ค์ด๋ฒ ์ฆ๊ถ URL
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url = "https://finance.naver.com/sise/sise_rise.naver?sosok=1"
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rate = columns[4].text.strip()
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volume = columns[5].text.strip()
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# '์ํ๊ฐ', '์์น' ๋ฑ์ ๊ธ์จ ์ ๊ฑฐ
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change_cleaned = re.sub(r'[^\d-]', '', change).strip()
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# ๊ฐ ์ด์ ๋ฐ์ดํฐ๋ฅผ ๋ฆฌ์คํธ๋ก ์ ์ฅ
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data.append([rank, name, price, change_cleaned, rate, volume])
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# DataFrame์ผ๋ก ๋ณํ
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df = pd.DataFrame(data, columns=["์์", "์ข
๋ชฉ๋ช
", "ํ์ฌ๊ฐ", "์ ์ผ๋น", "๋ฑ๋ฝ๋ฅ ", "๊ฑฐ๋๋"])
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# ์์
ํ์ผ๋ก ์ ์ฅ
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df.to_excel("naver_top_stocks.xlsx", index=False)
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return df
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# ์คํฌ๋ํ ์คํ ๋ฐ ์์
ํ์ผ ์ ์ฅ
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scrape_naver_finance()
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