OPEN-SOURCE SCRIPT
チャットGPT

import yfinance as yf
import pandas as pd
import requests
from bs4 import BeautifulSoup
# 株たんのスクリーニング結果URL(例:200日線以下)
url = "kabutan.jp/warning/?mode=3_1"
r = requests.get(url)
soup = BeautifulSoup(r.text, "html.parser")
# 銘柄コードと企業名を抽出
stocks = []
for link in soup.select("td a[href*='/stock/?code=']"):
code = link['href'].split('=')[-1]
name = link.text.strip()
if code.isdigit():
stocks.append({"code": code, "name": name})
results = []
for stock in stocks[:10]: # ←テスト用に10銘柄まで
ticker = f"{stock['code']}.T"
df = yf.download(ticker, period="1y", interval="1d")
# EMA200
df["EMA200"] = df["Close"].ewm(span=200, adjust=False).mean()
below_ema200 = df["Close"].iloc[-1] < df["EMA200"].iloc[-1]
# 株たんの個別ページからPER・成長率を取得
stock_url = f"kabutan.jp/stock/?code={stock['code']}"
res = requests.get(stock_url)
s = BeautifulSoup(res.text, "html.parser")
try:
per = s.find(text="PER").find_next("td").text
growth = s.find(text="売上高増減率").find_next("td").text
except:
per, growth = "N/A", "N/A"
results.append({
"銘柄コード": stock['code'],
"企業名": stock['name'],
"200EMA以下": below_ema200,
"PER": per,
"売上成長率": growth
})
# 結果をCSV出力
df_result = pd.DataFrame(results)
df_result.to_csv("割安EMA200以下銘柄.csv", index=False, encoding="utf-8-sig")
print(df_result)
import pandas as pd
import requests
from bs4 import BeautifulSoup
# 株たんのスクリーニング結果URL(例:200日線以下)
url = "kabutan.jp/warning/?mode=3_1"
r = requests.get(url)
soup = BeautifulSoup(r.text, "html.parser")
# 銘柄コードと企業名を抽出
stocks = []
for link in soup.select("td a[href*='/stock/?code=']"):
code = link['href'].split('=')[-1]
name = link.text.strip()
if code.isdigit():
stocks.append({"code": code, "name": name})
results = []
for stock in stocks[:10]: # ←テスト用に10銘柄まで
ticker = f"{stock['code']}.T"
df = yf.download(ticker, period="1y", interval="1d")
# EMA200
df["EMA200"] = df["Close"].ewm(span=200, adjust=False).mean()
below_ema200 = df["Close"].iloc[-1] < df["EMA200"].iloc[-1]
# 株たんの個別ページからPER・成長率を取得
stock_url = f"kabutan.jp/stock/?code={stock['code']}"
res = requests.get(stock_url)
s = BeautifulSoup(res.text, "html.parser")
try:
per = s.find(text="PER").find_next("td").text
growth = s.find(text="売上高増減率").find_next("td").text
except:
per, growth = "N/A", "N/A"
results.append({
"銘柄コード": stock['code'],
"企業名": stock['name'],
"200EMA以下": below_ema200,
"PER": per,
"売上成長率": growth
})
# 結果をCSV出力
df_result = pd.DataFrame(results)
df_result.to_csv("割安EMA200以下銘柄.csv", index=False, encoding="utf-8-sig")
print(df_result)
Open-source script
In true TradingView spirit, the creator of this script has made it open-source, so that traders can review and verify its functionality. Kudos to the author! While you can use it for free, remember that republishing the code is subject to our House Rules.
Disclaimer
The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView. Read more in the Terms of Use.
Open-source script
In true TradingView spirit, the creator of this script has made it open-source, so that traders can review and verify its functionality. Kudos to the author! While you can use it for free, remember that republishing the code is subject to our House Rules.
Disclaimer
The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView. Read more in the Terms of Use.