TKG With Python

 I found the trend by this code. This trend is from Japanese Workers' Pay Day(Every 25th day in a month). '''python import yfinance as yf import matplotlib . pyplot as plt import pandas as pd import seaborn as sns # 分析期間の設定 dateStart = "2015-01-01" dateEnd = "2026-05-23" ticker = "JPY=X" # ドル円 # yfinanceから取得（仕様変更の警告回避のため auto_adjust を明示） df = yf . download ( ticker , start = dateStart , end = dateEnd , auto_adjust = False , progress = False ) # yfinanceの仕様変更（MultiIndex化）に対応して終値を安全に抽出 if isinstance ( df . columns , pd . MultiIndex ): close = df [ "Close" ][ ticker ].dropna() else : close = df [ "Close" ]. dropna () # 前日比の変化率（%）を計算 # ドル円の場合、プラス = ドル買い/円売り、マイナス = ドル売り/円買い daily_return = close . pct_change () * 100 # 分析用のDataFrameを作成 analysis_df = pd . DataFrame ({ "Return" : daily_return }) analysis_df . index = pd . to_datetime ( analysis_df . index ...

Ratios Between Gold, Platinum and Silver Ratios between Gold, Platinum and Silver show clear trends. Gold/Silver ratio shows big fluctuations. Platinum/Silver ratio shows a clear downward trend. import yfinance as yf import matplotlib.pyplot as plt import pandas as pd dateStart = "2015-01-01" dateEnd = "2025-12-31" tickers = ["GC=F", "SI=F", "PL=F"] # Gold, Silver, Platinum futures # yfinanceからまとめて取得（警告回避のため auto_adjust を明示） df = yf.download( tickers, start=dateStart, end=dateEnd, auto_adjust=False, # True/FalseどちらでもOK。とにかく明示する progress=False ) # dfは MultiIndex columns になりやすい：['Close'] で3銘柄の終値DataFrameが取れる close = df["Close"].copy() # 月次平均（pandas警告対応：'M' -> 'ME'） close_m = close.resample("ME").mean() # 比率をDataFrameで計算（列名で参照） ratio = pd.DataFrame({ "Gold/Silver": close_m["GC=F"] / close_m["SI=F"], "Gol...