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Yen Currency Trend

 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 ...
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Products & Publications(制作物・著作物)

 Products & Publications

GitHub

https://github.com/Kouhei-Takagi/Books


Kindle Books
I have authored several Kindle books focusing on the core concepts of Emotionics, emotional abstraction, and AI-native system architecture.
Emotionics Series:

Blue Planet System & Green Planet Protocol Series:

Python Libraries
Open-source Python libraries developed to implement Emotionics frameworks for technical verification and edge AI integration.

  • emotionics - Core library for emotional state estimation.
  • hatsu - Library focused on specific algorithmic outputs for controlled system feedback.
    NPM Libraries
  • KeyTempo - Zero-dependency Keystroke Dynamics Extractor
    Blogs

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