謝宸峰EXCEL,Python_csv_matplotlib

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謝宸峰python 讀入csv檔案計算黃金交叉和死亡交叉

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import pandas as pd #謝宸峰googlen搜尋AI模式copy貼上 # 1. 讀取 CSV 檔案 df = pd.read_csv('stock_data.csv') # 確保日期格式正確並設為索引 df['Date'] = pd.to_datetime(df['Date']) df.set_index('Date', inplace=True) # 2. 計算移動平均線 (MA) # 例如：短線MA(5), 長線MA(20) short_window = 5 long_window = 20 df['SMA5'] = df['Close'].rolling(window=short_window).mean() df['SMA20'] = df['Close'].rolling(window=long_window).mean() # 去除 NaN 值 (MA 前幾天無法計算) df.dropna(inplace=True) # 3. 定義交叉訊號 (Signal) # 黃金交叉: 短線 > 長線 (1), 死亡交叉: 短線 df['SMA20']).astype(float) # 4. 找出訊號改變的點 (交叉點) # 差異 > 0 是黃金交叉，差異 目前台股市值前十大 使用聯發科驗證黃金交叉與死亡交叉 影片
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謝宸峰期末考

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import csv #德明科大謝宸峰改11列與16列 f = open('00960.csv','r',encoding='utf-8') csv_reader = csv.reader(f) header, rows = [], [] #宣告空白串列(陣列,清單) header = next(csv_reader) #串列header存放第一列標題 for row in csv_reader: #逐列讀檔案、附加append於rows串列 rows.append(row) f.close() idSet = set() component = dict() #zeros = [0 for i in range(21)] for row in rows: for j in range(0, 21): idSet.add(row[j*4]) for id in idSet: component[id] = [0 for i in range(21)]#取代原來的zeros for row in rows: for j in range(0, 21): if row[j*4+3] != '': component[row[j*4]][j] = row[j*4 + 3] print(row[j*4+1],component[row[j*4]]) for id in idSet: print(id, component[id]) 修改前 修改後 影片
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謝宸峰程式交易Markowitz 1952投資效率前緣 3月 05, 2026

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程式 import csv #輸入import輸出export,輸入csv套件 import math #輸入math套件 from tkinter import * #或者import tkinter as tk Dim = 10 def draw_circle(x, y, label): canvas.create_oval(100+x-5, 700-y-5, 100+x+5, 700-y+5, fill="black") canvas.create_text(100+x+20, 700-y, text = label, anchor='w', font=('微軟正黑體',20)) file = open('台灣.csv','r',encoding='utf-8') read = csv.reader(file) header, rows = [], [] header = next(read) for item in read: rows.append(item) file.close() num = len(rows) #資料表長度 #print(header) mean = [0 for i in range(Dim)]; mean50 = 0; vari50=0 meanTemp = [0 for i in range(Dim)] vari = [[0 for i in range(Dim)] for j in range(Dim)] for k in range(num): for i in range(Dim): meanTemp[i]=float(rows[k][i+1])/100 #轉換為小數 mean[i] += meanTemp[i] for j in range(i+1): vari[i][j] += meanTemp[i]*meanTemp[j] meanTemp50 = float(rows[k][33])/100; mea...
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