Python 計算股價 KDJ (2)

續上一篇：Python 計算股價 KDJ，這篇把它完備一點，再加上前一日收盤價格，今日收盤價格，差異和百分比：

我定義一個函數來取得最後日和前一日的收盤價格資料，並計算差異百分比，最後將結果傳回：

# 取得最後一天收盤資料

def last_day_data(name, df):

date = df.index[-1].strftime('%Y-%m-%d') # 取出最後一筆日期

price = round(df.Close[-1], 2) # 當日收盤價

pre_price = round(df.Close[-2], 2) # 前一日收盤價

diff = round(df.Close[-1] - df.Close[-2], 2) # 價格差異

percent = round(float(diff) * 100 / pre_price, 2) # 差異百分比

high = round(df.High[-1], 2) # 當日最高

low = round(df.Low[-1], 2) # 當日最低

return [date, name, pre_price, price, diff, percent, high, low]

完整程式碼如下：

import yfinance as yf

import pandas as pd

# 計算KDJ,以9日週期計算

def calc_kdj(df, n=9):

low_list = df['Low'].rolling(window=n).min()

low_list.fillna(value=df['Low'].expanding().min(), inplace=True)

high_list = df['High'].rolling(window=n).max()

high_list.fillna(value=df['High'].expanding().max(), inplace=True)

rsv = (df['Close'] - low_list) / (high_list - low_list) * 100

df['K'] = rsv.ewm(com=2).mean()

df['D'] = df['K'].ewm(com=2).mean()

df['J'] = 3 * df['K'] - 2 * df['D']

r = round(rsv.iloc[-1], 2)

k = round(df.iloc[-1].K, 2)

d = round(df.iloc[-1].D, 2)

j = round(df.iloc[-1].J, 2)

return [r, k, d, j]

 

# 取得最後一天收盤資料

def last_day_data(name, df):

date = df.index[-1].strftime('%Y-%m-%d') # 取出最後一筆日期

price = round(df.Close[-1], 2) # 當日收盤價

pre_price = round(df.Close[-2], 2) # 前一日收盤價

diff = round(df.Close[-1] - df.Close[-2], 2) # 價格差異

percent = round(float(diff) * 100 / pre_price, 2) # 差異百分比

high = round(df.High[-1], 2) # 當日最高

low = round(df.Low[-1], 2) # 當日最低

return [date, name, pre_price, price, diff, percent, high, low]

 

def list_conv_matrix(lst):

data, data_matrix = [], []

for val in lst:

data_matrix.append(val)

cols = ['Date', 'Name', '前一日', '收盤價', '差異', '%', '當日最高', '當日最低',

'RSV', 'K', 'D', 'J']

return pd.DataFrame(data_matrix, columns=cols).set_index('Date')

 

def get_ticker_data(ticker_list):

data = []

for ticker in ticker_list:

df = yf.download(ticker, period='30d')

kdj_list = calc_kdj(df) # 計算KDJ

data_list = last_day_data(ticker, df) # 取得最後一天收盤資料

date_str = data_list[0] # 取出日期

data_list.extend(kdj_list)

data.append(data_list)

return data

ticker_list = ['AAPL', 'AMZN', 'GOOGL']

df = list_conv_matrix(get_ticker_data(ticker_list))

df

 

執行結果：

 

你可以參考上一篇：

Python 計算股價 KDJ (1)