https://blog.csdn.net/Wilburzzz/article/details/109667926

# -*- coding: utf-8 -*-
# @Time    : 2021/11/7 20:40
# @Author  : zhaozhuang


# 匯入 efinance 如果沒有安裝則需要通過執行命令: pip install efinance 來安裝
import efinance as ef
import mplfinance as mpf
import pandas as pd

# import matplotlib.pyplot as plt

pd.set_option('
 
display.max_rows', 50000)
pd.set_option('display.max_columns', 50000)
pd.set_option('display.width', 2000)


# plt.rcParams['font.sans-serif'] = ['SimHei']
# plt.rcParams['axes.unicode_minus'] = False

# 解決mplfinance繪製輸出中文亂碼
# s = mpf.make_mpf_style(rc={'font.family': 'SimHei'})


def get_kchar(df: pd.DataFrame, code: str, name: str):
    date_index 
 
= df['日期']
    date_index = pd.to_datetime(date_index)
    data = df[['開盤', '最高', '最低', '收盤', '成交量']]
    data = data.rename(columns={'開盤': 'Open', '收盤': 'Close', '最高': 'High', '最低': 'Low', '成交量': 'Volume'})
    data.index = date_index

    my_color = mpf.make_marketcolors(up='red', down='green')
    my_style 
 
= mpf.make_mpf_style(marketcolors=my_color, rc={'font.family': 'SimHei'})
    add_plot = [
        mpf.make_addplot(turnover_rate, scatter=True, marker='^', color='red'),
        mpf.make_addplot(turnover_rate, color='red'),
        mpf.make_addplot(ma_turnover_rate, color='blue'),

        ]
    mpf.plot(data, type='candle', style=my_style, figscale=2, addplot=add_plot, mav=(5, 20, 30), ylabel='price',
             volume=True,
             title=f'\n\n\n {code} {name}  K_line')
    # mpf.plot(data, type='candle', style=my_style, figscale=2, addplot=add_plot, mav=(5, 20, 30), volume=True,
    #          title=f'\n\n\n {code} {name}  K_line')


paras = {
    'stock_code': '002626',
    'begin': '20210130',
    'end': '20251105',
    'freq': 101
    }

stock_code = paras['stock_code']
beg = paras['begin']
end = paras['end']
freq = paras['freq']

# 獲取最新一個交易日的分鐘級別股票行情資料
df = ef.stock.get_quote_history(stock_codes=stock_code, beg=beg, end=end, klt=freq)
# 將資料儲存到 csv 檔案中
# df.to_excel(f'{stock_code}_{freq}.xlsx', encoding='utf-8-sig', index=None)
print(f'股票: {stock_code} 的行情資料已儲存到檔案: {stock_code}_{freq}.xlsx 中！')
# 獲取一支股票的量比
name = df['股票名稱'].values[0]
vol_ma = df['成交量'].rolling(window=5).mean().values
vol_raito = df['成交量'].values / df['成交量'].rolling(window=5).mean().values
turnover_rate = df['換手率'].values
ma_turnover_rate = df['換手率'].rolling(window=21).mean().values
# print(vol_ma)
# print(vol_raito)
get_kchar(df, paras['stock_code'], name)