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Posted on 2021-11-21 19:38  心默默言  閱讀(112)  評論(0)  編輯  收藏  舉報(bào)

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

復(fù)制代碼

# -*- coding: utf-8 -*-

# @Time    : 2021/11/7 20:40

# @Author  : zhaozhuang

# 導(dǎo)入 efinance 如果沒有安裝則需要通過執(zhí)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繪制輸出中文亂碼

# 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(gè)交易日的分鐘級別股票行情數(shù)據(jù)

df = ef.stock.get_quote_history(stock_codes=stock_code, beg=beg, end=end, klt=freq)

# 將數(shù)據(jù)存儲(chǔ)到 csv 文件中

# df.to_excel(f'{stock_code}_{freq}.xlsx', encoding='utf-8-sig', index=None)

print(f'股票: {stock_code} 的行情數(shù)據(jù)已存儲(chǔ)到文件: {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)