研究打板策略

思路：

根据当前最强势板块以及前一天的涨停股票池，以及股票个股热度名单小于50

导入包：

import akshare as ak
import numpy as np
import pandas as pd
from datetime import datetime
import matplotlib.pyplot as plt
import mplfinance as mpf
from pylab import mpl
mpl.rcParams['font.sans-serif'] = ['SimHei']  # 设置中文字体为微软雅
plt.rcParams['font.sans-serif'] = ['SimHei']        # 字体设置
import matplotlib
matplotlib.rcParams['axes.unicode_minus']=False    # 负号显示问题


获取最热板块：
#获取最大涨幅板块
ind = ak.stock_board_industry_name_em()
bk = ind.sort_values('涨跌幅',ascending=False)['板块名称'][0]
bk

获取板块中涨停个股：
end =datetime.now().strftime('%Y%m%d')
stock_zt_pool_em_df = ak.stock_zt_pool_em(date=end)
stock_pool= stock_zt_pool_em_df[(stock_zt_pool_em_df['所属行业']==bk)]

数据修改： 
stock_hot_rank_wc_df = ak.stock_hot_rank_wc(date=end)
stock_hot_rank_wc_df.rename(columns= {'股票代码':'代码'},inplace=True)
stock_hot_rank_wc_df = stock_hot_rank_wc_df[(stock_hot_rank_wc_df['代码']==stock_pool.iloc[0,1])]
stock_pool = pd.merge(stock_pool,stock_hot_rank_wc_df,on='代码')


 绘图：
for i in range(len(stock_pool['代码'])):
    end =datetime.now().strftime('%Y%m%d')
    code= str(stock_pool['代码'].values[i])
    data =  ak.stock_zh_a_hist(symbol=code, period="daily", start_date="19900301", end_date=end, adjust="")
    data['日期'] = pd.to_datetime(data['日期'], format='%Y-%m-%d')
    data.rename(columns= {'日期':'date','开盘':'open','最高':'high','最低':'low','收盘':'close','成交量':'volume'},inplace=True)
    data['code'] = code
    data = data[['date','open','close','high','low','volume','code']]
    data['max'] = data['high'].rolling(20).max()
    data['volume_20m'] = data['volume'].rolling(20).mean()
    data['volume_5m'] = data['volume'].rolling(5).mean()
    data = data[(data['high']>=data['max'])&(data['volume']>data['volume_20m'])&(int((str(stock_pool['个股热度排名'].values).split('/'))[0][2:])<50)]
    data = data.set_index(data.date)
    data = data[['open','close','high','low','volume','code']]
    print(code)
    mpf.plot(data[-10:],type='candle',volume=True)

效果图