#参考：

#https://www.cnblogs.com/JuliaZhao/p/12034202.html #简单示例（筹码分布图）

#%% 筹码分布图 #import mpl_finance as mpf #import matplotlib.finance as mpf import matplotlib.pyplot as plt from matplotlib.finance import candlestick2_ohlc

cdata=DataAPI.MktEqudAdjGet(ticker=u"301037" , beginDate="20220101",endDate="20220602",tradeDate=u"",\                                  isOpen="1",field=u"ticker,secShortName,tradeDate,highestPrice,lowestPrice,openPrice,closePrice,turnoverRate,preClosePrice,turnoverVol,turnoverValue",pandas="1") #按日期倒排序（最近在前），为了计算到今天endDate总的换手率大致到1（全部换手）开始那天 #均价 cdata['mean']=cdata.apply(lambda x:x.turnoverValue/x.turnoverVol, axis = 1) cdata=cdata.sort(["tradeDate"],ascending=False) print cdata.head() #对换手率累计求和 cdata['turnoverRate_cumsum'] = cdata.turnoverRate.cumsum() #只取近似全换手（