Question

我有一个看起来像这样的DataFrame：

              LAST PRICE        VOLUME     volume_ratio
date                                                             
2005-01-03      1202.08     1.332210e+09       1.23       
2005-01-04      1188.05     1.552646e+09       1.55       
2005-01-05      1183.74     1.428365e+09       1.65         
2005-01-06      1187.89     1.331004e+09       1.23         
2005-01-07      1186.19     1.273960e+09       0.83        
2005-01-10      1190.25     1.213694e+09       1.06

使用period = 5，我想计算VAMA = CumSum/CumDiv和CumSum = (df['volume_ratio']*df['LAST PRICE']).cumsum()的移动平均线CumDiv = df['volume_ratio'].cumsum()，条件为CumDiv <= Period。

最初我认为使用expanding.sum()和df.apply会起作用，但我正在努力;类似的东西：

cum_div = df['volume_ratio'].expanding(min_periods = 1).sum()
cum_summ = (df['LAST PRICE']*df['volume_ratio']).expanding(min_periods                =1).sum()

df['cum_sum'] = df.apply(lambda x: cum_summ if cum_div <= 13, axis = 1)

这显然不起作用，所以我对攻击它的最佳方式感兴趣。

提前致谢

Answer 1

仅使用rolling http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.rolling.html

df['myrollingmean'] = df.VAMA.rolling(window = 5).mean()

Answer 2

(df['LAST PRICE']*df['volume_ratio']).cumsum()\
        .div(df['volume_ratio'].cumsum()).rolling(window=5).mean()

条件为cumdiv＆gt; = 5

(df['LAST PRICE']*df['volume_ratio']).cumsum()\
        .div(np.where(df['volume_ratio'].cumsum()<=5,df['volume_ratio'].cumsum(),np.nan))\
        .rolling(window=5).mean()

体积加权移动平均线

2 个答案: