python - Volume Weighted Moving Averages -


i have dataframe looks like:

              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

with period = 5, want compute moving average vama = cumsum/cumdiv cumsum = (df['volume_ratio']*df['last price']).cumsum() , cumdiv = df['volume_ratio'].cumsum(), condition cumdiv <= period.

initially thought using expanding.sum() , df.apply work struggling it; like:

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)

this doesn't work, interested in best way attack this.

thanks in advance

just using rolling http://pandas.pydata.org/pandas-docs/stable/generated/pandas.dataframe.rolling.html

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

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