python - Pandas and Rolling_Mean with Offset (Average Daily Volume Calculation) -


when pull stock data dataframe yahoo, want able calculate 5 day average of volume, excluding current date.

is there way use rolling mean offset? example, 5 day mean excludes current day , based on prior 5 days.

when run following code

r = datareader("bbry", "yahoo", '2015-01-01','2015-01-31')  r['adv']=pd.rolling_mean(r['volume'], window=5)

it returns 5 day volume, inclusive of current date, when @ below, 1/8 has average volume 1/2,1/5,1/6,1/7, , 1/8. want 1/9 first date returns average volume , contain data 1/2,1/5,1/6,1/7, , 1/8.

date    open    high    low close   volume  adj close   symbol   adv   1/2/2015    11.01   11.11   10.79   10.82   9733200 10.82   bbry     1/5/2015    10.6    10.77   10.37   10.76   12318100    10.76   bbry     1/6/2015    10.8    10.85   10.44   10.62   10176400    10.62   bbry     1/7/2015    10.65   10.8    10.48   10.67   10277400    10.67   bbry     1/8/2015    10.75   10.78   10.57   10.63   6868300 10.63   bbry     9,874,680.00   1/9/2015    10.59   10.65   10.28   10.38   7745600 10.38   bbry     9,477,160.00

thanks help

you can shift rows achieve want:

in [44]: r['adv'] = pd.rolling_mean(r['volume'].shift(), window=5) r  out[44]:              open   high    low  close    volume  adj close       adv date                                                                  2015-01-02  11.01  11.11  10.79  10.82   9733200      10.82       nan 2015-01-05  10.60  10.77  10.37  10.76  12318100      10.76       nan 2015-01-06  10.80  10.85  10.44  10.62  10176400      10.62       nan 2015-01-07  10.65  10.80  10.48  10.67  10277400      10.67       nan 2015-01-08  10.75  10.78  10.57  10.63   6868300      10.63       nan 2015-01-09  10.59  10.65  10.28  10.38   7745600      10.38   9874680 2015-01-12  10.36  10.37  10.02  10.12   7739600      10.12   9477160 2015-01-13  10.05  10.23   9.68   9.71  15292900       9.71   8561460 2015-01-14   9.61  12.63   9.32  12.60  83543900      12.60   9584760 2015-01-15  10.36  10.71  10.01  10.11  52574600      10.11  24238060 2015-01-16  10.12  10.39  10.11  10.24  16068900      10.24  33379320 2015-01-20  10.28  10.37   9.82  10.03  15185900      10.03  35043980 2015-01-21  10.03  10.38   9.81   9.93  19614500       9.93  36533240 2015-01-22  10.44  11.11  10.24  10.51  44594300      10.51  37397560 2015-01-23  10.78  11.03  10.61  10.71  21079800      10.71  29607640 2015-01-26  10.67  10.71  10.40  10.52   6982000      10.52  23308680 2015-01-27  10.38  10.63  10.32  10.56   7057200      10.56  21491300 2015-01-28  10.65  10.67  10.10  10.12   9705000      10.12  19865560 2015-01-29  10.05  10.27   9.85  10.25  12304700      10.25  17883660 2015-01-30  10.15  10.26  10.00  10.15   9203400      10.15  11425740

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