Python how to create a rolling mean with additional conditions-CodePudding

I have a pandas dataframe as seen below:

Date (DMY)     Total     3-day-min
01/03/2013     0.102        -    
02/03/2013     0.122        -    
03/03/2013     0.047       0.047  
04/03/2013     0.050       0.047 
05/03/2013     0.052       0.049  
06/03/2013     0.049       0.048   
07/03/2013     0.048       0.048   
08/03/2013     0.048       0.047

The first column is the date, the second is the total value, and the third column is a rolling three day minimum of the values in the [Total] column.

I'm trying to create a new column that is a rolling 3-day mean/average of the [3-day min] column, which I have done using this line:

df['rolling_mean'] = df['3-day-min'].rolling(3).mean()

However, what I'd like to do is introduce a condition where, in the new [rolling_mean] row, there is a check whether the value is higher than the value in the [Total] column. If the mean value is higher, then the value in the [Total] column should be checked instead.

Hope that makes sense. Any help would be appreciated.

CodePudding user response：

Use Series.where

df['rolling_mean'] = df['3-day-min'].rolling(3).mean().where(lambda x: x.le(df['3-day-min']), df['3-day-min'])

Or:

df['rolling_mean'] = df['3-day-min'].rolling(3).mean().mask(lambda x: x.gt(df['3-day-min']), df['3-day-min'])