pandas GroupBy and cumulative mean of previous rows in group

Question

I have a dataframe which looks like this:

pd.DataFrame({\'category\': [1,1,1,2,2,2,3,3,3,4],
              \'order_sta         


        

Answer 1

Inspired by my answer here, one can define a function first:

def mean_previous(df, Category, Order, Var):
    # Order the dataframe first 
    df.sort_values([Category, Order], inplace=True)

    # Calculate the ordinary grouped cumulative sum 
    # and then substract with the grouped cumulative sum of the last order
    csp = df.groupby(Category)[Var].cumsum() - df.groupby([Category, Order])[Var].cumsum()

    # Calculate the ordinary grouped cumulative count 
    # and then substract with the grouped cumulative count of the last order
    ccp = df.groupby(Category)[Var].cumcount() - df.groupby([Category, Order]).cumcount()

    return csp / ccp

And the desired column is

df['mean'] = mean_previous(df, 'category', 'order_start', 'time')

Performance-wise, I believe it's very fast.