Apply Function On Cumulative Values Of Pandas Series

Is there an equivalent of rolling_apply in pandas that applies function to the cumulative values of a series rather than the rolling values? I realize cumsum, cumprod, cummax, and

Solution 1:

You can use pd.expanding_apply. Below is a simple example which only really does a cumulative sum, but you could write whatever function you wanted for it.

import pandas as pd

df = pd.DataFrame({'data':[10*i for i inrange(0,10)]})

defsum_(x):
    returnsum(x)


df['example'] = pd.expanding_apply(df['data'], sum_)

print(df)

#   data  example#0     0        0#1    10       10#2    20       30#3    30       60#4    40      100#5    50      150#6    60      210#7    70      280#8    80      360#9    90      450

Solution 2:

[Follow up to @Ffisegydd's answer]

Update for pandas == 1.0.5

df['example'] = df['data'].expanding().apply(sum_)