I’m trying to translate a technical analysis operator from another proprietary language to python as using dataframes, but I got stuck on a problem that seems rather simple, but I can’t get to solve the pandas way. To simplify the problem let’s have the example of this dataframe:

d = {'value1': [0,1,2,3], 'value2': [4,5,6,7]}
df = pd.DataFrame(data=d)

which result in the following dataframe:


What I want to achieve is this:

enter image description here

which in Pseudocode I would achieve in the following way:

value1 = [0,1,2,3]
value2 = [4,5,6,7]
result = []

for i in range(len(value1)):
    calculation = value1[i] * value2[i]
    lookback = value1[i]
    for j in range(lookback):
       calculation -= value2[j]
    result[i] = calculation

How would I tackle a this in a dataframe context? Because the only similar approach that I found in the documentation is the usage of https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.apply.html# but there is no mentioning of interacting/manipulating the series contained in the columns/rows.


df['result'] = df.value1 * df.value2 - (df.value2.cumsum() - df.value2)


   value1   value2  result
0   0       4       0
1   1       5       1
2   2       6       3
3   3       7       6

We are calculating cumulative sum for value2 and subtracting the current value2 which in total is subtracted by the product of value1 and value2.

Source: https://stackoverflow.com/q/67547469

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