How to constuct a column of data frame recursively with pandas-python?

Question

Give such a data frame df:

id_      val     
11111    12
12003    22
88763    19
43721    77
...

I wish to add a column

Answer 1

Recursive functions are not easily vectorisable. However, you can optimize your algorithm with numba. This should be preferable to a regular loop.

from numba import jit

@jit(nopython=True)
def foo(val):
    diff = np.zeros(val.shape)
    diff[0] = val[0] * 0.4
    for i in range(1, diff.shape[0]):
        diff[i] = (val[i] - diff[i-1]) * 0.4 + diff[i-1]
    return diff

df['diff'] = foo(df['val'].values)

print(df)

     id_  val     diff
0  11111   12   4.8000
1  12003   22  11.6800
2  88763   19  14.6080
3  43721   77  39.5648