在Python中使用滞后值填充数据框

Question

I am trying to write a loop which fills the elements in a dataframe or matrix with the values of the previous year. The columns represent different years within the 50 year horizon. The rows represent different discrete ages (up to 50 years old). The initial distribution in year 1 (green vector) is given. I would like to successively move the elements through the df or matrix. Hence, element 1,1 depicts the surface of age 1 in year 1. As a consequence, that element moves to 2,2; 3,3 and so on. The last row should move to the first row in the next year (indicated by the blue arrow).

I have tried to iterate through the dataframe, but I think the Keyerror has to do with the fact that [index-1] has to be bound?

import numpy as np
import pandas as pd

years = np.arange(50)
a_vector = np.arange(50)
pop_matrix = pd.DataFrame(0, index=a_vector, columns=years)

#Initial vector (green)
A0 = 5000000
for a, rows in pop_matrix.iterrows():
    pop_matrix[0][a] = A0 / len(pop_matrix)

#Incorrect attempt
for t in years:
    for a, rows in pop_matrix.iterrows():
        if t-1 >= 0 and a-1 >= 0:
            pop_matrix[t][a] = pop_matrix[t-1][a-1]

Answer 1

I think the best way is to use numpy roll function.

Extract the values of your index and then apply numpy roll each time with a different shift. Example :

for year in years:
    col = pop_matrix.columns.tolist()[year]
    pop_matrix[col] = numpy.roll(a_vector, shift=year+1)