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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def crude_age_standardization(e, b, n):
 """A utility function to compute rate through crude age standardization Parameters e : array (n*h, 1), event variable measured for each age group across n spatial units b : array (n*h, 1), population at risk variable measured for each age group across n spatial units n : integer the number of spatial units Notes ----- e and b are arranged in the same order Returns ------- : array (n, 1), age standardized rate Examples -------- Creating an array of an event variable (e.g., the number of cancer patients) for 2 regions in each of which 4 age groups are available. The first 4 values are event values for 4 age groups in the region 1, and the next 4 values are for 4 age groups in the region 2. Creating another array of a population-at-risk variable (e.g., total population) for the same two regions. The order for entering values is the same as the case of e. Specifying the number of regions. Applying crude_age_standardization function to e and b array([0.2375 , 0.26666667]) """

    r = e * 1.0 / b
    b_by_n = sum_by_n(b, 1.0, n)
    age_weight = b * 1.0 / b_by_n.repeat(len(e) // n)
    return sum_by_n(r, age_weight, n)