repeat values of a column based on a condition

Question

I have a data frame including three columns named 'Altitude', 'Distance', 'Slope'. The column of 'Slope' is calculated using the two first columns 'Altitude', 'Distance'. @ the first step the purpose was to calculate 'Slope' using a condition explained below: A condition function was deployed to start from the top column of the "Distance" variable and add up (sum) values until the summation of them is greater or equal to 10 (>=10). If this condition corrects then calculate the "Slope" using the given formula: Slope=Average(Altitude)/(sum(Distance)). The summation of the 'Distance' was counting from the first value of that to the index that the 'Distance' has stopped there). The following code is for the above explanation (By Tim Roberts):

   Altitude  Distance
0      11.2     0.000
1      11.2     3.018
2      10.9     4.180
3      10.1     4.873
4       9.9     5.499
5       9.4     5.923
6       9.2     6.415
7       8.5     1.063
8       8.4     1.667
9       7.9     3.114

import pandas as pd

data = [
[11.2,     0],
[11.2,     3.018],
[10.9,     4.18],
[10.1,     4.873],
[9.9 ,     5.499],
[9.4 ,     5.923],
[9.2 ,     6.415],
[8.5 ,     1.063],
[8.4 ,     1.667],
[7.9 ,     3.114]
]

df = pd.DataFrame( data, columns=['Altitude','Distance'])
print( df )

s=[]
sumdist = 0
sumalt = 0
cntx = 0
for i in list(range(df.shape[0])):
    sumdist += df.loc[i,'Distance']
    sumalt += df.loc[i,'Altitude']
    cntx += 1
    if sumdist >= 10:
        KM_mean = sumalt / cntx / sumdist
        s.append(KM_mean)
        sumdist = sumalt = 0
        cntx = 0
if cntx:
    s.append( sumalt / cntx / sumdist )
print(s)

Output: SLOPE: [0.8988484798276862, 0.8448607949571003, 0.6933681376947548]

---

My QUESTION: Then The next PART: I am going to repeat the received number from the code: [0.8988484798276862, 0.8448607949571003, 0.6933681376947548]. I am looking to repeat each figure by the number of rows associated with it. for example, 0.8988484798276862 will be repeated four times in a new column then 0.8448607949571003 will be repeated two times and so on

I have written a code below but it returns me empty values:

RR=[]
for i in list(range(df.shape[0])):
    sumdist += df.loc[i,'Distance']
    sumalt += df.loc[i,'Altitude']
    cntx += 1
    if sumdist >= 10:
       R_s=np.repeat(df['Slope'].to_numpy()) 
       RR.append(R_s)

RR=DataFrame(RR)

Answer 1

Use this code after you calculate s to get slope column with desired values:

sum_distance = 0
count = 0
idx = 0
slopes = []

for i in df['Distance'].values:
    idx += 1
    sum_distance += i
    if sum_distance>=10:
        slopes += [s[count]]*idx
        count += 1
        sum_distance = 0
        idx = 0

if idx > 0:
    slopes += [s[count]]*idx

df['Slope'] = slopes

Output:

>>> df
   Altitude  Distance     Slope
0      11.2     0.000  0.898848
1      11.2     3.018  0.898848
2      10.9     4.180  0.898848
3      10.1     4.873  0.898848
4       9.9     5.499  0.844861
5       9.4     5.923  0.844861
6       9.2     6.415  0.693368
7       8.5     1.063  0.693368
8       8.4     1.667  0.693368
9       7.9     3.114  0.693368

Traversed the Distance column, summed up the values and kept count of the values traversed. Whenever the sum is 10 or more, pick value from s and insert them as many times as count showed. Reset sum, count and continue.