How to find the min and max elements in a list that has nan in between - python-3.x

Question

I have a dataframe that has a column named "score". I am extracting all the elements from that column into a list. It has 'nan's in between. I wish to identify the min and max of elements before every 'nan' occurs.
I was looking into converting the column into a list, and traverse the list until I encounter an "nan". But how do I traverse back to find the min and max elements right before nan?
This is the code I wrote to convert a column of a dataframe into a list and then identify the "nan".
score_list = description_df['score'].tolist()
for i in score_list:
print(i)
if math.isnan(i):
print("\n")
Suppose my data looks like this,
11.03680137760893
5.351482041139766
10.10019513222711
nan
0.960990030082931
nan
6.46983084276682
32.46794015293125
nan
Then, I should be able to identify max as 11.03680137760893
and min as 5.351482041139766 before the occurrence of the first "nan", 0.960990030082931 as the min and max before the occurrence of second nan and after the occurrence of first nan, and 32.46794015293125 as max and 6.46983084276682 as min after the second 'nan' and before the third 'nan'

Answer 1

You can create groups by testing missing values by Series.isna with Series.cumsum, aggregate by GroupBy.agg with min and max and last remove only missing rows by DataFrame.dropna:
df = df.groupby(df['score'].isna().cumsum())['score'].agg(['min','max']).dropna()
print (df)
min max
score
0 5.351482 11.036801
1 0.960990 0.960990
2 6.469831 32.467940

Answer 2

You can create two variables called min and max that begin with a default value each time you find a nan and print them (or store).
import sys
score_list = description_df['score'].tolist()
max = sys.float_info.min
min = sys.float_info.max
for i in score_list:
print(i)
if math.isnan(i):
print("max =", max, "min =", min, "\n")
max = sys.float_info.min
min = sys.float_info.max
else:
if i > max:
max = i
if i < min:
min = i