I am working on a test dataset which is
print(df.head(10))
0 NaN
1 93/2; 99/3; 05/4;
2 NaN
3 NaN
4 NaN
5 NaN
Now i want to convert the string "93/2; 99/3; 05/4;" to a more neat data structure for following analysis. Thus the first step would be so split on the ";"
df= df.apply(lambda x: x.split(';'))
which yields
0 []
1 [93/2, 99/3, 05/4, ]
2 []
3 []
4 []
5 []
6 []
7 []
8 []
9 []
As you see the last element of the list is an empty value, which i want to delete. I was thinking about using the .pop() function but that yields
df = df.apply(lambda x: x.pop())
print(df.head(10))
0
1
2
3
4
5
6
7
8
9
if i am using slicing
df = df.apply(lambda x: x[:-1])
i get the expected output
0 []
1 [93/2, 99/3, 05/4]
2 []
3 []
4 []
5 []
6 []
7 []
8 []
9 []
Could anyone please explain why the pop function is not working here as i expected?
Thank you in advance!
>Solution :
It works. You assign the return of pop() back into your df. pop() returns the element that gets popped. You assign that element to your df.