Nelly Yuki :
I have a pandas series that looks like this:
df['column_3'].head(10)
0 0.0
1 0.0
2 0.0
3 0.0
4 0.0
5 0.1
6 0.0
7 0.1
8 0.1
9 0.0
I would like to remove only the first appearances of zeros, so in this example only rows 0 - 4. The number of zeros in the beginning of the series may vary and I only want to remove the zeros that come before the first instance of a non-zero entry. When I did this:
df[df['column_3'] != 0.0]
It removes all zeros, no matter the placement, which is not what I want.
I want it to look like this:
5 0.1
6 0.0
7 0.1
8 0.1
9 0.0
Any suggestions?
Thanks!
Quang Hoang :
cumsum
is suitable for this situation:
df[df['column_3'].ne(0).cumsum().gt(0)]
Output:
column_3
5 0.1
6 0.0
7 0.1
8 0.1
9 0.0