Reputation: 11
I have a dataframe of two columns "ExplB" and "remP". Values in remP can be only 0 or 1. I'm trying to split the dataframe in multiple dataframes after the value 1 is met in column remP. How can I do this operation in Python?
How can I solve this? enter image description here
data = {'ExplB':[0,0,0,0.2,0.2,0.15,0,0,0,0,0,0,0,0,0],'remP':[0,0,0,1,0,0,0,0,1,0,0,0,1,0,0]}
df = pd.DataFrame(data, columns = ['ExplB', 'remP'])
Upvotes: 0
Views: 205
Reputation: 14113
you can use np.split
# find the index where df['remP']==1
idx = df[df['remP']==1].index
# split your df on that index
dfs = np.split(df, idx)
[ ExplB remP
0 0.0 0
1 0.0 0
2 0.0 0, ExplB remP
3 0.20 1
4 0.20 0
5 0.15 0
6 0.00 0
7 0.00 0, ExplB remP
8 0.0 1
9 0.0 0
10 0.0 0
11 0.0 0, ExplB remP
12 0.0 1
13 0.0 0
14 0.0 0]
or if you want to split the df after that index then do idx+1
idx = df[df['remP']==1].index
dfs = np.split(df, idx+1)
[ ExplB remP
0 0.0 0
1 0.0 0
2 0.0 0
3 0.2 1, ExplB remP
4 0.20 0
5 0.15 0
6 0.00 0
7 0.00 0
8 0.00 1, ExplB remP
9 0.0 0
10 0.0 0
11 0.0 0
12 0.0 1, ExplB remP
13 0.0 0
14 0.0 0]
Upvotes: 1