根据pandas中列的值删除行

Question

I have a dataframe like this:

col.1 : a a a a a b b b c c c
col.2 : 0 0 1 0 0 0 1 0 0 0 0

I want to drop all values for a similar value in col.1 after 1 is encountered in col.2. The result should be like:

col.1 : a a a b b c c c
col.2 : 0 0 1 0 1 0 0 0

Is there any way to do it fast in pandas? Currently I'm using numpy where and it seems to be very slow.

Answer 1

Try this:

df['col.2'] = df.groupby('col.1')['col.2'].cumsum()
df['col.2'] = df.groupby('col.1')['col.2'].cumsum()
df = df[df['col.2']<2]