How can I match length of DataFrame when comparing indexes?
df[df.index > df[df.a == 5].index]
(shape of df is dynamic)
Example:
df = pd.DataFrame([[0, 10], [5, 10], [0, 10], [5, 10], [0, 10], [0, 10]], columns=["a", "b"])
m = df.index > df[df.a == 5].index
df.loc[m, 'b'] -= np.arange(1, m.sum() + 1)
Desired result:
a b
0 0 10
1 5 9
2 0 9
3 5 8
4 0 8
5 0 8
The error happens because the length of df[df.a == 5] does not match the length of df, so following expression:
df.index > df[df.a == 5].index
is invalid. Both sides has to match in length or one side must be broadcastable, but if the lengths are 5 and 2, that's not possible.
It seems you want group rows according to the position "a" equals 5 and subtract the group number from "b". In that case, you could use eq + cumsum instead:
df['b'] -= df['a'].eq(5).cumsum()
Output:
a b
0 0 10
1 5 9
2 0 9
3 5 8
4 0 8
5 0 8