Calculating the number of concrete sequential equal values ​​in vector form in pandas

Question

Let's say we have the following pandas DataFrame:

In [1]: import pandas as pd import numpy as np df = pd.DataFrame([0, 1, 0, 0, 1, 1, 0, 1, 1, 1], columns=['in']) df Out[1]: in 0 0 1 1 2 0 3 0 4 1 5 1 6 0 7 1 8 1 9 1 

How to count the number of consecutive in vector form in pandas? I would like to get this result:

  in out 0 0 0 1 1 1 2 0 0 3 0 0 4 1 1 5 1 2 6 0 0 7 1 1 8 1 2 9 1 3 

Something like the cumsum vectorization operation, which is reset in a certain state.

Answer 1

You can do something like this (credit goes: how to emulate itertools.groupby with a series / dataframe? ):

 >>> df['in'].groupby((df['in'] != df['in'].shift()).cumsum()).cumsum() 0 0 1 1 2 0 3 0 4 1 5 2 6 0 7 1 8 2 9 3 dtype: int64