Get index where value changes in pandas dataframe column
Use
In [91]: df.ne(df.shift()).apply(lambda x: x.index[x].tolist())Out[91]:Group 1 [0, 4]Group 2 [0, 2, 4, 6]Product ID [0, 3, 6]dtype: objectIn [92]: df.ne(df.shift()).filter(like='Group').apply(lambda x: x.index[x].tolist())Out[92]:Group 1 [0, 4]Group 2 [0, 2, 4, 6]dtype: objectAlso for dict,
In [107]: {k: s.index[s].tolist() for k, s in df.ne(df.shift()).filter(like='Group').items()}Out[107]: {'Group 1': [0L, 4L], 'Group 2': [0L, 2L, 4L, 6L]}
This is one non-pandas solution. I like it because it is intuitive and requires no understanding of the large pandas library.
changes = {}for col in df.columns: changes[col] = [0] + [idx for idx, (i, j) in enumerate(zip(df[col], df[col][1:]), 1) if i != j]# {'Group 1': [0, 4], 'Group 2': [0, 2, 4, 6], 'Product ID': [0, 3, 6]}