I’ve following toy-dataframe:

    | id| date
--------------
0   | a | d1
1   | b | d1
2   | a | d2
3   | c | d2
4   | b | d3
5   | a | d3

import pandas as pd

df = pd.DataFrame({'id': ['a', 'b', 'a', 'c', 'b', 'a'], 'date': ['d1', 'd1', 'd2', 'd2', 'd3', 'd3']})

I want to obtaining ‘linking dicitionary’, like this: d = {0: 2, 2: 5, 1: 4},
where (numbers are just row index)

• 0:2 means link a from d1 to a from d2,
• 2:5 means link a from d2 to a from d3,
• 1:4 means link b from d1 to b from d3

Is there some simple and clean way to get it?

>Solution :

You can use groupby and reduce:

from functools import reduce

d = df.groupby('id').apply(lambda x: dict(zip(x.index, x.index[1:])))
d = reduce(lambda d1, d2: {**d1, **d2}, d)  # or reduce(lambda d1, d2: d1 | d2, d)
print(d)

# Output
{0: 2, 2: 5, 1: 4}