Getting column with days from first observed - trading data

Question

So I have some Trading data, and ultimately I would like to find 1 week return 1 month, 3 month and so on. To do this I think it is easiest if I can get a column with days existed for each asset.

Data is simplified to this:

Id	Date	Price
101	2014-09-14	0.7
101	2014-09-15	0.8
101	2014-09-16	0.9
101	2014-09-17	0.8
103	2014-10-03	1,6
103	2014-10-04	1.7
103	2014-10-05	1.7
103	2014-10-07	1.9
107	2015-10-17	24
107	2015-10-18	21
107	2015-10-23	22

I would then like an new column named "Days listed"

Id	Date	Price	Days listed
101	2014-09-14	0.7	1
101	2014-09-15	0.8	2
101	2014-09-16	0.9	3
101	2014-09-17	0.8	4
103	2014-10-03	1,6	1
103	2014-10-04	1.7	2
103	2014-10-05	1.7	3
103	2014-10-07	1.9	5
107	2015-10-17	24	1
107	2015-10-18	21	2
107	2015-10-23	22	7

I think it needs to be grouped by id, but other than that I am out of ideas.

Answer 1

use pd.groupby to get a earliest date for each group, which is then subtracted by the dates to get the days-listed

df['Date']=pd.to_datetime(df['Date'])
df['DaysListed']=(df['Date'] - df.groupby('Id')['Date'].transform('min')).dt.days+1
df

    Id  Date       Price    DaysListed
0   101 2014-09-14  0.7     1
1   101 2014-09-15  0.8     2
2   101 2014-09-16  0.9     3
3   101 2014-09-17  0.8     4
4   103 2014-10-03  1.6     1
5   103 2014-10-04  1.7     2
6   103 2014-10-05  1.7     3
7   103 2014-10-07  1.9     5
8   107 2015-10-17  24      1
9   107 2015-10-18  21      2
10  107 2015-10-23  22      7