如何计算最近日期和第二最近日期的行数之间的差异

Question

I have the following df:

Index     Address     Date     
0  0x06b  2021-12-02  16:03:09.332
1  0x04t  2021-12-03  16:03:09.332
2  0x12c  2021-12-03  16:03:09.332
3  0x3d5  2021-12-04  16:03:09.332
4  0x077  2021-12-04  16:03:09.332
5  0x998  2021-12-04  16:03:09.332

I want to calculate the difference in amount of the rows ( len() of the column) between the most recent date ( t ), which in this case is 2021-12-04 16:03:09.332 )and the previous date ( t-1 ) but also for any previous date ( t-2, t-3, ..., tn ).

In this case, the answer for t - (t-1) should be 1, because the most recent date has 3 rows and the secod most recent date has 2 rows. 3-2 = 1.

I have tried implementing the solution in this StackOverflow post , but it does not seem to work.

Answer 1

I take you want to calculate the delta of the number of records per day vs the latest available date - would the following achieve what you need:

df2 = df.groupby("Address")[["Address"]].count().rename(columns={"Address": "count"})
df2.at['2021-12-04',"count"] - df2

OUTPUT

            count
Address
2021-12-02      2
2021-12-03      1
2021-12-04      0