Python Equivalent to SQL Rank

Question

I want to have an SQL rank equivalent in python pandas module. I want to filter out all the dates which have the rank = 1

I've the following dataframe:

id    date
12    2021-06-01
12    2021-06-15
12    2021-06-21
34    2021-06-05
87    2021-06-19
53    2021-06-05

and I need to apply rank in the following way:

id    date          rank
12    2021-06-01      1
12    2021-06-15      2
12    2021-06-21      3
34    2021-06-05      1
87    2021-06-19      1
53    2021-06-05      1

The SQL for this would be

select id, date, rank() over (partition by id order by date asc) as rank 
from table;

Answer 1

IIUC use GroupBy.rank:

df['date'] = pd.to_datetime(df['date'])
df['rank'] = df.groupby('id')['date'].rank(method='dense').astype(int)
print (df)
   id       date  rank
0  12 2021-06-01     1
1  12 2021-06-15     2
2  12 2021-06-21     3
3  34 2021-06-05     1
4  87 2021-06-19     1
5  53 2021-06-05     1

If datetimes are sorted per groups is possible GroupBy.cumcount:

df = df.sort_values(['id','date'])
df['rank'] = df.groupby('id')['date'].cumcount().add(1)