I want to write this code in python.
proc sql;
select count(distinct ID_1)
from DATA
where ID_1 = ID_2 and ID_type in ("11","23","46");
quit;
I can do this in three steps
a = [x if x==y and z in ("11","23", "46") for x,y,z in zip(DATA['x'],DATA['y'],DATA['z'])]
a = [i for i in a if str(i) != 'nan']
len(np.unique(a))
Is there any efficient way to write the same code.
Most common SQL operations can be easily translated in python and pandas:
DATA[(DATA.ID_1 == DATA.ID_2) & (DATA.ID_type.isin(["11", "23", "46"]))].ID_1.nunique()
Read the introduction to pandas for more.
A different take filtering using query
method:
DATA.query('ID_1 == ID_2 and ID_type.isin(["11", "23", "46"])').ID_1.nunique()
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