[Python] Convert Pandas pivot_table function into Polars pivot Function

I'm trying to convert some python pandas into polars. I'm stuck trying to convert pandas pivot_table function into polars. The following is the working pandas code. I can't seem to get the same behavior with the Polars pivot function. The polars pivot function forces the column parameter and uses the column values as headers instead of the column label as a header. I'm going for the same output below but with Polars instead of Pandas.

df = pd.DataFrame({"obj" : ["ring", "shoe", "ring"], "price":["65", "42", "65"], "value":["53", "55", "54"], "date":["2022-02-07", "2022-01-07", "2022-03-07"]})

table = pd.pivot_table(df, values=['price','value','date'],index=['obj'], aggfunc={'price': pd.Series.nunique,'value'd.Series.nunique,'date'd.Series.nunique})

print(table)


Outputs the following:

date price value
obj
ring 2 1 2
shoe 1 1 1

Continue reading...