How to compare date values from rows in python polars?

Question

I have a dataframe with date of births as

pl.DataFrame({'idx':[1,2,3,4,5,6],
              'date_of_birth':['03/06/1990','3/06/1990','11/12/2000','01/02/2021','1/02/2021','3/06/1990']})

Here I would like to compare date of birth(Format: Month/Day/Year) of each row and tag yes if the months are equal such as 03 - 3, 01 -1.

There are dates as 03/06/1900, 3/06/1990, they are generally same. but here they are treated as different. How to figure out these kind scenarios ?

The expected output as:

Answer 1

Unlike other answers that use pandas to compute the result, let me do your CPU a favor and give a polars only solution.

df = pl.DataFrame({"idx":[1,2,3,4,5,6],
              "date_of_birth":["03/06/1990","3/06/1990","11/12/2000","01/02/2021","1/02/2021","3/06/1990"]})


df.with_columns(
   pl.when(
       pl.col("date_of_birth").str.to_date("%m/%d/%Y").dt.month().is_in([1, 3])
   )
   .then(pl.lit("Yes"))
   .otherwise(pl.lit("No"))
   .alias("match")
)

shape: (6, 3)
┌─────┬───────────────┬───────┐
│ idx ┆ date_of_birth ┆ match │
│ --- ┆ ---           ┆ ---   │
│ i64 ┆ str           ┆ str   │
╞═════╪═══════════════╪═══════╡
│ 1   ┆ 03/06/1990    ┆ Yes   │
│ 2   ┆ 3/06/1990     ┆ Yes   │
│ 3   ┆ 11/12/2000    ┆ No    │
│ 4   ┆ 01/02/2021    ┆ Yes   │
│ 5   ┆ 1/02/2021     ┆ Yes   │
│ 6   ┆ 3/06/1990     ┆ Yes   │
└─────┴───────────────┴───────┘