[Python] Delete row with negative data in polars, if row with same value in one column and...

Lets assume I have this Polars df:

import polars as pl

df = pl.DataFrame({'name': ['a', 'a', 'b', 'b'],
'found': ['yes', 'no', 'no', 'no'],
'found_in_iteration': ['1', 'not_found', 'not_found', 'not_found']})


(This df was generated in two iterations and for a some data was found in the first, but not in the second and for b no data was found in any iteration.) No I want to keep only those rows, where data was found, but if for one name, not data was found at all, I want to keep this information that it was not found once. The latter is pretty easy doable with unique(), but how do I get rid of the a,no row, if an a,yes exists. The solution should be usable even with more iterations like here:

df = pl.DataFrame({'name': ['a', 'a', 'a', 'b', 'b', 'b', 'c', 'c', 'c'],
'found': ['yes', 'no', 'yes', 'no', 'no', 'no', 'no', 'yes', 'no'],
'found_in_iteration': ['1', 'not_found', '3', 'not_found', 'not_found', 'not_found', 'not_found', '2', 'not_found']})


Here, a was found in two iterations, b was found not at all and c was found in one. Here for a, both columns with found == yes should be kept, for c, the one column with found == yes should be kept and for b one column with found == no should be kept. So this:

shape: (9, 3)
┌──────┬───────┬────────────────────┐
│ name ┆ found ┆ found_in_iteration │
│ --- ┆ --- ┆ --- │
│ str ┆ str ┆ str │
╞══════╪═══════╪════════════════════╡
│ a ┆ yes ┆ 1 │
│ a ┆ no ┆ not_found │
│ a ┆ yes ┆ 3 │
│ b ┆ no ┆ not_found │
│ b ┆ no ┆ not_found │
│ b ┆ no ┆ not_found │
│ c ┆ no ┆ not_found │
│ c ┆ yes ┆ 2 │
│ c ┆ no ┆ not_found │
└──────┴───────┴────────────────────┘


should be reduced to this:

shape: (9, 3)
┌──────┬───────┬────────────────────┐
│ name ┆ found ┆ found_in_iteration │
│ --- ┆ --- ┆ --- │
│ str ┆ str ┆ str │
╞══════╪═══════╪════════════════════╡
│ a ┆ yes ┆ 1 │
│ a ┆ yes ┆ 3 │
│ b ┆ no ┆ not_found │
│ c ┆ yes ┆ 2 │
└──────┴───────┴────────────────────┘

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