I am wondering if there's a way to do forward filling by columns in polars. df = pl.DataFrame( { "id": ["NY", "TK", "FD"], "eat2000": [1, 6, 3], "eat2001": [-2, None, 4], "eat2002": [None, None, None], "eat2003": [-9, 3, 8], "eat2004": [None, None, 8] } ); df shape: (3, 6) ┌─────┬─────────┬─────────┬─────────┬─────────┬─────────┐ │ id ┆ eat2000 ┆ eat2001 ┆ eat2002 ┆ eat2003 ┆ eat2004 │ │ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │ │ str ┆ i64 ┆ i64 ┆ f64 ┆ i64 ┆ i64 │ ╞═════╪═════════╪═════════╪═════════╪═════════╪═════════╡ │ NY ┆ 1 ┆ -2 ┆ null ┆ -9 ┆ null │ │ TK ┆ 6 ┆ null ┆ null ┆ 3 ┆ null │ │ FD ┆ 3 ┆ 4 ┆ null ┆ 8 ┆ 8 │ └─────┴─────────┴─────────┴─────────┴─────────┴─────────┘ I would like to do the equivlanet of .ffill(axis=1) in pandas. pl.from_pandas(df.to_pandas().ffill(axis=1)) shape: (3, 6) ┌─────┬─────────┬─────────┬─────────┬─────────┬─────────┐ │ id ┆ eat2000 ┆ eat2001 ┆ eat2002 ┆ eat2003 ┆ eat2004 │ │ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │ │ str ┆ i64 ┆ f64 ┆ f64 ┆ i64 ┆ f64 │ ╞═════╪═════════╪═════════╪═════════╪═════════╪═════════╡ │ NY ┆ 1 ┆ -2.0 ┆ -2.0 ┆ -9 ┆ -9.0 │ │ TK ┆ 6 ┆ 6.0 ┆ 6.0 ┆ 3 ┆ 3.0 │ │ FD ┆ 3 ┆ 4.0 ┆ 4.0 ┆ 8 ┆ 8.0 │ └─────┴─────────┴─────────┴─────────┴─────────┴─────────┘ Continue reading...