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python dataframe python-polars

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Accepted Answer
April 29, 2025 Score: 1 Rep: 5,399 Quality: High Completeness: 80%

You need to collapse the multiple-generated-expressions (imagine three matrices come out of that first pl.all(), one for each column) into a single column. You can do that with pl.allhorizontal(your, columns, here):

>>> df.filter(pl.allhorizontal(pl.col('*').isnot_null()))
shape: (3, 3)
┌─────┬───────────┬───────────┐
│ id  ┆ variable1 ┆ variable2 │
│ --- ┆ ---       ┆ ---       │
│ i64 ┆ i64       ┆ i64       │
╞═════╪═══════════╪═══════════╡
│ 1   ┆ 15        ┆ 40        │
│ 3   ┆ 5         ┆ 50        │
│ 4   ┆ 10        ┆ 10        │
└─────┴───────────┴───────────┘
April 29, 2025 Score: 3 Rep: 119,217 Quality: Medium Completeness: 50% 
>>> df.filter(pl.allhorizontal(pl.all().isnot_null()))
shape: (3, 3)
┌─────┬───────────┬───────────┐
│ id  ┆ variable1 ┆ variable2 │
│ --- ┆ ---       ┆ ---       │
│ i64 ┆ i64       ┆ i64       │
╞═════╪═══════════╪═══════════╡
│ 1   ┆ 15        ┆ 40        │
│ 3   ┆ 5         ┆ 50        │
│ 4   ┆ 10        ┆ 10        │
└─────┴───────────┴───────────┘
April 29, 2025 Score: 1 Rep: 24,546 Quality: Medium Completeness: 60%

This is probably one place where it's useful to know that pl.all() is shorthand for pl.col("")

pl.all()



pl.col("")

It just means "all column names" in this sense. (i.e. SELECT * from SQL)

The allhorizontal() is still required.

df.filter(pl.allhorizontal(pl.all().isnotnull()))

shape: (3, 3)
┌─────┬───────────┬───────────┐
│ id  ┆ variable1 ┆ variable2 │
│ --- ┆ ---       ┆ ---       │
│ i64 ┆ i64       ┆ i64       │
╞═════╪═══════════╪═══════════╡
│ 1   ┆ 15        ┆ 40        │
│ 3   ┆ 5         ┆ 50        │
│ 4   ┆ 10        ┆ 10        │
└─────┴───────────┴───────────┘