Replace value by condition across entire polars df

Question

I'd like to replace any value greater than some condition with zero for any column except the date column in a df. The closest I've found it

df.with_columns( 
   pl.when(pl.any_horizontal(pl.col(pl.Float32) > 20))
   .then(0)
   .otherwise(pl.col(pl.Float32))
)

But this will zero out the entire row.

My not working code is -

df=df.select(
    pl.col("date"),
    pl.when(pl.col(pl.Float32) > 20).then(0))

In Pandas I would do something like

df.where(df>2, 0)

if you get error then show it in question (not in comments) as text (not image) — furas
– furas, Commented Nov 5 at 0:37
maybe better create minimal working code with small example data directly in code (and with expected output) - so we could simply copy and test it. — furas
– furas, Commented Nov 5 at 0:37

thefrollickingnerd · Accepted Answer · 2025-11-05 00:42:35Z

2

I found the answer -

test = test.with_columns(
    pl.when(pl.col(pl.Float32) > 8)
      .then(0)
      .otherwise(pl.col(pl.Float32)).name.keep()
)

I needed otherwise and to explicitly keep the column names. I thought the expression expansion was the issue but this works.

answered Nov 5 at 0:42

thefrollickingnerd

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3 Comments

Henry Harbeck Nov 6 at 8:12

Technically, you do not answer your own question. You wanted to "replace any value... for any column except the date column", but instead replaced it for only float32 columns

Dean MacGregor Nov 6 at 12:29

but their answer would work with pl.all(). I think the important bit is they're not having to list out the column names.

thefrollickingnerd Nov 10 at 2:02

I guess the unsaid part of my question is every other column is a float except the date column so this works for my purposes. As Dean said, I didn't want to list every column

Henry Harbeck · Accepted Answer · 2025-11-06 08:09:46Z

2

df = pl.DataFrame({
    "date": [date(2025, 1, 1), date(2026, 1, 1)],
    "a": [1, 3],
    "b": [4.5, 1]
})

cols_excl_date = pl.exclude("date")

df.with_columns(pl.when(cols_excl_date <= 2).then(cols_excl_date).otherwise(0))

# or this works too

df.with_columns(pl.when(cols_excl_date > 2).then(0).otherwise(cols_excl_date).name.keep())

answered Nov 6 at 8:09

Henry Harbeck

1,8632 silver badges14 bronze badges

1 Comment

thefrollickingnerd Nov 10 at 2:03

Great to know you can do col expression expansion outside the select statements.

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