When I try to use numpy.mean within a polars dataframe I get an error message:

import numpy as np #v2.1.0
import polars as pl #v1.6.0
from polars import col

TRIALS = 1
SIMS = 10

np.random.seed(42)

df = pl.DataFrame({
  'a': np.random.binomial(TRIALS, .45, SIMS),
  'b': np.random.binomial(TRIALS, .5, SIMS),
  'c': np.random.binomial(TRIALS, .55, SIMS)
})

df.head()

df.with_columns(
  z_0 = np.mean(col("a"))
).head()

TypeError: mean() got an unexpected keyword argument 'axis'

Adding an explicit axis argument will not change the error.

df.with_columns(
  z_0 = np.mean(a=col("a"), axis=0)
).head()

TypeError: mean() got an unexpected keyword argument 'axis'

I know that I could complete this computation with:

df.with_columns(
  z_0 = ncol("a").mean()
).head()

But I am trying to understand how non-polars functions work within polars.