def test_lazy_functions(): df = pl.DataFrame({ "a": ["foo", "bar", "2"], "b": [1, 2, 3], "c": [1.0, 2.0, 3.0] }) out = df[[pl.count("a")]] assert out["a"] == 3 assert pl.count(df["a"]) == 3 out = df[[ pl.var("b"), pl.std("b"), pl.max("b"), pl.min("b"), pl.sum("b"), pl.mean("b"), pl.median("b"), pl.n_unique("b"), pl.first("b"), pl.last("b"), ]] expected = 1.0 assert np.isclose(out.select_at_idx(0), expected) assert np.isclose(pl.var(df["b"]), expected) expected = 1.0 assert np.isclose(out.select_at_idx(1), expected) assert np.isclose(pl.std(df["b"]), expected) expected = 3 assert np.isclose(out.select_at_idx(2), expected) assert np.isclose(pl.max(df["b"]), expected) expected = 1 assert np.isclose(out.select_at_idx(3), expected) assert np.isclose(pl.min(df["b"]), expected) expected = 6 assert np.isclose(out.select_at_idx(4), expected) assert np.isclose(pl.sum(df["b"]), expected) expected = 2 assert np.isclose(out.select_at_idx(5), expected) assert np.isclose(pl.mean(df["b"]), expected) expected = 2 assert np.isclose(out.select_at_idx(6), expected) assert np.isclose(pl.median(df["b"]), expected) expected = 3 assert np.isclose(out.select_at_idx(7), expected) assert np.isclose(pl.n_unique(df["b"]), expected) expected = 1 assert np.isclose(out.select_at_idx(8), expected) assert np.isclose(pl.first(df["b"]), expected) expected = 3 assert np.isclose(out.select_at_idx(9), expected) assert np.isclose(pl.last(df["b"]), expected) expected = 3 assert np.isclose(out.select_at_idx(9), expected) assert np.isclose(pl.last(df["b"]), expected)
def test_lazy_functions(): df = pl.DataFrame({ "a": ["foo", "bar", "2"], "b": [1, 2, 3], "c": [1.0, 2.0, 3.0] }) out = df[[pl.count("a")]] assert out[0] == 3 assert pl.count(df["a"]) == 3 out = df[[ pl.var("b"), pl.std("b"), pl.max("b"), pl.min("b"), pl.sum("b"), pl.mean("b"), pl.median("b"), pl.n_unique("b"), pl.first("b"), pl.last("b"), ]] expected = 1.0 assert np.isclose(out[0], expected) assert np.isclose(pl.var(df["b"]), expected) expected = 1.0 assert np.isclose(out[1], expected) assert np.isclose(pl.std(df["b"]), expected) expected = 3 assert np.isclose(out[2], expected) assert np.isclose(pl.max(df["b"]), expected) expected = 1 assert np.isclose(out[3], expected) assert np.isclose(pl.min(df["b"]), expected) expected = 6 assert np.isclose(out[4], expected) assert np.isclose(pl.sum(df["b"]), expected) expected = 2 assert np.isclose(out[5], expected) assert np.isclose(pl.mean(df["b"]), expected) expected = 2 assert np.isclose(out[6], expected) assert np.isclose(pl.median(df["b"]), expected) expected = 3 assert np.isclose(out[7], expected) assert np.isclose(pl.n_unique(df["b"]), expected) expected = 1 assert np.isclose(out[8], expected) assert np.isclose(pl.first(df["b"]), expected) expected = 3 assert np.isclose(out[9], expected) assert np.isclose(pl.last(df["b"]), expected) expected = 3 assert np.isclose(out[9], expected) assert np.isclose(pl.last(df["b"]), expected)
from .dataset import df import polars as pl from polars import col df = df[[ pl.sum("random").alias("sum"), pl.min("random").alias("min"), pl.max("random").alias("max"), col("random").max().alias("other_max"), pl.std("random").alias("std dev"), pl.var("random").alias("variance"), ]]