diff --git a/crates/polars-plan/src/dsl/mod.rs b/crates/polars-plan/src/dsl/mod.rs
index ac3439d20e3b..015e999851df 100644
--- a/crates/polars-plan/src/dsl/mod.rs
+++ b/crates/polars-plan/src/dsl/mod.rs
@@ -1885,12 +1885,17 @@ pub fn len() -> Expr {
     Expr::Len
 }
 
-/// First column in DataFrame.
+/// First column in a DataFrame.
 pub fn first() -> Expr {
     Expr::Nth(0)
 }
 
-/// Last column in DataFrame.
+/// Last column in a DataFrame.
 pub fn last() -> Expr {
     Expr::Nth(-1)
 }
+
+/// Nth column in a DataFrame.
+pub fn nth(n: i64) -> Expr {
+    Expr::Nth(n)
+}
diff --git a/py-polars/docs/source/reference/expressions/functions.rst b/py-polars/docs/source/reference/expressions/functions.rst
index 546c44360332..7fdde4dddac1 100644
--- a/py-polars/docs/source/reference/expressions/functions.rst
+++ b/py-polars/docs/source/reference/expressions/functions.rst
@@ -71,6 +71,7 @@ These functions are available from the Polars module root and can be used as exp
    min
    min_horizontal
    n_unique
+   nth
    ones
    quantile
    reduce
diff --git a/py-polars/polars/__init__.py b/py-polars/polars/__init__.py
index a2eaf7b826eb..29c5a66f061d 100644
--- a/py-polars/polars/__init__.py
+++ b/py-polars/polars/__init__.py
@@ -158,6 +158,7 @@
     min,
     min_horizontal,
     n_unique,
+    nth,
     ones,
     quantile,
     reduce,
@@ -401,6 +402,7 @@
     "mean",
     "median",
     "n_unique",
+    "nth",
     "quantile",
     "reduce",
     "rolling_corr",
diff --git a/py-polars/polars/functions/__init__.py b/py-polars/polars/functions/__init__.py
index 048587300c21..b658e5b4b3e9 100644
--- a/py-polars/polars/functions/__init__.py
+++ b/py-polars/polars/functions/__init__.py
@@ -61,6 +61,7 @@
     mean,
     median,
     n_unique,
+    nth,
     quantile,
     reduce,
     rolling_corr,
@@ -162,6 +163,7 @@
     "mean_horizontal",
     "median",
     "n_unique",
+    "nth",
     "quantile",
     "reduce",
     "rolling_corr",
diff --git a/py-polars/polars/functions/lazy.py b/py-polars/polars/functions/lazy.py
index 1a9059e00324..99a881cf6373 100644
--- a/py-polars/polars/functions/lazy.py
+++ b/py-polars/polars/functions/lazy.py
@@ -22,7 +22,6 @@
 with contextlib.suppress(ImportError):  # Module not available when building docs
     import polars.polars as plr
 
-
 if TYPE_CHECKING:
     from typing import Awaitable, Collection, Literal
 
@@ -518,18 +517,16 @@ def approx_n_unique(*columns: str) -> Expr:
 @deprecate_parameter_as_positional("column", version="0.20.4")
 def first(*columns: str) -> Expr:
     """
-    Get the first value.
-
-    This function has different behavior depending on the input type:
+    Get the first column or value.
 
-    - `None` -> Takes first column of a context (equivalent to `cs.first()`).
-    - `str` or `[str,]` -> Syntactic sugar for `pl.col(columns).first()`.
+    This function has different behavior depending on the presence of `columns`
+    values. If none given (the default), returns an expression that takes the first
+    column of the context; otherwise, takes the first value of the given column(s).
 
     Parameters
     ----------
     *columns
-        One or more column names. If not provided (default), returns an expression
-        to take the first column of the context instead.
+        One or more column names.
 
     Examples
     --------
@@ -540,6 +537,9 @@ def first(*columns: str) -> Expr:
     ...         "c": ["foo", "bar", "baz"],
     ...     }
     ... )
+
+    Return the first column:
+
     >>> df.select(pl.first())
     shape: (3, 1)
     ┌─────┐
@@ -551,6 +551,9 @@ def first(*columns: str) -> Expr:
     │ 8   │
     │ 3   │
     └─────┘
+
+    Return the first value for the given column(s):
+
     >>> df.select(pl.first("b"))
     shape: (1, 1)
     ┌─────┐
@@ -580,18 +583,16 @@ def first(*columns: str) -> Expr:
 @deprecate_parameter_as_positional("column", version="0.20.4")
 def last(*columns: str) -> Expr:
     """
-    Get the last value.
+    Get the last column or value.
 
-    This function has different behavior depending on the input type:
-
-    - `None` -> Takes last column of a context (equivalent to `cs.last()`).
-    - `str` or `[str,]` -> Syntactic sugar for `pl.col(columns).last()`.
+    This function has different behavior depending on the presence of `columns`
+    values. If none given (the default), returns an expression that takes the last
+    column of the context; otherwise, takes the last value of the given column(s).
 
     Parameters
     ----------
     *columns
-        One or more column names. If set to `None` (default), returns an expression
-        to take the last column of the context instead.
+        One or more column names.
 
     Examples
     --------
@@ -602,6 +603,9 @@ def last(*columns: str) -> Expr:
     ...         "c": ["foo", "bar", "baz"],
     ...     }
     ... )
+
+    Return the last column:
+
     >>> df.select(pl.last())
     shape: (3, 1)
     ┌─────┐
@@ -613,6 +617,9 @@ def last(*columns: str) -> Expr:
     │ bar │
     │ baz │
     └─────┘
+
+    Return the last value for the given column(s):
+
     >>> df.select(pl.last("a"))
     shape: (1, 1)
     ┌─────┐
@@ -639,6 +646,65 @@ def last(*columns: str) -> Expr:
     return F.col(*columns).last()
 
 
+def nth(n: int, *columns: str) -> Expr:
+    """
+    Get the nth column or value.
+
+    This function has different behavior depending on the presence of `columns`
+    values. If none given (the default), returns an expression that takes the nth
+    column of the context; otherwise, takes the nth value of the given column(s).
+
+    Parameters
+    ----------
+    n
+        Index of the column (or value) to get.
+    *columns
+        One or more column names. If omitted (the default), returns an
+        expression that takes the nth column of the context. Otherwise,
+        returns takes the nth value of the given column(s).
+
+    Examples
+    --------
+    >>> df = pl.DataFrame(
+    ...     {
+    ...         "a": [1, 8, 3],
+    ...         "b": [4, 5, 2],
+    ...         "c": ["foo", "bar", "baz"],
+    ...     }
+    ... )
+
+    Return the "nth" column:
+
+    >>> df.select(pl.nth(1))
+    shape: (3, 1)
+    ┌─────┐
+    │ b   │
+    │ --- │
+    │ i64 │
+    ╞═════╡
+    │ 4   │
+    │ 5   │
+    │ 2   │
+    └─────┘
+
+    Return the "nth" value for the given columns:
+
+    >>> df.select(pl.nth(-2, "b", "c"))
+    shape: (1, 2)
+    ┌─────┬─────┐
+    │ b   ┆ c   │
+    │ --- ┆ --- │
+    │ i64 ┆ str │
+    ╞═════╪═════╡
+    │ 5   ┆ bar │
+    └─────┴─────┘
+    """
+    if not columns:
+        return wrap_expr(plr.nth(n))
+
+    return F.col(*columns).get(n)
+
+
 def head(column: str, n: int = 10) -> Expr:
     """
     Get the first `n` rows.
diff --git a/py-polars/src/functions/lazy.rs b/py-polars/src/functions/lazy.rs
index 5266b9180aa3..a3755679ec09 100644
--- a/py-polars/src/functions/lazy.rs
+++ b/py-polars/src/functions/lazy.rs
@@ -386,6 +386,11 @@ pub fn last() -> PyExpr {
     dsl::last().into()
 }
 
+#[pyfunction]
+pub fn nth(n: i64) -> PyExpr {
+    dsl::nth(n).into()
+}
+
 #[pyfunction]
 pub fn lit(value: &PyAny, allow_object: bool) -> PyResult<PyExpr> {
     if value.is_instance_of::<PyBool>() {
diff --git a/py-polars/src/lib.rs b/py-polars/src/lib.rs
index ba5fccb77810..6abd7a3056e2 100644
--- a/py-polars/src/lib.rs
+++ b/py-polars/src/lib.rs
@@ -264,6 +264,7 @@ fn polars(py: Python, m: &Bound<PyModule>) -> PyResult<()> {
     m.add_wrapped(wrap_pyfunction!(functions::last)).unwrap();
     m.add_wrapped(wrap_pyfunction!(functions::lit)).unwrap();
     m.add_wrapped(wrap_pyfunction!(functions::map_mul)).unwrap();
+    m.add_wrapped(wrap_pyfunction!(functions::nth)).unwrap();
     m.add_wrapped(wrap_pyfunction!(functions::pearson_corr))
         .unwrap();
     m.add_wrapped(wrap_pyfunction!(functions::rolling_corr))
diff --git a/py-polars/tests/unit/dataframe/test_df.py b/py-polars/tests/unit/dataframe/test_df.py
index e2e7698c9889..0fc418c20141 100644
--- a/py-polars/tests/unit/dataframe/test_df.py
+++ b/py-polars/tests/unit/dataframe/test_df.py
@@ -2178,7 +2178,7 @@ def test_product() -> None:
     assert_frame_equal(out, expected, check_dtype=False)
 
 
-def test_first_last_expression(fruits_cars: pl.DataFrame) -> None:
+def test_first_last_nth_expressions(fruits_cars: pl.DataFrame) -> None:
     df = fruits_cars
     out = df.select(pl.first())
     assert out.columns == ["A"]
@@ -2186,6 +2186,15 @@ def test_first_last_expression(fruits_cars: pl.DataFrame) -> None:
     out = df.select(pl.last())
     assert out.columns == ["cars"]
 
+    out = df.select(pl.nth(0))
+    assert out.columns == ["A"]
+
+    out = df.select(pl.nth(1))
+    assert out.columns == ["fruits"]
+
+    out = df.select(pl.nth(-2))
+    assert out.columns == ["B"]
+
 
 def test_is_between(fruits_cars: pl.DataFrame) -> None:
     result = fruits_cars.select(pl.col("A").is_between(2, 4)).to_series()
diff --git a/py-polars/tests/unit/functions/test_functions.py b/py-polars/tests/unit/functions/test_functions.py
index 524df06eb9cc..e8b75888fe56 100644
--- a/py-polars/tests/unit/functions/test_functions.py
+++ b/py-polars/tests/unit/functions/test_functions.py
@@ -447,6 +447,7 @@ def test_lazy_functions() -> None:
         pl.first("a").name.suffix("_first"),
         pl.first("b", "c").name.suffix("_first"),
         pl.last("c", "b", "a").name.suffix("_last"),
+        pl.nth(1, "c", "a").name.suffix("_nth1"),
     )
     expected: dict[str, list[Any]] = {
         "b_var": [1.0],
@@ -469,6 +470,8 @@ def test_lazy_functions() -> None:
         "c_last": [4.0],
         "b_last": [3],
         "a_last": ["foo"],
+        "c_nth1": [2.0],
+        "a_nth1": ["bar"],
     }
     assert_frame_equal(
         out,