code: def cov(a: IntoExpr, b: IntoExpr, ddof: int = 1) -> Expr:
      """
      Compute the covariance between two columns/ expressions.
  
      Parameters
      ----------
      a
          Column name or Expression.
      b
          Column name or Expression.
      ddof
          "Delta Degrees of Freedom": the divisor used in the calculation is N - ddof,
          where N represents the number of elements.
          By default ddof is 1.
  
      Examples
      --------
      >>> df = pl.DataFrame({"a": [1, 8, 3], "b": [4, 5, 2], "c": ["foo", "bar", "foo"]})
      >>> df.select(pl.cov("a", "b"))
      shape: (1, 1)
      ┌─────┐
      │ a   │
      │ --- │
      │ f64 │
      ╞═════╡
      │ 3.0 │
      └─────┘
  
      """
      a = parse_as_expression(a)
      b = parse_as_expression(b)
      return wrap_expr(plr.cov(a, b, ddof))
  
imports: from __future__ import annotations
  import contextlib
  from typing import TYPE_CHECKING, Any, Callable, Iterable, Sequence, overload
  import polars._reexport
  import polars.functions
  from polars.datatypes import DTYPE_TEMPORAL_UNITS, Date, Datetime, Int64
  from polars.utils._async import _AioDataFrameResult, _GeventDataFrameResult
  from polars.utils._parse_expr_input import parse_as_expression, parse_as_list_of_expressions
  from polars.utils._wrap import wrap_df, wrap_expr
  from polars.utils.deprecation import deprecate_renamed_function
label_desc: Use image node_id 15 for calling a global function with example usage: cov(a, b, ddof) and returns: wrap_expr