From 482d38044b87ace2ddd28268a53652a7038ecdfd Mon Sep 17 00:00:00 2001
From: Shantanu <12621235+hauntsaninja@users.noreply.github.com>
Date: Mon, 10 May 2021 15:12:06 -0700
Subject: [PATCH] statistics: update for py310 (#5291)

---
 stdlib/statistics.pyi | 19 +++++++++++++++++--
 1 file changed, 17 insertions(+), 2 deletions(-)

diff --git a/stdlib/statistics.pyi b/stdlib/statistics.pyi
index d84296524..4435bf8a0 100644
--- a/stdlib/statistics.pyi
+++ b/stdlib/statistics.pyi
@@ -2,10 +2,11 @@ import sys
 from _typeshed import SupportsLessThanT
 from decimal import Decimal
 from fractions import Fraction
-from typing import Any, Hashable, Iterable, List, Optional, SupportsFloat, Type, TypeVar, Union
+from typing import Any, Hashable, Iterable, List, NamedTuple, Optional, Sequence, SupportsFloat, Type, TypeVar, Union
 
 _T = TypeVar("_T")
 # Most functions in this module accept homogeneous collections of one of these types
+_Number = Union[float, Decimal, Fraction]
 _NumberT = TypeVar("_NumberT", float, Decimal, Fraction)
 
 # Used in mode, multimode
@@ -18,7 +19,13 @@ if sys.version_info >= (3, 8):
     def geometric_mean(data: Iterable[SupportsFloat]) -> float: ...
 
 def mean(data: Iterable[_NumberT]) -> _NumberT: ...
-def harmonic_mean(data: Iterable[_NumberT]) -> _NumberT: ...
+
+if sys.version_info >= (3, 10):
+    def harmonic_mean(data: Iterable[_NumberT], weights: Optional[Iterable[_Number]] = ...) -> _NumberT: ...
+
+else:
+    def harmonic_mean(data: Iterable[_NumberT]) -> _NumberT: ...
+
 def median(data: Iterable[_NumberT]) -> _NumberT: ...
 def median_low(data: Iterable[SupportsLessThanT]) -> SupportsLessThanT: ...
 def median_high(data: Iterable[SupportsLessThanT]) -> SupportsLessThanT: ...
@@ -70,3 +77,11 @@ if sys.version_info >= (3, 8):
         def __rsub__(self, x2: Union[float, NormalDist]) -> NormalDist: ...
         __rmul__ = __mul__
         def __hash__(self) -> int: ...
+
+if sys.version_info >= (3, 10):
+    def correlation(__x: Sequence[_Number], __y: Sequence[_Number]) -> float: ...
+    def covariance(__x: Sequence[_Number], __y: Sequence[_Number]) -> float: ...
+    class LinearRegression(NamedTuple):
+        intercept: float
+        slope: float
+    def linear_regression(__regressor: Sequence[_Number], __dependent_variable: Sequence[_Number]) -> LinearRegression: ...