Re-organize directory structure (#4971)

See discussion in #2491

Co-authored-by: Ivan Levkivskyi <ilevkivskyi@dropbox.com>

stdlib/statistics.pyi

@@ -0,0 +1,72 @@
+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
+
+_T = TypeVar("_T")
+# Most functions in this module accept homogeneous collections of one of these types
+_NumberT = TypeVar("_NumberT", float, Decimal, Fraction)
+
+# Used in mode, multimode
+_HashableT = TypeVar("_HashableT", bound=Hashable)
+
+class StatisticsError(ValueError): ...
+
+if sys.version_info >= (3, 8):
+    def fmean(data: Iterable[SupportsFloat]) -> float: ...
+    def geometric_mean(data: Iterable[SupportsFloat]) -> float: ...
+
+def mean(data: Iterable[_NumberT]) -> _NumberT: ...
+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: ...
+def median_grouped(data: Iterable[_NumberT], interval: _NumberT = ...) -> _NumberT: ...
+def mode(data: Iterable[_HashableT]) -> _HashableT: ...
+
+if sys.version_info >= (3, 8):
+    def multimode(data: Iterable[_HashableT]) -> List[_HashableT]: ...
+
+def pstdev(data: Iterable[_NumberT], mu: Optional[_NumberT] = ...) -> _NumberT: ...
+def pvariance(data: Iterable[_NumberT], mu: Optional[_NumberT] = ...) -> _NumberT: ...
+
+if sys.version_info >= (3, 8):
+    def quantiles(data: Iterable[_NumberT], *, n: int = ..., method: str = ...) -> List[_NumberT]: ...
+
+def stdev(data: Iterable[_NumberT], xbar: Optional[_NumberT] = ...) -> _NumberT: ...
+def variance(data: Iterable[_NumberT], xbar: Optional[_NumberT] = ...) -> _NumberT: ...
+
+if sys.version_info >= (3, 8):
+    class NormalDist:
+        def __init__(self, mu: float = ..., sigma: float = ...) -> None: ...
+        @property
+        def mean(self) -> float: ...
+        @property
+        def median(self) -> float: ...
+        @property
+        def mode(self) -> float: ...
+        @property
+        def stdev(self) -> float: ...
+        @property
+        def variance(self) -> float: ...
+        @classmethod
+        def from_samples(cls: Type[_T], data: Iterable[SupportsFloat]) -> _T: ...
+        def samples(self, n: int, *, seed: Optional[Any] = ...) -> List[float]: ...
+        def pdf(self, x: float) -> float: ...
+        def cdf(self, x: float) -> float: ...
+        def inv_cdf(self, p: float) -> float: ...
+        def overlap(self, other: NormalDist) -> float: ...
+        def quantiles(self, n: int = ...) -> List[float]: ...
+        if sys.version_info >= (3, 9):
+            def zscore(self, x: float) -> float: ...
+        def __add__(self, x2: Union[float, NormalDist]) -> NormalDist: ...
+        def __sub__(self, x2: Union[float, NormalDist]) -> NormalDist: ...
+        def __mul__(self, x2: float) -> NormalDist: ...
+        def __truediv__(self, x2: float) -> NormalDist: ...
+        def __pos__(self) -> NormalDist: ...
+        def __neg__(self) -> NormalDist: ...
+        __radd__ = __add__
+        def __rsub__(self, x2: Union[float, NormalDist]) -> NormalDist: ...
+        __rmul__ = __mul__
+        def __hash__(self) -> int: ...