PR for DOC: inconsistency in doc argument types #40560

pandas/core/algorithms.py

@@ -1546,13 +1546,13 @@ def searchsorted(arr, value, side="left", sorter=None) -> np.ndarray:
         Input array. If `sorter` is None, then it must be sorted in
         ascending order, otherwise `sorter` must be an array of indices
         that sort it.
-    value : array_like
+    value : array-like
         Values to insert into `arr`.
     side : {'left', 'right'}, optional
         If 'left', the index of the first suitable location found is given.
         If 'right', return the last such index.  If there is no suitable
         index, return either 0 or N (where N is the length of `self`).
-    sorter : 1-D array_like, optional
+    sorter : 1-D array-like, optional
         Optional array of integer indices that sort array a into ascending
         order. They are typically the result of argsort.
 

pandas/core/array_algos/replace.py

@@ -45,14 +45,14 @@ def compare_or_regex_search(
     a: ArrayLike, b: Union[Scalar, Pattern], regex: bool, mask: np.ndarray
 ) -> Union[ArrayLike, bool]:
     """
-    Compare two array_like inputs of the same shape or two scalar values
+    Compare two array-like inputs of the same shape or two scalar values
 
     Calls operator.eq or re.search, depending on regex argument. If regex is
     True, perform an element-wise regex matching.
 
     Parameters
     ----------
-    a : array_like
+    a : array-like
     b : scalar or regex pattern
     regex : bool
     mask : np.ndarray[bool]

pandas/core/arrays/base.py

@@ -826,13 +826,13 @@ def searchsorted(self, value, side="left", sorter=None):
 
         Parameters
         ----------
-        value : array_like
+        value : array-like
             Values to insert into `self`.
         side : {'left', 'right'}, optional
             If 'left', the index of the first suitable location found is given.
             If 'right', return the last such index.  If there is no suitable
             index, return either 0 or N (where N is the length of `self`).
-        sorter : 1-D array_like, optional
+        sorter : 1-D array-like, optional
             Optional array of integer indices that sort array a into ascending
             order. They are typically the result of argsort.
 

pandas/core/base.py

@@ -1159,13 +1159,13 @@ def factorize(self, sort: bool = False, na_sentinel: Optional[int] = -1):
 
         Parameters
         ----------
-        value : array_like
+        value : array-like
             Values to insert into `self`.
         side : {{'left', 'right'}}, optional
             If 'left', the index of the first suitable location found is given.
             If 'right', return the last such index.  If there is no suitable
             index, return either 0 or N (where N is the length of `self`).
-        sorter : 1-D array_like, optional
+        sorter : 1-D array-like, optional
             Optional array of integer indices that sort `self` into ascending
             order. They are typically the result of ``np.argsort``.
 

pandas/core/indexes/base.py

@@ -6010,8 +6010,8 @@ def any(self, *args, **kwargs):
 
         Returns
         -------
-        any : bool or array_like (if axis is specified)
-            A single element array_like may be converted to bool.
+        any : bool or array-like (if axis is specified)
+            A single element array-like may be converted to bool.
 
         See Also
         --------
@@ -6054,7 +6054,7 @@ def all(self, *args, **kwargs):
 
         Returns
         -------
-        all : bool or array_like (if axis is specified)
+        all : bool or array-like (if axis is specified)
             A single element array_like may be converted to bool.
 
         See Also

pandas/core/indexes/multi.py

@@ -3893,7 +3893,7 @@ def maybe_droplevels(index: Index, key) -> Index:
     return index
 
 
-def _coerce_indexer_frozen(array_like, categories, copy: bool = False) -> np.ndarray:
+def _coerce_indexer_frozen(array-like, categories, copy: bool = False) -> np.ndarray:
     """
     Coerce the array_like indexer to the smallest integer dtype that can encode all
     of the given categories.

pandas/core/internals/blocks.py

@@ -1280,7 +1280,7 @@ def _unstack(self, unstacker, fill_value, new_placement):
         -------
         blocks : list of Block
             New blocks of unstacked values.
-        mask : array_like of bool
+        mask : array-like of bool
             The mask of columns of `blocks` we should keep.
         """
         new_values, mask = unstacker.get_new_values(

pandas/core/missing.py

@@ -524,11 +524,11 @@ def _from_derivatives(xi, yi, x, order=None, der=0, extrapolate=False):
 
     Parameters
     ----------
-    xi : array_like
+    xi : array-like
         sorted 1D array of x-coordinates
-    yi : array_like or list of array-likes
+    yi : array-like or list of array-likes
         yi[i][j] is the j-th derivative known at xi[i]
-    order: None or int or array_like of ints. Default: None.
+    order: None or int or array-like of ints. Default: None.
         Specifies the degree of local polynomials. If not None, some
         derivatives are ignored.
     der : int or list

pandas/plotting/_core.py

@@ -427,7 +427,7 @@ def hist_frame(
         y : label or position, optional
             Allows plotting of one column versus another. If not specified,
             all numerical columns are used.
-        color : str, array_like, or dict, optional
+        color : str, array-like, or dict, optional
             The color for each of the DataFrame's columns. Possible values are:
 
             - A single color string referred to by name, RGB or RGBA code,
@@ -1568,7 +1568,7 @@ def scatter(self, x, y, s=None, c=None, **kwargs):
         y : int or str
             The column name or column position to be used as vertical
             coordinates for each point.
-        s : str, scalar or array_like, optional
+        s : str, scalar or array-like, optional
             The size of each point. Possible values are:
 
             - A string with the name of the column to be used for marker's size.