Backport PR #39374: DOC: Clarify behavior for Series with dict-like data and index (#39645)

Co-authored-by: patrick <[email protected]>

Author: meeseeksmachine

pandas/core/series.py

@@ -169,8 +169,8 @@ class Series(base.IndexOpsMixin, generic.NDFrame):
         Values must be hashable and have the same length as `data`.
         Non-unique index values are allowed. Will default to
         RangeIndex (0, 1, 2, ..., n) if not provided. If data is dict-like
-        and index is None, then the values in the index are used to
-        reindex the Series after it is created using the keys in the data.
+        and index is None, then the keys in the data are used as the index. If the
+        index is not None, the resulting Series is reindexed with the index values.
     dtype : str, numpy.dtype, or ExtensionDtype, optional
         Data type for the output Series. If not specified, this will be
         inferred from `data`.
@@ -179,6 +179,33 @@ class Series(base.IndexOpsMixin, generic.NDFrame):
         The name to give to the Series.
     copy : bool, default False
         Copy input data.
+
+    Examples
+    --------
+    Constructing Series from a dictionary with an Index specified
+
+    >>> d = {'a': 1, 'b': 2, 'c': 3}
+    >>> ser = pd.Series(data=d, index=['a', 'b', 'c'])
+    >>> ser
+    a   1
+    b   2
+    c   3
+    dtype: int64
+
+    The keys of the dictionary match with the Index values, hence the Index
+    values have no effect.
+
+    >>> d = {'a': 1, 'b': 2, 'c': 3}
+    >>> ser = pd.Series(data=d, index=['x', 'y', 'z'])
+    >>> ser
+    x   NaN
+    y   NaN
+    z   NaN
+    dtype: float64
+
+    Note that the Index is first build with the keys from the dictionary.
+    After this the Series is reindexed with the given Index values, hence we
+    get all NaN as a result.
     """
 
     _typ = "series"