diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 4e86b3710a1bd..7171a02fb5aa4 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -1233,8 +1233,8 @@ def from_dict(cls, data, orient="columns", dtype=None, columns=None) -> "DataFra
 
         See Also
         --------
-        DataFrame.from_records : DataFrame from ndarray (structured
-            dtype), list of tuples, dict, or DataFrame.
+        DataFrame.from_records : DataFrame from structured ndarray, sequence
+            of tuples or dicts, or DataFrame.
         DataFrame : DataFrame object creation using constructor.
 
         Examples
@@ -1633,9 +1633,13 @@ def from_records(
         """
         Convert structured or record ndarray to DataFrame.
 
+        Creates a DataFrame object from a structured ndarray, sequence of
+        tuples or dicts, or DataFrame.
+
         Parameters
         ----------
-        data : ndarray (structured dtype), list of tuples, dict, or DataFrame
+        data : structured ndarray, sequence of tuples or dicts, or DataFrame
+            Structured input data.
         index : str, list of fields, array-like
             Field of array to use as the index, alternately a specific set of
             input labels to use.
@@ -1656,6 +1660,47 @@ def from_records(
         Returns
         -------
         DataFrame
+
+        See Also
+        --------
+        DataFrame.from_dict : DataFrame from dict of array-like or dicts.
+        DataFrame : DataFrame object creation using constructor.
+
+        Examples
+        --------
+        Data can be provided as a structured ndarray:
+
+        >>> data = np.array([(3, 'a'), (2, 'b'), (1, 'c'), (0, 'd')],
+        ...                 dtype=[('col_1', 'i4'), ('col_2', 'U1')])
+        >>> pd.DataFrame.from_records(data)
+           col_1 col_2
+        0      3     a
+        1      2     b
+        2      1     c
+        3      0     d
+
+        Data can be provided as a list of dicts:
+
+        >>> data = [{'col_1': 3, 'col_2': 'a'},
+        ...         {'col_1': 2, 'col_2': 'b'},
+        ...         {'col_1': 1, 'col_2': 'c'},
+        ...         {'col_1': 0, 'col_2': 'd'}]
+        >>> pd.DataFrame.from_records(data)
+           col_1 col_2
+        0      3     a
+        1      2     b
+        2      1     c
+        3      0     d
+
+        Data can be provided as a list of tuples with corresponding columns:
+
+        >>> data = [(3, 'a'), (2, 'b'), (1, 'c'), (0, 'd')]
+        >>> pd.DataFrame.from_records(data, columns=['col_1', 'col_2'])
+           col_1 col_2
+        0      3     a
+        1      2     b
+        2      1     c
+        3      0     d
         """
         # Make a copy of the input columns so we can modify it
         if columns is not None: