diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 1587dd8798ec3..a4408d1f5d23d 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -6609,6 +6609,8 @@ def groupby(
             duplicate values for one index/column pair.
         DataFrame.unstack : Pivot based on the index values instead of a
             column.
+        wide_to_long : Wide panel to long format. Less flexible but more
+            user-friendly than melt.
 
         Notes
         -----
@@ -6763,6 +6765,10 @@ def pivot(self, index=None, columns=None, values=None) -> "DataFrame":
         --------
         DataFrame.pivot : Pivot without aggregation that can handle
             non-numeric data.
+        DataFrame.melt: Unpivot a DataFrame from wide to long format,
+            optionally leaving identifiers set.
+        wide_to_long : Wide panel to long format. Less flexible but more
+            user-friendly than melt.
 
         Examples
         --------
diff --git a/pandas/core/reshape/melt.py b/pandas/core/reshape/melt.py
index 1ba6854a79265..8724f7674f0c8 100644
--- a/pandas/core/reshape/melt.py
+++ b/pandas/core/reshape/melt.py
@@ -144,14 +144,43 @@ def melt(
 @deprecate_kwarg(old_arg_name="label", new_arg_name=None)
 def lreshape(data: "DataFrame", groups, dropna: bool = True, label=None) -> "DataFrame":
     """
-    Reshape long-format data to wide. Generalized inverse of DataFrame.pivot
+    Reshape wide-format data to long. Generalized inverse of DataFrame.pivot.
+
+    Accepts a dictionary, ``groups``, in which each key is a new column name
+    and each value is a list of old column names that will be "melted" under
+    the new column name as part of the reshape.
 
     Parameters
     ----------
     data : DataFrame
+        The wide-format DataFrame.
     groups : dict
-        {new_name : list_of_columns}
-    dropna : boolean, default True
+        {new_name : list_of_columns}.
+    dropna : bool, default True
+        Do not include columns whose entries are all NaN.
+    label : None
+        Not used.
+
+        .. deprecated:: 1.0.0
+
+    Returns
+    -------
+    DataFrame
+        Reshaped DataFrame.
+
+    See Also
+    --------
+    melt : Unpivot a DataFrame from wide to long format, optionally leaving
+        identifiers set.
+    pivot : Create a spreadsheet-style pivot table as a DataFrame.
+    DataFrame.pivot : Pivot without aggregation that can handle
+        non-numeric data.
+    DataFrame.pivot_table : Generalization of pivot that can handle
+        duplicate values for one index/column pair.
+    DataFrame.unstack : Pivot based on the index values instead of a
+        column.
+    wide_to_long : Wide panel to long format. Less flexible but more
+        user-friendly than melt.
 
     Examples
     --------
@@ -169,10 +198,6 @@ def lreshape(data: "DataFrame", groups, dropna: bool = True, label=None) -> "Dat
     1  Yankees  2007  573
     2  Red Sox  2008  545
     3  Yankees  2008  526
-
-    Returns
-    -------
-    reshaped : DataFrame
     """
     if isinstance(groups, dict):
         keys = list(groups.keys())
@@ -262,6 +287,18 @@ def wide_to_long(
         A DataFrame that contains each stub name as a variable, with new index
         (i, j).
 
+    See Also
+    --------
+    melt : Unpivot a DataFrame from wide to long format, optionally leaving
+        identifiers set.
+    pivot : Create a spreadsheet-style pivot table as a DataFrame.
+    DataFrame.pivot : Pivot without aggregation that can handle
+        non-numeric data.
+    DataFrame.pivot_table : Generalization of pivot that can handle
+        duplicate values for one index/column pair.
+    DataFrame.unstack : Pivot based on the index values instead of a
+        column.
+
     Notes
     -----
     All extra variables are left untouched. This simply uses