diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index a75e3960cda16..920b0f5ae7b51 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -6572,7 +6572,10 @@ def clip_upper(self, threshold, axis=None, inplace=False):
 
     def clip_lower(self, threshold, axis=None, inplace=False):
         """
-        Return copy of the input with values below a threshold truncated.
+        Trim values below a given threshold.
+
+        Elements below the `threshold` will be changed to match the
+        `threshold` value(s).
 
         Parameters
         ----------
@@ -6597,17 +6600,22 @@ def clip_lower(self, threshold, axis=None, inplace=False):
 
         See Also
         --------
-        Series.clip : Return copy of input with values below and above
-            thresholds truncated.
-        Series.clip_upper : Return copy of input with values above
-            threshold truncated.
+        DataFrame.clip : General purpose method to trim `DataFrame` values to
+            given threshold(s)
+        DataFrame.clip_upper : Trim `DataFrame` values above given
+            threshold(s)
+        Series.clip : General purpose method to trim `Series` values to given
+            threshold(s)
+        Series.clip_upper : Trim `Series` values above given threshold(s)
 
         Returns
         -------
-        clipped : same type as input
+        clipped
+            Original data with values trimmed.
 
         Examples
         --------
+
         Series single threshold clipping:
 
         >>> s = pd.Series([5, 6, 7, 8, 9])
@@ -6659,17 +6667,18 @@ def clip_lower(self, threshold, axis=None, inplace=False):
         `threshold` should be the same length as the axis specified by
         `axis`.
 
-        >>> df.clip_lower(np.array([3, 3, 5]), axis='index')
+        >>> df.clip_lower([3, 3, 5], axis='index')
            A  B
         0  3  3
         1  3  4
         2  5  6
 
-        >>> df.clip_lower(np.array([4, 5]), axis='columns')
+        >>> df.clip_lower([4, 5], axis='columns')
            A  B
         0  4  5
         1  4  5
         2  5  6
+
         """
         return self._clip_with_one_bound(threshold, method=self.ge,
                                          axis=axis, inplace=inplace)