diff --git a/src/pykx/pandas_api/pandas_meta.py b/src/pykx/pandas_api/pandas_meta.py
index d0e44ec..e897711 100644
--- a/src/pykx/pandas_api/pandas_meta.py
+++ b/src/pykx/pandas_api/pandas_meta.py
@@ -153,6 +153,29 @@ def mean(self, axis: int = 0, numeric_only: bool = False):
             tab
         )
 
+    @api_return
+    def std(self, axis: int = 0, ddof: int = 1, numeric_only: bool = False):
+        tab = self
+        if 'Keyed' in str(type(tab)):
+            tab = q('{(keys x) _ 0!x}', tab)
+        if numeric_only:
+            tab = _get_numeric_only_subtable(tab)
+        key_str = '' if axis == 0 else '`$string '
+        val_str = '' if axis == 0 else '"f"$value '
+        query_str = 'cols[tab]' if axis == 0 else 'til[count[tab]]'
+        where_str = ' where not (::)~/:r[;1]'
+
+        res = q(f'{{[tab]{query_str}!count[{query_str}]#0n}}', tab)
+        if ddof != len(tab.pd()):
+            res = q(
+                '{[tab]'
+                f'r:{{[tab; x] ({key_str}x; {{avg sqrt (sum xexp[x-(avg x);2]) % count[x]-{ddof}}} {val_str}tab[x])}}[tab;] each {query_str};'
+                f'(,/) {{(enlist x 0)!(enlist x 1)}} each r{where_str}}}',
+                tab
+            )
+        return res
+
+
     @api_return
     def median(self, axis: int = 0, numeric_only: bool = False):
         tab = self
diff --git a/tests/test_pandas_api.py b/tests/test_pandas_api.py
index acfe55f..b987e78 100644
--- a/tests/test_pandas_api.py
+++ b/tests/test_pandas_api.py
@@ -1543,6 +1543,69 @@ def test_mean(kx, q):
         q_m = tab.mean(axis=1)
 
 
+def test_std(kx, q):
+    df = pd.DataFrame(
+        {
+            'a': [1, 2, 2, 4],
+            'b': [1, 2, 6, 7],
+            'c': [7, 8, 9, 10],
+            'd': [7, 11, 14, 14]
+        }
+    )
+    tab = kx.toq(df)
+    p_m = df.std()
+    q_m = tab.std()
+    for c in q.key(q_m).py():
+        assert p_m[c] == q_m[c].py()
+    p_m = df.std(axis=1)
+    q_m = tab.std(axis=1)
+    for c in range(len(q.cols(tab))):
+        assert p_m[c] == q_m[q('{`$string x}', c)].py()
+    p_m = df.std(ddof=0)
+    q_m = tab.std(ddof=0)
+    for c in q.key(q_m).py():
+        assert p_m[c] == q_m[c].py()
+
+    p_m = df.std(ddof=4)
+    q_m = tab.std(ddof=4)
+    for c in q.key(q_m).py():
+        assert np.isnan(p_m[c]) == np.isnan(q_m[c].py())
+
+    q['tab'] = kx.toq(df)
+    tab = q('1!`idx xcols update idx: til count tab from tab')
+    p_m = df.std()
+    q_m = tab.std()
+    for c in q.key(q_m).py():
+        assert p_m[c] == q_m[c].py()
+    p_m = df.std(axis=1)
+    q_m = tab.std(axis=1)
+    for c in range(len(q.cols(tab)) - 1):
+        assert p_m[c] == q_m[q('{`$string x}', c)].py()
+
+    df = pd.DataFrame(
+        {
+            'a': [1, 2, 2, 4],
+            'b': [1, 2, 6, 7],
+            'c': [7, 8, 9, 10],
+            'd': ['foo', 'bar', 'baz', 'qux']
+        }
+    )
+    tab = kx.toq(df)
+    p_m = df.std(numeric_only=True)
+    q_m = tab.std(numeric_only=True)
+    for c in q.key(q_m).py():
+        assert p_m[c] == q_m[c].py()
+    p_m = df.std(axis=1, numeric_only=True)
+    q_m = tab.std(axis=1, numeric_only=True)
+    for c in range(len(q.cols(tab))):
+        assert p_m[c] == q_m[q('{`$string x}', c)].py()
+
+    with pytest.raises(kx.QError):
+        q_m = tab.std()
+    with pytest.raises(kx.QError):
+        q_m = tab.std(axis=1)
+
+
 def test_median(kx, q):
     df = pd.DataFrame(
         {
@@ -2029,3 +2092,4 @@ def test_keyed_loc_fixes(q):
         mkt[['k1', 'y']]
     with pytest.raises(KeyError):
         mkt['k1']
+