add skew implementation

KxSystems · Dec 5, 2023 · f51d92d · f51d92d
1 parent 42470c8
commit f51d92d
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diff --git a/docs/user-guide/advanced/Pandas_API.ipynb b/docs/user-guide/advanced/Pandas_API.ipynb
@@ -2835,6 +2835,43 @@
     "tab.prod(numeric_only=True)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Table.skew()\n",
+    "\n",
+    "```\n",
+    "Table.skew(axis=0, skipna=True, numeric_only=False)\n",
+    "```\n",
+    "\n",
+    "Returns the skewness of all values across the given axis.\n",
+    "\n",
+    "**Parameters:**\n",
+    "\n",
+    "| Name         | Type | Description                                                                      | Default |\n",
+    "| :----------: | :--: | :------------------------------------------------------------------------------- | :-----: |\n",
+    "| axis         | int  | The axis to calculate the product across 0 is columns, 1 is rows.                | 0       |\n",
+    "| skipna       | bool | Ignore any null values along the axis.                                           | True    |\n",
+    "| numeric_only | bool | Only use columns of the table that are of a numeric data type.                   | False   |\n",
+    "\n",
+    "\n",
+    "**Returns:**\n",
+    "\n",
+    "| Type               | Description                                                          |\n",
+    "| :----------------: | :------------------------------------------------------------------- |\n",
+    "| Dictionary         | A dictionary where the key represent the column name / row number and the values are the result of calling `skew` on that column / row. |"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tab.skew(numeric_only=True)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "655c3ad2",
@@ -3317,7 +3354,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

diff --git a/src/pykx/pandas_api/pandas_meta.py b/src/pykx/pandas_api/pandas_meta.py
@@ -290,6 +290,17 @@ def prod(self, axis=0, skipna=True, numeric_only=False, min_count=0):
             min_count
         ), cols)
 
+    @convert_result
+    def skew(self, axis=0, skipna=True, numeric_only=False):
+        res, cols = preparse_computations(self, axis, skipna, numeric_only)
+        return (q(
+            '{[row]'
+            'm:{(sum(y-avg y)xexp x)%count y};'
+            'u:{sqrt[n*n-1]%neg[2]+n:count x};'
+            '{[u;m;x](u[x]*m[3][x]%(m[2][x]xexp 3%2))}[u;m]each row}',
+            res
+        ), cols)
+
     @convert_result
     def sum(self, axis=0, skipna=True, numeric_only=False, min_count=0):
         res, cols = preparse_computations(self, axis, skipna, numeric_only)