Add pandas API

docs/user-guide/advanced/Pandas_API.ipynb

@@ -3014,6 +3014,105 @@
     "\n",
     "Example Table."
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7f08eb84",
+   "metadata": {},
+   "source": [
+    "## Comparison\n",
+    "\n",
+    "### Table.isin()\n",
+    "\n",
+    "```\n",
+    "Table.apply(\n",
+    "    values\n",
+    ")\n",
+    "```\n",
+    "\n",
+    "Whether each element in the DataFrame is contained in values.\n",
+    "\n",
+    "**Parameters:**\n",
+    "\n",
+    "| Name             | Type                                | Description                                                                  | Default  |\n",
+    "| :--------------: | :---------------------------------: | :-------------------------------------------------------------------------- | :------: |\n",
+    "| values | Union[List, dict, Table, KeyedTable] | The result will only be true at a location if all the labels match. If values is a dict, the keys must be the column names, which must match. If values is a Table or KeyedTable, then both the index and column labels must match. |  None|\n",
+    "\n",
+    "\n",
+    "**Returns:**\n",
+    "\n",
+    "| Type                      | Description                                     |\n",
+    "| :-----------------------: | :---------------------------------------------- |\n",
+    "| Table | Boolean type Table/KeyedTable showing whether each element in the DataFrame is contained in values.|\n",
+    "\n",
+    "**Examples:**\n",
+    "\n",
+    "Example Table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f6e453c8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tab = kx.Table(data={'x': list(range(3)), 'y': [\"A\", \"B\", \"C\"]})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aadd23c1",
+   "metadata": {},
+   "source": [
+    "Find if element \"A\" or \"1\" is in the table:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d41d40e0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tab.isin([\"A\", 1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cff856fe",
+   "metadata": {},
+   "source": [
+    "Find if element \"A\" is in colum \"y\":"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bccf59d9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tab.isin({\"y\": [\"A\"]})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ed704cce",
+   "metadata": {},
+   "source": [
+    "Find if element \"A\" is in the first position of \"y\" column:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "41840cc0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tab.isin(kx.Table(data={\"y\":[\"A\"]}))"
+   ]
   }
  ],
  "metadata": {
@@ -3032,7 +3131,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,