add round implementation

docs/user-guide/advanced/Pandas_API.ipynb

@@ -2259,6 +2259,71 @@
     "tab.abs(numeric_only=True)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "499cac52",
+   "metadata": {},
+   "source": [
+    "### Table.round()\n",
+    "\n",
+    "```\n",
+    "Table.round(self, decimals: Union[int, Dict[str, int]] = 0)\n",
+    "```\n",
+    "\n",
+    "Round a Table to a variable number of decimal places.\n",
+    "\n",
+    "\n",
+    "**Parameters:**\n",
+    "\n",
+    "| Name             | Type                | Description                                                   | Default |\n",
+    "| :--------------: | :-----------------: | :------------------------------------------------------------ | :-----: |\n",
+    "| decimals         | int or Dict or list | Number of decimal places to round each column to. If an int is given, round each column to the same number of places. Otherwise dict and list round to variable numbers of places. Column names should be in the keys if decimals is a dict-like, or in the index if decimals is a list. Any columns not included in decimals will be left as is. Elements of decimals which are not columns of the input will be ignored.| 0       |\n",
+    "\n",
+    "**Note: functionality for list nyi**\n",
+    "\n",
+    "**Returns:**\n",
+    "\n",
+    "| Type       | Description                                                                              |\n",
+    "| :--------: | :--------------------------------------------------------------------------------------- |\n",
+    "| Table      | A Table with the affected columns rounded to the specified number of decimal places. |\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1b629def",
+   "metadata": {},
+   "source": [
+    "If an integer is provided it rounds every float column to set decimals."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "08c182c9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tab.round(1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "28853fc0",
+   "metadata": {},
+   "source": [
+    "If a dict whose keys are the column names and its values are the decimals to round set column is provided, it will round them accordingly.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7640df4c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tab.round({\"price\": 1, \"traded\": 0})"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "ad57d9cf",
@@ -2975,7 +3040,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -2989,7 +3054,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.3"
+   "version": "3.8.10"
   }
  },
  "nbformat": 4,

src/pykx/pandas_api/pandas_meta.py

@@ -1,4 +1,5 @@
 from pykx.pandas_api import api_return
+from typing import Union, Dict
 
 
 def _init(_q):
@@ -209,6 +210,27 @@ def abs(self, numeric_only=False):
             tab = _get_numeric_only_subtable(self)
         return q.abs(tab)
 
+    @api_return
+    def round(self, decimals: Union[int, Dict[str, int]] = 0):
+        tab = self
+        if 'Keyed' in str(type(tab)):
+            tab = q('{(keys x) _ 0!x}', tab)
+
+        return q("""{[t;d]
+            generate_ops:{[vdic]
+                tuples:{flip(2;count[x])#key[x],value[x]}[vdic];
+                key[vdic]!({(({"F"$.Q.f[y]x}[;x[1]])';x[0])}')tuples};
+            get_float_cols:{(key[ct]@where 9=value[ct:abs type each first x])};
+            fcols:get_float_cols[t];
+            ops:$[-7h=type d;
+                [$[0=d;
+                    fcols!({(_:';x)}')fcols;
+                    [vdic:fcols!count[fcols]#d;
+                        generate_ops vdic]]];
+                    [vdic:(key[d]i)!value[d]i:where key[d] in fcols;
+                        generate_ops vdic]];
+            ![t;();0b;ops]}""", tab, decimals)
+
     @convert_result
     def all(self, axis=0, bool_only=False, skipna=True):
         res, cols = preparse_computations(self, axis, skipna, bool_only=bool_only)

tests/test_pandas_api.py

@@ -1774,6 +1774,22 @@ def test_pandas_abs(kx, q):
     with pytest.raises(kx.QError):
         tab.abs()
 
+def test_pandas_round(kx, q):
+    q_tab = q('([]c1:1.0 .1 .01 .001 .0001 .00001;'
+              'c2:1.0 1.2 1.02 1.002 1.0002 1.00002;'
+              'c3:til 6;'
+              'c4:`a`b`c`d`e`f)')
+    pd_tab = q_tab.pd()
+    round_dict = {'c1': 0, 'c2': 2}
+
+    assert all(pd_tab.round() == q_tab.round().pd())
+    assert all(q_tab.round(0).pd() == q_tab.round().pd())
+    assert all(pd_tab.round(2) == q_tab.round(2).pd())
+    assert all(pd_tab.round(round_dict) == q_tab.round(round_dict).pd())
+
+    round_dict_non_numerical = {'c1': 0, 'c3': 2, 'c4': 2}
+    assert all(pd_tab.round(round_dict_non_numerical) == q_tab.round(round_dict_non_numerical).pd())
+
 
 def test_pandas_min(q):
     tab = q('([] sym: 100?`foo`bar`baz`qux; price: 250.0f - 100?500.0f; ints: 100 - 100?200)')