diff --git a/doc/source/user_guide/style.ipynb b/doc/source/user_guide/style.ipynb
index 12dd72f761408..24f344488d1ca 100644
--- a/doc/source/user_guide/style.ipynb
+++ b/doc/source/user_guide/style.ipynb
@@ -793,7 +793,8 @@
    "source": [
     "The next option you have are \"table styles\".\n",
     "These are styles that apply to the table as a whole, but don't look at the data.\n",
-    "Certain stylings, including pseudo-selectors like `:hover` can only be used this way."
+    "Certain stylings, including pseudo-selectors like `:hover` can only be used this way.\n",
+    "These can also be used to set specific row or column based class selectors, as will be shown."
    ]
   },
   {
@@ -831,9 +832,32 @@
     "The value for `props` should be a list of tuples of `('attribute', 'value')`.\n",
     "\n",
     "`table_styles` are extremely flexible, but not as fun to type out by hand.\n",
-    "We hope to collect some useful ones either in pandas, or preferable in a new package that [builds on top](#Extensibility) the tools here."
+    "We hope to collect some useful ones either in pandas, or preferable in a new package that [builds on top](#Extensibility) the tools here.\n",
+    "\n",
+    "`table_styles` can be used to add column and row based class descriptors. For large tables this can increase performance by avoiding repetitive individual css for each cell, and it can also simplify style construction in some cases.\n",
+    "If `table_styles` is given as a dictionary each key should be a specified column or index value and this will map to specific class CSS selectors of the given column or row.\n",
+    "\n",
+    "Note that `Styler.set_table_styles` will overwrite existing styles but can be chained by setting the `overwrite` argument to `False`."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "html = html.set_table_styles({\n",
+    "    'B': [dict(selector='', props=[('color', 'green')])],\n",
+    "    'C': [dict(selector='td', props=[('color', 'red')])], \n",
+    "    }, overwrite=False)\n",
+    "html"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -922,10 +946,12 @@
     "- DataFrame only `(use Series.to_frame().style)`\n",
     "- The index and columns must be unique\n",
     "- No large repr, and performance isn't great; this is intended for summary DataFrames\n",
-    "- You can only style the *values*, not the index or columns\n",
+    "- You can only style the *values*, not the index or columns (except with `table_styles` above)\n",
     "- You can only apply styles, you can't insert new HTML entities\n",
     "\n",
-    "Some of these will be addressed in the future.\n"
+    "Some of these will be addressed in the future.\n",
+    "Performance can suffer when adding styles to each cell in a large DataFrame.\n",
+    "It is recommended to apply table or column based styles where possible to limit overall HTML length, as well as setting a shorter UUID to avoid unnecessary repeated data transmission. \n"
    ]
   },
   {
diff --git a/doc/source/whatsnew/v1.2.0.rst b/doc/source/whatsnew/v1.2.0.rst
index 727b5ec92bdc4..ce0245036aded 100644
--- a/doc/source/whatsnew/v1.2.0.rst
+++ b/doc/source/whatsnew/v1.2.0.rst
@@ -232,6 +232,7 @@ Other enhancements
 - :class:`Index` with object dtype supports division and multiplication (:issue:`34160`)
 - :meth:`DataFrame.explode` and :meth:`Series.explode` now support exploding of sets (:issue:`35614`)
 - :meth:`DataFrame.hist` now supports time series (datetime) data (:issue:`32590`)
+- :meth:`Styler.set_table_styles` now allows the direct styling of rows and columns and can be chained (:issue:`35607`)
 - ``Styler`` now allows direct CSS class name addition to individual data cells (:issue:`36159`)
 - :meth:`Rolling.mean()` and :meth:`Rolling.sum()` use Kahan summation to calculate the mean to avoid numerical problems (:issue:`10319`, :issue:`11645`, :issue:`13254`, :issue:`32761`, :issue:`36031`)
 - :meth:`DatetimeIndex.searchsorted`, :meth:`TimedeltaIndex.searchsorted`, :meth:`PeriodIndex.searchsorted`, and :meth:`Series.searchsorted` with datetimelike dtypes will now try to cast string arguments (listlike and scalar) to the matching datetimelike type (:issue:`36346`)
diff --git a/pandas/io/formats/style.py b/pandas/io/formats/style.py
index 4b7a5e76cb475..638b4b1aed774 100644
--- a/pandas/io/formats/style.py
+++ b/pandas/io/formats/style.py
@@ -991,20 +991,46 @@ def set_caption(self, caption: str) -> "Styler":
         self.caption = caption
         return self
 
-    def set_table_styles(self, table_styles) -> "Styler":
+    def set_table_styles(self, table_styles, axis=0, overwrite=True) -> "Styler":
         """
         Set the table styles on a Styler.
 
         These are placed in a ``<style>`` tag before the generated HTML table.
 
+        This function can be used to style the entire table, columns, rows or
+        specific HTML selectors.
+
         Parameters
         ----------
-        table_styles : list
-            Each individual table_style should be a dictionary with
-            ``selector`` and ``props`` keys. ``selector`` should be a CSS
-            selector that the style will be applied to (automatically
-            prefixed by the table's UUID) and ``props`` should be a list of
-            tuples with ``(attribute, value)``.
+        table_styles : list or dict
+            If supplying a list, each individual table_style should be a
+            dictionary with ``selector`` and ``props`` keys. ``selector``
+            should be a CSS selector that the style will be applied to
+            (automatically prefixed by the table's UUID) and ``props``
+            should be a list of tuples with ``(attribute, value)``.
+            If supplying a dict, the dict keys should correspond to
+            column names or index values, depending upon the specified
+            `axis` argument. These will be mapped to row or col CSS
+            selectors. MultiIndex values as dict keys should be
+            in their respective tuple form. The dict values should be
+            a list as specified in the form with CSS selectors and
+            props that will be applied to the specified row or column.
+
+            .. versionchanged:: 1.2.0
+
+        axis : {0 or 'index', 1 or 'columns', None}, default 0
+            Apply to each column (``axis=0`` or ``'index'``), to each row
+            (``axis=1`` or ``'columns'``). Only used if `table_styles` is
+            dict.
+
+            .. versionadded:: 1.2.0
+
+        overwrite : boolean, default True
+            Styles are replaced if `True`, or extended if `False`. CSS
+            rules are preserved so most recent styles set will dominate
+            if selectors intersect.
+
+            .. versionadded:: 1.2.0
 
         Returns
         -------
@@ -1012,13 +1038,48 @@ def set_table_styles(self, table_styles) -> "Styler":
 
         Examples
         --------
-        >>> df = pd.DataFrame(np.random.randn(10, 4))
+        >>> df = pd.DataFrame(np.random.randn(10, 4),
+        ...                   columns=['A', 'B', 'C', 'D'])
         >>> df.style.set_table_styles(
         ...     [{'selector': 'tr:hover',
         ...       'props': [('background-color', 'yellow')]}]
         ... )
+
+        Adding column styling by name
+
+        >>> df.style.set_table_styles({
+        ...     'A': [{'selector': '',
+        ...            'props': [('color', 'red')]}],
+        ...     'B': [{'selector': 'td',
+        ...            'props': [('color', 'blue')]}]
+        ... }, overwrite=False)
+
+        Adding row styling
+
+        >>> df.style.set_table_styles({
+        ...     0: [{'selector': 'td:hover',
+        ...          'props': [('font-size', '25px')]}]
+        ... }, axis=1, overwrite=False)
         """
-        self.table_styles = table_styles
+        if is_dict_like(table_styles):
+            if axis in [0, "index"]:
+                obj, idf = self.data.columns, ".col"
+            else:
+                obj, idf = self.data.index, ".row"
+
+            table_styles = [
+                {
+                    "selector": s["selector"] + idf + str(obj.get_loc(key)),
+                    "props": s["props"],
+                }
+                for key, styles in table_styles.items()
+                for s in styles
+            ]
+
+        if not overwrite and self.table_styles is not None:
+            self.table_styles.extend(table_styles)
+        else:
+            self.table_styles = table_styles
         return self
 
     def set_na_rep(self, na_rep: str) -> "Styler":
diff --git a/pandas/tests/io/formats/test_style.py b/pandas/tests/io/formats/test_style.py
index 79f9bbace000e..64fe8a7730ae2 100644
--- a/pandas/tests/io/formats/test_style.py
+++ b/pandas/tests/io/formats/test_style.py
@@ -1712,6 +1712,28 @@ def test_set_data_classes(self, classes):
         assert '<td  class="data row1 col0" >2</td>' in s
         assert '<td  class="data row1 col1" >3</td>' in s
 
+    def test_chaining_table_styles(self):
+        # GH 35607
+        df = DataFrame(data=[[0, 1], [1, 2]], columns=["A", "B"])
+        styler = df.style.set_table_styles(
+            [{"selector": "", "props": [("background-color", "yellow")]}]
+        ).set_table_styles(
+            [{"selector": ".col0", "props": [("background-color", "blue")]}],
+            overwrite=False,
+        )
+        assert len(styler.table_styles) == 2
+
+    def test_column_and_row_styling(self):
+        # GH 35607
+        df = DataFrame(data=[[0, 1], [1, 2]], columns=["A", "B"])
+        s = Styler(df, uuid_len=0)
+        s = s.set_table_styles({"A": [{"selector": "", "props": [("color", "blue")]}]})
+        assert "#T__ .col0 {\n          color: blue;\n    }" in s.render()
+        s = s.set_table_styles(
+            {0: [{"selector": "", "props": [("color", "blue")]}]}, axis=1
+        )
+        assert "#T__ .row0 {\n          color: blue;\n    }" in s.render()
+
     def test_colspan_w3(self):
         # GH 36223
         df = DataFrame(data=[[1, 2]], columns=[["l0", "l0"], ["l1a", "l1b"]])