diff --git a/tests/dash/app_dropdown.py b/tests/dash/app_dropdown.py
new file mode 100644
index 000000000..6f9bfeb91
--- /dev/null
+++ b/tests/dash/app_dropdown.py
@@ -0,0 +1,189 @@
+from collections import OrderedDict
+from dash.dependencies import Input, Output
+import dash_core_components as dcc
+import dash_html_components as html
+import pandas as pd
+from textwrap import dedent
+
+import dash_table
+from index import app
+from .utils import section_title
+
+
+ID_PREFIX = "app_dropdown"
+IDS = {
+    "dropdown": ID_PREFIX,
+    "dropdown-by-cell": '{}-row-by-cell'.format(ID_PREFIX)
+}
+
+
+df = pd.DataFrame(OrderedDict([
+    ('climate',
+     ['Sunny', 'Snowy', 'Sunny', 'Rainy']),
+    ('temperature',
+     [13, 43, 50, 30]),
+    ('city',
+     ['NYC', 'Montreal', 'Miami', 'NYC'])
+]))
+
+df_per_row_dropdown = pd.DataFrame(OrderedDict([
+    ('City',
+     ['NYC', 'Montreal', 'Los Angeles']),
+    ('Neighborhood',
+     ['Brooklyn', 'Mile End', 'Venice']),
+    ('Temperature (F)',
+     [70, 60, 90]),
+]))
+
+
+def layout():
+    return html.Div([
+
+        dcc.Markdown(dedent('''
+        The Dash table includes support for per-column and
+        per-cell dropdowns. In future releases, this will
+        be tightly integrated with a more formal typing system.
+
+        For now, use the dropdown renderer as a way to limit the
+        options available when editing the values with an editable table.
+
+        ''')),
+
+        section_title('Dash Table with Per-Column Dropdowns'),
+
+        dash_table.Table(
+            id=IDS['dropdown'],
+            dataframe=df.to_dict('rows'),
+            columns=[
+                {'id': 'climate', 'name': 'climate'},
+                {'id': 'temperature', 'name': 'temperature'},
+                {'id': 'city', 'name': 'city'},
+            ],
+
+            editable=True,
+            column_static_dropdown=[
+                {
+                    'id': 'climate',
+                    'dropdown': [
+                        {'label': i, 'value': i}
+                        for i in df['climate'].unique()
+                    ]
+                },
+                {
+                    'id': 'city',
+                    'dropdown': [
+                        {'label': i, 'value': i}
+                        for i in df['city'].unique()
+                    ]
+                },
+            ]
+        ),
+
+        section_title('Dash Table with Per-Cell Dropdowns via Filtering UI'),
+
+        dash_table.Table(
+            id=IDS['dropdown-by-cell'],
+            dataframe=df_per_row_dropdown.to_dict('rows'),
+            columns=[
+                {'id': c, 'name': c}
+                for c in df_per_row_dropdown.columns
+            ],
+
+            editable=True,
+            column_conditional_dropdowns=[
+                {
+                    'id': 'Neighborhood',
+                    'dropdowns': [
+
+                        {
+                            'condition': 'City eq "NYC"',
+                            'dropdown': [
+                                {'label': i, 'value': i}
+                                for i in [
+                                    'Brooklyn',
+                                    'Queens',
+                                    'Staten Island'
+                                ]
+                            ]
+                        },
+
+                        {
+                            'condition': 'City eq "Montreal"',
+                            'dropdown': [
+                                {'label': i, 'value': i}
+                                for i in [
+                                    'Mile End',
+                                    'Plateau',
+                                    'Hochelaga'
+                                ]
+                            ]
+                        },
+
+                        {
+                            'condition': 'City eq "Los Angeles"',
+                            'dropdown': [
+                                {'label': i, 'value': i}
+                                for i in [
+                                    'Venice',
+                                    'Hollywood',
+                                    'Los Feliz'
+                                ]
+                            ]
+                        }
+
+                    ]
+                }
+            ]
+        ),
+
+        section_title('Dash Table with Per-Cell Dropdowns'),
+
+        html.Div('This example uses a deprecated API, `dropdown_properties`.'),
+
+        dash_table.Table(
+            id=IDS['dropdown-by-cell'],
+            dataframe=df_per_row_dropdown.to_dict('rows'),
+            columns=[
+                {'id': c, 'name': c}
+                for c in df_per_row_dropdown.columns
+            ],
+
+            editable=True,
+            dropdown_properties=[
+                {
+                    'options': [
+                        {'label': i, 'value': i}
+                        for i in [
+                            'Brooklyn',
+                            'Queens',
+                            'Staten Island'
+                        ]
+                    ]
+                },
+
+                {
+                    'options': [
+                        {'label': i, 'value': i}
+                        for i in [
+                            'Mile End',
+                            'Plateau',
+                            'Hochelaga'
+                        ]
+                    ]
+                },
+
+                {
+                    'options': [
+                        {'label': i, 'value': i}
+                        for i in [
+                            'Venice',
+                            'Hollywood',
+                            'Los Feliz'
+                        ]
+                    ]
+                },
+            ]
+
+        ),
+
+    ])