Add notebook regression tests.

tests/regression/test_datawarehouse_regression.py

@@ -4,6 +4,11 @@
 import os
 import pandas
 from pathlib import Path
+import plotly.express as px
+import plotly.io as pio
+# The next line is used for the line `pio.templates.default = 'timeseries'`.
+# Thus, we don't want the linter to think it is unused.
+import xdmod_data.themes  # noqa: F401
 import pytest
 from xdmod_data.warehouse import DataWarehouse
 
@@ -226,3 +231,50 @@ def test_get_durations(valid_dw):
         expected_durations.append(year)
     actual_durations = list(valid_dw.get_durations())
     assert expected_durations == actual_durations
+
+
+def test_first_example_notebook(valid_dw):
+    pio.templates.default = 'timeseries'
+    with valid_dw:
+        data = valid_dw.get_data(
+            duration=('2016-01-01', '2017-12-31'),
+            realm='Jobs',
+            metric='Number of Users: Active',
+        )
+    plot = px.line(data, y='Number of Users: Active')
+    plot.show()
+    data['Day Name'] = data.index.strftime('%a')
+    plot = px.box(
+        data,
+        x='Day Name',
+        y='Number of Users: Active',
+        category_orders={
+            'Day Name': ('Sun', 'Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat'),
+        },
+    )
+    plot.show()
+    metric_label = 'Number of Users: Active'
+    with valid_dw:
+        data = valid_dw.get_data(
+            duration=('2016-01-01', '2017-12-31'),
+            realm='Jobs',
+            metric=metric_label,
+            dimension='Resource',
+        )
+    plot = px.line(data, labels={'value': metric_label})
+    plot.show()
+    metric_label = 'Number of Users: Active'
+    with valid_dw:
+        data = valid_dw.get_data(
+            duration=('2016-01-01', '2017-12-31'),
+            realm='Jobs',
+            metric=metric_label,
+            dimension='Resource',
+            dataset_type='aggregate',
+        )
+    plot = px.bar(data, labels={'value': metric_label})
+    plot.update_layout(
+        showlegend=False,
+        xaxis_automargin=True,
+    )
+    plot.show()