diff --git a/packages/python/plotly/plotly/express/_core.py b/packages/python/plotly/plotly/express/_core.py
index dd2d53be1ed..167c8e90f93 100644
--- a/packages/python/plotly/plotly/express/_core.py
+++ b/packages/python/plotly/plotly/express/_core.py
@@ -1303,7 +1303,20 @@ def build_dataframe(args, constructor):
     # Cast data_frame argument to DataFrame (it could be a numpy array, dict etc.)
     df_provided = args["data_frame"] is not None
     if df_provided and not isinstance(args["data_frame"], pd.DataFrame):
-        args["data_frame"] = pd.DataFrame(args["data_frame"])
+        if hasattr(args["data_frame"], "__dataframe__"):
+            try:
+                import pandas.api.interchange
+            except ModuleNotFoundError:
+                raise NotImplementedError(
+                    "The dataframe you provided supports the dataframe interchange"
+                    "protocol, "
+                    "but pandas 1.5.0 or greater is required to consume it."
+                )
+            df_not_pandas = args["data_frame"]
+            df_pandas = pandas.api.interchange.from_dataframe(df_not_pandas)
+            args["data_frame"] = df_pandas
+        else:
+            args["data_frame"] = pd.DataFrame(args["data_frame"])
     df_input = args["data_frame"]
 
     # now we handle special cases like wide-mode or x-xor-y specification
diff --git a/packages/python/plotly/plotly/tests/test_optional/test_px/test_px_input.py b/packages/python/plotly/plotly/tests/test_optional/test_px/test_px_input.py
index 477e7dbcb04..b4fae3a6a5c 100644
--- a/packages/python/plotly/plotly/tests/test_optional/test_px/test_px_input.py
+++ b/packages/python/plotly/plotly/tests/test_optional/test_px/test_px_input.py
@@ -233,6 +233,19 @@ def test_build_df_with_index():
     assert_frame_equal(tips.reset_index()[out["data_frame"].columns], out["data_frame"])
 
 
+def test_build_df_protocol():
+    import vaex
+
+    # take out the 'species' columns since there are still some issues with strings
+    iris_pandas = px.data.iris()[["petal_width", "sepal_length"]]
+    iris_vaex = vaex.from_pandas(iris_pandas)
+    args = dict(data_frame=iris_vaex, x="petal_width", y="sepal_length")
+    out = build_dataframe(args, go.Scatter)
+    assert_frame_equal(
+        iris_pandas.reset_index()[out["data_frame"].columns], out["data_frame"]
+    )
+
+
 def test_timezones():
     df = pd.DataFrame({"date": ["2015-04-04 19:31:30+1:00"], "value": [3]})
     df["date"] = pd.to_datetime(df["date"])