diff --git a/.circleci/create_conda_optional_env.sh b/.circleci/create_conda_optional_env.sh
index c27cd43db3..17f3c999af 100755
--- a/.circleci/create_conda_optional_env.sh
+++ b/.circleci/create_conda_optional_env.sh
@@ -16,7 +16,7 @@ if [ ! -d $HOME/miniconda/envs/circle_optional ]; then
     # Create environment
     # PYTHON_VERSION=2.7 or 3.5
     $HOME/miniconda/bin/conda create -n circle_optional --yes python=$PYTHON_VERSION \
-requests nbformat six retrying psutil pandas decorator pytest mock nose poppler xarray scikit-image ipython jupyter ipykernel ipywidgets
+requests nbformat six retrying psutil pandas decorator pytest mock nose poppler xarray scikit-image ipython jupyter ipykernel ipywidgets statsmodels
 
     # Install orca into environment
     $HOME/miniconda/bin/conda install --yes -n circle_optional -c plotly plotly-orca==1.3.1
diff --git a/packages/python/plotly/plotly/express/_core.py b/packages/python/plotly/plotly/express/_core.py
index b2cd794db1..ae11d40f2b 100644
--- a/packages/python/plotly/plotly/express/_core.py
+++ b/packages/python/plotly/plotly/express/_core.py
@@ -241,18 +241,25 @@ def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
                     sorted_trace_data = trace_data.sort_values(by=args["x"])
                     y = sorted_trace_data[args["y"]]
                     x = sorted_trace_data[args["x"]]
-                    trace_patch["x"] = x
 
                     if x.dtype.type == np.datetime64:
                         x = x.astype(int) / 10 ** 9  # convert to unix epoch seconds
 
                     if attr_value == "lowess":
-                        trendline = sm.nonparametric.lowess(y, x)
+                        # missing ='drop' is the default value for lowess but not for OLS (None)
+                        # we force it here in case statsmodels change their defaults
+                        trendline = sm.nonparametric.lowess(y, x, missing="drop")
+                        trace_patch["x"] = trendline[:, 0]
                         trace_patch["y"] = trendline[:, 1]
                         hover_header = "<b>LOWESS trendline</b><br><br>"
                     elif attr_value == "ols":
-                        fit_results = sm.OLS(y.values, sm.add_constant(x.values)).fit()
+                        fit_results = sm.OLS(
+                            y.values, sm.add_constant(x.values), missing="drop"
+                        ).fit()
                         trace_patch["y"] = fit_results.predict()
+                        trace_patch["x"] = x[
+                            np.logical_not(np.logical_or(np.isnan(y), np.isnan(x)))
+                        ]
                         hover_header = "<b>OLS trendline</b><br>"
                         hover_header += "%s = %g * %s + %g<br>" % (
                             args["y"],
diff --git a/packages/python/plotly/plotly/tests/test_core/test_px/test_trendline.py b/packages/python/plotly/plotly/tests/test_core/test_px/test_trendline.py
new file mode 100644
index 0000000000..4c151148c1
--- /dev/null
+++ b/packages/python/plotly/plotly/tests/test_core/test_px/test_trendline.py
@@ -0,0 +1,14 @@
+import plotly.express as px
+import numpy as np
+
+
+def test_trendline_nan_values():
+    df = px.data.gapminder().query("continent == 'Oceania'")
+    start_date = 1970
+    df["pop"][df["year"] < start_date] = np.nan
+    modes = ["ols", "lowess"]
+    for mode in modes:
+        fig = px.scatter(df, x="year", y="pop", color="country", trendline=mode)
+        for trendline in fig["data"][1::2]:
+            assert trendline.x[0] >= start_date
+            assert len(trendline.x) == len(trendline.y)
diff --git a/packages/python/plotly/tox.ini b/packages/python/plotly/tox.ini
index 877ca978ac..dddc6e69ec 100644
--- a/packages/python/plotly/tox.ini
+++ b/packages/python/plotly/tox.ini
@@ -59,6 +59,7 @@ deps=
     pytest==3.5.1
     pandas==0.24.2
     xarray==0.10.9
+    statsmodels==0.10.2
     backports.tempfile==1.0
     optional: --editable=file:///{toxinidir}/../plotly-geo
     optional: numpy==1.16.5