From 44d437d73791756f5adc6c30c3c6b845167ed0e6 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Mon, 26 Oct 2020 15:16:58 -0400
Subject: [PATCH 01/24] ma and ewm trendlines

---
 .../python/plotly/plotly/express/_core.py     | 43 +++++++++++++++----
 1 file changed, 35 insertions(+), 8 deletions(-)

diff --git a/packages/python/plotly/plotly/express/_core.py b/packages/python/plotly/plotly/express/_core.py
index f8e391053b9..6cf453ef430 100644
--- a/packages/python/plotly/plotly/express/_core.py
+++ b/packages/python/plotly/plotly/express/_core.py
@@ -313,7 +313,7 @@ def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
                     mapping_labels["count"] = "%{x}"
             elif attr_name == "trendline":
                 if (
-                    attr_value in ["ols", "lowess"]
+                    attr_value[0] in ["ols", "lowess", "ma", "ewm"]
                     and args["x"]
                     and args["y"]
                     and len(trace_data[[args["x"], args["y"]]].dropna()) > 1
@@ -345,19 +345,36 @@ def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
                             )
 
                     # preserve original values of "x" in case they're dates
-                    trace_patch["x"] = sorted_trace_data[args["x"]][
-                        np.logical_not(np.logical_or(np.isnan(y), np.isnan(x)))
-                    ]
+                    non_missing = np.logical_not(
+                        np.logical_or(np.isnan(y), np.isnan(x))
+                    )
+                    trace_patch["x"] = sorted_trace_data[args["x"]][non_missing]
 
-                    if attr_value == "lowess":
+                    if attr_value[0] == "lowess":
+                        alpha = attr_value[1] or 0.6666666
                         # 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")
+                        trendline = sm.nonparametric.lowess(
+                            y, x, missing="drop", frac=alpha
+                        )
                         trace_patch["y"] = trendline[:, 1]
                         hover_header = "<b>LOWESS trendline</b><br><br>"
-                    elif attr_value == "ols":
+                    elif attr_value[0] == "ma":
+                        trace_patch["y"] = (
+                            pd.Series(y[non_missing])
+                            .rolling(window=attr_value[1] or 3)
+                            .mean()
+                        )
+                    elif attr_value[0] == "ewm":
+                        trace_patch["y"] = (
+                            pd.Series(y[non_missing])
+                            .ewm(alpha=attr_value[1] or 0.5)
+                            .mean()
+                        )
+                    elif attr_value[0] == "ols":
+                        add_constant = attr_value[1] is not False
                         fit_results = sm.OLS(
-                            y, sm.add_constant(x), missing="drop"
+                            y, sm.add_constant(x) if add_constant else x, missing="drop"
                         ).fit()
                         trace_patch["y"] = fit_results.predict()
                         hover_header = "<b>OLS trendline</b><br>"
@@ -368,6 +385,12 @@ def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
                                 args["x"],
                                 fit_results.params[0],
                             )
+                        elif not add_constant:
+                            hover_header += "%s = %g* %s<br>" % (
+                                args["y"],
+                                fit_results.params[0],
+                                args["x"],
+                            )
                         else:
                             hover_header += "%s = %g<br>" % (
                                 args["y"],
@@ -1827,6 +1850,10 @@ def infer_config(args, constructor, trace_patch, layout_patch):
     ):
         args["facet_col_wrap"] = 0
 
+    if args.get("trendline", None) is not None:
+        if isinstance(args["trendline"], str):
+            args["trendline"] = (args["trendline"], None)
+
     # Compute applicable grouping attributes
     for k in group_attrables:
         if k in args:

From 10199859135384a50b4c62988b8cd0630d45162f Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Fri, 25 Dec 2020 10:43:13 -0500
Subject: [PATCH 02/24] extract trendline function API

---
 .../plotly/plotly/express/_chart_types.py     |   2 +
 .../python/plotly/plotly/express/_core.py     | 121 ++++++++++--------
 packages/python/plotly/plotly/express/_doc.py |   4 +
 3 files changed, 72 insertions(+), 55 deletions(-)

diff --git a/packages/python/plotly/plotly/express/_chart_types.py b/packages/python/plotly/plotly/express/_chart_types.py
index 6cfb6a90367..5051c8a5367 100644
--- a/packages/python/plotly/plotly/express/_chart_types.py
+++ b/packages/python/plotly/plotly/express/_chart_types.py
@@ -46,6 +46,7 @@ def scatter(
     marginal_x=None,
     marginal_y=None,
     trendline=None,
+    trendline_options=None,
     trendline_color_override=None,
     log_x=False,
     log_y=False,
@@ -90,6 +91,7 @@ def density_contour(
     marginal_x=None,
     marginal_y=None,
     trendline=None,
+    trendline_options=None,
     trendline_color_override=None,
     log_x=False,
     log_y=False,
diff --git a/packages/python/plotly/plotly/express/_core.py b/packages/python/plotly/plotly/express/_core.py
index 6cf453ef430..8567afb909e 100644
--- a/packages/python/plotly/plotly/express/_core.py
+++ b/packages/python/plotly/plotly/express/_core.py
@@ -239,6 +239,56 @@ def make_mapping(args, variable):
     )
 
 
+def lowess(options, x, y, x_label, y_label, non_missing):
+    import statsmodels.api as sm
+
+    frac = options.get("frac", 0.6666666)
+    # missing ='drop' is the default value for lowess but not for OLS (None)
+    # we force it here in case statsmodels change their defaults
+    y_out = sm.nonparametric.lowess(y, x, missing="drop", frac=frac)[:, 1]
+    hover_header = "<b>LOWESS trendline</b><br><br>"
+    return y_out, hover_header, None
+
+
+def ma(options, x, y, x_label, y_label, non_missing):
+    y_out = pd.Series(y, index=x).rolling(**options).mean()[non_missing]
+    hover_header = "<b>Moving Average trendline</b><br><br>"
+    return y_out, hover_header, None
+
+
+def ewm(options, x, y, x_label, y_label, non_missing):
+    y_out = pd.Series(y, index=x).ewm(**options).mean()[non_missing]
+    hover_header = "<b>EWM trendline</b><br><br>"
+    return y_out, hover_header, None
+
+
+def ols(options, x, y, x_label, y_label, non_missing):
+    import statsmodels.api as sm
+
+    add_constant = options.get("add_constant", True)
+    fit_results = sm.OLS(
+        y, sm.add_constant(x) if add_constant else x, missing="drop"
+    ).fit()
+    y_out = fit_results.predict()
+    hover_header = "<b>OLS trendline</b><br>"
+    if len(fit_results.params) == 2:
+        hover_header += "%s = %g * %s + %g<br>" % (
+            y_label,
+            fit_results.params[1],
+            x_label,
+            fit_results.params[0],
+        )
+    elif not add_constant:
+        hover_header += "%s = %g* %s<br>" % (y_label, fit_results.params[0], x_label,)
+    else:
+        hover_header += "%s = %g<br>" % (y_label, fit_results.params[0],)
+    hover_header += "R<sup>2</sup>=%f<br><br>" % fit_results.rsquared
+    return y_out, hover_header, fit_results
+
+
+trendline_functions = dict(lowess=lowess, ma=ma, ewm=ewm, ols=ols)
+
+
 def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
     """Populates a dict with arguments to update trace
 
@@ -313,12 +363,11 @@ def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
                     mapping_labels["count"] = "%{x}"
             elif attr_name == "trendline":
                 if (
-                    attr_value[0] in ["ols", "lowess", "ma", "ewm"]
+                    attr_value in trendline_functions
                     and args["x"]
                     and args["y"]
                     and len(trace_data[[args["x"], args["y"]]].dropna()) > 1
                 ):
-                    import statsmodels.api as sm
 
                     # sorting is bad but trace_specs with "trendline" have no other attrs
                     sorted_trace_data = trace_data.sort_values(by=args["x"])
@@ -349,56 +398,19 @@ def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
                         np.logical_or(np.isnan(y), np.isnan(x))
                     )
                     trace_patch["x"] = sorted_trace_data[args["x"]][non_missing]
-
-                    if attr_value[0] == "lowess":
-                        alpha = attr_value[1] or 0.6666666
-                        # 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", frac=alpha
-                        )
-                        trace_patch["y"] = trendline[:, 1]
-                        hover_header = "<b>LOWESS trendline</b><br><br>"
-                    elif attr_value[0] == "ma":
-                        trace_patch["y"] = (
-                            pd.Series(y[non_missing])
-                            .rolling(window=attr_value[1] or 3)
-                            .mean()
-                        )
-                    elif attr_value[0] == "ewm":
-                        trace_patch["y"] = (
-                            pd.Series(y[non_missing])
-                            .ewm(alpha=attr_value[1] or 0.5)
-                            .mean()
-                        )
-                    elif attr_value[0] == "ols":
-                        add_constant = attr_value[1] is not False
-                        fit_results = sm.OLS(
-                            y, sm.add_constant(x) if add_constant else x, missing="drop"
-                        ).fit()
-                        trace_patch["y"] = fit_results.predict()
-                        hover_header = "<b>OLS trendline</b><br>"
-                        if len(fit_results.params) == 2:
-                            hover_header += "%s = %g * %s + %g<br>" % (
-                                args["y"],
-                                fit_results.params[1],
-                                args["x"],
-                                fit_results.params[0],
-                            )
-                        elif not add_constant:
-                            hover_header += "%s = %g* %s<br>" % (
-                                args["y"],
-                                fit_results.params[0],
-                                args["x"],
-                            )
-                        else:
-                            hover_header += "%s = %g<br>" % (
-                                args["y"],
-                                fit_results.params[0],
-                            )
-                        hover_header += (
-                            "R<sup>2</sup>=%f<br><br>" % fit_results.rsquared
-                        )
+                    trendline_function = trendline_functions[attr_value]
+                    y_out, hover_header, fit_results = trendline_function(
+                        args["trendline_options"],
+                        x,
+                        y,
+                        args["x"],
+                        args["y"],
+                        non_missing,
+                    )
+                    assert len(y_out) == len(
+                        trace_patch["x"]
+                    ), "missing-data-handling failure in trendline code"
+                    trace_patch["y"] = y_out
                     mapping_labels[get_label(args, args["x"])] = "%{x}"
                     mapping_labels[get_label(args, args["y"])] = "%{y} <b>(trend)</b>"
             elif attr_name.startswith("error"):
@@ -1850,9 +1862,8 @@ def infer_config(args, constructor, trace_patch, layout_patch):
     ):
         args["facet_col_wrap"] = 0
 
-    if args.get("trendline", None) is not None:
-        if isinstance(args["trendline"], str):
-            args["trendline"] = (args["trendline"], None)
+    if "trendline_options" in args and args["trendline_options"] is None:
+        args["trendline_options"] = dict()
 
     # Compute applicable grouping attributes
     for k in group_attrables:
diff --git a/packages/python/plotly/plotly/express/_doc.py b/packages/python/plotly/plotly/express/_doc.py
index f2f2ab0544d..1a218a9edbb 100644
--- a/packages/python/plotly/plotly/express/_doc.py
+++ b/packages/python/plotly/plotly/express/_doc.py
@@ -406,6 +406,10 @@
         "If `'ols'`, an Ordinary Least Squares regression line will be drawn for each discrete-color/symbol group.",
         "If `'lowess`', a Locally Weighted Scatterplot Smoothing line will be drawn for each discrete-color/symbol group.",
     ],
+    trendline_options=[
+        "dict",
+        "Options passed to the function named in the `trendline` argument.",
+    ],
     trendline_color_override=[
         "str",
         "Valid CSS color.",

From 560fad72594a101f0b9bc3e07ea21895aa541853 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Fri, 25 Dec 2020 10:43:28 -0500
Subject: [PATCH 03/24] ols log options checkpoint

---
 packages/python/plotly/plotly/express/_core.py | 15 ++++++++++++---
 1 file changed, 12 insertions(+), 3 deletions(-)

diff --git a/packages/python/plotly/plotly/express/_core.py b/packages/python/plotly/plotly/express/_core.py
index 8567afb909e..d46c0354d4b 100644
--- a/packages/python/plotly/plotly/express/_core.py
+++ b/packages/python/plotly/plotly/express/_core.py
@@ -266,10 +266,19 @@ def ols(options, x, y, x_label, y_label, non_missing):
     import statsmodels.api as sm
 
     add_constant = options.get("add_constant", True)
-    fit_results = sm.OLS(
-        y, sm.add_constant(x) if add_constant else x, missing="drop"
-    ).fit()
+    log_x = options.get("log_x", False)
+    log_y = options.get("log_y", False)
+
+    if log_y:
+        y = np.log(y)
+    if log_x:
+        x = np.log(x)
+    if add_constant:
+        x = sm.add_constant(x)
+    fit_results = sm.OLS(y, x, missing="drop").fit()
     y_out = fit_results.predict()
+    if log_y:
+        y_out = np.exp(y_out)
     hover_header = "<b>OLS trendline</b><br>"
     if len(fit_results.params) == 2:
         hover_header += "%s = %g * %s + %g<br>" % (

From 50572d51a176a4cde2dd591654e748cab3e7f5ad Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Tue, 29 Dec 2020 13:30:32 -0500
Subject: [PATCH 04/24] move trendline code to own module

---
 doc/apidoc/plotly.express.rst                 |  1 +
 .../python/plotly/plotly/express/__init__.py  |  2 +-
 .../python/plotly/plotly/express/_core.py     | 61 +------------------
 .../plotly/express/trendline_functions.py     | 58 ++++++++++++++++++
 4 files changed, 62 insertions(+), 60 deletions(-)
 create mode 100644 packages/python/plotly/plotly/express/trendline_functions.py

diff --git a/doc/apidoc/plotly.express.rst b/doc/apidoc/plotly.express.rst
index cd252158cb4..36550a0a0fb 100644
--- a/doc/apidoc/plotly.express.rst
+++ b/doc/apidoc/plotly.express.rst
@@ -60,3 +60,4 @@ plotly's high-level API for rapid figure generation. ::
 
    generated/plotly.express.data.rst
    generated/plotly.express.colors.rst
+   generated/plotly.express.trendline_functions.rst
diff --git a/packages/python/plotly/plotly/express/__init__.py b/packages/python/plotly/plotly/express/__init__.py
index 140a0fbe814..f0c2d4e154c 100644
--- a/packages/python/plotly/plotly/express/__init__.py
+++ b/packages/python/plotly/plotly/express/__init__.py
@@ -60,7 +60,7 @@
 
 from ._special_inputs import IdentityMap, Constant, Range  # noqa: F401
 
-from . import data, colors  # noqa: F401
+from . import data, colors, trendline_functions  # noqa: F401
 
 __all__ = [
     "scatter",
diff --git a/packages/python/plotly/plotly/express/_core.py b/packages/python/plotly/plotly/express/_core.py
index d46c0354d4b..d0b00b5437d 100644
--- a/packages/python/plotly/plotly/express/_core.py
+++ b/packages/python/plotly/plotly/express/_core.py
@@ -2,6 +2,7 @@
 import plotly.io as pio
 from collections import namedtuple, OrderedDict
 from ._special_inputs import IdentityMap, Constant, Range
+from .trendline_functions import ols, lowess, ma, ewm
 
 from _plotly_utils.basevalidators import ColorscaleValidator
 from plotly.colors import qualitative, sequential
@@ -239,65 +240,6 @@ def make_mapping(args, variable):
     )
 
 
-def lowess(options, x, y, x_label, y_label, non_missing):
-    import statsmodels.api as sm
-
-    frac = options.get("frac", 0.6666666)
-    # missing ='drop' is the default value for lowess but not for OLS (None)
-    # we force it here in case statsmodels change their defaults
-    y_out = sm.nonparametric.lowess(y, x, missing="drop", frac=frac)[:, 1]
-    hover_header = "<b>LOWESS trendline</b><br><br>"
-    return y_out, hover_header, None
-
-
-def ma(options, x, y, x_label, y_label, non_missing):
-    y_out = pd.Series(y, index=x).rolling(**options).mean()[non_missing]
-    hover_header = "<b>Moving Average trendline</b><br><br>"
-    return y_out, hover_header, None
-
-
-def ewm(options, x, y, x_label, y_label, non_missing):
-    y_out = pd.Series(y, index=x).ewm(**options).mean()[non_missing]
-    hover_header = "<b>EWM trendline</b><br><br>"
-    return y_out, hover_header, None
-
-
-def ols(options, x, y, x_label, y_label, non_missing):
-    import statsmodels.api as sm
-
-    add_constant = options.get("add_constant", True)
-    log_x = options.get("log_x", False)
-    log_y = options.get("log_y", False)
-
-    if log_y:
-        y = np.log(y)
-    if log_x:
-        x = np.log(x)
-    if add_constant:
-        x = sm.add_constant(x)
-    fit_results = sm.OLS(y, x, missing="drop").fit()
-    y_out = fit_results.predict()
-    if log_y:
-        y_out = np.exp(y_out)
-    hover_header = "<b>OLS trendline</b><br>"
-    if len(fit_results.params) == 2:
-        hover_header += "%s = %g * %s + %g<br>" % (
-            y_label,
-            fit_results.params[1],
-            x_label,
-            fit_results.params[0],
-        )
-    elif not add_constant:
-        hover_header += "%s = %g* %s<br>" % (y_label, fit_results.params[0], x_label,)
-    else:
-        hover_header += "%s = %g<br>" % (y_label, fit_results.params[0],)
-    hover_header += "R<sup>2</sup>=%f<br><br>" % fit_results.rsquared
-    return y_out, hover_header, fit_results
-
-
-trendline_functions = dict(lowess=lowess, ma=ma, ewm=ewm, ols=ols)
-
-
 def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
     """Populates a dict with arguments to update trace
 
@@ -371,6 +313,7 @@ def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
                 if trace_spec.constructor == go.Histogram:
                     mapping_labels["count"] = "%{x}"
             elif attr_name == "trendline":
+                trendline_functions = dict(lowess=lowess, ma=ma, ewm=ewm, ols=ols)
                 if (
                     attr_value in trendline_functions
                     and args["x"]
diff --git a/packages/python/plotly/plotly/express/trendline_functions.py b/packages/python/plotly/plotly/express/trendline_functions.py
new file mode 100644
index 00000000000..611067ce8a8
--- /dev/null
+++ b/packages/python/plotly/plotly/express/trendline_functions.py
@@ -0,0 +1,58 @@
+import pandas as pd
+import numpy as np
+
+
+def ols(options, x, y, x_label, y_label, non_missing):
+    import statsmodels.api as sm
+
+    add_constant = options.get("add_constant", True)
+    log_x = options.get("log_x", False)
+    log_y = options.get("log_y", False)
+
+    if log_y:
+        y = np.log(y)
+        y_label = "log(%s)" % y_label
+    if log_x:
+        x = np.log(x)
+        x_label = "log(%s)" % x_label
+    if add_constant:
+        x = sm.add_constant(x)
+    fit_results = sm.OLS(y, x, missing="drop").fit()
+    y_out = fit_results.predict()
+    if log_y:
+        y_out = np.exp(y_out)
+    hover_header = "<b>OLS trendline</b><br>"
+    if len(fit_results.params) == 2:
+        hover_header += "%s = %g * %s + %g<br>" % (
+            y_label,
+            fit_results.params[1],
+            x_label,
+            fit_results.params[0],
+        )
+    elif not add_constant:
+        hover_header += "%s = %g* %s<br>" % (y_label, fit_results.params[0], x_label,)
+    else:
+        hover_header += "%s = %g<br>" % (y_label, fit_results.params[0],)
+    hover_header += "R<sup>2</sup>=%f<br><br>" % fit_results.rsquared
+    return y_out, hover_header, fit_results
+
+
+def lowess(options, x, y, x_label, y_label, non_missing):
+    import statsmodels.api as sm
+
+    frac = options.get("frac", 0.6666666)
+    y_out = sm.nonparametric.lowess(y, x, missing="drop", frac=frac)[:, 1]
+    hover_header = "<b>LOWESS trendline</b><br><br>"
+    return y_out, hover_header, None
+
+
+def ma(options, x, y, x_label, y_label, non_missing):
+    y_out = pd.Series(y, index=x).rolling(**options).mean()[non_missing]
+    hover_header = "<b>Moving Average trendline</b><br><br>"
+    return y_out, hover_header, None
+
+
+def ewm(options, x, y, x_label, y_label, non_missing):
+    y_out = pd.Series(y, index=x).ewm(**options).mean()[non_missing]
+    hover_header = "<b>EWM trendline</b><br><br>"
+    return y_out, hover_header, None

From d1001c6d1d3a2a41cf9fbe3c80cc2559b0d3f730 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Tue, 29 Dec 2020 19:35:09 -0500
Subject: [PATCH 05/24] get trendline_functions into apidoc

---
 packages/python/plotly/plotly/express/__init__.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/packages/python/plotly/plotly/express/__init__.py b/packages/python/plotly/plotly/express/__init__.py
index f0c2d4e154c..8bc5da53910 100644
--- a/packages/python/plotly/plotly/express/__init__.py
+++ b/packages/python/plotly/plotly/express/__init__.py
@@ -100,6 +100,7 @@
     "imshow",
     "data",
     "colors",
+    "trendline_functions",
     "set_mapbox_access_token",
     "get_trendline_results",
     "IdentityMap",

From 2d3e8b0b9aec836b9c45b2adbfebaeea97933a54 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Tue, 29 Dec 2020 21:20:10 -0500
Subject: [PATCH 06/24] tests for new trendlines

---
 .../python/plotly/plotly/express/_core.py     |   5 +-
 .../plotly/express/trendline_functions.py     |  18 +--
 .../test_optional/test_px/test_trendline.py   | 142 ++++++++++++++----
 3 files changed, 127 insertions(+), 38 deletions(-)

diff --git a/packages/python/plotly/plotly/express/_core.py b/packages/python/plotly/plotly/express/_core.py
index d0b00b5437d..fd395d739ee 100644
--- a/packages/python/plotly/plotly/express/_core.py
+++ b/packages/python/plotly/plotly/express/_core.py
@@ -2,7 +2,7 @@
 import plotly.io as pio
 from collections import namedtuple, OrderedDict
 from ._special_inputs import IdentityMap, Constant, Range
-from .trendline_functions import ols, lowess, ma, ewm
+from .trendline_functions import ols, lowess, ma, ewma
 
 from _plotly_utils.basevalidators import ColorscaleValidator
 from plotly.colors import qualitative, sequential
@@ -313,7 +313,7 @@ def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
                 if trace_spec.constructor == go.Histogram:
                     mapping_labels["count"] = "%{x}"
             elif attr_name == "trendline":
-                trendline_functions = dict(lowess=lowess, ma=ma, ewm=ewm, ols=ols)
+                trendline_functions = dict(lowess=lowess, ma=ma, ewma=ewma, ols=ols)
                 if (
                     attr_value in trendline_functions
                     and args["x"]
@@ -353,6 +353,7 @@ def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
                     trendline_function = trendline_functions[attr_value]
                     y_out, hover_header, fit_results = trendline_function(
                         args["trendline_options"],
+                        sorted_trace_data[args["x"]],
                         x,
                         y,
                         args["x"],
diff --git a/packages/python/plotly/plotly/express/trendline_functions.py b/packages/python/plotly/plotly/express/trendline_functions.py
index 611067ce8a8..78d447353d6 100644
--- a/packages/python/plotly/plotly/express/trendline_functions.py
+++ b/packages/python/plotly/plotly/express/trendline_functions.py
@@ -2,7 +2,7 @@
 import numpy as np
 
 
-def ols(options, x, y, x_label, y_label, non_missing):
+def ols(options, x_raw, x, y, x_label, y_label, non_missing):
     import statsmodels.api as sm
 
     add_constant = options.get("add_constant", True)
@@ -30,14 +30,14 @@ def ols(options, x, y, x_label, y_label, non_missing):
             fit_results.params[0],
         )
     elif not add_constant:
-        hover_header += "%s = %g* %s<br>" % (y_label, fit_results.params[0], x_label,)
+        hover_header += "%s = %g * %s<br>" % (y_label, fit_results.params[0], x_label,)
     else:
         hover_header += "%s = %g<br>" % (y_label, fit_results.params[0],)
     hover_header += "R<sup>2</sup>=%f<br><br>" % fit_results.rsquared
     return y_out, hover_header, fit_results
 
 
-def lowess(options, x, y, x_label, y_label, non_missing):
+def lowess(options, x_raw, x, y, x_label, y_label, non_missing):
     import statsmodels.api as sm
 
     frac = options.get("frac", 0.6666666)
@@ -46,13 +46,13 @@ def lowess(options, x, y, x_label, y_label, non_missing):
     return y_out, hover_header, None
 
 
-def ma(options, x, y, x_label, y_label, non_missing):
-    y_out = pd.Series(y, index=x).rolling(**options).mean()[non_missing]
-    hover_header = "<b>Moving Average trendline</b><br><br>"
+def ma(options, x_raw, x, y, x_label, y_label, non_missing):
+    y_out = pd.Series(y, index=x_raw).rolling(**options).mean()[non_missing]
+    hover_header = "<b>MA trendline</b><br><br>"
     return y_out, hover_header, None
 
 
-def ewm(options, x, y, x_label, y_label, non_missing):
-    y_out = pd.Series(y, index=x).ewm(**options).mean()[non_missing]
-    hover_header = "<b>EWM trendline</b><br><br>"
+def ewma(options, x_raw, x, y, x_label, y_label, non_missing):
+    y_out = pd.Series(y, index=x_raw).ewm(**options).mean()[non_missing]
+    hover_header = "<b>EWMA trendline</b><br><br>"
     return y_out, hover_header, None
diff --git a/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py b/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
index 41064bd19df..19d4db4efdf 100644
--- a/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
+++ b/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
@@ -5,10 +5,27 @@
 from datetime import datetime
 
 
-@pytest.mark.parametrize("mode", ["ols", "lowess"])
-def test_trendline_results_passthrough(mode):
+@pytest.mark.parametrize(
+    "mode,options",
+    [
+        ("ols", None),
+        ("ols", dict(log_x=True, log_y=True)),
+        ("lowess", None),
+        ("lowess", dict(frac=0.3)),
+        ("ma", dict(window=2)),
+        ("ewma", dict(alpha=0.5)),
+    ],
+)
+def test_trendline_results_passthrough(mode, options):
     df = px.data.gapminder().query("continent == 'Oceania'")
-    fig = px.scatter(df, x="year", y="pop", color="country", trendline=mode)
+    fig = px.scatter(
+        df,
+        x="year",
+        y="pop",
+        color="country",
+        trendline=mode,
+        trendline_options=options,
+    )
     assert len(fig.data) == 4
     for trace in fig["data"][0::2]:
         assert "trendline" not in trace.hovertemplate
@@ -20,90 +37,161 @@ def test_trendline_results_passthrough(mode):
     if mode == "ols":
         assert len(results) == 2
         assert results["country"].values[0] == "Australia"
-        assert results["country"].values[0] == "Australia"
         au_result = results["px_fit_results"].values[0]
         assert len(au_result.params) == 2
     else:
         assert len(results) == 0
 
 
-@pytest.mark.parametrize("mode", ["ols", "lowess"])
-def test_trendline_enough_values(mode):
-    fig = px.scatter(x=[0, 1], y=[0, 1], trendline=mode)
+@pytest.mark.parametrize(
+    "mode,options",
+    [
+        ("ols", None),
+        ("ols", dict(add_constant=False, log_x=True, log_y=True)),
+        ("lowess", None),
+        ("lowess", dict(frac=0.3)),
+        ("ma", dict(window=2)),
+        ("ewma", dict(alpha=0.5)),
+    ],
+)
+def test_trendline_enough_values(mode, options):
+    fig = px.scatter(x=[0, 1], y=[0, 1], trendline=mode, trendline_options=options)
     assert len(fig.data) == 2
     assert len(fig.data[1].x) == 2
-    fig = px.scatter(x=[0], y=[0], trendline=mode)
+    fig = px.scatter(x=[0], y=[0], trendline=mode, trendline_options=options)
     assert len(fig.data) == 2
     assert fig.data[1].x is None
-    fig = px.scatter(x=[0, 1], y=[0, None], trendline=mode)
+    fig = px.scatter(x=[0, 1], y=[0, None], trendline=mode, trendline_options=options)
     assert len(fig.data) == 2
     assert fig.data[1].x is None
-    fig = px.scatter(x=[0, 1], y=np.array([0, np.nan]), trendline=mode)
+    fig = px.scatter(
+        x=[0, 1], y=np.array([0, np.nan]), trendline=mode, trendline_options=options
+    )
     assert len(fig.data) == 2
     assert fig.data[1].x is None
-    fig = px.scatter(x=[0, 1, None], y=[0, None, 1], trendline=mode)
+    fig = px.scatter(
+        x=[0, 1, None], y=[0, None, 1], trendline=mode, trendline_options=options
+    )
     assert len(fig.data) == 2
     assert fig.data[1].x is None
     fig = px.scatter(
-        x=np.array([0, 1, np.nan]), y=np.array([0, np.nan, 1]), trendline=mode
+        x=np.array([0, 1, np.nan]),
+        y=np.array([0, np.nan, 1]),
+        trendline=mode,
+        trendline_options=options,
     )
     assert len(fig.data) == 2
     assert fig.data[1].x is None
-    fig = px.scatter(x=[0, 1, None, 2], y=[1, None, 1, 2], trendline=mode)
+    fig = px.scatter(
+        x=[0, 1, None, 2], y=[1, None, 1, 2], trendline=mode, trendline_options=options
+    )
     assert len(fig.data) == 2
     assert len(fig.data[1].x) == 2
     fig = px.scatter(
-        x=np.array([0, 1, np.nan, 2]), y=np.array([1, np.nan, 1, 2]), trendline=mode
+        x=np.array([0, 1, np.nan, 2]),
+        y=np.array([1, np.nan, 1, 2]),
+        trendline=mode,
+        trendline_options=options,
     )
     assert len(fig.data) == 2
     assert len(fig.data[1].x) == 2
 
 
-@pytest.mark.parametrize("mode", ["ols", "lowess"])
-def test_trendline_nan_values(mode):
+@pytest.mark.parametrize(
+    "mode,options",
+    [
+        ("ols", None),
+        ("ols", dict(add_constant=False, log_x=True, log_y=True)),
+        ("lowess", None),
+        ("lowess", dict(frac=0.3)),
+        ("ma", dict(window=2)),
+        ("ewma", dict(alpha=0.5)),
+    ],
+)
+def test_trendline_nan_values(mode, options):
     df = px.data.gapminder().query("continent == 'Oceania'")
     start_date = 1970
     df["pop"][df["year"] < start_date] = np.nan
-    fig = px.scatter(df, x="year", y="pop", color="country", trendline=mode)
+    fig = px.scatter(
+        df,
+        x="year",
+        y="pop",
+        color="country",
+        trendline=mode,
+        trendline_options=options,
+    )
     for trendline in fig["data"][1::2]:
         assert trendline.x[0] >= start_date
         assert len(trendline.x) == len(trendline.y)
 
 
-def test_no_slope_ols_trendline():
+def test_ols_trendline_slopes():
     fig = px.scatter(x=[0, 1], y=[0, 1], trendline="ols")
-    assert "y = 1" in fig.data[1].hovertemplate  # then + x*(some small number)
+    assert "y = 1 * x + 0<br>" in fig.data[1].hovertemplate
     results = px.get_trendline_results(fig)
     params = results["px_fit_results"].iloc[0].params
     assert np.all(np.isclose(params, [0, 1]))
 
+    fig = px.scatter(x=[0, 1], y=[1, 2], trendline="ols")
+    assert "y = 1 * x + 1<br>" in fig.data[1].hovertemplate
+    results = px.get_trendline_results(fig)
+    params = results["px_fit_results"].iloc[0].params
+    assert np.all(np.isclose(params, [1, 1]))
+
+    fig = px.scatter(
+        x=[0, 1], y=[1, 2], trendline="ols", trendline_options=dict(add_constant=False)
+    )
+    assert "y = 2 * x<br>" in fig.data[1].hovertemplate
+    results = px.get_trendline_results(fig)
+    params = results["px_fit_results"].iloc[0].params
+    assert np.all(np.isclose(params, [2]))
+
+    fig = px.scatter(
+        x=[1, 1], y=[0, 0], trendline="ols", trendline_options=dict(add_constant=False)
+    )
+    assert "y = 0 * x<br>" in fig.data[1].hovertemplate
+    results = px.get_trendline_results(fig)
+    params = results["px_fit_results"].iloc[0].params
+    assert np.all(np.isclose(params, [0]))
+
     fig = px.scatter(x=[1, 1], y=[0, 0], trendline="ols")
-    assert "y = 0" in fig.data[1].hovertemplate
+    assert "y = 0<br>" in fig.data[1].hovertemplate
     results = px.get_trendline_results(fig)
     params = results["px_fit_results"].iloc[0].params
     assert np.all(np.isclose(params, [0]))
 
     fig = px.scatter(x=[1, 2], y=[0, 0], trendline="ols")
-    assert "y = 0" in fig.data[1].hovertemplate
+    assert "y = 0 * x + 0<br>" in fig.data[1].hovertemplate
     fig = px.scatter(x=[0, 0], y=[1, 1], trendline="ols")
-    assert "y = 0 * x + 1" in fig.data[1].hovertemplate
+    assert "y = 0 * x + 1<br>" in fig.data[1].hovertemplate
     fig = px.scatter(x=[0, 0], y=[1, 2], trendline="ols")
-    assert "y = 0 * x + 1.5" in fig.data[1].hovertemplate
+    assert "y = 0 * x + 1.5<br>" in fig.data[1].hovertemplate
 
 
-@pytest.mark.parametrize("mode", ["ols", "lowess"])
-def test_trendline_on_timeseries(mode):
+@pytest.mark.parametrize(
+    "mode,options",
+    [
+        ("ols", None),
+        ("ols", dict(add_constant=False, log_x=True, log_y=True)),
+        ("lowess", None),
+        ("lowess", dict(frac=0.3)),
+        ("ma", dict(window=2)),
+        ("ma", dict(window="10d")),
+        ("ewma", dict(alpha=0.5)),
+    ],
+)
+def test_trendline_on_timeseries(mode, options):
     df = px.data.stocks()
 
     with pytest.raises(ValueError) as err_msg:
-        px.scatter(df, x="date", y="GOOG", trendline=mode)
+        px.scatter(df, x="date", y="GOOG", trendline=mode, trendline_options=options)
     assert "Could not convert value of 'x' ('date') into a numeric type." in str(
         err_msg.value
     )
 
     df["date"] = pd.to_datetime(df["date"])
     df["date"] = df["date"].dt.tz_localize("CET")  # force a timezone
-    fig = px.scatter(df, x="date", y="GOOG", trendline=mode)
+    fig = px.scatter(df, x="date", y="GOOG", trendline=mode, trendline_options=options)
     assert len(fig.data) == 2
     assert len(fig.data[0].x) == len(fig.data[1].x)
     assert type(fig.data[0].x[0]) == datetime

From 81a76c7a6859804c832773e86f65bb13c7cb4861 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Tue, 29 Dec 2020 22:00:20 -0500
Subject: [PATCH 07/24] apidoc and tests

---
 .../__init__.py}                                              | 0
 .../plotly/tests/test_optional/test_px/test_trendline.py      | 4 ----
 2 files changed, 4 deletions(-)
 rename packages/python/plotly/plotly/express/{trendline_functions.py => trendline_functions/__init__.py} (100%)

diff --git a/packages/python/plotly/plotly/express/trendline_functions.py b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
similarity index 100%
rename from packages/python/plotly/plotly/express/trendline_functions.py
rename to packages/python/plotly/plotly/express/trendline_functions/__init__.py
diff --git a/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py b/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
index 19d4db4efdf..661f46bba2a 100644
--- a/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
+++ b/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
@@ -9,7 +9,6 @@
     "mode,options",
     [
         ("ols", None),
-        ("ols", dict(log_x=True, log_y=True)),
         ("lowess", None),
         ("lowess", dict(frac=0.3)),
         ("ma", dict(window=2)),
@@ -47,7 +46,6 @@ def test_trendline_results_passthrough(mode, options):
     "mode,options",
     [
         ("ols", None),
-        ("ols", dict(add_constant=False, log_x=True, log_y=True)),
         ("lowess", None),
         ("lowess", dict(frac=0.3)),
         ("ma", dict(window=2)),
@@ -101,7 +99,6 @@ def test_trendline_enough_values(mode, options):
     "mode,options",
     [
         ("ols", None),
-        ("ols", dict(add_constant=False, log_x=True, log_y=True)),
         ("lowess", None),
         ("lowess", dict(frac=0.3)),
         ("ma", dict(window=2)),
@@ -172,7 +169,6 @@ def test_ols_trendline_slopes():
     "mode,options",
     [
         ("ols", None),
-        ("ols", dict(add_constant=False, log_x=True, log_y=True)),
         ("lowess", None),
         ("lowess", dict(frac=0.3)),
         ("ma", dict(window=2)),

From 16a9c63d3baf30019a23ea50b2e382d5e0dd12ee Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Wed, 30 Dec 2020 20:36:06 -0500
Subject: [PATCH 08/24] fix up tests

---
 packages/python/plotly/plotly/express/_core.py       | 12 +++++++++---
 .../plotly/express/trendline_functions/__init__.py   |  8 ++++++++
 .../tests/test_optional/test_px/test_trendline.py    |  4 +++-
 3 files changed, 20 insertions(+), 4 deletions(-)

diff --git a/packages/python/plotly/plotly/express/_core.py b/packages/python/plotly/plotly/express/_core.py
index fd395d739ee..bd5befafb58 100644
--- a/packages/python/plotly/plotly/express/_core.py
+++ b/packages/python/plotly/plotly/express/_core.py
@@ -17,6 +17,7 @@
 )
 
 NO_COLOR = "px_no_color_constant"
+trendline_functions = dict(lowess=lowess, ma=ma, ewma=ewma, ols=ols)
 
 # Declare all supported attributes, across all plot types
 direct_attrables = (
@@ -313,10 +314,8 @@ def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
                 if trace_spec.constructor == go.Histogram:
                     mapping_labels["count"] = "%{x}"
             elif attr_name == "trendline":
-                trendline_functions = dict(lowess=lowess, ma=ma, ewma=ewma, ols=ols)
                 if (
-                    attr_value in trendline_functions
-                    and args["x"]
+                    args["x"]
                     and args["y"]
                     and len(trace_data[[args["x"], args["y"]]].dropna()) > 1
                 ):
@@ -1815,6 +1814,13 @@ def infer_config(args, constructor, trace_patch, layout_patch):
     ):
         args["facet_col_wrap"] = 0
 
+    if "trendline" in args and args["trendline"] is not None:
+        if args["trendline"] not in trendline_functions:
+            raise ValueError(
+                "Value '%s' for `trendline` must be one of %s"
+                % (args["trendline"], trendline_functions.keys())
+            )
+
     if "trendline_options" in args and args["trendline_options"] is None:
         args["trendline_options"] = dict()
 
diff --git a/packages/python/plotly/plotly/express/trendline_functions/__init__.py b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
index 78d447353d6..79bb2de125f 100644
--- a/packages/python/plotly/plotly/express/trendline_functions/__init__.py
+++ b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
@@ -10,9 +10,17 @@ def ols(options, x_raw, x, y, x_label, y_label, non_missing):
     log_y = options.get("log_y", False)
 
     if log_y:
+        if np.any(y == 0):
+            raise ValueError(
+                "Can't do OLS trendline with `log_y=True` when `y` contains zeros."
+            )
         y = np.log(y)
         y_label = "log(%s)" % y_label
     if log_x:
+        if np.any(x == 0):
+            raise ValueError(
+                "Can't do OLS trendline with `log_x=True` when `x` contains zeros."
+            )
         x = np.log(x)
         x_label = "log(%s)" % x_label
     if add_constant:
diff --git a/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py b/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
index 661f46bba2a..848e8f68003 100644
--- a/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
+++ b/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
@@ -99,6 +99,7 @@ def test_trendline_enough_values(mode, options):
     "mode,options",
     [
         ("ols", None),
+        ("ols", dict(add_constant=False, log_x=True, log_y=True)),
         ("lowess", None),
         ("lowess", dict(frac=0.3)),
         ("ma", dict(window=2)),
@@ -124,7 +125,8 @@ def test_trendline_nan_values(mode, options):
 
 def test_ols_trendline_slopes():
     fig = px.scatter(x=[0, 1], y=[0, 1], trendline="ols")
-    assert "y = 1 * x + 0<br>" in fig.data[1].hovertemplate
+    # should be "y = 1 * x + 0" but sometimes is some tiny number instead
+    assert "y = 1 * x + " in fig.data[1].hovertemplate
     results = px.get_trendline_results(fig)
     params = results["px_fit_results"].iloc[0].params
     assert np.all(np.isclose(params, [0, 1]))

From c413a31796c48f145aced35ce11ea1d9db9a2210 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Thu, 31 Dec 2020 21:35:14 -0500
Subject: [PATCH 09/24] docstrings

---
 packages/python/plotly/plotly/express/_doc.py | 11 +++-
 .../express/trendline_functions/__init__.py   | 60 ++++++++++++++-----
 2 files changed, 53 insertions(+), 18 deletions(-)

diff --git a/packages/python/plotly/plotly/express/_doc.py b/packages/python/plotly/plotly/express/_doc.py
index 1a218a9edbb..ded3b039d55 100644
--- a/packages/python/plotly/plotly/express/_doc.py
+++ b/packages/python/plotly/plotly/express/_doc.py
@@ -402,18 +402,23 @@
     ],
     trendline=[
         "str",
-        "One of `'ols'` or `'lowess'`.",
+        "One of `'ols'`, `'lowess'`, `'ma'` or `'ewma'`.",
         "If `'ols'`, an Ordinary Least Squares regression line will be drawn for each discrete-color/symbol group.",
         "If `'lowess`', a Locally Weighted Scatterplot Smoothing line will be drawn for each discrete-color/symbol group.",
+        "If `'ma`', a Moving Average line will be drawn for each discrete-color/symbol group.",
+        "If `'ewma`', an Exponentially Weighted Moving Average line will be drawn for each discrete-color/symbol group.",
+        "See the docstrings for the functions in `plotly.express.trendline_functions` for more details on these functions and how",
+        "to configure them with the `trendline_options` argument.",
     ],
     trendline_options=[
         "dict",
-        "Options passed to the function named in the `trendline` argument.",
+        "Options passed as the first argument to the function from `plotly.express.trendline_functions` ",
+        "named in the `trendline` argument.",
     ],
     trendline_color_override=[
         "str",
         "Valid CSS color.",
-        "If provided, and if `trendline` is set, all trendlines will be drawn in this color.",
+        "If provided, and if `trendline` is set, all trendlines will be drawn in this color rather than in the same color as the traces from which they draw their inputs.",
     ],
     render_mode=[
         "str",
diff --git a/packages/python/plotly/plotly/express/trendline_functions/__init__.py b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
index 79bb2de125f..c36482ec8e7 100644
--- a/packages/python/plotly/plotly/express/trendline_functions/__init__.py
+++ b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
@@ -2,33 +2,47 @@
 import numpy as np
 
 
-def ols(options, x_raw, x, y, x_label, y_label, non_missing):
+def ols(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
+    """Ordinary Least Squares trendline function
+
+    Requires `statsmodels` to be installed.
+
+    Valid keys for the `trendline_options` dict are:
+
+    `add_constant` (`bool`, default `True`): if `False`, the trendline passes through
+    the origin but if `True` a y-intercept is fitted.
+
+    `log_x` and `log_y` (`bool`, default `False`): if `True` the OLS is computed with
+    respect to the base 10 logarithm of the input. Note that this means no zeros can
+    be present in the input.
+    """
+
     import statsmodels.api as sm
 
-    add_constant = options.get("add_constant", True)
-    log_x = options.get("log_x", False)
-    log_y = options.get("log_y", False)
+    add_constant = trendline_options.get("add_constant", True)
+    log_x = trendline_options.get("log_x", False)
+    log_y = trendline_options.get("log_y", False)
 
     if log_y:
         if np.any(y == 0):
             raise ValueError(
                 "Can't do OLS trendline with `log_y=True` when `y` contains zeros."
             )
-        y = np.log(y)
-        y_label = "log(%s)" % y_label
+        y = np.log10(y)
+        y_label = "log10(%s)" % y_label
     if log_x:
         if np.any(x == 0):
             raise ValueError(
                 "Can't do OLS trendline with `log_x=True` when `x` contains zeros."
             )
-        x = np.log(x)
-        x_label = "log(%s)" % x_label
+        x = np.log10(x)
+        x_label = "log10(%s)" % x_label
     if add_constant:
         x = sm.add_constant(x)
     fit_results = sm.OLS(y, x, missing="drop").fit()
     y_out = fit_results.predict()
     if log_y:
-        y_out = np.exp(y_out)
+        y_out = np.power(10, y_out)
     hover_header = "<b>OLS trendline</b><br>"
     if len(fit_results.params) == 2:
         hover_header += "%s = %g * %s + %g<br>" % (
@@ -45,22 +59,38 @@ def ols(options, x_raw, x, y, x_label, y_label, non_missing):
     return y_out, hover_header, fit_results
 
 
-def lowess(options, x_raw, x, y, x_label, y_label, non_missing):
+def lowess(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
+    """Locally Weighted Scatterplot Smoothing trendline function
+
+    Requires `statsmodels` to be installed.
+
+    Valid keys for the `trendline_options` dict are:
+
+    `frac` (`float`, default `0.6666666`): the `frac` parameter from `statsmodels.api.nonparametric.lowess`
+    """
     import statsmodels.api as sm
 
-    frac = options.get("frac", 0.6666666)
+    frac = trendline_options.get("frac", 0.6666666)
     y_out = sm.nonparametric.lowess(y, x, missing="drop", frac=frac)[:, 1]
     hover_header = "<b>LOWESS trendline</b><br><br>"
     return y_out, hover_header, None
 
 
-def ma(options, x_raw, x, y, x_label, y_label, non_missing):
-    y_out = pd.Series(y, index=x_raw).rolling(**options).mean()[non_missing]
+def ma(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
+    """Moving Average trendline function
+
+    The `trendline_options` dict is passed as keyword arguments into the `pandas.Series.rolling` function.
+    """
+    y_out = pd.Series(y, index=x_raw).rolling(**trendline_options).mean()[non_missing]
     hover_header = "<b>MA trendline</b><br><br>"
     return y_out, hover_header, None
 
 
-def ewma(options, x_raw, x, y, x_label, y_label, non_missing):
-    y_out = pd.Series(y, index=x_raw).ewm(**options).mean()[non_missing]
+def ewma(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
+    """Exponentially Weighted Moving Average trendline function
+
+    The `trendline_options` dict is passed as keyword arguments into the `pandas.Series.ewma` function.
+    """
+    y_out = pd.Series(y, index=x_raw).ewm(**trendline_options).mean()[non_missing]
     hover_header = "<b>EWMA trendline</b><br><br>"
     return y_out, hover_header, None

From aad79b441fd405f339224da2ea1e683c77be38f9 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Thu, 31 Dec 2020 21:46:30 -0500
Subject: [PATCH 10/24] docstrings

---
 .../express/trendline_functions/__init__.py   | 29 +++++++++++++------
 1 file changed, 20 insertions(+), 9 deletions(-)

diff --git a/packages/python/plotly/plotly/express/trendline_functions/__init__.py b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
index c36482ec8e7..f5175351cbf 100644
--- a/packages/python/plotly/plotly/express/trendline_functions/__init__.py
+++ b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
@@ -3,16 +3,20 @@
 
 
 def ols(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
-    """Ordinary Least Squares trendline function
+    """Ordinary Least Squares (OLS) trendline function
 
     Requires `statsmodels` to be installed.
 
+    This trendline function causes fit results to be stored within the figure,
+    accessible via the `plotly.express.get_trendline_results` function. The fit results
+    are the output of the `statsmodels.api.OLS` function.
+
     Valid keys for the `trendline_options` dict are:
 
-    `add_constant` (`bool`, default `True`): if `False`, the trendline passes through
+    - `add_constant` (`bool`, default `True`): if `False`, the trendline passes through
     the origin but if `True` a y-intercept is fitted.
 
-    `log_x` and `log_y` (`bool`, default `False`): if `True` the OLS is computed with
+    - `log_x` and `log_y` (`bool`, default `False`): if `True` the OLS is computed with
     respect to the base 10 logarithm of the input. Note that this means no zeros can
     be present in the input.
     """
@@ -60,13 +64,14 @@ def ols(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
 
 
 def lowess(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
-    """Locally Weighted Scatterplot Smoothing trendline function
+    """LOcally WEighted Scatterplot Smoothing (LOWESS) trendline function
 
     Requires `statsmodels` to be installed.
 
     Valid keys for the `trendline_options` dict are:
 
-    `frac` (`float`, default `0.6666666`): the `frac` parameter from `statsmodels.api.nonparametric.lowess`
+    - `frac` (`float`, default `0.6666666`): the `frac` parameter from the
+    `statsmodels.api.nonparametric.lowess` function
     """
     import statsmodels.api as sm
 
@@ -77,9 +82,12 @@ def lowess(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
 
 
 def ma(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
-    """Moving Average trendline function
+    """Moving Average (MA) trendline function
+
+    Requires `pandas` to be installed.
 
-    The `trendline_options` dict is passed as keyword arguments into the `pandas.Series.rolling` function.
+    The `trendline_options` dict is passed as keyword arguments into the
+    `pandas.Series.rolling` function.
     """
     y_out = pd.Series(y, index=x_raw).rolling(**trendline_options).mean()[non_missing]
     hover_header = "<b>MA trendline</b><br><br>"
@@ -87,9 +95,12 @@ def ma(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
 
 
 def ewma(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
-    """Exponentially Weighted Moving Average trendline function
+    """Exponentially Weighted Moving Average (EWMA) trendline function
+
+    Requires `pandas` to be installed.
 
-    The `trendline_options` dict is passed as keyword arguments into the `pandas.Series.ewma` function.
+    The `trendline_options` dict is passed as keyword arguments into the
+    `pandas.Series.ewma` function.
     """
     y_out = pd.Series(y, index=x_raw).ewm(**trendline_options).mean()[non_missing]
     hover_header = "<b>EWMA trendline</b><br><br>"

From ce73f31fa5a38ad0478cb5021059eda4d2f2a977 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Fri, 1 Jan 2021 19:05:53 -0500
Subject: [PATCH 11/24] docstrings

---
 .../plotly/express/trendline_functions/__init__.py     | 10 ++++++++++
 1 file changed, 10 insertions(+)

diff --git a/packages/python/plotly/plotly/express/trendline_functions/__init__.py b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
index f5175351cbf..3872d3f81a3 100644
--- a/packages/python/plotly/plotly/express/trendline_functions/__init__.py
+++ b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
@@ -1,3 +1,13 @@
+"""
+The `trendline_functions` module contains functions which are called by Plotly Express
+when the `trendline` argument is used. Valid values for `trendline` are the names of the
+functions in this module, and the value of the `trendline_options` argument to PX
+functions is passed in as the first argument to these functions when called.
+
+Note that the functions in this module are not meant to be called directly, and are
+exposed as part of the public API for documentation purposes.
+"""
+
 import pandas as pd
 import numpy as np
 

From 1fa9fac50a189b1dba8c7377ae9a59edaa5cb3d9 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Mon, 4 Jan 2021 15:17:14 -0500
Subject: [PATCH 12/24] add PX utility functions to apidoc

---
 doc/apidoc/plotly.express.rst | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/doc/apidoc/plotly.express.rst b/doc/apidoc/plotly.express.rst
index 36550a0a0fb..bff238d6684 100644
--- a/doc/apidoc/plotly.express.rst
+++ b/doc/apidoc/plotly.express.rst
@@ -49,6 +49,8 @@ plotly's high-level API for rapid figure generation. ::
     density_heatmap
     density_mapbox
     imshow
+    set_mapbox_access_token
+    get_trendline_results
 
 
 `plotly.express` subpackages

From d0ab458536412ca45745ca0ce982f901299e07d5 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Sun, 1 Aug 2021 20:39:12 -0400
Subject: [PATCH 13/24] refactor new trendlines

---
 .../python/plotly/plotly/express/_core.py     |  6 +-
 .../express/trendline_functions/__init__.py   | 57 +++++++++++++------
 .../test_optional/test_px/test_trendline.py   | 22 ++++---
 3 files changed, 56 insertions(+), 29 deletions(-)

diff --git a/packages/python/plotly/plotly/express/_core.py b/packages/python/plotly/plotly/express/_core.py
index bd5befafb58..e55949a64bc 100644
--- a/packages/python/plotly/plotly/express/_core.py
+++ b/packages/python/plotly/plotly/express/_core.py
@@ -2,7 +2,7 @@
 import plotly.io as pio
 from collections import namedtuple, OrderedDict
 from ._special_inputs import IdentityMap, Constant, Range
-from .trendline_functions import ols, lowess, ma, ewma
+from .trendline_functions import ols, lowess, rolling, expanding, ewm
 
 from _plotly_utils.basevalidators import ColorscaleValidator
 from plotly.colors import qualitative, sequential
@@ -17,7 +17,9 @@
 )
 
 NO_COLOR = "px_no_color_constant"
-trendline_functions = dict(lowess=lowess, ma=ma, ewma=ewma, ols=ols)
+trendline_functions = dict(
+    lowess=lowess, rolling=rolling, ewm=ewm, expanding=expanding, ols=ols
+)
 
 # Declare all supported attributes, across all plot types
 direct_attrables = (
diff --git a/packages/python/plotly/plotly/express/trendline_functions/__init__.py b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
index 3872d3f81a3..442280178c7 100644
--- a/packages/python/plotly/plotly/express/trendline_functions/__init__.py
+++ b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
@@ -66,9 +66,9 @@ def ols(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
             fit_results.params[0],
         )
     elif not add_constant:
-        hover_header += "%s = %g * %s<br>" % (y_label, fit_results.params[0], x_label,)
+        hover_header += "%s = %g * %s<br>" % (y_label, fit_results.params[0], x_label)
     else:
-        hover_header += "%s = %g<br>" % (y_label, fit_results.params[0],)
+        hover_header += "%s = %g<br>" % (y_label, fit_results.params[0])
     hover_header += "R<sup>2</sup>=%f<br><br>" % fit_results.rsquared
     return y_out, hover_header, fit_results
 
@@ -91,27 +91,48 @@ def lowess(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
     return y_out, hover_header, None
 
 
-def ma(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
-    """Moving Average (MA) trendline function
+def _pandas(mode, trendline_options, x_raw, y, non_missing):
+    modes = dict(rolling="Rolling", ewm="Exponentially Weighted", expanding="Expanding")
+    function_name = trendline_options.pop("function", "mean")
+    function_args = trendline_options.pop("function_args", dict())
+    series = pd.Series(y, index=x_raw)
+    agg = getattr(series, mode)  # e.g. series.rolling
+    agg_obj = agg(**trendline_options)  # e.g. series.rolling(**opts)
+    function = getattr(agg_obj, function_name)  # e.g. series.rolling(**opts).mean
+    y_out = function(**function_args)  # e.g. series.rolling(**opts).mean(**opts)
+    y_out = y_out[non_missing]
+    hover_header = "<b>%s %s trendline</b><br><br>" % (modes[mode], function_name)
+    return y_out, hover_header, None
+
 
-    Requires `pandas` to be installed.
+def rolling(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
+    """Rolling trendline function
 
-    The `trendline_options` dict is passed as keyword arguments into the
-    `pandas.Series.rolling` function.
+    The value of the `function` key of the `trendline_options` dict is the function to
+    use (defaults to `mean`) and the value of the `function_args` key are taken to be
+    its arguments as a dict. The remainder of  the `trendline_options` dict is passed as
+    keyword arguments into the `pandas.Series.rolling` function.
     """
-    y_out = pd.Series(y, index=x_raw).rolling(**trendline_options).mean()[non_missing]
-    hover_header = "<b>MA trendline</b><br><br>"
-    return y_out, hover_header, None
+    return _pandas("rolling", trendline_options, x_raw, y, non_missing)
 
 
-def ewma(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
-    """Exponentially Weighted Moving Average (EWMA) trendline function
+def expanding(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
+    """Expanding trendline function
 
-    Requires `pandas` to be installed.
+    The value of the `function` key of the `trendline_options` dict is the function to
+    use (defaults to `mean`) and the value of the `function_args` key are taken to be
+    its arguments as a dict. The remainder of  the `trendline_options` dict is passed as
+    keyword arguments into the `pandas.Series.expanding` function.
+    """
+    return _pandas("expanding", trendline_options, x_raw, y, non_missing)
 
-    The `trendline_options` dict is passed as keyword arguments into the
-    `pandas.Series.ewma` function.
+
+def ewm(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
+    """Exponentially weighted trendline function
+
+    The value of the `function` key of the `trendline_options` dict is the function to
+    use (defaults to `mean`) and the value of the `function_args` key are taken to be
+    its arguments as a dict. The remainder of  the `trendline_options` dict is passed as
+    keyword arguments into the `pandas.Series.ewm` function.
     """
-    y_out = pd.Series(y, index=x_raw).ewm(**trendline_options).mean()[non_missing]
-    hover_header = "<b>EWMA trendline</b><br><br>"
-    return y_out, hover_header, None
+    return _pandas("ewm", trendline_options, x_raw, y, non_missing)
diff --git a/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py b/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
index 848e8f68003..5f47cad2f6f 100644
--- a/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
+++ b/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
@@ -11,8 +11,9 @@
         ("ols", None),
         ("lowess", None),
         ("lowess", dict(frac=0.3)),
-        ("ma", dict(window=2)),
-        ("ewma", dict(alpha=0.5)),
+        ("rolling", dict(window=2)),
+        ("expanding", None),
+        ("ewm", dict(alpha=0.5)),
     ],
 )
 def test_trendline_results_passthrough(mode, options):
@@ -48,8 +49,9 @@ def test_trendline_results_passthrough(mode, options):
         ("ols", None),
         ("lowess", None),
         ("lowess", dict(frac=0.3)),
-        ("ma", dict(window=2)),
-        ("ewma", dict(alpha=0.5)),
+        ("rolling", dict(window=2)),
+        ("expanding", None),
+        ("ewm", dict(alpha=0.5)),
     ],
 )
 def test_trendline_enough_values(mode, options):
@@ -102,8 +104,9 @@ def test_trendline_enough_values(mode, options):
         ("ols", dict(add_constant=False, log_x=True, log_y=True)),
         ("lowess", None),
         ("lowess", dict(frac=0.3)),
-        ("ma", dict(window=2)),
-        ("ewma", dict(alpha=0.5)),
+        ("rolling", dict(window=2)),
+        ("expanding", None),
+        ("ewm", dict(alpha=0.5)),
     ],
 )
 def test_trendline_nan_values(mode, options):
@@ -173,9 +176,10 @@ def test_ols_trendline_slopes():
         ("ols", None),
         ("lowess", None),
         ("lowess", dict(frac=0.3)),
-        ("ma", dict(window=2)),
-        ("ma", dict(window="10d")),
-        ("ewma", dict(alpha=0.5)),
+        ("rolling", dict(window=2)),
+        ("rolling", dict(window="10d")),
+        ("expanding", None),
+        ("ewm", dict(alpha=0.5)),
     ],
 )
 def test_trendline_on_timeseries(mode, options):

From 619c6938ec25bf441692e0f4c69f072d5eb947ac Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Mon, 2 Aug 2021 21:49:33 -0400
Subject: [PATCH 14/24] clarify

---
 packages/python/plotly/plotly/express/_core.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/packages/python/plotly/plotly/express/_core.py b/packages/python/plotly/plotly/express/_core.py
index e55949a64bc..975ae24e248 100644
--- a/packages/python/plotly/plotly/express/_core.py
+++ b/packages/python/plotly/plotly/express/_core.py
@@ -869,7 +869,9 @@ def make_trace_spec(args, constructor, attrs, trace_patch):
     # Add trendline trace specifications
     if "trendline" in args and args["trendline"]:
         trace_spec = TraceSpec(
-            constructor=go.Scattergl if constructor == go.Scattergl else go.Scatter,
+            constructor=go.Scattergl
+            if constructor == go.Scattergl  # could be contour
+            else go.Scatter,
             attrs=["trendline"],
             trace_patch=dict(mode="lines"),
             marginal=None,

From 744afb98e0ebf83f6e416591348a38bce9696c17 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Mon, 2 Aug 2021 22:57:28 -0400
Subject: [PATCH 15/24] docstring

---
 .../plotly/plotly/express/trendline_functions/__init__.py       | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/packages/python/plotly/plotly/express/trendline_functions/__init__.py b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
index 442280178c7..ace0c15bc61 100644
--- a/packages/python/plotly/plotly/express/trendline_functions/__init__.py
+++ b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
@@ -128,7 +128,7 @@ def expanding(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
 
 
 def ewm(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
-    """Exponentially weighted trendline function
+    """Exponentially Weighted Moment (EWM) trendline function
 
     The value of the `function` key of the `trendline_options` dict is the function to
     use (defaults to `mean`) and the value of the `function_args` key are taken to be

From e7a2fbcb9c8768e58b9e973ee8f283939a73617e Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Tue, 3 Aug 2021 14:14:51 -0400
Subject: [PATCH 16/24] bugfix

---
 .../python/plotly/plotly/express/trendline_functions/__init__.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/packages/python/plotly/plotly/express/trendline_functions/__init__.py b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
index ace0c15bc61..67c0c540558 100644
--- a/packages/python/plotly/plotly/express/trendline_functions/__init__.py
+++ b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
@@ -93,6 +93,7 @@ def lowess(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
 
 def _pandas(mode, trendline_options, x_raw, y, non_missing):
     modes = dict(rolling="Rolling", ewm="Exponentially Weighted", expanding="Expanding")
+    trendline_options = trendline_options.copy()
     function_name = trendline_options.pop("function", "mean")
     function_args = trendline_options.pop("function_args", dict())
     series = pd.Series(y, index=x_raw)

From b6806ffc8137dcbe6399d4fcdc7282cf8f8cd266 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Wed, 4 Aug 2021 23:12:37 -0400
Subject: [PATCH 17/24] trendline_scope

---
 .../plotly/plotly/express/_chart_types.py     | 16 ++++--
 .../python/plotly/plotly/express/_core.py     | 54 ++++++++++++++-----
 packages/python/plotly/plotly/express/_doc.py |  9 +++-
 .../test_optional/test_px/test_trendline.py   | 39 ++++++++++++++
 4 files changed, 100 insertions(+), 18 deletions(-)

diff --git a/packages/python/plotly/plotly/express/_chart_types.py b/packages/python/plotly/plotly/express/_chart_types.py
index 5051c8a5367..25e5991c9bc 100644
--- a/packages/python/plotly/plotly/express/_chart_types.py
+++ b/packages/python/plotly/plotly/express/_chart_types.py
@@ -48,6 +48,7 @@ def scatter(
     trendline=None,
     trendline_options=None,
     trendline_color_override=None,
+    trendline_scope="trace",
     log_x=False,
     log_y=False,
     range_x=None,
@@ -93,6 +94,7 @@ def density_contour(
     trendline=None,
     trendline_options=None,
     trendline_color_override=None,
+    trendline_scope="trace",
     log_x=False,
     log_y=False,
     range_x=None,
@@ -202,7 +204,9 @@ def density_heatmap(
         z=[
             "For `density_heatmap` and `density_contour` these values are used as the inputs to `histfunc`.",
         ],
-        histfunc=["The arguments to this function are the values of `z`.",],
+        histfunc=[
+            "The arguments to this function are the values of `z`.",
+        ],
     ),
 )
 
@@ -467,7 +471,9 @@ def histogram(
         args=locals(),
         constructor=go.Histogram,
         trace_patch=dict(
-            histnorm=histnorm, histfunc=histfunc, cumulative=dict(enabled=cumulative),
+            histnorm=histnorm,
+            histfunc=histfunc,
+            cumulative=dict(enabled=cumulative),
         ),
         layout_patch=dict(barmode=barmode, barnorm=barnorm),
     )
@@ -527,7 +533,11 @@ def violin(
         args=locals(),
         constructor=go.Violin,
         trace_patch=dict(
-            points=points, box=dict(visible=box), scalegroup=True, x0=" ", y0=" ",
+            points=points,
+            box=dict(visible=box),
+            scalegroup=True,
+            x0=" ",
+            y0=" ",
         ),
         layout_patch=dict(violinmode=violinmode),
     )
diff --git a/packages/python/plotly/plotly/express/_core.py b/packages/python/plotly/plotly/express/_core.py
index 975ae24e248..cc0e98375b2 100644
--- a/packages/python/plotly/plotly/express/_core.py
+++ b/packages/python/plotly/plotly/express/_core.py
@@ -347,6 +347,9 @@ def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
                             )
 
                     # preserve original values of "x" in case they're dates
+                    # otherwise numpy/pandas can mess with the timezones
+                    # NB this means trendline functions must output one-to-one with the input series
+                    # i.e. we can't do resampling, because then the X values might not line up!
                     non_missing = np.logical_not(
                         np.logical_or(np.isnan(y), np.isnan(x))
                     )
@@ -867,23 +870,25 @@ def make_trace_spec(args, constructor, attrs, trace_patch):
             result.append(trace_spec)
 
     # Add trendline trace specifications
-    if "trendline" in args and args["trendline"]:
-        trace_spec = TraceSpec(
-            constructor=go.Scattergl
-            if constructor == go.Scattergl  # could be contour
-            else go.Scatter,
-            attrs=["trendline"],
-            trace_patch=dict(mode="lines"),
-            marginal=None,
-        )
-        if args["trendline_color_override"]:
-            trace_spec.trace_patch["line"] = dict(
-                color=args["trendline_color_override"]
-            )
-        result.append(trace_spec)
+    if args.get("trendline") and args.get("trendline_scope", "trace") == "trace":
+        result.append(make_trendline_spec(args, constructor))
     return result
 
 
+def make_trendline_spec(args, constructor):
+    trace_spec = TraceSpec(
+        constructor=go.Scattergl
+        if constructor == go.Scattergl  # could be contour
+        else go.Scatter,
+        attrs=["trendline"],
+        trace_patch=dict(mode="lines"),
+        marginal=None,
+    )
+    if args["trendline_color_override"]:
+        trace_spec.trace_patch["line"] = dict(color=args["trendline_color_override"])
+    return trace_spec
+
+
 def one_group(x):
     return ""
 
@@ -2127,6 +2132,27 @@ def make_figure(args, constructor, trace_patch=None, layout_patch=None):
         fig.update_layout(template=args["template"], overwrite=True)
     fig.frames = frame_list if len(frames) > 1 else []
 
+    if args.get("trendline") and args.get("trendline_scope", "trace") == "overall":
+        trendline_spec = make_trendline_spec(args, constructor)
+        trendline_trace = trendline_spec.constructor(
+            name="Overall Trendline", legendgroup="Overall Trendline", showlegend=False
+        )
+        if "line" not in trendline_spec.trace_patch:  # no color override
+            for m in grouped_mappings:
+                if m.variable == "color":
+                    next_color = m.sequence[len(m.val_map) % len(m.sequence)]
+                    trendline_spec.trace_patch["line"] = dict(color=next_color)
+        patch, fit_results = make_trace_kwargs(
+            args, trendline_spec, args["data_frame"], {}, sizeref
+        )
+        trendline_trace.update(patch)
+        fig.add_trace(
+            trendline_trace, row="all", col="all", exclude_empty_subplots=True
+        )
+        fig.update_traces(selector=-1, showlegend=True)
+        if fit_results is not None:
+            trendline_rows.append(dict(px_fit_results=fit_results))
+
     fig._px_trendlines = pd.DataFrame(trendline_rows)
 
     configure_axes(args, constructor, fig, orders)
diff --git a/packages/python/plotly/plotly/express/_doc.py b/packages/python/plotly/plotly/express/_doc.py
index ded3b039d55..60e474e7adb 100644
--- a/packages/python/plotly/plotly/express/_doc.py
+++ b/packages/python/plotly/plotly/express/_doc.py
@@ -325,7 +325,10 @@
         "Setting this value is recommended when using `plotly.express.colors.diverging` color scales as the inputs to `color_continuous_scale`.",
     ],
     size_max=["int (default `20`)", "Set the maximum mark size when using `size`."],
-    markers=["boolean (default `False`)", "If `True`, markers are shown on lines.",],
+    markers=[
+        "boolean (default `False`)",
+        "If `True`, markers are shown on lines.",
+    ],
     log_x=[
         "boolean (default `False`)",
         "If `True`, the x-axis is log-scaled in cartesian coordinates.",
@@ -420,6 +423,10 @@
         "Valid CSS color.",
         "If provided, and if `trendline` is set, all trendlines will be drawn in this color rather than in the same color as the traces from which they draw their inputs.",
     ],
+    trendline_scope=[
+        "str (one of `'trace'` or `'overall'`, default `'trace'`)",
+        "If `'trace'`, then one trendline is drawn per trace (i.e. per color, symbol, facet, animation frame etc) and if `'overall'` then one trendline is computed for the entire dataset, and replicated across all facets.",
+    ],
     render_mode=[
         "str",
         "One of `'auto'`, `'svg'` or `'webgl'`, default `'auto'`",
diff --git a/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py b/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
index 5f47cad2f6f..66046981eff 100644
--- a/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
+++ b/packages/python/plotly/plotly/tests/test_optional/test_px/test_trendline.py
@@ -200,3 +200,42 @@ def test_trendline_on_timeseries(mode, options):
     assert type(fig.data[1].x[0]) == datetime
     assert np.all(fig.data[0].x == fig.data[1].x)
     assert str(fig.data[0].x[0]) == str(fig.data[1].x[0])
+
+
+def test_overall_trendline():
+    df = px.data.tips()
+    fig1 = px.scatter(df, x="total_bill", y="tip", trendline="ols")
+    assert len(fig1.data) == 2
+    assert "trendline" in fig1.data[1].hovertemplate
+    results1 = px.get_trendline_results(fig1)
+    params1 = results1["px_fit_results"].iloc[0].params
+
+    fig2 = px.scatter(
+        df,
+        x="total_bill",
+        y="tip",
+        color="sex",
+        trendline="ols",
+        trendline_scope="overall",
+    )
+    assert len(fig2.data) == 3
+    assert "trendline" in fig2.data[2].hovertemplate
+    results2 = px.get_trendline_results(fig2)
+    params2 = results2["px_fit_results"].iloc[0].params
+
+    assert np.all(np.array_equal(params1, params2))
+
+    fig3 = px.scatter(
+        df,
+        x="total_bill",
+        y="tip",
+        facet_row="sex",
+        trendline="ols",
+        trendline_scope="overall",
+    )
+    assert len(fig3.data) == 4
+    assert "trendline" in fig3.data[3].hovertemplate
+    results3 = px.get_trendline_results(fig3)
+    params3 = results3["px_fit_results"].iloc[0].params
+
+    assert np.all(np.array_equal(params1, params3))

From 6ef46bfa2a7ea6613af77b8655f6ff36d7f9212d Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Wed, 4 Aug 2021 23:29:35 -0400
Subject: [PATCH 18/24] black

---
 .../python/plotly/plotly/express/_chart_types.py   | 14 +++-----------
 packages/python/plotly/plotly/express/_doc.py      |  5 +----
 2 files changed, 4 insertions(+), 15 deletions(-)

diff --git a/packages/python/plotly/plotly/express/_chart_types.py b/packages/python/plotly/plotly/express/_chart_types.py
index 25e5991c9bc..f335e78de34 100644
--- a/packages/python/plotly/plotly/express/_chart_types.py
+++ b/packages/python/plotly/plotly/express/_chart_types.py
@@ -204,9 +204,7 @@ def density_heatmap(
         z=[
             "For `density_heatmap` and `density_contour` these values are used as the inputs to `histfunc`.",
         ],
-        histfunc=[
-            "The arguments to this function are the values of `z`.",
-        ],
+        histfunc=["The arguments to this function are the values of `z`.",],
     ),
 )
 
@@ -471,9 +469,7 @@ def histogram(
         args=locals(),
         constructor=go.Histogram,
         trace_patch=dict(
-            histnorm=histnorm,
-            histfunc=histfunc,
-            cumulative=dict(enabled=cumulative),
+            histnorm=histnorm, histfunc=histfunc, cumulative=dict(enabled=cumulative),
         ),
         layout_patch=dict(barmode=barmode, barnorm=barnorm),
     )
@@ -533,11 +529,7 @@ def violin(
         args=locals(),
         constructor=go.Violin,
         trace_patch=dict(
-            points=points,
-            box=dict(visible=box),
-            scalegroup=True,
-            x0=" ",
-            y0=" ",
+            points=points, box=dict(visible=box), scalegroup=True, x0=" ", y0=" ",
         ),
         layout_patch=dict(violinmode=violinmode),
     )
diff --git a/packages/python/plotly/plotly/express/_doc.py b/packages/python/plotly/plotly/express/_doc.py
index 60e474e7adb..37d16cd1e11 100644
--- a/packages/python/plotly/plotly/express/_doc.py
+++ b/packages/python/plotly/plotly/express/_doc.py
@@ -325,10 +325,7 @@
         "Setting this value is recommended when using `plotly.express.colors.diverging` color scales as the inputs to `color_continuous_scale`.",
     ],
     size_max=["int (default `20`)", "Set the maximum mark size when using `size`."],
-    markers=[
-        "boolean (default `False`)",
-        "If `True`, markers are shown on lines.",
-    ],
+    markers=["boolean (default `False`)", "If `True`, markers are shown on lines.",],
     log_x=[
         "boolean (default `False`)",
         "If `True`, the x-axis is log-scaled in cartesian coordinates.",

From f37eb06303e5873780b57e20cb6e46097cf0daad Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Wed, 4 Aug 2021 23:33:33 -0400
Subject: [PATCH 19/24] changelog

---
 CHANGELOG.md | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 8985395f77b..1fd1096655d 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -8,6 +8,9 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 ### Added
   - Extra flags were added to the `gapminder` and `stocks` dataset to facilitate testing, documentation and demos [#3305](https://github.com/plotly/plotly.py/issues/3305)
   - All line-like Plotly Express functions now accept `markers` argument to display markers, and all but `line_mapbox` accept `symbol` to map a field to the symbol attribute, similar to scatter-like functions [#3326](https://github.com/plotly/plotly.py/issues/3326)
+  - `px.scatter` and `px.density_contours` now support new `trendline` types `"rolling"`, `"expanding"` and `"ewm`
+  - `px.scatter` and `px.density_contours` now support new `trendline_options` argument to parameterize trendlines, with support for constant control and log-scaling in `'ols'` and specification of the fraction used for `'lowess'`
+  - `px.scatter` and `px.density_contours` now support new `trendline_scope` argument that accepts the value `'overall'` to request a single trendline for all traces, including across facets and animation frames
 
 ### Fixed
   - Fixed regression introduced in version 5.0.0 where pandas/numpy arrays with `dtype` of Object were being converted to `list` values when added to a Figure ([#3292](https://github.com/plotly/plotly.py/issues/3292), [#3293](https://github.com/plotly/plotly.py/pull/3293))

From 03c146cd52a922c043302fed4aa6c726a43a9c1a Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Wed, 4 Aug 2021 23:34:09 -0400
Subject: [PATCH 20/24] changelog

---
 CHANGELOG.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 1fd1096655d..9ddd0bd04c8 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -8,9 +8,9 @@ This project adheres to [Semantic Versioning](http://semver.org/).
 ### Added
   - Extra flags were added to the `gapminder` and `stocks` dataset to facilitate testing, documentation and demos [#3305](https://github.com/plotly/plotly.py/issues/3305)
   - All line-like Plotly Express functions now accept `markers` argument to display markers, and all but `line_mapbox` accept `symbol` to map a field to the symbol attribute, similar to scatter-like functions [#3326](https://github.com/plotly/plotly.py/issues/3326)
-  - `px.scatter` and `px.density_contours` now support new `trendline` types `"rolling"`, `"expanding"` and `"ewm`
-  - `px.scatter` and `px.density_contours` now support new `trendline_options` argument to parameterize trendlines, with support for constant control and log-scaling in `'ols'` and specification of the fraction used for `'lowess'`
-  - `px.scatter` and `px.density_contours` now support new `trendline_scope` argument that accepts the value `'overall'` to request a single trendline for all traces, including across facets and animation frames
+  - `px.scatter` and `px.density_contours` now support new `trendline` types `'rolling'`, `'expanding'` and `'ewm'` [#2997](https://github.com/plotly/plotly.py/pull/2997)
+  - `px.scatter` and `px.density_contours` now support new `trendline_options` argument to parameterize trendlines, with support for constant control and log-scaling in `'ols'` and specification of the fraction used for `'lowess'`, as well as pass-through to Pandas for `'rolling'`, `'expanding'` and `'ewm'` [#2997](https://github.com/plotly/plotly.py/pull/2997)
+  - `px.scatter` and `px.density_contours` now support new `trendline_scope` argument that accepts the value `'overall'` to request a single trendline for all traces, including across facets and animation frames [#2997](https://github.com/plotly/plotly.py/pull/2997)
 
 ### Fixed
   - Fixed regression introduced in version 5.0.0 where pandas/numpy arrays with `dtype` of Object were being converted to `list` values when added to a Figure ([#3292](https://github.com/plotly/plotly.py/issues/3292), [#3293](https://github.com/plotly/plotly.py/pull/3293))

From bd0d368bea5f110027c41510c6bdcf8313930e5b Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Wed, 4 Aug 2021 23:40:05 -0400
Subject: [PATCH 21/24] validate trendline_options

---
 .../express/trendline_functions/__init__.py      | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)

diff --git a/packages/python/plotly/plotly/express/trendline_functions/__init__.py b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
index 67c0c540558..9d1c5f5e534 100644
--- a/packages/python/plotly/plotly/express/trendline_functions/__init__.py
+++ b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
@@ -30,6 +30,13 @@ def ols(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
     respect to the base 10 logarithm of the input. Note that this means no zeros can
     be present in the input.
     """
+    valid_options = ["add_constant", "log_x", "log_y"]
+    for k in trendline_options.keys():
+        if k not in valid_options:
+            raise ValueError(
+                "OLS trendline_options keys must be one of [%s] but got '%s'"
+                % (", ".join(valid_options), k)
+            )
 
     import statsmodels.api as sm
 
@@ -83,6 +90,15 @@ def lowess(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
     - `frac` (`float`, default `0.6666666`): the `frac` parameter from the
     `statsmodels.api.nonparametric.lowess` function
     """
+
+    valid_options = ["frac"]
+    for k in trendline_options.keys():
+        if k not in valid_options:
+            raise ValueError(
+                "LOWESS trendline_options keys must be one of [%s] but got '%s'"
+                % (", ".join(valid_options), k)
+            )
+
     import statsmodels.api as sm
 
     frac = trendline_options.get("frac", 0.6666666)

From 860a321aa6416cf06d0a539e9a6a3bb9d256b637 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Thu, 5 Aug 2021 11:39:01 -0400
Subject: [PATCH 22/24] tweak docstrings

---
 packages/python/plotly/plotly/express/_doc.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/packages/python/plotly/plotly/express/_doc.py b/packages/python/plotly/plotly/express/_doc.py
index 37d16cd1e11..65d9f0588ff 100644
--- a/packages/python/plotly/plotly/express/_doc.py
+++ b/packages/python/plotly/plotly/express/_doc.py
@@ -402,11 +402,12 @@
     ],
     trendline=[
         "str",
-        "One of `'ols'`, `'lowess'`, `'ma'` or `'ewma'`.",
+        "One of `'ols'`, `'lowess'`, `'rolling'`, `'expanding'` or `'ewm'`.",
         "If `'ols'`, an Ordinary Least Squares regression line will be drawn for each discrete-color/symbol group.",
         "If `'lowess`', a Locally Weighted Scatterplot Smoothing line will be drawn for each discrete-color/symbol group.",
-        "If `'ma`', a Moving Average line will be drawn for each discrete-color/symbol group.",
-        "If `'ewma`', an Exponentially Weighted Moving Average line will be drawn for each discrete-color/symbol group.",
+        "If `'rolling`', a Rolling (e.g. rolling average, rolling median) line will be drawn for each discrete-color/symbol group.",
+        "If `'expanding`', an Expanding (e.g. expanding average, expanding sum) line will be drawn for each discrete-color/symbol group.",
+        "If `'ewm`', an Exponentially Weighted Moment (e.g. exponentially-weighted moving average) line will be drawn for each discrete-color/symbol group.",
         "See the docstrings for the functions in `plotly.express.trendline_functions` for more details on these functions and how",
         "to configure them with the `trendline_options` argument.",
     ],

From ab0e0aba3b809567b2a77855427aa1d0bfb15034 Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Wed, 11 Aug 2021 12:11:23 -0400
Subject: [PATCH 23/24] positive values only for logs

---
 .../plotly/plotly/express/trendline_functions/__init__.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/packages/python/plotly/plotly/express/trendline_functions/__init__.py b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
index 9d1c5f5e534..f0fc29cee4b 100644
--- a/packages/python/plotly/plotly/express/trendline_functions/__init__.py
+++ b/packages/python/plotly/plotly/express/trendline_functions/__init__.py
@@ -45,16 +45,16 @@ def ols(trendline_options, x_raw, x, y, x_label, y_label, non_missing):
     log_y = trendline_options.get("log_y", False)
 
     if log_y:
-        if np.any(y == 0):
+        if np.any(y <= 0):
             raise ValueError(
-                "Can't do OLS trendline with `log_y=True` when `y` contains zeros."
+                "Can't do OLS trendline with `log_y=True` when `y` contains non-positive values."
             )
         y = np.log10(y)
         y_label = "log10(%s)" % y_label
     if log_x:
-        if np.any(x == 0):
+        if np.any(x <= 0):
             raise ValueError(
-                "Can't do OLS trendline with `log_x=True` when `x` contains zeros."
+                "Can't do OLS trendline with `log_x=True` when `x`  contains non-positive values."
             )
         x = np.log10(x)
         x_label = "log10(%s)" % x_label

From f42c5afe5153f2394ed997df0a8e34d2dbd3521a Mon Sep 17 00:00:00 2001
From: Nicolas Kruchten <nicolas@plot.ly>
Date: Wed, 11 Aug 2021 20:32:43 -0400
Subject: [PATCH 24/24] docs for trendlines

---
 doc/python/linear-fits.md | 165 +++++++++++++++++++++++++++++++++++---
 1 file changed, 156 insertions(+), 9 deletions(-)

diff --git a/doc/python/linear-fits.md b/doc/python/linear-fits.md
index 7f1f1a2971f..0029be6c4be 100644
--- a/doc/python/linear-fits.md
+++ b/doc/python/linear-fits.md
@@ -5,8 +5,8 @@ jupyter:
     text_representation:
       extension: .md
       format_name: markdown
-      format_version: '1.1'
-      jupytext_version: 1.1.1
+      format_version: '1.2'
+      jupytext_version: 1.4.2
   kernelspec:
     display_name: Python 3
     language: python
@@ -20,11 +20,12 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.6.8
+    version: 3.7.7
   plotly:
     description: Add linear Ordinary Least Squares (OLS) regression trendlines or
       non-linear Locally Weighted Scatterplot Smoothing (LOWESS) trendlines to scatterplots
-      in Python.
+      in Python. Options for moving averages (rolling means) as well as exponentially-weighted
+      and expanding functions.
     display_as: statistical
     language: python
     layout: base
@@ -39,7 +40,7 @@ jupyter:
 
 [Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on a variety of types of data](/python/px-arguments/) and produces [easy-to-style figures](/python/styling-plotly-express/).
 
-Plotly Express allows you to add [Ordinary Least](https://en.wikipedia.org/wiki/Ordinary_least_squares) Squares regression trendline to scatterplots with the `trendline` argument. In order to do so, you will need to install `statsmodels` and its dependencies. Hovering over the trendline will show the equation of the line and its R-squared value.
+Plotly Express allows you to add [Ordinary Least Squares](https://en.wikipedia.org/wiki/Ordinary_least_squares) regression trendline to scatterplots with the `trendline` argument. In order to do so, you will need to [install `statsmodels` and its dependencies](https://www.statsmodels.org/stable/install.html). Hovering over the trendline will show the equation of the line and its R-squared value.
 
 ```python
 import plotly.express as px
@@ -66,14 +67,160 @@ print(results)
 results.query("sex == 'Male' and smoker == 'Yes'").px_fit_results.iloc[0].summary()
 ```
 
-### Non-Linear Trendlines
+### Displaying a single trendline with multiple traces
 
-Plotly Express also supports non-linear [LOWESS](https://en.wikipedia.org/wiki/Local_regression) trendlines.
+_new in v5.2_
+
+To display a single trendline using the entire dataset, set the `trendline_scope` argument to `"overall"`. The same trendline will be overlaid on all facets and animation frames. The trendline color can be overridden with `trendline_color_override`.
+
+```python
+import plotly.express as px
+
+df = px.data.tips()
+fig = px.scatter(df, x="total_bill", y="tip", symbol="smoker", color="sex", trendline="ols", trendline_scope="overall")
+fig.show()
+```
+
+```python
+import plotly.express as px
+
+df = px.data.tips()
+fig = px.scatter(df, x="total_bill", y="tip", facet_col="smoker", color="sex", 
+                 trendline="ols", trendline_scope="overall", trendline_color_override="black")
+fig.show()
+```
+
+### OLS Parameters
+
+_new in v5.2_
+
+OLS trendlines can be fit with log transformations to both X or Y data using the `trendline_options` argument, independently of whether or not the plot has [logarithmic axes](https://plotly.com/python/log-plot/).
+
+```python
+import plotly.express as px
+
+df = px.data.gapminder(year=2007)
+fig = px.scatter(df, x="gdpPercap", y="lifeExp", 
+                 trendline="ols", trendline_options=dict(log_x=True),
+                 title="Log-transformed fit on linear axes")
+fig.show()
+```
+
+```python
+import plotly.express as px
+
+df = px.data.gapminder(year=2007)
+fig = px.scatter(df, x="gdpPercap", y="lifeExp", log_x=True, 
+                 trendline="ols", trendline_options=dict(log_x=True),
+                 title="Log-scaled X axis and log-transformed fit")
+fig.show()
+```
+
+### Locally WEighted Scatterplot Smoothing (LOWESS)
+
+Plotly Express also supports non-linear [LOWESS](https://en.wikipedia.org/wiki/Local_regression) trendlines. In order use this feature, you will need to [install `statsmodels` and its dependencies](https://www.statsmodels.org/stable/install.html).
+
+```python
+import plotly.express as px
+
+df = px.data.stocks(datetimes=True)
+fig = px.scatter(df, x="date", y="GOOG", trendline="lowess")
+fig.show()
+```
+
+_new in v5.2_
+
+The level of smoothing can be controlled via the `frac` trendline option, which indicates the fraction of the data that the LOWESS smoother should include. The default is a fairly smooth line with `frac=0.6666` and lowering this fraction will give a line that more closely follows the data.
+
+```python
+import plotly.express as px
+
+df = px.data.stocks(datetimes=True)
+fig = px.scatter(df, x="date", y="GOOG", trendline="lowess", trendline_options=dict(frac=0.1))
+fig.show()
+```
+
+### Moving Averages
+
+_new in v5.2_
+
+Plotly Express can leverage Pandas' [`rolling`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.rolling.html), [`ewm`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.ewm.html) and [`expanding`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.expanding.html) functions in trendlines as well, for example to display moving averages. Values passed to `trendline_options` are passed directly to the underlying Pandas function (with the exception of the `function` and `function_options` keys, see below).
+
+```python
+import plotly.express as px
+
+df = px.data.stocks(datetimes=True)
+fig = px.scatter(df, x="date", y="GOOG", trendline="rolling", trendline_options=dict(window=5),
+                title="5-point moving average")
+fig.show()
+```
+
+```python
+import plotly.express as px
+
+df = px.data.stocks(datetimes=True)
+fig = px.scatter(df, x="date", y="GOOG", trendline="ewm", trendline_options=dict(halflife=2),
+                title="Exponentially-weighted moving average (halflife of 2 points)")
+fig.show()
+```
+
+```python
+import plotly.express as px
+
+df = px.data.stocks(datetimes=True)
+fig = px.scatter(df, x="date", y="GOOG", trendline="expanding", title="Expanding mean")
+fig.show()
+```
+
+### Other Functions
+
+The `rolling`, `expanding` and `ewm` trendlines support other functions than the default `mean`, enabling, for example, a moving-median trendline, or an expanding-max trendline.
 
 ```python
 import plotly.express as px
 
-df = px.data.gapminder().query("year == 2007")
-fig = px.scatter(df, x="gdpPercap", y="lifeExp", color="continent", trendline="lowess")
+df = px.data.stocks(datetimes=True)
+fig = px.scatter(df, x="date", y="GOOG", trendline="rolling", trendline_options=dict(function="median", window=5),
+                title="Rolling Median")
 fig.show()
 ```
+
+```python
+import plotly.express as px
+
+df = px.data.stocks(datetimes=True)
+fig = px.scatter(df, x="date", y="GOOG", trendline="expanding", trendline_options=dict(function="max"),
+                title="Expanding Maximum")
+fig.show()
+```
+
+In some cases, it is necessary to pass options into the underying Pandas function, for example the `std` parameter must be provided if the `win_type` argument to `rolling` is `"gaussian"`. This is possible with the `function_args` trendline option.
+
+```python
+import plotly.express as px
+
+df = px.data.stocks(datetimes=True)
+fig = px.scatter(df, x="date", y="GOOG", trendline="rolling", 
+                 trendline_options=dict(window=5, win_type="gaussian", function_args=dict(std=2)),
+                title="Rolling Mean with Gaussian Window")
+fig.show()
+```
+
+### Displaying only the trendlines
+
+In some cases, it may be desirable to show only the trendlines, by removing the scatter points.
+
+```python
+import plotly.express as px
+
+df = px.data.stocks(indexed=True, datetimes=True)
+fig = px.scatter(df, trendline="rolling", trendline_options=dict(window=5),
+                title="5-point moving average")
+fig.data = [t for t in fig.data if t.mode == "lines"]
+fig.update_traces(showlegend=True) #trendlines have showlegend=False by default
+fig.show()
+```
+
+```python
+
+```