mostly finished ECDF

Author: nicolaskruchten

Diff for: packages/python/plotly/plotly/express/_chart_types.py

@@ -476,6 +476,7 @@ def ecdf(
     x=None,
     y=None,
     color=None,
+    text=None,
     line_dash=None,
     facet_row=None,
     facet_col=None,
@@ -495,9 +496,9 @@ def ecdf(
     marginal=None,
     opacity=None,
     orientation=None,
-    line_shape=None,
-    norm=None,  # TODO use this
-    complementary=None,  # TODO use this
+    line_shape="hv",
+    norm="probability",
+    complementary=False,
     log_x=False,
     log_y=False,
     range_x=None,

Diff for: packages/python/plotly/plotly/express/_core.py

@@ -153,13 +153,17 @@ def get_decorated_label(args, column, role):
         or (role == "x" and "orientation" in args and args["orientation"] == "h")
         or (role == "y" and "orientation" in args and args["orientation"] == "v")
     ):
-        if label:
-            label = "%s of %s" % (args["histfunc"] or "count", label)
+        histfunc = args["histfunc"] or "count"
+        if label and histfunc != "count":
+            label = "%s of %s" % (histfunc, label)
         else:
             label = "count"
 
         if "histnorm" in args and args["histnorm"] is not None:
-            label = "%s of %s" % (args["histnorm"], label)
+            if label == "count":
+                label = args["histnorm"]
+            else:
+                label = "%s of %s" % (args["histnorm"], label)
 
         if "barnorm" in args and args["barnorm"] is not None:
             label = "%s (normalized as %s)" % (label, args["barnorm"])
@@ -1421,11 +1425,7 @@ def build_dataframe(args, constructor):
 
         if hist1d_orientation:
             args["x" if orient_v else "y"] = value_name
-            if wide_cross_name is None and constructor == go.Scatter:
-                args["y" if orient_v else "x"] = count_name
-                df_output[count_name] = 1
-            else:
-                args["y" if orient_v else "x"] = wide_cross_name
+            args["y" if orient_v else "x"] = wide_cross_name
             args["color"] = args["color"] or var_name
         elif constructor in [go.Scatter, go.Funnel] + hist2d_types:
             args["x" if orient_v else "y"] = wide_cross_name
@@ -1447,6 +1447,21 @@ def build_dataframe(args, constructor):
         elif constructor in [go.Violin, go.Box]:
             args["x" if orient_v else "y"] = wide_cross_name or var_name
             args["y" if orient_v else "x"] = value_name
+
+    if hist1d_orientation and constructor == go.Scatter:
+        if args["x"] is not None and args["y"] is not None:
+            args["histfunc"] = "sum"
+        elif args["x"] is None:
+            args["histfunc"] = None
+            args["orientation"] = "h"
+            args["x"] = count_name
+            df_output[count_name] = 1
+        else:
+            args["histfunc"] = None
+            args["orientation"] = "v"
+            args["y"] = count_name
+            df_output[count_name] = 1
+
     if no_color:
         args["color"] = None
     args["data_frame"] = df_output
@@ -1743,8 +1758,10 @@ def infer_config(args, constructor, trace_patch, layout_patch):
             trace_patch["opacity"] = args["opacity"]
         else:
             trace_patch["marker"] = dict(opacity=args["opacity"])
-    if "line_group" in args:
-        trace_patch["mode"] = "lines" + ("+markers+text" if args["text"] else "")
+    if "line_group" in args or "line_dash" in args:
+        trace_patch["mode"] = "lines" + (
+            "+markers+text" if args.get("text", None) is not None else ""
+        )
     elif constructor != go.Splom and (
         "symbol" in args or constructor == go.Scattermapbox
     ):
@@ -2001,7 +2018,17 @@ def make_figure(args, constructor, trace_patch=None, layout_patch=None):
                 base = args["x"] if args["orientation"] == "v" else args["y"]
                 var = args["x"] if args["orientation"] == "h" else args["y"]
                 group = group.sort_values(by=base)
+                group_sum = group[var].sum()
                 group[var] = group[var].cumsum()
+                if args["complementary"]:
+                    group[var] = group_sum - group[var]
+
+                if args["norm"] == "probability":
+                    group[var] = group[var] / group_sum
+                elif args["norm"] == "percent":
+                    group[var] = 100.0 * group[var] / group_sum
+                args["histnorm"] = args["norm"]
+                # TODO norm, including histnorm-like naming
 
             patch, fit_results = make_trace_kwargs(
                 args, trace_spec, group, mapping_labels.copy(), sizeref