PX: Avoid groupby when possible and access groups more efficiently

packages/python/plotly/plotly/express/_core.py

@@ -1904,7 +1904,7 @@ def infer_config(args, constructor, trace_patch, layout_patch):
     return trace_specs, grouped_mappings, sizeref, show_colorbar
 
 
-def get_orderings(args, grouper, grouped):
+def get_orderings(args, grouper):
     """
     `orders` is the user-supplied ordering with the remaining data-frame-supplied
     ordering appended if the column is used for grouping. It includes anything the user
@@ -1915,29 +1915,43 @@ def get_orderings(args, grouper, grouped):
     of tuples like [("value1", ""), ("value2", "")] where each tuple contains the name
     of a single dimension-group
     """
-
     orders = {} if "category_orders" not in args else args["category_orders"].copy()
+
+    # figure out orders and what the single group name would be if there were one
+    single_group_name = []
     for col in grouper:
-        if col != one_group:
+        if col == one_group:
+            single_group_name.append("")
+        else:
             uniques = list(args["data_frame"][col].unique())
+            if len(uniques) == 1:
+                single_group_name.append(uniques[0])
             if col not in orders:
                 orders[col] = uniques
             else:
                 orders[col] = list(OrderedDict.fromkeys(list(orders[col]) + uniques))
 
-    sorted_group_names = []
-    for group_name in grouped.groups:
-        if len(grouper) == 1:
-            group_name = (group_name,)
-        sorted_group_names.append(group_name)
-
-    for i, col in reversed(list(enumerate(grouper))):
-        if col != one_group:
-            sorted_group_names = sorted(
-                sorted_group_names,
-                key=lambda g: orders[col].index(g[i]) if g[i] in orders[col] else -1,
-            )
-    return orders, sorted_group_names
+    if len(single_group_name) == len(grouper):
+        # we have a single group, so we can skip all group-by operations!
+        grouped = None
+        sorted_group_names = [tuple(single_group_name)]
+    else:
+        grouped = args["data_frame"].groupby(grouper, sort=False)
+        sorted_group_names = []
+        for group_name in grouped.groups:
+            if len(grouper) == 1:
+                group_name = (group_name,)
+            sorted_group_names.append(group_name)
+
+        for i, col in reversed(list(enumerate(grouper))):
+            if col != one_group:
+                sorted_group_names = sorted(
+                    sorted_group_names,
+                    key=lambda g: orders[col].index(g[i])
+                    if g[i] in orders[col]
+                    else -1,
+                )
+    return grouped, orders, sorted_group_names
 
 
 def make_figure(args, constructor, trace_patch=None, layout_patch=None):
@@ -1956,9 +1970,7 @@ def make_figure(args, constructor, trace_patch=None, layout_patch=None):
         args, constructor, trace_patch, layout_patch
     )
     grouper = [x.grouper or one_group for x in grouped_mappings] or [one_group]
-    grouped = args["data_frame"].groupby(grouper, sort=False)
-
-    orders, sorted_group_names = get_orderings(args, grouper, grouped)
+    grouped, orders, sorted_group_names = get_orderings(args, grouper)
 
     col_labels = []
     row_labels = []
@@ -1988,7 +2000,12 @@ def make_figure(args, constructor, trace_patch=None, layout_patch=None):
     trace_name_labels = None
     facet_col_wrap = args.get("facet_col_wrap", 0)
     for group_name in sorted_group_names:
-        group = grouped.get_group(group_name if len(group_name) > 1 else group_name[0])
+        if grouped is not None:
+            group = grouped.get_group(
+                group_name if len(group_name) > 1 else group_name[0]
+            )
+        else:
+            group = args["data_frame"]
         mapping_labels = OrderedDict()
         trace_name_labels = OrderedDict()
         frame_name = ""