Support implicit dataframe argument.

plotly_express/_chart_types.py

@@ -4,7 +4,7 @@
 
 
 def scatter(
-    data_frame,
+    data_frame=None,
     x=None,
     y=None,
     color=None,
@@ -56,7 +56,7 @@ def scatter(
 
 
 def density_contour(
-    data_frame,
+    data_frame=None,
     x=None,
     y=None,
     z=None,
@@ -166,7 +166,7 @@ def density_heatmap(
 
 
 def line(
-    data_frame,
+    data_frame=None,
     x=None,
     y=None,
     line_group=None,
@@ -210,7 +210,7 @@ def line(
 
 
 def area(
-    data_frame,
+    data_frame=None,
     x=None,
     y=None,
     line_group=None,
@@ -254,7 +254,7 @@ def area(
 
 
 def bar(
-    data_frame,
+    data_frame=None,
     x=None,
     y=None,
     color=None,
@@ -303,7 +303,7 @@ def bar(
 
 
 def histogram(
-    data_frame,
+    data_frame=None,
     x=None,
     y=None,
     color=None,
@@ -360,7 +360,7 @@ def histogram(
 
 
 def violin(
-    data_frame,
+    data_frame=None,
     x=None,
     y=None,
     color=None,
@@ -410,7 +410,7 @@ def violin(
 
 
 def box(
-    data_frame,
+    data_frame=None,
     x=None,
     y=None,
     color=None,
@@ -504,7 +504,7 @@ def strip(
 
 
 def scatter_3d(
-    data_frame,
+    data_frame=None,
     x=None,
     y=None,
     z=None,
@@ -554,7 +554,7 @@ def scatter_3d(
 
 
 def line_3d(
-    data_frame,
+    data_frame=None,
     x=None,
     y=None,
     z=None,
@@ -599,7 +599,7 @@ def line_3d(
 
 
 def scatter_ternary(
-    data_frame,
+    data_frame=None,
     a=None,
     b=None,
     c=None,
@@ -637,7 +637,7 @@ def scatter_ternary(
 
 
 def line_ternary(
-    data_frame,
+    data_frame=None,
     a=None,
     b=None,
     c=None,
@@ -671,7 +671,7 @@ def line_ternary(
 
 
 def scatter_polar(
-    data_frame,
+    data_frame=None,
     r=None,
     theta=None,
     color=None,
@@ -714,7 +714,7 @@ def scatter_polar(
 
 
 def line_polar(
-    data_frame,
+    data_frame=None,
     r=None,
     theta=None,
     color=None,
@@ -753,7 +753,7 @@ def line_polar(
 
 
 def bar_polar(
-    data_frame,
+    data_frame=None,
     r=None,
     theta=None,
     color=None,
@@ -790,7 +790,7 @@ def bar_polar(
 
 
 def choropleth(
-    data_frame,
+    data_frame=None,
     lat=None,
     lon=None,
     locations=None,
@@ -829,7 +829,7 @@ def choropleth(
 
 
 def scatter_geo(
-    data_frame,
+    data_frame=None,
     lat=None,
     lon=None,
     locations=None,
@@ -872,7 +872,7 @@ def scatter_geo(
 
 
 def line_geo(
-    data_frame,
+    data_frame=None,
     lat=None,
     lon=None,
     locations=None,
@@ -913,7 +913,7 @@ def line_geo(
 
 
 def scatter_mapbox(
-    data_frame,
+    data_frame=None,
     lat=None,
     lon=None,
     color=None,
@@ -948,7 +948,7 @@ def scatter_mapbox(
 
 
 def line_mapbox(
-    data_frame,
+    data_frame=None,
     lat=None,
     lon=None,
     color=None,
@@ -978,7 +978,7 @@ def line_mapbox(
 
 
 def scatter_matrix(
-    data_frame,
+    data_frame=None,
     dimensions=None,
     color=None,
     symbol=None,
@@ -1015,7 +1015,7 @@ def scatter_matrix(
 
 
 def parallel_coordinates(
-    data_frame,
+    data_frame=None,
     dimensions=None,
     color=None,
     labels={},
@@ -1039,7 +1039,7 @@ def parallel_coordinates(
 
 
 def parallel_categories(
-    data_frame,
+    data_frame=None,
     dimensions=None,
     color=None,
     labels={},

plotly_express/_core.py

@@ -659,6 +659,28 @@ def apply_default_cascade(args):
         if args["color_discrete_sequence"] is None:
             args["color_discrete_sequence"] = qualitative.Plotly
 
+def has_value(collection, key):
+    return collection.get(key, None) is not None
+
+def build_dataframe(args, attrables):
+    """
+    Constructs an implicit dataframe and modifies `args` in-place.
+
+    `attrables` is a list of keys into `args`, all of whose corresponding
+    values are converted into columns of a dataframe.
+
+    Used to be support calls to plotting function that elide a dataframe argument;
+    for example `scatter(x=[1,2], y=[3,4])`.
+    """
+    data_frame_columns = {}
+    for field in attrables:
+        if not has_value(args, field):
+            continue
+        data_frame_columns[field] = args[field]
+        # This sets the label of an attribute to be the name of the attribute.
+        args[field] = field
+    args["data_frame"] = pandas.DataFrame(data_frame_columns)
+    return args
 
 def infer_config(args, constructor, trace_patch):
     attrables = (
@@ -669,11 +691,12 @@ def infer_config(args, constructor, trace_patch):
     )
     array_attrables = ["dimensions", "hover_data"]
     group_attrables = ["animation_frame", "facet_row", "facet_col", "line_group"]
-
+    all_attrables = attrables + group_attrables + ["color"]
+    if not has_value(args, "data_frame"):
+        build_dataframe(args, all_attrables)
     df_columns = args["data_frame"].columns
-
-    for attr in attrables + group_attrables + ["color"]:
-        if attr in args and args[attr] is not None:
+    for attr in all_attrables:
+        if has_value(args, attr):
             maybe_col_list = [args[attr]] if attr not in array_attrables else args[attr]
             for maybe_col in maybe_col_list:
                 try:
@@ -790,7 +813,6 @@ def get_orderings(args, grouper, grouped):
 
     return orders, group_names
 
-
 def make_figure(args, constructor, trace_patch={}, layout_patch={}):
     apply_default_cascade(args)
     trace_specs, grouped_mappings, sizeref, show_colorbar = infer_config(