address review comments

Author: emmanuelle

doc/python/hover-text-and-formatting.md

@@ -124,7 +124,7 @@ fig.show()
 * `True` to add a different column, with default formatting
 * a formatting string starting with `:` for numbers [d3-format's syntax](https://github.com/d3/d3-3.x-api-reference/blob/master/Formatting.md#d3_forma), and `|` for dates in [d3-time-format's syntax](https://github.com/d3/d3-3.x-api-reference/blob/master/Time-Formatting.md#format), for example `:.3f`, `|%a`.
 
-For passing new data, the value is a tuple, which first element is one of the possible values described above for existing columns, and the second element correspond to the hover values, for example `(True, [1, 2, 3])` or `(':.1f', [1.54, 2.345])`.
+It is also possible to pass new data as values of the `hover_data` dict, either as list-like data, or inside a tuple, which first element is one of the possible values described above for existing columns, and the second element correspond to the list-like data, for example `(True, [1, 2, 3])` or `(':.1f', [1.54, 2.345])`.
 
 These different cases are illustrated in the following example.
 
@@ -138,7 +138,7 @@ fig = px.scatter(df, x='petal_length', y='sepal_length', facet_col='species', co
                              'petal_width':True, # add other column, default formatting
                              'sepal_width':':.2f', # add other column, customized formatting
                              # data not in dataframe, default formatting
-                             'suppl_1': (True, np.random.random(len(df))),
+                             'suppl_1': np.random.random(len(df)),
                              # data not in dataframe, customized formatting
                              'suppl_2': (':.3f', np.random.random(len(df)))
                             })

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

@@ -885,6 +885,10 @@ def _get_reserved_col_names(args, attrables, array_attrables):
     return reserved_names
 
 
+def _isinstance_listlike(x):
+    return isinstance(x, list) or isinstance(x, np.ndarray) or isinstance(x, pd.Series)
+
+
 def build_dataframe(args, attrables, array_attrables):
     """
     Constructs a dataframe and modifies `args` in-place.
@@ -944,6 +948,8 @@ def build_dataframe(args, attrables, array_attrables):
     # If dict, convert all values of hover_data to tuples to simplify processing
     if hover_data_is_dict:
         for k in args["hover_data"]:
+            if _isinstance_listlike(args["hover_data"][k]):
+                args["hover_data"][k] = (True, args["hover_data"][k])
             if not isinstance(args["hover_data"][k], tuple):
                 args["hover_data"][k] = (args["hover_data"][k], None)
 

packages/python/plotly/plotly/express/_doc.py

@@ -186,6 +186,7 @@
         "or a dict with column names as keys, with values True (for default formatting)",
         "False (in order to remove this column from hover information),",
         "or a formatting string, for example ':.3f' or '|%a'",
+        "or list-like data to appear in the hover tooltip",
         "or tuples with a bool or formatting string as first element,",
         "and list-like data to appear in hover as second element",
         "Values from these columns appear as extra data in the hover tooltip.",

packages/python/plotly/plotly/tests/test_core/test_px/test_px_hover.py

@@ -38,7 +38,12 @@ def test_composite_hover():
     assert ":.1f" in fig.data[0].hovertemplate
 
 
-def test_tuple_hover_data():
+def test_newdatain_hover_data():
+    fig = px.scatter(x=[1, 2, 3], y=[3, 4, 5], hover_data={"comment": ["a", "b", "c"]})
+    assert (
+        fig.data[0].hovertemplate
+        == "x=%{x}<br>y=%{y}<br>comment=%{customdata[0]}<extra></extra>"
+    )
     fig = px.scatter(
         x=[1, 2, 3], y=[3, 4, 5], hover_data={"comment": (True, ["a", "b", "c"])}
     )