Add tests for basic plot input variable parsing

Author: mwaskom

doc/releases/v0.9.0.txt

@@ -2,6 +2,6 @@
 v0.9.0 (Unreleased)
 -------------------
 
-- Final removal of the previously-deprecated ``coefcplot`` and ``interactplot`` functions.
+- Final removal of the previously-deprecated ``coefplot`` and ``interactplot`` functions.
 
 - Updated the testing infrastructure to execute tests with `pytest <https://docs.pytest.org/en/latest/>` (although many individual tests still use nose assertion).

seaborn/basic.py

@@ -44,28 +44,35 @@ def establish_variables(self, x=None, y=None,
             # We will assign the index to x, the values to y,
             # and the columns names to both hue and style
 
+            # TODO accept a dict and try to coerce to a dataframe?
+
             if isinstance(data, pd.DataFrame):
 
                 # Enforce numeric values
                 try:
                     data.astype(np.float)
                 except ValueError:
-                    raise ValueError("A wide-form dataframe must have only "
-                                     "numeric values.")
+                    err = "A wide-form input must have only numeric values."
+                    raise ValueError(err)
 
                 plot_data = pd.melt(data.assign(x=data.index), "x",
                                     var_name="hue", value_name="y")
                 plot_data["style"] = plot_data["hue"]
 
-            # TODO accept a dict and try to coerce to a dataframe?
-
             # Option 1b:
             # The input data is an array or list
             # ----------------------------------
 
             else:
 
-                if hasattr(data, "shape"):
+                if np.isscalar(data[0]):
+
+                    # The input data is a flat list(like):
+                    # We assign a numeric index for x and use the values for y
+
+                    plot_data = pd.DataFrame(dict(x=np.arange(len(data)),
+                                                  y=data))
+                elif hasattr(data, "shape"):
 
                     # The input data is an array(like):
                     # We assign a numeric index to x, the values to y, and
@@ -77,18 +84,10 @@ def establish_variables(self, x=None, y=None,
                                         var_name="hue", value_name="y")
                     plot_data["style"] = plot_data["hue"]
 
-                elif np.isscalar(data[0]):
-
-                    # The input data is a flat list(like):
-                    # We assign a numeric index for x and use the values for y
-
-                    plot_data = pd.DataFrame(dict(x=np.arange(len(data)),
-                                                  y=data))
-
                 else:
 
                     # The input data is a nested list: We will assign a numeric
-                    # index for x, use the values for, y and use numieric
+                    # index for x, use the values for, y and use numeric
                     # hue/style identifiers for each entry.
 
                     plot_data = pd.concat([