Smarter error handling for nulls in domain. #77

leather/scales/ordinal.py

@@ -28,7 +28,11 @@ def project(self, value, range_min, range_max):
 
         segments = len(self._domain)
         segment_size = (range_max - range_min) / segments
-        pos = range_min + (self._domain.index(value) * segment_size) + (segment_size / 2)
+
+        try:
+            pos = range_min + (self._domain.index(value) * segment_size) + (segment_size / 2)
+        except ValueError:
+            raise ValueError('Value "%s" is not present in Ordinal scale domain' % value)
 
         return pos
 
@@ -44,8 +48,11 @@ def project_interval(self, value, range_min, range_max):
         segment_size = (range_max - range_min) / segments
         gap = segment_size / Decimal(20)
 
-        a = range_min + (self._domain.index(value) * segment_size) + gap
-        b = range_min + ((self._domain.index(value) + 1) * segment_size) - gap
+        try:
+            a = range_min + (self._domain.index(value) * segment_size) + gap
+            b = range_min + ((self._domain.index(value) + 1) * segment_size) - gap
+        except ValueError:
+            raise ValueError('Value "%s" is not present in Ordinal scale domain' % value)
 
         return (a, b)
 

leather/series/base.py

@@ -6,7 +6,7 @@
 import six
 
 from leather.data_types import DataType
-from leather.utils import X, Y, Datum
+from leather.utils import DIMENSION_NAMES, X, Y, Datum
 
 
 class Series(object):
@@ -51,8 +51,8 @@ def __init__(self, data, x=None, y=None, name=None):
         ]
 
         self._types = [
-            self._infer_type(self._keys[X]),
-            self._infer_type(self._keys[Y])
+            self._infer_type(X),
+            self._infer_type(Y)
         ]
 
     def _make_key(self, key):
@@ -64,18 +64,20 @@ def _make_key(self, key):
         else:
             return lambda row, index: row[key]
 
-    def _infer_type(self, key):
+    def _infer_type(self, dimension):
         """
         Infer the datatype of this column by sampling the data.
         """
+        key = self._keys[dimension]
+
         for i, row in enumerate(self._data):
             v = key(row, i)
 
             if v is not None:
                 break
 
         if v is None:
-            raise ValueError('All values in dimension were null.')
+            raise ValueError('All values in %s dimension are null.' % DIMENSION_NAMES[dimension])
 
         return DataType.infer(v)
 

leather/series/category.py

@@ -56,9 +56,9 @@ def __init__(self, data, x=None, y=None, z=None, name=None):
         ]
 
         self._types = [
-            self._infer_type(self._keys[X]),
-            self._infer_type(self._keys[Y]),
-            self._infer_type(self._keys[Z])
+            self._infer_type(X),
+            self._infer_type(Y),
+            self._infer_type(Z)
         ]
 
     def data(self):

test.py

@@ -22,8 +22,7 @@
 
 data1 = [
     (2, None),
-    (6, None),
-    (9, None)
+    (3, None)
 ]
 
 chart = leather.Chart()