Make sure reshaping is done before converting units

dstansby · dstansby · commit f66d5c5987a4 · 2017-11-01T21:27:51.000Z
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -6091,13 +6091,24 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
                              "Please only use 'density', since 'normed'"
                              "will be deprecated.")
 
+        # basic input validation
+        input_empty = np.size(x) == 0
+        # Massage 'x' for processing.
+        if input_empty:
+            x = np.array([[]])
+        else:
+            x = cbook._reshape_2D(x, 'x')
+        nx = len(x)  # number of datasets
+
         # Process unit information
         # If doing a stacked histogram, the input is a list of datasets, so
         # we need to do the unit conversion individually on eaach dataset
         if stacked:
             self._process_unit_info(xdata=x[0], kwargs=kwargs)
-            for i, xi in enumerate(x):
-                x[i] = self.convert_xunits(xi)
+            newx = []
+            for xi in x:
+                newx.append(self.convert_xunits(xi))
+            x = newx
         else:
             self._process_unit_info(xdata=x, kwargs=kwargs)
             x = self.convert_xunits(x)
@@ -6108,15 +6119,6 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
         # Check whether bins or range are given explicitly.
         binsgiven = (cbook.iterable(bins) or bin_range is not None)
 
-        # basic input validation
-        input_empty = np.size(x) == 0
-
-        # Massage 'x' for processing.
-        if input_empty:
-            x = np.array([[]])
-        else:
-            x = cbook._reshape_2D(x, 'x')
-        nx = len(x)  # number of datasets
 
         # We need to do to 'weights' what was done to 'x'
         if weights is not None:
