Fix ValueError being raised when plotting hist and hexbin on empty dataset (Fix #3886)

lib/matplotlib/axes/_axes.py

@@ -3846,10 +3846,9 @@ def hexbin(self, x, y, C=None, gridsize=100, bins=None,
         if extent is not None:
             xmin, xmax, ymin, ymax = extent
         else:
-            xmin = np.amin(x)
-            xmax = np.amax(x)
-            ymin = np.amin(y)
-            ymax = np.amax(y)
+            xmin, xmax = (np.amin(x), np.amax(x)) if x.any() else (0, 1)
+            ymin, ymax = (np.amin(y), np.amax(y)) if y.any() else (0, 1)
+
             # to avoid issues with singular data, expand the min/max pairs
             xmin, xmax = mtrans.nonsingular(xmin, xmax, expander=0.1)
             ymin, ymax = mtrans.nonsingular(ymin, ymax, expander=0.1)
@@ -5606,12 +5605,14 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
 
         # basic input validation
         flat = np.ravel(x)
-        if len(flat) == 0:
-            raise ValueError("x must have at least one data point")
+
+        input_empty = len(flat) == 0
 
         # Massage 'x' for processing.
         # NOTE: Be sure any changes here is also done below to 'weights'
-        if isinstance(x, np.ndarray) or not iterable(x[0]):
+        if input_empty:
+            x = np.array([[]])
+        elif isinstance(x, np.ndarray) or not iterable(x[0]):
             # TODO: support masked arrays;
             x = np.asarray(x)
             if x.ndim == 2:
@@ -5640,7 +5641,9 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
 
         # We need to do to 'weights' what was done to 'x'
         if weights is not None:
-            if isinstance(weights, np.ndarray) or not iterable(weights[0]):
+            if input_empty:
+                w = np.array([])
+            elif isinstance(weights, np.ndarray) or not iterable(weights[0]):
                 w = np.array(weights)
                 if w.ndim == 2:
                     w = w.T
@@ -5678,7 +5681,7 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
         #hist_kwargs = dict(range=range, normed=bool(normed))
         # We will handle the normed kwarg within mpl until we
         # get to the point of requiring numpy >= 1.5.
-        hist_kwargs = dict(range=bin_range)
+        hist_kwargs = dict(range=bin_range) if not input_empty else dict()
 
         n = []
         mlast = None
@@ -5871,17 +5874,18 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
                     if np.sum(m) > 0:  # make sure there are counts
                         xmin = np.amin(m[m != 0])
                         # filter out the 0 height bins
-                xmin = max(xmin*0.9, minimum)
+                xmin = max(xmin*0.9, minimum) if not input_empty else minimum
                 xmin = min(xmin0, xmin)
                 self.dataLim.intervalx = (xmin, xmax)
             elif orientation == 'vertical':
                 ymin0 = max(_saved_bounds[1]*0.9, minimum)
                 ymax = self.dataLim.intervaly[1]
+
                 for m in n:
                     if np.sum(m) > 0:  # make sure there are counts
                         ymin = np.amin(m[m != 0])
                         # filter out the 0 height bins
-                ymin = max(ymin*0.9, minimum)
+                ymin = max(ymin*0.9, minimum) if not input_empty else minimum
                 ymin = min(ymin0, ymin)
                 self.dataLim.intervaly = (ymin, ymax)
 

lib/matplotlib/tests/test_axes.py

@@ -482,6 +482,12 @@ def test_hexbin_extent():
 
     ax.hexbin(x, y, extent=[.1, .3, .6, .7])
 
+@image_comparison(baseline_images=['hexbin_empty'], remove_text=True,
+	extensions=['png'])
+def test_hexbin_empty():
+    # From #3886: creating hexbin from empty dataset raises ValueError
+    ax = plt.gca()
+    ax.hexbin([], [])
 
 @cleanup
 def test_hexbin_pickable():
@@ -1001,6 +1007,19 @@ def test_hist_log():
     ax = fig.add_subplot(111)
     ax.hist(data, fill=False, log=True)
 
+@image_comparison(baseline_images=['hist_bar_empty'], remove_text=True,
+	extensions=['png'])
+def test_hist_bar_empty():
+    # From #3886: creating hist from empty dataset raises ValueError
+    ax = plt.gca()
+    ax.hist([], histtype='bar')
+
+@image_comparison(baseline_images=['hist_step_empty'], remove_text=True,
+	extensions=['png'])
+def test_hist_step_empty():
+    # From #3886: creating hist from empty dataset raises ValueError
+    ax = plt.gca()
+    ax.hist([], histtype='step')
 
 @image_comparison(baseline_images=['hist_steplog'], remove_text=True)
 def test_hist_steplog():
@@ -3508,7 +3527,7 @@ def test_color_None():
 def test_numerical_hist_label():
     fig, ax = plt.subplots()
     ax.hist([range(15)] * 5, label=range(5))
-    
+
 @cleanup
 def test_move_offsetlabel():
     data = np.random.random(10) * 1e-22