matplotlib
diff --git a/‎galleries/examples/statistics/histogram_bihistogram.py
Copy file name to clipboardExpand all lines: galleries/examples/statistics/histogram_bihistogram.py
+6-3Lines changed: 6 additions & 3 deletions b/‎galleries/examples/statistics/histogram_bihistogram.py
Copy file name to clipboardExpand all lines: galleries/examples/statistics/histogram_bihistogram.py
+6-3Lines changed: 6 additions & 3 deletions
@@ -21,20 +21,23 @@
 # one to be negative. We'll generate data below and plot the bihistogram.
 
 N_points = 10_000
-n_bins = 30
 
 # Generate two normal distributions
 dataset1 = np.random.normal(0, 1, size=N_points)
 dataset2 = np.random.normal(1, 2, size=N_points)
 
+# Use a constant bin width to make the two histograms easier to compare visually
+bin_width = 0.25
+bins=np.arange(np.min([dataset1, dataset2]), np.max([dataset1, dataset2]) + bin_width, bin_width)
+
 fig, ax = plt.subplots()
 
 # Plot the first histogram
-ax.hist(dataset1, bins=n_bins, label="Dataset 1")
+ax.hist(dataset1, bins=bins, label="Dataset 1")
 
 # Plot the second histogram
 # (notice the negative weights, which flip the histogram upside down)
-ax.hist(dataset2, weights=-np.ones_like(dataset2), bins=n_bins, label="Dataset 2")
+ax.hist(dataset2, weights=-np.ones_like(dataset2), bins=bins, label="Dataset 2")
 ax.axhline(0, color="k")
 ax.legend()