diff --git a/counterr/plots.py b/counterr/plots.py
index dafcd67..87c938d 100644
--- a/counterr/plots.py
+++ b/counterr/plots.py
@@ -10,8 +10,8 @@ def plot_per_read_Q_stats(means_pass, meds_pass, stds_pass, means_fail, meds_fai
         bins = np.arange(-0.5, 30.5, 1.)        
     fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 12))
     # pass
-    ax1.hist(means_pass, bins=bins, histtype="step", color="black", label="pass/mean", lw=1.5, normed=True)
-    ax1.hist(meds_pass, bins=bins, histtype="step", color="red", label="pass/med", lw=1.5, normed=True)
+    ax1.hist(means_pass, bins=bins, histtype="step", color="black", label="pass/mean", lw=1.5, density=True)
+    ax1.hist(meds_pass, bins=bins, histtype="step", color="red", label="pass/med", lw=1.5, density=True)
     ax1.set_title("Pass reads", fontsize=ft_size)
     ax1.set_xlabel("Q-score stat", fontsize=ft_size)
     if illumina:
@@ -20,8 +20,8 @@ def plot_per_read_Q_stats(means_pass, meds_pass, stds_pass, means_fail, meds_fai
         ax1.set_xlim([0, 30])        
     ax1.legend(loc="upper right", fontsize=ft_size)
     # fail
-    ax2.hist(means_fail, bins=bins, histtype="step", color="black", label="fail/mean", lw=1.5, normed=True)
-    ax2.hist(meds_fail, bins=bins, histtype="step", color="red", label="fail/med", lw=1.5, normed=True)
+    ax2.hist(means_fail, bins=bins, histtype="step", color="black", label="fail/mean", lw=1.5, density=True)
+    ax2.hist(meds_fail, bins=bins, histtype="step", color="red", label="fail/med", lw=1.5, density=True)
     ax2.set_title("Fail reads", fontsize=ft_size)
     ax2.set_xlabel("Q-score stat", fontsize=ft_size)    
     if illumina:
@@ -44,8 +44,8 @@ def plot_per_read_Q_stats(means_pass, meds_pass, stds_pass, means_fail, meds_fai
         bins = np.arange(-0.5, 30.5, 1.)
     fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 12))
     # pass
-    ax1.hist(means_pass, bins=bins, histtype="step", color="black", label="pass/mean", lw=1.5, normed=True)
-    ax1.hist(means_fail, bins=bins, histtype="step", color="red", label="fail/mean", lw=1.5, normed=True)
+    ax1.hist(means_pass, bins=bins, histtype="step", color="black", label="pass/mean", lw=1.5, density=True)
+    ax1.hist(means_fail, bins=bins, histtype="step", color="red", label="fail/mean", lw=1.5, density=True)
     ax1.set_title("Mean", fontsize=ft_size)
     ax1.set_xlabel("Q-score stat", fontsize=ft_size)        
     if illumina:
@@ -54,8 +54,8 @@ def plot_per_read_Q_stats(means_pass, meds_pass, stds_pass, means_fail, meds_fai
         ax1.set_xlim([0, 30])                
     ax1.legend(loc="upper right", fontsize=ft_size)
     # fail
-    ax2.hist(meds_pass, bins=bins, histtype="step", color="black", label="pass/med", lw=1.5, normed=True)
-    ax2.hist(meds_fail, bins=bins, histtype="step", color="red", label="fail/med", lw=1.5, normed=True)
+    ax2.hist(meds_pass, bins=bins, histtype="step", color="black", label="pass/med", lw=1.5, density=True)
+    ax2.hist(meds_fail, bins=bins, histtype="step", color="red", label="fail/med", lw=1.5, density=True)
     ax2.set_title("Med", fontsize=ft_size)
     ax2.set_xlabel("Q-score stat", fontsize=ft_size)    
     if illumina:
@@ -84,8 +84,8 @@ def plot_per_read_Q_stats(means_pass, meds_pass, stds_pass, means_fail, meds_fai
     ax.set_ylabel("Std", fontsize=ft_size)
     lgnd = plt.legend(loc="upper right", fontsize=ft_size, numpoints=1)
     #change the marker size manually
-    lgnd.legendHandles[0]._sizes = [30]
-    lgnd.legendHandles[1]._sizes = [30]    
+    lgnd.legend_handles[0]._sizes = [30]
+    lgnd.legend_handles[1]._sizes = [30]    
     if illumina:
         ax.set_xlim([0, 50])
         ax.set_ylim([0, 25])
@@ -116,8 +116,8 @@ def plot_per_read_Q_stats_aligned(means_in, stds_in, lens_in, means_out, stds_ou
     # ax.set_title("Mean", fontsize = 10)
     lgnd = plt.legend(loc="upper right", fontsize=ft_size, numpoints=1)
     #change the marker size manually
-    lgnd.legendHandles[0]._sizes = [30]
-    lgnd.legendHandles[1]._sizes = [30]
+    lgnd.legend_handles[0]._sizes = [30]
+    lgnd.legend_handles[1]._sizes = [30]
     if illumina:
         ax.set_xlim([0, 50])
         ax.set_ylim([0, 25])
@@ -143,8 +143,8 @@ def plot_per_read_Q_stats_aligned(means_in, stds_in, lens_in, means_out, stds_ou
     len_max = max(len_max_in, len_max_out)*1.05
     if len_max > 10: # Otherwise what's the point?
         bins = np.arange(0, len_max, len_max/100.)        
-        ax.hist(lens_in, bins=bins, color="black", label="Aligned", histtype="step", normed=True)
-        ax.hist(lens_out, bins=bins, color="red", label="Unaligned", histtype="step", normed=True)
+        ax.hist(lens_in, bins=bins, color="black", label="Aligned", histtype="step", density=True)
+        ax.hist(lens_out, bins=bins, color="red", label="Unaligned", histtype="step", density=True)
         ax.set_xlabel("Length", fontsize=ft_size)
         ax.set_xlim([0, len_max])
         ax.legend(loc="upper right", fontsize=ft_size)    
@@ -247,10 +247,10 @@ def plot_per_read_error_stats(lens, lens_aligned, nums_match, nums_sub, nums_ins
     ax.plot([0, len_max_lim], [0, len_max_lim], ls="--", lw=0.5, c="red")
     fig_name = os.path.join(output_dir, "per_read_len_vs_error_div_len_aligned.png")
     lgnd = ax.legend(loc="center right", fontsize=ft_size, scatterpoints=1)
-    lgnd.legendHandles[0]._sizes = [20]
-    lgnd.legendHandles[1]._sizes = [20]
-    lgnd.legendHandles[2]._sizes = [20]
-    lgnd.legendHandles[3]._sizes = [20]
+    lgnd.legend_handles[0]._sizes = [20]
+    lgnd.legend_handles[1]._sizes = [20]
+    lgnd.legend_handles[2]._sizes = [20]
+    lgnd.legend_handles[3]._sizes = [20]
     ax.set_xlabel("Length", fontsize=ft_size)
     ax.set_ylabel("(# occurrence) / length aligned", fontsize=ft_size)
     ax.set_xlim([0, len_max_lim])