diff --git a/rl_portfolio_management/callbacks/notebook_plot.py b/rl_portfolio_management/callbacks/notebook_plot.py
index 94db233..b39c12b 100644
--- a/rl_portfolio_management/callbacks/notebook_plot.py
+++ b/rl_portfolio_management/callbacks/notebook_plot.py
@@ -1,6 +1,8 @@
 import os
 import numpy as np
 from matplotlib import pyplot as plt
+import matplotlib
+import logging
 
 
 class LivePlotNotebook(object):
@@ -15,8 +17,10 @@ class LivePlotNotebook(object):
     liveplot.update(x, [ya,yb])
     """
 
-    def __init__(self, log_dir=None, episode=0, labels=[], title=''):
-        # TODO check warn if note using right matplotlib backend
+    def __init__(self, log_dir=None, episode=0, labels=[], title='', ylabel='returns'):
+        if not matplotlib.rcParams['backend'] == 'nbAgg':
+            logging.warn("The liveplot callback only work when matplotlib is using the nbAgg backend. Execute 'matplotlib.use('nbAgg', force=True)'' or '%matplotlib notebook'")
+
         self.log_dir = log_dir
         self.i = episode
 
diff --git a/rl_portfolio_management/environments/portfolio.py b/rl_portfolio_management/environments/portfolio.py
index 284b0c2..870947f 100644
--- a/rl_portfolio_management/environments/portfolio.py
+++ b/rl_portfolio_management/environments/portfolio.py
@@ -325,7 +325,7 @@ class PortfolioEnv(gym.Env):
         # plot prices and performance
         if not self._plot:
             self._plot = LivePlotNotebook(
-                '/tmp', title='prices & performance', labels=self.sim.asset_names + ["Portfolio"])
+                '/tmp', title='prices & performance', labels=self.sim.asset_names + ["Portfolio"], ylabel='value')
         x = df_info.index
         y_portfolio = df_info["portfolio_value"]
         y_assets = [df_info['price_' + name].cumprod()
@@ -335,7 +335,7 @@ class PortfolioEnv(gym.Env):
         # plot portfolio weights
         if not self._plot2:
             self._plot2 = LivePlotNotebook(
-                '/tmp', labels=self.sim.asset_names, title='weights')
+                '/tmp', labels=self.sim.asset_names, title='weights', ylabel='weight')
         ys = [df_info['weight_' + name] for name in self.sim.asset_names]
         self._plot2.update(x, ys)