diff --git a/napp_plotlib.py b/napp_plotlib.py
index f1580d6..063b57a 100644
--- a/napp_plotlib.py
+++ b/napp_plotlib.py
@@ -15,10 +15,19 @@ def plot_image(dataframe,filter):
         ax.imshow(meas['image'],extent = [x_min,x_max,y_min,y_max])
         ax.set_xlabel('scientaEkin_eV')
         ax.set_ylabel('Replicates')
-        ax.set_title(meas['name'][0]+ '\n'+meas['sample'][0]+ '\n' + meas['lastModifiedDatestr'][0])
+        ax.set_title(meas['name'][0] + '\n' + meas['sample'][0]+ '\n' + meas['lastModifiedDatestr'][0])
 
-def plot_spectrum(dataframe,filter,):
+def plot_spectra(dataframe,filter):
 
+    """ plot_spectra plots XPS spectra associated to 'dataframe' after row reduced by 'filter'. 
+    When more than one row are specified by the 'filter' input, indivial spectrum are superimposed
+    on the same plot.
+
+    Parameters:
+    dataframe (pandas.DataFrame): table with heterogenous entries obtained by read_hdf5_as_dataframe.py.
+    filter (binaray array): binary indexing array with same number of entries as rows in dataframe.
+
+    """
     fig = plt.figure()
     ax = plt.gca()
 
@@ -32,13 +41,11 @@ def plot_spectrum(dataframe,filter,):
         y_min, y_max = 0, rows
         #for i in range(cols):
         ax.plot(bindingEnergy_eV, spectrum_countsPerSecond,label = meas['name'][0])
-        #ax.plot(bindingEnergy_eV, np.mean(meas['image'],axis=0))
-        ax.set_xlabel('bindingEnergy_eV')
-        ax.set_ylabel('counts Per Second')
-        if len(meas)>1:
-            ax.set_title('\n'+meas['sample'][0]+ '\n' + meas['lastModifiedDatestr'][0])
-        else:
-            ax.set_title(meas['name'][0] + '\n'+meas['sample'][0]+ '\n' + meas['lastModifiedDatestr'][0])
+
+    ax.set_xlabel('bindingEnergy_eV')
+    ax.set_ylabel('counts Per Second')
+    ax.set_title('\n'+meas['sample'][0]+ '\n' + 'PE spectra')
+    #ax.set_title(meas['name'][0] + '\n'+meas['sample'][0]+ '\n' + meas['lastModifiedDatestr'][0])
     ax.legend()